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ClaudeandClaude Opus 5.5 decd419e94 docs: cite only the recorded MRT parity pass (K1 7813334)
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 07:08:31 +00:00
ClaudeandClaude Opus 5.5 1c47cb8570 docs: supported settings review fixes (exact parity test IDs, divisibility guard)
Names the exact SRT/MRT parity tests and their sub-case scope (SRT: one
of 18 sub-cases, unidentified; MRT: 12 sub-cases, default outlet settings,
with the runs that recorded the pass), cites blocks.py:134 for tile
divisibility, labels refinement.py:457 as the fine-boundary re-check, and
says 'measured at 36ffc8b1' for the Taylor-Green observation.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 07:05:34 +00:00
ClaudeandClaude Opus 5.5 8e9fc72e19 docs: curved-wall observation states only the recorded matrix outcome
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:59:14 +00:00
ClaudeandClaude Opus 5.5 d2cd1114ed docs: supported settings for the 2D Jet + multilevel candidate
One page listing supported settings, each with the guard enforcing it
(file:line at c95a7ba) and the existing tests exercising it. Measured
observations are labelled by their exact tested case (SRT strict-parity
1/4320 values ~2 ULP with unresolved cause; V3 TG constant explosion
aggregate; curved-wall r1 pilot; V4 NOT_STEADY), not stated as general
bounds. Documentation only.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:59:02 +00:00
ClaudeandClaude Opus 5.5 c95a7baae4 test_projected_pairs: regenerate pinned build sources from NUMERICAL_REVISION kernels
The pinned BUILD_SOURCES are the a135252 qualification build inputs.
generate_config hashes the whole kernel snapshot, so after K1/K2 the
working-tree kernels (legitimately) no longer reproduce them. The test
now archives src/CelerisLab/lbm/kernels at NUMERICAL_REVISION and points
compiler_v2._KERNEL_DIR there; config headers are still rendered by
today's compiler. BUILD_SOURCES and the equality assertion are unchanged;
each size is a subTest; a missing NUMERICAL_REVISION fails (no skip).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:26:45 +00:00
ClaudeandClaude Opus 5.5 f4372a84c0 Merge a454f023 (claude/jet-shapes-once) for integration review
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:03:36 +00:00
ClaudeandClaude Opus 5.5 e48498d089 Merge 580fcf65 (grok/p1-docs-wording) for integration review
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:03:36 +00:00
ClaudeandClaude Opus 5.5 531739454e Merge 1cbdc479 (claude/step-single-sync) for integration review
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:03:36 +00:00
ClaudeandClaude Opus 5.5 b93de2ce24 Merge 1fa498c7 (claude/k2-block-coords) for integration review
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 06:03:36 +00:00
ClaudeandClaude Opus 5.5 a454f02355 Jets: compute jet link shapes once per boundary preparation
surface_link_velocity already runs jet_link_shapes; CurvedLinkSoA.
assign_surface and _prepare_blocked_boundary then ran it again with the
same jets and hits to fill the host jet cache. A private _surface_links
returns (velocity, aperture, shape, jet_id) from the one call; both
callers use it. surface_link_velocity keeps its two-value public
contract (now a thin wrapper). Same values, same validation order, same
cache contents; host geometry preparation only.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 05:57:11 +00:00
Grok 580fcf6525 docs(P1): align wording with level-list API only
Drop legacy constructor prose (child=/mutual exclusion), retarget
README and fixed_three_level_multipatch examples to refinements /
level_blocks, and fix stepper error/doc strings that still named
fine_block/base_block or a fixed gap >= 4 (unions use dependency
closure). Wording only; no behavior change.
2026-10-21 11:07:29 +08:00
ClaudeandClaude Opus 5.5 18f018befe README: several regions are refinements[0], not bounds
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 02:02:38 +00:00
ClaudeandClaude Opus 5.5 ec9b3d721c P1 (12/12): one FixedPatchStepper construction and initialize API
Removes the legacy entry points now that every caller is migrated:
FixedPatchStepper(cfg, *, context, refinements, coarse_boundary,
level_blocks, level_objects, level_jets, observe_*, explosion) and
initialize(*level_g). Deleted: positional bounds, fine_block, base_block,
fine_objects, jets, child, child_block, child_objects, child_jets,
child_rectangles_in_parent, initialize(coarse_g/fine_g/child_g),
_legacy_levels and _initial_levels. Docstring, README and docs describe
the level lists. Compatibility views (patch, fine_boundary, ...) and the
PeriodicPatchStepper alias are unchanged (separate follow-up).

Error -> rule table (legacy keyword check -> level-list rule now firing):
- several patches without fine_block/base_block -> _check_levels
  'several patches require fine_block and base_block' (unchanged rule)
- base_block without fine_block -> 'a blocked level requires blocked
  refined levels below it'
- nested child without all blocks -> 'three or more levels must all be
  blocked' / 'a blocked level requires ...'
- fine_objects/jets with a nested child ('only on L2') -> 'bodies/Jets are
  supported only on the finest level of a nested hierarchy'
- child_objects/child_jets without a nested child -> 'level_objects/
  level_jets needs one entry per level'
- scalar child with several L1 patches ('scalar child requires one parent
  patch') -> hierarchy 'a scalar child requires a scalar parent'
- child vs child_rectangles_in_parent mutually exclusive -> no level-list
  equivalent (cannot be expressed); covered by the new explicit
  RemovedLegacyAPI test: removed keywords and positional bounds raise
  TypeError before any context use, initialize has only *level_g.
The InitialLevels test of the removed adapter is replaced by that test.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 02:02:29 +00:00
ClaudeandClaude Opus 5.5 84b76f49cc P1 (11/n): multipatch GPU/CPU tests use the level-list constructor
One local levels(bounds, blocks, objects, jets, **rest) builds the
two-level lists; run_steps and every rejection case use it. All five
before-CUDA rejections, the margin and one-jet checks keep their inputs.
Assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 02:00:59 +00:00
ClaudeandClaude Opus 5.5 050d12b76c P1 (10/n): blocked-fine GPU/CPU tests use the level-list constructor
Dense root + blocked fine level is level_blocks=[None, block]; bodies go
to level_objects[1]. Both before-CUDA rejections (non-dividing and
malformed fine block) keep their inputs. Assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 02:00:15 +00:00
ClaudeandClaude Opus 5.5 ec3e3b928a P1 (9/n): refinement follow-up tests pass refinements=[bounds]
FixedPatchStepper and the PeriodicPatchStepper alias are called with
refinements=[bounds] instead of the positional legacy bounds (same
_legacy_levels result). Assertions, including the before-CUDA and
four-cell/omega/layout rejections, unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:59:56 +00:00
ClaudeandClaude Opus 5.5 2be80324ad P1 (8/n): three-level GPU/CPU tests use the level-list constructor
KW becomes levels() (scalar L1 + scalar L2, per-level blocks, objects,
Jets). All rejection cases are kept per level. Two cases change branch:
L2 bodies/Jets with no nested child (legacy 'child_objects/child_jets
require a nested child') are now an entry for a level that does not
exist ('needs one entry per level'); several L1 patches + scalar child
now meets 'a scalar child requires a scalar parent'. Both still reject
before CUDA. Assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:59:37 +00:00
ClaudeandClaude Opus 5.5 0fcd4ac4cb P1 (7/n): MRT, shifted-jet and blocked-base GPU tests migrated
test_refinement_mrt_gpu, test_shifted_jets_gpu and
test_refinement_blocked_base pass refinements/level_* lists. The three
blocked-base rejection cases keep their inputs per level; base-only
blocks now meet the level-list rule (blocked refined levels below) where
the legacy keyword check fired before. Assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:58:57 +00:00
ClaudeandClaude Opus 5.5 af0566db98 P1 (6/n): exchange-window, raw-exchange, Jet and pinned-remap GPU tests migrated
test_exchange_window, test_raw_exchange_gpu (one fine(block) helper for
the repeated circle+jet construction), test_refinement_jets,
test_multiple_pinned_remap_gpu and test_pinned_body_remap_gpu pass
refinements/level_* lists. Dense fine levels stay level_blocks=[None,
None|block] as before. Assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:58:15 +00:00
ClaudeandClaude Opus 5.5 0b1b3d938f P1 (5/n): six GPU validation tests use the level-list constructor
test_refinement_gpu (incl. PeriodicPatchStepper alias calls),
test_channel_root_gpu, test_fine_surface_gpu, test_shifted_remap_gpu,
test_runtime_child_remap_gpu and test_refinement_three_level_multipatch_gpu
pass refinements/level_* lists; scalar and set children map to the second
refinement entry exactly as _legacy_levels did. Assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:48:09 +00:00
ClaudeandClaude Opus 5.5 5167c79378 P1 (4/n): unit tests and examples use the level-list constructor
test_shifted_jets, test_shifted_storage, test_raw_exchange and
test_channel_root pass refinements/level_* lists; examples
fixed_patch_jet and fixed_periodic_patch pass refinements=[BOUNDS]
instead of the positional bounds. Assertions kept; the shifted-storage
case base_block-without-fine_block now expects the level-list rule
'blocked refined levels below' (same constraint).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:46:52 +00:00
ClaudeandClaude Opus 5.5 aedddc35b1 P1 (3/n): three-level multipatch unit tests use the level-list constructor
KW (legacy base/fine/child blocks + child_rectangles_in_parent) becomes
levels(): refinements=[PARENTS, CHILDREN], level_blocks, level_objects,
level_jets. Every negative case is kept and expressed per level (child
rectangles, per-level blocks); the L1-body case now expects the level-list
rule's message 'only on the finest level' instead of the legacy keyword
message 'only on L2' (same constraint).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:46:06 +00:00
ClaudeandClaude Opus 5.5 1cbdc479cf test_block_step_sync: locate block_stepper without importing it
The module-level import of CelerisLab.lbm.block_stepper loaded
pycuda.driver into the shared test process, unlike the other CPU host
tests (which load mocked copies via AST). find_spec gives the source path
without the import. Test content and assertions unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:39:52 +00:00
ClaudeandClaude Opus 5.5 7821c6ad71 P1 (2/n): runners and example use the level-list constructor
run_refined_dfg, run_dfg_re20, time_window_dfg, time_refined_dfg,
run_jet_circle_cv and examples/fixed_patch_circle pass refinements /
level_blocks / level_objects / level_jets instead of bounds, base_block,
fine_block, fine_objects and jets. One-to-one with _legacy_levels: same
rectangle (FixedPatch2D frame), same blocks, bodies and Jets.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:35:04 +00:00
ClaudeandClaude Opus 5.5 392314e1ae P1 (1/n): remap_child builds its candidate through the level-list API
The only in-library caller of the legacy constructor keywords now passes
refinements=[L1 bounds, L2 set], level_blocks=[base, fine, child],
level_objects=[(), (), child_objects], level_jets=[(), (), jets] -- the
exact lists _legacy_levels produced for it. Legacy keywords stay until
every caller is migrated (final P1 commit).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:34:33 +00:00
ClaudeandClaude Opus 5.5 f3f1e3d588 PeriodicBlockStepper.step: mid-batch launch failure test; async-error docstring note
Review follow-up (non-blocking items): a launch failure on the second of
three steps fails closed without the batch wait, keeps step_count at its
entry value and blocks download; the docstring now states, as for
FixedPatchStepper, that async faults surface at the single wait.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:31:09 +00:00
ClaudeandClaude Opus 5.5 3648ad70ef PeriodicBlockStepper.step(n): wait on the stream once per call
Same change as the reviewed FixedPatchStepper end-sync (cherry-picked
ad1d82c+512dcc9 above): the n steps are enqueued in order and the host
waits once; step(0) launches nothing; step_count advances after the wait
and keeps its entry value on failure. Launches, buffer roles and bits are
those of n step(1) calls. Mocked-driver host test covers the single
wait, launch/role equality with n step(1), step(0) and failure.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:25:16 +00:00
ClaudeandClaude Opus 5.5 5399c9c0a6 step(n) docstring: raw-exchange ledger holds the final interval only
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:24:36 +00:00
ClaudeandClaude Opus 5.5 54be33e006 FixedPatchStepper.step(n): wait on the stream once per call
Enqueue all n base intervals in order on the one stream and synchronize
once before returning (step(0): no launch, no wait). step_count, the raw
exchange ledger and an open window are published only after that wait;
any failure leaves step_count at its entry value and invalidates both
ledgers. Async device errors are no longer attributed to an interval;
the docstring says to use step(1) loops to localize one. Launch order and
buffers are unchanged. Adds a mocked-driver host test of the contract.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:24:36 +00:00
ClaudeandClaude Opus 5.5 1fa498c7d7 kernels: shared block-window to global coordinate helper
BlockStep (slot-reservoir wall rows) and BlockChannelStep computed the
global cell of a block-window cell with the same four lines.
block_global_xy (core/layout.cuh, 2D, __forceinline__) now holds them;
both kernels call it with their own domain width. Same integer
operations: no numerical, ABI or scheduling change. The slot-reservoir
kernel layout is unchanged (no split).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:24:27 +00:00
ClaudeandClaude Opus 5.5 781333407e kernels: one shared unforced MRT collision for blocked, channel and patch paths
BlockStep, BlockChannelStep and refinement.cu patch_collide each carried
the same compute_rho_u -> omega clamp -> collide_mrt_no_force sequence.
collide_mrt_unforced (collision_mrt.cuh, __forceinline__) now holds it
once; the three sites call it. Same operations in the same order: no
numerical, ABI or SRT change. The host source contract now requires one
helper definition and exactly one call per file, and forbids the old
inline sequence.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 01:15:47 +00:00
ClaudeandCodex 750e8a483e test: DFG Re20 steady rule as agreed (10 % range, 2 % slope, window-mean verdict)
Supersedes 71221837. Samples every t* 0.5 (interval-mean forces), trailing
t* 50..60 window (21 samples); range <= 10 % and |slope*window| <= 2 % of
each official band width. Verdict on the window mean with the distance to
the nearest band edge. Our engineering rule, frozen before any run.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
(cherry picked from commit 869d60d78e)
2026-10-20 21:59:15 +08:00
ClaudeandCodex 6a03f463bc test: DFG Re20 steady rule per review (1 % band, range and slope, 0.5 s samples)
Samples every 0.5 s at synchronized root steps; trailing 5 s window (11
samples); range and |slope*window| each at most 1 % of the official band
width. States the fluid-on-cylinder force sign, reports cd_positive,
defaults to the refined case and uses the review's label.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
(cherry picked from commit 71221837f9)
2026-10-20 21:59:15 +08:00
ClaudeandCodex 46dc6ba086 test: add DFG 2D-1 Re20 runner against official reference intervals
Reuses the pinned Re100 runner and helpers unchanged; sets only the
lattice viscosity for Re 20. Reports Cd, Cl and p_diff (dp * 0.04 for
U = 0.2 m/s), a steady rule frozen before any run (window ranges at most
a tenth of each official interval width) and no interval verdict when
not steady. Declares the pressure-NEQ outlet and Zou-He inlet deviations.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
(cherry picked from commit 9b8ff90609)
2026-10-20 21:59:15 +08:00
ClaudeandCodex e1efc18274 test: follow the recursive _advance in three-level feed checks
baba5e0 replaced _advance_child with _advance(index, parent_buffer) driven
from _hop; the two feed-order tests still patched the removed method.
Patch _advance and record only index 2 (L1 hop feeding L2); assertions,
expected order and the stale-feed negative control are unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
(cherry picked from commit 3f47436073)
2026-10-20 21:57:57 +08:00
ClaudeandClaude Opus 5.5 9660894a1b docs: checkpoint save/load scope and read_surface_exchange wording
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 13:38:30 +00:00
ClaudeandClaude Opus 5.5 ba3772e3b8 docs: record cut-link ownership and read_surface_exchange changes from 87c3a31
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 13:29:44 +00:00
CodexandFrank14f b4692e6ec4 test: select single-case resolution and compact refinement 2026-10-19 23:55:26 +08:00
CodexandFrank14f 5731c5171b test: add optional public macro CV observations 2026-10-19 22:43:22 +08:00
CodexandFrank14f 05de02ee60 test: parameterize matched public MRT Jet diagnostics 2026-10-19 22:43:22 +08:00
CodexandFrank14f 87c3a3165e fix: validate passive boundary ownership and expose Jet exchange 2026-10-19 22:43:22 +08:00
Codex eec4677db1 test: add explicit projected-port LES source profile 2026-10-18 16:13:30 -07:00
Codex 2cf9853952 test: prepare matched projected pair Taylor-Green repeat 2026-10-18 15:38:04 -07:00
Codex 1aa8110ec8 test: add bounded projected pair CUDA qualification gate 2026-10-18 15:04:51 -07:00
Codex a135252ae7 feat: add experimental projected explosion per refinement pair 2026-10-18 14:54:17 -07:00
Codex ed9d8c937d docs: correct refinement topology and diagnostics scope 2026-10-18 13:13:53 -07:00
82 changed files with 4302 additions and 3694 deletions
+62 -38
View File
@@ -112,8 +112,9 @@ from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
cfg = LBMConfig(nx=32, ny=24, viscosity=.1)
body = SimObject(0, geometry=CircleGeometry(16.0, 12.0, 2.15), center=(16.0, 12.0), radius=2.15,
surface_actuation=SurfaceActuation(0.7, 0.85, 0.002)) # angle, half-width, speed
with CudaContext(0) as ctx, FixedPatchStepper(cfg, (8, 6, 24, 18), context=ctx,
fine_objects=[body], fine_block=(16, 20)) as run:
with CudaContext(0) as ctx, FixedPatchStepper(cfg, context=ctx, refinements=[(8, 6, 24, 18)],
level_blocks=[None, (16, 20)],
level_objects=[(), (body,)]) as run:
rest = np.asarray(compute_feq_d2q9(1.0, 0.0, 0.0), np.float32)[:, None, None]
# (9, ny, nx) postcollision populations per level; non-leaf cells are discarded.
run.initialize(np.broadcast_to(rest, (9, *run.patch.coarse_shape)),
@@ -123,7 +124,9 @@ with CudaContext(0) as ctx, FixedPatchStepper(cfg, (8, 6, 24, 18), context=ctx,
```
Scope and limits:
- D2Q9, SRT, FP32, double buffer, unshifted, no LES or forcing; fixed 2:1 patch(es), two levels (or one nested third).
- The examples below use D2Q9, SRT, FP32, double buffer, unshifted, no LES or
forcing. Fixed 2:1 hierarchies use level lists of arbitrary depth; two- and
three-level examples below use that same constructor.
- `coarse_boundary="periodic"` (default) or `"slot_reservoir"` (bottom slot, top
reservoir; patch needs `y0 >= 4`, `y1 <= ny-4`). Periodic mode ignores the wall/slot config fields.
- Object centers/radii use the coarse **cell-edge** frame (cell `I` spans `[I, I+1)`),
@@ -131,46 +134,51 @@ Scope and limits:
- Bodies must be stationary circles whose whole boundary stencil lies in the fine
active region, clear of the coarse/fine transfer cells; violations are rejected
before any GPU allocation.
- `fine_block=(by, bx)` stores the fine level in fixed-size blocks; `by`/`bx` must
- `level_blocks=[None, (by, bx)]` stores the fine level in fixed-size blocks; `by`/`bx` must
divide the WHOLE fine allocation, i.e. `2*(y1-y0)+8` by `2*(x1-x0)+8` including the
four-cell ghost band. It gives results identical to dense storage and is
infrastructure for future block AMR, not a speedup.
- Several separated patches: pass a sequence of `(x0, y0, x1, y1)`
rectangles as `bounds`, at least 4 coarse cells apart, with both `fine_block`
and `base_block`. The fine level is then one level-wide grid `(2*ny, 2*nx)`:
- Several regions: pass a sequence of `(x0, y0, x1, y1)` rectangles as
`refinements[0]`, with both levels blocked (`level_blocks`). Transfers are built once
from their union; adjacent, overlapping and concave unions are accepted when
their actual dependencies close. There is no fixed rectangle-gap rule.
The fine level is then one level-wide grid `(2*ny, 2*nx)`:
`run.patch.fine_shape` gives it, `initialize`/`download` use it, and only the
patch windows (active region plus 4-cell ghost band, origin `(2*y0-4, 2*x0-4)`)
are stored; each window must align with `fine_block`. Order of rectangles does
not matter. `fine_objects`/`jets` work as for one patch: each circle (same
coarse cell-edge frame) must lie wholly inside one patch's active region with
grid-aligned tiles intersecting the union plus its four-cell ghost band are stored.
Block sizes must divide the level-wide grid; rectangle edges need not align
with tiles. Order of rectangles does not matter. L1 bodies/Jets (`level_objects[1]`/`level_jets[1]`) work
as for one patch: each circle (same coarse cell-edge frame) must lie wholly
inside the union's active region with
its boundary stencil clear of transfer cells; a jet may not select links of two
different bodies, even across patches. No wall-touching patches or nesting yet.
different bodies, even across regions. Wall-touching patches remain unsupported.
For nesting, add further `refinements` entries as shown below.
```python
cfg = LBMConfig(nx=32, ny=16, viscosity=.1)
rest = np.asarray(compute_feq_d2q9(1.0, 0.0, 0.0), np.float32)[:, None, None]
with CudaContext(0) as ctx, FixedPatchStepper(
cfg, ((4, 4, 12, 12), (16, 4, 24, 12)), context=ctx,
fine_block=(4, 4), base_block=(4, 4)) as run:
cfg, context=ctx, refinements=[((4, 4, 12, 12), (16, 4, 24, 12))],
level_blocks=[(4, 4), (4, 4)]) as run:
run.initialize(np.broadcast_to(rest, (9, *run.patch.coarse_shape)),
np.broadcast_to(rest, (9, *run.patch.fine_shape))) # (9, 32, 64)
run.step(32)
coarse_g, fine_g = run.download() # coarse: NaN on every covered cell;
# fine: NaN on every non-ACTIVE cell
```
- Three levels (one nested chain): add `child=(x0, y0, x1, y1)` in
**L1 window cells** (the patch's fine grid including its 4-cell ghost band) and
`child_block`, with `fine_block` and `base_block`. L2 must sit inside L1's
ACTIVE cells, away from L1's ghost band and transfer footprint (checked before
any GPU allocation). `initialize` and `download` take/return three arrays; each
level is NaN on its non-ACTIVE (and child-covered) cells. One coarse step = 2 L1
steps = 4 L2 steps. One L1 patch only. Optional stationary circles and Jets
live on L2 via `child_objects` and `child_jets`; `fine_objects`/`jets` retain
their L1 meaning and must be empty in this mode. All object and Jet geometry
uses the **L0 edge frame**, not the child bounds' L1 window frame. L2 has
dx=dt=0.25, so prescribed lattice velocity is unchanged. Each whole body and
its BFL stencil must be inside L2 ACTIVE cells, outside the transfer footprint.
A Jet may select one physical body across multiple blocks, never two bodies.
- Three-level nested windows: pass two scalar rectangles in `refinements` —
L1 in L0 cells, L2 in **L1 window cells** (the parent's fine grid including its
4-cell ghost band) — plus all three `level_blocks` entries. L2 must sit inside
L1's ACTIVE cells, away from L1's ghost band and transfer footprint (checked
before any GPU allocation). `initialize` and `download` take/return three
arrays; each level is NaN on its non-ACTIVE (and child-covered) cells. One
coarse step = 2 L1 steps = 4 L2 steps. One L1 window only in this scalar
chain. Optional stationary circles and Jets live on L2 via `level_objects[2]`
and `level_jets[2]`; L1 bodies/Jets retain their L1 meaning and must be empty
in this mode. All object and Jet geometry uses the **L0 edge frame**, not the
child bounds' L1 window frame. L2 has dx=dt=0.25, so prescribed lattice
velocity is unchanged. Each whole body and its BFL stencil must be inside L2
ACTIVE cells, outside the transfer footprint. A Jet may select one physical
body across multiple blocks, never two bodies.
```python
from CelerisLab.body.geometry.circle import CircleGeometry
@@ -182,9 +190,9 @@ Scope and limits:
jet = Jet(Tube((6.5, 8.), 0., 3., .3), Parallel(0.), amplitude=.002)
rest = np.asarray(compute_feq_d2q9(1.0, 0.0, 0.0), np.float32)[:, None, None]
with CudaContext(0) as ctx, FixedPatchStepper(
cfg, (4, 4, 12, 12), context=ctx, fine_block=(4, 4), base_block=(4, 4),
child=(8, 8, 16, 16), child_block=(4, 4),
child_objects=[body], child_jets=[jet]) as run:
cfg, context=ctx, refinements=[(4, 4, 12, 12), (8, 8, 16, 16)],
level_blocks=[(4, 4)] * 3, level_objects=[(), (), (body,)],
level_jets=[(), (), (jet,)]) as run:
shapes = (run.patch.coarse_shape, run.patch.fine_shape, run.child_patch.fine_shape)
run.initialize(*(np.broadcast_to(rest, (9, *s)) for s in shapes)) # 16², 24², 24²
run.step(4)
@@ -192,14 +200,30 @@ Scope and limits:
run.step(4)
coarse_g, l1_g, l2_g = run.download() # solids/covered/nonleaves are NaN
```
- Not available: per-link surface exchange/force readout in blocked mode,
checkpoints, moving bodies, L1 bodies/Jets in a three-level chain,
several patches per level with nesting, dynamic refinement, `Simulation`
integration. Validation so far is storage/operator equivalence and short runs,
not accuracy, convergence or long-time stability. The new L2-body GPU gates
(layouts, masks, amplitude reversal, legacy equivalence) and independent
every-substep numerical replay remain required acceptance checks; CPU tests
alone do not establish GPU numerical correctness.
- Level lists (the only constructor): `refinements[l]` describes level `l+1`
in allocated level-`l` integer cells; use a rectangle list for a union, or a
scalar rectangle for a single window (a scalar child requires a scalar
parent). `level_blocks`, `level_objects` and `level_jets` each have one entry
per level, including L0. Three or more levels require all-blocked storage and
bodies/Jets only on the finest level. Every adjacent pair must preserve
inherited ACTIVE coverage, valid donors/receivers, surviving pulls and the
upstream transfer footprint. Level `l` takes `2**l` steps per base interval.
This describes implemented topology and scheduling, not accuracy or
convergence qualification.
- Blocked body levels can enable `observe_raw_exchange=True` and call
`read_raw_exchange(body_id, level=...)` after a completed base interval.
It reduces unique cut-link observations into wall/aperture/total force,
torque and mass exchange in base-lattice units per unit depth, for the last
base interval (default) or `window="last_substep"`.
`observe_window_exchange=True`, alongside `observe_raw_exchange=True`, enables
`start_exchange_window()` / `read_exchange_window(body_id, level=...)` across
completed base intervals. These are raw boundary-reaction diagnostics, not a general
stress or nozzle-load accuracy claim; dense body layouts are unsupported.
- Not available: checkpoints, moving bodies, L1 bodies/Jets in a three-level
chain, automatic dynamic refinement, `Simulation` integration. Qualification
depends on the tested configuration; see [the validation scope](docs/validation/2d_scope.md).
CPU topology/schedule tests alone do not establish GPU numerical correctness,
general convergence or long-time stability.
## Installation
+35
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@@ -0,0 +1,35 @@
# Compatibility and API changes
Changes that can make a previously accepted setup or call behave differently.
Each entry names the commit, the affected entry points and the observable result.
## 87c3a31: cut-link ownership is validated for every body
`validate_cut_link_ownership` (`body/preprocess/flag_overlay.py`) now runs for
passive bodies as well as Jet/aperture bodies. Every cut link must have an
active fluid receiver (FLUID set, SOLID clear), and each `(receiver, direction)`
population may have only one writer.
Rejected with `ValueError`, before flags, populations or device buffers change:
1. Overlapping or touching passive solids whose cut links write the same
population ("Boundary requires unique cut-link writers").
2. A body whose cut-link receiver is a non-fluid cell, e.g. a channel wall row
or the inlet/outlet column ("Cut links must have active fluid receivers").
Both were previously accepted silently for passive bodies; the interpolated
boundary then had undefined results. The rules apply to the cut links of all
bodies together, so a passive body overlapping a Jet body is rejected as well.
The check runs in `Simulation.initialize`, runtime body sync (`sync_bodies`),
checkpoint save and checkpoint load (`common/checkpoint.py`). Load validates
before restoring anything, so a checkpoint whose saved geometry violates either
rule no longer restores; rebuild the geometry with separated bodies.
## 87c3a31: `Simulation.read_surface_exchange` accepts Jet-driven bodies
`read_surface_exchange(id)` previously required `SurfaceActuation` on the body.
It now also accepts bodies that own Jet aperture links, including Jets with zero
or negative amplitude (the aperture test is geometric). Bodies with neither
`SurfaceActuation` nor aperture links still raise
`ValueError("Body has no surface actuation")`. The value is unchanged: the latest
step's wall/aperture exchange, not total nozzle force.
@@ -0,0 +1,57 @@
# Experimental projected G explosion
`FixedPatchStepper(..., explosion="projected_linear")` changes only the existing
G-to-G explosion reconstruction. The omitted/default `"constant"` selector retains
the same kernel, launch arguments and device allocations. Projected mode adds two
compact tables per adjacent pair; recursion, collision, BFL, restriction, buffer
ownership and synchronized publication are unchanged. `remap_child` preserves it.
Runtime eligibility is periodic-root, fully blocked D2Q9/SRT/FP32, body/Jet-free,
without LES; the fixed-patch backend has no forcing interface. Shifted and unshifted
storage use the same reconstruction. One generic builder handles scalar windows,
unique union rows and all adjacent hierarchy pairs without depth/rectangle caps.
Donors are original explosion donors intersected with owned, uncovered ACTIVE
cells. An axis uses centered differences only if both neighbors are legal;
otherwise both addresses repeat the center. Nested layout periodicity is explicit.
No covered cells, holes, inactive cells or stale halo copies enter the stencil.
The 33-line kernel is unchanged from our `519473a` experiment and retains its
mathematical attribution. Host tests cover union decomposition, concavity, narrow
gaps, grazing packet paths, offsets, sparse/nested owner addresses, three/four-level
source timing, unchanged constant dispatch, remapping and shifted/unshifted actual
kernel arithmetic compiled as host C++. These are not CUDA or flow validation.
## Reviewed bounded evidence
The `1aa8110` CUDA gate, with production exactly `a135252`, passed exact-dev
omitted/default and explicit-constant equivalence, per-population reconstruction,
scalar/union/four-level scheduling, alternate layouts, and changed remapping in
both storage modes. Operator maximum error was 2.98023224e-8; the eight-step
concave replay maximum was 1.58037614e-7. Whole-step mass/momentum remain
finite diagnostics, not an FP32 conservation certificate. Reviewed evidence:
`7aa66ff0542175092753ea099f40b903ece0527e`.
The fresh four-case `2cf9853` N128/256 Taylor–Green repeat retained all `11901a7`
settings and gates. All 20 main scalar rows and 260 early-pressure samples matched
the older receipts exactly; this is not field-array equality. Projected worst
velocity was 0.001995299260844 versus 0.002 (only 0.235% margin), pressure
0.012157174904932 and energy 0.001184362645162. Constant velocity
0.004418076615223 failed its gate, so the aggregate verdict remains false.
The projected early sampled pressure peak was 0.021621453573334; it remains a
descriptive sampled maximum. Reviewed evidence: `90849a55cad4a0da9b72747da7bfe6eb75962a44`.
The old N64 projected failures remain relevant. These results support only this
bounded plumbing gate and short periodic Re100 smooth-decay experiment. They do
not establish union/multilevel physics accuracy, convergence, long-time stability,
body/Jet, boundary, forcing, MRT or LES suitability. Constant remains the default.
## Separate LES source profile
The two older LES source manifests and the historical default are unchanged and
correctly reject this different source tree. The existing LES runner now offers
`--experiment a135252`, pinning all 101 actual committed corrected source files.
Its explicit baseline-header override describes only a synthetic isolated reverse
control, never the committed a135252 header. The unchanged corrected-only uniform
LES regression (Cs=0/.16/1) is the remaining integration gate; no LES result is
inherited from the projected evidence. The separate historical jet-CV `channel.py`
pin mismatch predates this port and is not addressed here.
+1 -1
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@@ -1,6 +1,6 @@
# Blocked AMR root channel increment
Opt in with `FixedPatchStepper(..., coarse_boundary="channel", base_block=(by,bx), fine_block=(fy,fx))`, or the existing level-list form. Every level must be blocked. The supported boundary is the existing uniform D2Q9/SRT/FP32 double-buffer channel: local Zou-He west inlet, pressure-NEQ east outlet, stationary halfway bounce-back y walls. Uniform and parabolic inlet profiles and shifted/unshifted storage are supported; the existing configuration guards still reject MRT/LES and incompatible storage. This does not change the external DFG MRT reference.
Opt in with `FixedPatchStepper(..., coarse_boundary="channel", refinements=[bounds], level_blocks=[(by,bx), (fy,fx)])`. Every level must be blocked. The supported boundary is the existing uniform D2Q9/SRT/FP32 double-buffer channel: local Zou-He west inlet, pressure-NEQ east outlet, stationary halfway bounce-back y walls. Uniform and parabolic inlet profiles and shifted/unshifted storage are supported; the existing configuration guards still reject MRT/LES and incompatible storage. This does not change the external DFG MRT reference.
`step/block_channel.cu` is a small root-only kernel. Fine kernels, transfer kernels and recursive hop scheduling are unchanged. Global coordinates and the global profile height/velocity are separate from block-local storage strides. Corner ownership and collision phases match `OneStep`:
+33 -21
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@@ -1,23 +1,26 @@
# Fixed three-level separated patches
# Fixed three-level rectangle unions
`FixedPatchStepper` supports exactly three static, blocked levels with separated
rectangle sets on either adjacent pair. This is not general AMR: there is no
per-region timestep, moving geometry, dynamic refinement or L1 body support.
This page describes three-level `FixedPatchStepper` setups built from the
`refinements` level list, with rectangle unions on either adjacent pair. The
same constructor supports arbitrary depth; three or more levels require
all-blocked storage and bodies/Jets only on the finest level. This is not
general AMR: there is no per-region timestep, moving geometry, automatic
dynamic refinement or L1 body support in the three-level form.
All regions share one current/spare buffer pair per level. The existing schedule
advances L0 once, L1 twice and L2 four times per base step, with aggregate transfers.
No CUDA kernel changes are involved.
## Explicit coordinate frames
Keep the existing scalar `child=(x0,y0,x1,y1)` for a single scalar parent patch.
Its coordinates retain their original meaning: half-open integer indices in the
allocated L1 window, including its ghost band.
For a single scalar parent patch, pass a scalar rectangle as `refinements[1]`:
`(x0,y0,x1,y1)` in half-open integer indices of the allocated L1 window,
including its ghost band.
The new keyword `child_rectangles_in_parent=[...]` is mutually exclusive with
`child`. It accepts a scalar or a set parent and interprets every rectangle in
the actual allocated L1 array, including ghost bands and holes. It never infers
region-local coordinates. The physical root cell edge corresponding to an L1
index `(x,y)` is `parent.fine_origin + (x,y)/2`:
A rectangle list as `refinements[1]` accepts a scalar or a set parent and
interprets every rectangle in the actual allocated L1 array, including ghost
bands and holes. It never infers region-local coordinates. The physical root
cell edge corresponding to an L1 index `(x,y)` is
`parent.fine_origin + (x,y)/2`:
- A scalar L1 parent has a shifted window origin.
- A set L1 parent has origin `(0,0)` and public shape `(2*ny,2*nx)`.
@@ -30,20 +33,23 @@ are physically equivalent to parent set `[(4,4,12,12)]` with child set
`[(8,8,16,16)]`. Reusing the same numbers after changing the parent frame can
move the physical region.
Both adjacent pairs require a Chebyshev gap of at least four in their own
parent-cell units. The whole child union must preserve inherited ACTIVE
coverage, uncovered ACTIVE donors/receivers, surviving pulls, and the upstream
Both adjacent pairs are built from their unions, without a fixed rectangle-gap
rule. Adjacent, overlapping and concave unions are accepted only when their
actual transfer dependencies close. The whole child union must preserve
inherited ACTIVE coverage, uncovered ACTIVE donors/receivers, surviving pulls, and the upstream
restriction footprint. Sparse holes remain unowned; inherited INNER remains
stream-only and OUTER remains invalid. Block sizes must align with every
support edge, including its four-cell ghost band.
stream-only and OUTER remains invalid. Block sizes must divide their allocated
level grids. Sparse storage owns every grid-aligned tile intersecting the union
plus its four-cell ghost band; rectangle and support edges need not align with
tile edges.
## Example
```python
run = FixedPatchStepper(
cfg, [(4, 4, 20, 28), (24, 4, 44, 28)], context=ctx,
base_block=(4, 4), fine_block=(4, 4), child_block=(4, 4),
child_rectangles_in_parent=[(16, 16, 32, 40), (56, 16, 80, 40)],
cfg, context=ctx,
refinements=[[(4, 4, 20, 28), (24, 4, 44, 28)], [(16, 16, 32, 40), (56, 16, 80, 40)]],
level_blocks=[(4, 4)] * 3,
)
```
@@ -51,7 +57,7 @@ This example uses a 48x32 root. `initialize` and `download` use three Q-major
dense arrays. Public arrays and masks still scale with the full allocated
extent; sparse device buffers do not remove that host-memory limit.
Stationary whole-circle `child_objects` and `child_jets` use root edge
Stationary whole-circle L2 bodies and Jets (`level_objects[2]`, `level_jets[2]`) use root edge
coordinates and a single L2 boundary object. Body IDs are physical object-list
positions, not region IDs or caller `obj_id`. Complete boundary stencils must
avoid the transfer footprint. Change a child Jet with
@@ -65,6 +71,12 @@ CPU geometry, table, pre-CUDA rejection, schedule and cleanup tests:
PYTHONPATH=src python -m unittest discover -s tests/unit -p 'test_refinement*.py' -v
```
`tests/unit/test_union_refinement.py` covers union dependencies and tile
ownership; `tests/unit/test_hierarchy.py` covers composed geometry through four
levels. `tests/unit/test_raw_exchange.py` checks the four-level host schedule
with CUDA mocks. These establish topology/control-flow coverage, not numerical
qualification at every depth or interface shape.
Explicit GPU gates are in
`tests/validation/multigrid/test_refinement_three_level_multipatch_gpu.py`.
They cover physical-frame equivalence, twins, asymmetric refinement, multiple
+87
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@@ -0,0 +1,87 @@
# Supported settings: 2D Jet + fixed multilevel refinement (candidate c95a7ba)
Every entry names the guard that enforces it (file:line at c95a7ba) and, where one
exists, an existing test that exercises it. A setting not listed here is not
claimed. Observations at the end are tied to the exact case in which they were
measured; they are not general bounds.
## Lattice, storage, collision
| Setting | Supported | Guard |
|---|---|---|
| Dimension / lattice | 2D D2Q9 only (3D refinement is future work) | `lbm/refinement.py:65`, `lbm/kernels/blocks.cu:25`, `lbm/kernels/refinement.cu:26` |
| Precision / streaming | FP32 storage, double buffer | same guards |
| Collision on refinement levels | SRT or MRT; TRT and LES rejected | `lbm/refinement.py:65` (re-checked for fine boundaries at `lbm/refinement.py:457`) |
| Shifted (ddf_shifting) storage | only when every level is blocked; dense or mixed rejected | `lbm/refinement_stepper.py:198`, `:469`; `lbm/kernels/refinement.cu:26` (dense patch kernel unshifted only) |
| Fine relaxation | 1/tau_fine must lie inside the configured omega guards | `lbm/refinement.py:80` |
| Uniform blocked backend `PeriodicBlockStepper` | doubly periodic, SRT only, stationary passive circles | `lbm/block_stepper.py:84`, `:91`, `:45`-`:67` |
Tests: `tests/unit/test_refinement_mrt.py`, `tests/validation/multigrid/test_refinement_mrt_gpu.py`,
`tests/unit/test_shifted_storage.py`, `tests/unit/test_shifted_block_operators.py`.
## Refinement hierarchy (`FixedPatchStepper(cfg, *, context, refinements, ...)`)
| Setting | Supported | Guard |
|---|---|---|
| Depth | at least one refinement level; one entry per level in `level_blocks`/`level_objects`/`level_jets` | `lbm/refinement_stepper.py:72`, `:75` |
| Single L1 rectangle | two-coarse-cell margin to the domain edge | `lbm/refinement.py:73` |
| Several L1 rectangles (union) | require `level_blocks[0]` and `level_blocks[1]`; transfers must close (dependency checks, no fixed gap rule) | `lbm/refinement_stepper.py:84`; `lbm/refinement.py:283`-`:295` |
| Nested levels | depth >= 3 must be all blocked; a blocked level requires blocked levels below; a scalar child needs a scalar parent | `lbm/refinement_stepper.py:82`, `:87`; `lbm/hierarchy.py:54` |
| Nested transfer support | child only over inherited ACTIVE cells, donors/receivers uncovered ACTIVE, no child over the parent restriction footprint | `lbm/refinement.py:391`-`:407` |
| Tile shape | positive `(by, bx)`; the level allocation must be divisible by the tile (no partial tiles yet) | `lbm/refinement_stepper.py:78`, `lbm/refinement.py:246` (shape); `lbm/blocks.py:134` (divisibility) |
| Coarse boundary | `periodic`, `slot_reservoir` or `channel` | `lbm/refinement_stepper.py:177` |
| `slot_reservoir` | on-site velocity bottom slot, reservoir top, velocity 0, 2 <= slot width < nx, patch rows 4..ny-4 | `lbm/refinement_stepper.py:205`, `:212`; `lbm/refinement.py:546` |
| `channel` | all levels blocked; Zou-He inlet, pressure-NEQ outlet, stationary bounce-back walls; transfers away from the closure | `lbm/channel.py:22`, `:26`, `:43`, `:54` |
| Explosion | `constant` (default); `projected_linear` only periodic, all-blocked SRT, no bodies/Jets, no LES (experimental) | `lbm/refinement_stepper.py:188`, `:193` |
| L2 runtime remap (`remap_child`) | periodic three-level L2 sets only, no L0/L1 bodies, identical pinned boundary | `lbm/refinement_stepper.py:557`, `:567`-`:581` |
Tests: `tests/unit/test_refinement_three_level_multipatch.py`, `tests/validation/multigrid/test_refinement_multipatch.py`,
`test_refinement_three_level.py`, `test_refinement_three_level_multipatch_gpu.py`, `test_refinement_blocked_base.py`,
`test_refinement_blocked_fine.py`, `test_channel_root_gpu.py`, `tests/unit/test_channel_root.py`,
`tests/unit/test_projected_pair_stepper.py`, `test_runtime_child_remap_gpu.py`, `test_pinned_body_remap_gpu.py`.
## Bodies and Jets on refined levels
| Setting | Supported | Guard |
|---|---|---|
| Bodies | stationary circles without sensor/force-region roles, entirely inside the patch union, fully resolved, disjoint, stencil away from the two-hop transfer footprint | `lbm/refinement.py:474`-`:542` |
| Level | not on L0; only on the finest level of a nested hierarchy | `lbm/refinement_stepper.py:80`, `:89` |
| Jet condition | velocity only; `pressure` is reserved and raises NotImplementedError | `body/jets.py:148`, `:150` |
| Jet geometry | each Jet selects resolved links of exactly one stationary body; no Jet/Jet or Jet/SurfaceActuation overlap; abs(amplitude) < 1 lattice | `body/jets.py:155`, `:175`, `:177`, `:255`, `:261`, `:263` |
| Jets with shifted storage | only in the all-blocked stepper with SRT and no LES | `body/jets.py:249` |
| SurfaceActuation | unshifted storage only | `body/objects.py:155` |
| Raw boundary exchange (force) | blocked body levels only; the window ledger requires `observe_raw_exchange` | `lbm/refinement_stepper.py:264`, `:269` |
| Checkpoint with Jets | refused | `simulation.py:687` |
Raw exchange is the cut-link momentum reaction (wall + aperture), not a validated
nozzle thrust or stress load. Jet amplitude is a lattice velocity, not a flow rate.
Tests: `tests/unit/test_jets.py`, `test_jets_review.py`, `test_shifted_jets.py`, `test_raw_exchange.py`,
`tests/validation/multigrid/test_refinement_jets.py`, `test_shifted_jets_gpu.py`, `test_raw_exchange_gpu.py`,
`test_exchange_window.py`, `test_fine_surface_gpu.py`.
## Observations from specific tested cases (not general bounds)
- SRT channel root vs uniform OneStep, strict-parity test
`tests/validation/multigrid/test_channel_root_gpu.py::ChannelRootGPU::test_uniform_matched_root`:
in one of its 18 sub-cases (2 storage modes x 3 profile/clamp/damp settings x 3 blocks; which
one is not recorded), 1 of the 4320 compared values differs, max abs 2.33e-10, max rel 1.77e-7
(about 2 ULP). The test remains failed; its cause and any general bound are unresolved.
- MRT root parity test
`tests/validation/multigrid/test_refinement_mrt_gpu.py::RefinementMRTGPU::test_uniform_matched_mrt_root`
(12 sub-cases: 2 storage modes x 2 profiles x 3 blocks, default outlet settings) passed bitwise
in the Horsea focused GPU run at K1 7813334 (2026-10-21).
- Periodic Taylor-Green Re 100, measured at 36ffc8b1 (V3 matched pair, N128 depth 2):
every per-sample screen passed; the constant explosion's aggregate worst velocity L2,
0.004418, exceeds its preregistered 0.002 budget, while projected_linear passed that budget.
- Curved-wall pressure (pilot harness, exact-q analytic annulus, tau 0.8): the coarse swirl r1
case exceeded its terminal density-gain cap (1.105e-4 vs 1e-4), so the frozen 9-case matrix
is NOT_ESTABLISHED. No validated fix exists. This is a pilot harness, not production code.
- DFG 2D-1 Re 20 (V4, SRT, t* 60, pressure-NEQ outlet and local Zou-He inlet): refined and uniform
runs were NOT_STEADY under the frozen steady rule, so no interval verdict was given.
## Not supported in this release
3D, dynamic/automatic AMR (tagging, time-varying hierarchies beyond `remap_child`),
moving bodies on refined levels, pressure Jets, Jet checkpoints, LES or TRT on refined
levels, partial (non-dividing) tiles.
+37 -25
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@@ -1,11 +1,15 @@
# Synchronized leaf G remap and manual continuation
This is a CPU state-transfer component, **not a runtime adaptive solver**.
It changes only a separated L2 rectangle set in a three-level, body-free,
periodic hierarchy. L0/L1 topology, relaxation parameters, direction order,
It changes only an L2 rectangle union in a three-level periodic hierarchy.
The body-free case is shown first; stationary L2 bodies/Jets follow the bounded
support contract below. L0/L1 topology, relaxation parameters, direction order,
physical frame and completed time remain unchanged. Existing geometry checks
validate child support/nesting and separation. The CPU helper itself adds no CUDA, scheduler, allocator, boundary handling,
collision or ghost refill. A bounded runtime adapter is described below.
validate child support/nesting and actual transfer dependencies, without a fixed
rectangle-gap rule. The three-level remap limit is unchanged by the stepper's
arbitrary-depth level-list support. The CPU helper itself adds no CUDA,
scheduler, allocator, boundary handling, collision or ghost refill. A bounded
runtime adapter is described below.
```python
from CelerisLab.lbm.refinement import FixedPatchSet2D
@@ -29,11 +33,13 @@ origin is retained. Physical lower edges are `origin + spacing*(x,y)` on L0,
`origin + spacing*(parent.fine_origin + (x,y)/4)` on L2.
Factory options `coarse_boundary` and `objects` must declare `"periodic"` and
an empty body collection (all levels). LBMConfig's channel settings do not
select this operator's boundary mode. Geometry metadata is factory-created;
an empty collection; L2 bodies use `child_objects` as described below.
LBMConfig's channel settings do not select this operator's boundary mode.
Geometry metadata is factory-created;
manual mutation/forging of metadata is unsupported. Caller certifies the
actual state has no bodies/forcing, that all device work and old readers are
quiescent, and that inputs are the **current owned-leaf postcollision G**.
actual state matches the declared boundary and has no forcing, that all device
work and old readers are quiescent, and that inputs are the **current owned-leaf
postcollision G**.
Count/phase stamps check consistency, not freshness or active-buffer identity.
`current_g` is three NumPy Q-major arrays `(9,ny,nx)`. For blocked inputs,
@@ -73,9 +79,10 @@ PYTHONPATH=src python -m unittest discover -s tests/unit -p 'test_synchronized_r
`replacement = current.remap_child(rectangles)` returns a new ready
`FixedPatchStepper` at the **same absolute step_count**. It supports only
body-free periodic three-level runs whose existing L2 uses
`child_rectangles_in_parent`. Scalar or union L1 parents are supported; scalar
`child=` is deliberately rejected. L0/L1, relaxation and block sizes stay fixed.
periodic three-level runs with no L0/L1 bodies and an existing L2
`FixedPatchSet2D`; stationary L2 bodies/Jets follow the support contract below.
Scalar or union L1 parents are supported; scalar `child=` is deliberately
rejected. L0/L1, relaxation and block sizes stay fixed.
No tagger, scheduler, in-place replacement, or general rollback is provided.
The method holds the stepper lock, validates geometry, synchronizes its stream,
@@ -113,13 +120,14 @@ Per-population conservation is not an advancement target under collision.
### Bounded pinned-body extension
`replacement = current.remap_child(rectangles, child_objects=original_objects)`
also accepts stationary Circles in separated L2 rectangles. Every body’s
**complete containing rectangle must remain identical**. Several bodies may
share one pinned rectangle; there need not be any fluid-only rectangles.
Separated fluid-only rectangles may be added, removed or moved. Existing
nesting, four-cell gap, full-circle containment, reverse cut-link coverage and two-hop BFL
transfer-footprint checks still apply. This is manual remapping, not adaptive
body tracking or runtime body editing.
also accepts stationary Circles inside the L2 union. Each body's **physical
boundary, complete BFL support and current per-link velocity must remain
identical**. Rectangles are not pinned: they may be split, merged or resized,
and other fluid coverage may change, including within the same connected union,
provided that physical support is unchanged. Existing nesting, union transfer
dependencies, full-circle containment, reverse cut-link
coverage and two-hop BFL transfer-footprint checks still apply. This is manual
remapping, not adaptive body tracking or runtime body editing.
Supply all original root edge-frame definitions in their construction order.
Do not pass `current.child_boundary.objects`: those are projected fine-local copies.
@@ -128,8 +136,8 @@ state, remapping reprojects the supplied definition onto the old topology and
compares exact ordered circle centers/radii, flags, physical cut links, body
IDs, q, lever arms, hits, BFL support,
legacy SurfaceActuation specification and current per-link velocity against
the existing boundary. Omission, changed geometry/actuation and changed body
rectangle fail without device reads or allocations; reordered bodies fail
the existing boundary. Omission, changed geometry/actuation or changed physical
boundary/BFL support fail without device reads or allocations; reordered bodies fail
too. Root object IDs are still assigned by list position, as in the constructor.
Jets are taken from the live L2 boundary, including the most recent successful
@@ -141,12 +149,16 @@ boundary and velocities must match exactly.
typed `FineBoundary2D`; it derives L2 fluid leaves as ACTIVE minus SOLID. No
caller mask is accepted. Solids, ghosts and holes are never donors and remain
NaN, physical-fluid overlap is exact, and exposed L1 still restricts all four
old fluid children. The helper checks the old/new body pins and boundary too.
Its immutable `pinned_rectangles` is a canonical, deduplicated tuple, empty for body-free layouts; rectangle input
order does not affect it. Scalar-parent window offsets remain part of the
coordinate conversion.
old fluid children. The helper checks old/new physical boundary and velocity
equality too. Its immutable `pinned_rectangles` is legacy containment metadata,
not a remap eligibility constraint; it may be empty for a seam-spanning body.
Scalar-parent window offsets remain part of the coordinate conversion.
Focused CPU mocks: `tests/unit/test_pinned_body_remap.py`. GPU declarations:
Focused CPU mocks: `tests/unit/test_pinned_body_remap.py`.
`tests/unit/test_union_body_support.py` also checks seam-spanning circles,
rectangle repartition/resize, unchanged physical support and live-Jet
preservation. These host checks do not establish GPU evolution accuracy.
GPU declarations:
`tests/validation/multigrid/test_pinned_body_remap_gpu.py`, covering no-op
next-step bitwise identity, moved-fluid A→B→A, current-amplitude preservation,
physical boundary/velocity equality, source independence and absolute counts.
+49
View File
@@ -0,0 +1,49 @@
# DFG 2D-1 (Re 20) against the official reference intervals
`tests/validation/run_dfg_re20.py` runs the steady DFG 2D-1 case on the refined
channel root (D40 root, D80 wide fine patch) and on the uniform D80 grid. Geometry,
inflow, initial state, layout and observation are those of the pinned Re100 runner
(`run_refined_dfg.py`, `re100_helpers.py`, both unchanged); only the lattice
viscosity is set for Re 20 (root tau 0.56, fine 0.62, uniform 0.62, lattice speed 0.01).
Label: "compared against the official reference bands", not a full benchmark
certification: the outlet is pressure-NEQ (`neq_extrap`), not do-nothing, and the
inlet is local Zou-He.
## Quantities
- Cd = 2 Fx / (rho U^2 D), Cl = 2 Fy / (rho U^2 D), interval means over each sample.
- p_diff = p(0.15, 0.2) - p(0.25, 0.2), linear extrapolation to the exact surface
points (`re100_helpers.pressure_probes`). The helper returns dp / (rho U^2) in
scaled units; p_diff = dp * 0.04 for U = 0.2 m/s, rho = 1. Both are reported.
- Official intervals (Schaefer & Turek 1996): Cd [5.57, 5.59], Cl [0.0104, 0.0110],
p_diff [0.1172, 0.1176].
## Bounds and steady rule (frozen before any run)
- End time t* = 60 (30 s physical): 240,000 refined root steps, 480,000 uniform steps.
- One sample every t* = 0.5 (0.25 s) at the end of a synchronized root step; Cd and
Cl are interval means. Trailing window t* 50..60 inclusive (21 samples).
- Steady rule (our engineering choice, not official): in the window, for each of Cd,
Cl, p_diff, max - min <= 10 % and |least-squares slope x window| <= 2 % of its
official interval width (range 2e-3 / 6e-5 / 4e-5; slope 4e-4 / 1.2e-5 / 8e-6).
Absolute limits, so the small Cl is never a divisor. Never relaxed after a run.
- The verdict uses the window mean; the distance to the nearest interval edge is
reported for each quantity (negative outside).
- Force sign: fluid on cylinder, x along the inflow, y up from the bottom wall; Cd > 0
and the official Cl > 0 (`cd_positive` is reported).
- Not steady at t* = 60: status `NOT_STEADY`, no interval verdict. Health limits
(Mach <= 0.2, rho in [0.5, 1.5]) stop the run with `UNHEALTHY`.
- Steady: `WITHIN_INTERVALS` or `OUTSIDE_INTERVALS`, with the per-quantity verdict.
## Run
```
python tests/validation/run_dfg_re20.py --output <new-dir> --plan
CUDA_VISIBLE_DEVICES=<n> python tests/validation/run_dfg_re20.py --case both \
--collision SRT --output <new-dir> --max-wall-seconds <cap>
```
The uniform D80 control separates method error from refinement error. `--plan` writes `plan.json` only. A GPU run writes `plan.json` and `result.json`
(per case: lattice parameters, every sample, window ranges, status, verdict).
Host contract tests: `tests/unit/test_dfg_re20.py`.
+59
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@@ -56,3 +56,62 @@ Root must independently review and admit any execution. An admitted paired pilot
the existing watchdog, device selection, `--gpu-gates-approved`, positive
`--max-wall-seconds` and a new output directory, adding only `--exchange-window` to the
selected collision's pilot command. No GPU or remote action was performed for this patch.
## Public Jet diagnostic option
`--collision MRT --exchange-window --jet-scenario zero|fixed|reverse` selects
unshifted FP32, no LES, constant transfer on both existing public backends. Default
`none` and the historical manifests remain unchanged. `zero` registers both Jets at
zero amplitude and retains every existing DFG verdict, including pressure. `fixed`
uses outward radial parabolic sectors at pi/2 and 3pi/2, half-width pi/12, peaks
(+.001,-.001). Both use the existing D40/D80 geometry and U=.01. Sector origins are
(80.5,81) in root edge coordinates and (160,160.5) in uniform node coordinates;
radial extent is [0,1.005R]. `reverse` keeps those peaks through t*=300, updates both
public setters at that completed boundary, and continues to 305 with opposite signs.
Fixed diagnostic windows are 250–260, 260–270, 270–280, 280–290 and 290–300; reversal
adds 300–305. Histories retain exact interval endpoints and root/uniform lattice
impulses. The refined window uses total exchange; uniform uses public `read_force`
batch averages. Driven windows report mean/min/max/RMS Cd/Cl without applying DFG
reference or periodicity gates. Exit zero means healthy execution, not qualification;
`matched_case_pass` remains false. No independent CV or stress-load claim is made.
This opt-in records current source/helper hashes with the existing manifest format,
checkout revision/dirty state and runner hash. Pilot/full must match that snapshot
and the exact scenario. It does not relabel current source as historical evidence.
Use the existing bounded plan/pilot/full commands with the three option flags above;
full requires the matching completed t*=5 paired pilot. `step_seconds` includes force
readback; observation/overhead and total wall time are separate, not kernel throughput.
Add `--observe-cv` to record independent scalar control-volume samples from the
already downloaded public macros. The pilot exercises this path at t*=.02..5;
full records 501 endpoints at 290..300. Each `cv_history.jsonl` row contains actual
root time, preceding interval start/duration/impulse, and two inventories/outward
fluxes ordered [mass,Px,Py]. Exclude the first row's preceding impulse: that row
supplies the initial inventory. Uniform native impulse converts by .5² to root
units; refined ledger impulse is already in root units. Explicit native-aligned
contours differ by .25 root cells in x and are recorded in the plan. Cropping
retains the two-cell face-gradient stencils. No fields or per-link arrays are saved.
`cv_observation_seconds` is the CV portion of observation/overhead time. Helper hash
and the observation flag must match pilot/full. Time integration, temporal
coarsening and any physical assessment remain separate offline work.
## Bounded resolution and placement controls
Defaults remain `--case both --uniform-diameter 80 --placement wide`. Single-case
runs use `--case uniform` or `--case refined` and never report a matched-case pass.
Their own reference/periodicity or driven-diagnostic results remain available.
A single zero-Jet full run exits successfully only when its periodicity and the
unchanged complete DFG reference verdict pass; driven completion is not qualification.
The D160 option requires `--case uniform --uniform-diameter 160` and an explicit
public Jet scenario. U and Jet speeds stay .01 and ±.001; viscosity is .016,
grid 3521×658, center (320,320.5), radius80. CV uses root spacing/time factor .25,
origin (.375,.75), impulse factor .0625, root viscosity .004, and x-face shift .125.
`--case refined --placement compact` selects root bounds (48,48,128,128), fine
168×168 and origin (46,46), with the same D40/fineD80 body/Jet resolution. Its CV
contours are (52,52,112,112) and (50,50,120,120); complete face-gradient stencils
are clear of both solids and the transfer footprint. Compact is refined-only.
CV metadata gives each grid's spacing/origin/contours explicitly. Case, uniform
diameter and placement must match the newly completed pilot in every receipt.
+2 -2
View File
@@ -90,8 +90,8 @@ def main():
# The caller owns the CUDA context; the stepper must be closed first (the
# nested with-statement does that).
with CudaContext(0) as context, FixedPatchStepper(
cfg, BOUNDS, context=context, coarse_boundary=args.mode,
fine_objects=[body], fine_block=fine_block) as run:
cfg, context=context, coarse_boundary=args.mode, refinements=[BOUNDS],
level_blocks=[None, fine_block], level_objects=[(), (body,)]) as run:
p = run.patch
# Rest equilibrium is already postcollision G, so no initial collision is
# needed. Non-leaf entries (covered, ghost, solid) are discarded by initialize.
+2 -2
View File
@@ -148,8 +148,8 @@ def main():
samples=[], status='running', last_synchronized_coarse_step=0)
start, run = time.monotonic(), None
try:
with CudaContext(0) as context, FixedPatchStepper(cfg, BOUNDS, context=context,
coarse_boundary='slot_reservoir') as run:
with CudaContext(0) as context, FixedPatchStepper(cfg, context=context,
coarse_boundary='slot_reservoir', refinements=[BOUNDS]) as run:
p = run.patch
masks = [np.ones(p.coarse_shape, bool), p.fine_kind == ACTIVE]
masks[0][[0, -1]] = False
+1 -1
View File
@@ -48,7 +48,7 @@ def main():
nx=16, ny=16, viscosity=.1, velocity=1e-3, rho=1.0,
lattice_model="D2Q9", collision="SRT", streaming="double_buffer",
store_precision="FP32", ddf_shifting=False, les_enabled=False)
with CudaContext(0) as context, PeriodicPatchStepper(cfg, (4, 4, 12, 12), context=context) as run:
with CudaContext(0) as context, PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)]) as run:
p = run.patch
coarse = shear_equilibrium(p.coarse_shape, (0, 0), 1.0, cfg.ny)
fine = shear_equilibrium(p.fine_shape, p.fine_origin, .5, cfg.ny)
+16 -8
View File
@@ -207,22 +207,30 @@ def surface_link_velocity(objects, cfg, flags, fluid_idx, dir, body_id, rx, ry,
jets=(), hits=None, *, _shifted_blocked=False):
"""Per-link prescribed surface velocity (n, 2) FP32 and aperture mask.
See _surface_links, which also returns the unit-amplitude jet shapes.
"""
return _surface_links(objects, cfg, flags, fluid_idx, dir, body_id, rx, ry, jets, hits,
_shifted_blocked=_shifted_blocked)[:2]
def _surface_links(objects, cfg, flags, fluid_idx, dir, body_id, rx, ry,
jets=(), hits=None, *, _shifted_blocked=False):
"""(velocity, aperture, jet shape, jet id); the last two are None without jets.
Host-only and storage-neutral: rows follow the given physical cut-link
order. Returns (None, None) when neither an object carries surface
order. Returns all None when neither an object carries surface
actuation nor a jet is given. Jets need true FP64 ``hits`` (n, 2) and may
not share a link with each other or with a legacy aperture.
Shifted storage is privately enabled only by the all-blocked stepper.
"""
enabled = [obj for obj in objects if obj.surface_actuation is not None]
if not enabled and not jets:
return None, None
from ..lbm.descriptors import FLUID, SOLID
if np.any((flags[fluid_idx] & FLUID) == 0) or np.any(flags[fluid_idx] & SOLID):
raise ValueError("Surface cut links must have active fluid receivers")
if len(np.unique(fluid_idx.astype(np.uint64)*cfg.nq+dir)) != len(dir):
raise ValueError("Surface boundary requires unique cut-link writers")
return None, None, None, None
from .preprocess.flag_overlay import validate_cut_link_ownership
validate_cut_link_ownership(flags, fluid_idx, dir, cfg.nq)
surface_velocity = np.zeros((len(dir), 2), np.float32)
surface_aperture = np.zeros(len(dir), bool)
shape = jet_id = None
for obj in enabled:
obj.validate_surface_actuation(cfg)
selected = body_id == obj.obj_id
@@ -255,4 +263,4 @@ def surface_link_velocity(objects, cfg, flags, fluid_idx, dir, body_id, rx, ry,
raise ValueError("Jet overlaps a SurfaceActuation aperture")
surface_velocity[driven] = jet_link_velocity(jets, shape, jet_id)[driven]
surface_aperture |= driven
return surface_velocity, surface_aperture
return surface_velocity, surface_aperture, shape, jet_id
+17 -12
View File
@@ -27,7 +27,7 @@ import pycuda.driver as cuda
from .objects import SimObject
from .registry import BodyRegistry
from .preprocess.flag_overlay import merge_flag_masks
from .preprocess.flag_overlay import merge_flag_masks, validate_cut_link_ownership
from ..cuda.compiler_v2 import obs_layout
from ..cuda.obs_layout import ObsLayout
from ..lbm.descriptors import (
@@ -369,9 +369,9 @@ class ObjectManager:
Args:
objects: List of SimObject instances to process.
domain_flags: Optional uint16 flags for donor-cell classification.
domain_flags: Optional uint16 flags for receiver/donor classification.
sensor_cell_counts_out: Int array to fill with per-object sensor
cell counts. If provided, ``fill(0)`` is called first.
cell counts after the full geometry has passed validation.
hits_out: List that receives one FP64 (n, 2) array of true hit
points row-aligned with the cut-link columns (for Jets).
@@ -394,8 +394,8 @@ class ObjectManager:
active_fluid = ((domain_flags & FLUID) != 0) & ((domain_flags & SOLID) == 0)
force_owners: set[int] = set()
if sensor_cell_counts_out is not None:
sensor_cell_counts_out.fill(0)
sensor_counts = (np.zeros_like(sensor_cell_counts_out)
if sensor_cell_counts_out is not None else None)
ez = None
if self.cfg and self.cfg.is_d3q19:
@@ -430,9 +430,9 @@ class ObjectManager:
if len(cells) > 0:
s_cells.append(cells)
s_ids.append(ids)
if (sensor_cell_counts_out is not None
and 0 <= obj.obj_id < sensor_cell_counts_out.size):
sensor_cell_counts_out[obj.obj_id] = int(len(cells))
if (sensor_counts is not None
and 0 <= obj.obj_id < sensor_counts.size):
sensor_counts[obj.obj_id] = int(len(cells))
if obj.is_force_region and hasattr(obj, 'get_sensor_list'):
cells, ids = obj.get_sensor_list(self.nx, self.ny, self.nz)
keep = active_fluid[cells]
@@ -461,8 +461,9 @@ class ObjectManager:
r_fr_ids = np.concatenate(fr_ids) if fr_ids else np.zeros(0, dtype=np.int32)
r_hit = np.concatenate(cl_hit) if cl_hit else np.zeros((0, 2))
if hits_out is not None:
hits_out.append(r_hit)
# Passive walls need the same ownership guarantees as driven walls.
# Overlapping solids are not a supported union-boundary operation.
validate_cut_link_ownership(domain_flags, r_idx, r_dir, self.nq)
if self.jets or any(obj.surface_actuation is not None for obj in objects):
# Reject unresolved apertures/ownership before sync or restart mutates state.
from ..lbm.curved_links import CurvedLinkSoA
@@ -470,6 +471,11 @@ class ObjectManager:
links.assign_host(r_idx, r_dir, r_q, r_bid, r_rx, r_ry, r_rz, r_fallback)
links.assign_surface(objects, self.cfg, domain_flags, jets=self.jets, hits=r_hit)
if sensor_cell_counts_out is not None:
sensor_cell_counts_out[:] = sensor_counts
if hits_out is not None:
hits_out.append(r_hit)
return (
r_idx, r_dir, r_q, r_bid,
r_rx, r_ry, r_rz, r_fallback,
@@ -487,8 +493,6 @@ class ObjectManager:
the caller has already prepared and uploaded the final flag field
for this geometry, such as during initialization.
"""
self._telemetry_field = field
next_flags = self.build_flags(field.build_channel_flags()) if rebuild_flags else field.flag
hits = []
@@ -499,6 +503,7 @@ class ObjectManager:
fr_cells, fr_obj_id,
) = self.build_compact_lists(domain_flags=next_flags, hits_out=hits)
self._telemetry_field = field
if rebuild_flags:
field.flag = next_flags
field.upload_flags()
+10 -1
View File
@@ -1,6 +1,6 @@
# CelerisLab/body/preprocess/flag_overlay.py
"""
Flag overlay: merge per-object flag masks onto a clean domain base.
Flag overlay and cut-link ownership checks against the merged domain.
"""
from __future__ import annotations
@@ -12,6 +12,15 @@ import numpy as np
from ...lbm.descriptors import FLUID, SOLID, SENSOR_FLAG, FRC_REGION
def validate_cut_link_ownership(flags, fluid_idx, directions, nq):
"""Reject solid receivers and multiple writers to one population."""
if np.any((flags[fluid_idx] & FLUID) == 0) or np.any(flags[fluid_idx] & SOLID):
raise ValueError("Cut links must have active fluid receivers")
writers = fluid_idx.astype(np.uint64) * nq + directions
if len(np.unique(writers)) != len(directions):
raise ValueError("Boundary requires unique cut-link writers")
def merge_flag_masks(
base: np.ndarray,
masks: List[np.ndarray],
+14 -4
View File
@@ -204,11 +204,21 @@ class PeriodicBlockStepper:
raise
def step(self, n=1):
"""Advance n steps: halo refresh, then core pull/collide, per step."""
"""Advance n steps: halo refresh, then core pull/collide, per step.
All n steps are enqueued in order on the one stream and the host waits
once before returning (same launches and bits as n step(1) calls).
Asynchronous device errors surface at that single wait, so they are not
attributed to the step that caused them; call step(1) repeatedly to
localize one. On any failure the instance is failed and step_count keeps
its entry value.
"""
if isinstance(n, bool) or not isinstance(n, Integral) or n < 0:
raise ValueError("n must be a nonnegative integer")
with self._lock, self.ctx.activate():
self._require("ready")
if n == 0:
return
kw = dict(block=self._block, stream=self._stream)
try:
self._status = "advancing"
@@ -224,9 +234,9 @@ class PeriodicBlockStepper:
self._step(self._current, self._spare, np.uint32(self.layout.halo),
self._tables.get("flags", np.uintp(0)), np.uintp(0), # no kind
grid=self._grid, **kw)
self._stream.synchronize()
self._current, self._spare = self._spare, self._current
self._step_count += 1
self._current, self._spare = self._spare, self._current # host handles only
self._stream.synchronize()
self._step_count += n
self._status = "ready"
except BaseException:
self._status = "failed"
+2 -4
View File
@@ -94,12 +94,10 @@ class CurvedLinkSoA:
"""
self.surface_velocity = self.aperture = None
self.jets, self.jet_shape, self.jet_id = tuple(jets), None, None
self.surface_velocity, self.aperture = surface_link_velocity(
from ..body.jets import _surface_links
self.surface_velocity, self.aperture, self.jet_shape, self.jet_id = _surface_links(
objects, cfg, flags, self.fluid_idx, self.dir, self.body_id, self.rx, self.ry,
jets=self.jets, hits=hits)
if self.jets:
from ..body.jets import jet_link_shapes
self.jet_shape, self.jet_id = jet_link_shapes(self.jets, hits)
def set_jet_amplitude(self, index, amplitude, stream=None):
"""Rewrite jet rows from cached shapes; re-upload only the velocity column.
+36 -9
View File
@@ -63,6 +63,39 @@ extern "C" __global__ void BlockExplode(
to[index_f(t % TOTAL_CELLS, q)] = from[q * coarse_cells + d % coarse_cells];
}
// Experimental Schornbaum--Ruede (arXiv:1508.07982, Algorithm 2)
// and Chen et al. (doi:10.1016/j.physa.2005.09.036) population interpolation.
// Independent implementation of the mathematical stencil; no upstream source copied.
// Stencil cells are owner cores; a disabled axis repeats its center twice.
extern "C" __global__ void BlockExplodeProjected(
const fpxx* coarse, fpxx* fine, const uint64_t* target, const uint64_t* donor,
unsigned int count, unsigned long coarse_cells,
const uint64_t* neighbors, const float* offsets)
{
unsigned int row = blockIdx.x * blockDim.x + threadIdx.x;
if (row >= count) return;
const uint64_t t = target[row], d = donor[row];
fpxx* to = fine + (t / TOTAL_CELLS) * NQ * TOTAL_CELLS;
for (unsigned int q = 0; q < NQ; ++q) {
float v[4];
for (unsigned int a = 0; a < 4; ++a) {
const uint64_t n = neighbors[4ul * row + a];
v[a] = coarse[(n / coarse_cells) * NQ * coarse_cells
+ q * coarse_cells + n % coarse_cells];
}
float gx = .5f * (v[1] - v[0]), gy = .5f * (v[3] - v[2]);
const float ex = d_cx[q], ey = d_cy[q];
if (q != 0) {
const float along = (ex * gx + ey * gy) / (ex * ex + ey * ey);
gx -= ex * along;
gy -= ey * along;
}
to[index_f(t % TOTAL_CELLS, q)] =
coarse[(d / coarse_cells) * NQ * coarse_cells + q * coarse_cells + d % coarse_cells]
+ offsets[2ul * row] * gx + offsets[2ul * row + 1] * gy;
}
}
// Targets are receiver-local SOURCE slots for the immediately following pull.
// Keep child summation order identical to PatchCoarseStep; no collision here.
extern "C" __global__ void BlockCoalesce(
@@ -135,21 +168,15 @@ extern "C" __global__ void BlockStep(const fpxx* in, fpxx* out, unsigned int hal
stream_pull_load(k, f, in + base, j);
if (cell_kind == KIND_ACTIVE) {
if (d_block_wall.nx != 0) {
const unsigned int bx = NX - 2 * halo, by = NY - 2 * halo;
const unsigned int nbx = d_block_wall.nx / bx;
const unsigned int gx = (blockIdx.z % nbx) * bx + x - halo;
const unsigned int gy = (blockIdx.z / nbx) * by + y - halo;
unsigned int gx, gy;
block_global_xy(x, y, halo, d_block_wall.nx, gx, gy);
if (gy == 1)
reconstruct_bottom_velocity(f, 0.0f, bottom_wall_normal_velocity(
gx, d_block_wall.nx, d_block_wall.slot_width, d_block_wall.amplitude));
else if (gy == d_block_wall.ny - 2) reconstruct_top_reservoir(f, RHO);
}
#if COLLISION_MODEL == 2
// Uniform MRT sequence (collide_dispatch, zero forcing); SRT path below unchanged.
float rho, ux, uy;
compute_rho_u(f, rho, ux, uy);
collide_mrt_no_force(f, rho, ux, uy,
fminf(OMEGA_COLLISION_MAX, fmaxf(OMEGA_COLLISION_MIN, d_params.omega)));
collide_mrt_unforced(f); // SRT path below unchanged.
#else
float rho, ux, uy, feq[NQ];
compute_rho_u(f, rho, ux, uy);
@@ -53,6 +53,18 @@ __device__ __forceinline__ void index_from_thread(unsigned int& x,
k = (unsigned long)y * NX + x;
}
// Global cell of window cell (x, y) in block blockIdx.z of a row-major,
// full-domain block layout domain_nx cells wide. NX/NY are the local strides.
__device__ __forceinline__ void block_global_xy(unsigned int x, unsigned int y,
unsigned int halo, unsigned int domain_nx,
unsigned int& gx, unsigned int& gy)
{
const unsigned int bx = NX - 2 * halo, by = NY - 2 * halo;
const unsigned int nbx = domain_nx / bx;
gx = (blockIdx.z % nbx) * bx + x - halo;
gy = (blockIdx.z / nbx) * by + y - halo;
}
// ---------------------------------------------------------------------------
// Neighbor list (periodic BCs via modular arithmetic)
// ---------------------------------------------------------------------------
@@ -114,6 +114,16 @@ __device__ __forceinline__ void collide_mrt_no_force(float* __restrict__ g,
collide_mrt(g, rho, ux, uy, Fin, omega);
}
// Unforced MRT with the clamped device omega, as in collide_dispatch with zero
// forcing. Shared by the blocked, channel-root and dense-patch collisions.
__device__ __forceinline__ void collide_mrt_unforced(float* __restrict__ g)
{
float rho, ux, uy;
compute_rho_u(g, rho, ux, uy);
collide_mrt_no_force(g, rho, ux, uy,
fminf(OMEGA_COLLISION_MAX, fmaxf(OMEGA_COLLISION_MIN, d_params.omega)));
}
#elif LATTICE_MODEL == LATTICE_D3Q19
__device__ __forceinline__ void collide_mrt(float* __restrict__ g,
+1 -4
View File
@@ -37,10 +37,7 @@ __device__ unsigned int incoming_counts[NQ * TOTAL_CELLS];
__device__ __forceinline__ void patch_collide(float* f, unsigned long k) {
#if COLLISION_MODEL == 2
float rho, ux, uy;
compute_rho_u(f, rho, ux, uy);
collide_mrt_no_force(f, rho, ux, uy,
fminf(OMEGA_COLLISION_MAX, fmaxf(OMEGA_COLLISION_MIN, d_params.omega)));
collide_mrt_unforced(f);
#else
float rho, ux, uy, feq[NQ];
compute_rho_u(f, rho, ux, uy);
@@ -15,10 +15,8 @@ extern "C" __global__ void BlockChannelStep(
unsigned int x, y; unsigned long k;
index_from_thread(x, y, k);
if (x < halo || y < halo || x >= NX - halo || y >= NY - halo) return;
const unsigned int bx = NX - 2 * halo, by = NY - 2 * halo;
const unsigned int nbx = d_block_channel.nx / bx;
const unsigned int gx = (blockIdx.z % nbx) * bx + x - halo;
const unsigned int gy = (blockIdx.z / nbx) * by + y - halo;
unsigned int gx, gy;
block_global_xy(x, y, halo, d_block_channel.nx, gx, gy);
const unsigned long base = (unsigned long)blockIdx.z * NQ * TOTAL_CELLS;
const unsigned long cell = (unsigned long)blockIdx.z * TOTAL_CELLS + k;
float f[NQ];
@@ -55,11 +53,7 @@ extern "C" __global__ void BlockChannelStep(
}
if (!wall && !outlet) {
#if COLLISION_MODEL == 2
// Match uniform MRT arithmetic (collide_dispatch, zero forcing).
float rho, ux, uy;
compute_rho_u(f, rho, ux, uy);
collide_mrt_no_force(f, rho, ux, uy,
fminf(OMEGA_COLLISION_MAX, fmaxf(OMEGA_COLLISION_MIN, d_params.omega)));
collide_mrt_unforced(f);
#else
// Match uniform SRT arithmetic, including its shifted equilibrium path.
float rho, ux, uy, feq[NQ], forcing[NQ] = {};
+110 -146
View File
@@ -22,7 +22,7 @@ from .block_stepper import MAX_GRID_DIM
from .hierarchy import build_hierarchy, is_rectangle
from .refinement import ACTIVE, HALO, FixedPatch2D, FixedPatchSet2D, prepare_fine_boundary
from .refinement_tables import (blocked_base_tables, blocked_fine_tables, # noqa: F401 (re-export)
blocked_kind, _prepare_blocked_boundary,
blocked_kind, projected_explosion_tables, _prepare_blocked_boundary,
BLOCKED_BOUNDARY_DEVICE_COLUMNS)
from .descriptors import SOLID
from .raw_exchange import summarize_exchange
@@ -41,6 +41,8 @@ class _Pair:
n_ghosts: int
n_rows: int
parent_cells: int # parent block window cells (explode donor stride)
neighbors: object = None # projected-only owner-core cells; constant allocates neither
offsets: object = None
@dataclass
@@ -63,52 +65,8 @@ def _level_name(level):
return ("base", "fine", "child")[level] if level < 3 else f"level {level}"
def _legacy_levels(bounds, *, fine_block, base_block, child, child_block, child_rectangles_in_parent,
fine_objects, jets, child_objects, child_jets):
"""Normalise the original two/three-level keywords to per-level lists (original errors)."""
if child is not None and child_rectangles_in_parent is not None:
raise ValueError("child and child_rectangles_in_parent are mutually exclusive")
nested = child is not None or child_rectangles_in_parent is not None
bounds = tuple(bounds)
if not is_rectangle(bounds) and (fine_block is None or base_block is None):
raise ValueError("several patches require fine_block and base_block")
fine_objects, jets = tuple(fine_objects), tuple(jets)
child_objects, child_jets = tuple(child_objects), tuple(child_jets)
if not nested and (child_objects or child_jets):
raise ValueError("child_objects/child_jets require a nested child")
if base_block is not None and fine_block is None:
raise ValueError("base_block requires fine_block")
refinements, blocks = [bounds], [base_block, fine_block]
objects, level_jets = [(), fine_objects], [(), jets]
if nested:
if child is not None and not is_rectangle(bounds):
raise ValueError("scalar child requires one parent patch; use child_rectangles_in_parent")
if fine_block is None or base_block is None or child_block is None:
raise ValueError("a nested child needs fine_block, base_block and child_block")
if fine_objects or jets:
raise ValueError("a nested child supports bodies/Jets only on L2; use child_objects/child_jets")
refinements.append(tuple(child) if child is not None else tuple(child_rectangles_in_parent))
blocks.append(child_block)
objects.append(child_objects)
level_jets.append(child_jets)
return refinements, blocks, objects, level_jets
def _initial_levels(level_g, coarse_g, fine_g, child_g):
"""One tuple of per-level arrays from initialize()'s positional or legacy named form."""
if coarse_g is None and fine_g is None:
if child_g is not None and len(level_g) != 2:
raise TypeError("child_g needs exactly the coarse and fine arrays before it")
return tuple(level_g) + (() if child_g is None else (child_g,))
if level_g:
raise TypeError("pass level arrays positionally or as coarse_g/fine_g/child_g, not both")
if coarse_g is None or fine_g is None:
raise TypeError("coarse_g and fine_g are both required in the named form")
return (coarse_g, fine_g) + (() if child_g is None else (child_g,))
def _check_levels(refinements, blocks, objects, jets):
"""Candidate limits shared by the list and the legacy entry points."""
"""Candidate limits of the level lists, checked before any device work."""
depth = len(refinements) + 1
if depth < 2:
raise ValueError("at least one refinement level is required")
@@ -117,13 +75,13 @@ def _check_levels(refinements, blocks, objects, jets):
raise ValueError(f"{name} needs one entry per level ({depth})")
for level, block in enumerate(blocks):
if block is not None and len(block) != 2:
raise ValueError(f"{_level_name(level)}_block must be (by, bx)")
raise ValueError(f"level_blocks[{level}] must be (by, bx)")
if objects[0] or jets[0]:
raise ValueError("base-level bodies/Jets are not supported")
if any(blocks[level - 1] is not None and blocks[level] is None for level in range(1, depth)):
raise ValueError("a blocked level requires blocked refined levels below it")
if not is_rectangle(refinements[0]) and (blocks[0] is None or blocks[1] is None):
raise ValueError("several patches require fine_block and base_block")
raise ValueError("several L1 patches require level_blocks[0] and level_blocks[1]")
if depth > 2:
if any(block is None for block in blocks):
raise ValueError("three or more levels must all be blocked")
@@ -132,7 +90,14 @@ def _check_levels(refinements, blocks, objects, jets):
class FixedPatchStepper:
"""D2Q9/SRT/FP32, one unforced internal 2:1 patch in an x-periodic box.
"""D2Q9 SRT/MRT FP32 fixed 2:1 refinement hierarchy, built from level lists.
``refinements[l]`` gives level l+1 in level-l integer cells: one rectangle
(x0, y0, x1, y1) (FixedPatch2D, a fine window with its own origin) or a
sequence of rectangles (FixedPatchSet2D, a dependency-validated union on one
level-wide grid, public fine arrays (2*ny, 2*nx), NaN outside ACTIVE cells);
see lbm.hierarchy. ``level_blocks``, ``level_objects`` and ``level_jets``
hold one entry per level, L0 included (L0 bodies/Jets are not supported).
``coarse_boundary`` is ``periodic`` (default) or ``slot_reservoir``:
a bottom on-site slot and top fixed-density reservoir from ``cfg``.
@@ -143,111 +108,91 @@ class FixedPatchStepper:
actual channel closure footprint. Channel remapping is not supported.
Periodic mode does not apply the wall/slot boundary fields in ``cfg``.
Outer walls remain coarse; fine halo donors must be ordinary fluid.
``fine_objects`` accepts fixed circles in coarse physical coordinates;
velocities are in coarse lattice units (dx=dt=1). Independent local copies
are projected at fine cell centers. Their complete stencil must be active
and disjoint from the actual two-hop transfer footprint.
These use the edge/cell-center frame (coarse centers I+.5), whereas ordinary Simulation objects use the integer-node frame.
``initialize(coarse_g, fine_g)`` accepts physical Q-major (9,ny,nx) arrays
already in postcollision phase. It does not collide or build channel flags.
Every ``step()`` publishes only after both levels complete on one stream.
On a device/launch failure the instance becomes unusable: close and recreate
it, rather than pretending the partially advanced fine buffer rolled back.
Bodies are fixed circles in root (L0) physical coordinates; velocities are
in root lattice units (dx=dt=1). Independent local copies are projected at
fine cell centers; their complete stencil must be active and disjoint from
the actual two-hop transfer footprint. These use the edge/cell-center frame
(coarse centers I+.5), whereas ordinary Simulation objects use the
integer-node frame. Jets (body.jets.Jet) use the same frame and drive cut
links selected at their true hits; ``set_jet_amplitude(index, amplitude,
level=l)`` re-uploads the per-link velocity column only.
``initialize(*level_g)`` accepts one physical Q-major (9, ny, nx) array per
level, already in postcollision phase. It does not collide or build channel
flags. Every ``step()`` publishes only after all levels complete on one
stream. On a device/launch failure the instance becomes unusable: close and
recreate it, rather than pretending a partially advanced buffer rolled back.
A ``level_blocks`` entry (by, bx) stores that level in blocks.cu storage:
the ENTIRE level shape, including the four-cell patch ghost band, is
partitioned by a non-periodic BlockLayout2D with one-cell same-level halos.
Patch kinds stay per cell (OUTER invalid, INNER stream only, ACTIVE
collide); halos are gathered before each hop. Public arrays keep the dense
shapes; only the allocation differs. A blocked level requires blocked
refined levels below it; several L1 rectangles and depth >= 3 require all
levels blocked. Blocked bodies are stationary circles, optionally
surface-actuated: prepare_fine_boundary decides legality on the dense grid,
then cut links are staged receiver-local per hop: halo -> BFL -> step, same
buffer. A blocked parent gathers halos before receiver-local coalescence
staging and pull/collision; covered cells are poisoned on every step.
``fine_block=(by, bx)`` (opt-in) stores the fine level in
blocks.cu storage: the ENTIRE fine_shape, including the four-cell patch
ghost band, is partitioned by a non-periodic BlockLayout2D with one-cell
same-level halos. Patch kinds stay per cell (OUTER invalid, INNER stream
only, ACTIVE collide); halos are gathered before each fine hop. Public
arrays keep the dense (9, ny, nx) fine shape; only the allocation differs.
Blocked fine_objects are stationary circles, optionally surface-actuated:
prepare_fine_boundary decides legality on the dense fine grid, then cut
links are staged receiver-local per hop: halo -> BFL -> step, same buffer.
``base_block=(by, bx)`` also blocks the parent; it requires ``fine_block``.
Parent halos precede receiver-local coalescence staging and pull/collision;
covered cells are explicitly poisoned on every step. Public shapes stay dense.
``observe_raw_exchange=True`` records blocked physical cut-link exchange
without changing populations. read_raw_exchange reports the last complete
base interval or last substep in base-lattice units per unit depth. This
is boundary momentum reaction, not a validated nozzle/stress load. Dense
body layouts are not supported by this new diagnostic in this candidate.
body levels are not supported by this diagnostic.
``observe_window_exchange=True`` (requires observe_raw_exchange) adds a second
per-link FP64 ledger accumulated by the same kernel between
start_exchange_window() and read_exchange_window(); disabled by default.
``jets`` (body.jets.Jet) use the same edge frame as ``fine_objects`` and
drive fine cut links selected at their true hits; ``set_jet_amplitude``
re-uploads the per-link velocity column only.
Several patches: pass ``bounds`` as a sequence of (x0, y0, x1, y1)
rectangles (FixedPatchSet2D, dependency-validated union). This requires
fine_block and base_block; fine_objects/jets are projected once onto the
level-wide fine grid (each circle inside the union, body ids = object
positions, jet and writer checks level-wide), and
uses one level-wide fine grid (2*ny, 2*nx): public fine arrays have that
shape, NaN outside the patches' ACTIVE cells. The step sequence is the
blocked one above, with unique union transfers in one launch each.
Nested levels: a child set's coordinates index the allocated parent array,
including ghost bands and holes: root edge = parent fine_origin + index / 2
(zero origin for a parent set; a scalar parent keeps its shifted window
origin). A scalar child requires a scalar parent. Rectangle unions impose no
fixed gap rule: adjacent, overlapping and concave unions are accepted when
their actual transfer dependencies close (FixedPatchSet2D /
nest_patch_set). All regions share one buffer pair per level and the fixed
schedule of 2**l hops per base step at level l. Bodies/Jets are supported only on the
finest level of a nested hierarchy (L2 dx=dt=.25 in root units, unchanged
lattice velocity); every whole circle and its BFL stencil must fit strictly
away from that level's transfer footprint.
Three-level separated unions: ``child_rectangles_in_parent=[...]`` is
mutually exclusive with scalar ``child`` and accepts either parent form.
Coordinates index the allocated L1 array, including ghost bands and holes:
root edge = patch.fine_origin + L1 index / 2. A parent set has origin zero;
a scalar parent retains its shifted window origin. The child set's public
extent is twice the allocated L1 shape, even though storage is sparse.
Each pair requires gap >= 4 in its own parent-cell units. All regions share
one buffer pair per level and the fixed 1:2:4 schedule; L2-only bodies/Jets
below apply unchanged, with object IDs assigned over the whole level.
``explosion="projected_linear"`` selects experimental transverse linear
reconstruction on each adjacent pair. Default "constant" is unchanged.
Projected mode requires periodic root, all-blocked SRT levels without
bodies/Jets or LES; this backend supplies no forcing. Geometry is generic,
but union/multilevel GPU and matched-physics qualification remain pending.
Three-level single chain: ``child`` bounds use L1 window cells; all three
levels must be blocked. ``child_objects`` and ``child_jets`` use the L0
edge frame, with L2 dx=dt=.25 and unchanged lattice velocity. L1 bodies
and Jets remain unsupported in a chain. Every whole circle and its BFL
stencil must fit strictly away from the L2 transfer footprint. L2 runs
halo -> BFL -> step four times per base step. Runtime child Jet changes
require ``set_jet_amplitude(index, amplitude, level=2)``.
Level lists (any depth): ``refinements[l]`` gives level l+1 in level-l
integer cells (scalar window or rectangle list, see lbm.hierarchy);
``level_blocks``/``level_objects``/``level_jets`` hold one entry per level,
L0 included. They are mutually exclusive with the legacy keywords above,
which are normalised to the same lists. One recursive hop advances every
level: a child explodes from its parent's current hop source, takes two
hops, then the parent gathers halos, stages restriction, applies BFL and
steps. Depth >= 3 must be fully blocked with bodies/Jets on the finest level.
One recursive hop advances every level: a child explodes from its parent's
current hop source, takes two hops, then the parent gathers halos, stages
restriction, applies BFL and steps.
"""
def __init__(self, cfg, bounds=None, *, context, coarse_boundary="periodic", fine_objects=(),
fine_block=None, base_block=None, jets=(), child=None, child_block=None,
child_objects=(), child_jets=(), child_rectangles_in_parent=None,
refinements=None, level_blocks=None, level_objects=None, level_jets=None,
observe_raw_exchange=False, observe_window_exchange=False):
def __init__(self, cfg, *, context, refinements, coarse_boundary="periodic",
level_blocks=None, level_objects=None, level_jets=None,
observe_raw_exchange=False, observe_window_exchange=False, explosion="constant"):
if HALO != 4:
raise RuntimeError("refinement.cu requires a four-cell fine halo")
if coarse_boundary not in ("periodic", "slot_reservoir", "channel"):
raise ValueError("coarse_boundary must be periodic, slot_reservoir or channel")
if refinements is None:
if bounds is None:
raise ValueError("bounds or refinements is required")
if level_blocks is not None or level_objects is not None or level_jets is not None:
raise ValueError("level_blocks/level_objects/level_jets require refinements")
refinements, level_blocks, level_objects, level_jets = _legacy_levels(
bounds, fine_block=fine_block, base_block=base_block, child=child,
child_block=child_block, child_rectangles_in_parent=child_rectangles_in_parent,
fine_objects=fine_objects, jets=jets, child_objects=child_objects,
child_jets=child_jets)
else:
if (bounds is not None or child is not None or child_rectangles_in_parent is not None
or fine_block is not None or base_block is not None or child_block is not None
or tuple(fine_objects) or tuple(jets) or tuple(child_objects) or tuple(child_jets)):
raise ValueError("refinements and the legacy patch keywords are mutually exclusive")
depth = len(refinements) + 1
level_blocks = [None] * depth if level_blocks is None else list(level_blocks)
level_objects = [()] * depth if level_objects is None else list(level_objects)
level_jets = [()] * depth if level_jets is None else list(level_jets)
depth = len(refinements) + 1
level_blocks = [None] * depth if level_blocks is None else list(level_blocks)
level_objects = [()] * depth if level_objects is None else list(level_objects)
level_jets = [()] * depth if level_jets is None else list(level_jets)
level_objects = [tuple(o) for o in level_objects]
level_jets = [tuple(j) for j in level_jets]
level_blocks = [None if b is None else tuple(b) for b in level_blocks]
_check_levels(refinements, level_blocks, level_objects, level_jets)
depth = len(refinements) + 1
if explosion not in ("constant", "projected_linear"):
raise ValueError("explosion must be constant or projected_linear")
if explosion == "projected_linear" and (
coarse_boundary != "periodic" or any(b is None for b in level_blocks)
or any(level_objects) or any(level_jets)
or cfg.collision != "SRT" or cfg.les_enabled):
raise ValueError("projected explosion requires periodic all-blocked SRT levels "
"without bodies/Jets or LES")
self._explosion = explosion
self._ddf_shifting = bool(cfg.ddf_shifting)
if self._ddf_shifting and any(b is None for b in level_blocks):
raise ValueError("shifted populations require all-blocked levels; dense/mixed is unsupported")
@@ -479,6 +424,11 @@ class FixedPatchStepper:
self._upload(children), len(ghosts), len(targets),
int(np.prod(pair.coarse_shape if parent.layout is None
else parent.layout.local_shape)))
if self._explosion == "projected_linear":
neighbors, offsets = projected_explosion_tables(
pair, parent.layout, self.hierarchy.kinds[index])
result.explode = child.module.get_function("BlockExplodeProjected")
result.neighbors, result.offsets = self._upload(neighbors), self._upload(offsets)
if child.layout is not None:
child.kind = self._upload(blocked_kind(child.layout, self.hierarchy.kinds[index + 1]))
if index == 0 and base is not None:
@@ -518,13 +468,13 @@ class FixedPatchStepper:
if self._ddf_shifting and any(layout is None for layout in self._layouts):
raise ValueError("shifted populations require all-blocked levels")
def initialize(self, *level_g, coarse_g=None, fine_g=None, child_g=None):
def initialize(self, *level_g):
"""Upload physical postcollision G, encoding before any FP32 rounding.
Shifted input should be physical FP64 to retain small perturbations.
Public initialization resets the step count; non-leaves are discarded.
"""
given = _initial_levels(level_g, coarse_g, fine_g, child_g)
given = tuple(level_g)
with self._lock, self.ctx.activate():
self._require("new", "ready")
self._check_storage()
@@ -648,12 +598,11 @@ class FixedPatchStepper:
old, new, source, base_count=count, level_steps=(count, 2*count, 4*count),
phase="postcollision_g", **options)
candidate = type(self)(
cfg, pairs[0].bounds, context=self.ctx, base_block=base_block,
fine_block=fine_block, child_block=child_block,
child_rectangles_in_parent=new.child.bounds,
child_objects=child_objects, child_jets=jets,
cfg, context=self.ctx, refinements=[pairs[0].bounds, new.child.bounds],
level_blocks=[base_block, fine_block, child_block],
level_objects=[(), (), child_objects], level_jets=[(), (), jets],
observe_raw_exchange=self._observe_raw_exchange,
observe_window_exchange=self._observe_window)
observe_window_exchange=self._observe_window, explosion=self._explosion)
try:
if self._ddf_shifting:
candidate._initialize_raw(_StoredPopulations(transferred.g, transferred.shifted))
@@ -746,6 +695,7 @@ class FixedPatchStepper:
pair, level = self._pairs[index - 1], self._levels[index]
pair.explode(parent_buffer, level.current, pair.ghosts, pair.donors, np.uint32(pair.n_ghosts),
np.uint64(pair.parent_cells),
*((pair.neighbors, pair.offsets) if pair.neighbors is not None else ()),
grid=((pair.n_ghosts + self._block[0] - 1) // self._block[0], 1), **kw)
self._hop(index, level.current, level.spare, **kw)
self._hop(index, level.spare, level.current, **kw)
@@ -799,27 +749,41 @@ class FixedPatchStepper:
grid=((pairs + self._block[0] - 1) // self._block[0], 1), **kw)
def step(self, n=1):
"""Advance G→G by n base intervals: level l takes 2**l hops per interval."""
"""Advance G→G by n base intervals: level l takes 2**l hops per interval.
All n intervals are enqueued in order on the one stream, and the host waits
once, before returning; step(0) launches and waits for nothing. On return
the device work is complete, step_count and an open window cover all n
intervals, and the raw-exchange ledger holds the final interval only.
Asynchronous device errors surface at that single wait, so they are not
attributed to the interval that caused them; call step(1) repeatedly to
localize one (same launches, same bits). On any failure the instance is
failed, the exchange ledger and window are invalid, and step_count keeps
its value from entry to the failing call.
"""
if isinstance(n, bool) or not isinstance(n, Integral) or n < 0:
raise ValueError("n must be a nonnegative integer")
with self._lock, self.ctx.activate():
self._require("ready")
if n == 0:
return
root = self._levels[0]
kw = dict(block=self._block, stream=self._stream)
try:
self._status = "advancing"
self._exchange_valid = False
for _ in range(n):
if self._observe_raw_exchange:
self._exchange_valid = False
if self._observe_raw_exchange: # stream-ordered: holds the last interval only
for b in self._level_boundaries:
if b is not None:
cuda.memset_d8_async(b.interval_integral, 0,
len(b.tables["cell"]) * 32, self._stream)
self._hop(0, root.current, root.spare, **kw)
self._stream.synchronize()
root.current, root.spare = root.spare, root.current
self._step_count += 1
self._exchange_valid = self._observe_raw_exchange
root.current, root.spare = root.spare, root.current # host handles only
self._stream.synchronize()
self._step_count += n
self._exchange_valid = self._observe_raw_exchange
self._status = "ready"
except BaseException:
self._window_valid = False
+50 -4
View File
@@ -8,7 +8,7 @@ from dataclasses import dataclass, replace
import numpy as np
from .blocks import blocked_link_tables
from ..body.jets import jet_link_shapes, surface_link_velocity
from ..body.jets import _surface_links
from .descriptors import D2Q9_EX, D2Q9_EY
from .refinement import ACTIVE, OUTER_GHOST
@@ -66,6 +66,50 @@ def blocked_base_tables(patch, layout, order, wall_aware=False, *, composed_kind
blocked_kind(layout, dense_kind))
def projected_explosion_tables(pair, parent_layout, composed_parent_kind):
"""Experimental transverse linear explosion, in the pair's existing row order.
Schornbaum & Rüde (2016), arXiv:1508.07982, Algorithm 2, following
Chen et al., doi:10.1016/j.physa.2005.09.036. Independently implemented
from the mathematics: centered gradients, perpendicular projection and
child offsets +/-1/4. The kernel applies the projection per population.
Only original explosion donors that are owned, uncovered ACTIVE cells
may supply gradients. Both axis neighbors must be legal; otherwise repeat
the center twice for zero slope. Owner-core addresses avoid stale halos.
The same rule applies to scalar windows, unions and every adjacent pair;
nested layouts retain their own per-axis (usually nonperiodic) topology.
"""
ny, nx = pair.coarse_shape
kind = np.asarray(composed_parent_kind)
if parent_layout.shape != pair.coarse_shape or kind.shape != pair.coarse_shape:
raise ValueError("projected explosion parent layout/kind has the wrong shape")
donor = pair.ghost_coarse.astype(np.intp)
legal = np.zeros(ny * nx, bool)
legal[donor] = True
legal &= (parent_layout.owned.ravel() & ~pair.covered.ravel()
& (kind.ravel() == ACTIVE))
if not legal[donor].all():
raise ValueError("projected explosion donors need owned uncovered parent ACTIVE cells")
y, x = np.divmod(donor, nx)
neighbors = np.repeat(donor[:, None], 4, axis=1)
for axis, (dx, dy) in enumerate(((1, 0), (0, 1))):
minus = ((y - dy) % ny) * nx + (x - dx) % nx
plus = ((y + dy) % ny) * nx + (x + dx) % nx
valid = legal[minus] & legal[plus]
if not parent_layout.periodic[axis]:
coordinate, extent = (x, nx) if axis == 0 else (y, ny)
valid &= (coordinate > 0) & (coordinate < extent - 1)
neighbors[valid, 2 * axis] = minus[valid]
neighbors[valid, 2 * axis + 1] = plus[valid]
fy, fx = np.divmod(pair.ghost_fine, pair.fine_shape[1])
ox, oy = pair.fine_origin
offsets = np.column_stack((ox + (fx + .5) / 2 - (x + .5),
oy + (fy + .5) / 2 - (y + .5)))
return (np.ascontiguousarray(parent_layout.owner.ravel()[neighbors], dtype=np.uint64),
np.ascontiguousarray(offsets, dtype=np.float32))
# Required device columns plus optional actuation; observation arms are uploaded
# separately only when enabled. body_id/aperture remain host reduction metadata.
BLOCKED_BOUNDARY_DEVICE_COLUMNS = ("block", "cell", "dir", "q", "fallback", "surface_velocity")
@@ -98,11 +142,13 @@ def _prepare_blocked_boundary(boundary, layout, cfg, jets, *, _shifted_blocked=F
tables.update(body_id=np.asarray(body_id, np.int32), rx=np.asarray(rx, np.float32),
ry=np.asarray(ry, np.float32), aperture=np.zeros(len(dirs), bool))
actuated = bool(jets) or any(o.surface_actuation is not None for o in boundary.objects)
jet_cache = None
if actuated:
cfg = replace(cfg)
cfg.validate()
tables["surface_velocity"], tables["aperture"] = surface_link_velocity(
tables["surface_velocity"], tables["aperture"], shape, jet_id = _surface_links(
boundary.objects, cfg, boundary.flags, fluid_idx, dirs, body_id, rx, ry,
jets=jets, hits=boundary.curved_hits, _shifted_blocked=_shifted_blocked)
return _BlockedBoundary(boundary, tables, jets, actuated,
jet_link_shapes(jets, boundary.curved_hits) if jets else None)
if jets:
jet_cache = (shape, jet_id)
return _BlockedBoundary(boundary, tables, jets, actuated, jet_cache)
+17 -8
View File
@@ -336,13 +336,19 @@ class Simulation:
def read_surface_exchange(self, id: int):
"""Latest step's wall/aperture (Fx,Fy,Tz) exchange, not total nozzle force.
Supports SurfaceActuation and Jet-driven bodies, including zero-amplitude
apertures. Passive bodies without an aperture are rejected.
Unlike read_body this is not accumulated/time-averaged. It resets after
geometry sync or checkpoint load; advance before interpreting it.
"""
if self.bodies.get(id).surface_actuation is None:
obj = self.bodies.get(id)
curved = self.field.curved
has_aperture = (curved.aperture is not None
and np.any(curved.aperture & (curved.body_id == id)))
if obj.surface_actuation is None and not has_aperture:
raise ValueError("Body has no surface actuation")
self.stream.synchronize()
return self.field.curved.surface_exchange(id)
return curved.surface_exchange(id)
@context_bound
def read_body(self, id: int, *,
@@ -451,18 +457,21 @@ class Simulation:
@context_bound
def initialize(self):
"""Initialize flow field and sync objects to GPU."""
# Recompile if objects were added after construction.
self._assert_allocation_contract()
# Validate the complete geometry before flags, populations or modules
# change. Compact-list construction publishes no outputs on failure.
next_flags = self.bodies.build_flags(self.field.build_channel_flags())
if self.bodies.jets and self.bodies.count == 0:
raise ValueError("Jets need bodies with cut links")
self.bodies.build_compact_lists_for(self.bodies.objects, next_flags)
# Recompile if objects were added after construction.
if self._read_generated_n_objects() != self.bodies.count:
self.recompile()
self.field.flag = self.field.build_channel_flags()
if self.bodies.count > 0:
self.field.flag = self.bodies.build_flags(self.field.flag)
self.field.flag = next_flags
self.field.upload_flags()
if self.bodies.jets and self.bodies.count == 0:
raise ValueError("Jets need bodies with cut links")
self.stepper.initialize()
if self.bodies.count > 0:
self.bodies.sync_to_gpu(self.field, rebuild_flags=False)
+104
View File
@@ -0,0 +1,104 @@
"""Host contract of PeriodicBlockStepper.step(n): one stream wait per call (mocked driver)."""
import ast
from contextlib import nullcontext
import importlib.util
from pathlib import Path
import types
from unittest.mock import Mock
import unittest
import numpy as np
from CelerisLab.config import LBMConfig
from CelerisLab.lbm.blocks import BlockLayout2D
def host_module():
"""block_stepper with pycuda/compiler replaced by mocks; no GPU context."""
# Locate the source without importing it: importing block_stepper loads pycuda.driver,
# which CPU-only import-boundary tests (test_build_contracts) must never see.
path = Path(importlib.util.find_spec("CelerisLab.lbm.block_stepper").origin)
tree = ast.parse(path.read_text())
tree.body = [node for node in tree.body if not (
isinstance(node, ast.Import) and any(a.name == "pycuda.driver" for a in node.names)
or isinstance(node, ast.ImportFrom) and node.module == "cuda")]
module = types.ModuleType("CelerisLab.lbm._test_host_block_stepper")
module.__package__ = "CelerisLab.lbm"
module.__dict__.update(cuda=Mock(), compiler=Mock())
exec(compile(tree, str(path), "exec"), module.__dict__)
return module
def backend():
host, log = host_module(), []
host.cuda.mem_get_info.return_value = (1 << 40, 1 << 40)
host.cuda.mem_alloc.side_effect = lambda size: Mock(size=size) # distinct buffers
module = Mock()
module.get_global.return_value = (Mock(), 20)
module.get_function.side_effect = lambda name: Mock(
side_effect=lambda *a, **k: log.append((name, a[:2])))
host.compiler.load_module.return_value = module
cfg = LBMConfig(nx=16, ny=16, viscosity=.1)
run = host.PeriodicBlockStepper(cfg, BlockLayout2D.build(16, 16, 8, 8),
context=Mock(activate=nullcontext, sm_arch="sm_70"))
run._stream.synchronize.side_effect = lambda: log.append(("sync", ()))
run.initialize(np.full((9, 16, 16), 1 / 9))
log.clear()
return run, log
class BlockStepSync(unittest.TestCase):
def test_step_n_waits_once_and_matches_n_single_steps(self):
many, log_many = backend()
many.step(3)
single, log_single = backend()
for _ in range(3):
single.step(1)
names = [name for name, _ in log_many]
self.assertEqual(names.count("sync"), 1)
self.assertEqual(names[-1], "sync")
self.assertEqual(names.count("BlockStep"), 3)
# Same launch order and buffer roles as three step(1) calls.
strip = lambda log: [(n, tuple(id(x) for x in a)) for n, a in log if n != "sync"]
roles = lambda run, log: [(n, tuple({id(run._current): "c", id(run._spare): "s"}.get(x, "-")
for x in ids)) for n, ids in strip(log)]
self.assertEqual([n for n, _ in strip(log_many)], [n for n, _ in strip(log_single)])
self.assertEqual(roles(many, log_many), roles(single, log_single))
self.assertIsNot(many._current, many._spare)
self.assertEqual((many.step_count, single.step_count), (3, 3))
def test_step_zero_launches_and_waits_for_nothing(self):
run, log = backend()
run.step(0)
self.assertEqual((log, run.step_count), ([], 0))
def test_failure_keeps_entry_step_count(self):
run, log = backend()
run.step(1)
run._stream.synchronize.side_effect = RuntimeError("device fault")
with self.assertRaises(RuntimeError):
run.step(2)
self.assertEqual((run.step_count, run._status), (1, "failed"))
def test_launch_failure_mid_batch_fails_closed_without_waiting(self):
run, log = backend()
calls = []
step = run._step
def failing(*args, **kwargs):
calls.append(1)
if len(calls) == 2:
raise RuntimeError("launch failure")
return step(*args, **kwargs)
run._step = failing
with self.assertRaises(RuntimeError):
run.step(3)
self.assertNotIn("sync", [name for name, _ in log])
self.assertEqual((run.step_count, run._status), (0, "failed"))
with self.assertRaises(RuntimeError):
run.download()
if __name__ == "__main__":
unittest.main()
+2 -2
View File
@@ -80,8 +80,8 @@ def test_evolved_ghost_snapshot_and_physical_download():
host.cuda.memcpy_dtoh.side_effect = lambda a, ptr: np.copyto(a, storage[id(ptr)])
context = Mock(activate=nullcontext, sm_arch="sm_70")
cfg = LBMConfig(nx=24, ny=20, viscosity=.1, velocity=.025)
backend = host.FixedPatchStepper(cfg, (6, 6, 18, 14), context=context,
coarse_boundary="channel", base_block=(4, 6), fine_block=(4, 4))
backend = host.FixedPatchStepper(cfg, context=context, coarse_boundary="channel",
refinements=[(6, 6, 18, 14)], level_blocks=[(4, 6), (4, 4)])
try:
weights = np.array([4/9]+[1/9]*4+[1/36]*4)[:, None, None]
arrays = [np.broadcast_to(weights, level.shape).copy() for level in backend._levels]
+79
View File
@@ -0,0 +1,79 @@
"""CPU-only contract tests for run_dfg_re20. Not CUDA or DFG acceptance evidence."""
import sys
from pathlib import Path
import unittest
sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "validation"))
import run_dfg_re20 as v # noqa: E402
import run_refined_dfg as rr # noqa: E402
h, _ = rr.helpers(rr.DEFAULT_SOURCE)
def rows(values, tstar_end=v.TSTAR_MAX):
n = int(round(tstar_end / v.SAMPLE_TSTAR))
return [dict(tstar=(i + 1) * v.SAMPLE_TSTAR, **values(i)) for i in range(n)]
class Re20Contract(unittest.TestCase):
def test_lattice_parameters_and_bounds(self):
root, uniform = v.lattice_parameters(40), v.lattice_parameters(80)
self.assertAlmostEqual(root["tau"], 0.56, places=12)
self.assertAlmostEqual(uniform["tau"], 0.62, places=12)
self.assertEqual((root["steps"], root["interval"]), (240000, 2000))
self.assertEqual((uniform["steps"], uniform["interval"]), (480000, 4000))
self.assertAlmostEqual(v.plan()["refined_fine_tau"], 0.62, places=12)
def test_config_only_changes_viscosity(self):
base = v._re100_config(h, 40, "SRT", "none")
cfg, body, p = v.config(h, 40, "SRT")
self.assertAlmostEqual(cfg["physics"]["viscosity"], 0.01 * 40 / 20, places=15)
self.assertEqual((p["re"], p["viscosity"]), (20.0, cfg["physics"]["viscosity"]))
base[0]["physics"]["viscosity"] = cfg["physics"]["viscosity"]
self.assertEqual(base[0], cfg)
self.assertEqual(base[1], body)
with self.assertRaisesRegex(ValueError, "no Jets"):
v.config(h, 40, "MRT", "zero")
def test_units(self):
s = v.sample([2.0, -0.5], 4, 40, 3.0)
den = rr.SPEED**2 * 40 / 2
self.assertAlmostEqual(s["cd"], 2.0 / 4 / den)
self.assertAlmostEqual(s["cl"], -0.5 / 4 / den)
self.assertAlmostEqual(s["p_diff"], 3.0 * 0.04)
self.assertEqual(s["dp_scaled"], 3.0)
def test_steady_and_verdict(self):
inside = dict(cd=5.58, cl=0.0106, p_diff=0.1174)
out = v.summarize(rows(lambda i: inside))
self.assertEqual((out["status"], out["steady"], out["window_samples"]),
("WITHIN_INTERVALS", True, 21))
self.assertTrue(out["cd_positive"])
self.assertAlmostEqual(out["edge_distance"]["cl"], 0.0002)
self.assertTrue(all(out["verdict"].values()))
low = v.summarize(rows(lambda i: dict(inside, cl=0.0100)))
self.assertEqual(low["status"], "OUTSIDE_INTERVALS")
self.assertFalse(low["verdict"]["cl"])
def test_slow_drift_gives_no_verdict(self):
# Range 2e-5 passes (limit 6e-5); slope * window 2e-5 exceeds 1.2e-5.
out = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106 + 1e-6 * i, p_diff=0.1174)))
self.assertEqual((out["status"], out["verdict"]), ("NOT_STEADY", None))
self.assertLessEqual(out["ranges"]["cl"], out["range_limits"]["cl"])
self.assertGreater(out["drifts"]["cl"], out["slope_limits"]["cl"])
def test_noise_range(self):
quiet = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106 + 2e-5 * (i % 2), p_diff=0.1174)))
self.assertTrue(quiet["steady"]) # within the range limit, no trend
noisy = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106 + 1e-4 * (i % 2), p_diff=0.1174)))
self.assertEqual(noisy["status"], "NOT_STEADY")
self.assertGreater(noisy["ranges"]["cl"], noisy["range_limits"]["cl"])
def test_incomplete_run_gives_no_verdict(self):
out = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106, p_diff=0.1174), tstar_end=30))
self.assertEqual((out["status"], out["verdict"]), ("INCOMPLETE", None))
if __name__ == "__main__":
unittest.main()
+34
View File
@@ -16,6 +16,7 @@ from run_jet_circle_cv import (
case,
state,
cv,
cv_from_macros,
aperture_probe,
measured_aperture_flux,
verify,
@@ -28,6 +29,39 @@ def eq(rho, u, v):
class Host(unittest.TestCase):
def test_public_macros_pressure_advection_and_cropped_frames(self):
for h, origin, shape, rect in (
(.5, (0., 0.), (48, 64), (5., 4., 25., 20.)),
(.5, (.25, .5), (48, 64), (5.25, 4., 25.25, 20.)),
(.25, (.375, .75), (96, 128), (5.125, 4., 25.125, 20.)),
):
y, x = np.indices(shape)
x = origin[0] + h * (x + .5)
k, u, v = 1e-5, .02, -.01
rho = 1 + 3 * k * x # p=(rho-1)/3=k*x
ux, uy, fluid = np.full(shape, u), np.full(shape, v), np.ones(shape, bool)
result = cv_from_macros(rho, ux, uy, fluid, origin, rect, .004, h)
expected = 320 * np.array([3*k*u, k + 3*k*u*u, 3*k*u*v])
np.testing.assert_allclose(result[1], expected, rtol=1e-11, atol=1e-13)
np.testing.assert_allclose(result, cv(eq(rho, u, v), fluid, origin, rect, .004, h), atol=1e-12)
x0, y0, x1, y1 = np.rint((np.array(rect)-np.tile(origin, 2))/h).astype(int)
selection = np.s_[y0-2:y1+2, x0-2:x1+2]
cropped_origin = np.asarray(origin) + h*np.array([x0-2, y0-2])
cropped = cv_from_macros(rho[selection], ux[selection], uy[selection],
fluid[selection], cropped_origin, rect, .004, h)
np.testing.assert_array_equal(cropped, result)
def test_public_macros_full_normal_viscous_stress(self):
y, x = np.indices((48, 64))
x = (x + .5) * .5
rho, ux, uy, fluid = np.ones_like(x), 1e-4*x*x, np.zeros_like(x), np.ones(x.shape, bool)
args = (rho, ux, uy, fluid, (0., 0.), (5., 4., 25., 20.))
_, viscous = cv_from_macros(*args, .004)
_, inviscid = cv_from_macros(*args, 0.)
np.testing.assert_allclose(viscous-inviscid, [0, -4*.004*1e-4*320, 0], atol=1e-13)
with self.assertRaisesRegex(ValueError, "matching 2D"):
cv_from_macros(rho, ux, uy[:-1], fluid, (0, 0), (5, 4, 25, 20), .004)
def test_descriptor_and_uniform_closed_flux(self):
from CelerisLab.lbm.descriptors import D2Q9_EX, D2Q9_EY
+49
View File
@@ -188,6 +188,55 @@ def jet_case(device, jets):
return field, bodies
def test_public_surface_exchange_for_jet_preserves_aperture_at_zero_and_reverse(device):
from CelerisLab.simulation import Simulation
jet = Jet(Sector(CENTER, 0., .6, 3.), Radial(CENTER, inward=False), "quartic", 2e-3)
field, bodies = jet_case(device, [jet])
sim = SimpleNamespace(bodies=bodies, field=field, _initialized=True,
stream=SimpleNamespace(synchronize=device.synchronize))
cl = field.curved
assert bodies.get(0).surface_actuation is None
aperture, velocity = cl.aperture, cl.surface_velocity.copy()
assert aperture.any() and (~aperture).any()
# Synthetic per-link exchanges test readback/splitting, not kernel physics.
values = np.arange(cl.count * 3, dtype=np.float32).reshape(-1, 3)
device.htod(cl.link_exchange_gpu, values)
for amplitude in (2e-3, 0., -1e-3):
Simulation.set_jet_amplitude(sim, 0, amplitude)
result = Simulation.read_surface_exchange(sim, 0)
assert cl.aperture is aperture
np.testing.assert_array_equal(aperture, cl.jet_id >= 0)
np.testing.assert_allclose(cl.surface_velocity, velocity * (amplitude / 2e-3))
for name, mask in (("wall", ~aperture), ("aperture", aperture)):
np.testing.assert_array_equal(result[name], values[mask].sum(axis=0, dtype=np.float64))
def test_public_surface_exchange_keeps_legacy_and_passive_guards(device):
from CelerisLab.simulation import Simulation
field = make_field(device)
bodies = manager(field, [circle(SurfaceActuation(0., .6, .002), radius=2.)])
bodies.sync_to_gpu(field)
sim = SimpleNamespace(bodies=bodies, field=field,
stream=SimpleNamespace(synchronize=device.synchronize))
for value in Simulation.read_surface_exchange(sim, 0).values():
np.testing.assert_array_equal(value, 0.)
field.curved.free_gpu_columns()
with pytest.raises(RuntimeError, match="diagnostic is allocated"):
Simulation.read_surface_exchange(sim, 0)
# An exchange buffer elsewhere in the scene must not admit a passive body.
for jets in ([], [Jet(Sector(CENTER, 0., .6, 3.), Radial(CENTER))]):
field, bodies = jet_case(device, jets)
passive = bodies.add(circle(center=(2., 3.), radius=.6))
bodies.sync_to_gpu(field)
sim.bodies, sim.field = bodies, field
with pytest.raises(ValueError, match="Body has no surface actuation"):
Simulation.read_surface_exchange(sim, passive)
if not jets:
with pytest.raises(ValueError, match="Body has no surface actuation"):
Simulation.read_surface_exchange(sim, 0)
def test_manager_passes_true_hits_and_reuploads_only_velocity(device):
# CPU memory double only: checks host/device bookkeeping, not GPU numerics.
jet = Jet(Sector(CENTER, 0., .6, 3.), Radial(CENTER, inward=False), "quartic", 2e-3)
+39 -18
View File
@@ -43,12 +43,12 @@ class GuardTests(unittest.TestCase):
def test_current_corrected_pins(self):
self.assertEqual(
source_guard(ROOT, "corrected", "dev8403956")["base_commit"],
"8403956a9afc0b0bb89265cec374392013d89016",
source_guard(ROOT, "corrected", "a135252")["base_commit"],
"a135252ae78b47b57d7e77d19001700b3bedac8b",
)
def test_corrected_and_tamper_guard(self):
pins = json.loads((HERE / "data/les_flow/source_pins_dev8403956.json").read_text())
pins = json.loads((HERE / "data/les_flow/source_pins_a135252.json").read_text())
with TemporaryDirectory() as directory:
root = Path(directory)
for name in pins["sources"]:
@@ -59,24 +59,45 @@ class GuardTests(unittest.TestCase):
"run_uniform_les_flow.subprocess.check_output",
return_value="isolated-fixture\n",
):
source_guard(root, "corrected", "dev8403956")
source_guard(root, "corrected", "a135252")
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(root, "baseline", "dev8403956")
target = root / "src/CelerisLab/lbm/kernels/step/one_step_double.cu"
target.write_bytes(target.read_bytes() + b"\n// tamper\n")
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(root, "corrected", "dev8403956")
source_guard(root, "baseline", "a135252")
for name in ("kernels/step/one_step_double.cu", "kernels/blocks.cu",
"refinement_stepper.py", "refinement_tables.py"):
target = root / "src/CelerisLab/lbm" / name
original = target.read_bytes()
target.write_bytes(original + b"\n// tamper\n")
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(root, "corrected", "a135252")
target.write_bytes(original)
def test_historical_default_and_manifest_unchanged(self):
manifest = HERE / "data/les_flow/source_pins.json"
self.assertEqual(hashlib.sha256(manifest.read_bytes()).hexdigest(),
"87ca033619da1fc02bee822bfc5681b518a92a155c3c3d1dbbe5265c96066b39")
for variant in ("baseline", "corrected"):
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(ROOT, variant)
historical = {
"historical": ("source_pins.json", "87ca033619da1fc02bee822bfc5681b518a92a155c3c3d1dbbe5265c96066b39"),
"dev8403956": ("source_pins_dev8403956.json", "58187908485f2af7c78677d53de98015878372444265ce9e667683b8ef5d410f"),
}
for experiment, (name, expected) in historical.items():
manifest = HERE / "data/les_flow" / name
self.assertEqual(hashlib.sha256(manifest.read_bytes()).hexdigest(), expected)
for variant in ("baseline", "corrected"):
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(ROOT, variant, experiment)
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(ROOT, "corrected") # Omission still uses the historical profile.
def test_current_manifest_pins_actual_corrected_tree(self):
pins = json.loads((HERE / "data/les_flow/source_pins_a135252.json").read_text())
tracked = subprocess.check_output(["git", "-C", str(ROOT), "ls-files", "src"], text=True)
self.assertEqual(set(pins["sources"]), set(tracked.splitlines()))
for name, expected in pins["sources"].items():
self.assertEqual(hashlib.sha256((ROOT / name).read_bytes()).hexdigest(), expected)
self.assertEqual(pins["sources"][HEADER], pins["candidate_header_sha256"])
self.assertNotEqual(pins["sources"][HEADER], pins["baseline_header_sha256"])
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(ROOT, "baseline", "a135252")
def test_named_baseline_accepts_only_reversed_header(self):
pins = json.loads((HERE / "data/les_flow/source_pins_dev8403956.json").read_text())
pins = json.loads((HERE / "data/les_flow/source_pins_a135252.json").read_text())
with TemporaryDirectory() as directory:
root = Path(directory)
for name in pins["sources"]:
@@ -85,9 +106,9 @@ class GuardTests(unittest.TestCase):
shutil.copyfile(ROOT / name, dest)
subprocess.run(["git", "apply", "--reverse", str(HERE / "les/data/smagorinsky_normalization.patch")], cwd=root, check=True)
with patch("run_uniform_les_flow.subprocess.check_output", return_value="baseline-fixture\n"):
source_guard(root, "baseline", "dev8403956")
source_guard(root, "baseline", "a135252")
with self.assertRaisesRegex(RuntimeError, "Source pin mismatch"):
source_guard(root, "corrected", "dev8403956")
source_guard(root, "corrected", "a135252")
def test_gpu_requires_opt_in_before_import(self):
with TemporaryDirectory() as directory:
+394
View File
@@ -0,0 +1,394 @@
"""CPU stencil and actual closed-interface packet budgets; no CUDA claims."""
import numpy as np
import unittest
from pathlib import Path
from dataclasses import replace
import shutil
import subprocess
import tempfile
from CelerisLab.config import LBMConfig
from CelerisLab.lbm.blocks import BlockLayout2D
from CelerisLab.lbm.descriptors import D2Q9_EX, D2Q9_EY
from CelerisLab.lbm.refinement import FixedPatch2D, FixedPatchSet2D, ACTIVE, OUTER_GHOST
from CelerisLab.lbm.refinement_tables import projected_explosion_tables
from CelerisLab.lbm.hierarchy import build_hierarchy
from tests.unit.test_hierarchy import CFG, FOUR
E = np.array([D2Q9_EX, D2Q9_EY]).T
W = np.array([4/9] + [1/9]*4 + [1/36]*4)
def setup(union=False, bounds=(4, 4, 12, 12)):
cfg = LBMConfig(nx=16, ny=16, viscosity=.1)
p = (FixedPatchSet2D.from_config(cfg, [bounds]) if union else
FixedPatch2D.from_config(cfg, bounds))
layout = BlockLayout2D.build(16, 16, 4, 4, periodic=(True, True))
neighbors, offsets = projected_explosion_tables(p, layout, np.where(p.covered, OUTER_GHOST, ACTIVE))
inverse = np.full(layout.nblocks * np.prod(layout.local_shape), -1, dtype=int)
inverse[layout.owner.ravel()] = np.arange(256)
return p, inverse[neighbors], offsets
def reconstruct(c, p, neighbors, offsets, project=True):
# Independent NumPy evaluation of the documented stencil; neighbors have
# been decoded from actual blocked owner IDs, not recomputed geometry.
values = c.reshape(9, -1)[:, neighbors]
g = .5 * (values[:, :, 1::2] - values[:, :, ::2])
if project:
g[1:] -= (np.einsum('qra,qa->qr', g[1:], E[1:]) /
np.sum(E[1:]**2, axis=1)[:, None])[:, :, None] * E[1:, None, :]
out = c.reshape(9, -1)[:, p.ghost_coarse] + np.einsum('qra,ra->qr', g, offsets)
return out, g
def check_legal_footprint_mean_and_characteristic(union, bounds):
p, neighbors, offsets = setup(union, bounds)
assert set(neighbors.ravel()) <= set(p.ghost_coarse)
assert not p.covered.ravel()[neighbors].any()
assert (neighbors >= 0).all()
c = np.random.default_rng(72).normal(size=(9,16,16))
c[:, p.covered] = np.nan # poison every forbidden donor
out, g = reconstruct(c, p, neighbors, offsets)
assert np.isfinite(out).all()
np.testing.assert_allclose(np.einsum('qra,qa->qr', g, E), 0, atol=5e-16)
for d in np.unique(p.ghost_coarse):
rows = p.ghost_coarse == d
assert rows.sum() == 4
np.testing.assert_allclose(out[:, rows].mean(axis=1), c.reshape(9,-1)[:,d], atol=5e-16)
for q in range(1,9):
delta = offsets[rows, None, :] - offsets[None, rows, :]
# Parallel displacements have zero 2D cross product.
parallel = np.isclose(delta[...,0]*E[q,1]-delta[...,1]*E[q,0], 0)
diff = out[q, rows][:,None]-out[q, rows][None,:]
np.testing.assert_allclose(diff[parallel], 0, atol=5e-16)
const = np.broadcast_to(W[:,None,None], (9,16,16)).copy()
constant, _ = reconstruct(const,p,neighbors,offsets)
np.testing.assert_array_equal(constant, np.broadcast_to(W[:,None], constant.shape))
def collide(f, tau):
rho = f.sum(axis=0)
u = np.einsum('qa,q...->a...', E, f) / rho
cu = np.einsum('qa,a...->q...', E, u)
eq = W[:,None] * rho * (1 + 3*cu + 4.5*cu**2 - 1.5*np.sum(u*u,axis=0))
return f + (eq-f)/tau
def totals(c, f, p):
q = c[:,~p.covered].sum(axis=1)+.25*f[:,p.fine_kind==ACTIVE].sum(axis=1)
return np.r_[q.sum(), E.T@q]
def check_full_two_hop_closed_corner_budget(union, collision, bounds):
p, neighbors, offsets = setup(union,bounds)
rng=np.random.default_rng(17)
c=W[:,None,None]*(1+rng.normal(0,.002,(9,16,16)))
f=W[:,None,None]*(1+rng.normal(0,.002,(9,*p.fine_shape)))
start=totals(c,f,p)
# Count exactly the eight coarse diagonal links whose source is also
# uncovered, but whose midpoint lies on the closed rectangular interface.
q, k=np.divmod(p.coalesce_coarse.astype(np.int64),256)
y,x=np.divmod(k,16)
grazing=~p.covered[y-E[q,1],x-E[q,0]]
assert grazing.sum()==8
c[:,p.covered]=np.nan
for _ in range(8):
f.reshape(9,-1)[:,p.ghost_fine]=reconstruct(c,p,neighbors,offsets)[0]
for _ in range(2):
f=np.array([np.roll(f[q],(ey,ex),(0,1)) for q,(ex,ey) in enumerate(E)])
f[:,p.fine_kind==OUTER_GHOST]=np.nan
if collision:
f[:,p.fine_kind==ACTIVE]=collide(f[:,p.fine_kind==ACTIVE],p.tau_fine)
out=np.array([np.roll(c[q],(ey,ex),(0,1)) for q,(ex,ey) in enumerate(E)])
packets=f.reshape(-1)[p.coalesce_fine].mean(axis=1)
assert np.isfinite(packets[grazing]).all()
out.reshape(-1)[p.coalesce_coarse]=packets
if collision:out[:,~p.covered]=collide(out[:,~p.covered],p.tau_coarse)
out[:,p.covered]=np.nan
c=out
np.testing.assert_allclose(totals(c,f,p),start,rtol=0,atol=2e-12)
def check_projection_is_distinguished_by_characteristic_not_global_mass():
p,n,o=setup()
c=np.random.default_rng(8).normal(size=(9,16,16))
_,g=reconstruct(c,p,n,o,project=False)
assert np.max(abs(np.einsum('qra,qa->qr',g,E))) > .1
class ProjectedExplosionTests(unittest.TestCase):
def test_stencil(self):
for union in (False, True):
for bounds in ((4,4,12,12),(2,3,9,10),(2,2,3,3)):
with self.subTest(union=union,bounds=bounds):
check_legal_footprint_mean_and_characteristic(union,bounds)
def test_closed_interface(self):
for union in (False,True):
for collision in (False,True):
for bounds in ((4,4,12,12),(2,3,14,12),(2,2,3,3)):
with self.subTest(union=union,collision=collision,bounds=bounds):
check_full_two_hop_closed_corner_budget(union,collision,bounds)
def test_projection(self):
check_projection_is_distinguished_by_characteristic_not_global_mass()
def test_affine_and_shift_invariance(self):
p,n,o=setup()
y,x=np.indices((16,16))
c=np.array([.7+q*.01+x*.03+y*.05 for q in range(9)])
out,g=reconstruct(c,p,n,o)
available=n[:,::2]!=n[:,1::2]
gradient=np.array([.03,.05])*available
expected=np.broadcast_to(gradient,(9,*gradient.shape)).copy()
expected[1:]-=(np.einsum('qra,qa->qr',expected[1:],E[1:])/
np.sum(E[1:]**2,axis=1)[:,None])[:,:,None]*E[1:,None,:]
np.testing.assert_allclose(g,expected,atol=2e-16)
shifted,_=reconstruct(c-W[:,None,None],p,n,o)
np.testing.assert_allclose(out-W[:,None],shifted,atol=5e-16)
class ProjectedKernelTests(unittest.TestCase):
@unittest.skipUnless(shutil.which("g++"), "g++ is required for actual-kernel CPU arithmetic")
def test_actual_kernel_fp32_shifted_and_unshifted(self):
p, neighbors, offsets = setup(True)
parent = BlockLayout2D.build(16,16,4,4,periodic=(True,True))
child = p.fine_layout((8,4)) # deliberately unequal parent/child strides
ids, offsets = projected_explosion_tables(p,parent,np.where(p.covered,OUTER_GHOST,ACTIVE))
cells = int(np.prod(parent.local_shape))
targets = child.owner.ravel()[p.ghost_fine]
donors = parent.owner.ravel()[p.ghost_coarse]
source = (Path(__file__).resolve().parents[2] /
"src/CelerisLab/lbm/kernels/blocks.cu").read_text()
kernel = source.split('extern "C" __global__ void BlockExplodeProjected(',1)[1]
kernel = 'void BlockExplodeProjected(' + kernel.split('// Targets are receiver-local SOURCE slots',1)[0]
def array(name, values, kind):
v = np.asarray(values).ravel()
text = ','.join(str(int(x)) if kind=='uint64_t' else float(x).hex()+'f' for x in v)
return f"{kind} {name}[] = {{{text}}};\n"
for shifted in (False,True):
c=np.random.default_rng(11).normal(0,.001,(9,16,16))
if not shifted:c+=W[:,None,None]
c=c.astype(np.float32)
packed=np.full(parent.nblocks*9*cells,np.nan,np.float32)
for q in range(9):packed[parent.slot(parent.owner.ravel(),q)]=c[q].ravel()
# All halo/covered inputs are poisoned; kernel must use legal cores.
for q in range(9):packed[parent.slot(parent.owner.ravel()[p.covered.ravel()],q)]=np.nan
# Hex initializer needs a portable expression for poisoned NaNs.
data=array('coarse',packed,'float').replace('nanf','NAN')
code = '#include <cstdint>\n#include <cmath>\n#include <cstdio>\nusing fpxx=float;\n'
code += f'constexpr unsigned NQ=9, TOTAL_CELLS={int(np.prod(child.local_shape))};\n'
code += 'struct Id {unsigned x;}; Id blockIdx{0},blockDim{1},threadIdx{0};\n'
code += 'unsigned index_f(unsigned k,unsigned q){return q*TOTAL_CELLS+k;}\n'
code += 'int d_cx[]={0,1,-1,0,0,1,-1,1,-1},d_cy[]={0,0,0,1,-1,1,-1,-1,1};\n'+kernel
code += data+array('target',targets,'uint64_t')+array('donor',donors,'uint64_t')
code += array('neighbor',ids,'uint64_t')+array('offset',offsets,'float')
code += f'float fine[{child.nblocks*9*int(np.prod(child.local_shape))}]={{}};\n'
code += f'int main(){{for(unsigned r=0;r<{len(targets)};++r){{threadIdx.x=r;BlockExplodeProjected(coarse,fine,target,donor,{len(targets)},{cells},neighbor,offset);}}'
code += f'for(unsigned q=0;q<9;++q)for(unsigned r=0;r<{len(targets)};++r){{auto t=target[r];printf("%.9g\\n",fine[(t/TOTAL_CELLS)*9*TOTAL_CELLS+q*TOTAL_CELLS+t%TOTAL_CELLS]);}}}}'
with tempfile.TemporaryDirectory() as folder:
src=Path(folder)/'kernel.cpp'; binary=Path(folder)/'kernel'
src.write_text(code)
subprocess.run(['g++','-std=c++17','-O2',str(src),'-o',str(binary)],check=True,capture_output=True)
result=np.fromstring(subprocess.check_output([str(binary)],text=True),sep=' ').reshape(9,-1)
expected,_=reconstruct(c.astype(float),p,neighbors,offsets)
np.testing.assert_allclose(result,expected,atol=6e-8,rtol=2e-7)
UNIONS = [
[(8, 8, 24, 20)],
[(8, 8, 16, 20), (16, 8, 24, 20)], # abutting
[(8, 8, 18, 20), (14, 8, 24, 20)], # overlap
[(8, 8, 16, 20), (17, 8, 24, 20)], # gap 1
[(8, 8, 16, 20), (18, 8, 24, 20)], # gap 2
[(8, 8, 16, 20), (19, 8, 24, 20)], # gap 3
[(8, 8, 20, 14), (8, 14, 14, 22)], # L concavity
[(4, 4, 10, 10), (18, 16, 26, 26)], # separated
[(4, 4, 5, 7), (4, 5, 7, 7)], # known concave exit/re-entry path
]
def decode(layout, neighbors):
inverse = np.full(layout.hole, -1, dtype=int)
inverse[layout.owner[layout.owned]] = np.flatnonzero(layout.owned)
return inverse[neighbors]
def check_pair_stencil(pair, layout, kind):
ids, offsets = projected_explosion_tables(pair, layout, kind)
neighbors = decode(layout, ids)
legal = set(map(int, pair.ghost_coarse))
assert len(np.unique(pair.ghost_fine)) == len(pair.ghost_fine)
assert set(neighbors.ravel()) <= legal
assert layout.owned.ravel()[neighbors].all()
assert (kind.ravel()[neighbors] == ACTIVE).all()
assert not pair.covered.ravel()[neighbors].any()
ny, nx = pair.coarse_shape
for row, donor in enumerate(pair.ghost_coarse):
y, x = divmod(int(donor), nx)
for axis, (dx, dy) in enumerate(((1, 0), (0, 1))):
ends = [(x - dx, y - dy), (x + dx, y + dy)]
expected = []
for xx, yy in ends:
outside = not (0 <= xx < nx and 0 <= yy < ny)
if outside and not layout.periodic[axis]:
break
cell = (yy % ny) * nx + xx % nx
if cell not in legal:
break
expected.append(cell)
if len(expected) != 2:
expected = [int(donor)] * 2
np.testing.assert_array_equal(neighbors[row, 2*axis:2*axis+2], expected)
fy, fx = divmod(int(pair.ghost_fine[row]), pair.fine_shape[1])
expected = [pair.fine_origin[0]+(fx+.5)/2-(x+.5),
pair.fine_origin[1]+(fy+.5)/2-(y+.5)]
np.testing.assert_array_equal(offsets[row], expected)
assert set(offsets.ravel()) == {-.25, .25}
assert ids.dtype == np.uint64 and ids.flags.c_contiguous
assert offsets.dtype == np.float32 and offsets.flags.c_contiguous
return neighbors, offsets
class GenericProjectedPairs(unittest.TestCase):
def test_single_window_and_singleton_union_exact_stencils(self):
for bounds in ((4,4,12,12), (2,3,9,10), (2,2,3,3)):
a, an, ao = setup(False, bounds)
b, bn, bo = setup(True, bounds)
np.testing.assert_array_equal(a.ghost_coarse, b.ghost_coarse)
np.testing.assert_array_equal(an, bn)
np.testing.assert_array_equal(ao, bo)
# Coordinates differ between scalar and union arrays; physical rows don't.
ay, ax = np.divmod(a.ghost_fine, a.fine_shape[1])
by, bx = np.divmod(b.ghost_fine, b.fine_shape[1])
np.testing.assert_array_equal(ax + 2*a.fine_origin[0], bx)
np.testing.assert_array_equal(ay + 2*a.fine_origin[1], by)
def test_union_decomposition_permutation_and_topologies(self):
cfg = LBMConfig(nx=30, ny=30, viscosity=.1)
layout = BlockLayout2D.build(30,30,6,5,periodic=(True,True))
stencils = []
for rectangles in UNIONS:
pair = FixedPatchSet2D.from_config(cfg, rectangles)
kind = np.where(pair.covered, OUTER_GHOST, ACTIVE)
n, o = check_pair_stencil(pair, layout, kind)
other = FixedPatchSet2D.from_config(cfg, rectangles[::-1])
on, oo = projected_explosion_tables(other, layout, kind)
np.testing.assert_array_equal(n, decode(layout, on))
np.testing.assert_array_equal(o, oo)
stencils.append((pair.ghost_fine, pair.ghost_coarse, n, o))
c = np.random.default_rng(92).normal(size=(9,30,30))
c[:, pair.covered] = np.nan
values, gradients = reconstruct(c, pair, n, o)
self.assertTrue(np.isfinite(values).all())
np.testing.assert_allclose(np.einsum('qra,qa->qr', gradients, E),0,atol=1e-15)
# q0 keeps its full gradient; no division by zero or forced zero.
expected_q0 = .5*(c[0].ravel()[n[:,1::2]]-c[0].ravel()[n[:,::2]])
np.testing.assert_array_equal(gradients[0], expected_q0)
self.assertGreater(np.max(abs(gradients[0])), .1)
for donor in np.unique(pair.ghost_coarse):
rows = pair.ghost_coarse == donor
self.assertEqual(rows.sum(),4)
np.testing.assert_allclose(values[:,rows].mean(axis=1),c.reshape(9,-1)[:,donor],atol=1e-15)
for q in range(1,9):
delta = o[rows,None,:]-o[None,rows,:]
parallel = delta[...,0]*E[q,1] == delta[...,1]*E[q,0]
diff = values[q,rows][:,None]-values[q,rows][None,:]
np.testing.assert_allclose(diff[parallel],0,atol=1e-15)
for split in stencils[1:3]:
for expected, actual in zip(stencils[0],split):
np.testing.assert_array_equal(actual,expected)
def test_nested_scalar_origins_sparse_holes_and_unequal_strides(self):
cases = [(CFG, FOUR), (LBMConfig(nx=16,ny=16,viscosity=.02),
[(4,4,12,12),(8,8,16,16),(8,8,16,16)])]
for cfg, refs in cases:
hierarchy = build_hierarchy(cfg,refs)
for index,pair in enumerate(hierarchy.pairs):
if index == 0:
layout = BlockLayout2D.build(cfg.ny,cfg.nx,4,4,periodic=(True,True))
else:
prior = hierarchy.pairs[index-1]
layout = (prior.fine_layout((4,8)) if isinstance(prior,FixedPatchSet2D)
else BlockLayout2D.build(*prior.fine_shape,4,8,periodic=(False,False)))
kind = hierarchy.kinds[index]
n,o = check_pair_stencil(pair,layout,kind)
c = np.random.default_rng(index).normal(size=(9,*pair.coarse_shape))
c[:,~layout.owned | (kind != ACTIVE)] = np.nan
self.assertTrue(np.isfinite(reconstruct(c,pair,n,o)[0]).all())
if index and isinstance(pair,FixedPatchSet2D):
self.assertTrue((~layout.owned).any())
self.assertEqual(layout.periodic, (index == 0, index == 0))
def test_periodicity_is_per_axis_and_missing_pairs_repeat_center(self):
cfg=LBMConfig(nx=16,ny=16,viscosity=.1)
p=FixedPatch2D.from_config(cfg,(2,2,14,14))
kind=np.where(p.covered,OUTER_GHOST,ACTIVE)
results=[]
for periodic in ((False,False),(True,False),(False,True),(True,True)):
layout=BlockLayout2D.build(16,16,4,4,periodic=periodic)
n,_=check_pair_stencil(p,layout,kind)
results.append(n)
y,x=np.divmod(p.ghost_coarse,16)
for axis,coordinate in enumerate((x,y)):
edge=(coordinate==0)|(coordinate==15)
if not periodic[axis]:
np.testing.assert_array_equal(n[edge,2*axis:2*axis+2],
np.repeat(p.ghost_coarse[edge,None],2,axis=1))
self.assertTrue((results[0]!=results[1]).any())
self.assertTrue((results[0]!=results[2]).any())
self.assertTrue((results[1]!=results[3]).any())
def test_invalid_parent_donors_reject_before_owner_lookup(self):
p,_,_=setup()
layout=BlockLayout2D.build(16,16,4,4)
kind=np.where(p.covered,OUTER_GHOST,ACTIVE)
for nonactive in (1,2,255):
bad=kind.copy(); bad.ravel()[p.ghost_coarse[0]]=nonactive
with self.assertRaisesRegex(ValueError,'ACTIVE'):
projected_explosion_tables(p,layout,bad)
with self.assertRaisesRegex(ValueError,'shape'):
projected_explosion_tables(p,layout,kind[:1])
hole_layout=BlockLayout2D.build(16,16,4,4,origins=[(0,0)])
with self.assertRaisesRegex(ValueError,'owned'):
projected_explosion_tables(p,hole_layout,kind)
def test_generic_two_hop_mass_and_momentum_budget(self):
cfg=LBMConfig(nx=30,ny=30,viscosity=.1)
layout=BlockLayout2D.build(30,30,6,5)
grazing_counts=set()
for rectangles in UNIONS:
pair=FixedPatchSet2D.from_config(cfg,rectangles)
ids,o=projected_explosion_tables(pair,layout,np.where(pair.covered,OUTER_GHOST,ACTIVE))
n=decode(layout,ids)
q,k=np.divmod(pair.coalesce_coarse.astype(np.int64),900)
y,x=np.divmod(k,30)
grazing=~pair.covered[(y-E[q,1])%30,(x-E[q,0])%30]
grazing_counts.add(int(grazing.sum()))
self.assertTrue(grazing.any())
for collision in (False,True):
rng=np.random.default_rng(17)
c=W[:,None,None]*(1+rng.normal(0,.002,(9,30,30)))
f=W[:,None,None]*(1+rng.normal(0,.002,(9,*pair.fine_shape)))
start=totals(c,f,pair)
c[:,pair.covered]=np.nan
for _ in range(4):
f.reshape(9,-1)[:,pair.ghost_fine]=reconstruct(c,pair,n,o)[0]
for _ in range(2):
f=np.array([np.roll(f[q],(ey,ex),(0,1)) for q,(ex,ey) in enumerate(E)])
f[:,pair.fine_kind==OUTER_GHOST]=np.nan
if collision:
f[:,pair.fine_kind==ACTIVE]=collide(f[:,pair.fine_kind==ACTIVE],pair.tau_fine)
out=np.array([np.roll(c[q],(ey,ex),(0,1)) for q,(ex,ey) in enumerate(E)])
packets=f.reshape(-1)[pair.coalesce_fine].mean(axis=1)
self.assertTrue(np.isfinite(packets[grazing]).all())
out.reshape(-1)[pair.coalesce_coarse]=packets
if collision:
out[:,~pair.covered]=collide(out[:,~pair.covered],pair.tau_coarse)
out[:,pair.covered]=np.nan
c=out
np.testing.assert_allclose(totals(c,f,pair),start,rtol=0,atol=4e-12)
self.assertGreater(len(grazing_counts),1) # not a hard-coded eight-corner oracle
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"""Host-only checks for the opt-in CUDA gate; never imports or compiles CUDA."""
from copy import deepcopy
import importlib.util
from pathlib import Path
import unittest
from unittest.mock import patch
import numpy as np
from CelerisLab.config import LBMConfig
from CelerisLab.lbm.blocks import BlockLayout2D
from CelerisLab.lbm.hierarchy import build_hierarchy
from CelerisLab.lbm.refinement import ACTIVE, OUTER_GHOST, FixedPatch2D, FixedPatchSet2D
from CelerisLab.lbm.refinement_tables import projected_explosion_tables
from tests.unit.test_hierarchy import CFG, FOUR
from tests.unit.test_projected_explosion import decode, reconstruct, totals
PATH = Path(__file__).resolve().parents[1] / 'validation/multigrid/check_projected_pairs.py'
spec = importlib.util.spec_from_file_location('projected_pair_gate', PATH)
gate = importlib.util.module_from_spec(spec)
spec.loader.exec_module(gate)
class ProjectedGateOracle(unittest.TestCase):
def check_pair(self, pair, layout, kind):
ids, offsets = projected_explosion_tables(pair, layout, kind)
neighbors = decode(layout, ids)
coarse = np.random.default_rng(731).normal(size=(9, *pair.coarse_shape))
legal = np.zeros(pair.coarse_shape, bool)
legal.ravel()[pair.ghost_coarse] = True
coarse[:, ~legal] = np.nan
expected, _ = reconstruct(coarse, pair, neighbors, offsets)
# The coordinate oracle must not accidentally share production tables.
with patch('CelerisLab.lbm.refinement_tables.projected_explosion_tables',
side_effect=AssertionError('oracle used production stencil')):
actual = gate.independent_explosion(coarse, pair, layout, kind)
np.testing.assert_allclose(actual, expected, rtol=0, atol=2e-15)
center = coarse.reshape(9, -1)[:, pair.ghost_coarse]
self.assertTrue(np.isfinite(actual).all())
self.assertGreater(np.max(abs(actual[0] - center[0])), .01)
self.assertGreater(np.max(abs(actual[1:] - center[1:])), .01)
return coarse, neighbors, offsets, actual
def test_scalar_union_nested_sparse_and_unequal_strides(self):
def fine_layout(pair, block):
return (pair.fine_layout(block) if isinstance(pair, FixedPatchSet2D) else
BlockLayout2D.build(*pair.fine_shape, *block, periodic=(False,False)))
small = LBMConfig(nx=16, ny=16, viscosity=.02)
fixtures = [(small, [(4,4,12,12), (8,8,16,16), (8,8,16,16)]),
(CFG, FOUR), (small, [[(4,4,5,7), (4,5,7,7)]])]
for cfg, refs in fixtures:
hierarchy = build_hierarchy(cfg, refs)
for index, pair in enumerate(hierarchy.pairs):
block, child_block = ((4,4), (4,8)) if index % 2 == 0 else ((4,8), (4,4))
layout = (BlockLayout2D.build(cfg.ny, cfg.nx, *block) if index == 0
else fine_layout(hierarchy.pairs[index-1], block))
with self.subTest(refs=refs, pair=index):
self.assertNotEqual(np.prod(layout.local_shape),
np.prod(fine_layout(pair, child_block).local_shape))
if index and isinstance(pair, FixedPatchSet2D):
self.assertTrue((~layout.owned).any())
self.check_pair(pair, layout, hierarchy.kinds[index])
def test_axis_periodicity_and_mean_preserving_mutants(self):
pair = FixedPatch2D.from_config(LBMConfig(nx=16,ny=16,viscosity=.1), (2,2,14,14))
kind = np.where(pair.covered, OUTER_GHOST, ACTIVE)
outputs = []
for periodic in ((False,False), (True,False), (False,True), (True,True)):
layout = BlockLayout2D.build(16,16,4,4,periodic=periodic)
coarse, neighbors, offsets, actual = self.check_pair(pair, layout, kind)
outputs.append(actual)
donors, first, inverse = np.unique(pair.ghost_coarse, return_index=True, return_inverse=True)
wrong = neighbors[first[np.roll(np.arange(len(donors)), 1)]][inverse]
for bad_neighbors, bad_offsets in ((neighbors, -offsets), (wrong, offsets)):
mutant, _ = reconstruct(coarse, pair, bad_neighbors, bad_offsets)
self.assertGreater(np.max(abs(mutant - actual)), .01)
for donor in donors:
rows = pair.ghost_coarse == donor
self.assertEqual(rows.sum(), 4)
np.testing.assert_allclose(mutant[:,rows].mean(axis=1),
coarse.reshape(9,-1)[:,donor], rtol=0, atol=1e-15)
bad_kind = kind.copy(); bad_kind.ravel()[pair.ghost_coarse[0]] = OUTER_GHOST
with self.assertRaisesRegex(AssertionError, 'illegal center donor'):
gate.independent_explosion(coarse, pair, layout, bad_kind)
for i, j in ((0,1), (0,2), (1,3), (2,3)):
self.assertGreater(np.max(abs(outputs[i] - outputs[j])), .01)
def test_concave_replay_preserves_existing_fp64_budget(self):
cfg, refs, blocks = gate.cases()['concave']
hierarchy = build_hierarchy(cfg, refs); pair = hierarchy.pairs[0]
layout = BlockLayout2D.build(cfg.ny, cfg.nx, *blocks[0])
rng = np.random.default_rng(17)
values = tuple(gate.W[:,None,None] * (1 + rng.normal(0,.002,(9,*shape)))
for shape in (pair.coarse_shape, pair.fine_shape))
start = totals(*values, pair)
values[0][:,pair.covered] = np.nan
for _ in range(8):
values = gate.replay_two_hops(values, pair, layout, hierarchy.kinds[0])
np.testing.assert_allclose(totals(*values, pair), start, rtol=0, atol=4e-12)
self.assertEqual(gate.REPLAY_ATOL, 3e-6) # CUDA replay bound is separate.
class ProjectedGateReceipts(unittest.TestCase):
def test_digest_exact_finite_bits_and_nan_masks(self):
values = np.array([0., -0., np.nan, 1.], dtype=np.float32)
self.assertEqual(gate.digest(values), gate.digest(values.copy()))
payload = values.copy(); payload.view(np.uint32)[2] = 0x7fc00001
self.assertEqual(gate.digest(values), gate.digest(payload))
variants = [np.array([-0., -0., np.nan, 1.], np.float32),
np.array([0., np.nan, -0., 1.], np.float32),
np.array([0., -0., np.nan, np.nextafter(np.float32(1), np.float32(2))], np.float32),
values.reshape(2,2), values.astype(np.float64)]
for changed in variants:
self.assertNotEqual(gate.digest(values), gate.digest(changed))
with self.assertRaisesRegex(AssertionError, 'infinite'):
gate.digest(np.array([np.inf]))
def test_snapshot_negative_controls_and_exact_dev_options(self):
snapshot = [dict(step=0, levels=[dict(raw='raw',public='public',active=4)],
mass_momentum=[1.,0.,0.],observed_level_hops=[0,0])]
gate.compare_snapshots(snapshot, deepcopy(snapshot))
diagnostic = deepcopy(snapshot); diagnostic[0]['mass_momentum'][0] = 2.
gate.compare_snapshots(snapshot, diagnostic) # Diagnostics are not bitwise gate fields.
mutants = [[]]
for key, value in (('raw','changed'), ('public','changed'), ('active',3)):
changed = deepcopy(snapshot); changed[0]['levels'][0][key] = value
mutants.append(changed)
changed = deepcopy(snapshot); changed[0]['step'] = 1; mutants.append(changed)
changed = deepcopy(snapshot); changed[0]['observed_level_hops'] = [0,1]; mutants.append(changed)
for changed in mutants:
with self.assertRaises(AssertionError):
gate.compare_snapshots(snapshot, changed)
self.assertEqual(gate.default_options('omitted'), {})
self.assertEqual(gate.default_options('constant'), {'explosion':'constant'})
self.assertEqual(gate.default_options('projected_linear'), {'explosion':'projected_linear'})
def test_baseline_receipt_rejects_provenance_and_contract_mutants(self):
keys = [f'{name}:shifted={shifted}' for name in gate.cases() for shifted in (False,True)]
good = dict(completed=True,dry_run=False,mode='baseline',production_revision=gate.BASE,
source=dict(revision=gate.BASE,dirty=False),driver_sha256='driver',
stops=list(gate.STOPS),operator_tolerance=[6e-8,2e-7],
rest_tolerance=[3e-7,1e-6],replay_tolerance=[3e-6,0],default_snapshots=dict.fromkeys(keys, []),
actual_build_sidecars=[{'ptx_sha256':'captured'}])
self.assertIs(gate.baseline_receipt(good, 'driver', keys), good)
mutants = dict(completed=False,dry_run=True,mode='candidate',production_revision='wrong',
driver_sha256='wrong',stops=[0,1,2],operator_tolerance=[1e-6,2e-7],
rest_tolerance=[3e-7,1e-5],replay_tolerance=[3e-6,1e-7],actual_build_sidecars=[],default_snapshots={})
for field, value in mutants.items():
bad = deepcopy(good); bad[field] = value
with self.subTest(field=field), self.assertRaises(ValueError):
gate.baseline_receipt(bad, 'driver', keys)
for changes in (dict(revision='wrong'), dict(dirty=True), dict(dirty=None)):
bad = deepcopy(good); bad['source'].update(changes)
with self.assertRaises(ValueError):
gate.baseline_receipt(bad, 'driver', keys)
bad = deepcopy(good); bad['default_snapshots']['unexpected'] = []
with self.assertRaises(ValueError):
gate.baseline_receipt(bad, 'driver', keys)
if __name__ == '__main__':
unittest.main()
+198
View File
@@ -0,0 +1,198 @@
"""Production host dispatch with CUDA doubles; no CUDA compilation or flow runs."""
from contextlib import nullcontext
from dataclasses import replace
from unittest.mock import Mock
import unittest
import numpy as np
from CelerisLab.config import LBMConfig
from tests.unit.test_hierarchy import CFG, FOUR
from tests.unit.test_refinement_three_level_multipatch import host_module
def backend(**options):
host = host_module()
calls, allocations, storage = [], [], {}
context = Mock(activate=nullcontext, sm_arch='sm_70')
host.cuda.mem_alloc.side_effect = lambda size: allocate(size)
def allocate(size):
pointer = Mock(name=f'buffer{len(allocations)}', size=size)
allocations.append(pointer)
return pointer
def load(_):
module = Mock()
module.get_global.return_value = (Mock(), 20)
module.get_function.side_effect = lambda name: Mock(
name=name, side_effect=lambda *a, **kw: calls.append((name, a, kw)))
return module
host.compiler.load_module.side_effect = load
host.cuda.memcpy_htod.side_effect = lambda ptr, a: storage.__setitem__(id(ptr), np.array(a, copy=True))
host.cuda.memcpy_dtoh.side_effect = lambda a, ptr: np.copyto(a, storage[id(ptr)])
cfg = options.pop('cfg', CFG)
refinements = options.pop('refinements', FOUR)
blocks = options.pop('level_blocks', [(4, 4)] * (len(refinements) + 1))
run = host.FixedPatchStepper(cfg, context=context, refinements=refinements,
level_blocks=blocks, **options)
run.initialize(*(np.full(level.shape, 1/9, np.float32) for level in run._levels))
return run, host, calls, allocations, storage
def trace(run, calls, allocations, storage):
"""Stable pointer identities expose allocations/arguments, not just kernel names."""
pointer = {id(value): index for index, value in enumerate(allocations)}
launches = [(name, tuple(('ptr', pointer[id(a)]) if id(a) in pointer else int(a)
for a in args), kw['grid'], kw['block'])
for name, args, kw in calls]
uploads = [(index, value.dtype.str, value.shape, value.tobytes())
for index, ptr in enumerate(allocations) if (value := storage.get(id(ptr))) is not None]
return [p.size for p in allocations], uploads, launches
class ProjectedPairDispatch(unittest.TestCase):
def test_omitted_and_constant_have_identical_allocations_uploads_and_launches(self):
results = []
for options in ({}, {'explosion': 'constant'}):
run, host, calls, allocations, storage = backend(**options)
self.assertEqual(run._explosion, 'constant')
self.assertTrue(all(p.neighbors is None and p.offsets is None for p in run._pairs))
run.step()
explosion = [args for name, args, _ in calls if name == 'BlockExplode']
self.assertEqual(len(explosion), 7)
self.assertTrue(all(len(args) == 6 for args in explosion))
self.assertFalse(any(name == 'BlockExplodeProjected' for name, _, _ in calls))
results.append(trace(run, calls, allocations, storage))
run.close()
self.assertEqual(*results)
def test_projected_adds_exactly_two_tables_per_adjacent_pair(self):
for depth in (2, 3, 4):
constant, _, _, ca, _ = backend(refinements=FOUR[:depth-1])
projected, _, calls, pa, storage = backend(
refinements=FOUR[:depth-1], explosion='projected_linear')
self.assertEqual(len(pa)-len(ca), 2*(depth-1))
for pair, geometry in zip(projected._pairs, projected.hierarchy.pairs):
self.assertEqual(storage[id(pair.neighbors)].shape, (len(geometry.ghost_fine), 4))
self.assertEqual(storage[id(pair.offsets)].shape, (len(geometry.ghost_fine), 2))
self.assertEqual(pair.neighbors.size, len(geometry.ghost_fine)*4*8)
self.assertEqual(pair.offsets.size, len(geometry.ghost_fine)*2*4)
projected.step()
explosions = [args for name, args, _ in calls if name == 'BlockExplodeProjected']
self.assertEqual(len(explosions), 2**(depth-1)-1)
self.assertTrue(all(len(args) == 8 for args in explosions))
self.assertFalse(any(name == 'BlockExplode' for name, _, _ in calls))
for args in explosions:
pair = next(p for p in projected._pairs if args[2] is p.ghosts)
self.assertIs(args[6], pair.neighbors)
self.assertIs(args[7], pair.offsets)
self.assertEqual(args[5], pair.parent_cells)
constant.close(); projected.close()
def test_three_and_four_level_schedule_has_fresh_midpoint_sources(self):
for depth in (3, 4):
for explosion in ('constant', 'projected_linear'):
run, host, calls, allocations, storage = backend(
refinements=FOUR[:depth-1], explosion=explosion)
before = len(allocations)
events = []
for index, pair in enumerate(run._pairs):
pair.explode.side_effect = lambda source, *a, index=index, **kw: events.append(('explode', index, source))
pair.coalesce.side_effect = lambda child, source, *a, index=index, **kw: events.append(('restrict', index, source))
for index, level in enumerate(run._levels):
level.kernel.side_effect = lambda source, *a, index=index, **kw: events.append(('step', index, source))
level.halo_copy.side_effect = lambda source, *a, index=index, **kw: events.append(('halo', index, source))
expected = []
def hop(index, source):
if index+1 < depth:
expected.append(('explode', index, source))
child = run._levels[index+1]
hop(index+1, child.current)
hop(index+1, child.spare)
expected.append(('halo', index, source))
if index+1 < depth:
expected.append(('restrict', index, source))
expected.append(('step', index, source))
hop(0, run._levels[0].current)
run.step()
self.assertEqual(events, expected)
self.assertEqual([level.kernel.call_count for level in run._levels], [2**i for i in range(depth)])
self.assertEqual(len(allocations), before)
self.assertEqual(run.step_count, 1)
for index in range(1, depth-1):
feeds = [source for name, pair, source in events if name == 'explode' and pair == index]
self.assertEqual(feeds, [run._levels[index].current, run._levels[index].spare] * (2**(index-1)))
run.close()
def test_scalar_windows_follow_the_same_pair_path(self):
run, _, _, _, _ = backend(cfg=LBMConfig(nx=16,ny=16,viscosity=.02),
refinements=[(4,4,12,12),(8,8,16,16),(8,8,16,16)],
level_blocks=[(4,4),(4,8),(8,4),(4,4)], explosion='projected_linear')
self.assertTrue(all(pair.neighbors is not None for pair in run._pairs))
self.assertEqual([pair.parent_cells for pair in run._pairs], [36,60,60])
run.step()
self.assertEqual([level.kernel.call_count for level in run._levels], [1,2,4,8])
run.close()
def test_physics_gate_precedes_context_and_allocations(self):
host = host_module()
context = Mock()
options = dict(refinements=FOUR[:1], level_blocks=[(4,4)]*2,
explosion='projected_linear', context=context)
for cfg, changes in [(CFG, {'explosion':'unknown'}),
(CFG, {'coarse_boundary':'slot_reservoir'}),
(CFG, {'coarse_boundary':'channel'}),
(CFG, {'level_blocks':[None,None], 'refinements':[(6,6,26,26)]}),
(CFG, {'level_objects':[(),(object(),)]}),
(CFG, {'level_jets':[(),(object(),)]}),
(replace(CFG,collision='MRT'), {}),
(replace(CFG,les_enabled=True), {})]:
with self.subTest(changes=changes, cfg=cfg), self.assertRaisesRegex(ValueError,'explosion'):
host.FixedPatchStepper(cfg, **dict(options, **changes))
context.activate.assert_not_called()
host.cuda.mem_alloc.assert_not_called()
# The legacy constant path still allows MRT and dense storage.
for options in ({'cfg':replace(CFG,collision='MRT')},
{'level_blocks':[None,None], 'refinements':[(6,6,26,26)]}):
run, _, _, _, _ = backend(**options)
run.close()
def test_remap_preserves_selector_tables_and_constant_default(self):
for explosion in ('constant','projected_linear'):
run, host, _, _, storage = backend(refinements=FOUR[:2], explosion=explosion)
run._step_count = 7
old = run.download()
clone = run.remap_child(FOUR[1])
self.assertEqual(clone._explosion, explosion)
self.assertEqual(clone.step_count, 7)
for pair in clone._pairs:
self.assertEqual(pair.neighbors is None, explosion == 'constant')
for expected, actual in zip(old, clone.download()):
np.testing.assert_array_equal(actual,expected)
clone.step()
self.assertEqual((run.step_count,clone.step_count), (7,8))
clone.close(); run.close()
def test_changed_remap_geometry_keeps_projected_in_both_representations(self):
changed = [(22,22,42,42), (72,68,76,76)]
for shifted in (False, True):
run, _, _, _, _ = backend(cfg=replace(CFG,ddf_shifting=shifted),
refinements=FOUR[:2], explosion='projected_linear')
run._step_count = 3
before = run.download()
clone = run.remap_child(changed)
self.assertEqual(clone._explosion, 'projected_linear')
self.assertEqual(clone.hierarchy.pairs[1].bounds, tuple(changed))
self.assertNotEqual(clone._pairs[1].n_ghosts, run._pairs[1].n_ghosts)
for old, new in zip(run._pairs, clone._pairs):
self.assertIsNot(old.neighbors, new.neighbors)
self.assertIsNotNone(new.neighbors)
for expected, actual in zip(before, run.download()):
np.testing.assert_array_equal(actual, expected)
clone.step()
self.assertEqual((run.step_count, clone.step_count), (3, 4))
clone.close(); run.close()
+3 -2
View File
@@ -157,8 +157,9 @@ class RawExchange(unittest.TestCase):
host = host_module()
ctx = Mock()
with self.assertRaisesRegex(ValueError, 'blocked body'):
host.FixedPatchStepper(LBMConfig(nx=32, ny=32, viscosity=.1), (4, 4, 28, 28),
context=ctx, fine_objects=[body(radius=2.15)], observe_raw_exchange=True)
host.FixedPatchStepper(LBMConfig(nx=32, ny=32, viscosity=.1), context=ctx,
refinements=[(4, 4, 28, 28)],
level_objects=[(), (body(radius=2.15),)], observe_raw_exchange=True)
ctx.activate.assert_not_called()
def test_all_depth_weights(self):
+174 -4
View File
@@ -146,23 +146,26 @@ def test_full_requires_completed_pilot():
r.verify_pilot(None, r.verify_source(r.DEFAULT_SOURCE, "MRT", "window"))
def pilot_fixture(path, observation_mode="window"):
def pilot_fixture(path, observation_mode="window", jet_scenario="none", case_selection="both", uniform_diameter=80, placement="wide"):
"""Synthetic contract fixture only; never a physical result or run receipt."""
manifest = (r.verify_source(r.DEFAULT_SOURCE, "MRT", "window")
manifest = (r.verify_source(r.DEFAULT_SOURCE, "MRT", "window", jet_scenario)
if observation_mode == "window" else
json.loads((r.HERE / "data/refined_dfg/source_manifest_mrt.json").read_text()))
selection = dict(case_selection=case_selection, uniform_diameter=uniform_diameter, placement=placement)
(path / "plan.json").write_text(
json.dumps(
dict(
source_manifest=manifest,
**selection,
collision="MRT",
jet_scenario=jet_scenario,
observation_mode=observation_mode,
bounds_root_edge=list(r.BOUNDS),
bounds_root_edge=list(r.PLACEMENTS[placement]),
runner_sha256=r.runner_hash(),
)
)
)
for case, diameter in (("uniform", 80), ("refined", 40)):
for case, diameter in r.selected_cases(case_selection, uniform_diameter):
dest = path / case
dest.mkdir()
interval = round(0.02 * diameter / r.SPEED)
@@ -189,7 +192,9 @@ def pilot_fixture(path, observation_mode="window"):
json.dumps(
dict(
case=case,
**selection,
collision="MRT",
jet_scenario=jet_scenario,
observation_mode=observation_mode,
mode="pilot",
status="pilot_complete",
@@ -206,7 +211,9 @@ def pilot_fixture(path, observation_mode="window"):
json.dumps(
dict(
case=case,
**selection,
collision="MRT",
jet_scenario=jet_scenario,
observation_mode=observation_mode,
mode="pilot",
step=interval,
@@ -451,6 +458,169 @@ def test_window_contract_rejection():
assert not backend.events
def test_public_jet_configuration_and_geometry():
for diameter, center, radius in ((40, (80.5, 81), 20), (80, (160, 160.5), 40)):
cfg, _, _ = r.config(h, diameter, "MRT", "fixed")
assert not cfg["method"]["ddf_shifting"] and not cfg["method"]["les"]["enabled"]
jets = r.public_jets(center, radius, "fixed")
assert [j.amplitude for j in jets] == [.001, -.001]
assert all(j.field.inward is False and j.profile == "parabolic" for j in jets)
assert all(j.region.r_max == radius * 1.005 for j in jets)
assert all(j.amplitude == 0 for j in r.public_jets(center, radius, "zero"))
cfg, _, _, host = r.host_geometry(r.DEFAULT_SOURCE, h, "MRT", "fixed")
assert not cfg.ddf_shifting and len(host.boundary_cells) > 0
assert r.public_jets((0, 0), 1, "none") == ()
with unittest.TestCase().assertRaises(ValueError):
r.config(h, 40, "SRT", "fixed")
def test_public_jet_reversal_boundary_and_windows():
from types import SimpleNamespace
calls = []
handle = SimpleNamespace(set_jet_amplitude=lambda i, a: calls.append((i, a)))
for diameter in (40, 80):
boundary = round(250 * diameter / r.SPEED)
assert r.jet_interval(handle, "fixed", boundary - 3, 80, diameter) == (3, None)
switch = round(300 * diameter / r.SPEED)
assert r.jet_interval(handle, "reverse", switch - 3, 80, diameter) == (3, None)
assert not calls
n, event = r.jet_interval(handle, "reverse", switch, 80, diameter)
assert n == 80 and event["step"] == switch and event["tstar"] == 300
assert calls == [(0, -.001), (1, .001)]
calls.clear()
assert r.jet_interval(handle, "reverse", switch + 80, 80, diameter) == (80, None)
assert r.jet_interval(handle, "fixed", switch, 80, diameter) == (80, None)
assert not calls
rows = [dict(tstar=t, tstar_force=t - .5, cd=2.0, cl=-.1) for t in range(251, 306)]
windows = r.jet_diagnostics(rows, "reverse")
assert len(windows) == 6 and all(w["complete"] for w in windows)
assert all(w["cd"]["mean"] == 2 and np.isclose(w["cl"]["mean"], -.1) for w in windows)
assert windows[-1]["covered_tstar"] == 5
with unittest.TestCase().assertRaisesRegex(ValueError, "crosses"):
r.jet_diagnostics([dict(tstar=250.5, tstar_force=250, cd=1, cl=0)], "fixed")
assert r.plan(h, "MRT", "window", "reverse")["modes"]["full_tstar"] == 305
def test_public_jet_source_and_pilot_separation():
from tempfile import TemporaryDirectory
with TemporaryDirectory() as tmp:
path = Path(tmp)
manifest = pilot_fixture(path, jet_scenario="fixed")
assert manifest["source_capture"].startswith("current checkout")
assert len(manifest["checkout_revision"]) == 40
assert r.verify_pilot(path, manifest, "MRT", "window", "fixed") == 3606.0
for scenario in ("none", "zero", "reverse"):
with unittest.TestCase().assertRaisesRegex(ValueError, "Jet scenario"):
r.verify_pilot(path, manifest, "MRT", "window", scenario)
for relative in ("uniform/summary.json", "refined/ready.json"):
receipt = path / relative
record = json.loads(receipt.read_text())
receipt.write_text(json.dumps(dict(record, jet_scenario="zero")))
with unittest.TestCase().assertRaises(ValueError):
r.verify_pilot(path, manifest, "MRT", "window", "fixed")
receipt.write_text(json.dumps(record))
with unittest.TestCase().assertRaises(ValueError):
r.verify_source(r.DEFAULT_SOURCE, "MRT", "last_base_step", "fixed")
def test_cv_snapshot_common_units_and_window_endpoints():
records = []
for refined, shape, origin, diameter, impulse in (
(True, (240, 568), (38., 22.), 40, [4., -8.]),
(False, (330, 1761), (.25, .5), 80, [16., -32.]),
(False, (658, 3521), (.375, .75), 160, [64., -128.]),
):
rho, ux, uy, fluid = np.ones(shape), np.full(shape, .01), np.zeros(shape), np.ones(shape, bool)
begin, n = round(290*diameter/r.SPEED), round(.02*diameter/r.SPEED)
record = r.cv_snapshot(rho, ux, uy, fluid, origin, refined, begin, n, diameter, impulse)
records.append(record)
np.testing.assert_allclose(record["outward_flux"], 0, atol=1e-12)
assert r.cv_selected(begin, diameter, "full") and not r.cv_selected(begin-n, diameter, "full")
end = round(300*diameter/r.SPEED)
assert r.cv_selected(end, diameter, "full") and not r.cv_selected(end+n, diameter, "full")
assert r.cv_selected(n, diameter, "pilot")
assert sum(r.cv_selected(step, diameter, "full") for step in range(begin-n, end+n+1, n)) == 501
for key in ("time_root", "interval_start_root", "interval_dt_root", "interval_impulse_root", "inventory"):
for record in records[1:]:
np.testing.assert_allclose(records[0][key], record[key], rtol=0, atol=1e-10)
assert records[0]["interval_dt_root"] == 80 and np.isclose(records[0]["tstar"], 290.02)
np.testing.assert_array_equal(records[0]["interval_impulse_root"], [4, -8])
def test_cv_pilot_mode_and_helper_provenance():
from tempfile import TemporaryDirectory
manifest = r.verify_source(r.DEFAULT_SOURCE, "MRT", "window", "fixed", True)
assert "tests/validation/run_jet_circle_cv.py" in manifest["sha256"]
with TemporaryDirectory() as tmp:
path = Path(tmp)
old = pilot_fixture(path, jet_scenario="fixed")
with unittest.TestCase().assertRaisesRegex(ValueError, "CV observation mode"):
r.verify_pilot(path, old, "MRT", "window", "fixed", True)
for relative in ("plan.json", "uniform/summary.json", "refined/summary.json",
"uniform/ready.json", "refined/ready.json"):
file = path / relative
record = json.loads(file.read_text())
record.update(observe_cv=True, cv_samples=250)
if relative == "plan.json":
record["source_manifest"] = manifest
file.write_text(json.dumps(record))
assert r.verify_pilot(path, manifest, "MRT", "window", "fixed", True) == 3606
def test_compact_geometry_and_cv_stencils():
from CelerisLab.lbm.refinement import ACTIVE
from CelerisLab.lbm.descriptors import SOLID
_, pair, _, host = r.host_geometry(r.DEFAULT_SOURCE, h, "MRT", "fixed", "compact")
assert pair.fine_shape == (168, 168) and tuple(pair.fine_origin) == (46, 46)
fluid = (pair.fine_kind == ACTIVE) & ((host.flags.reshape(pair.fine_shape) & SOLID) == 0)
rho, ux, uy = np.ones(pair.fine_shape), np.full(pair.fine_shape, .01), np.zeros(pair.fine_shape)
record = r.cv_snapshot(rho, ux, uy, fluid, pair.fine_origin, True, 1160000, 80, 40, [1, 2], "compact")
np.testing.assert_allclose(record["outward_flux"], 0, atol=1e-12)
stencil = np.zeros(pair.fine_shape, bool)
for rect in r.cv_contours(True, 40, "compact"):
x0, y0, x1, y1 = np.rint((rect - np.tile(pair.fine_origin, 2))/.5).astype(int)
stencil[y0-2:y1+2, x0-2:x0+2] = stencil[y0-2:y1+2, x1-2:x1+2] = True
stencil[y0-2:y0+2, x0-2:x1+2] = stencil[y1-2:y1+2, x0-2:x1+2] = True
assert fluid[stencil].all() and not stencil.ravel()[host.transfer_fine_cells].any()
def test_d160_config_and_single_case_receipts():
from tempfile import TemporaryDirectory
from unittest.mock import patch
cfg, _, p = r.config(h, 160, "MRT", "fixed")
assert (p["nx"], p["ny"], p["center"], p["radius"]) == (3521, 658, [320, 320.5], 80)
assert p["viscosity"] == .016 and p["mean_speed"] == .01 and not cfg["method"]["ddf_shifting"]
assert r.uniform_origin(160) == (.375, .75)
np.testing.assert_array_equal(r.cv_contours(False, 160), r.CV_CONTOURS + [.125, 0, .125, 0])
for scenario, expected_exit in (("fixed", 0), ("zero", 2)):
with TemporaryDirectory() as tmp:
path = Path(tmp)
manifest = pilot_fixture(path, jet_scenario=scenario, case_selection="uniform", uniform_diameter=160)
assert r.verify_pilot(path, manifest, "MRT", "window", scenario, False, "uniform", 160) == 1803
for selection, diameter, placement in (("both", 160, "wide"), ("uniform", 80, "wide"), ("uniform", 160, "compact")):
with unittest.TestCase().assertRaises(ValueError):
r.verify_pilot(path, manifest, "MRT", "window", scenario, False, selection, diameter, placement)
# Synthetic dispatch/result check: no CUDA imports or execution.
output = path / "full"
argv = ["runner", "--collision", "MRT", "--exchange-window", "--jet-scenario", scenario,
"--case", "uniform", "--uniform-diameter", "160", "--mode", "full",
"--pilot-results", str(path), "--output", str(output), "--max-wall-seconds", "10", "--gpu-gates-approved"]
result = dict(case="uniform", healthy=True, periodic=scenario == "zero", jet_diagnostic_windows=[],
status="driven_diagnostics_complete" if scenario == "fixed" else "periodic",
reference_comparison=dict(reference_agreement=False))
with patch.object(sys, "argv", argv), patch.dict(r.os.environ, CUDA_VISIBLE_DEVICES="mock-no-gpu"), \
patch.object(r, "run_case", return_value=result) as run:
assert r.main() == expected_exit and run.call_count == 1
comparison = json.loads((output / "comparison.json").read_text())
assert comparison["matched_case_pass"] is False and "refined_vs_uniform" not in comparison
assert comparison["status"].startswith("single_case_")
if __name__ == "__main__":
suite = unittest.TestSuite(
unittest.FunctionTestCase(fn)
+6 -1
View File
@@ -37,8 +37,13 @@ class RefinementMRTHost(unittest.TestCase):
self.assertIn("STORE_PRECISION != 0", source)
self.assertIn('#if COLLISION_MODEL == 2\n#include "operators/collision_mrt.cuh"\n#endif', source)
self.assertIn("USE_DDF_SHIFTING ||", refinement) # dense/mixed shifted stays rejected
# One shared unforced MRT body; each blocked/patch path calls it exactly once.
mrt = (KERNELS / "operators/collision_mrt.cuh").read_text()
self.assertEqual(mrt.count("void collide_mrt_unforced("), 1)
for source in (blocks, channel, refinement):
self.assertEqual(source.count("collide_mrt_no_force("), 1)
self.assertEqual(source.count("collide_mrt_unforced(f);"), 1)
self.assertNotIn("collide_mrt_no_force(", source)
self.assertNotIn("compute_rho_u(f, rho, ux, uy);\n collide_mrt", source)
if __name__ == "__main__": unittest.main()
@@ -173,8 +173,10 @@ def bodies_and_jets(speed=.002):
return bodies,jets
KW=dict(base_block=(4,4),fine_block=(4,4),child_block=(4,4),
child_rectangles_in_parent=CHILDREN)
def levels(parents=PARENTS,children=CHILDREN,blocks=((4,4),)*3,objects=((),(),()),jets=((),(),())):
"""Level-list constructor keywords for the L0 set, L1 set and L2 set used here."""
return dict(refinements=[parents,children],level_blocks=list(blocks),
level_objects=list(objects),level_jets=list(jets))
def mock_backend(*, children=CHILDREN, bodies=False, fail_compile=False, fail_upload=False):
@@ -201,9 +203,8 @@ def mock_backend(*, children=CHILDREN, bodies=False, fail_compile=False, fail_up
module.cuda.memcpy_htod.side_effect=upload
objects,jets=bodies_and_jets() if bodies else ((),())
try:
run=module.FixedPatchStepper(CFG,PARENTS,context=context,
child_objects=objects,child_jets=jets,
**dict(KW,child_rectangles_in_parent=children))
run=module.FixedPatchStepper(CFG,context=context,
**levels(children=children,objects=((),(),objects),jets=((),(),jets)))
except RuntimeError:
for allocation in allocations:
allocation.free.assert_called_once_with()
@@ -214,28 +215,29 @@ def mock_backend(*, children=CHILDREN, bodies=False, fail_compile=False, fail_up
class ConstructorAndSchedule(unittest.TestCase):
def test_invalid_inputs_fail_before_context_or_allocations(self):
context=Mock()
cases=[dict(child=(8,8,16,16)),dict(child_rectangles_in_parent=[]),
dict(child_rectangles_in_parent=[(16,16,32)]),
dict(child_rectangles_in_parent=[(16.5,16,32,40)]),
dict(child_rectangles_in_parent=[(16,16,32,24),(16,27,32,55)]),
dict(child_rectangles_in_parent=[(40,16,48,40)]),
dict(child_rectangles_in_parent=[(8,16,32,40)]),
dict(child_block=None),dict(fine_block=None),dict(base_block=None),
dict(child_block=(5,4)),dict(fine_block=(5,4)),
dict(child_block=(4,)),dict(child_rectangles_in_parent=(16,16,32,40))]
b=(4,4)
cases=[dict(children=(8,8,16,16)),dict(children=[]),
dict(children=[(16,16,32)]),
dict(children=[(16.5,16,32,40)]),
dict(children=[(16,16,32,24),(16,27,32,55)]),
dict(children=[(40,16,48,40)]),
dict(children=[(8,16,32,40)]),
dict(blocks=(b,b,None)),dict(blocks=(b,None,b)),dict(blocks=(None,b,b)),
dict(blocks=(b,b,(5,4))),dict(blocks=(b,(5,4),b)),
dict(blocks=(b,b,(4,))),dict(children=(16,16,32,40))]
for changes in cases:
with self.subTest(changes=changes),self.assertRaises((ValueError,TypeError)):
host.FixedPatchStepper(CFG,PARENTS,context=context,**dict(KW,**changes))
host.FixedPatchStepper(CFG,context=context,**levels(**changes))
with self.assertRaisesRegex(ValueError,'margin'):
host.FixedPatchStepper(CFG,[(1,4,20,28),(23,4,44,28)],context=context,**KW)
host.FixedPatchStepper(CFG,context=context,**levels(parents=[(1,4,20,28),(23,4,44,28)]))
objects,jets=bodies_and_jets()
with self.assertRaisesRegex(ValueError,'only on L2'):
host.FixedPatchStepper(CFG,PARENTS,context=context,fine_objects=objects,**KW)
with self.assertRaisesRegex(ValueError,'only on the finest level'):
host.FixedPatchStepper(CFG,context=context,**levels(objects=((),objects,())))
from CelerisLab.body.jets import Jet,Tube,Parallel
spanning=Jet(Tube((10.5,14.),0.,25.,.3),Parallel(0.),amplitude=0.)
with self.assertRaisesRegex(ValueError,'one jet'):
host.FixedPatchStepper(CFG,PARENTS,context=context,child_objects=objects,
child_jets=[spanning],**KW)
host.FixedPatchStepper(CFG,context=context,
**levels(objects=((),(),objects),jets=((),(),[spanning])))
context.activate.assert_not_called()
host.cuda.mem_alloc.assert_not_called()
@@ -313,21 +315,23 @@ class ConstructorAndSchedule(unittest.TestCase):
class InitialLevels(unittest.TestCase):
"""initialize() entry adapter: positional per-level arrays or the legacy names, never both."""
class RemovedLegacyAPI(unittest.TestCase):
"""The pre-level-list constructor/initialize forms are gone and fail loudly."""
def test_forms(self):
a, b, c = object(), object(), object()
f = host._initial_levels
self.assertEqual(f((a, b), None, None, None), (a, b))
self.assertEqual(f((a, b, c), None, None, None), (a, b, c))
self.assertEqual(f((a, b), None, None, c), (a, b, c)) # old initialize(c, f, child_g=g)
self.assertEqual(f((), a, b, None), (a, b))
self.assertEqual(f((), a, b, c), (a, b, c))
for args in (((a,), None, None, c), ((a, b, c), None, None, c), ((a,), a, b, None),
((), a, None, None), ((), None, b, c)):
with self.subTest(args=args), self.assertRaises(TypeError):
f(*args)
def test_removed_constructor_forms_raise_type_error(self):
import inspect
context = Mock()
with self.assertRaises(TypeError): # positional bounds
host.FixedPatchStepper(CFG, PARENTS, context=context)
removed = dict(bounds=PARENTS, fine_block=(4, 4), base_block=(4, 4), fine_objects=(),
jets=(), child=(8, 8, 16, 16), child_block=(4, 4), child_objects=(),
child_jets=(), child_rectangles_in_parent=CHILDREN)
for name, value in removed.items():
with self.subTest(keyword=name), self.assertRaises(TypeError):
host.FixedPatchStepper(CFG, context=context, **levels(), **{name: value})
context.activate.assert_not_called()
self.assertEqual(list(inspect.signature(host.FixedPatchStepper.initialize).parameters),
["self", "level_g"]) # no coarse_g/fine_g/child_g
if __name__=='__main__':
+5 -6
View File
@@ -54,14 +54,13 @@ class ShiftedJets(unittest.TestCase):
(Jet(Tube((10.,14.),0.,26.,.3),Parallel(0.)),))]
for objects,jets in cases:
with self.subTest(objects=len(objects),jets=len(jets)),self.assertRaises(ValueError):
module.FixedPatchStepper(CFG,backend.PARENTS,context=None,
base_block=(4,4),fine_block=(4,4),child_block=(4,4),
child_rectangles_in_parent=A,child_objects=objects,child_jets=jets)
module.FixedPatchStepper(CFG,context=None,refinements=[backend.PARENTS,A],
level_blocks=[(4,4)]*3,level_objects=[(),(),objects],level_jets=[(),(),jets])
for blocks in ((None,None,None),((4,4),None,(4,4))):
with self.assertRaises(ValueError):
module.FixedPatchStepper(CFG,backend.PARENTS,context=None,
base_block=blocks[0],fine_block=blocks[1],child_block=blocks[2],
child_rectangles_in_parent=A,child_objects=(body(),),child_jets=(jet(),))
module.FixedPatchStepper(CFG,context=None,refinements=[backend.PARENTS,A],
level_blocks=list(blocks),level_objects=[(),(),(body(),)],
level_jets=[(),(),(jet(),)])
module.cuda.mem_alloc.assert_not_called()
module.compiler.compile_kernel.assert_not_called()
+4 -3
View File
@@ -129,9 +129,10 @@ class ShiftedStorage(unittest.TestCase):
def test_dense_or_mixed_shifted_rejected_before_compilation(self):
module=backend.host_module()
cfg=replace(backend.CFG,ddf_shifting=True)
for kwargs in ({},dict(base_block=(4,4)),dict(fine_block=(4,4))):
with self.assertRaisesRegex(ValueError,'all-blocked|base_block requires fine_block'):
module.FixedPatchStepper(cfg,(4,4,20,28),context=None,**kwargs)
for blocks in ([None,None],[(4,4),None],[None,(4,4)]):
with self.assertRaisesRegex(ValueError,'all-blocked|blocked refined levels below'):
module.FixedPatchStepper(cfg,context=None,refinements=[(4,4,20,28)],
level_blocks=blocks)
module.compiler.compile_kernel.assert_not_called()
def test_uniform_block_codec_and_raw_snapshot(self):
+75
View File
@@ -238,6 +238,81 @@ def test_overlapping_force_regions_rejected(device):
bodies.build_compact_lists(bodies.build_flags(field.flag))
@pytest.mark.parametrize("second_x,error", [(14., "unique cut-link writers"),
(17., "active fluid receivers")])
def test_passive_overlap_rejected_before_publishing_lists(second_x, error):
cfg = LBMConfig(nx=32, ny=24)
cfg.validate()
bodies = ObjectManager(cfg.nx, cfg.ny, cfg.nz, cfg.nq, cfg)
for x in (14., second_x):
bodies.add(obj(x=x, y=12., r=4.3))
bodies.add(obj(x=4., y=4., r=2., is_sensor=True))
counts = np.full(bodies.count, 91, np.int32)
hits = []
flags = bodies.build_flags(np.full(cfg.nx * cfg.ny, FLUID, np.uint16))
for domain_flags in (flags, None):
with pytest.raises(ValueError, match=error):
bodies.build_compact_lists_for(bodies.objects, domain_flags,
sensor_cell_counts_out=counts, hits_out=hits)
np.testing.assert_array_equal(counts, 91)
assert hits == []
@pytest.mark.parametrize("centers", [((10., 12.), (22., 12.)),
((10.5, 12.), (19.5, 12.))])
def test_separated_passive_bodies_keep_valid_writers(centers):
# The second case has a subcell physical gap with a resolved fluid column.
cfg = LBMConfig(nx=32, ny=24)
cfg.validate()
bodies = ObjectManager(cfg.nx, cfg.ny, cfg.nz, cfg.nq, cfg)
for x, y in centers:
bodies.add(obj(x=x, y=y, r=4.3))
flags = bodies.build_flags(np.full(cfg.nx * cfg.ny, FLUID, np.uint16))
indices, directions, _, ids, *_ = bodies.build_compact_lists(flags)
assert set(ids) == {0, 1}
assert np.all(flags[indices] & FLUID) and not np.any(flags[indices] & SOLID)
assert len(np.unique(indices.astype(np.uint64) * cfg.nq + directions)) == len(indices)
@pytest.mark.parametrize("entry", ["sync", "initialize", "runtime_edit"])
@pytest.mark.parametrize("second_x", [5., 6.])
def test_passive_overlap_failure_keeps_live_state(device, entry, second_x):
from CelerisLab.simulation import Simulation
field = make_field(device)
bodies = manager(field, [obj(), obj(x=9., y=3., r=1., is_sensor=True)])
bodies.sync_to_gpu(field)
overlapping = obj(x=second_x)
if entry == "runtime_edit":
bodies.stage_add(overlapping)
else:
bodies.add(overlapping)
objects = bodies.objects
flags, curved, counts = field.flag.copy(), field.curved.fluid_idx.copy(), bodies.sensor_cell_counts.copy()
action = bodies.action.copy()
buffers = [(block, bytes(block.data), block.freed) for block in device.blocks]
writes = device.writes
sim = SimpleNamespace(bodies=bodies, field=field, lbm_cfg=field.cfg,
_initialized=entry == "runtime_edit",
_assert_allocation_contract=lambda: None,
stream=SimpleNamespace(synchronize=device.synchronize))
with pytest.raises(ValueError, match="active fluid receivers|unique cut-link writers"):
if entry == "sync":
bodies.sync_to_gpu(field)
elif entry == "initialize":
Simulation.initialize(sim)
else:
Simulation.sync_bodies(sim)
assert bodies.objects == objects
assert bodies.has_pending_edit() == (entry == "runtime_edit")
assert sim._initialized == (entry == "runtime_edit")
assert device.writes == writes and len(device.blocks) == len(buffers)
assert all(bytes(block.data) == data and block.freed == freed for block, data, freed in buffers)
np.testing.assert_array_equal(field.flag, flags)
np.testing.assert_array_equal(field.curved.fluid_idx, curved)
np.testing.assert_array_equal(bodies.sensor_cell_counts, counts)
np.testing.assert_array_equal(bodies.action, action)
def test_action_upload_and_scratch_are_pinned(device):
field = make_field(device, streaming="esopull")
bodies = manager(field, [obj(is_force_region=True)])
+170
View File
@@ -0,0 +1,170 @@
"""Host contract of FixedPatchStepper.step(n): one stream wait per call (mocked driver).
All n base intervals are enqueued in order on the backend stream and the host
waits once before step returns. Launch order and buffer arguments must equal n
step(1) calls; completion metadata, raw-exchange and window ledgers, and failure
invalidation are published only after that wait.
"""
from contextlib import nullcontext
from unittest.mock import Mock
import unittest
import numpy as np
from CelerisLab.config import LBMConfig
from tests.unit.test_raw_exchange import body
from tests.unit.test_refinement_three_level_multipatch import host_module
BODY_LEVEL, HOPS = 3, 8 # body on L3: 2**3 hops per base interval
def backend(window=False):
"""Four-level host backend; every launch, memset and stream wait goes to one log."""
host = host_module()
log, allocations = [], []
def allocate(size):
allocations.append(Mock(size=size))
return allocations[-1]
module = Mock()
module.get_global.return_value = (Mock(), 20)
module.get_function.side_effect = lambda name: Mock(
side_effect=lambda *a, **k: log.append((name, a, k)))
host.compiler.load_module.return_value = module
host.cuda.mem_alloc.side_effect = allocate
host.cuda.memcpy_dtoh.side_effect = lambda array, pointer: array.fill(0)
host.cuda.memset_d8_async.side_effect = lambda *a: log.append(("memset", a, {}))
run = host.FixedPatchStepper(
LBMConfig(nx=48, ny=48, viscosity=.02), context=Mock(activate=nullcontext, sm_arch="sm_70"),
refinements=[[(6, 6, 26, 26)], [(20, 20, 44, 44)], [(56, 56, 72, 72)]],
level_blocks=[(4, 4)] * 4, level_objects=[(), (), (), (body(),)],
observe_raw_exchange=True, observe_window_exchange=window)
run._stream.synchronize.side_effect = lambda: log.append(("sync", (), {}))
run.initialize(*[np.full(level.shape, 1 / 9, np.float32) for level in run._levels])
log.clear()
return run, log, allocations
def signature(log, allocations):
"""Event names with device-pointer arguments replaced by allocation index."""
index = {id(a): i for i, a in enumerate(allocations)}
return [(name, tuple(index.get(id(a), "-") for a in args)) for name, args, _ in log]
def names(log):
return [name for name, _, _ in log]
class StepSync(unittest.TestCase):
def test_step1_waits_once_after_all_launches(self):
run, log, _ = backend()
run.step(1)
self.assertEqual(names(log).count("sync"), 1)
self.assertEqual(names(log)[-1], "sync")
self.assertEqual(names(log)[0], "memset")
self.assertEqual(names(log).count("BlockStep"), 1 + 2 + 4 + 8)
self.assertEqual(run.step_count, 1)
run.close()
def test_step_n_equals_n_step1_launches_with_one_wait(self):
single, single_log, single_alloc = backend()
for _ in range(3):
single.step(1)
batched, batched_log, batched_alloc = backend()
batched.step(3)
expected = [e for e in signature(single_log, single_alloc) if e[0] != "sync"]
got = signature(batched_log, batched_alloc)
self.assertEqual(got[-1][0], "sync")
self.assertEqual(names(batched_log).count("sync"), 1)
self.assertEqual(got[:-1], expected) # same order, same ping-pong buffers
self.assertEqual(names(batched_log).count("memset"), 3)
self.assertEqual(batched.step_count, single.step_count)
index = [{id(a): i for i, a in enumerate(alloc)} for alloc in (single_alloc, batched_alloc)]
self.assertEqual(index[1][id(batched._levels[0].current)],
index[0][id(single._levels[0].current)])
single.close()
batched.close()
def test_step0_launches_and_waits_for_nothing(self):
run, log, _ = backend()
run.step(2)
log.clear()
run.step(0)
self.assertEqual(log, [])
self.assertEqual(run.step_count, 2)
value = run.read_raw_exchange(0, level=BODY_LEVEL) # step(0) keeps the ledger valid
self.assertEqual((value["time_start"], value["time_end"]), (1, 2))
run.close()
def test_completion_metadata_covers_all_intervals(self):
run, _, _ = backend()
with self.assertRaisesRegex(RuntimeError, "completed"):
run.read_raw_exchange(0, level=BODY_LEVEL)
run.step(3)
value = run.read_raw_exchange(0, level=BODY_LEVEL)
self.assertEqual((value["time_start"], value["time_end"], value["sample_count"]),
(2, 3, HOPS)) # step(n) retains only the final base interval
run.step(2)
self.assertEqual(run.read_raw_exchange(0, level=BODY_LEVEL)["time_end"], 5)
run.close()
def test_window_accounting_across_batched_calls(self):
windows = []
for calls in ((1, 3), (4,), (1, 1, 1, 1)):
run, log, _ = backend(window=True)
run.step(1)
run.start_exchange_window()
log.clear()
for n in calls:
run.step(n)
self.assertEqual(names(log).count("BlockAccumulateExchange"), 2 * 4 * HOPS)
self.assertEqual(names(log).count("sync"), len(calls))
out = run.read_exchange_window(0, level=BODY_LEVEL)
windows.append((out["time_start"], out["time_end"], out["sample_count"]))
run.close()
self.assertEqual(windows, [(1., 5, 4 * HOPS)] * 3)
def test_failed_wait_publishes_nothing(self):
run, _, _ = backend(window=True)
run.step(2)
run.start_exchange_window()
run._stream.synchronize.side_effect = RuntimeError("device failure")
with self.assertRaisesRegex(RuntimeError, "device failure"):
run.step(3)
self.assertEqual(run.step_count, 2) # value at entry to the failing call
self.assertFalse(run._exchange_valid)
self.assertFalse(run._window_valid)
for read in (lambda: run.read_raw_exchange(0, level=BODY_LEVEL),
lambda: run.read_exchange_window(0, level=BODY_LEVEL), run.download,
lambda: run.step(1)):
with self.assertRaisesRegex(RuntimeError, "failed"):
read()
run._stream.synchronize.side_effect = None
run.close()
def test_launch_error_mid_batch_skips_wait_and_fails(self):
run, log, _ = backend()
run.step(1)
log.clear()
hop, calls = run._hop, []
def failing(index, *args, **kw):
if index == 0:
calls.append(1)
if len(calls) == 2:
raise RuntimeError("launch failure")
return hop(index, *args, **kw)
run._hop = failing
with self.assertRaisesRegex(RuntimeError, "launch failure"):
run.step(3)
self.assertNotIn("sync", names(log))
self.assertEqual(run.step_count, 1)
self.assertFalse(run._exchange_valid)
with self.assertRaisesRegex(RuntimeError, "failed"):
run.read_raw_exchange(0, level=BODY_LEVEL)
run.close()
if __name__ == "__main__":
unittest.main()
@@ -0,0 +1,110 @@
{
"base_commit": "a135252ae78b47b57d7e77d19001700b3bedac8b",
"production_origin_commit": "a135252ae78b47b57d7e77d19001700b3bedac8b",
"source_experiment": "Explicit a135252 uniform SRT LES regression. Sources pin the committed corrected tree; baseline is a synthetic isolated reverse-header control, not the committed a135252 source. Historical profiles and receipts remain unchanged.",
"sources": {
"src/CelerisLab/__init__.py": "21cc469bd6e970a1f9ff5970c8eea4602065e41fc881854759ee565ee55c10c6",
"src/CelerisLab/body/__init__.py": "e4e0e8f0769a94428d5b02fac790443997556cfc5515a5f1ed1595d2c694d69d",
"src/CelerisLab/body/action_smoother.py": "b1a23ee6bbd4850b172cb8738c5c3546ee465a54189e6af9d8044f023d4687dc",
"src/CelerisLab/body/coupling/__init__.py": "c931f7eb318d48408c3e2febcc6917c88c8dcc1697cbf4329b1f340d94c35763",
"src/CelerisLab/body/coupling/soa_packer.py": "8ec26fd55ef74801bbd5ab6bd3d0a7dabc750cbd498aaac2ca4c61a0108ad3c9",
"src/CelerisLab/body/ddf_patch.py": "60fcfb7441e73bf290bcff41ca3a83da3e7ddad765d7247464e8f02e3043b4e2",
"src/CelerisLab/body/geometry/__init__.py": "ada88980ab672959aca9aa3a4c4aade3219524b2ab68110cd2a2f41e3e0ca90a",
"src/CelerisLab/body/geometry/base.py": "cceca14361ca2f34d34a3e43730e1a79b8ca81be00f0dd62e884db32b479419f",
"src/CelerisLab/body/geometry/circle.py": "7605ca7c21103f1d801ac73ab8dd18dffbdac425b2dee7b8858b283628a9e436",
"src/CelerisLab/body/jets.py": "4104c24af4651f4bb4f8d8fd36fb6d88f41c6e4469822f36e22e74c9ede31dac",
"src/CelerisLab/body/manager.py": "01b653d25bd9b4333379c8bfd12383596b686d2029f2e91b1c91b618540ec6b3",
"src/CelerisLab/body/objects.py": "8e63cee8faa9cc6243bcff428be628dfad73a02a9a3b8ece7d78c0a63406a08d",
"src/CelerisLab/body/preprocess/__init__.py": "dfd9d58bc07f626ab23a70053e31b88a6d9165d2e4c76a4e9f48abe674d3d2ec",
"src/CelerisLab/body/preprocess/flag_overlay.py": "831fc9e9736b758847759a085ff133eb49ec91318ace4fda76f85960138ee300",
"src/CelerisLab/body/registry.py": "fbb7327780adbdc6da15ebdb799980daf32df22ee974af0893d7409f177bbb68",
"src/CelerisLab/body/sync_plan.py": "3a15bfe9ebeb91482dbfc68850761ef39c872cc12d2efc795babd0c01e392323",
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}
@@ -0,0 +1,425 @@
"""Bounded exact-source CUDA plumbing gate; never a flow-accuracy certificate.
Run this driver externally against exact dev with --mode baseline first, then
against the experimental source with --mode candidate --baseline <receipt>.
Only scalar receipts/hashes and actual compiler sidecars are retained. Whole-step
mass/momentum are diagnostics: no verified FP32 conservation bound is claimed.
"""
import argparse
from contextlib import contextmanager
from dataclasses import replace
import hashlib
import json
import os
import shutil
from pathlib import Path
import subprocess
import sys
import numpy as np
BASE = 'ed9d8c937d446b854d6963bd92d718bb4fb98b96'
PRODUCTION = 'a135252ae78b47b57d7e77d19001700b3bedac8b'
STOPS = (0, 1, 2, 8)
OPERATOR_ATOL, OPERATOR_RTOL = 6e-8, 2e-7
REST_ATOL, REST_RTOL = 3e-7, 1e-6
REPLAY_ATOL = 3e-6
E = np.array([(0,0),(1,0),(-1,0),(0,1),(0,-1),(1,1),(-1,-1),(1,-1),(-1,1)])
W = np.array([4/9]+[1/9]*4+[1/36]*4)
def digest(array):
"""All finite bits (including signed zero) and exact NaN mask; no NaN payloads."""
array = np.asarray(array)
if np.isinf(array).any():
raise AssertionError('infinite population')
finite = np.isfinite(array)
h = hashlib.sha256()
h.update(str((array.shape, array.dtype.str)).encode())
h.update(np.ascontiguousarray(finite).tobytes())
h.update(np.ascontiguousarray(array[finite]).tobytes())
return h.hexdigest()
def independent_explosion(coarse, pair, layout, kind):
"""Coordinate oracle; never reads the production neighbor/offset tables."""
ny, nx = pair.coarse_shape
legal = np.zeros((ny,nx), bool)
legal.ravel()[pair.ghost_coarse] = True
legal &= layout.owned & ~pair.covered & (kind == 0)
if not legal.ravel()[pair.ghost_coarse].all():
raise AssertionError('illegal center donor')
out = np.empty((9,len(pair.ghost_fine)))
flat = np.asarray(coarse, np.float64).reshape(9,-1)
for row, (target, donor) in enumerate(zip(pair.ghost_fine,pair.ghost_coarse)):
y,x = divmod(int(donor),nx)
gradient = np.zeros((9,2))
for axis, (dx,dy) in enumerate(((1,0),(0,1))):
ends = [(x-dx,y-dy),(x+dx,y+dy)]
if not layout.periodic[axis] and any(not (0<=xx<nx and 0<=yy<ny) for xx,yy in ends):
continue
ends = [(xx%nx,yy%ny) for xx,yy in ends]
if all(legal[yy,xx] for xx,yy in ends):
(xm,ym),(xp,yp) = ends
gradient[:,axis] = (flat[:,yp*nx+xp]-flat[:,ym*nx+xm])/2
for q in range(1,9):
gradient[q] -= E[q]*np.dot(E[q],gradient[q])/np.dot(E[q],E[q])
fy,fx = divmod(int(target),pair.fine_shape[1])
offset = np.array([pair.fine_origin[0]+(fx+.5)/2-(x+.5),
pair.fine_origin[1]+(fy+.5)/2-(y+.5)])
out[:,row] = flat[:,int(donor)] + gradient@offset
return out
def default_options(selector):
# Exact dev has no explosion keyword. Baseline and omitted paths pass none.
return {} if selector == 'omitted' else {'explosion':selector}
def snapshot(run, raw):
from CelerisLab.lbm.refinement import ACTIVE, OUTER_GHOST
stored, public = raw(run), run.download()
hashes, totals = [], np.zeros(3)
for level,(values,visible,kind) in enumerate(zip(stored,public,run.hierarchy.kinds)):
active = kind == ACTIVE
if not np.isfinite(visible[:,active]).all() or not np.isnan(visible[:,~active]).all():
raise AssertionError('public ACTIVE/invalid mask mismatch')
if not np.isnan(values[:,kind==OUTER_GHOST]).all():
raise AssertionError('OUTER owner core is not poisoned')
population = visible[:,active].sum(axis=1,dtype=np.float64)*(.25**level)
totals += np.r_[population.sum(), E.T@population]
hashes.append(dict(raw=digest(values), public=digest(visible), active=int(active.sum())))
if not np.isfinite(totals).all():
raise AssertionError('nonfinite mass/momentum diagnostic')
return dict(step=run.step_count, levels=hashes, mass_momentum=totals.tolist())
def initialize(run, rest=False):
arrays, origin, spacing = [], np.zeros(2), 1.
for index,level in enumerate(run._levels):
if index:
origin += spacing*np.asarray(run.hierarchy.pairs[index-1].fine_origin)
spacing /= 2
y,x = np.indices(level.shape[1:],dtype=np.float64)
x,y = origin[0]+spacing*(x+.5),origin[1]+spacing*(y+.5)
q = np.arange(9)[:,None,None]
values = np.broadcast_to(W[:,None,None],level.shape).copy()
if not rest:
# q-distinct smooth non-equilibrium G; same physical frame on all levels.
values += 1e-4*np.sin(.17*x+.23*y+q)
arrays.append(values)
run.initialize(*arrays)
def operator_case(run, index):
import pycuda.driver as cuda
parent,child = run._levels[index:index+2]
geometry,pair = run.hierarchy.pairs[index],run._pairs[index]
c = np.random.default_rng(19+index).normal(0,.001,(9,*geometry.coarse_shape))
if not run._ddf_shifting:
c += W[:,None,None]
c = c.astype(np.float32)
legal = np.zeros(geometry.coarse_shape,bool)
legal.ravel()[geometry.ghost_coarse] = True
c[:,~legal] = np.nan
packed = parent.layout.to_blocked(c)
output = np.full(child.layout.blocked_shape,np.nan,np.float32)
cuda.memcpy_htod(parent.current,packed)
cuda.memcpy_htod(child.current,output)
calls, hop = [],run._hop
try:
run._hop = lambda *a,**kw: calls.append(a)
run._advance(index+1,parent.current,block=run._block,stream=run._stream)
run._stream.synchronize()
finally:
run._hop = hop
if calls != [(index+1,child.current,child.spare),(index+1,child.spare,child.current)]:
raise AssertionError('explosion changed two-hop launch contract')
cuda.memcpy_dtoh(output,child.current)
target = child.layout.owner.ravel()[geometry.ghost_fine]
slots = np.array([child.layout.slot(target,q) for q in range(9)])
actual = output.ravel()[slots]
expected = independent_explosion(c,geometry,parent.layout,run.hierarchy.kinds[index])
constant = c.reshape(9,-1)[:,geometry.ghost_coarse]
if not np.isfinite(actual).all() or np.max(abs(expected-constant)) <= 1e-5:
raise AssertionError('operator must exercise finite nonzero projected slopes')
np.testing.assert_allclose(actual,expected,atol=OPERATOR_ATOL,rtol=OPERATOR_RTOL)
untouched = np.ones(output.size,bool); untouched[slots.ravel()] = False
if not np.isnan(output.ravel()[untouched]).all():
raise AssertionError('explosion wrote outside its targets')
return dict(pair=index,rows=len(target),parent_stride=pair.parent_cells,
child_stride=int(np.prod(child.layout.local_shape)),
max_error_by_q=np.max(abs(actual-expected),axis=1).tolist(),
nonzero_projection=True,poisoned_nondonors=True,untouched_preserved=True)
def replay_two_hops(values, pair, layout, kind):
"""Existing FP64 two-hop algebra, using the independent coordinate oracle."""
from tests.unit.test_projected_explosion import collide
coarse,fine = (a.copy() for a in values)
fine.reshape(9,-1)[:,pair.ghost_fine] = independent_explosion(coarse,pair,layout,kind)
for _ in range(2):
fine = np.array([np.roll(fine[q],(ey,ex),(0,1)) for q,(ex,ey) in enumerate(E)])
fine[:,pair.fine_kind==2] = np.nan
active = pair.fine_kind==0
fine[:,active] = collide(fine[:,active],pair.tau_fine)
out = np.array([np.roll(coarse[q],(ey,ex),(0,1)) for q,(ex,ey) in enumerate(E)])
out.reshape(-1)[pair.coalesce_coarse] = fine.reshape(-1)[pair.coalesce_fine].mean(axis=1)
out[:,~pair.covered] = collide(out[:,~pair.covered],pair.tau_coarse)
out[:,pair.covered] = np.nan
return out,fine
def run_case(ctx, case, shifted, selector, raw, projected=False, replay=False):
from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
cfg,refs,blocks = case
cfg = replace(cfg,velocity=0,ddf_shifting=shifted)
with FixedPatchStepper(cfg,context=ctx,refinements=refs,level_blocks=blocks,
**default_options(selector)) as run:
operator = [operator_case(run,i) for i in range(len(run._pairs))] if projected else []
counts = [0]*len(run._levels)
for index,level in enumerate(run._levels):
def counted(*a, index=index, kernel=level.kernel, **kw):
counts[index] += 1
return kernel(*a,**kw)
level.kernel = counted
def check_counts(stop):
if counts != [stop*2**index for index in range(len(counts))]:
raise AssertionError('actual level hop counts differ from acoustic schedule')
rest = []
if projected:
initialize(run,rest=True)
for stop in STOPS:
run.step(stop-run.step_count)
check_counts(stop)
snapshot(run,raw) # actual public and raw invalid masks at every stop
maximum = 0.
for values,kind in zip(run.download(),run.hierarchy.kinds):
active = values[:,kind==0]
np.testing.assert_allclose(active,np.broadcast_to(W[:,None],active.shape),
atol=REST_ATOL,rtol=REST_RTOL)
maximum = max(maximum,float(np.max(abs(active-W[:,None]))))
rest.append(dict(step=stop,max_absolute_error=maximum))
counts[:] = [0]*len(counts)
initialize(run)
reference = tuple(a.astype(np.float64) for a in run.download()) if replay else None
snapshots,replay_errors,previous = [],[],0
for stop in STOPS:
run.step(stop-run.step_count)
if replay:
for _ in range(stop-previous):
reference = replay_two_hops(reference,run.hierarchy.pairs[0],
run._levels[0].layout,run.hierarchy.kinds[0])
errors = []
for actual,expected,kind in zip(run.download(),reference,run.hierarchy.kinds):
np.testing.assert_allclose(actual[:,kind==0],expected[:,kind==0],
atol=REPLAY_ATOL,rtol=0)
errors.append(np.max(abs(actual[:,kind==0]-expected[:,kind==0]),axis=1).tolist())
replay_errors.append(dict(step=stop,max_error_by_level_q=errors))
check_counts(stop)
snapshots.append(dict(snapshot(run,raw),observed_level_hops=counts.copy())); previous = stop
change = (np.array(snapshots[-1]['mass_momentum'])-
np.array(snapshots[0]['mass_momentum'])).tolist()
return dict(operator=operator,snapshots=snapshots,rest_fixed_point=rest,
replay_max_errors=replay_errors,mass_momentum_change_diagnostic=change,
conservation_status='diagnostic_only_no_FP32_bound')
def compare_snapshots(actual,expected):
if len(actual) != len(expected):
raise AssertionError('snapshot count differs')
for got,want in zip(actual,expected):
if (got['step'] != want['step'] or got['levels'] != want['levels']
or got.get('observed_level_hops') != want.get('observed_level_hops')):
raise AssertionError('owner bits, public values or masks differ')
def cases():
from CelerisLab.config import LBMConfig
from tests.unit.test_hierarchy import CFG, FOUR
scalar = (LBMConfig(nx=16,ny=16,viscosity=.02),
[(4,4,12,12),(8,8,16,16),(8,8,16,16)],
[(4,4),(4,8),(6,4),(4,6)])
four = (CFG,FOUR,[(6,8),(8,6),(12,8),(16,12)])
concave = (LBMConfig(nx=30,ny=30,viscosity=.1),
[[(4,4,5,7),(4,5,7,7)]],[(6,5),(4,6)])
return dict(scalar=scalar,four=four,concave=concave)
def baseline_receipt(receipt, driver_hash, keys):
if (receipt.get('completed') is not True or receipt.get('dry_run') is not False
or receipt.get('mode') != 'baseline' or receipt.get('production_revision') != BASE
or receipt.get('source',{}).get('revision') != BASE
or receipt.get('source',{}).get('dirty') is not False
or receipt.get('driver_sha256') != driver_hash
or receipt.get('stops') != list(STOPS)
or receipt.get('operator_tolerance') != [OPERATOR_ATOL,OPERATOR_RTOL]
or receipt.get('rest_tolerance') != [REST_ATOL,REST_RTOL]
or receipt.get('replay_tolerance') != [REPLAY_ATOL,0]
or set(receipt.get('default_snapshots',{})) != set(keys)
or not receipt.get('actual_build_sidecars')):
raise ValueError('baseline receipt does not match the frozen exact-dev gate')
return receipt
def remap_case(ctx, shifted, raw):
from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
cfg,refs,blocks = cases()['four']
with FixedPatchStepper(replace(cfg,velocity=0,ddf_shifting=shifted),context=ctx,
refinements=refs[:2],level_blocks=blocks[:3],explosion='projected_linear') as run:
initialize(run); run.step(1)
before = snapshot(run,raw)
with run.remap_child([(22,22,42,42),(72,68,76,76)]) as clone:
if clone._explosion != 'projected_linear' or any(p.neighbors is None for p in clone._pairs):
raise AssertionError('remap lost projected selection')
if clone.step_count != 1: raise AssertionError('remap lost synchronized count')
initial = snapshot(clone,raw)
clone.step(1)
after = snapshot(clone,raw)
if clone.step_count != 2: raise AssertionError('remap did not continue count')
compare_snapshots([snapshot(run,raw)],[before])
return dict(shifted=shifted,source_unchanged=True,initial=initial,continued=after)
@contextmanager
def capture_builds(report, save, baseline=None):
from CelerisLab.cuda import compiler_v2 as compiler
original = compiler.load_module
def load(path):
path = Path(path)
metadata = json.loads(Path(str(path)+'.json').read_text())
if metadata['ptx_sha256'] != hashlib.sha256(path.read_bytes()).hexdigest():
raise AssertionError('actual PTX and build sidecar disagree')
if baseline and (metadata['arch'],metadata['flags']) not in [
(m['arch'],m['flags']) for m in baseline['actual_build_sidecars']]:
raise AssertionError('baseline build architecture or flags differ')
report['actual_build_sidecars'].append(metadata)
save() # capture AMR metadata before production cleanup removes scratch
return original(str(path))
compiler.load_module = load
try:
yield
finally:
compiler.load_module = original
def preflight(repo, revision, mode):
git = lambda *a: subprocess.check_output(['git','-C',str(repo),*a],text=True).strip()
if git('rev-parse','HEAD') != revision or git('status','--porcelain'):
raise ValueError('requires the exact expected clean checkout')
source = BASE if mode == 'baseline' else PRODUCTION
if mode == 'baseline' and revision != BASE:
raise ValueError('baseline must be exact ed9d8c9')
if subprocess.call(['git','-C',str(repo),'diff','--quiet',source,'--','src']):
raise ValueError('production source differs from the frozen source revision')
return source
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--repo',type=Path,required=True)
parser.add_argument('--expected-revision',required=True)
parser.add_argument('--mode',choices=('baseline','candidate'),required=True)
parser.add_argument('--baseline',type=Path)
parser.add_argument('--output',type=Path,required=True)
parser.add_argument('--run-gpu',action='store_true')
parser.add_argument('--dry-run',action='store_true')
args = parser.parse_args()
if args.output.exists(): parser.error('output already exists')
selected = os.environ.get('CUDA_VISIBLE_DEVICES','')
if not args.dry_run and (not args.run_gpu or not selected or ',' in selected or selected=='-1'):
parser.error('--run-gpu and exactly one explicit CUDA_VISIBLE_DEVICES are required')
repo = args.repo.resolve()
source = preflight(repo,args.expected_revision,args.mode)
baseline = None
if args.mode == 'candidate':
if args.baseline is None: parser.error('candidate requires --baseline receipt')
baseline = json.loads(args.baseline.read_text())
sys.path[:0] = [str(repo/'src'),str(repo),str(repo/'tests/validation/multigrid'),
str(repo/'tests/validation/taylor_green')]
import CelerisLab
if Path(CelerisLab.__file__).resolve() != repo/'src/CelerisLab/__init__.py':
raise RuntimeError('wrong imported checkout')
from run_case import provenance
driver_hash = hashlib.sha256(Path(__file__).read_bytes()).hexdigest()
keys = [f'{name}:shifted={shifted}' for name in cases() for shifted in (False,True)]
if baseline is not None: baseline_receipt(baseline,driver_hash,keys)
report = dict(mode=args.mode,production_revision=source,source=provenance(repo),
driver_sha256=driver_hash,
device_selection=selected,completed=False,dry_run=args.dry_run,
operator_tolerance=[OPERATOR_ATOL,OPERATOR_RTOL],
rest_tolerance=[REST_ATOL,REST_RTOL],replay_tolerance=[REPLAY_ATOL,0],stops=STOPS,
conservation_status='diagnostic_only_no_FP32_bound',
actual_build_sidecars=[],default_snapshots={},default_equivalence=[],
projected_operator=[],union_multilevel_smoke=[],changed_remap=[])
args.output.parent.mkdir(parents=True,exist_ok=True)
def save():
text = json.dumps(report,indent=2,allow_nan=False)+'\n'
if len(text.encode()) > 8*1024*1024: raise RuntimeError('receipt exceeds 8 MiB cap')
temporary = args.output.with_suffix(args.output.suffix+'.tmp')
temporary.write_text(text); os.replace(temporary,args.output)
save()
if args.dry_run:
print('Source preflight only; no CUDA imports or execution.'); return
try:
from CelerisLab.cuda.context import CudaContext
from test_refinement_blocked_base import raw
with CudaContext(0) as ctx, capture_builds(report,save,baseline):
import pycuda.driver as cuda
report['device'] = dict(name=ctx.device.name(),pci_bus_id=ctx.device.pci_bus_id(),
capability=list(ctx.device.compute_capability()),
driver=cuda.get_driver_version(),runtime=list(cuda.get_version()))
nvcc = shutil.which('nvcc') or '/usr/local/cuda/bin/nvcc'
report['nvcc_version'] = subprocess.check_output([nvcc,'--version'],text=True).strip()
if baseline and (report['device'] != baseline.get('device')
or report['nvcc_version'] != baseline.get('nvcc_version')
or selected != baseline.get('device_selection')):
raise ValueError('baseline GPU/device selection or toolchain differs')
for name,case in cases().items():
for shifted in (False,True):
key = f'{name}:shifted={shifted}'
report['active_case'] = f'default:{key}'
result = run_case(ctx,case,shifted,'omitted',raw)
report['default_snapshots'][key] = result['snapshots']
if baseline:
compare_snapshots(result['snapshots'],baseline['default_snapshots'][key])
explicit = run_case(ctx,case,shifted,'constant',raw)
compare_snapshots(explicit['snapshots'],result['snapshots'])
report['default_equivalence'].append(dict(case=key,passed=True))
save()
if baseline:
for name,case in cases().items():
for shifted in (False,True):
report['active_case'] = f'projected:{name}:shifted={shifted}'
result = run_case(ctx,case,shifted,'projected_linear',raw,True,name=='concave')
cfg,refs,blocks = case
if name == 'four':
variant_refs = [list(reversed(rects)) for rects in refs]
elif name == 'concave':
variant_refs = [[(4,5,7,7),(4,4,5,5)]] # same union, disjoint decomposition
else:
variant_refs = refs
variant = (cfg,variant_refs,[(2,2)]*len(blocks))
alternate = run_case(ctx,variant,shifted,'projected_linear',raw,True)
compare_snapshots(alternate['snapshots'],result['snapshots'])
report['projected_operator'].append(dict(case=name,shifted=shifted,rows=result['operator']))
report['union_multilevel_smoke'].append(dict(case=name,shifted=shifted,result=result,
alternate_bits_identical=True))
save()
for shifted in (False,True):
report['active_case'] = f'changed-remap:shifted={shifted}'
report['changed_remap'].append(remap_case(ctx,shifted,raw)); save()
expected_builds = {(s['arch'],tuple(s['flags'])) for s in baseline['actual_build_sidecars']}
actual_builds = {(s['arch'],tuple(s['flags'])) for s in report['actual_build_sidecars']}
if actual_builds != expected_builds:
raise AssertionError('baseline build architecture or compiler flags differ')
report['completed'] = True
save()
except Exception as error:
report['error'] = f'{type(error).__name__}: {error}'
save(); raise
print(json.dumps(dict(completed=True,mode=args.mode,receipt=str(args.output))))
if __name__ == '__main__':
main()
@@ -1,263 +0,0 @@
"""Four opt-in shifted GPU controls: U64/U128/U256 and refined base128/fine256."""
import argparse
import hashlib
import inspect
import json
import os
from pathlib import Path
import resource
import subprocess
import time
import numpy as np
import run_spacetime_gpu_n64 as old
gpu,ref,tg,ROOT = old.gpu,old.ref,old.tg,old.ROOT
BASE='26d0d3853c9d4d3cd6ae3f27653dced56f8c5fec'
REFERENCE_SHA='9d154c989b087bf288f86d413db0f3067b73767b618c329d4b9e53c4eee00032'
CASES=(('uniform64',64,False),('uniform128',128,False),('uniform256',256,False),('refined128',128,True))
LIMITS=old.LIMITS
SECONDS,RSS_MIB=600.,512.
def setup(n, refined):
return dict(base_n=n,finest_n=2*n if refined else n,normalized_domain=[0.,1.,0.,1.],
re_L=100,U=.03,mach=.03*np.sqrt(3),viscosity=.0003*n,
tau=[.5+.0009*n]+([.5+.0018*n] if refined else []),
bounds=[n//8,n//8,7*n//8,3*n//4] if refined else None,
normalized_patch=[.125,.125,.875,.75] if refined else None,
intervals=16*n,sample_steps=[4*n,8*n,12*n,16*n],sample_times=list(old.TIMES),
early_steps=list(range(0,4*n+1,n//16)),early_times=(np.arange(65)*.001875).tolist(),
phase='arrival_f',storage='shifted_FP32',collision='SRT',
initialization='common analytic FP64 equilibrium at actual cell centers, production shifted codec')
def pressure_projection(arrays,masks,t,n,viscosity):
"""One global gauge and a weighted Gram fit, including unequal leaf areas."""
rows=[]
for level,(a,mask) in enumerate(zip(arrays,masks)):
rho=np.asarray(a[:,mask],np.float64).sum(axis=0)
x,y=tg.centers(mask.shape,level); x,y=x[mask],y[mask]
exact=tg.exact(x,y,t,n,viscosity)[2]
angle=4*np.pi/n
basis=np.column_stack((np.cos(angle*x),np.sin(angle*x),np.cos(angle*y),np.sin(angle*y)))
rows.append(((rho-1)/3,exact,np.full(len(rho),.25**level),basis))
p,exact,w,b=[np.concatenate(x) for x in zip(*rows)]
volume=w.sum(); p-=w@p/volume; exact-=w@exact/volume; e=p-exact
b-=w@b/volume
gram=b.T@(w[:,None]*b); rhs=b.T@(w*e)
coefficients=np.linalg.solve(gram,rhs); residual=e-b@coefficients
norm=float(w@(e*e)); exact_norm=float(w@(exact*exact)); remaining=float(w@(residual*residual))
projected=float(coefficients@gram@coefficients)
return dict(step=t,tstar=t*.03/n,absolute_rms=np.sqrt(norm/volume),relative_rms=np.sqrt(norm/exact_norm),
coefficients=coefficients.tolist(),basis=['cos_4pi_x','sin_4pi_x','cos_4pi_y','sin_4pi_y'],
residual_rms=np.sqrt(remaining/volume),residual_relative=np.sqrt(remaining/exact_norm),
gram_condition=float(np.linalg.cond(gram)),
orthogonality=(b.T@(w*residual)/volume).tolist(),energy_closure=(norm-projected-remaining)/volume)
def load_reference(path):
if old.sha(path)!=REFERENCE_SHA:
raise ValueError('verified shifted N64 receipt differs')
data=json.loads(Path(path).read_text())
if (not data['completed'] or not data['passed'] or data['source']['commit']!=BASE
or data['setup']['storage']!='shifted_FP32' or data['setup']['bounds']!=[8,8,56,48]
or data['setup']['interval_count']!=1024 or len(data['rows'])!=4):
raise ValueError('N64 reference identity differs')
if tuple(row['tstar'] for row in data['rows'])!=old.TIMES:
raise ValueError('N64 reference sample times differ')
return data
def source_identity(reference):
git=lambda *args:subprocess.check_output(['git',*args],cwd=ROOT,text=True).strip()
if git('status','--porcelain'):
raise RuntimeError('clean committed checkout required')
unchanged=['src','tests/validation/taylor_green/oracle.py']+[f'tests/validation/multigrid/{name}' for name in
('spacetime_gpu.cu','spacetime_reference.py','cpu_reference.py','run_spacetime_gpu_n64.py','test_spacetime_gpu.py')]
subprocess.check_call(['git','diff','--exit-code',BASE,'--',*unchanged],cwd=ROOT)
previous=subprocess.check_output(['git','show',f'{BASE}:tests/validation/multigrid/spacetime_gpu.py'],cwd=ROOT,text=True)
# The raw interval schedule remains byte-for-byte unchanged despite the new owner.
method=inspect.getsource(gpu.SpaceTimeGPU.step)
if method not in previous or np.__version__!=reference['source']['numpy']:
raise RuntimeError('raw schedule or NumPy identity changed')
files=[Path(__file__),Path(gpu.__file__),Path(old.table_guard.__file__),Path(__file__).with_name('test_spacetime_gpu_ladder.py')]
return dict(commit=git('rev-parse','HEAD'),dirty=False,numpy=np.__version__,production_tree=git('rev-parse','HEAD:src'),
hashes={p.name:old.sha(p) for p in files},cuda_sha256=old.sha(Path(gpu.__file__).with_suffix('.cu')),
raw_schedule_sha256=hashlib.sha256(method.encode()).hexdigest(),unchanged_against=BASE,
reference_hashes=gpu.PINS)
def directional(arrays,masks):
return sum(.25**level*np.asarray(a[:,m],np.float64).sum(axis=1) for level,(a,m) in enumerate(zip(arrays,masks)))
def populations(run,refined,*,raw=False):
state=run._download_stored() if raw else run.download()
if not refined:
return (state,)
if state.phase!='arrival_f' or state.tick!=2*run.step_count:
raise AssertionError('refined sample is not synchronized arrival F')
return state.coarse_f,state.fine_f
def assess(rows,health):
checks={key:all(np.isfinite(row[key]) and 0<=row[key]<=limit for row in rows) for key,limit in LIMITS.items()}
checks['population_health']=not any(health)
checks['sampled_population_positive']=all(row['minimum_population']>0 for row in rows)
return dict(worst={key:max(row[key] for row in rows) for key in LIMITS},campaign_checks=checks,
campaign_pass=all(checks.values()),accuracy_comparison_status='descriptive_only_no_new_threshold')
def ratios(a,b,*,trend=False):
out=dict(ratio=a/b if b>0 else None,ratio_status='defined' if b>0 else 'zero_denominator')
if trend:
out.update(two_point_slope=np.log2(a/b) if a>0 and b>0 else None,
slope_status='defined' if a>0 and b>0 else 'zero_error_log_undefined')
return out
def comparisons(runs,reference):
data={r['name']:r for r in runs}; data['refined64']=reference
out=[]
for refined,base,fine in (('refined64','uniform64','uniform128'),('refined128','uniform128','uniform256')):
for control in (base,fine):
out.append(dict(candidate=refined,control=control,control_spacing='base' if control==base else 'finest',
samples=[dict(tstar=a['tstar'],**{key:dict(candidate=a[key],control=b[key],**ratios(a[key],b[key]))
for key in ('velocity_l2','pressure_l2','energy_relative')})
for a,b in zip(data[refined]['rows'],data[control]['rows'])]))
trends=[]
for coarse,fine in (('uniform64','uniform128'),('uniform128','uniform256'),('refined64','refined128')):
trends.append(dict(coarse=coarse,fine=fine,samples=[dict(tstar=a['tstar'],**{
key:ratios(a[key],b[key],trend=True)
for key in ('velocity_l2','pressure_l2','energy_relative')})
for a,b in zip(data[coarse]['rows'],data[fine]['rows'])]))
return dict(controls=out,trends=trends,caveat='norm differences are not interface error; fixed Mach and two refined sizes do not certify convergence')
def main():
p=argparse.ArgumentParser(description=__doc__)
p.add_argument('--gpu-admitted',action='store_true'); p.add_argument('--reference-n64',type=Path,required=True)
p.add_argument('--output',type=Path,required=True); args=p.parse_args()
if not args.gpu_admitted or not os.environ.get('CUDA_VISIBLE_DEVICES'):
p.error('explicit GPU admission and CUDA_VISIBLE_DEVICES required')
if args.output.exists() or args.output.with_suffix(args.output.suffix+'.tmp').exists(): p.error('output or partial receipt exists; preserve it')
reference=load_reference(args.reference_n64); source=source_identity(reference); gpu.check_sources()
started=time.monotonic()
report=dict(completed=False,passed=False,source=source,runs=[],limits=dict(seconds=SECONDS,peak_rss_mib=RSS_MIB),
campaign_limits=LIMITS,reference=dict(sha256=REFERENCE_SHA,source=reference['source'],
coverage='verified refined base64/fine128 four-time rows only; early pressure trace unavailable'),
historical_pressure_gate=dict(scope='reused_refined64_only',**reference['historical_pressure_gate']),
n64_experimental_screen=dict(scope='reused_refined64_only',checks=reference['experimental_checks']),
frozen_cases=[setup(n,r) for _,n,r in CASES],early_trace_scope='65 predeclared rows per new run, no field snapshots',
cuda_visible_devices=os.environ['CUDA_VISIBLE_DEVICES'])
run=context=ledger=None
case_started=None
def save():
report['resources']=dict(seconds=time.monotonic()-started,peak_rss_mib=resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024,
rss_scope='Python process peak; external wrapper monitors process group and wall time')
report['resources']['within_limits']=report['resources']['seconds']<=SECONDS and report['resources']['peak_rss_mib']<=RSS_MIB
if report['completed'] and not report['resources']['within_limits']: report['passed']=False
if run is not None:
report['runs'][-1].update(completed_intervals=run.step_count,health_counts=run.health_counts.tolist(),
seconds=time.monotonic()-case_started)
if ledger is not None:
report['runs'][-1].update(ledger=ledger.snapshot(),audited_intervals=ledger.steps)
temporary=args.output.with_suffix(args.output.suffix+'.tmp')
ref.write_receipt(temporary,report); os.replace(temporary,args.output)
def cap():
if time.monotonic()-started>SECONDS or resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024>RSS_MIB:
raise RuntimeError('frozen aggregate resource cap exceeded')
save()
try:
from CelerisLab.cuda.context import CudaContext
context=CudaContext(0)
if context.name!=reference['device'] or context.sm_arch!=reference['sm_arch']:
raise RuntimeError('matched reference device identity differs')
report.update(device=context.name,sm_arch=context.sm_arch)
for name,n,refined in CASES:
cap(); ledger=None; case_started=time.monotonic(); cfg=old.LBMConfig(nx=n,ny=n,viscosity=.0003*n,velocity=0.,ddf_shifting=True)
case=dict(name=name,setup=setup(n,refined),completed=False,phase='setup',rows=[],early_pressure=[],prefixes=[],health_counts=[0]*6,
ledger_scope='all intervals; fine/transfer components are mathematically absent for uniform runs')
report['runs'].append(case); save()
run=gpu.SpaceTimeGPU(cfg,tuple(case['setup']['bounds']),context=context,allow_n128=True) if refined else gpu.UniformGPU(cfg,context=context)
case.update(build_metadata=run.build_metadata,device_allocations_bytes=run.device_bytes,
device_memory_scope='owner allocations; excludes driver/context/compiler')
expected_modules=None
if not refined and n in (64,128): expected_modules=[reference['build_metadata'][0 if n==64 else 1]]
if refined: expected_modules=[report['runs'][1]['build_metadata'][0],report['runs'][2]['build_metadata'][0]]
if expected_modules is not None:
if run.build_metadata!=expected_modules: raise RuntimeError('matched source/config/PTX metadata differs')
case['matched_build_metadata']=True
if any(m['flags']!=reference['build_metadata'][0]['flags'] for m in run.build_metadata):
raise RuntimeError('compiler flags differ from reference')
if refined:
case['tables']=old.table_guard.validate_tables(run.plan,run.tables,allow_n128=True)
masks=(run.plan.maps.coarse_active,run.plan.maps.fine_active)
else: masks=(np.ones((n,n),bool),)
analytic=tuple(tg.initial(m.shape,l,n,cfg.viscosity) for l,m in enumerate(masks))
initial=ref.cpu.State(*analytic) if refined else analytic[0]
physical=lambda:populations(run,refined)
stored=lambda:populations(run,refined,raw=True)
run.initialize(initial); raw0=stored(); direction0=directional(raw0,masks)
case['phase']='warm_reset'; warm_started=time.monotonic()
for _ in range(32): cap(); run.step()
case['warmup_seconds']=time.monotonic()-warm_started
run.initialize(initial)
for a,b in zip(raw0,stored()): np.testing.assert_array_equal(a.view(np.uint32),b.view(np.uint32))
if run.step_count or run.health_counts.any(): raise AssertionError('warm reset failed')
case['raw_reset_verified']=True; arrays=physical()
first=tg.metrics(arrays,masks,0,n,cfg.viscosity); mass0=first['mass']; moment0=ref.cpu.MOMENTS.T@directional(arrays,masks)
case['initial']=dict(mass=mass0,momentum=moment0[1:].tolist(),minimum_population=min(float(a[:,m].min()) for a,m in zip(arrays,masks)))
case['initial_quantization']=[float(abs(a[:,m]-b[:,m]).max()) for a,b,m in zip(arrays,analytic,masks)]
case['early_pressure'].append(pressure_projection(arrays,masks,0,n,cfg.viscosity))
ledger=old.LedgerTotals(); case['phase']='trajectory'; trajectory_started=time.monotonic()
case['all_interval_mass']=dict(maximum_relative=0.,step=0,signed_change_at_maximum=0.,limit=LIMITS['mass_relative'],passed=True)
for step in range(1,16*n+1):
cap(); measured=run.step(); ledger.add(measured)
if run.step_count!=step: raise AssertionError('interval count differs')
mass_change=float(ledger.sums[0].sum()); drift=abs(mass_change)/mass0
if drift>case['all_interval_mass']['maximum_relative']:
case['all_interval_mass'].update(maximum_relative=drift,step=step,signed_change_at_maximum=mass_change,passed=drift<=LIMITS['mass_relative'])
if step in case['setup']['early_steps'] or step in case['setup']['sample_steps']:
arrays=physical()
if step in case['setup']['early_steps']:
case['early_pressure'].append(pressure_projection(arrays,masks,step,n,cfg.viscosity)); save()
if step in case['setup']['sample_steps']:
row=tg.metrics(arrays,masks,step,n,cfg.viscosity,mass0)
row.update(step=step,momentum_change=(ref.cpu.MOMENTS.T@directional(arrays,masks)-moment0)[1:].tolist(),
mass_change=row['mass']-mass0,minimum_population=min(float(a[:,m].min()) for a,m in zip(arrays,masks)))
if not all(np.isfinite(v).all() for v in row.values()): raise FloatingPointError('nonfinite sampled metric')
case['rows'].append(row); prefix=ledger.snapshot(directional(stored(),masks)-direction0)
prefix['physical_minus_raw_endpoint_moments']=(ref.cpu.MOMENTS.T@directional(arrays,masks)-moment0-ref.cpu.MOMENTS.T@np.array(prefix['endpoint_directional_change'])).tolist()
case['prefixes'].append(prefix)
if not prefix['closure_pass'] or not prefix['component_split_pass']: raise AssertionError('cumulative budget failed')
save(); print(json.dumps(dict(case=name,**row),allow_nan=False),flush=True)
case.update(assess(case['rows'],run.health_counts))
cap(); case.update(completed=True,phase='completed',health_counts=run.health_counts.tolist(),audited_intervals=ledger.steps,
ledger=ledger.snapshot(),trajectory_seconds=time.monotonic()-trajectory_started,seconds=time.monotonic()-case_started)
case['passed']=case['campaign_pass'] and case['all_interval_mass']['passed'] and ledger.steps==16*n and len(case['early_pressure'])==65
run.close(); run=None; save()
cap(); report.update(completed=True,passed=all(c['passed'] for c in report['runs']),comparisons=comparisons(report['runs'],reference))
except Exception as exc:
report['failure']=repr(exc)
raise
finally:
if run is not None and ledger is not None:
current=report['runs'][-1]
current['failure_endpoint_status']='unavailable_owner_not_ready'
if run.status=='ready':
try:
current['failure_endpoint']=ledger.snapshot(directional(populations(run,refined,raw=True),masks)-direction0)
current['failure_endpoint_status']='measured'
except Exception as exc: current['failure_endpoint_status']=repr(exc)
for owner in (run,context):
if owner is not None:
try: owner.close()
except Exception as exc: report.setdefault('cleanup_errors',[]).append(repr(exc)); report['passed']=False
save()
return 0 if report['passed'] else 1
if __name__=='__main__':
raise SystemExit(main())
@@ -1,392 +0,0 @@
"""Opt-in, frozen N64 space-time GPU trajectory; no convergence certification."""
import argparse
import hashlib
import json
import os
from pathlib import Path
import resource
import subprocess
import sys
import time
import numpy as np
ROOT = Path(__file__).resolve().parents[3]
sys.path.insert(0, str(ROOT/'src'))
sys.path.insert(0, str(Path(__file__).parents[1]/'taylor_green'))
from CelerisLab.config import LBMConfig
import oracle as tg
import spacetime_gpu as gpu
import spacetime_table_guard as table_guard
ref = gpu.ref
CPU_SHA = '180eef90a1c3f43113fe18cc54981ee4723cfc0cc2724334907ff188022fa770'
UNIFORM_SHA = '01e7415ae39456f2de7f0c3d331afb971c49d19353b43038650e32e80737f1e7'
CUDA_SHA = 'afea11ea4a1c2c3800b2f6a7a8e81f5568989fc9e1cc02fb52d7e1ea3864e003'
AUDIT_SHA = 'fba340b1533bec308b666ee84666df0ac9d08e2872be31ee379e2d1447565158'
STEPS = (256, 512, 768, 1024)
TIMES = (.12, .24, .36, .48)
FACTORS = dict(velocity_l2=.8, pressure_l2=1., energy_relative=1.)
LIMITS = dict(velocity_l2=.05, pressure_l2=.15, energy_relative=.05, mass_relative=1e-5)
HEALTH = ('boundary_pre_nonfinite', 'boundary_pre_nonpositive', 'boundary_stored_nonfinite',
'boundary_stored_nonpositive', 'physical_population_nonfinite', 'physical_population_nonpositive')
def sha(path):
return hashlib.sha256(Path(path).read_bytes()).hexdigest()
def load_references(cpu_path, uniform_path):
for path, expected in ((cpu_path, CPU_SHA), (uniform_path, UNIFORM_SHA)):
if sha(path) != expected:
raise ValueError(f'pinned reference receipt differs: {path}')
cpu, uniform = [json.loads(Path(p).read_text()) for p in (cpu_path, uniform_path)]
assert cpu['completed'] and cpu['experimental_pass'] and not cpu['source']['dirty']
assert cpu['source']['commit'] == '07879bc52bfef8d95503146c55d3823c8b6f8d0a'
assert [r['mode'] for r in cpu['runs']] == ['constant_ivp', 'spacetime']
assert all(tuple(row['tstar'] for row in r['rows']) == TIMES for r in cpu['runs'])
assert uniform['completed'] and not uniform['source']['dirty']
assert uniform['source']['revision'] == '9805383f9c50d867e8555471baf5dbda8333a652'
assert (uniform['n'], uniform['depth'], uniform['viscosity']) == (64, 1, .0192)
assert uniform['limits'] == tg.LIMITS == LIMITS
return cpu, uniform
def total(state, maps):
arrays = [a.astype(np.float64) for a in (state.coarse_f, state.fine_f)]
return ref.cpu.MOMENTS.T @ ref.directional(ref.cpu.State(*arrays), maps)
def differing_fields(actual, expected):
"""Compare serialized sample numerics exactly, including the sign of zero."""
if actual.keys() != expected.keys():
return ['field_set']
return [key for key in actual if np.asarray(actual[key]).dtype != np.asarray(expected[key]).dtype
or np.asarray(actual[key]).shape != np.asarray(expected[key]).shape
or np.asarray(actual[key]).tobytes() != np.asarray(expected[key]).tobytes()]
def sample_difference(actual, expected):
"""Descriptive comparison only; never an equivalence gate for different codecs."""
return {key:dict(reference=value,signed=(np.asarray(actual[key])-value).tolist(),
absolute=np.abs(np.asarray(actual[key])-value).tolist()) for key,value in expected.items()}
class LedgerTotals:
"""Compensated directional sums; retain absolute step sums to expose cancellation."""
names = ('net_change','physical_collision','coarse_collision','fine0_collision','fine1_collision',
'child_rounding','child_interpolation','child_cast','register_rounding','receiver_rounding','unexplained')
def __init__(self):
self.sums = np.zeros((len(self.names),9)); self.correction = self.sums.copy()
self.absolute = self.sums.copy(); self.absolute_moments = np.zeros((len(self.names),3))
self.maxima = self.sums.copy(); self.max_steps = np.zeros(self.sums.shape,np.int64)
self.cells = np.zeros((3,4)); self.cell_correction = self.cells.copy()
self.steps = 0; self.bound = 0.; self.maximum = 0.
def add(self, ledger):
values = np.array([ledger[name] for name in self.names],np.float64)
cells = np.asarray(ledger['collision_cell_mass'],np.float64)
if (values.shape != self.sums.shape or not np.isfinite(values).all()
or cells.shape != (3,4) or not np.isfinite(cells).all()
or not np.isfinite(ledger['unexplained_bound']) or ledger['unexplained_bound'] <= 0):
raise AssertionError('invalid diagnostic ledger')
delta = values-self.correction
updated = self.sums+delta
self.correction = (updated-self.sums)-delta
self.sums = updated
self.absolute += abs(values)
self.absolute_moments += abs(values @ ref.cpu.MOMENTS)
larger = abs(values) > self.maxima
self.max_steps[larger] = self.steps+1; self.maxima = np.maximum(self.maxima,abs(values))
delta = cells-self.cell_correction
updated = self.cells+delta
self.cell_correction = (updated-self.cells)-delta; self.cells = updated
self.steps += 1; self.bound += ledger['unexplained_bound']
self.maximum = max(self.maximum,float(abs(values[-1]).max()))
def snapshot(self, endpoint_change=None):
values = dict(zip(self.names,self.sums))
accounted = sum(values[key] for key in ('physical_collision','child_rounding','register_rounding','receiver_rounding'))
closure = None if endpoint_change is None else endpoint_change-accounted
telescoping = None if endpoint_change is None else endpoint_change-values['net_change']
closure_pass = None if closure is None else max(float(abs(closure).max()),float(abs(telescoping).max())) <= self.bound
collision_split = values['physical_collision']-sum(values[key] for key in ('coarse_collision','fine0_collision','fine1_collision'))
child_split = values['child_rounding']-values['child_interpolation']-values['child_cast']
split_pass = max(float(abs(collision_split).max()),float(abs(child_split).max())) <= self.bound
return dict(intervals=self.steps, summed_per_step_bound=self.bound, max_step_unexplained=self.maximum,
closure_pass=closure_pass,component_split_pass=split_pass,
endpoint_status='not_measured' if endpoint_change is None else 'measured',
endpoint_directional_change=None if endpoint_change is None else endpoint_change.tolist(),
closure_residual=None if closure is None else closure.tolist(),
telescoping_residual=None if telescoping is None else telescoping.tolist(),
closure_mass_momentum=None if closure is None else (ref.cpu.MOMENTS.T@closure).tolist(),
collision_split_residual=collision_split.tolist(),child_split_residual=child_split.tolist(),
collision_cell_mass=dict(levels=['coarse','fine0','fine1'],columns=['net','positive','negative','l1'],
applied_volume_weights=[1.,.25,.25],values=self.cells.tolist()),
components={key:dict(directional=self.sums[i].tolist(),mass_momentum=(self.sums[i]@ref.cpu.MOMENTS).tolist(),
absolute_step_directional_sum=self.absolute[i].tolist(),
absolute_step_mass_momentum_sum=self.absolute_moments[i].tolist(),
max_absolute_interval=self.maxima[i].tolist(),max_absolute_interval_step=self.max_steps[i].tolist())
for i,key in enumerate(self.names)})
def warm_and_reset(run, initial, check_cap, *, audit=False):
"""Time 32 synchronized intervals, then restore exact uploaded arrival F."""
run.initialize(initial)
before = run.download()
started = time.monotonic()
for _ in range(32):
check_cap()
run.step(audit=audit)
seconds = time.monotonic()-started
warm_health = run.health_counts.tolist()
run.initialize(initial)
after = run.download()
for a, b in zip((before.coarse_f, before.fine_f), (after.coarse_f, after.fine_f)):
np.testing.assert_array_equal(a, b)
if run.step_count != 0 or after.tick != 0 or run.health_counts.any():
raise AssertionError('warm-up reset did not restore tick/counters')
return after, dict(intervals=32, seconds=seconds, estimated_1024_seconds=32*seconds,
health_counts=warm_health, reset_verified=True, ledger_audit=audit)
def assess(rows, cpu, uniform, health_counts):
if tuple(row['tstar'] for row in rows) != TIMES:
raise ValueError('four frozen sample times required')
worst = {key: max(row[key] for row in rows) for key in LIMITS}
campaign = {key: all(np.isfinite(row[key]) and 0 <= row[key] <= limit for row in rows)
for key, limit in LIMITS.items()}
campaign['population_health'] = not any(health_counts)
campaign['sampled_positive_finite'] = all(
np.isfinite(row[key]) and row[key] > 0 for row in rows
for key in ('minimum_population', 'minimum_boundary_pre', 'minimum_boundary_stored'))
baseline, candidate = cpu['runs']
thresholds = {key: factor*baseline['worst'][key] for key, factor in FACTORS.items()}
experimental = {key: all(np.isfinite(row[key]) and row[key] >= 0 for row in rows)
and worst[key] <= threshold for key, threshold in thresholds.items()}
differences = []
for actual, expected in zip(rows, candidate['rows']):
delta = {}
for key, value in expected.items():
d = np.asarray(actual[key])-np.asarray(value)
delta[key] = dict(cpu=value, signed=d.tolist(), absolute=np.abs(d).tolist())
differences.append(dict(tstar=actual['tstar'], fields=delta))
historical_worst = max(row['pressure_l2'] for row in uniform['rows'] if row['tstar'] > 0)
historical_limit = max(2*historical_worst, .02)
assert historical_limit == .024506347612699403
return dict(worst=worst, campaign_checks=campaign, campaign_pass=all(campaign.values()),
experimental_thresholds=thresholds, experimental_checks=experimental,
experimental_pass=all(experimental.values()),
gpu_minus_cpu=dict(status='descriptive_only_no_equivalence_tolerance', rows=differences),
historical_pressure_gate=dict(status='historical_shifted_FP32_uniform_vs_unshifted_FP32_candidate',
matched_storage=False, uniform_worst=historical_worst, threshold=historical_limit,
candidate_worst=worst['pressure_l2'], passed=worst['pressure_l2'] <= historical_limit))
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--gpu-admitted', action='store_true')
parser.add_argument('--cpu-receipt', type=Path, required=True)
parser.add_argument('--uniform-receipt', type=Path, required=True)
parser.add_argument('--audit-against', type=Path, help='audit every interval and compare exact saved 1779cf2 samples')
parser.add_argument('--shifted', action='store_true', help='opt-in shifted storage with all interval ledgers')
parser.add_argument('--unshifted-receipt', type=Path, help='pinned1779 comparison, descriptive only')
parser.add_argument('--output', type=Path, required=True)
args = parser.parse_args()
if not args.gpu_admitted or not os.environ.get('CUDA_VISIBLE_DEVICES'):
parser.error('explicit --gpu-admitted and CUDA_VISIBLE_DEVICES required')
if args.output.exists():
parser.error('output exists; preserve evidence and choose a new path')
if args.shifted != (args.unshifted_receipt is not None) or (args.shifted and args.audit_against):
parser.error('--shifted requires --unshifted-receipt and cannot use exact --audit-against')
exact_repeat = args.audit_against is not None
cpu, uniform = load_references(args.cpu_receipt, args.uniform_receipt)
previous = None
comparison_path = args.audit_against or args.unshifted_receipt
if comparison_path is not None:
if sha(comparison_path) != AUDIT_SHA:
raise ValueError('pinned GPU trajectory receipt differs')
previous = json.loads(comparison_path.read_text())
if previous['source']['numpy'] != np.__version__:
raise RuntimeError('audited repeat requires unchanged NumPy environment')
gpu.check_sources()
if sha(Path(gpu.__file__).with_suffix('.cu')) != CUDA_SHA:
raise RuntimeError('reviewed CUDA source changed')
source = dict(commit=subprocess.check_output(['git', 'rev-parse', 'HEAD'], cwd=ROOT, text=True).strip(),
dirty=bool(subprocess.check_output(['git', 'status', '--porcelain'], cwd=ROOT, text=True)),
hashes={p.name: sha(p) for p in (Path(__file__), Path(gpu.__file__), Path(gpu.__file__).with_suffix('.cu'),
Path(__file__).with_name('test_spacetime_gpu.py'), Path(table_guard.__file__))},
reference_hashes=gpu.PINS, numpy=np.__version__, checkout=str(ROOT))
if source['dirty']:
raise RuntimeError('clean committed checkout required')
started = time.monotonic()
report = dict(scope='N64 experimental space-time GPU; no grid-convergence qualification',
completed=False, passed=False, source=source, rows=[], health_counts=[0]*6, health_labels=HEALTH,
setup=dict(n=64, bounds=[8,8,56,48], re_L=100, U=.03, viscosity=.0192, tau=[.5576,.6152],
phase='arrival_f', storage='shifted_FP32' if args.shifted else 'unshifted_FP32', collision='SRT', interval_count=1024,
initialization='common analytic FP64 field, encoded using production FP64 weights before FP32 upload' if args.shifted
else 'same physical FP64 equilibrium as CPU, rounded to FP32 on upload',
cpu_storage='FP64', sample_steps=STEPS, sample_times=TIMES),
references=dict(cpu_receipt_sha256=CPU_SHA, cpu_source=cpu['source'],
cpu_archive_drive_id='197F9nwDOGf_YROK1a46YpVvNrSldnH_w',
cpu_archive_sha256='850ddce3f5203ef38e76e5153e718a9b92e137d1fc388ba7cd12f5d47eab83b4',
uniform_receipt_sha256=UNIFORM_SHA, uniform_source=uniform['source'],
uniform_storage='historical_shifted_FP32'),
frozen_screen=dict(campaign_limits=LIMITS, experimental_factors=FACTORS,
gpu_cpu_equivalence_tolerance=None, historical_pressure_threshold=.024506347612699403),
boundary_budget_status='pending_measurement' if previous else 'not_measured', max_directional_residual=None,
minima_scope='initial and four sampled physical arrival states; boundary minima at four samples',
limits=dict(seconds=180., peak_rss_mib=512.), cuda_visible_devices=os.environ['CUDA_VISIBLE_DEVICES'])
run = context = None
ledger_totals = LedgerTotals() if previous else None
if previous:
report['diagnostic'] = dict(completed=False, passed=False, reference_sha256=AUDIT_SHA,
reference_source=previous['source']['commit'], sample_checks=[], prefixes=[],
scope='net drift attribution; exact saved diagnostics only, not full-field trajectory certification' if exact_repeat
else 'raw stored-value ledger; unshifted and CPU comparisons descriptive, initial codecs differ')
phase = 'setup'
def save():
report['resources'] = dict(seconds=time.monotonic()-started,
peak_rss_mib=resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024,
device_allocations_bytes=None if run is None else run.device_bytes,
device_memory_scope='owner allocations; excludes compiler, driver and context')
if run is not None:
report['health_counts'] = run.health_counts.tolist()
report['completed_intervals'] = run.step_count
if ledger_totals is not None:
report['audited_intervals'] = ledger_totals.steps
if ledger_totals.steps:
report['boundary_budget_status'] = 'measured' if ledger_totals.steps==1024 else 'measured_prefix'
report['diagnostic']['accumulated'] = ledger_totals.snapshot()
ref.write_receipt(args.output, report)
def check_cap():
if time.monotonic()-started > 180 or resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024 > 512:
raise RuntimeError('frozen resource cap exceeded')
save()
try:
from CelerisLab.cuda.context import CudaContext
context = CudaContext(0)
config = LBMConfig(nx=64, ny=64, viscosity=.0192, velocity=0., ddf_shifting=args.shifted)
run = gpu.SpaceTimeGPU(config, (8,8,56,48), context=context)
report.update(device=context.name, sm_arch=context.sm_arch, build_metadata=run.build_metadata,
table_sha256=gpu.table_hash(run.tables))
report['table_validation'] = table_guard.validate_tables(run.plan,run.tables)
if previous:
for key in ('device','sm_arch','table_sha256') + (('build_metadata',) if exact_repeat else ()):
if report[key] != previous[key]:
raise AssertionError(f'audited repeat identity differs: {key}')
analytic = ref.cpu.State(tg.initial((64,64),0,64,.0192), tg.initial((128,128),1,64,.0192))
initial = analytic
phase = 'warm_reset'
initial, report['warmup'] = warm_and_reset(run, initial, check_cap, audit=previous is not None)
maps = run.plan.maps
masks = (maps.coarse_active, maps.fine_active)
arrays = (initial.coarse_f, initial.fine_f)
mass0 = tg.metrics(arrays, masks, 0, 64, .0192)['mass']
moment0 = total(initial, maps)
report['initial'] = dict(mass=mass0, momentum=moment0[1:].tolist(),
minimum_population=min(float(a[:,m].min()) for a,m in zip(arrays,masks)))
if exact_repeat and differing_fields(report['initial'],previous['initial']):
raise AssertionError('audited repeat initial state diagnostics differ')
raw_initial = run._download_stored() if args.shifted else initial
direction0 = ref.directional(ref.cpu.State(*(a.astype(np.float64) for a in
(raw_initial.coarse_f,raw_initial.fine_f))),maps)
if args.shifted:
errors=[]; unshifted_errors=[]
for raw,actual,wanted,mask in zip((raw_initial.coarse_f,raw_initial.fine_f),arrays,
(analytic.coarse_f,analytic.fine_f),masks):
encoded=gpu._encode_physical(wanted,True)
np.testing.assert_array_equal(raw[:,mask].view(np.uint32),encoded[:,mask].view(np.uint32))
errors.append(float(abs(actual[:,mask]-wanted[:,mask]).max()))
unshifted_errors.append(float(abs(gpu._encode_physical(wanted,False)[:,mask]-wanted[:,mask]).max()))
report['warmup']['raw_reset_verified']=True
report['initial_quantization']=dict(maximum_population_error_by_level=errors,
unshifted_codec_error_by_level=unshifted_errors,
moment_change_vs_analytic=(moment0-total(analytic,maps)).tolist(),
cpu_start='pinned analytic FP64 trajectory, not reinitialized to decoded GPU upload',
matched_cpu_initial_bits=False)
report['unshifted_comparison']=dict(status='descriptive_only_codecs_have_different_initial_bits',
reference_sha256=AUDIT_SHA,initial=sample_difference(report['initial'],previous['initial']),rows=[])
save()
check_cap()
phase = 'trajectory'
trajectory_started = time.monotonic()
for step in range(1,1025):
check_cap()
ledger = run.step(audit=previous is not None)
if ledger_totals is not None:
ledger_totals.add(ledger)
report['max_directional_residual'] = ledger_totals.maximum
if step in STEPS:
state = run.download()
if state.tick != 2*step:
raise AssertionError('sample is not synchronized arrival state')
arrays = (state.coarse_f, state.fine_f)
row = tg.metrics(arrays, masks, step, 64, .0192, mass0)
row.update(step=step, momentum_change=(total(state,maps)-moment0)[1:].tolist(),
mass_change=row['mass']-mass0,
minimum_population=min(float(a[:,m].min()) for a,m in zip(arrays,masks)))
if ledger_totals is not None:
row['minimum_boundary_pre'] = ledger['minimum_pre']
row['minimum_boundary_stored'] = ledger['minimum_stored']
else:
with context.activate():
row['minimum_boundary_pre'] = float(run.read(run.pre,(len(run.plan.groups),4),np.float64).min())
row['minimum_boundary_stored'] = float(run.read(run.h,(len(run.plan.groups),4)).min())
if not all(np.isfinite(value).all() for value in row.values()):
report['failed_sample'] = {key: repr(value) for key,value in row.items()}
raise FloatingPointError('nonfinite sample diagnostic')
report['rows'].append(row)
if previous:
expected=previous['rows'][len(report['rows'])-1]
changed = differing_fields(row,expected) if exact_repeat else []
report['diagnostic']['sample_checks'].append(dict(step=step,
status='exact_repeat' if exact_repeat else 'descriptive_only',differing_fields=changed if exact_repeat else None))
if args.shifted:
report['unshifted_comparison']['rows'].append(dict(step=step,fields=sample_difference(row,expected)))
raw_state=run._download_stored() if args.shifted else state
endpoint = ref.directional(ref.cpu.State(*(a.astype(np.float64) for a in
(raw_state.coarse_f,raw_state.fine_f))),maps)-direction0
prefix = ledger_totals.snapshot(endpoint)
if args.shifted:
prefix['physical_minus_raw_endpoint_moments'] = (
total(state,maps)-moment0-ref.cpu.MOMENTS.T@endpoint).tolist()
report['diagnostic']['prefixes'].append(prefix)
if not prefix['closure_pass'] or not prefix['component_split_pass']:
raise AssertionError('cumulative ledger does not close within summed existing per-step bounds')
if changed:
raise AssertionError(f'audited repeat sample differs: {changed}')
save()
print(json.dumps(row, allow_nan=False), flush=True)
report['trajectory_seconds'] = time.monotonic()-trajectory_started
check_cap()
report.update(assess(report['rows'], cpu, uniform, run.health_counts))
if args.shifted:
report['historical_pressure_gate'].update(status='historical_shifted_FP32_uniform_vs_shifted_FP32_candidate',
matched_storage=True,matched_control=False)
report['completed'] = True
report['passed'] = report['campaign_pass'] and report['experimental_pass']
if previous:
report['diagnostic'].update(completed=True,passed=ledger_totals.steps==1024 and len(report['rows'])==4)
except Exception as exc:
report['failure'] = dict(phase=phase, error=repr(exc))
raise
finally:
# Preserve the primary failure and every completed sample even if cleanup fails.
for owner in (run, context):
if owner is not None:
try:
owner.close()
except Exception as exc:
report.setdefault('cleanup_errors', []).append(repr(exc))
report['passed'] = False
save()
return 0 if report['passed'] else 1
if __name__ == '__main__':
raise SystemExit(main())
-165
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@@ -1,165 +0,0 @@
// Test-only arrival-f space-time coupling. No production scheduler changes.
#include <stdint.h>
#include <math.h>
#include "config.h"
#include "core/precision.cuh"
#include "core/descriptors.cuh"
#include "core/layout.cuh"
#include "operators/macro.cuh"
#include "operators/collision_srt.cuh"
#include "streaming/pull_double_buffer.cuh"
#if DIM != 2 || NQ != 9 || COLLISION_MODEL != 0 || STORE_PRECISION != 0 || USE_LES || STREAMING_MODEL != 0
#error "Space-time experiment requires FP32 D2Q9 SRT double buffers without LES"
#endif
__device__ __forceinline__ void collide(float* f, float omega) {
float rho, ux, uy, feq[NQ];
compute_rho_u(f, rho, ux, uy);
#if USE_DDF_SHIFTING
// Same perturbation-preserving SRT branch as production BlockStep.
const float drho = f[0]+f[1]+f[2]+f[3]+f[4]+f[5]+f[6]+f[7]+f[8];
const float jx = f[1]-f[2]+f[5]-f[6]+f[7]-f[8];
const float jy = f[3]-f[4]+f[5]-f[6]-f[7]+f[8];
compute_feq_from_momentum(drho, jx, jy, ux, uy, feq);
#else
compute_feq(rho, ux, uy, feq);
#endif
collide_srt_no_force(f, feq, omega);
}
__device__ __forceinline__ double physical(double value, unsigned int q) {
#if USE_DDF_SHIFTING
// Match population_storage.py's FP64 weights, not promoted FP32 d_w.
return value + (q == 0 ? 4.0/9.0 : (q < 5 ? 1.0/9.0 : 1.0/36.0));
#else
return value;
#endif
}
__device__ __forceinline__ void health(float stored, unsigned int q, unsigned int* counts) {
const double value = physical((double)stored, q);
if (!isfinite(value)) atomicAdd(counts + 4, 1u);
if (value <= 0.0f) atomicAdd(counts + 5, 1u);
}
extern "C" __global__ void CoarseStart(
const float* coarse, const float* fine, float* out, float omega,
unsigned int x0, unsigned int y0, unsigned int x1, unsigned int y1,
unsigned int* counts)
{
unsigned int x, y; unsigned long k;
index_from_thread(x, y, k);
if (x >= NX || y >= NY) return;
const bool covered = x >= x0 && x < x1 && y >= y0 && y < y1;
float f[NQ];
for (unsigned int q = 0; q < NQ; ++q) {
const unsigned long s = q * 4ul * TOTAL_CELLS + 2ul * y * (2u * NX) + 2u * x;
f[q] = covered ? 0.25f * (fine[s] + fine[s+1] + fine[s+2u*NX] + fine[s+2u*NX+1])
: coarse[index_f(k, q)];
}
collide(f, omega);
for (int q = 0; q < NQ; ++q) if (!covered) health(f[q], q, counts);
stream_pull_store(k, f, out);
}
extern "C" __global__ void Collide(
const float* in, float* out, const unsigned char* active, float omega,
unsigned int* counts)
{
unsigned int x, y; unsigned long k;
index_from_thread(x, y, k);
if (x >= NX || y >= NY) return;
float f[NQ];
if (active == nullptr || active[k]) {
for (int q = 0; q < NQ; ++q) f[q] = in[index_f(k, q)];
collide(f, omega);
if (active != nullptr) for (int q = 0; q < NQ; ++q) health(f[q], q, counts);
} else {
for (int q = 0; q < NQ; ++q) f[q] = NAN;
}
stream_pull_store(k, f, out);
}
extern "C" __global__ void Pull(
const float* in, float* out, const unsigned char* active, unsigned int* counts)
{
unsigned int x, y; unsigned long k;
index_from_thread(x, y, k);
if (x >= NX || y >= NY) return;
float f[NQ];
if (active == nullptr || active[k]) {
unsigned long j[NQ];
compute_neighbors(x, y, j);
stream_pull_load(k, f, in, j);
if (active != nullptr) for (int q = 0; q < NQ; ++q) health(f[q], q, counts);
} else {
for (int q = 0; q < NQ; ++q) f[q] = NAN;
}
stream_pull_store(k, f, out);
}
extern "C" __global__ void Interpolate(
const float* g0, const float* gp, const uint32_t* samples,
const uint32_t* origins, const int* sizes, const double* weights,
double* pre, float* h, unsigned int groups, unsigned int frozen,
unsigned int* counts)
{
unsigned int group = blockIdx.x * blockDim.x + threadIdx.x;
if (group >= groups) return;
const int size = sizes[group];
const unsigned int q = origins[group] / TOTAL_CELLS;
for (int child = 0; child < 4; ++child) {
double value = frozen ? (double)g0[origins[group]] : 0.0;
if (!frozen) for (int j = 0; j < size; ++j) {
const float* source = j < size/2 ? g0 : gp;
value += weights[(4u*group+child)*10u+j] * (double)source[samples[10u*group+j]];
}
const float stored = __double2float_rn(value);
pre[4u*group+child] = value;
h[4u*group+child] = stored;
if (!isfinite(physical(value, q))) atomicAdd(counts, 1u);
if (physical(value, q) <= 0.0) atomicAdd(counts+1, 1u);
if (!isfinite(physical((double)stored, q))) atomicAdd(counts+2, 1u);
if (physical((double)stored, q) <= 0.0) atomicAdd(counts+3, 1u);
}
}
extern "C" __global__ void Inject(
float* fine, const float* h, const uint32_t* rows, unsigned int count,
unsigned int omit_first)
{
unsigned int row = blockIdx.x * blockDim.x + threadIdx.x;
if (row >= count || (omit_first && row == 0)) return;
fine[rows[2u*row]] = h[rows[2u*row+1]];
}
extern "C" __global__ void Register(
const float* predicted, const float* fine, const float* h,
const uint32_t* targets, const uint32_t* sources, const int* times,
double* registers, unsigned int count, int substep, int mutation)
{
unsigned int row = blockIdx.x * blockDim.x + threadIdx.x;
if (row >= count) return;
double value = substep == 0 ? -(double)predicted[targets[row]] : registers[row];
for (int j = 0; j < 4; ++j) {
const unsigned int slot = 4u*row+j;
const int when = times[slot];
if (when != substep && !(substep == 0 && when == -1)) continue;
if ((mutation == 1 && when == -1) || (mutation == 2 && when == 0)
|| (mutation == 3 && when == 1)) continue;
value += 0.25 * (double)(when == -1 ? h[sources[slot]] : fine[sources[slot]]);
}
registers[row] = value;
}
extern "C" __global__ void ApplyRegisters(
float* predicted, const double* registers, const uint32_t* targets,
unsigned int count, unsigned int* counts)
{
unsigned int row = blockIdx.x * blockDim.x + threadIdx.x;
if (row >= count) return;
const unsigned int slot = targets[row];
predicted[slot] = __double2float_rn((double)predicted[slot] + registers[row]);
health(predicted[slot], slot / TOTAL_CELLS, counts);
}
-472
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@@ -1,472 +0,0 @@
"""Test-only arrival-f GPU owner; CUDA compilation/execution requires admission."""
from dataclasses import replace
import hashlib
from numbers import Integral
from pathlib import Path
import numpy as np
import spacetime_reference as ref
from CelerisLab.lbm.population_storage import _encode_physical, _decode_stored, _WEIGHTS
PINS = {"spacetime_reference.py": "1fe13242b9a41062a1227db4a6f9b695165aefab7f4c0b3b2adff0c9023552bf",
"cpu_reference.py": "bba2a06a9f6517b32079ffff15e4060d8c3b7ed35f16ca134e1877226c9e4e1e",
"../taylor_green/oracle.py": "83e4d7425d45538278e9fb181af450a36358bd9a5ed6be57ff611dd9ae5eb35b"}
def check_sources():
for name, expected in PINS.items():
if hashlib.sha256((Path(__file__).parent/name).read_bytes()).hexdigest() != expected:
raise RuntimeError(f"reference source changed: {name}")
def validate_config(config, *, uniform=False, allow_n128=False):
if type(uniform) is not bool or type(allow_n128) is not bool:
raise ValueError("admission flags must be bool")
cfg = replace(config)
cfg.validate()
if (cfg.nx != cfg.ny or not 8 <= cfg.nx <= (256 if uniform else (128 if allow_n128 else 64)) or cfg.nz != 1
or cfg.collision != "SRT" or not cfg.is_d2q9
or cfg.streaming != "double_buffer" or cfg.store_precision != "FP32"
or cfg.data_type != "FP32" or type(cfg.ddf_shifting) is not bool or cfg.les_enabled
or cfg.velocity != 0 or cfg.wall_slot_width or cfg.wall_normal_velocity):
raise ValueError("experiment requires periodic unforced square FP32 D2Q9/SRT within admitted size")
if uniform:
return (cfg,)
fine = replace(cfg, nx=2*cfg.nx, ny=2*cfg.ny, viscosity=2*cfg.viscosity)
fine.validate()
return cfg, fine
def pack_plan(plan):
"""Pack reviewed coordinate events; no production transfer builder imports."""
n, nf = plan.n, plan.nf
groups, receivers = plan.groups, plan.receivers
data = dict(samples=np.zeros((len(groups), 10), np.uint32),
origins=np.empty(len(groups), np.uint32), sizes=np.empty(len(groups), np.int32),
weights=np.zeros((len(groups), 4, 10), np.float64),
targets=(receivers[:, 0]*n*n+receivers[:, 1]).astype(np.uint32))
lookup = {tuple(row): i for i, row in enumerate(receivers)}
packets = [[] for _ in receivers]; incoming = [[], []]
for i, g in enumerate(groups):
size = len(g.samples)
if size not in (6, 10):
raise ValueError("unexpected interpolation stencil")
data['samples'][i, :size] = g.q*n*n+g.samples
data['origins'][i] = g.q*n*n+g.source
data['sizes'][i] = size
data['weights'][i, :, :size] = g.weights
for k, event in enumerate(g.events):
if event is None:
packets[lookup[(g.q, g.receiver)]].append((-1, 4*i+k))
else:
m, slot = event
incoming[m].append((g.q*nf*nf+slot, 4*i+k))
for m, outgoing in enumerate(plan.outgoing):
for q, source, target in outgoing:
packets[lookup[(int(q), int(target))]].append((m, int(q*nf*nf+source)))
if any(len(row) != 4 or len(set(row)) != 4 for row in packets):
raise ValueError("each receiver needs four distinct quarter-packets")
if len({packet for row in packets for packet in row}) != 4*len(receivers):
raise ValueError("packet has multiple receiver owners")
data['times'] = np.array([[t for t, _ in row] for row in packets], np.int32)
data['sources'] = np.array([[s for _, s in row] for row in packets], np.uint32)
for m, rows in enumerate(incoming):
data[f'incoming{m}'] = np.array(rows, np.uint32)
if len({slot for slot, _ in rows}) != len(rows):
raise ValueError("duplicate incoming writer")
return {key: np.ascontiguousarray(value) for key, value in data.items()}
def table_hash(data):
digest = hashlib.sha256()
for key, value in sorted(data.items()):
digest.update(f"{key}:{value.dtype}:{value.shape}".encode()+value.tobytes())
return digest.hexdigest()
def rounding_ledger(plan, tables, before, after, g0, predicted, fine_phases, pre, h, registers, *, shifted=False):
"""Audit actual stored FP32 phases; never call a missing packet 'rounding'."""
maps, n = plan.maps, plan.n
f64 = lambda a: np.asarray(a, dtype=np.float64)
difference = f64(g0[:, maps.coarse_active])-f64(before.coarse_f[:, maps.coarse_active])
coarse_collision = difference.sum(axis=1)
cell_mass = [difference.sum(axis=0)]
collision = coarse_collision.copy(); fine_collision = []
for f, g in fine_phases:
difference = f64(g[:, maps.fine_active])-f64(f[:, maps.fine_active])
fine_collision.append(.25*difference.sum(axis=1))
cell_mass.append(.25*difference.sum(axis=0))
collision += fine_collision[-1]
np.testing.assert_array_equal(h, pre.astype(np.float32))
origins = f64(g0).ravel()[tables['origins']]
np.testing.assert_allclose(pre.mean(axis=1), origins, rtol=0, atol=2e-14)
group = np.bincount(tables['origins']//(n*n), weights=f64(h).mean(axis=1)-origins, minlength=9)
interpolation = np.bincount(tables['origins']//(n*n), weights=pre.mean(axis=1)-origins, minlength=9)
child_cast = np.bincount(tables['origins']//(n*n), weights=f64(h).mean(axis=1)-pre.mean(axis=1), minlength=9)
packet = np.empty(tables['times'].shape, np.float64)
for when, source in ((-1, h), (0, fine_phases[0][1]), (1, fine_phases[1][1])):
mask = tables['times'] == when
packet[mask] = f64(source).ravel()[tables['sources'][mask]]
p = f64(predicted).ravel()[tables['targets']]
ideal = -p + .25*packet.sum(axis=1)
reg_error = registers-ideal
bound = 16*np.finfo(float).eps*(abs(p)+.25*abs(packet).sum(axis=1))
if np.any(abs(reg_error) > bound):
raise AssertionError("receiver packet register mismatch (not roundoff)")
actual = after.coarse_f.ravel()[tables['targets']]
np.testing.assert_array_equal(actual, (p+registers).astype(np.float32))
q = tables['targets']//(n*n)
store_error = np.bincount(q, weights=f64(actual)-(p+registers), minlength=9)
register_error = np.bincount(q, weights=reg_error, minlength=9)
# directional() must sum converted arrays, not accumulate in FP32.
total = lambda s: ref.directional(ref.cpu.State(f64(s.coarse_f), f64(s.fine_f)), maps)
net = total(after)-total(before)
raw = net-collision
unexplained = raw-group-store_error-register_error
limit = float(64*np.finfo(float).eps*(total(before).sum()+int(shifted)*n*n))
np.testing.assert_allclose(unexplained, 0, rtol=0, atol=limit)
offset = _WEIGHTS.ravel()[tables['origins']//(n*n),None] if shifted else 0.
return dict(raw=raw.tolist(), net_change=net.tolist(), physical_collision=collision.tolist(),
coarse_collision=coarse_collision.tolist(), fine0_collision=fine_collision[0].tolist(),
fine1_collision=fine_collision[1].tolist(), child_interpolation=interpolation.tolist(),
child_cast=child_cast.tolist(),
collision_cell_mass=[[float(a.sum()),float(a[a>0].sum()),float(a[a<0].sum()),float(abs(a).sum())]
for a in cell_mass],
child_rounding=group.tolist(), receiver_rounding=store_error.tolist(),
register_rounding=register_error.tolist(), unexplained=unexplained.tolist(),
unexplained_bound=limit, minimum_pre=float((pre+offset).min()),
minimum_stored=float((f64(h)+offset).min()))
class SpaceTimeGPU:
"""Caller-owned context, one stream, explicit synchronized arrival state."""
def __init__(self, config, bounds, *, context, mode='spacetime', identity=False, allow_n128=False):
check_sources()
self.configs = validate_config(config,allow_n128=allow_n128)
if mode not in ('spacetime', 'frozen') or type(identity) is not bool:
raise ValueError("unsupported interpolation or debug collision mode")
self.bounds = tuple(bounds)
if len(self.bounds) != 4 or any(isinstance(v, bool) or not isinstance(v, Integral) for v in self.bounds):
raise ValueError("rectangle bounds must be four integers")
self.plan = ref.Plan(config.nx, self.bounds)
self.tables = pack_plan(self.plan)
self.ctx, self.mode, self.identity = context, mode, identity
self.allocations, self.modules, self.build_metadata = [], [], []
self.status, self.step_count, self.device_bytes = 'new', 0, 0
self.health_counts = np.zeros(6, np.uint64)
import pycuda.driver as cuda
from CelerisLab.cuda import compiler_v2 as compiler
root = Path(__file__).resolve().parents[3]
if Path(compiler._KERNEL_DIR).resolve() != root/'src/CelerisLab/lbm/kernels':
raise RuntimeError("wrong production kernel checkout")
self.cuda = cuda
with context.activate():
self.stream = cuda.Stream()
try:
source = Path(__file__).with_suffix('.cu')
for cfg in self.configs:
build = compiler.generate_config(cfg)
try:
Path(build, source.name).write_bytes(source.read_bytes())
ptx = compiler.compile_kernel(context.sm_arch, source=source.name, build_dir=build)
self.modules.append(compiler.load_module(ptx))
import json
metadata = json.loads(Path(ptx+'.json').read_text())
metadata['test_entry_sha256'] = hashlib.sha256(source.read_bytes()).hexdigest()
self.build_metadata.append(metadata)
finally:
compiler.cleanup_build_dir(build)
self.device_tables = {key: self.upload(value) for key, value in self.tables.items()}
self.active = self.upload(self.plan.maps.fine_active.astype(np.uint8))
self.coarse = [self.allocate(9*config.nx**2*4) for _ in range(4)]
self.fine = [self.allocate(9*(2*config.nx)**2*4) for _ in range(3)]
self.pre = self.allocate(len(self.plan.groups)*4*8)
self.h = self.allocate(len(self.plan.groups)*4*4)
self.registers = self.allocate(len(self.plan.receivers)*8)
self.counts = self.allocate(6*4)
except BaseException:
try:
self.close()
except Exception:
pass
raise
def allocate(self, size):
pointer = self.cuda.mem_alloc(size)
self.allocations.append(pointer); self.device_bytes += size
return pointer
def upload(self, array):
pointer = self.allocate(array.nbytes)
self.cuda.memcpy_htod(pointer, array)
return pointer
def read(self, pointer, shape, dtype=np.float32):
self.stream.synchronize()
out = np.empty(shape, dtype)
self.cuda.memcpy_dtoh(out, pointer)
return out
def launch(self, level, name, *args, count=None):
cfg = self.configs[level]
nt = cfg.threads_per_block
grid = ((cfg.nx+nt-1)//nt, cfg.ny) if count is None else ((count+nt-1)//nt, 1)
self.modules[level].get_function(name)(*args, block=(nt,1,1), grid=grid, stream=self.stream)
def initialize(self, state):
if (self.status not in ('new', 'ready') or state.phase != 'arrival_f'
or isinstance(state.tick, bool) or not isinstance(state.tick, Integral) or state.tick != 0):
raise ValueError("initial synchronized arrival state with tick=0 required")
shifted = self.configs[0].ddf_shifting
arrays = []
for values, mask in zip((state.coarse_f,state.fine_f),
(self.plan.maps.coarse_active,self.plan.maps.fine_active)):
if np.shape(values) != (9,*mask.shape):
raise ValueError("positive finite leaf populations and exact shapes required")
a = _encode_physical(values,shifted)
physical = _decode_stored(a,shifted)
if not np.isfinite(physical[:,mask]).all() or (physical[:,mask] <= 0).any():
raise ValueError("positive finite leaf populations and exact shapes required")
a[:,~mask] = np.nan
arrays.append(a)
with self.ctx.activate():
try:
self.cuda.memcpy_htod(self.coarse[0], arrays[0])
self.cuda.memcpy_htod(self.fine[0], arrays[1])
except BaseException:
self.status = 'failed'
raise
self.status, self.step_count = 'ready', 0
self.health_counts.fill(0)
def _download_stored(self):
"""Private audit/reset snapshot; values remain in their storage representation."""
if self.status != 'ready':
raise RuntimeError(f"GPU owner is {self.status}")
try:
with self.ctx.activate():
arrays = [self.read(self.coarse[0], (9,self.plan.n,self.plan.n)),
self.read(self.fine[0], (9,self.plan.nf,self.plan.nf))]
except BaseException:
self.status = 'failed'
raise
for a, mask in zip(arrays, (self.plan.maps.coarse_active,self.plan.maps.fine_active)):
a[:,~mask] = np.nan
return ref.cpu.State(*arrays, tick=2*self.step_count)
def download(self):
"""Physical arrival populations; shifted values are reconstructed in FP64."""
stored = self._download_stored()
return ref.cpu.State(*(_decode_stored(a,self.configs[0].ddf_shifting)
for a in (stored.coarse_f,stored.fine_f)),tick=stored.tick)
def step(self, *, mutation=0, audit=True):
"""One interval; audit=False skips only host ledger snapshots, never health checks."""
if (self.status != 'ready' or type(mutation) is not int or mutation not in range(5)
or type(audit) is not bool or (mutation and not audit)):
raise RuntimeError("ready owner and known test mutation required")
before = self._download_stored() if audit else None
n, nf, t = self.plan.n, self.plan.nf, self.device_tables
ng, nr = len(self.plan.groups), len(self.plan.receivers)
u32, null = np.uint32, np.uintp(0)
omega = [np.float32(0 if self.identity else cfg.omega) for cfg in self.configs]
with self.ctx.activate():
try:
self.status = 'advancing'
self.cuda.memset_d32_async(self.counts, 0, 6, self.stream)
fc, g0, predicted, gp = self.coarse
self.launch(0, 'CoarseStart', fc,self.fine[0],g0,omega[0],
*(u32(v) for v in self.bounds),self.counts)
self.launch(0, 'Pull', g0,predicted,null,self.counts)
self.launch(0, 'Collide', predicted,gp,null,omega[0],self.counts)
self.launch(0, 'Interpolate', g0,gp,t['samples'],t['origins'],t['sizes'],t['weights'],
self.pre,self.h,u32(ng),u32(self.mode=='frozen'),self.counts,count=ng)
if audit:
coarse_g = self.read(g0,(9,n,n)); prediction = self.read(predicted,(9,n,n))
fine_phases = []
for m in (0,1):
f, out, g = self.fine
if audit:
old_f = self.read(f,(9,nf,nf))
self.launch(1, 'Collide', f,g,self.active,omega[1],self.counts)
if audit:
fine_phases.append((old_f,self.read(g,(9,nf,nf))))
self.launch(0, 'Register', predicted,g,self.h,t['targets'],t['sources'],t['times'],
self.registers,u32(nr),np.int32(m),np.int32(mutation),count=nr)
rows = self.tables[f'incoming{m}']
self.launch(1, 'Inject', g,self.h,t[f'incoming{m}'],u32(len(rows)),u32(mutation==4),count=len(rows))
self.launch(1, 'Pull', g,out,self.active,self.counts)
self.fine[0], self.fine[1] = out, f
self.launch(0, 'ApplyRegisters', predicted,self.registers,t['targets'],u32(nr),self.counts,count=nr)
counts = self.read(self.counts,(6,),np.uint32)
self.health_counts += counts.astype(np.uint64)
if counts.any():
raise AssertionError(f"boundary/leaf health failed: {counts.tolist()}")
ledger = dict(boundary_budget_status='not_measured',unexplained=None)
if audit:
coarse_after = self.read(predicted,(9,n,n))
coarse_after[:,~self.plan.maps.coarse_active] = np.nan
after = ref.cpu.State(coarse_after,self.read(self.fine[0],(9,nf,nf)),tick=2*(self.step_count+1))
ledger = rounding_ledger(self.plan,self.tables,before,after,coarse_g,prediction,fine_phases,
self.read(self.pre,(ng,4),np.float64),self.read(self.h,(ng,4)),
self.read(self.registers,(nr,),np.float64),
shifted=self.configs[0].ddf_shifting)
ledger['boundary_budget_status'] = 'measured'
ledger['health_counts'] = counts.tolist()
self.coarse[0], self.coarse[2] = predicted, fc
self.step_count += 1
self.status = 'ready'
return ledger
except BaseException:
self.status = 'failed'
raise
def close(self):
if self.status == 'closed':
return
with self.ctx.activate():
error = None
try:
self.stream.synchronize()
except Exception as exc:
error = exc
failed = []
for pointer in self.allocations:
try:
pointer.free()
except Exception as exc:
error = error or exc
failed.append(pointer)
self.allocations = failed
self.status = 'cleanup_failed' if failed else 'closed'
if not failed:
self.modules.clear()
if error:
raise error
def __enter__(self):
return self
def __exit__(self, kind, value, traceback):
try:
self.close()
except Exception:
if kind is None:
raise
def uniform_ledger(before, after, collided, *, shifted):
"""Periodic streaming permutes each direction; only collision changes its sum."""
a,b,g = [np.asarray(x,np.float64) for x in (before,after,collided)]
collision=(g-a).sum(axis=(1,2)); net=b.sum(axis=(1,2))-a.sum(axis=(1,2))
residual=net-collision
bound=float(64*np.finfo(float).eps*(a.sum()+int(shifted)*a.shape[1]*a.shape[2]))
np.testing.assert_allclose(residual,0,rtol=0,atol=bound)
cells=(g-a).sum(axis=0)
out={key:[0.]*9 for key in ('fine0_collision','fine1_collision','child_rounding',
'child_interpolation','child_cast','register_rounding','receiver_rounding')}
out.update(net_change=net.tolist(),physical_collision=collision.tolist(),coarse_collision=collision.tolist(),
unexplained=residual.tolist(),unexplained_bound=bound,
collision_cell_mass=[[float(cells.sum()),float(cells[cells>0].sum()),
float(cells[cells<0].sum()),float(abs(cells).sum())],[0.]*4,[0.]*4],
boundary_budget_status='not_applicable_uniform',inactive_components='fine, child, register, receiver')
return out
class UniformGPU(SpaceTimeGPU):
"""One explicit arrival-F level; reuse the reviewed kernels and owner helpers."""
def __init__(self, config, *, context, identity=False):
check_sources()
self.configs=validate_config(config,uniform=True)
if type(identity) is not bool:
raise ValueError('identity must be bool')
self.ctx,self.identity=context,identity
self.allocations,self.modules,self.build_metadata=[],[],[]
self.status,self.step_count,self.device_bytes='new',0,0
self.health_counts=np.zeros(6,np.uint64)
import pycuda.driver as cuda
from CelerisLab.cuda import compiler_v2 as compiler
if Path(compiler._KERNEL_DIR).resolve()!=Path(__file__).resolve().parents[3]/'src/CelerisLab/lbm/kernels':
raise RuntimeError('wrong production kernel checkout')
self.cuda=cuda
with context.activate():
self.stream=cuda.Stream()
try:
source=Path(__file__).with_suffix('.cu')
build=compiler.generate_config(self.configs[0])
try:
Path(build,source.name).write_bytes(source.read_bytes())
ptx=compiler.compile_kernel(context.sm_arch,source=source.name,build_dir=build)
self.modules.append(compiler.load_module(ptx))
import json
metadata=json.loads(Path(ptx+'.json').read_text())
metadata['test_entry_sha256']=hashlib.sha256(source.read_bytes()).hexdigest()
self.build_metadata.append(metadata)
finally:
compiler.cleanup_build_dir(build)
n=config.nx
self.buffers=[self.allocate(9*n*n*4) for _ in range(3)]
self.active=self.upload(np.ones((n,n),np.uint8))
self.counts=self.allocate(6*4)
except BaseException:
try:
self.close()
except BaseException:
pass
raise
def initialize(self, physical):
cfg=self.configs[0]
if self.status not in ('new','ready') or np.shape(physical)!=(9,cfg.ny,cfg.nx):
raise ValueError('ready owner and exact uniform population shape required')
stored=_encode_physical(physical,cfg.ddf_shifting)
decoded=_decode_stored(stored,cfg.ddf_shifting)
if not np.isfinite(decoded).all() or (decoded<=0).any():
raise ValueError('positive finite physical populations required')
try:
with self.ctx.activate():
self.cuda.memcpy_htod(self.buffers[0],stored)
self.health_counts[:]=0; self.step_count=0; self.status='ready'
except BaseException:
self.status='failed'
raise
def _download_stored(self):
if self.status!='ready':
raise RuntimeError('uniform owner is not ready')
try:
with self.ctx.activate():
n=self.configs[0].nx
return self.read(self.buffers[0],(9,n,n))
except BaseException:
self.status='failed'
raise
def download(self):
return _decode_stored(self._download_stored(),self.configs[0].ddf_shifting)
def step(self, *, audit=True):
if self.status!='ready' or type(audit) is not bool:
raise RuntimeError('ready owner and bool audit required')
cfg=self.configs[0]; shape=(9,cfg.ny,cfg.nx)
before=self._download_stored() if audit else None
with self.ctx.activate():
try:
self.status='advancing'
self.cuda.memset_d32_async(self.counts,0,6,self.stream)
f,g,out=self.buffers
self.launch(0,'Collide',f,g,self.active,np.float32(0 if self.identity else cfg.omega),self.counts)
self.launch(0,'Pull',g,out,self.active,self.counts)
counts=self.read(self.counts,(6,),np.uint32)
self.health_counts+=counts.astype(np.uint64)
if counts.any():
raise AssertionError(f'uniform population health failed: {counts.tolist()}')
ledger=uniform_ledger(before,self.read(out,shape),self.read(g,shape),shifted=cfg.ddf_shifting) if audit else dict(
boundary_budget_status='not_measured',unexplained=None)
ledger['health_counts']=counts.tolist()
self.buffers[0],self.buffers[2]=out,f
self.step_count+=1; self.status='ready'
return ledger
except BaseException:
self.status='failed'
raise
@@ -1,334 +0,0 @@
"""Experimental FP64 BVP coupling: one periodic rectangle, D2Q9, ratio two.
Guzik et al., https://www.osti.gov/servlets/purl/1226215, sections 3.2--3.5.
Coordinate-generated stream events; CPUREF collision only, no production imports.
This is a mathematical prototype, not a certified accuracy implementation.
"""
from dataclasses import dataclass
from functools import lru_cache
import argparse
import hashlib
import json
from pathlib import Path
import resource
import sys
import subprocess
import time
import numpy as np
import cpu_reference as cpu
class Spec(cpu.Spec):
@property
def n_fine(self):
return 2 * self.n_coarse
def geometry(n, bounds):
x0, y0, x1, y1 = bounds
if not (2 <= x0 < x1 <= n - 2 and 2 <= y0 < y1 <= n - 2):
raise ValueError("one interior rectangle with two coarse cells of clearance required")
y, x = np.indices((n, n))
covered = (x >= x0) & (x < x1) & (y >= y0) & (y < y1)
y, x = np.indices((2*n, 2*n))
active = (x >= 2*x0) & (x < 2*x1) & (y >= 2*y0) & (y < 2*y1)
inner = (x >= 2*x0-2) & (x < 2*x1+2) & (y >= 2*y0-2) & (y < 2*y1+2) & ~active
rows, links = [], []
for ky, kx in zip(*np.nonzero(~covered)):
for q, (cy, cx) in enumerate(zip(cpu.CY, cpu.CX)):
if any(active[2*ky+dy-cy, 2*kx+dx-cx]
for dy in (0, 1) for dx in (0, 1)
if 0 <= 2*ky+dy-cy < 2*n and 0 <= 2*kx+dx-cx < 2*n):
rows.append((q, ky, kx))
sy, sx = (ky-cy) % n, (kx-cx) % n
if not covered[sy, sx]:
links.append(cpu.CornerLink(f"{kx}_{ky}_{q}", q, (sx, sy), (kx, ky)))
kind = np.where(active, 0, np.where(inner, 1, 2))
return cpu.Maps(~covered, covered, active, inner, kind == 2, kind,
np.arange(2*n)//2, (np.arange(2*n)+.5)/2,
np.array(rows, dtype=int), tuple(links))
@lru_cache(None)
def interpolation(kind, points):
"""Return data coordinates, evaluation matrix, and constrained coefficient map."""
if kind == "face":
samples = np.array([(s, t) for t in (0., 1.) for s in (-1., 0., 1.)])
a = np.array([[1, s, t, s*t] for s, t in samples])
e = np.array([[1, s, t, s*t] for s, t in points])
b = e.mean(axis=0, keepdims=True)
d = np.zeros((1, 6)); d[0, 1] = 1
else:
cross = ((0, 0), (-1, 0), (1, 0), (0, -1), (0, 1))
samples = np.array([(x, y, t) for t in (0., 1.) for x, y in cross])
a = np.array([[1, x, y, t] for x, y, t in samples])
e = np.array([[1, x, y, t] for x, y, t in points])
b = np.stack((e.mean(axis=0), [0, 0, 0, 1]))
d = np.zeros((2, 10)); d[0, 0] = 1; d[1, 0] = -1; d[1, 5] = 1
kkt = np.block([[a.T @ a, b.T], [b, np.zeros((len(b), len(b)))]])
coeff = np.linalg.solve(kkt, np.vstack((a.T, d)))[:4]
if not np.allclose(b @ coeff, d, rtol=0, atol=2e-14):
raise AssertionError("invalid constrained interpolation matrix")
return samples, a, e, coeff
@dataclass
class Group:
q: int
source: int
receiver: int
kind: str
points: tuple
samples: np.ndarray
weights: np.ndarray
events: tuple # (substep, fine ghost slot), or None for a leftover
class Plan:
def __init__(self, n, bounds):
self.n, self.nf = n, 2*n
self.maps = geometry(n, bounds)
active = self.maps.fine_active
lo, hi = np.array(bounds[1::-1]), np.array(bounds[3:1:-1])
self.groups = []
for iy, ix in zip(*np.nonzero(self.maps.coarse_active)):
origin = np.array((iy, ix))
for q in range(1, 9):
c = np.array((cpu.CY[q], cpu.CX[q]))
starts = [2*origin + (dy, dx) for dy in (0, 1) for dx in (0, 1)]
events = []
for p in starts:
event = None
for m in (0, 1):
old, new = p+m*c, p+(m+1)*c
inside = lambda z: bool(np.all(z >= 0) and np.all(z < 2*n) and active[tuple(z)])
if not inside(old) and inside(new):
event = (m, int(old[0]*2*n+old[1]))
break
events.append(event)
if all(event is None for event in events):
continue
axes = [j for j in range(2) if origin[j] < lo[j] or origin[j] >= hi[j]]
kind = "corner" if len(axes) == 2 else "face"
points = []
for p in starts:
x = (p+.5)/2
times = [(float(lo[j] if c[j] > 0 else hi[j])-x[j])/c[j] for j in axes]
time = max(times)
offset = x+c*time-(origin+.5+c*.5)
points.append((float(offset[1]), float(offset[0]), float(time-.5))
if kind == "corner" else (float(offset[1-axes[0]]), float(time-.5)))
points = tuple(points)
samples, _, e, coeff = interpolation(kind, points)
indices = []
for row in samples:
shift = np.array((row[1], row[0]), dtype=int) if kind == "corner" else np.eye(2, dtype=int)[1-axes[0]]*int(row[0])
pos = (origin+shift) % n
indices.append(int(pos[0]*n+pos[1]))
target = (origin+c) % n
self.groups.append(Group(q, int(iy*n+ix), int(target[0]*n+target[1]), kind,
points, np.array(indices), e @ coeff, tuple(events)))
self.outgoing = []
# m is zero-based: a substep-0 exit travels two fine spacings by
# synchronization; a substep-1 exit travels one.
for m in (0, 1):
records = []
for q in range(1, 9):
c = np.array((cpu.CY[q], cpu.CX[q]))
for y, x in zip(*np.nonzero(active)):
p = np.array((y, x)); endpoint = p+c
if not active[tuple(endpoint)]:
target = (p+(2-m)*c)//2
assert self.maps.coarse_active[tuple(target)]
records.append((q, int(y*2*n+x), int(target[0]*n+target[1])))
self.outgoing.append(np.array(records, dtype=int))
incoming = [(m, g.q, slot) for g in self.groups for event in g.events
if event is not None for m, slot in [event]]
assert len(incoming) == len(set(incoming)), "duplicate incoming writer"
expected = {(m, int(q), int((y-cpu.CY[q])*2*n+x-cpu.CX[q]))
for m in (0, 1) for q in range(1, 9)
for y, x in zip(*np.nonzero(active)) if not active[y-cpu.CY[q], x-cpu.CX[q]]}
assert set(incoming) == expected, "incoming coverage mismatch"
receivers = {(int(q), int(target)) for out in self.outgoing for q, _, target in out}
receivers |= {(g.q, g.receiver) for g in self.groups if None in g.events}
assert receivers == {(int(q), int(y*n+x)) for q, y, x in self.maps.coalesce}
self.receivers = np.array(sorted(receivers), dtype=int)
def directional(state, maps):
return state.coarse_f[:, maps.coarse_active].sum(axis=1) + .25*state.fine_f[:, maps.fine_active].sum(axis=1)
def advance(spec, plan, state, mode="spacetime", mutation=None):
"""One arrival-to-arrival interval. 'frozen' disables space AND time variation."""
if mode not in ("frozen", "spacetime"):
raise ValueError(mode)
n, nf, maps = plan.n, plan.nf, plan.maps
if state.phase != "arrival_f" or state.tick % 2:
raise ValueError("synchronized arrival state required")
fc, ff = state.coarse_f.copy(), state.fine_f.copy()
covered_mean = ff.reshape(9, n, 2, n, 2).mean(axis=(2, 4))
fc[:, maps.coarse_covered] = covered_mean[:, maps.coarse_covered]
all_cells = np.ones((n, n), dtype=bool)
def collide(f, mask, tau):
return cpu._collide(spec, f, np.isfinite(f), tau, mask, np.zeros(mask.shape, dtype=int))
gc = collide(fc, all_cells, spec.tau_coarse)
collision = (gc[:, maps.coarse_active]-fc[:, maps.coarse_active]).sum(axis=1)
predicted = cpu._stream_periodic(gc)
gp = collide(predicted, all_cells, spec.tau_coarse) if mode == "spacetime" else gc
registers = np.zeros((9, n*n))
q, target = plan.receivers.T
registers[q, target] = -predicted.reshape(9, -1)[q, target]
incoming = [[], []]
group_error = 0.
min_boundary = float("inf")
negative_boundary = nonfinite_boundary = 0
dropped = False
for group in plan.groups:
q = group.q
count = len(group.samples)//2
data = np.concatenate((gc.reshape(9, -1)[q, group.samples[:count]], gp.reshape(9, -1)[q, group.samples[count:]]))
value = (group.weights @ data if mode == "spacetime"
else np.full(4, gc.reshape(9, -1)[q, group.source]))
min_boundary = min(min_boundary, float(value.min()))
negative_boundary += int(np.count_nonzero(value < 0))
nonfinite_boundary += int(np.count_nonzero(~np.isfinite(value)))
group_error = max(group_error, abs(value.mean()-gc.reshape(9, -1)[q, group.source]))
for k, event in enumerate(group.events):
if event is None:
if mutation == "omit_leftover" and not dropped:
dropped = True
else:
registers[q, group.receiver] += .25*value[k]
else:
m, slot = event
incoming[m].append((q, slot, value[k]))
for m in (0, 1):
gf = collide(ff, maps.fine_active, spec.tau_fine)
collision += .25*(gf[:, maps.fine_active]-ff[:, maps.fine_active]).sum(axis=1)
out = plan.outgoing[m]
if mutation != f"omit_outgoing_{m}":
np.add.at(registers, (out[:, 0], out[:, 2]), .25*gf.reshape(9, -1)[out[:, 0], out[:, 1]])
for q, slot, value in incoming[m]:
gf.reshape(9, -1)[q, slot] = value
fresh = np.full_like(ff, np.nan)
for q in range(9):
moved = cpu._shift(gf[q], int(cpu.CY[q]), int(cpu.CX[q]), np.nan)
fresh[q, maps.fine_active] = moved[maps.fine_active]
if not np.isfinite(fresh[:, maps.fine_active]).all():
raise AssertionError("invalid fine incoming population")
ff = fresh
final_c = predicted + registers.reshape(9, n, n)
final_c[:, maps.coarse_covered] = np.nan
final = cpu.State(final_c, ff, tick=state.tick+2)
residual = directional(final, maps)-directional(state, maps)-collision
minimum = min(float(final_c[:, maps.coarse_active].min()), float(ff[:, maps.fine_active].min()))
return final, dict(directional_residual=residual, collision=collision,
group_error=group_error, min_boundary=min_boundary, min_population=minimum,
negative_boundary_count=negative_boundary, nonfinite_boundary_count=nonfinite_boundary)
def write_receipt(path, result):
"""Normalize NumPy scalars at the JSON boundary; reject other unknown types."""
def scalar(value):
if isinstance(value, np.generic):
return value.item()
raise TypeError(f"Object of type {type(value).__name__} is not JSON serializable")
path.write_text(json.dumps(result, indent=2, allow_nan=False, default=scalar)+"\n")
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--n64", action="store_true", help="explicitly run the frozen 1024-interval experiment")
parser.add_argument("--output", type=Path, required=True)
parser.add_argument("--max-seconds",type=float,default=180.,help="wall-time cap, including plan generation")
parser.add_argument("--max-rss-mib",type=float,default=256.,help="Linux peak-RSS screening cap")
args = parser.parse_args()
if not args.n64:
parser.error("full trajectory requires --n64")
if args.output.exists():
parser.error("output exists; preserve prior evidence and choose a new path")
if not (np.isfinite(args.max_seconds) and args.max_seconds>0 and np.isfinite(args.max_rss_mib) and args.max_rss_mib>0):
parser.error("positive finite resource caps required")
started = time.monotonic()
sys.path.insert(0, str(Path(__file__).parents[1]/"taylor_green"))
import oracle as tg
plan = Plan(64, (8, 8, 56, 48))
spec = Spec(n_coarse=64, patch_lo=8, halo=16, tau_coarse=.5576, tau_fine=.6152, collision="srt")
arrays = [tg.initial((64,64), 0, 64, .0192), tg.initial((128,128), 1, 64, .0192)]
for a, mask in zip(arrays, (plan.maps.coarse_active, plan.maps.fine_active)):
a[:, ~mask] = np.nan
initial = cpu.State(*arrays)
mass0 = tg.metrics(arrays, (plan.maps.coarse_active, plan.maps.fine_active), 0, 64, .0192)["mass"]
metrics = ("velocity_l2", "pressure_l2", "energy_relative")
frozen_baseline = dict(zip(metrics, (.01131134574353476, .03592961319244149, .012514764591008386)))
budget_bound = float(64*np.finfo(float).eps*mass0)
root = Path(__file__).resolve().parents[3]
source = dict(commit=subprocess.check_output(["git", "rev-parse", "HEAD"],cwd=root,text=True).strip(),
dirty=bool(subprocess.check_output(["git","status","--porcelain"],cwd=root,text=True)),
hashes={p.name:hashlib.sha256(p.read_bytes()).hexdigest()
for p in (Path(__file__),Path(cpu.__file__),Path(tg.__file__))},numpy=np.__version__)
result = dict(scope="experimental CPU FP64; no GPU/accuracy certification", source=source,
screen=dict(velocity_factor=.8, pressure_factor=1., energy_factor=1.,
directional_step_bound=budget_bound, mass_relative=1e-11,
momentum_absolute=1e-9, baseline_metric_atol=1e-10),
limits=dict(seconds=args.max_seconds,rss_mib=args.max_rss_mib),runs=[],completed=False)
def save():
result["resources"] = dict(seconds=time.monotonic()-started,peak_rss_mib=resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024)
write_receipt(args.output, result)
save()
try:
for mode in ("constant_ivp", "spacetime"):
measured = mode == "spacetime"
state = initial; record = dict(mode=mode,rows=[],
boundary_budget_status="measured" if measured else "not_measured",
max_directional_residual=0. if measured else None,
minimum_boundary=None,negative_boundary_count=0 if measured else None,
nonfinite_boundary_count=0 if measured else None)
result["runs"].append(record)
for k in range(1, 1025):
if time.monotonic()-started>args.max_seconds or resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/1024>args.max_rss_mib:
raise RuntimeError("experiment resource cap exceeded")
if mode == "constant_ivp":
state,_ = cpu.advance_coarse_once(spec,plan.maps,state)
else:
state,diagnostic = advance(spec,plan,state)
error = float(np.max(np.abs(diagnostic["directional_residual"])))
record["max_directional_residual"] = max(record["max_directional_residual"],error)
if np.isfinite(diagnostic["min_boundary"]):
record["minimum_boundary"] = (diagnostic["min_boundary"] if record["minimum_boundary"] is None else min(record["minimum_boundary"],diagnostic["min_boundary"]))
for name in ("negative_boundary_count","nonfinite_boundary_count"):
record[name] += diagnostic[name]
if (not np.isfinite(error) or error>budget_bound or diagnostic["group_error"]>2e-14
or diagnostic["negative_boundary_count"] or diagnostic["nonfinite_boundary_count"]
or not np.isfinite(diagnostic["min_boundary"]) or diagnostic["min_boundary"]<=0
or not np.isfinite(diagnostic["min_population"]) or diagnostic["min_population"]<=0):
record["failed_diagnostic"] = {name: repr(value) for name,value in diagnostic.items()}
raise AssertionError("candidate directional/health invariant failed")
if k in (256,512,768,1024):
row = tg.metrics((state.coarse_f,state.fine_f),(plan.maps.coarse_active,plan.maps.fine_active),k,64,.0192,mass0)
row["momentum_change"] = (cpu.MOMENTS.T@(directional(state,plan.maps)-directional(initial,plan.maps)))[1:].tolist()
record["rows"].append(row)
save(); print(mode,k,json.dumps(row),flush=True)
record["worst"] = {key:max(row[key] for row in record["rows"]) for key in metrics}
if mode == "constant_ivp":
for key,value in frozen_baseline.items():
if abs(record["worst"][key]-value)>1e-10:
raise AssertionError(f"frozen baseline mismatch: {key}")
baseline,candidate = result["runs"]
result["checks"] = {key:candidate["worst"][key]<=factor*baseline["worst"][key]
for key,factor in zip(metrics,(.8,1.,1.))}
result["checks"]["mass_momentum"] = all(row["mass_relative"]<=1e-11 and max(map(abs,row["momentum_change"]))<=1e-9 for row in candidate["rows"])
result["completed"] = True
result["experimental_pass"] = all(result["checks"].values())
save()
return 0 if result["experimental_pass"] else 1
except Exception as exc:
result["failure"] = dict(mode=mode,step=k,error=repr(exc))
save()
raise
if __name__ == "__main__":
raise SystemExit(main())
@@ -1,92 +0,0 @@
"""N64/N128 admission check: exact topology and independently rational interpolation.
Raw FP64 bytes are diagnostic: different LAPACK builds need not produce them
identically. The 2e-14 ceiling is the existing interpolation constraint policy,
not a universal LAPACK error theorem. This module never changes runtime weights.
"""
from fractions import Fraction as F
from functools import lru_cache
import numpy as np
from spacetime_gpu import table_hash
STRUCTURE_SHA = 'cd1842952c4dd4df82da8015454c25da9be12b983270236cc65b4044fa38e6e4'
STRUCTURES = {64: (STRUCTURE_SHA, 532),
128: ('ee4ecb645674ae04eb87220a5217851405ccc0f45fbb0fe210499dcea5cd93b1', 1060)}
ATOL = 2e-14
def _transpose(a):
return list(map(list, zip(*a)))
def _multiply(a, b):
return [[sum(x*y for x,y in zip(row,column)) for column in zip(*b)] for row in a]
@lru_cache(None)
def exact_weights(kind, points):
"""Solve the small documented constrained fit using exact rational arithmetic."""
if kind == 'face':
a = [[F(1),F(s),F(t),F(s*t)] for t in (0,1) for s in (-1,0,1)]
e = [[F(1),F(s),F(t),F(s)*F(t)] for s,t in points]
b = [[sum(column)/4 for column in zip(*e)]]
d = [[F(int(j==1)) for j in range(6)]]
elif kind == 'corner':
a = [[F(1),F(x),F(y),F(t)] for t in (0,1) for x,y in ((0,0),(-1,0),(1,0),(0,-1),(0,1))]
e = [[F(1),F(x),F(y),F(t)] for x,y,t in points]
b = [[sum(column)/4 for column in zip(*e)], [F(0),F(0),F(0),F(1)]]
d = [[F(int(j==0)) for j in range(10)], [F(int(j==5)-int(j==0)) for j in range(10)]]
else:
raise ValueError('unsupported interpolation kind')
kkt = [r+s for r,s in zip(_multiply(_transpose(a),a),_transpose(b))]
kkt += [row+[F(0)]*len(b) for row in b]
rhs = _transpose(a)+d
n = len(kkt)
augmented = [row+data for row,data in zip(kkt,rhs)]
for j in range(n):
pivot = next(i for i in range(j,n) if augmented[i][j])
augmented[j],augmented[pivot] = augmented[pivot],augmented[j]
divisor = augmented[j][j]
augmented[j] = [v/divisor for v in augmented[j]]
for i in range(n):
if i != j:
factor = augmented[i][j]
augmented[i] = [x-factor*y for x,y in zip(augmented[i],augmented[j])]
solution = [row[n:] for row in augmented]
if _multiply(kkt,solution) != rhs:
raise AssertionError('exact interpolation solve failed')
return np.array(_multiply(e,solution[:4]), dtype=np.float64)
def validate_tables(plan, tables, *, allow_n128=False):
"""Reject topology, layout, padding, operator, or constraint changes separately."""
structure = table_hash({key:value for key,value in tables.items() if key != 'weights'})
admitted = (64,128) if allow_n128 is True else (64,)
if plan.n not in admitted or structure != STRUCTURES[plan.n][0]:
raise ValueError('frozen integer topology changed')
w = tables['weights']
if (w.dtype != np.dtype(np.float64) or w.shape != (STRUCTURES[plan.n][1],4,10) or len(plan.groups) != w.shape[0]
or not all(a.flags.c_contiguous for a in tables.values()) or not np.isfinite(w).all()):
raise ValueError('weight dtype/shape/layout/finiteness changed')
errors = dict(coefficient=0., constant=0., mean=0., temporal=0.)
for i,g in enumerate(plan.groups):
size = len(g.samples)
if size != tables['sizes'][i] or size != {'face':6,'corner':10}.get(g.kind) or len(g.points) != 4:
raise ValueError('interpolation group coverage/size changed')
if w[i,:,size:].tobytes() != np.zeros((4,10-size),np.float64).tobytes():
raise ValueError('weight padding is not exact positive zero')
actual = w[i,:,:size]
errors['coefficient'] = max(errors['coefficient'],float(abs(actual-exact_weights(g.kind,g.points)).max()))
errors['constant'] = max(errors['constant'],float(abs(actual.sum(axis=1)-1).max()))
central = np.zeros(size); central[1 if g.kind=='face' else 0] = 1
errors['mean'] = max(errors['mean'],float(abs(actual.mean(axis=0)-central).max()))
if g.kind == 'corner':
early,late = (g.points.index((0.,0.,t)) for t in (-.25,.25))
slope = np.zeros(size); slope[0],slope[5] = -1,1
errors['temporal'] = max(errors['temporal'],float(abs(2*(actual[late]-actual[early])-slope).max()))
if any(error > ATOL for error in errors.values()):
raise ValueError(f'exact interpolation/constraint check failed: {errors}; bound={ATOL}')
return dict(status='passed', structure_sha256=structure, raw_table_sha256=table_hash(tables),
coefficient_oracle='exact rational KKT, rounded once to FP64', atol=ATOL, rtol=0.,
maximum_absolute_errors=errors, positive_zero_padding=True)
@@ -1,239 +0,0 @@
"""Host-only experimental union event contract; no solver or runtime admission.
Consumes existing level-wide union geometry, never its legacy transfer tables.
The frozen 707afe6 rectangle oracle remains independent and unchanged. Topology
acceptance proves packet accounting, not interpolation accuracy or GPU support.
"""
from types import SimpleNamespace
import numpy as np
import spacetime_reference as ref
class UnresolvedTopology(ValueError):
"""An experimental coupling limitation, not a production geometry rejection."""
def __init__(self, code, **detail):
self.code, self.detail = code, detail
super().__init__(f"experimental space-time topology unresolved: {code}: {detail}")
def owned_slots(layout, directions, cells):
"""Map dense logical reads/writes to existing owner-core storage, not halos."""
cells = np.asarray(cells)
if not np.issubdtype(cells.dtype, np.integer) or np.any((cells < 0) | (cells >= np.prod(layout.shape))):
raise ValueError('invalid dense cell index')
owner = layout.owner.ravel()[cells]
if np.any(owner == layout.hole):
raise UnresolvedTopology('missing_block_owner', cells=cells[owner == layout.hole].tolist())
return layout.slot(owner, directions)
def _first_entry(covered, origin, child, c):
"""First continuous union entry of one characteristic, in exact quarter times.
Probe the cells immediately before/after each crossed grid line using integer
eighth-cell coordinates. Return only actual exterior faces of the UNION.
"""
start4 = 4*origin + 2*child + 1
for t4 in (1, 3):
before = (2*start4 + c*(2*t4-1))//8
after = (2*start4 + c*(2*t4+1))//8
if not covered[tuple(before)] and covered[tuple(after)]:
axes = []
for j in range(2):
if before[j] != after[j]:
neighbor = after.copy(); neighbor[j] = before[j]
if not covered[tuple(neighbor)]: axes.append(j)
return t4, axes
return None
def _crossing_time(covered, origin, position, c, axes):
"""Fig.11 convex T uses the last plane; Fig.13 concave T uses the first.
Both use the same KKT formulation on different boundary geometry.
DOI/primary PDF: https://www.osti.gov/servlets/purl/1226215, §3.5.1.
"""
times=[(origin[j]+int(c[j]>0)-position[j])/c[j] for j in axes]
if len(axes)==1: return times[0]
sides=[bool(covered[tuple(origin+np.eye(2,dtype=int)[j]*c[j])]) for j in axes]
if sides[0]!=sides[1]:
raise UnresolvedTopology('mixed_corner_support',source_yx=origin.tolist())
return min(times) if all(sides) else max(times)
class UnionPlan:
"""Two-level, level-wide square geometry; all coordinates are level-local.
Assumes a complete parent domain; does not validate nested parent coverage.
``pair`` is existing FixedPatchSet2D geometry, even for one rectangle. Scalar
window origins and nested state coverage need their own contract; they are
explicitly unadmitted here. No global rectangle-gap rule is imposed.
"""
phase = 'arrival_f'
runtime_supported = False
interpolation_accuracy = 'unqualified_for_new_unions'
def __init__(self, pair):
ny, nx = pair.coarse_shape
self.origin = tuple(pair.fine_origin)
if ny != nx or pair.fine_shape != (2*ny, 2*nx) or self.origin != (0., 0.):
raise UnresolvedTopology('requires_level_wide_square_pair',
coarse_shape=pair.coarse_shape, fine_shape=pair.fine_shape, origin=self.origin)
self.n, self.nf = nx, 2*nx
covered = np.array(pair.covered, dtype=bool, copy=True)
active = np.kron(covered, np.ones((2, 2), bool))
if not np.array_equal(active, pair.fine_kind == 0):
raise UnresolvedTopology('non_pair_active_coverage')
self.maps = SimpleNamespace(coarse_active=~covered, coarse_covered=covered, fine_active=active)
self.outgoing, transit = [[], []], []
# Guzik et al. §3.5.4, Fig.19 (https://www.osti.gov/servlets/purl/1226215):
# retain substep-0 outgoing G at source, then fill the substep-1 ghost.
# Rows are (q, fine source, next ghost); no covered coarse receiver credit.
for q in range(1, 9):
c = np.array((ref.cpu.CY[q], ref.cpu.CX[q]))
boundary = active & ~np.roll(active, tuple(-c), axis=(0, 1))
for y, x in zip(*np.nonzero(boundary)):
p = np.array((y, x))
for m in (0, 1):
target = (p+(2-m)*c)//2
if covered[tuple(target)]:
if m != 0 or not active[tuple(p+2*c)]:
raise UnresolvedTopology('unsupported_transit', q=q, substep=m, source_yx=p.tolist())
ghost=p+c
transit.append((q,int(y*self.nf+x),int(ghost[0]*self.nf+ghost[1])))
else:
self.outgoing[m].append((q, int(y*self.nf+x), int(target[0]*nx+target[1])))
self.outgoing = [np.array(x, dtype=np.int64).reshape(-1, 3) for x in self.outgoing]
self.transit = np.array(transit,dtype=np.int64).reshape(-1,3)
self.groups = []
for iy, ix in zip(*np.nonzero(~covered)):
origin = np.array((iy, ix))
# Two-cell production margins make all nearby probes in bounds.
if not covered[max(0,iy-1):iy+2,max(0,ix-1):ix+2].any(): continue
for q in range(1, 9):
c = np.array((ref.cpu.CY[q], ref.cpu.CX[q]))
children = [np.array((dy, dx)) for dy in (0, 1) for dx in (0, 1)]
starts = [2*origin+child for child in children]
events = []
for p in starts:
event = None
for m in (0, 1):
old, new = p+m*c, p+(m+1)*c
if not active[tuple(old)] and active[tuple(new)]:
event = (m, int(old[0]*self.nf+old[1])); break
events.append(event)
if all(e is None for e in events): continue
entries = [_first_entry(covered, origin, child, c) for child in children]
axes = sorted({j for entry in entries if entry is not None for j in entry[1]})
if not axes:
raise UnresolvedTopology('missing_exterior_support', source_yx=origin.tolist(), q=q)
points = []
for p, entry, event in zip(starts, entries, events):
position = (p+.5)/2
time = _crossing_time(covered,origin,position,c,axes)
if entry is not None and (4*time != entry[0] or event is None):
raise UnresolvedTopology('nonconvex_entry_support', source_yx=origin.tolist(), q=q,
quarter_time=entry[0], support_quarter_time=float(4*time))
offset = position+c*time-(origin+.5+c*.5)
points.append((float(offset[1]), float(offset[0]), float(time-.5)) if len(axes)==2
else (float(offset[1-axes[0]]), float(time-.5)))
kind = 'corner' if len(axes)==2 else 'face'; points = tuple(points)
samples, _, evaluation, coefficients = ref.interpolation(kind, points)
indices = []
for row in samples:
shift = np.array((row[1],row[0]), int) if kind=='corner' else np.eye(2,dtype=int)[1-axes[0]]*int(row[0])
pos = (origin+shift) % nx; indices.append(int(pos[0]*nx+pos[1]))
target = (origin+c) % nx
self.groups.append(ref.Group(q,int(iy*nx+ix),int(target[0]*nx+target[1]),kind,
points,np.array(indices),evaluation@coefficients,tuple(events)))
receivers = {(int(q),int(target)) for rows in self.outgoing for q,_,target in rows}
receivers |= {(g.q,g.receiver) for g in self.groups if None in g.events}
self.receivers = np.array(sorted(receivers),dtype=np.int64).reshape(-1,2)
self.proof = validate_ownership(self)
def validate_ownership(plan):
"""Independent mask-based event coverage and four-quarter receiver accounting."""
n, nf, active = plan.n, plan.nf, plan.maps.fine_active
actual = [(m,g.q,slot) for g in plan.groups for e in g.events if e is not None for m,slot in [e]]
expected_transit={(q,int(y*nf+x),int((y+ref.cpu.CY[q])*nf+x+ref.cpu.CX[q]))
for q in range(1,9) for y,x in zip(*np.nonzero(active))
if not active[y+ref.cpu.CY[q],x+ref.cpu.CX[q]]
and active[y+2*ref.cpu.CY[q],x+2*ref.cpu.CX[q]]}
routes=[tuple(map(int,row)) for row in plan.transit]
if len(routes)!=len(set(routes)) or set(routes)!=expected_transit:
raise ValueError('transit provenance/uniqueness/coverage failed')
actual += [(1,q,ghost) for q,source,ghost in routes]
expected = {(m,q,int((y-ref.cpu.CY[q])*nf+x-ref.cpu.CX[q]))
for m in (0,1) for q in range(1,9) for y,x in zip(*np.nonzero(active))
if not active[y-ref.cpu.CY[q],x-ref.cpu.CX[q]]}
if len(actual)!=len(set(actual)) or set(actual)!=expected:
raise ValueError('incoming writer uniqueness/coverage failed')
packets = {tuple(map(int,row)):[] for row in plan.receivers}
if len(packets)!=len(plan.receivers): raise ValueError('duplicate coarse receiver')
anchors = set()
for i,g in enumerate(plan.groups):
if not 1<=g.q<9 or not 0<=g.source<n*n or not plan.maps.coarse_active.ravel()[g.source]:
raise ValueError('invalid coarse source anchor')
if (g.q,g.source) in anchors: raise ValueError('duplicate coarse source group')
anchors.add((g.q,g.source))
origin=np.array(divmod(g.source,n)); c=np.array((ref.cpu.CY[g.q],ref.cpu.CX[g.q]))
target=(origin+c)%n
if g.receiver!=target[0]*n+target[1]: raise ValueError('group receiver provenance failed')
ordered=[]; entries=[]
for dy,dx in ((0,0),(0,1),(1,0),(1,1)):
p=2*origin+(dy,dx); event=None
for m in (0,1):
old,new=p+m*c,p+(m+1)*c
if not active[tuple(old)] and active[tuple(new)]:
event=(m,int(old[0]*nf+old[1])); break
ordered.append(event)
entries.append(_first_entry(plan.maps.coarse_covered,origin,np.array((dy,dx)),c))
if tuple(ordered)!=g.events or all(e is None for e in ordered):
raise ValueError('ordered child characteristic provenance failed')
axes=sorted({j for e in entries if e is not None for j in e[1]})
if not axes or g.kind!=('corner' if len(axes)==2 else 'face'):
raise ValueError('group supporting axes differ')
samples,_,evaluation,coefficients=ref.interpolation(g.kind,g.points)
indices=[]
for row in samples:
shift=np.array((row[1],row[0]),int) if g.kind=='corner' else np.eye(2,dtype=int)[1-axes[0]]*int(row[0])
pos=(origin+shift)%n; indices.append(int(pos[0]*n+pos[1]))
if not np.array_equal(g.samples,indices): raise ValueError('sample anchor provenance failed')
for k,(dy,dx) in enumerate(((0,0),(0,1),(1,0),(1,1))):
position=origin+(np.array((dy,dx))+.5)/2
time=_crossing_time(plan.maps.coarse_covered,origin,position,c,axes)
offset=position+c*time-(origin+.5+c*.5)
point=(float(offset[1]),float(offset[0]),float(time-.5)) if g.kind=='corner' else (float(offset[1-axes[0]]),float(time-.5))
if g.points[k]!=point: raise ValueError('evaluation point provenance failed')
source=np.zeros(len(g.samples)); source[0 if g.kind=='corner' else 1]=1
if (not np.allclose(g.weights,evaluation@coefficients,rtol=0,atol=2e-14)
or not np.allclose(g.weights.mean(axis=0),source,rtol=0,atol=2e-14)):
raise ValueError('group coefficients/directional budget failed')
for k,event in enumerate(g.events):
if event is None:
if (g.q,g.receiver) not in packets: raise ValueError('missing leftover receiver')
packets[(g.q,g.receiver)].append(('leftover',i,k))
for m,rows in enumerate(plan.outgoing):
expected_out = {(q,int(y*nf+x),int(((y+(2-m)*ref.cpu.CY[q])//2)*n+(x+(2-m)*ref.cpu.CX[q])//2))
for q in range(1,9) for y,x in zip(*np.nonzero(active))
if not active[y+ref.cpu.CY[q],x+ref.cpu.CX[q]]
and plan.maps.coarse_active[(y+(2-m)*ref.cpu.CY[q])//2,(x+(2-m)*ref.cpu.CX[q])//2]}
actual_out = [tuple(map(int,row)) for row in rows]
if len(actual_out)!=len(set(actual_out)) or set(actual_out)!=expected_out:
raise ValueError('outgoing uniqueness/coverage failed')
for q,slot,target in actual_out: packets[(q,target)].append(('outgoing',m,q,slot))
expected_receivers = {(q,int(y*n+x)) for y,x in zip(*np.nonzero(plan.maps.coarse_active))
for q in range(1,9) if any(active[2*y+dy-ref.cpu.CY[q],2*x+dx-ref.cpu.CX[q]]
for dy in (0,1) for dx in (0,1)
if 0<=2*y+dy-ref.cpu.CY[q]<nf and 0<=2*x+dx-ref.cpu.CX[q]<nf)}
if set(packets)!=expected_receivers: raise ValueError('coarse receiver coverage failed')
tokens=[token for row in packets.values() for token in row]
if any(len(row)!=4 for row in packets.values()) or len(tokens)!=len(set(tokens)):
raise ValueError('receiver needs four distinct quarter-packets')
return dict(topology='supported',incoming_events=len(actual),outgoing_events=sum(map(len,plan.outgoing)),
transit_events=len(routes),
groups=len(plan.groups),receivers=len(packets),receiver_quarter_packets=len(tokens),
interpolation_accuracy=plan.interpolation_accuracy,runtime_supported=False,
scope='pair-local ownership/coefficients; complete parent domain assumed, nested coverage unvalidated')
@@ -106,9 +106,10 @@ class ChannelRootGPU(unittest.TestCase):
cfg = LBMConfig(nx=48, ny=32, viscosity=.1, velocity=.015, ddf_shifting=shifted)
reference = None
for block in ((32,48), (8,8), (4,1)):
with FixedPatchStepper(cfg, (8,6,40,26), context=context,
coarse_boundary="channel", base_block=block, fine_block=(8,8),
fine_objects=(body,) if bodies else (), jets=(jet,) if bodies else ()) as backend:
with FixedPatchStepper(cfg, context=context, coarse_boundary="channel",
refinements=[(8,6,40,26)], level_blocks=[block, (8,8)],
level_objects=[(), (body,) if bodies else ()],
level_jets=[(), (jet,) if bodies else ()]) as backend:
arrays = [state(*level.shape[1:]) for level in backend._levels]
backend.initialize(*arrays)
backend.step(4)
@@ -25,8 +25,8 @@ EPS = np.finfo(np.float64).eps
def build(m, window=True, raw=True):
return FixedPatchStepper(config("periodic"), BOUNDS, context=m["context"], base_block=(3, 4),
fine_block=(16, 20), fine_objects=[circle()],
return FixedPatchStepper(config("periodic"), context=m["context"], refinements=[BOUNDS],
level_blocks=[(3, 4), (16, 20)], level_objects=[(), (circle(),)],
observe_raw_exchange=raw, observe_window_exchange=window)
@@ -109,10 +109,11 @@ class ExchangeWindowGPU(unittest.TestCase):
from test_raw_exchange_gpu import BOUNDS as RB, CFG, circle as rc, jet, state
from CelerisLab.cuda.context import CudaContext
with CudaContext(0) as ctx:
kw = dict(context=ctx, fine_block=(16, 20), fine_objects=[rc()], jets=[jet()],
kw = dict(context=ctx, refinements=[RB], level_blocks=[None, (16, 20)],
level_objects=[(), (rc(),)], level_jets=[(), (jet(),)],
observe_raw_exchange=True)
with FixedPatchStepper(CFG, RB, observe_window_exchange=True, **kw) as windowed, \
FixedPatchStepper(CFG, RB, **kw) as plain:
with FixedPatchStepper(CFG, observe_window_exchange=True, **kw) as windowed, \
FixedPatchStepper(CFG, **kw) as plain:
arrays = [state(level.shape) for level in windowed._levels]
windowed.initialize(*arrays)
plain.initialize(*arrays)
@@ -200,11 +201,11 @@ class ExchangeWindowShiftedMRTGPU(unittest.TestCase):
from CelerisLab.cuda.context import CudaContext
cfg = LBMConfig(nx=32, ny=24, viscosity=.1, collision="MRT", ddf_shifting=True)
with CudaContext(0) as ctx:
kw = dict(context=ctx, base_block=(12, 8), fine_block=(16, 20), fine_objects=[rc()],
observe_raw_exchange=True)
with FixedPatchStepper(cfg, RB, observe_window_exchange=True, **kw) as windowed, \
FixedPatchStepper(cfg, RB, observe_window_exchange=True, **kw) as split, \
FixedPatchStepper(cfg, RB, **kw) as plain:
kw = dict(context=ctx, refinements=[RB], level_blocks=[(12, 8), (16, 20)],
level_objects=[(), (rc(),)], observe_raw_exchange=True)
with FixedPatchStepper(cfg, observe_window_exchange=True, **kw) as windowed, \
FixedPatchStepper(cfg, observe_window_exchange=True, **kw) as split, \
FixedPatchStepper(cfg, **kw) as plain:
arrays = [state(level.shape) for level in windowed._levels]
for run in (windowed, split, plain):
run.initialize(*arrays)
@@ -140,7 +140,8 @@ def run_patch(speed, *, audit=True):
build = (patch.object(compiler, "compile_kernel", audit_compiler(compiler.compile_kernel))
if audit else nullcontext())
with build:
backend = implementation.FixedPatchStepper(cfg, BOUNDS, context=context, fine_objects=[source])
backend = implementation.FixedPatchStepper(cfg, context=context, refinements=[BOUNDS],
level_objects=[(), (source,)])
with backend, context.activate():
c, f = backend._levels
cl = backend._fine_curved
@@ -325,6 +326,7 @@ def test_cross_interface_donor_rejects_before_cuda():
context.activate.side_effect = AssertionError("must reject before CUDA activation")
with patch.object(cuda, "mem_alloc") as allocate:
with pytest.raises(ValueError, match="donor crosses"):
implementation.FixedPatchStepper(cfg, BOUNDS, context=context, fine_objects=[source])
implementation.FixedPatchStepper(cfg, context=context, refinements=[BOUNDS],
level_objects=[(), (source,)])
context.activate.assert_not_called()
allocate.assert_not_called()
@@ -48,9 +48,8 @@ def make(context):
for (x, y), amplitude in zip(centers, (.003, -.002))
)
run = FixedPatchStepper(
CFG, PARENTS, context=context, base_block=(4, 4), fine_block=(4, 4),
child_block=(4, 4), child_rectangles_in_parent=START,
child_objects=objects, child_jets=jets,
CFG, context=context, refinements=[PARENTS, START], level_blocks=[(4, 4)] * 3,
level_objects=[(), (), objects], level_jets=[(), (), jets],
)
return run, objects
@@ -25,9 +25,8 @@ B = ((16,16,32,40), (60,16,76,40))
def make(ctx):
body = SimObject(71, geometry=CircleGeometry(12.,14.,.8),center=(12.,14.),radius=.8)
jet = Jet(Tube((10.5,14.),0.,3.,.3),Parallel(0.),'parabolic',.003)
run = FixedPatchStepper(CFG,PARENTS,context=ctx,base_block=(4,4),fine_block=(4,4),
child_block=(4,4),child_rectangles_in_parent=A,
child_objects=(body,),child_jets=(jet,))
run = FixedPatchStepper(CFG,context=ctx,refinements=[PARENTS,A],level_blocks=[(4,4)]*3,
level_objects=[(),(),(body,)],level_jets=[(),(),(jet,)])
return run,(body,)
@@ -90,14 +90,18 @@ def census(run, index, buffer):
return totals(dense, leaf), external, independent
def fine(block):
"""Two-level circle+jet construction on BOUNDS; block None keeps the dense fine level."""
return dict(refinements=[BOUNDS], level_blocks=[None, block],
level_objects=[(), (circle(),)], level_jets=[(), (jet(),)])
class RawExchangeGPU(unittest.TestCase):
def test_row_ledger_interval_jet_switch_and_no_population_effect(self):
with CudaContext(0) as ctx:
for block in ((32, 40), (16, 20), (8, 10)):
with FixedPatchStepper(CFG, BOUNDS, context=ctx, fine_block=block,
fine_objects=[circle()], jets=[jet()], observe_raw_exchange=True) as measured, \
FixedPatchStepper(CFG, BOUNDS, context=ctx, fine_block=block,
fine_objects=[circle()], jets=[jet()]) as plain:
with FixedPatchStepper(CFG, context=ctx, **fine(block), observe_raw_exchange=True) as measured, \
FixedPatchStepper(CFG, context=ctx, **fine(block)) as plain:
arrays = [state(l.shape) for l in measured._levels]
measured.initialize(*arrays)
plain.initialize(*arrays)
@@ -146,9 +150,8 @@ class RawExchangeGPU(unittest.TestCase):
"""Same fine resolution/initial data with dense storage: a numerical
reference for cut-link rows, not a uniform-whole-domain convergence study."""
with CudaContext(0) as ctx:
with FixedPatchStepper(CFG, BOUNDS, context=ctx, fine_objects=[circle()], jets=[jet()]) as dense, \
FixedPatchStepper(CFG, BOUNDS, context=ctx, fine_block=(16, 20),
fine_objects=[circle()], jets=[jet()], observe_raw_exchange=True) as blocked:
with FixedPatchStepper(CFG, context=ctx, **fine(None)) as dense, \
FixedPatchStepper(CFG, context=ctx, **fine((16, 20)), observe_raw_exchange=True) as blocked:
arrays = [state(l.shape) for l in blocked._levels]
dense.initialize(*arrays)
blocked.initialize(*arrays)
@@ -229,8 +232,7 @@ class RawExchangeGPU(unittest.TestCase):
layout = BlockLayout2D.build(48, 64, 8, 8)
with CudaContext(0) as ctx:
with PeriodicBlockStepper(fine_cfg, layout, context=ctx, objects=[obj]) as uniform, \
FixedPatchStepper(CFG, BOUNDS, context=ctx, fine_block=(16, 20),
fine_objects=[circle()], jets=[jet()], observe_raw_exchange=True) as amr:
FixedPatchStepper(CFG, context=ctx, **fine((16, 20)), observe_raw_exchange=True) as amr:
amr.initialize(*(state(l.shape) for l in amr._levels))
uniform.initialize(state((9, 48, 64)))
b = amr._level_boundaries[1]
@@ -83,11 +83,10 @@ def mocked_backend(mode="periodic", fail_alloc=None):
class BlockedBaseCPU(unittest.TestCase):
def test_reject_before_cuda(self):
context = Mock(activate=Mock(side_effect=AssertionError("CUDA reached")))
for kwargs in ({"base_block": (12, 8)},
{"base_block": (7, 8), "fine_block": FINE_BLOCK},
{"base_block": (12,), "fine_block": FINE_BLOCK}):
with self.subTest(kwargs=kwargs), self.assertRaises(ValueError):
FixedPatchStepper(config("periodic"), BOUNDS, context=context, **kwargs)
for blocks in ([(12, 8), None], [(7, 8), FINE_BLOCK], [(12,), FINE_BLOCK]):
with self.subTest(blocks=blocks), self.assertRaises(ValueError):
FixedPatchStepper(config("periodic"), context=context, refinements=[BOUNDS],
level_blocks=blocks)
context.activate.assert_not_called()
def test_all_arrival_rows_donors_and_kind_masks(self):
@@ -193,9 +192,10 @@ class BlockedBaseCPU(unittest.TestCase):
def test_launch_order_stream_wall_constants_and_buffer_swaps(self):
with mocked_backend("slot_reservoir") as m:
backend = FixedPatchStepper(config("slot_reservoir"), BOUNDS, context=m["context"],
coarse_boundary="slot_reservoir", fine_block=FINE_BLOCK,
base_block=(3, 4), fine_objects=[circle(actuation(.002))])
backend = FixedPatchStepper(config("slot_reservoir"), context=m["context"],
coarse_boundary="slot_reservoir", refinements=[BOUNDS],
level_blocks=[(3, 4), FINE_BLOCK],
level_objects=[(), (circle(actuation(.002)),)])
try:
backend.initialize(state(NY, NX, 1), state(*backend.patch.fine_shape, 2))
coarse, fine = backend._levels
@@ -236,16 +236,16 @@ class BlockedBaseCPU(unittest.TestCase):
for fail_at in (1, 6, 10):
with self.subTest(fail_at=fail_at), mocked_backend(fail_alloc=fail_at) as m:
with self.assertRaisesRegex(MemoryError, "injected allocation"):
FixedPatchStepper(config("periodic"), BOUNDS, context=m["context"],
fine_block=FINE_BLOCK, base_block=(3, 4))
FixedPatchStepper(config("periodic"), context=m["context"], refinements=[BOUNDS],
level_blocks=[(3, 4), FINE_BLOCK])
self.assertEqual(len(m["allocations"]), fail_at)
for allocation in m["allocations"]:
allocation.free.assert_called_once_with()
def test_failed_parent_stage_cannot_publish_or_resume(self):
with mocked_backend() as m:
backend = FixedPatchStepper(config("periodic"), BOUNDS, context=m["context"],
fine_block=FINE_BLOCK, base_block=(3, 4))
backend = FixedPatchStepper(config("periodic"), context=m["context"], refinements=[BOUNDS],
level_blocks=[(3, 4), FINE_BLOCK])
backend.initialize(state(NY, NX, 1), state(*backend.patch.fine_shape, 2))
m["functions"]["BlockCoalesce"].side_effect = RuntimeError("injected parent stage failure")
current = backend._levels[0].current
@@ -289,9 +289,10 @@ class BlockedBaseGPU(unittest.TestCase):
for base_block in (None, *layouts):
label = f"{mode} width={width} speed={speed} base={base_block}"
snapshots = []
with FixedPatchStepper(cfg, BOUNDS, context=context, coarse_boundary=mode,
fine_block=FINE_BLOCK, base_block=base_block,
fine_objects=() if speed is None else [circle(actuation(speed))]) as backend:
with FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
refinements=[BOUNDS], level_blocks=[base_block, FINE_BLOCK],
level_objects=[(), () if speed is None
else (circle(actuation(speed)),)]) as backend:
backend.initialize(*arrays)
for step in (0, 1, 2, 8):
if step == 1 and base_block is not None:
@@ -105,9 +105,10 @@ class BlockedFineCPU(unittest.TestCase):
return Mock(activate=Mock(side_effect=AssertionError("CUDA reached")), sm_arch="sm_70")
def test_rejections_before_cuda(self):
for kw in ({"fine_block": (7, 7)}, {"fine_block": (16,)}):
for kw in ({"level_blocks": [None, (7, 7)]}, {"level_blocks": [None, (16,)]}):
with self.subTest(kw=kw), self.assertRaises(ValueError):
FixedPatchStepper(config("periodic"), BOUNDS, context=self.forbidden_context(), **kw)
FixedPatchStepper(config("periodic"), context=self.forbidden_context(),
refinements=[BOUNDS], **kw)
def test_single_block_layout_allocates_no_empty_halo_tables(self):
# A 1x1 non-periodic fine layout has zero halo pairs; CUDA rejects mem_alloc(0).
@@ -125,8 +126,8 @@ class BlockedFineCPU(unittest.TestCase):
patch.object(compiler, "compile_kernel"), patch.object(compiler, "cleanup_build_dir"), \
patch.object(compiler, "load_module", return_value=module), \
patch.object(cuda, "mem_alloc", side_effect=alloc), patch.object(cuda, "memcpy_htod"):
backend = FixedPatchStepper(config("periodic"), BOUNDS, context=context,
fine_block=FINE_BLOCKS[0])
backend = FixedPatchStepper(config("periodic"), context=context, refinements=[BOUNDS],
level_blocks=[None, FINE_BLOCKS[0]])
self.assertEqual(len(backend.fine_layout.halo_dst), 0)
self.assertIsNone(backend._levels[1].halo_dst)
backend._gather_halo(backend._levels[1], Mock()) # no launch without pairs
@@ -177,8 +178,9 @@ class BlockedFineCPU(unittest.TestCase):
patch.object(cuda, "mem_alloc", side_effect=lambda size: Mock()), \
patch.object(cuda, "memcpy_htod"), \
patch.object(curved_links, "CurvedLinkSoA", side_effect=AssertionError("dense SoA built")):
backend = FixedPatchStepper(config("periodic"), BOUNDS, context=context,
fine_objects=objects, fine_block=FINE_BLOCKS[1])
backend = FixedPatchStepper(config("periodic"), context=context, refinements=[BOUNDS],
level_blocks=[None, FINE_BLOCKS[1]],
level_objects=[(), tuple(objects)])
backend.initialize(state(NY, NX, 1), state(*backend.patch.fine_shape, 2))
return backend, calls
@@ -289,8 +291,9 @@ class BlockedFineGPU(unittest.TestCase):
results = []
with CudaContext(0) as context:
for fine_block in (None, *FINE_BLOCKS):
with FixedPatchStepper(cfg, BOUNDS, context=context, coarse_boundary=mode,
fine_block=fine_block) as backend:
with FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
refinements=[BOUNDS],
level_blocks=[None, fine_block]) as backend:
backend.initialize(g_coarse, g_fine)
backend.step(STEPS)
self.assertEqual(backend.step_count, STEPS)
@@ -318,8 +321,9 @@ class BlockedFineGPU(unittest.TestCase):
results = []
with CudaContext(0) as context:
for fine_block in (None, *FINE_BLOCKS):
with FixedPatchStepper(cfg, BOUNDS, context=context, coarse_boundary=mode,
fine_objects=[circle()], fine_block=fine_block) as backend:
with FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
refinements=[BOUNDS], level_blocks=[None, fine_block],
level_objects=[(), (circle(),)]) as backend:
backend.initialize(g_coarse, g_fine)
backend.step(STEPS)
results.append((backend.download(), raw(backend)))
@@ -346,9 +350,9 @@ class BlockedFineGPU(unittest.TestCase):
results = []
with CudaContext(0) as context:
for fine_block in (None, *FINE_BLOCKS):
with FixedPatchStepper(cfg, BOUNDS, context=context, coarse_boundary=mode,
fine_objects=[circle(actuation(speed))],
fine_block=fine_block) as backend:
with FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
refinements=[BOUNDS], level_blocks=[None, fine_block],
level_objects=[(), (circle(actuation(speed)),)]) as backend:
backend.initialize(g_coarse, g_fine)
backend.step(STEPS)
results.append((backend.download(), raw(backend)))
@@ -94,7 +94,8 @@ class FaultGuardsCPU(unittest.TestCase):
("slot_reservoir", (12, 4, 20, 21))):
with self.subTest(mode=mode, bounds=bounds):
with self.assertRaises(ValueError):
implementation.FixedPatchStepper(cfg, bounds, context=context, coarse_boundary=mode)
implementation.FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
refinements=[bounds])
context.activate.assert_not_called()
# Both exact channel limits and the original periodic two-cell margin
# must reach context activation, with no allocation or device required.
@@ -102,7 +103,8 @@ class FaultGuardsCPU(unittest.TestCase):
("periodic", (2, 2, 6, 5))):
with self.subTest(mode=mode, bounds=bounds):
with self.assertRaisesRegex(RuntimeError, "validated before CUDA"):
implementation.FixedPatchStepper(cfg, bounds, context=context, coarse_boundary=mode)
implementation.FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
refinements=[bounds])
def fake_backend(self):
backend = PeriodicPatchStepper.__new__(PeriodicPatchStepper)
@@ -154,12 +156,12 @@ class FaultGuardsCPU(unittest.TestCase):
context = Mock(activate=nullcontext, sm_arch="sm_70")
with patch.object(implementation, "HALO", 2):
with self.assertRaisesRegex(RuntimeError, "four-cell"):
PeriodicPatchStepper(cfg, (4, 4, 12, 12), context=context)
PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)])
p = implementation.FixedPatch2D.from_config(cfg, (4, 4, 12, 12))
with patch.object(cuda, "Stream"), patch.object(implementation.FixedPatch2D, "from_config",
return_value=replace(p, tau_coarse=.9)):
with self.assertRaisesRegex(RuntimeError, "omega/tau"):
PeriodicPatchStepper(cfg, p.bounds, context=context)
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds])
module = Mock()
module.get_global.return_value = (Mock(), 16)
with patch.object(cuda, "Stream"), patch.object(compiler, "generate_config"), \
@@ -167,7 +169,7 @@ class FaultGuardsCPU(unittest.TestCase):
patch.object(compiler, "load_module", return_value=module), \
patch.object(cuda, "memcpy_htod") as upload:
with self.assertRaisesRegex(RuntimeError, "layout mismatch"):
PeriodicPatchStepper(cfg, p.bounds, context=context)
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds])
upload.assert_not_called()
@@ -241,7 +243,7 @@ class NormalBuildGPU(unittest.TestCase):
max_error = max_bc_error = 0.0
with CudaContext(0) as context:
with patch.object(compiler, "generate_config", side_effect=record_config):
backend = implementation.FixedPatchStepper(cfg, bounds, context=context,
backend = implementation.FixedPatchStepper(cfg, context=context, refinements=[bounds],
coarse_boundary="slot_reservoir")
with backend:
self.assertEqual(len(generated), 2)
@@ -311,7 +313,8 @@ class NormalBuildGPU(unittest.TestCase):
for a in (initial.coarse_f, initial.fine_f)))
max_pop = max_drift = max_moment = 0.0
with CudaContext(0) as context, PeriodicPatchStepper(
LBMConfig(nx=16, ny=16, viscosity=.1), (4, 4, 12, 12), context=context) as backend:
LBMConfig(nx=16, ny=16, viscosity=.1), context=context,
refinements=[(4, 4, 12, 12)]) as backend:
backend.initialize(*postcollision(state, spec, maps))
before = totals(backend.download(), maps)
for step in range(1, 9):
@@ -342,7 +345,7 @@ class NormalBuildGPU(unittest.TestCase):
fine_mask[4:-4, 4:-4] = True
initial[1][:, ~fine_mask] = np.nan
expected = scalar_interval(*[a.astype(np.float64) for a in initial], bounds)
with CudaContext(0) as context, PeriodicPatchStepper(cfg, bounds, context=context) as backend:
with CudaContext(0) as context, PeriodicPatchStepper(cfg, context=context, refinements=[bounds]) as backend:
self.assertEqual(backend.patch.fine_shape, (14, 16))
p = backend.patch
allocated = 2 * 9 * (17*13+16*14) * 4 + sum(a.nbytes for a in
@@ -84,13 +84,13 @@ class CoupledGPU(unittest.TestCase):
cases = (("dense_unshifted", False, {}),
("blocked_shifted", True,
dict(base_block=(4, 4), fine_block=(6, 6))))
dict(level_blocks=[(4, 4), (6, 6)])))
with CudaContext(0) as context:
for label, shifted, storage in cases:
with self.subTest(storage=label):
cfg = LBMConfig(nx=16, ny=16, viscosity=.0192,
ddf_shifting=shifted)
with FixedPatchStepper(cfg, (4, 4, 12, 12), context=context,
with FixedPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)],
**storage) as backend:
self.assertAlmostEqual(backend.patch.tau_coarse, spec.tau_coarse)
self.assertAlmostEqual(backend.patch.tau_fine, spec.tau_fine)
@@ -148,7 +148,7 @@ class CoupledGPU(unittest.TestCase):
maps = ref.build_maps(spec)
with CudaContext(0) as context:
with PeriodicPatchStepper(LBMConfig(nx=16, ny=16, viscosity=.1),
(4, 4, 12, 12), context=context) as backend:
context=context, refinements=[(4, 4, 12, 12)]) as backend:
backend.initialize(*postcollision(ref.make_state(spec), spec, maps))
coarse, fine = backend._levels
@@ -187,7 +187,7 @@ class CoupledGPU(unittest.TestCase):
with CudaContext(0) as context:
with patch.object(compiler, "compile_kernel", audit_compile):
backend = PeriodicPatchStepper(cfg, (4, 4, 12, 12), context=context)
backend = PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)])
with backend:
# Production allocations: four DDF arrays and four compact tables.
device_bytes = 2 * 9 * (16**2 + 24**2) * 4
@@ -270,7 +270,7 @@ class CoupledGPU(unittest.TestCase):
backend.download()
# Compile and execute the actual non-audited entry as well: one step.
with PeriodicPatchStepper(cfg, (4, 4, 12, 12), context=context) as plain:
with PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)]) as plain:
rest = postcollision(ref.make_state(spec), spec, maps)
plain.initialize(*rest)
plain.step()
@@ -41,8 +41,9 @@ def mocked(objects, jets, fine_block):
patch.object(compiler, "load_module", return_value=module), \
patch.object(cuda, "mem_alloc", side_effect=lambda size: Mock()), \
patch.object(cuda, "memcpy_htod", htod):
backend = FixedPatchStepper(config("periodic"), BOUNDS, context=context,
fine_objects=objects, fine_block=fine_block, jets=jets)
backend = FixedPatchStepper(config("periodic"), context=context, refinements=[BOUNDS],
level_blocks=[None, fine_block], level_objects=[(), tuple(objects)],
level_jets=[(), tuple(jets)])
return backend, htod
@@ -149,8 +150,9 @@ class JetStepperCPU(unittest.TestCase):
def test_jet_overlapping_legacy_aperture_rejected_before_cuda(self):
with patch.object(cuda, "Stream", side_effect=AssertionError("CUDA touched")):
with self.assertRaisesRegex(ValueError, "SurfaceActuation"):
FixedPatchStepper(config("periodic"), BOUNDS, context=Mock(),
fine_objects=[circle(actuation(SPEED))], jets=[jet()])
FixedPatchStepper(config("periodic"), context=Mock(), refinements=[BOUNDS],
level_objects=[(), (circle(actuation(SPEED)),)],
level_jets=[(), (jet(),)])
def run(mode, fine_block, *, objects, jets, switch=None):
@@ -158,8 +160,9 @@ def run(mode, fine_block, *, objects, jets, switch=None):
cfg = config(mode)
patch_ = FixedPatch2D.from_config(cfg, BOUNDS)
with CudaContext(0) as context, FixedPatchStepper(
cfg, BOUNDS, context=context, coarse_boundary=mode, fine_objects=objects,
fine_block=fine_block, jets=jets) as backend:
cfg, context=context, coarse_boundary=mode, refinements=[BOUNDS],
level_blocks=[None, fine_block], level_objects=[(), tuple(objects)],
level_jets=[(), tuple(jets)]) as backend:
backend.initialize(state(NY, NX, 1), state(*patch_.fine_shape, 2))
if switch is None:
backend.step(STEPS)
@@ -42,8 +42,9 @@ class RefinementMRTGPU(unittest.TestCase):
collision="MRT", ddf_shifting=shifted)
reference = None
for block in ((32, 48), (8, 8), (4, 1)):
with FixedPatchStepper(cfg, (8, 6, 40, 26), context=context, coarse_boundary=boundary,
base_block=block, fine_block=(8, 8), fine_objects=(body,)) as backend:
with FixedPatchStepper(cfg, context=context, coarse_boundary=boundary,
refinements=[(8, 6, 40, 26)], level_blocks=[block, (8, 8)],
level_objects=[(), (body,)]) as backend:
backend.initialize(*[state(*level.shape[1:]) for level in backend._levels])
backend.step(8)
raw = backend._download_raw()
@@ -63,8 +64,8 @@ class RefinementMRTGPU(unittest.TestCase):
results = {}
layouts = ((None, None), *((base, FINE_BLOCK) for base in (None, *BASE_BLOCKS)))
for base_block, fine_block in layouts:
with FixedPatchStepper(cfg, BOUNDS, context=context, fine_block=fine_block,
base_block=base_block) as backend:
with FixedPatchStepper(cfg, context=context, refinements=[BOUNDS],
level_blocks=[base_block, fine_block]) as backend:
backend.initialize(*[fixture.state(*level.shape[1:], seed) for seed, level in enumerate(backend._levels)])
backend.step(4)
results[base_block, fine_block] = raw(backend)
@@ -75,9 +76,9 @@ class RefinementMRTGPU(unittest.TestCase):
def test_shifted_all_blocked_three_level_mrt_smoke(self):
"""Per-level shear rate omega_l = 1/(3*2**l*nu + 1/2); finite ACTIVE leaves."""
cfg = LBMConfig(nx=16, ny=16, viscosity=.1, collision="MRT", ddf_shifting=True)
kw = dict(fine_block=(4, 4), base_block=(4, 4), child=(8, 8, 16, 16), child_block=(4, 4))
kw = dict(refinements=[(4, 4, 12, 12), (8, 8, 16, 16)], level_blocks=[(4, 4)] * 3)
with CudaContext(0) as context:
with FixedPatchStepper(cfg, (4, 4, 12, 12), context=context, **kw) as backend:
with FixedPatchStepper(cfg, context=context, **kw) as backend:
self.assertEqual(len(backend._level_cfgs), 3)
for level, level_cfg in enumerate(backend._level_cfgs):
checked = replace(level_cfg)
@@ -26,6 +26,12 @@ FACE = ((4, 4, 8, 12), (12, 4, 16, 12))
S1 = ((4, 4, 12, 12), (20, 4, 28, 12))
def levels(bounds, blocks=(None, None), objects=(), jets=(), **rest):
"""Two-level constructor keywords: one L1 rectangle or set, per-level blocks, L1 bodies/Jets."""
return dict(refinements=[bounds], level_blocks=list(blocks),
level_objects=[(), tuple(objects)], level_jets=[(), tuple(jets)], **rest)
def level_fine(patch_set, windows):
"""Level-wide fine array with each patch window filled from `windows`."""
out = np.full((9, *patch_set.fine_shape), np.nan, np.float32)
@@ -45,21 +51,21 @@ class MultipatchCPU(unittest.TestCase):
def test_rejections_before_cuda(self):
cfg = config("periodic")
context = object() # never activated: every case must fail first
for kw in (dict(), dict(fine_block=(8, 4)), dict(base_block=(4, 4)),
dict(fine_block=(8, 4), base_block=(4, 4), fine_objects=[circle()]),
dict(fine_block=(5, 4), base_block=(4, 4))):
for kw in (dict(), dict(blocks=(None, (8, 4))), dict(blocks=((4, 4), None)),
dict(blocks=((4, 4), (8, 4)), objects=[circle()]),
dict(blocks=((4, 4), (5, 4)))):
with self.subTest(kw=kw), self.assertRaises(ValueError):
FixedPatchStepper(cfg, ((4, 4, 8, 12), (14, 4, 18, 12)), context=context, **kw)
FixedPatchStepper(cfg, context=context, **levels(((4, 4, 8, 12), (14, 4, 18, 12)), **kw))
with self.assertRaisesRegex(ValueError, "margin"):
FixedPatchStepper(cfg, ((1, 4, 8, 12), (10, 4, 14, 12)), context=context,
fine_block=(8, 4), base_block=(4, 4))
FixedPatchStepper(cfg, context=context,
**levels(((1, 4, 8, 12), (10, 4, 14, 12)), blocks=((4, 4), (8, 4))))
from CelerisLab.body.jets import Jet, Parallel, Tube
cfg32 = LBMConfig(nx=32, ny=16, viscosity=.1)
span = Jet(Tube((5., 8.), 0., 22., .6), Parallel(0.), amplitude=0.)
with self.assertRaisesRegex(ValueError, "one jet"): # same obj_id cannot bypass it
FixedPatchStepper(cfg32, ((2, 2, 14, 14), (18, 2, 30, 14)), context=context,
fine_block=(4, 4), base_block=(4, 4),
fine_objects=[body(8., 8.), body(24., 8.)], jets=[span])
FixedPatchStepper(cfg32, context=context,
**levels(((2, 2, 14, 14), (18, 2, 30, 14)), blocks=((4, 4), (4, 4)),
objects=[body(8., 8.), body(24., 8.)], jets=[span]))
class MultipatchGPU(unittest.TestCase):
@@ -67,7 +73,7 @@ class MultipatchGPU(unittest.TestCase):
def run_steps(self, context, cfg, bounds, coarse, fine, **kw):
out = []
with FixedPatchStepper(cfg, bounds, context=context, **kw) as backend:
with FixedPatchStepper(cfg, context=context, **levels(bounds, **kw)) as backend:
backend.initialize(coarse, fine)
for step in self.STEPS:
backend.step(step - backend.step_count)
@@ -82,7 +88,7 @@ class MultipatchGPU(unittest.TestCase):
p = FixedPatch2D.from_config(cfg, BOUNDS)
s = FixedPatchSet2D.from_config(cfg, (BOUNDS,))
coarse, fine = state(NY, NX, 1), state(*p.fine_shape, 2)
kw = dict(coarse_boundary=mode, fine_block=(8, 4), base_block=(3, 4))
kw = dict(coarse_boundary=mode, blocks=((3, 4), (8, 4)))
old = self.run_steps(context, cfg, BOUNDS, coarse, fine, **kw)
new = self.run_steps(context, cfg, (BOUNDS,), coarse, level_fine(s, [fine]), **kw)
for step, a, b in zip(self.STEPS, old, new):
@@ -99,7 +105,7 @@ class MultipatchGPU(unittest.TestCase):
one = FixedPatchSet2D.from_config(cfg16, (S1[0],))
two = FixedPatchSet2D.from_config(cfg32, S1)
coarse, fine = state(16, 16, 3), state(*one.patches[0].fine_shape, 4)
kw = dict(fine_block=(4, 4), base_block=(4, 4))
kw = dict(blocks=((4, 4), (4, 4)))
with CudaContext(0) as context:
ref = self.run_steps(context, cfg16, (S1[0],), coarse, level_fine(one, [fine]), **kw)
tiled = np.concatenate([coarse, coarse], axis=2)
@@ -118,7 +124,7 @@ class MultipatchGPU(unittest.TestCase):
s = FixedPatchSet2D.from_config(cfg, FACE)
coarse = state(16, 24, 5)
fine = level_fine(s, [state(*p.fine_shape, 6 + i) for i, p in enumerate(s.patches)])
kw = dict(fine_block=(4, 4), base_block=(4, 4))
kw = dict(blocks=((4, 4), (4, 4)))
leaf = s.fine_kind == ACTIVE
support = s.fine_layout((4, 4)).owned
outer = support & (s.fine_kind == OUTER_GHOST)
@@ -164,7 +170,7 @@ class MultipatchBodiesGPU(unittest.TestCase):
def run_steps(self, context, cfg, bounds, coarse, fine, switch=None, **kw):
out = []
with FixedPatchStepper(cfg, bounds, context=context, **kw) as backend:
with FixedPatchStepper(cfg, context=context, **levels(bounds, **kw)) as backend:
backend.initialize(coarse, fine)
for step in self.STEPS:
if switch is not None and step == 8:
@@ -182,8 +188,7 @@ class MultipatchBodiesGPU(unittest.TestCase):
p = FixedPatch2D.from_config(cfg, BOUNDS)
s = FixedPatchSet2D.from_config(cfg, (BOUNDS,))
coarse, fine = state(NY, NX, 1), state(*p.fine_shape, 2)
kw = dict(coarse_boundary=mode, fine_block=(8, 4), base_block=(3, 4),
fine_objects=[circle()])
kw = dict(coarse_boundary=mode, blocks=((3, 4), (8, 4)), objects=[circle()])
old = self.run_steps(context, cfg, BOUNDS, coarse, fine, **kw)
new = self.run_steps(context, cfg, (BOUNDS,), coarse, level_fine(s, [fine]), **kw)
for step, a, b in zip(self.STEPS, old, new):
@@ -202,17 +207,17 @@ class MultipatchBodiesGPU(unittest.TestCase):
two = FixedPatchSet2D.from_config(cfg32, self.PATCHES)
coarse, fine = state(16, 16, 3), state(*one.patches[0].fine_shape, 4)
jet = lambda x: Jet(Tube((x, 8.), 0., 6., .6), Parallel(0.), amplitude=.002)
kw = dict(fine_block=(4, 4), base_block=(4, 4))
kw = dict(blocks=((4, 4), (4, 4)))
with CudaContext(0) as context:
for jets in ((), (jet(5.),)):
ref = self.run_steps(context, cfg16, self.PATCHES[:1], coarse, level_fine(one, [fine]),
switch=[(0, -.001)] if jets else None,
fine_objects=[body(8., 8.)], jets=jets, **kw)
objects=[body(8., 8.)], jets=jets, **kw)
both = jets and (jet(5.), jet(21.))
got = self.run_steps(context, cfg32, self.PATCHES, np.concatenate([coarse, coarse], 2),
level_fine(two, [fine, fine]),
switch=[(0, -.001), (1, -.001)] if jets else None,
fine_objects=[body(8., 8., 5), body(24., 8., 5)],
objects=[body(8., 8., 5), body(24., 8., 5)],
jets=both or (), **kw)
for step, a, b in zip(self.STEPS, ref, got):
label = f"jets={len(jets)} step {step}"
@@ -27,7 +27,16 @@ from test_refinement_blocked_base import raw
CFG = LBMConfig(nx=16, ny=16, viscosity=.1)
L1, L2 = (4, 4, 12, 12), (8, 8, 16, 16)
KW = dict(fine_block=(4, 4), base_block=(4, 4), child=L2, child_block=(4, 4))
B = (4, 4)
def levels(l1=L1, l2=L2, blocks=(B, B, B), objects=((), (), ()), jets=((), (), ())):
"""Level-list keywords for the scalar L1 patch with one scalar L2 child."""
return dict(refinements=[l1, l2], level_blocks=list(blocks),
level_objects=list(objects), level_jets=list(jets))
KW = levels()
def child_body(spec=None):
@@ -52,26 +61,29 @@ def mocked_child():
patch.object(compiler, "load_module", return_value=module), \
patch.object(cuda, "mem_alloc", side_effect=lambda size: Mock()), \
patch.object(cuda, "memcpy_htod"):
return FixedPatchStepper(CFG, L1, context=context, child_objects=[child_body()],
child_jets=[child_jet()], **KW)
return FixedPatchStepper(CFG, context=context,
**levels(objects=((), (), (child_body(),)), jets=((), (), (child_jet(),))))
class ThreeLevelCPU(unittest.TestCase):
def test_rejections_before_cuda(self):
context = object() # never activated: every case must fail first
bad = (dict(KW, child_block=None), dict(KW, fine_block=None),
dict(KW, fine_objects=[circle()]), dict(KW, child=(4, 8, 16, 16)),
dict(KW, child_block=(5, 4)))
bad = (levels(blocks=(B, B, None)), levels(blocks=(B, None, B)),
levels(objects=((), (circle(),), ())), levels(l2=(4, 8, 16, 16)),
levels(blocks=(B, B, (5, 4))))
for kw in bad:
with self.subTest(kw=kw), self.assertRaises(ValueError):
FixedPatchStepper(CFG, L1, context=context, **kw)
for kw in (dict(child_objects=[child_body()]), dict(child_jets=[child_jet()]),
dict(KW, child_jets=[child_jet()])):
FixedPatchStepper(CFG, context=context, **kw)
# L2 bodies/Jets without an L2 level (one entry too many), and an L2 Jet without a body.
two_level = dict(refinements=[L1], level_blocks=[None, None])
for kw in (dict(two_level, level_objects=[(), (), (child_body(),)]),
dict(two_level, level_jets=[(), (), (child_jet(),)]),
levels(jets=((), (), (child_jet(),)))):
with self.assertRaises(ValueError):
FixedPatchStepper(CFG, L1, context=context, **kw)
with self.assertRaises(ValueError): # several L1 patches + child: not yet
FixedPatchStepper(LBMConfig(nx=32, ny=16, viscosity=.1), ((4, 4, 12, 12), (20, 4, 28, 12)),
context=context, **KW)
FixedPatchStepper(CFG, context=context, **kw)
with self.assertRaises(ValueError): # several L1 patches + scalar child: not yet
FixedPatchStepper(LBMConfig(nx=32, ny=16, viscosity=.1), context=context,
**levels(l1=((4, 4, 12, 12), (20, 4, 28, 12))))
def test_four_halo_bfl_steps_and_fresh_middle_feeds(self):
@@ -80,11 +92,12 @@ class ThreeLevelCPU(unittest.TestCase):
f, g = run._levels[1:]
b = g.boundary
events, feeds = [], []
advance, gather = run._advance_child, run._gather_halo
def record_feed(buffer, **kw):
self.assertIs(buffer, (f.current, f.spare)[len(feeds)])
feeds.append(buffer)
advance(buffer, **kw)
advance, gather = run._advance, run._gather_halo
def record_feed(index, buffer, **kw): # index 2: L1 hop feeds L2
if index == 2:
self.assertIs(buffer, (f.current, f.spare)[len(feeds)])
feeds.append(buffer)
advance(index, buffer, **kw)
def record_halo(level, buffer, **kw):
if level is g:
events.append(("halo", buffer))
@@ -95,7 +108,7 @@ class ThreeLevelCPU(unittest.TestCase):
self.assertIs(kind, g.kind)
events.append(("step", src))
g.kernel.side_effect = record_step
with patch.object(run, "_advance_child", side_effect=record_feed), \
with patch.object(run, "_advance", side_effect=record_feed), \
patch.object(run, "_gather_halo", side_effect=record_halo):
run.step()
self.assertEqual(feeds, [f.current, f.spare])
@@ -105,8 +118,8 @@ class ThreeLevelCPU(unittest.TestCase):
self.assertGreater(len(np.unique(b.tables["block"])), 1)
# Negative control: reusing L1's old source at the midpoint must fail.
feeds.clear()
with patch.object(run, "_advance_child", side_effect=lambda buffer, **kw:
record_feed(f.current, **kw)):
with patch.object(run, "_advance", side_effect=lambda index, buffer, **kw:
record_feed(index, f.current if index == 2 else buffer, **kw)):
with self.assertRaises(AssertionError):
run.step()
run.close()
@@ -155,7 +168,7 @@ class ThreeLevelGPU(unittest.TestCase):
def test_equilibrium_is_kept_on_every_level(self):
from CelerisLab.cuda.context import CudaContext
feq = np.asarray(compute_feq_d2q9(1.0, .03, -.02), np.float32)[:, None, None]
with CudaContext(0) as ctx, FixedPatchStepper(CFG, L1, context=ctx, **KW) as run:
with CudaContext(0) as ctx, FixedPatchStepper(CFG, context=ctx, **KW) as run:
shapes = ((16, 16), run.patch.fine_shape, run.child_patch.fine_shape)
run.initialize(*(np.broadcast_to(feq, (9, *s)).copy() for s in shapes))
run.step(8)
@@ -168,15 +181,16 @@ class ThreeLevelGPU(unittest.TestCase):
def test_nonequilibrium_masks_and_fresh_middle_feeds(self):
from CelerisLab.cuda.context import CudaContext
with CudaContext(0) as ctx, FixedPatchStepper(CFG, L1, context=ctx, **KW) as run:
with CudaContext(0) as ctx, FixedPatchStepper(CFG, context=ctx, **KW) as run:
p1, p2 = run.patch, run.child_patch
run.initialize(state(16, 16, 1), state(*p1.fine_shape, 2), state(*p2.fine_shape, 3))
f = run._levels[1]
feeds, original = [], run._advance_child
def record(buffer, **kw):
feeds.append(int(buffer))
original(buffer, **kw)
with patch.object(run, "_advance_child", side_effect=record):
feeds, original = [], run._advance
def record(index, buffer, **kw): # index 2: L1 hop feeds L2
if index == 2:
feeds.append(int(buffer))
original(index, buffer, **kw)
with patch.object(run, "_advance", side_effect=record):
cur, spare = int(f.current), int(f.spare)
run.step(1)
self.assertEqual(feeds, [cur, spare]) # current G, then the new G of hop 1
@@ -203,8 +217,9 @@ class ThreeLevelBodyGPU(unittest.TestCase):
CFG, velocity=0., wall_normal_velocity=.001, wall_slot_width=4,
y_wall_bc="on_site_velocity", top_wall_bc="reservoir")
with CudaContext(0) as ctx, FixedPatchStepper(
cfg, L1, context=ctx, coarse_boundary=mode, child_objects=[child_body(spec)],
child_jets=jets, **dict(KW, child_block=block)) as run:
cfg, context=ctx, coarse_boundary=mode,
**levels(blocks=(B, B, block), objects=((), (), (child_body(spec),)),
jets=((), (), tuple(jets)))) as run:
run.initialize(*(state(*level.shape[1:], i + 1) for i, level in enumerate(run._levels)))
snapshots = []
for stop in (0, 1, 2, 4, 8):
@@ -78,10 +78,10 @@ class ThreeLevelMultipatchGPU(unittest.TestCase):
def run_case(self, ctx, cfg=CFG, parents=PARENTS, children=CHILDREN,
mode='periodic', blocks=((4, 4), (4, 4)), objects=(), drive=(), switch=False,
scalar_child=None):
kwargs = dict(child_rectangles_in_parent=children) if scalar_child is None else dict(child=scalar_child)
with FixedPatchStepper(config(cfg, mode), parents, context=ctx, coarse_boundary=mode,
base_block=(4, 4), fine_block=blocks[0], child_block=blocks[1],
child_objects=objects, child_jets=drive, **kwargs) as run:
child = children if scalar_child is None else scalar_child
with FixedPatchStepper(config(cfg, mode), context=ctx, coarse_boundary=mode,
refinements=[parents, child], level_blocks=[(4, 4), blocks[0], blocks[1]],
level_objects=[(), (), objects], level_jets=[(), (), drive]) as run:
frame = frames(run)
run.initialize(*(physical_state(level.shape[1:], *f)
for level, f in zip(run._levels, frame)))
@@ -26,9 +26,8 @@ FP64_ATOL = 3e-6
def make(ctx):
return FixedPatchStepper(CFG, PARENTS, context=ctx, base_block=(4, 4),
fine_block=(4, 4), child_block=(4, 4),
child_rectangles_in_parent=A)
return FixedPatchStepper(CFG, context=ctx, refinements=[PARENTS, A],
level_blocks=[(4, 4)] * 3)
def initial(run, uniform):
@@ -136,8 +136,8 @@ class ShiftedJetsGPU(unittest.TestCase):
Parallel(0.),amplitude=.013)
for rho in (.99,1.01):
with self.subTest(rho=rho),CudaContext(0) as ctx:
with FixedPatchStepper(cfg,(8,6,24,18),context=ctx,base_block=(4,4),fine_block=(4,4),
fine_objects=(obj,),jets=(whole,),observe_raw_exchange=True) as run:
with FixedPatchStepper(cfg,context=ctx,refinements=[(8,6,24,18)],level_blocks=[(4,4)]*2,
level_objects=[(),(obj,)],level_jets=[(),(whole,)],observe_raw_exchange=True) as run:
run._initialize_raw(initial(run,rho,u=.013,v=0.))
expected=run._download_raw();ledger=Ledger(self,run,1)
self.assertTrue(run._level_boundaries[1].tables['aperture'].all())
@@ -153,7 +153,8 @@ class ShiftedJetsGPU(unittest.TestCase):
obj=circle((16.,12.),2.15);j=drive((16.,12.),2.15)
for rho in (.99,1.01):
with self.subTest(rho=rho),CudaContext(0) as ctx,ExitStack() as owned:
settings=dict(bounds=(8,6,24,18),context=ctx,base_block=(4,4),fine_block=(4,4),fine_objects=(obj,),jets=(j,))
settings=dict(context=ctx,refinements=[(8,6,24,18)],level_blocks=[(4,4)]*2,
level_objects=[(),(obj,)],level_jets=[(),(j,)])
measured=owned.enter_context(FixedPatchStepper(cfg,observe_raw_exchange=True,**settings))
plain=owned.enter_context(FixedPatchStepper(cfg,**settings))
measured._initialize_raw(initial(measured,rho));plain._initialize_raw(initial(plain,rho))
@@ -186,8 +187,9 @@ class ShiftedJetsGPU(unittest.TestCase):
parents=((4,4,20,28),(24,4,44,28));a=((16,16,32,40),(56,16,72,40));b=(a[0],(60,16,76,40))
obj=circle((12.,14.),.8);j=drive((12.,14.),.8)
with CudaContext(0) as ctx,ExitStack() as owned:
old=owned.enter_context(FixedPatchStepper(cfg,parents,context=ctx,base_block=(4,4),fine_block=(4,4),
child_block=(4,4),child_rectangles_in_parent=a,child_objects=(obj,),child_jets=(j,),observe_raw_exchange=True))
old=owned.enter_context(FixedPatchStepper(cfg,context=ctx,refinements=[parents,a],
level_blocks=[(4,4)]*3,level_objects=[(),(),(obj,)],level_jets=[(),(),(j,)],
observe_raw_exchange=True))
old._initialize_raw(initial(old,.99));ledger=Ledger(self,old,2)
for speed in (.002,-.001):old.set_jet_amplitude(0,speed,level=2);ledger.step()
before=old._download_raw();count=old.step_count
@@ -22,9 +22,8 @@ B=((20,16,36,40),)
def make(ctx):
return FixedPatchStepper(CFG,PARENTS,context=ctx,base_block=(4,4),
fine_block=(4,4),child_block=(4,4),
child_rectangles_in_parent=A)
return FixedPatchStepper(CFG,context=ctx,refinements=[PARENTS,A],
level_blocks=[(4,4)]*3)
def initial(run):
@@ -1,497 +0,0 @@
"""Explicit host-only checks or admitted tiny GPU audit; never a long trajectory."""
import argparse
from contextlib import nullcontext
from dataclasses import replace
import hashlib
import json
import os
from pathlib import Path
import subprocess
import sys
import tempfile
import time
from types import SimpleNamespace
import unittest
from unittest.mock import Mock
import numpy as np
ROOT = Path(__file__).resolve().parents[3]
sys.path.insert(0, str(ROOT/'src'))
from CelerisLab.config import LBMConfig
import spacetime_gpu as gpu
import run_spacetime_gpu_n64 as trajectory
ref = gpu.ref
RECORDS = []
REPORT = None
OUTPUT = None
GPU_ADMITTED = False
def record(value):
RECORDS.append(value)
if OUTPUT is not None:
ref.write_receipt(OUTPUT,REPORT)
def config(n, shifted=False):
return LBMConfig(nx=n,ny=n,viscosity=.0192,velocity=0.,ddf_shifting=shifted)
def initial(plan, tagged=True):
arrays = []
for n, mask in ((plan.n,plan.maps.coarse_active),(plan.nf,plan.maps.fine_active)):
a = np.broadcast_to(ref.cpu.W[:,None,None], (9,n,n)).copy()
if tagged:
a *= 1+1e-3*np.random.default_rng(n).standard_normal(a.shape)
a[:,~mask] = np.nan
arrays.append(a)
return ref.cpu.State(*arrays)
class Host(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.plan = ref.Plan(12,(3,3,9,8))
def test_pins_and_supported_config(self):
gpu.check_sources()
for n in (12,16,64):
c,f = gpu.validate_config(config(n))
self.assertAlmostEqual(c.omega,1/.5576)
self.assertAlmostEqual(f.omega,1/.6152)
for change in (dict(ddf_shifting=1),dict(collision='TRT'),dict(nx=128,ny=128),
dict(ny=16),dict(les_enabled=True),dict(velocity=.03)):
with self.subTest(change=change), self.assertRaises(ValueError):
gpu.validate_config(replace(config(12),**change))
def test_shifted_codec_and_uploaded_physical_validation(self):
for n in (12,64):
self.assertTrue(gpu.validate_config(config(n,True))[1].ddf_shifting)
physical=gpu._WEIGHTS+2.**-35
stored=gpu._encode_physical(physical,True)
np.testing.assert_array_equal(stored,np.full((9,1,1),2.**-35,np.float32))
np.testing.assert_array_equal(gpu._decode_stored(stored,True),physical)
run=gpu.SpaceTimeGPU.__new__(gpu.SpaceTimeGPU)
run.status='new'; run.configs=gpu.validate_config(config(12,True)); run.plan=self.plan
run.ctx=SimpleNamespace(activate=nullcontext); run.cuda=Mock()
run.coarse=['coarse']; run.fine=['fine']; run.health_counts=np.zeros(6,np.uint64)
state=initial(self.plan,False)
run.initialize(state)
for call in run.cuda.memcpy_htod.call_args_list:
self.assertTrue((call.args[1][np.isfinite(call.args[1])]==0).all())
state.coarse_f[:]-=.01; state.fine_f[:]-=.01
run.initialize(state) # Valid negative stored values.
with self.assertRaisesRegex(ValueError,'exact shapes'):
run.initialize(ref.cpu.State(state.coarse_f[:1],state.fine_f))
for invalid in (-.01,np.nan):
bad=ref.cpu.State(state.coarse_f.copy(),state.fine_f.copy())
bad.coarse_f[0,0,0]=invalid
with self.assertRaisesRegex(ValueError,'positive finite'):
run.initialize(bad)
def test_shifted_transfer_translation_and_raw_ledger(self):
p=self.plan; t=gpu.pack_plan(p)
rng=np.random.default_rng(19)
for g in p.groups:
values=rng.uniform(.02,.45,len(g.samples)); weight=gpu._WEIGHTS[g.q,0,0]
np.testing.assert_allclose(g.weights@(values-weight),g.weights@values-weight,rtol=0,atol=2e-14)
# Uniform nonzero stored packets expose register omissions; exact rest would not.
arrays=[np.full((9,n,n),-.01,np.float32) for n in (p.n,p.nf)]
for a,m in zip(arrays,(p.maps.coarse_active,p.maps.fine_active)):
a[:,~m]=np.nan
state=ref.cpu.State(*arrays); g0=np.full((9,p.n,p.n),-.01,np.float32)
pre=np.repeat(g0.ravel()[t['origins'],None].astype(float),4,axis=1)
h=pre.astype(np.float32); registers=np.zeros(len(p.receivers))
args=(p,t,state,state,g0,g0,[(state.fine_f,state.fine_f)]*2,pre,h,registers)
ledger=gpu.rounding_ledger(*args,shifted=True)
self.assertEqual(max(map(abs,ledger['unexplained'])),0.)
self.assertGreater(ledger['unexplained_bound'],0.)
self.assertGreater(ledger['minimum_stored'],0.)
expected_mass=p.n*p.n*(1.+9*float(np.float32(-.01)))
self.assertEqual(ledger['unexplained_bound'],64*np.finfo(float).eps*expected_mass)
decoded=ref.cpu.State(*(gpu._decode_stored(a,True) for a in arrays))
with self.assertRaises(AssertionError):
gpu.rounding_ledger(p,t,decoded,*args[3:],shifted=True)
registers[0]+=.25*float(np.float32(-.01))
with self.assertRaisesRegex(AssertionError,'register mismatch'):
gpu.rounding_ledger(*args,shifted=True)
def test_packed_weights_and_packet_ownership(self):
for plan in (self.plan,ref.Plan(16,(4,5,11,12))):
t = gpu.pack_plan(plan)
self.assertEqual(t['sources'].shape,(len(plan.receivers),4))
self.assertEqual(np.count_nonzero(t['times']==-1),24)
self.assertEqual(gpu.table_hash(t),gpu.table_hash(gpu.pack_plan(plan)))
for i,g in enumerate(plan.groups):
np.testing.assert_array_equal(t['weights'][i,:,:len(g.samples)],g.weights)
np.testing.assert_allclose(t['weights'][i].sum(axis=1),1,rtol=0,atol=2e-14)
np.testing.assert_array_equal(t['samples'][i,:len(g.samples)],g.q*plan.n**2+g.samples)
for m in (0,1):
self.assertEqual(len(t[f'incoming{m}']),len(plan.outgoing[m]))
def test_duplicate_writer_is_rejected(self):
plan = self.plan
groups = list(plan.groups)
a,b = next((i,k) for i,g in enumerate(groups) for k,e in enumerate(g.events) if e is not None)
event = groups[a].events[b]
other = next(i for i,g in enumerate(groups) if i!=a and g.q==groups[a].q and event[0] in [e[0] for e in g.events if e])
events = list(groups[other].events)
k = next(k for k,e in enumerate(events) if e is not None and e[0]==event[0])
events[k] = event; groups[other] = replace(groups[other],events=tuple(events))
fake = SimpleNamespace(n=plan.n,nf=plan.nf,groups=groups,receivers=plan.receivers,outgoing=plan.outgoing)
with self.assertRaisesRegex(ValueError,'duplicate incoming'):
gpu.pack_plan(fake)
def test_rest_ledger_and_missing_packet_discrimination(self):
p,t = self.plan,gpu.pack_plan(self.plan)
state = initial(p,False)
state = ref.cpu.State(state.coarse_f.astype(np.float32),state.fine_f.astype(np.float32))
g0 = np.broadcast_to(ref.cpu.W.astype(np.float32)[:,None,None],(9,p.n,p.n)).copy()
pre = np.repeat(g0.ravel()[t['origins'],None].astype(float),4,axis=1)
h = pre.astype(np.float32); registers = np.zeros(len(p.receivers))
phases = [(state.fine_f,state.fine_f)]*2
args = (p,t,state,state,g0,g0,phases,pre,h)
ledger = gpu.rounding_ledger(*args,registers)
self.assertEqual(max(map(abs,ledger['unexplained'])),0)
np.testing.assert_array_equal(ledger['physical_collision'],np.array(ledger['coarse_collision'])
+ledger['fine0_collision']+ledger['fine1_collision'])
np.testing.assert_array_equal(ledger['child_rounding'],np.array(ledger['child_cast'])+ledger['child_interpolation'])
np.testing.assert_array_equal(ledger['collision_cell_mass'],np.zeros((3,4)))
registers[0] = .01
with self.assertRaisesRegex(AssertionError,'register mismatch'):
gpu.rounding_ledger(*args,registers)
def test_second_substep_characteristic_donor(self):
p = ref.Plan(16,(4,4,12,12)); t = gpu.pack_plan(p)
row = t['incoming1'][t['incoming1'][:,0]==5*32*32+10*32+7][0]
self.assertEqual(t['origins'][row[1]//4],5*16*16+4*16+3)
def test_failed_free_remains_retryable(self):
run=gpu.SpaceTimeGPU.__new__(gpu.SpaceTimeGPU)
run.ctx=SimpleNamespace(activate=nullcontext); run.stream=Mock()
first,second=Mock(),Mock(); first.free.side_effect=[RuntimeError('free failed'),None]
run.allocations=[first,second]; run.modules=[]; run.status='ready'
with self.assertRaisesRegex(RuntimeError,'free failed'):
run.close()
self.assertEqual(run.allocations,[first]); self.assertEqual(run.status,'cleanup_failed')
run.close()
self.assertEqual(run.status,'closed'); self.assertEqual(run.allocations,[])
second.free.assert_called_once()
def test_unmeasured_schedule_and_health_failure(self):
run=gpu.SpaceTimeGPU.__new__(gpu.SpaceTimeGPU)
run.status='ready'; run.step_count=0; run.identity=False; run.mode='spacetime'
run.ctx=SimpleNamespace(activate=nullcontext); run.cuda=Mock(); run.stream=Mock()
run.plan=self.plan; run.bounds=(3,3,9,8)
run.configs=gpu.validate_config(config(12)); run.coarse=list('abcd'); run.fine=list('efg')
run.tables=gpu.pack_plan(self.plan); run.device_tables={key:key for key in run.tables}
run.active='active'; run.pre='pre'; run.h='h'; run.registers='registers'; run.counts='counts'
run.health_counts=np.zeros(6,np.uint64)
run.launch=Mock(); run.read=Mock(return_value=np.zeros(6,np.uint32)); run.download=Mock()
names=['CoarseStart','Pull','Collide','Interpolate','Collide','Register','Inject','Pull',
'Collide','Register','Inject','Pull','ApplyRegisters']
for _ in range(2):
result=run.step(audit=False)
self.assertEqual(result['boundary_budget_status'],'not_measured')
self.assertIsNone(result['unexplained'])
self.assertEqual([call.args[1] for call in run.launch.call_args_list],names*2)
self.assertEqual(run.read.call_count,2); run.download.assert_not_called()
self.assertEqual(run.step_count,2); self.assertEqual(run.coarse,list('abcd'))
run.read.return_value=np.array([0,0,0,0,1,0],np.uint32)
with self.assertRaisesRegex(AssertionError,'health failed'):
run.step(audit=False)
self.assertEqual(run.status,'failed'); self.assertEqual(run.step_count,2)
self.assertEqual(run.health_counts.tolist(),[0,0,0,0,1,0])
def test_warmup_resets_arrivals_and_counters(self):
audits=[]
class Fake:
def initialize(self,state):
self.state=ref.cpu.State(state.coarse_f.copy(),state.fine_f.copy())
self.step_count=0; self.health_counts=np.zeros(6,np.uint64)
def download(self):
return ref.cpu.State(self.state.coarse_f.copy(),self.state.fine_f.copy(),tick=2*self.step_count)
def step(self,*,audit):
audits.append(audit)
self.step_count+=1; self.state.coarse_f[:]+=1e-4
fake=Fake(); check=Mock(); state=initial(self.plan)
actual,warm=trajectory.warm_and_reset(fake,state,check)
np.testing.assert_array_equal(actual.coarse_f,state.coarse_f)
self.assertEqual(check.call_count,32); self.assertEqual(fake.step_count,0)
self.assertTrue(warm['reset_verified']); self.assertEqual(warm['intervals'],32)
trajectory.warm_and_reset(fake,state,check,audit=True)
self.assertEqual(audits,[False]*32+[True]*32)
def test_accumulated_drift_ledger_and_exact_samples(self):
totals=trajectory.LedgerTotals()
for sign in (1.,-1.):
ledger={name:np.zeros(9) for name in totals.names}
ledger['coarse_collision'][0]=sign*2.**-20
ledger['physical_collision']=ledger['coarse_collision'].copy()
ledger['child_cast'][5]=sign*2.**-30
ledger['child_interpolation'][5]=sign*2.**-50
ledger['child_rounding']=ledger['child_cast']+ledger['child_interpolation']
ledger['receiver_rounding'][5]=-sign*2.**-32
ledger['net_change']=sum(ledger[k] for k in ('physical_collision','child_rounding','receiver_rounding'))
mass=ledger['coarse_collision'].sum()
ledger.update(unexplained_bound=1e-12,collision_cell_mass=[[mass,max(mass,0.),min(mass,0.),abs(mass)],[0.]*4,[0.]*4])
totals.add(ledger)
result=totals.snapshot(np.zeros(9))
self.assertEqual(result['intervals'],2)
self.assertEqual(result['components']['physical_collision']['directional'],[0.]*9)
self.assertGreater(result['components']['physical_collision']['absolute_step_mass_momentum_sum'][0],0)
self.assertEqual(result['components']['physical_collision']['max_absolute_interval_step'][0],1)
self.assertEqual(totals.snapshot()['endpoint_status'],'not_measured')
self.assertFalse(totals.snapshot(np.ones(9)*1e-8)['closure_pass'])
self.assertEqual(trajectory.differing_fields(dict(a=1.,b=[0.,2.]),dict(a=1.,b=[0.,2.])),[])
self.assertEqual(trajectory.differing_fields(dict(a=0.),dict(a=-0.)),['a'])
self.assertEqual(trajectory.differing_fields(dict(a=1.),dict(a=np.nextafter(1.,2.))),['a'])
def test_trajectory_screens_differences_and_json(self):
rows=[dict(tstar=t,velocity_l2=np.float64(.01),pressure_l2=.03,energy_relative=.01,
mass_relative=1e-7,momentum_change=[1e-6,-2e-6],minimum_population=.02,
minimum_boundary_pre=.02,minimum_boundary_stored=.02) for t in trajectory.TIMES]
cpu=dict(runs=[dict(worst=dict(velocity_l2=.02,pressure_l2=.04,energy_relative=.02)),
dict(rows=[dict(tstar=t,velocity_l2=.009,momentum_change=[0.,0.]) for t in trajectory.TIMES])])
uniform=dict(rows=[dict(tstar=.12,pressure_l2=.012253173806349701)])
result=trajectory.assess(rows,cpu,uniform,[0]*6)
self.assertTrue(result['campaign_pass']); self.assertTrue(result['experimental_pass'])
self.assertFalse(result['historical_pressure_gate']['passed'])
self.assertFalse(result['historical_pressure_gate']['matched_storage'])
self.assertAlmostEqual(result['gpu_minus_cpu']['rows'][0]['fields']['velocity_l2']['signed'],.001)
with tempfile.TemporaryDirectory() as directory:
path=Path(directory)/'receipt.json'
ref.write_receipt(path,dict(completed=True,**result))
self.assertTrue(json.loads(path.read_text())['completed'])
rows[0]['velocity_l2']=.06
failed=trajectory.assess(rows,cpu,uniform,[0,1,0,0,0,0])
ref.write_receipt(path,dict(completed=True,**failed))
saved=json.loads(path.read_text())
self.assertFalse(saved['campaign_pass']); self.assertFalse(saved['experimental_pass'])
for invalid in (float('nan'),-.01):
rows[0]['velocity_l2']=.01; rows[-1]['velocity_l2']=invalid
failed=trajectory.assess(rows,cpu,uniform,[0]*6)
self.assertFalse(failed['campaign_pass']); self.assertFalse(failed['experimental_pass'])
path.write_text('changed reference')
with self.assertRaisesRegex(ValueError,'pinned reference'):
trajectory.load_references(path,path)
def test_shifted_descriptive_comparison_and_runner_pin(self):
expected=dict(mass=4096.,momentum=[0.,-1e-4])
actual=dict(mass=4096.+2.**-20,momentum=[-1e-6,-2e-4])
difference=trajectory.sample_difference(actual,expected)
self.assertEqual(difference['mass']['signed'],2.**-20)
self.assertEqual(difference['momentum']['absolute'],[1e-6,1e-4])
self.assertEqual(trajectory.sha(Path(gpu.__file__).with_suffix('.cu')),trajectory.CUDA_SHA)
self.assertEqual(trajectory.LIMITS,dict(velocity_l2=.05,pressure_l2=.15,energy_relative=.05,mass_relative=1e-5))
self.assertEqual(trajectory.FACTORS,dict(velocity_l2=.8,pressure_l2=1.,energy_relative=1.))
def test_n64_table_guard_and_balanced_mutation(self):
guard=trajectory.table_guard
plan=ref.Plan(64,(8,8,56,48)); tables=gpu.pack_plan(plan)
self.assertEqual(guard.validate_tables(plan,tables)['status'],'passed')
face=next(i for i,g in enumerate(plan.groups) if g.kind=='face')
changed={key:value.copy() for key,value in tables.items()}
changed['weights'][face,0,0]=np.nextafter(changed['weights'][face,0,0],np.inf)
self.assertEqual(guard.validate_tables(plan,changed)['status'],'passed')
for mutation in ('coordinate','order','dtype','shape','layout','padding','negative_zero','nan','inf','balanced'):
changed={key:value.copy() for key,value in tables.items()}
w=changed['weights']
if mutation=='coordinate': changed['incoming1'][0,0]^=1
elif mutation=='order': changed['origins']=changed['origins'][::-1].copy()
elif mutation=='dtype': changed['weights']=w.astype(np.float32)
elif mutation=='shape': changed['weights']=w.reshape(532,10,4)
elif mutation=='layout': changed['weights']=np.asfortranarray(w)
elif mutation=='padding': w[face,0,9]=1e-30
elif mutation=='negative_zero': w[face,0,9]=-0.
elif mutation=='nan': w[face,0,0]=np.nan
elif mutation=='inf': w[face,0,0]=np.inf
else:
w[face,:2,:2] += 2.**-30*np.array([[1.,-1.],[-1.,1.]])
np.testing.assert_array_equal(w[face].sum(axis=1),tables['weights'][face].sum(axis=1))
np.testing.assert_array_equal(w[face].mean(axis=0),tables['weights'][face].mean(axis=0))
with self.subTest(mutation=mutation), self.assertRaises(ValueError):
guard.validate_tables(plan,changed)
changed={key:value.copy() for key,value in tables.items()}
changed['weights'][-1,0,0]+=1.
with self.assertRaises(ValueError):
guard.validate_tables(SimpleNamespace(n=64,groups=plan.groups[:-1]),changed)
groups=list(plan.groups); groups[0]=replace(groups[0],samples=groups[0].samples[:-1])
with self.assertRaisesRegex(ValueError,'coverage/size'):
guard.validate_tables(SimpleNamespace(n=64,groups=groups),tables)
class Device(unittest.TestCase):
shifted = False
def config(self,n):
return config(n,self.shifted)
@classmethod
def setUpClass(cls):
if not GPU_ADMITTED:
raise unittest.SkipTest('CUDA compilation/execution requires explicit tiny-job admission')
from CelerisLab.cuda.context import CudaContext
cls.context = CudaContext(0)
@classmethod
def tearDownClass(cls):
cls.context.close()
def test_tiny_equivalence_budgets_and_phase(self):
for mode,identity in (('spacetime',False),('spacetime',True),('frozen',False),('frozen',True)):
with self.subTest(mode=mode,identity=identity), gpu.SpaceTimeGPU(
self.config(12),(3,3,9,8),context=self.context,mode=mode,identity=identity) as run:
spec = ref.Spec(n_coarse=12,patch_lo=1,halo=2,tau_coarse=.5576,tau_fine=.6152,
collision='identity' if identity else 'srt')
for tagged,steps in ((False,2),(True,8)):
expected = initial(run.plan,tagged); run.initialize(expected)
before = run.download()
if self.shifted:
expected = before
for k in range(1,steps+1):
expected,_ = ref.advance(spec,run.plan,expected,mode)
ledger = run.step(); actual = run.download()
self.assertEqual(actual.tick,2*k); self.assertEqual(run.step_count,k)
for a,b in zip((actual.coarse_f,actual.fine_f),(expected.coarse_f,expected.fine_f)):
np.testing.assert_array_equal(np.isnan(a),np.isnan(b))
np.testing.assert_allclose(a,b,rtol=0,atol=3e-6,equal_nan=True)
total = lambda s: ref.cpu.MOMENTS.T @ ref.directional(
ref.cpu.State(s.coarse_f.astype(float),s.fine_f.astype(float)),run.plan.maps)
np.testing.assert_allclose(total(actual),total(before),rtol=0,atol=2e-4)
if tagged and not identity and k==1:
for a,b,tau,mask in zip((actual.coarse_f,actual.fine_f),
(expected.coarse_f,expected.fine_f),(.5576,.6152),
(run.plan.maps.coarse_active,run.plan.maps.fine_active)):
wrong = ref.cpu._collide(spec,b,np.isfinite(b),tau,mask,np.zeros(mask.shape,int))
self.assertGreater(float(np.nanmax(abs(a-wrong))),3e-6)
if k in (1,2,8):
record(dict(case='tiny',shifted=self.shifted,mode=mode,identity=identity,tagged=tagged,
step=k,device_bytes=run.device_bytes,ledger=ledger))
def test_omitted_packets_and_ghosts_fail(self):
for mutation in (1,2,3,4):
with self.subTest(mutation=mutation), gpu.SpaceTimeGPU(
self.config(12),(3,3,9,8),context=self.context,identity=self.shifted) as run:
state=initial(run.plan,not self.shifted)
if self.shifted:
state.coarse_f[:]+=1e-4; state.fine_f[:]+=1e-4
for a,mask in zip((state.coarse_f,state.fine_f),(run.plan.maps.coarse_active,run.plan.maps.fine_active)):
self.assertTrue((gpu._encode_physical(a,True)[:,mask]>0).all())
run.initialize(state)
with self.assertRaises(AssertionError):
run.step(mutation=mutation)
self.assertEqual(run.step_count,0)
self.assertEqual(run.status,'failed')
with self.assertRaises(RuntimeError):
run.download()
def test_frozen_donor_trap(self):
with gpu.SpaceTimeGPU(self.config(16),(4,4,12,12),context=self.context,mode='frozen',identity=True) as run:
state = initial(run.plan,False)
state.coarse_f[5,4,3]=1.; state.coarse_f[5,5,3]=2.
run.initialize(state); donor=run.download().coarse_f[5,4,3]; run.step()
self.assertEqual(run.download().fine_f[5,11,8],donor)
# Negative stored values can be physical in shifted mode; never clip either case.
with self.context.activate():
for physical_negative in ((False,True) if self.shifted else (True,)):
data=np.full((9,16,16),-.01,np.float32)
if self.shifted and physical_negative:
data=np.broadcast_to(-gpu._WEIGHTS-.01,(9,16,16)).astype(np.float32).copy()
run.cuda.memcpy_htod(run.coarse[1],data); run.cuda.memcpy_htod(run.coarse[3],data)
run.cuda.memset_d32_async(run.counts,0,6,run.stream)
t=run.device_tables; ng=len(run.plan.groups)
run.launch(0,'Interpolate',run.coarse[1],run.coarse[3],t['samples'],t['origins'],
t['sizes'],t['weights'],run.pre,run.h,np.uint32(ng),np.uint32(0),run.counts,count=ng)
counts=run.read(run.counts,(6,),np.uint32)
self.assertEqual(counts[1],4*ng*physical_negative)
self.assertEqual(counts[3],4*ng*physical_negative)
self.assertTrue((run.read(run.h,(ng,4))<0).all())
def test_n64_one_interval_only(self):
sys.path.insert(0,str(Path(__file__).parents[1]/'taylor_green'))
import oracle as tg
with gpu.SpaceTimeGPU(self.config(64),(8,8,56,48),context=self.context) as run:
arrays = [tg.initial((64,64),0,64,.0192),tg.initial((128,128),1,64,.0192)]
for a,mask in zip(arrays,(run.plan.maps.coarse_active,run.plan.maps.fine_active)):
a[:,~mask]=np.nan
state = ref.cpu.State(*arrays); run.initialize(state)
spec = ref.Spec(n_coarse=64,patch_lo=8,halo=16,tau_coarse=.5576,tau_fine=.6152,collision='srt')
expected,_ = ref.advance(spec,run.plan,run.download() if self.shifted else state)
started=time.monotonic(); ledger=run.step(); seconds=time.monotonic()-started
actual=run.download()
errors=[]
for a,b in zip((actual.coarse_f,actual.fine_f),(expected.coarse_f,expected.fine_f)):
np.testing.assert_array_equal(np.isnan(a),np.isnan(b))
np.testing.assert_allclose(a,b,rtol=0,atol=3e-6,equal_nan=True)
errors.append(float(np.nanmax(abs(a-b))))
record(dict(case='N64_one_interval',shifted=self.shifted,errors=errors,ledger=ledger,seconds=seconds,
device_bytes=run.device_bytes,table_sha256=gpu.table_hash(run.tables),
build_metadata=run.build_metadata,device=self.context.name))
def test_unmeasured_path_and_warm_reset(self):
with gpu.SpaceTimeGPU(self.config(12),(3,3,9,8),context=self.context) as run:
state=initial(run.plan)
run.initialize(state)
raw_initial=run._download_stored()
for _ in range(2):
run.step()
expected=run._download_stored()
run.initialize(state)
for _ in range(2):
result=run.step(audit=False)
self.assertEqual(result['boundary_budget_status'],'not_measured')
actual=run._download_stored()
for a,b in zip((actual.coarse_f,actual.fine_f),(expected.coarse_f,expected.fine_f)):
np.testing.assert_array_equal(a.view(np.uint32),b.view(np.uint32))
reset,warm=trajectory.warm_and_reset(run,state,lambda:None)
raw_reset=run._download_stored()
for a,b in zip((raw_reset.coarse_f,raw_reset.fine_f),(raw_initial.coarse_f,raw_initial.fine_f)):
np.testing.assert_array_equal(a.view(np.uint32),b.view(np.uint32))
record(dict(case='unmeasured_bitwise_and_reset',shifted=self.shifted,warmup=warm,health_counts=run.health_counts.tolist()))
class ShiftedDevice(Device):
shifted = True
def main():
global REPORT,OUTPUT,GPU_ADMITTED
parser=argparse.ArgumentParser(description=__doc__)
mode=parser.add_mutually_exclusive_group(required=True)
mode.add_argument('--host-only',action='store_true')
mode.add_argument('--gpu-admitted',action='store_true')
parser.add_argument('--output',type=Path)
args=parser.parse_args()
GPU_ADMITTED=args.gpu_admitted
if args.gpu_admitted and (not os.environ.get('CUDA_VISIBLE_DEVICES') or args.output is None):
parser.error('GPU job requires explicit CUDA_VISIBLE_DEVICES and --output')
if args.output is not None and args.output.exists():
parser.error('output exists; retain evidence and choose a new path')
started=time.monotonic()
report=dict(scope='tiny GPU equivalence and rounding audit; no long trajectory',completed=False,
requested_mode='admitted_tiny_gpu' if args.gpu_admitted else 'host_only',
commit=subprocess.check_output(['git','rev-parse','HEAD'],cwd=ROOT,text=True).strip(),
dirty=bool(subprocess.check_output(['git','status','--porcelain'],cwd=ROOT,text=True)),
hashes={p.name:hashlib.sha256(p.read_bytes()).hexdigest() for p in
(Path(__file__),Path(gpu.__file__),Path(gpu.__file__).with_suffix('.cu'))},
reference_hashes=gpu.PINS,cuda_visible_devices=os.environ.get('CUDA_VISIBLE_DEVICES'),records=RECORDS)
REPORT,OUTPUT=report,args.output
if args.output:
ref.write_receipt(args.output,report)
suite=unittest.TestLoader().loadTestsFromTestCase(Host)
if args.gpu_admitted:
suite.addTests(unittest.TestLoader().loadTestsFromTestCase(Device))
suite.addTests(unittest.TestLoader().loadTestsFromTestCase(ShiftedDevice))
result=unittest.TextTestRunner(verbosity=2).run(suite)
report.update(completed=True,passed=result.wasSuccessful(),tests=result.testsRun,
failures=[dict(test=str(test),error=error) for test,error in result.failures+result.errors],
seconds=time.monotonic()-started)
if args.output:
ref.write_receipt(args.output,report)
return 0 if result.wasSuccessful() else 1
if __name__=='__main__':
raise SystemExit(main())
@@ -1,205 +0,0 @@
"""Host checks or separately admitted tiny GPU ladder capability; no trajectories."""
import argparse
from contextlib import nullcontext
import json
import os
from pathlib import Path
import subprocess
import tempfile
import time
from types import SimpleNamespace
import unittest
from unittest.mock import Mock
import numpy as np
import run_spacetime_gpu_ladder as ladder
gpu,ref,tg=ladder.gpu,ladder.ref,ladder.tg
RECORDS=[]
ADMITTED=False
def config(n):
return ladder.old.LBMConfig(nx=n,ny=n,viscosity=.0003*n,velocity=0.,ddf_shifting=True)
class Host(unittest.TestCase):
def test_scaling_and_admission(self):
for _,n,refined in ladder.CASES:
s=ladder.setup(n,refined)
self.assertEqual(s['finest_n'],n*(2 if refined else 1))
self.assertEqual(len(s['early_steps']),65)
np.testing.assert_allclose(np.array(s['early_steps'])*.03/n,s['early_times'],rtol=0,atol=3e-17)
self.assertEqual(s['intervals']*.03/n,.48)
gpu.validate_config(config(n),uniform=not refined,allow_n128=refined)
with self.assertRaises(ValueError): gpu.validate_config(config(128))
with self.assertRaises(ValueError): gpu.validate_config(config(256),allow_n128=True)
with self.assertRaises(ValueError): gpu.validate_config(config(512),uniform=True)
def test_n128_tables_and_mutations(self):
plan=ref.Plan(128,(16,16,112,96)); tables=gpu.pack_plan(plan)
out=ladder.old.table_guard.validate_tables(plan,tables,allow_n128=True)
self.assertEqual(out['structure_sha256'],'ee4ecb645674ae04eb87220a5217851405ccc0f45fbb0fe210499dcea5cd93b1')
self.assertEqual(len(plan.groups),1060)
with self.assertRaises(ValueError): ladder.old.table_guard.validate_tables(plan,tables)
for kind in ('topology','balanced_weights'):
bad={k:v.copy() for k,v in tables.items()}
if kind=='topology': bad['sources'][0,0]+=1
else: bad['weights'][0,:2,:2]+=1e-5*np.array([[1,-1],[-1,1]])
with self.assertRaises(ValueError): ladder.old.table_guard.validate_tables(plan,bad,allow_n128=True)
def test_projection_manufactured_nonuniform_leaves(self):
n=16; plan=ref.Plan(n,(3,3,13,12)); masks=(plan.maps.coarse_active,plan.maps.fine_active)
coords=[tg.centers(m.shape,l) for l,m in enumerate(masks)]
x=np.concatenate([v[0][m] for v,m in zip(coords,masks)])
y=np.concatenate([v[1][m] for v,m in zip(coords,masks)])
w=np.concatenate([np.full(m.sum(),.25**l) for l,m in enumerate(masks)])
b=np.column_stack((np.cos(4*np.pi*x/n),np.sin(4*np.pi*x/n),np.cos(4*np.pi*y/n),np.sin(4*np.pi*y/n)))
b-=w@b/w.sum(); gram=b.T@(w[:,None]*b)
residual=np.cos(6*np.pi*x/n)+np.sin(6*np.pi*y/n); residual-=w@residual/w.sum()
residual-=b@np.linalg.solve(gram,b.T@(w*residual)); residual*=1e-5
coefficients=np.array([2,-3,4,-1])*1e-5
pressure=tg.exact(x,y,0,n,.0003*n)[2]+b@coefficients+residual+.017
arrays=[]; offset=0
for m in masks:
a=np.full((9,*m.shape),np.nan); count=m.sum()
a[:,m]=ref.cpu.W[:,None]*(1+3*pressure[offset:offset+count]); arrays.append(a); offset+=count
result=ladder.pressure_projection(arrays,masks,0,n,.0003*n)
np.testing.assert_allclose(result['coefficients'],coefficients,rtol=0,atol=3e-17)
self.assertAlmostEqual(result['residual_rms'],np.sqrt(w@(residual*residual)/w.sum()),places=15)
np.testing.assert_allclose(result['orthogonality'],0,rtol=0,atol=1e-18)
self.assertLess(abs(result['energy_closure']),1e-20)
expected=tg.metrics(arrays,masks,0,n,.0003*n)['pressure_l2']
self.assertAlmostEqual(result['relative_rms'],expected,places=12)
def test_uniform_budget_and_negative_control(self):
rng=np.random.default_rng(12); a=rng.normal(0,.001,(9,12,12)).astype(np.float32)
g=(a*.99).astype(np.float32)
b=np.stack([np.roll(g[q],(int(ref.cpu.CY[q]),int(ref.cpu.CX[q])),axis=(0,1)) for q in range(9)])
ledger=gpu.uniform_ledger(a,b,g,shifted=True)
self.assertLess(max(abs(np.array(ledger['unexplained']))),ledger['unexplained_bound'])
b[1,0,0]+=1e-4
with self.assertRaises(AssertionError): gpu.uniform_ledger(a,b,g,shifted=True)
def test_uniform_failed_io_poisoning(self):
run=object.__new__(gpu.UniformGPU); run.configs=(config(12),); run.status='ready'
run.ctx=SimpleNamespace(activate=nullcontext); run.buffers=['f']; run.cuda=SimpleNamespace(memcpy_htod=Mock(side_effect=RuntimeError('copy')))
with self.assertRaisesRegex(RuntimeError,'copy'): run.initialize(np.broadcast_to(ref.cpu.W[:,None,None],(9,12,12)))
self.assertEqual(run.status,'failed'); run.status='ready'; run.read=Mock(side_effect=RuntimeError('read'))
with self.assertRaisesRegex(RuntimeError,'read'): run._download_stored()
self.assertEqual(run.status,'failed')
def test_uniform_health_mask_reaches_both_kernels(self):
run=object.__new__(gpu.UniformGPU); run.configs=(config(16),); run.status='ready'; run.identity=False
run.ctx=SimpleNamespace(activate=nullcontext); run.buffers=['f','g','out']; run.active=object(); run.counts='counts'
run.stream=object(); run.cuda=SimpleNamespace(memset_d32_async=Mock()); run.launch=Mock()
run.read=Mock(return_value=np.zeros(6,np.uint32)); run.health_counts=np.zeros(6,np.uint64); run.step_count=0
run.step(audit=False)
self.assertEqual([call.args[1] for call in run.launch.call_args_list],['Collide','Pull'])
self.assertTrue(all(call.args[4] is run.active for call in run.launch.call_args_list))
def test_zero_error_comparisons(self):
rows=[dict(tstar=t,velocity_l2=0.,pressure_l2=0.,energy_relative=0.) for t in ladder.old.TIMES]
result=ladder.comparisons([dict(name=name,rows=rows) for name,_,_ in ladder.CASES],dict(rows=rows))
self.assertIsNone(result['trends'][0]['samples'][0]['pressure_l2']['ratio'])
self.assertNotIn('two_point_slope',result['controls'][0]['samples'][0]['pressure_l2'])
self.assertIn('two_point_slope',result['trends'][0]['samples'][0]['pressure_l2'])
json.dumps(result,allow_nan=False)
def test_frozen_screen_and_json_receipt(self):
rows=[dict(tstar=t,minimum_population=.02,**{key:np.float64(limit*.5) for key,limit in ladder.LIMITS.items()}) for t in ladder.old.TIMES]
self.assertTrue(ladder.assess(rows,[0]*6)['campaign_pass'])
rows[0]['mass_relative']=2e-5
failed=ladder.assess(rows,[0]*6); self.assertFalse(failed['campaign_pass'])
with tempfile.TemporaryDirectory() as tmp:
path=Path(tmp)/'receipt.json'; ref.write_receipt(path,dict(completed=True,passed=np.bool_(False),assessment=failed))
saved=json.loads(path.read_text()); self.assertFalse(saved['passed']); self.assertTrue(saved['completed'])
class Device(unittest.TestCase):
@classmethod
def setUpClass(cls):
if not ADMITTED: raise unittest.SkipTest('explicit tiny GPU admission required')
from CelerisLab.cuda.context import CudaContext
cls.context=CudaContext(0)
@classmethod
def tearDownClass(cls): cls.context.close()
def test_uniform_actual_upload_oracle_and_reset(self):
for n in (16,64,128,256):
with gpu.UniformGPU(config(n),context=self.context) as run:
analytic=tg.initial((n,n),0,n,.0003*n); run.initialize(analytic); start=run._download_stored()
actual_start=run.download(); mask=np.ones((n,n),bool)
spec=ref.Spec(n_coarse=n,patch_lo=1,halo=2,tau_coarse=.5+.0009*n,tau_fine=.5+.0018*n,collision='srt')
collided=ref.cpu._collide(spec,actual_start,np.isfinite(actual_start),spec.tau_coarse,mask,np.zeros((n,n),int))
expected=np.stack([np.roll(collided[q],(int(ref.cpu.CY[q]),int(ref.cpu.CX[q])),axis=(0,1)) for q in range(9)])
ledger=run.step(); actual=run.download()
np.testing.assert_allclose(actual,expected,rtol=0,atol=3e-6)
audited=run._download_stored(); run.initialize(analytic); run.step(audit=False)
np.testing.assert_array_equal(audited.view(np.uint32),run._download_stored().view(np.uint32))
run.initialize(analytic); np.testing.assert_array_equal(start.view(np.uint32),run._download_stored().view(np.uint32))
self.assertEqual(run.step_count,0); self.assertFalse(run.health_counts.any())
RECORDS.append(dict(case=f'uniform{n}_one_interval',error=float(abs(actual-expected).max()),ledger=ledger,
build_metadata=run.build_metadata,device_bytes=run.device_bytes,raw_reset_verified=True))
def test_uniform_tagged_phase_and_health_controls(self):
n=16; rng=np.random.default_rng(n)
analytic=np.broadcast_to(ref.cpu.W[:,None,None],(9,n,n))*(1+1e-3*rng.standard_normal((9,n,n)))
for identity in (True,False):
with gpu.UniformGPU(config(n),context=self.context,identity=identity) as run:
run.initialize(analytic); start=run.download(); raw_start=run._download_stored(); mask=np.ones((n,n),bool)
spec=ref.Spec(tau_coarse=.5+.0009*n,collision='identity' if identity else 'srt')
collided=ref.cpu._collide(spec,start,np.isfinite(start),spec.tau_coarse,mask,np.zeros((n,n),int))
expected=np.stack([np.roll(collided[q],(int(ref.cpu.CY[q]),int(ref.cpu.CX[q])),axis=(0,1)) for q in range(9)])
ledger=run.step(); actual=run.download(); np.testing.assert_allclose(actual,expected,rtol=0,atol=3e-6)
if identity:
rolled=np.stack([np.roll(raw_start[q],(int(ref.cpu.CY[q]),int(ref.cpu.CX[q])),axis=(0,1)) for q in range(9)])
np.testing.assert_array_equal(run._download_stored().view(np.uint32),rolled.view(np.uint32))
if not identity:
wrong=ref.cpu._collide(spec,expected,np.isfinite(expected),spec.tau_coarse,mask,np.zeros((n,n),int))
self.assertGreater(float(abs(actual-wrong).max()),3e-6)
RECORDS.append(dict(case='uniform_tagged',identity=identity,error=float(abs(actual-expected).max()),ledger=ledger))
with gpu.UniformGPU(config(n),context=self.context) as run:
run.initialize(analytic)
with self.context.activate():
bad=np.broadcast_to(-gpu._WEIGHTS-.01,(9,n,n)).astype(np.float32).copy()
run.cuda.memcpy_htod(run.buffers[0],bad)
with self.assertRaises(AssertionError): run.step()
self.assertTrue(run.health_counts.any()); self.assertEqual(run.status,'failed')
RECORDS.append(dict(case='uniform_health_negative_control',health_counts=run.health_counts.tolist()))
def test_refined_n128_actual_upload_oracle(self):
with gpu.SpaceTimeGPU(config(128),(16,16,112,96),context=self.context,allow_n128=True) as run:
tables=ladder.old.table_guard.validate_tables(run.plan,run.tables,allow_n128=True)
run.initialize(ref.cpu.State(tg.initial((128,128),0,128,.0384),tg.initial((256,256),1,128,.0384)))
spec=ref.Spec(n_coarse=128,patch_lo=16,halo=32,tau_coarse=.6152,tau_fine=.7304,collision='srt')
expected,_=ref.advance(spec,run.plan,run.download()); ledger=run.step(); actual=run.download(); errors=[]
for a,b in zip((actual.coarse_f,actual.fine_f),(expected.coarse_f,expected.fine_f)):
np.testing.assert_allclose(a,b,rtol=0,atol=3e-6,equal_nan=True); errors.append(float(np.nanmax(abs(a-b))))
RECORDS.append(dict(case='refined128_one_interval',errors=errors,ledger=ledger,tables=tables,
build_metadata=run.build_metadata,device_bytes=run.device_bytes))
def main():
global ADMITTED
p=argparse.ArgumentParser(description=__doc__); modes=p.add_mutually_exclusive_group(required=True)
modes.add_argument('--host-only',action='store_true'); modes.add_argument('--gpu-admitted',action='store_true')
p.add_argument('--output',type=Path,required=True); args=p.parse_args(); ADMITTED=args.gpu_admitted
if args.output.exists(): p.error('output exists; preserve evidence')
if ADMITTED and not os.environ.get('CUDA_VISIBLE_DEVICES'): p.error('explicit CUDA_VISIBLE_DEVICES required')
paths=(Path(__file__),Path(ladder.__file__),Path(gpu.__file__),Path(gpu.__file__).with_suffix('.cu'),Path(ladder.old.table_guard.__file__))
report=dict(completed=False,passed=False,mode='tiny_gpu' if ADMITTED else 'host_only',records=RECORDS,
source=dict(commit=subprocess.check_output(['git','rev-parse','HEAD'],cwd=ladder.ROOT,text=True).strip(),
dirty=bool(subprocess.check_output(['git','status','--porcelain'],cwd=ladder.ROOT,text=True)),
hashes={p.name:ladder.old.sha(p) for p in paths}))
ref.write_receipt(args.output,report); started=time.monotonic()
suite=unittest.TestLoader().loadTestsFromTestCase(Host)
if ADMITTED: suite.addTests(unittest.TestLoader().loadTestsFromTestCase(Device))
result=unittest.TextTestRunner(verbosity=2).run(suite)
report.update(completed=True,passed=result.wasSuccessful(),tests=result.testsRun,seconds=time.monotonic()-started,
failures=[dict(test=str(t),error=e) for t,e in result.errors+result.failures])
ref.write_receipt(args.output,report); return 0 if report['passed'] else 1
if __name__=='__main__': raise SystemExit(main())
@@ -1,155 +0,0 @@
"""Tiny CPU algebra/event tests; no full trajectory or GPU execution."""
from dataclasses import replace
import json
from pathlib import Path
import tempfile
import unittest
import numpy as np
import spacetime_reference as st
class SpaceTime(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.plan = st.Plan(12, (3, 3, 9, 8))
cls.spec = st.Spec(n_coarse=12, patch_lo=1, halo=2,
tau_coarse=.5576, tau_fine=.6152, collision="srt")
def state(self, tagged=False):
arrays = []
for n, mask in ((12,self.plan.maps.coarse_active),(24,self.plan.maps.fine_active)):
q, y, x = np.indices((9,n,n))
a = np.broadcast_to(st.cpu.W[:,None,None], (9,n,n)).copy()
if tagged:
a *= 1+1e-3*np.random.default_rng(n).normal(size=a.shape)
a[:,~mask] = np.nan
arrays.append(a)
return st.cpu.State(*arrays)
def test_events_and_corner_leftovers(self):
groups = [g for g in self.plan.groups if None in g.events]
self.assertEqual(len(groups), 8)
self.assertTrue(all(g.events.count(None)==3 for g in groups))
for m in (0,1):
events = list(map(tuple,self.plan.outgoing[m]))
self.assertEqual(len(events),len(set(events)))
st.Plan(16,(4,5,11,12))
def test_interpolation(self):
for g in self.plan.groups:
samples, a, e, coeff = st.interpolation(g.kind,g.points)
np.testing.assert_allclose(g.weights@np.ones(len(samples)),1,rtol=0,atol=2e-14)
np.testing.assert_allclose(g.weights.mean(axis=0), np.eye(len(samples))[1 if g.kind=='face' else 0],rtol=0,atol=2e-14)
if g.kind=='face':
beta=np.array([1.,.03,.02,0.])
else:
cx,cy=st.cpu.CX[g.q],st.cpu.CY[g.q]
beta=np.array([1.,.03,.02,-cx*.03-cy*.02])
steady=a@np.array([1.,.03,.02,0.])
self.assertLess(abs((coeff@steady)[3]),2e-14)
np.testing.assert_allclose(g.weights@(a@beta),e@beta,rtol=0,atol=2e-14)
def test_rest(self):
initial=self.state()
final,d=st.advance(self.spec,self.plan,initial)
for a,b in zip((initial.coarse_f,initial.fine_f),(final.coarse_f,final.fine_f)):
np.testing.assert_allclose(a,b,rtol=0,atol=2e-14,equal_nan=True)
def test_frozen_recovers_ivp(self):
for collision in ('identity','srt'):
spec=replace(self.spec,collision=collision)
a=b=self.state(True)
for _ in range(2):
a,_=st.advance(spec,self.plan,a,'frozen')
b,_=st.cpu.advance_coarse_once(spec,self.plan.maps,b)
for aa,bb in zip((a.coarse_f,a.fine_f),(b.coarse_f,b.fine_f)):
np.testing.assert_allclose(aa,bb,rtol=0,atol=2e-14,equal_nan=True)
def test_second_substep_uses_characteristic_origin(self):
# Review counterexample in (x,y): ghost (7,10), m=1 traces back
# to (6,9), parent (3,4), not its current parent (3,5).
plan=st.Plan(16,(4,4,12,12))
owners=[g for g in plan.groups if g.q==5 and (1,10*32+7) in g.events]
self.assertEqual(len(owners),1)
self.assertEqual(owners[0].source,4*16+3)
spec=st.Spec(n_coarse=16,patch_lo=2,halo=4,collision='identity')
arrays=[]
for n,mask in ((16,plan.maps.coarse_active),(32,plan.maps.fine_active)):
a=np.broadcast_to(st.cpu.W[:,None,None],(9,n,n)).copy()
a[:,~mask]=np.nan
arrays.append(a)
arrays[0][5,4,3]=1.; arrays[0][5,5,3]=2.
final,_=st.advance(spec,plan,st.cpu.State(*arrays),'frozen')
self.assertEqual(final.fine_f[5,11,8],1.)
self.assertNotEqual(final.fine_f[5,11,8],arrays[0][5,5,3])
def test_corner_affine_tradeoff_is_explicit(self):
group=next(g for g in self.plan.groups if g.kind=='corner')
_,a,e,coeff=st.interpolation(group.kind,group.points)
linear_x=np.array([0.,1.,0.,0.])
# The two paper constraints are consistent. Arbitrary affine exactness
# is the incompatible additional demand.
self.assertEqual(abs(float((e@linear_x).mean())),.125)
fitted=coeff@(a@linear_x)
self.assertLess(abs(fitted[3]),2e-14)
self.assertLess(abs(float((e@fitted).mean())),2e-14)
self.assertGreater(np.max(np.abs(e@fitted-e@linear_x)),.01)
def test_directional_budgets(self):
for collision in ('identity','srt'):
spec=replace(self.spec,collision=collision)
a=self.state(True)
for _ in range(2):
a,d=st.advance(spec,self.plan,a)
np.testing.assert_allclose(d['directional_residual'],0,rtol=0,atol=2e-12)
self.assertLess(d['group_error'],2e-14)
def test_missing_packets_fail(self):
for mutation in ('omit_leftover','omit_outgoing_0','omit_outgoing_1'):
_,d=st.advance(self.spec,self.plan,self.state(True),mutation=mutation)
self.assertGreater(np.max(np.abs(d['directional_residual'])),1e-5)
def test_negative_interpolation_is_reported_not_clipped(self):
initial=self.state()
group=self.plan.groups[0]
initial.coarse_f.reshape(9,-1)[group.q,group.source]=-.01
spec=replace(self.spec,collision='identity')
_,d=st.advance(spec,self.plan,initial,'frozen')
self.assertGreaterEqual(d['negative_boundary_count'],4)
self.assertEqual(d['min_boundary'],-.01)
self.assertEqual(d['nonfinite_boundary_count'],0)
class Receipts(unittest.TestCase):
def test_completed_and_failed_screen_receipts(self):
for passed in (True, False):
with self.subTest(passed=passed), tempfile.TemporaryDirectory() as directory:
# Same NumPy comparison type produced by the final metric screen.
checks = {'velocity_l2': np.float64(.5 if passed else 1.) <= .8,
'mass_momentum': True}
self.assertIsInstance(checks['velocity_l2'], np.bool_)
result = dict(completed=True, checks=checks,
experimental_pass=all(checks.values()),
runs=[dict(rows=[dict(step=np.int64(1024),
mass_relative=np.float32(0.))])])
path = Path(directory)/'receipt.json'
st.write_receipt(path, result)
saved = json.loads(path.read_text())
self.assertIs(saved['completed'], True)
self.assertIs(saved['experimental_pass'], passed)
self.assertIs(saved['checks']['velocity_l2'], passed)
self.assertEqual(saved['runs'][0]['rows'][0],
dict(step=1024, mass_relative=0.))
def test_receipts_still_reject_nonfinite_and_unknown_values(self):
with tempfile.TemporaryDirectory() as directory:
path = Path(directory)/'receipt.json'
with self.assertRaises(ValueError):
st.write_receipt(path, {'invalid': np.float32('nan')})
with self.assertRaises(TypeError):
st.write_receipt(path, {'invalid': object()})
self.assertFalse(path.exists())
if __name__=='__main__':
unittest.main(verbosity=2)
@@ -1,287 +0,0 @@
"""Host-only ownership/geometry tests, never a GPU or accuracy admission."""
import copy
import json
import sys
import unittest
import numpy as np
from CelerisLab.config import LBMConfig
from CelerisLab.lbm.blocks import BlockLayout2D
from CelerisLab.lbm.refinement import FixedPatch2D, FixedPatchSet2D
from spacetime_union_plan import UnionPlan, UnresolvedTopology, owned_slots, validate_ownership
import spacetime_reference as ref
import spacetime_gpu as frozen # pack_plan only: no CUDA import/owner construction
from spacetime_table_guard import exact_weights
MATRIX=[]
ENUMERATION={}
CASES={
'rectangle': ([(4,4,12,12)],True),
'two_separated': ([(3,3,6,6),(9,9,12,12)],True),
'one_cell_face_gap': ([(3,3,6,10),(7,3,10,10)],True),
'one_cell_diagonal_gap': ([(3,3,6,6),(7,7,10,10)],True),
'staggered_gap': ([(3,3,6,8),(7,5,11,10)],True),
'thin_rectangle': ([(4,4,5,11)],True),
'concave_L': ([(4,4,5,7),(4,5,7,7)],True),
'corner_contact': ([(3,3,6,6),(6,6,9,9)],True),
'cross': ([(3,6,13,9),(6,3,9,13)],True),
'narrow_notch': ([(3,3,6,11),(7,3,10,11),(3,9,10,11)],True),
'hole': ([(3,3,13,5),(3,11,13,13),(3,5,5,11),(11,5,13,11)],True),
}
def pair(rects,n=16,ny=None):
cfg=LBMConfig(nx=n,ny=n if ny is None else ny,viscosity=.0192,velocity=0.)
return FixedPatchSet2D.from_config(cfg,rects)
def assert_same(test,a,b):
# Includes event-child order, zero padding, integer dtype/shape and FP64 bits.
aa,bb=frozen.pack_plan(a),frozen.pack_plan(b)
test.assertEqual(aa.keys(),bb.keys())
for key in aa:
test.assertEqual((aa[key].dtype,aa[key].shape,aa[key].tobytes()),
(bb[key].dtype,bb[key].shape,bb[key].tobytes()),key)
for x,y in zip(a.groups,b.groups):
test.assertEqual((x.q,x.source,x.receiver,x.kind,x.points,x.events),
(y.q,y.source,y.receiver,y.kind,y.points,y.events))
# Frozen pack_plan has no transit column and is NOT a union runtime format.
np.testing.assert_array_equal(getattr(a,'transit',np.empty((0,3),int)),
getattr(b,'transit',np.empty((0,3),int)))
class UnionContract(unittest.TestCase):
def test_single_rectangle_exact_707afe6(self):
frozen.check_sources()
for n,b in ((12,(3,3,9,8)),(16,(4,5,11,12)),(16,(4,4,5,7)),(64,(8,8,56,48))):
with self.subTest(n=n,bounds=b):
assert_same(self,UnionPlan(pair([b],n)),ref.Plan(n,b))
self.assertNotIn('pycuda.driver',sys.modules)
def test_union_decomposition_and_permutation_invariance(self):
baseline=UnionPlan(pair([(4,4,12,12)]))
decompositions=[[(4,4,8,12),(8,4,12,12)],[(4,4,10,12),(6,4,12,12)],
[(4,4,12,8),(4,8,12,12)],[(4,4,12,12),(4,4,12,12)]]
for rectangles in decompositions:
for order in (rectangles,list(reversed(rectangles))):
assert_same(self,baseline,UnionPlan(pair(order)))
two=CASES['two_separated'][0]
assert_same(self,UnionPlan(pair(two)),UnionPlan(pair(list(reversed(two)))))
lshape=CASES['concave_L'][0]
for decomposition in (list(reversed(lshape)),[(4,4,5,5),(4,5,7,7)],lshape+lshape):
assert_same(self,UnionPlan(pair(lshape)),UnionPlan(pair(decomposition)))
def test_supported_unresolved_matrix(self):
for name,(rectangles,supported) in CASES.items():
geometry=pair(rectangles) # Existing production accepts EVERY fixture.
row=dict(case=name,rectangles=rectangles,production_geometry_accepted=True,
runtime_supported=False,interpolation_accuracy='unqualified_for_new_unions')
if supported:
plan=UnionPlan(geometry); row.update(plan.proof)
self.assertEqual(plan.proof['receiver_quarter_packets'],4*len(plan.receivers))
else:
with self.assertRaises(UnresolvedTopology) as caught: UnionPlan(geometry)
row.update(topology='unresolved',code=caught.exception.code,witness=caught.exception.detail)
MATRIX.append(row)
def test_L_witness_and_reflections(self):
rectangles=CASES['concave_L'][0]
plan=UnionPlan(pair(rectangles))
self.assertIn((5,8*32+9,9*32+10),map(tuple,plan.transit))
directions=set()
for reflect in (False,True):
transformed=[(16-x1,y0,16-x0,y1) if reflect else (x0,y0,x1,y1) for x0,y0,x1,y1 in rectangles]
for _ in range(4):
plan=UnionPlan(pair(transformed)); self.assertEqual(len(plan.transit),2)
for q,source,ghost in plan.transit:
directions.add(q); p=np.array(divmod(source,32)); c=np.array((ref.cpu.CY[q],ref.cpu.CX[q]))
self.assertEqual(ghost,(p+c)[0]*32+(p+c)[1])
self.assertEqual([bool(plan.maps.fine_active[tuple(p+j*c)]) for j in range(3)],[True,False,True])
transformed=[(16-y1,x0,16-y0,x1) for x0,y0,x1,y1 in transformed]
self.assertEqual(directions,{5,6,7,8})
def test_Fig19_two_hop_transport_and_quarter_budget(self):
# Guzik §3.5.4 Fig.19: https://www.osti.gov/servlets/purl/1226215 .
# Isolated tagged transport only: no collision law or union evolution.
for name in ('concave_L','corner_contact','hole'):
p=UnionPlan(pair(CASES[name][0])); q,source,ghost=p.transit.T
stride=ref.cpu.CY[q]*p.nf+ref.cpu.CX[q]; target=ghost+stride
tags=(np.arange(len(q),dtype=np.float32)+1)/256
active=p.maps.fine_active
def run(shifted,mutation=None):
scratch=np.full((9,p.nf,p.nf),np.nan,np.float32)
scratch.reshape(9,-1)[q,source]=tags
def moment(field):
value=field.astype(float)+(ref.cpu.W[:,None,None] if shifted else 0)
return .25*np.where(np.isfinite(field)&active,value,0).sum(axis=(1,2))
def pull(field):
moved=np.stack([np.roll(field[j],(ref.cpu.CY[j],ref.cpu.CX[j]),axis=(0,1)) for j in range(9)])
moved[:,~active]=np.nan
return moved
initial=moment(scratch)
carry=[(int(j),int(h),v.copy()) for j,h,v in zip(q,ghost,scratch.reshape(9,-1)[q,source])]
if mutation=='drop': carry.pop()
if mutation=='duplicate': carry.append(carry[0])
first=pull(scratch) # m0 ghost arrivals are outside the ACTIVE mask.
inventory=np.zeros(9)
for j,h,value in carry: inventory[j]+=.25*(float(value)+(ref.cpu.W[j] if shifted else 0))
np.testing.assert_allclose(moment(first)+inventory,initial,rtol=0,atol=2e-14)
if mutation=='early':
for j,h,value in carry: scratch.reshape(9,-1)[j,h]=value
scratch[:]=np.nan # m1 collision scratch reuse destroys an early injection.
while carry:
j,h,value=carry.pop()
if mutation!='early': scratch.reshape(9,-1)[j,h]=value
final=pull(scratch)
self.assertEqual(carry,[]) # Consumed route inventory, not subtraction of identical sums.
np.testing.assert_allclose(moment(final),initial,rtol=0,atol=2e-14)
arrivals=final.reshape(9,-1)[q,target]
np.testing.assert_array_equal(arrivals.view(np.uint32),tags.view(np.uint32))
for shifted in (False,True):
run(shifted)
for mutation in ('drop','duplicate','early'):
with self.assertRaises(AssertionError): run(shifted,mutation)
for direction,slot,_ in p.transit:
self.assertNotIn((direction,slot),{tuple(row[:2]) for row in p.outgoing[0]})
for change in (lambda b:setattr(b,'transit',b.transit[1:]),
lambda b:setattr(b,'transit',np.vstack((b.transit,b.transit[0]))),
lambda b:b.transit.__setitem__((0,2),b.transit[0,2]+1),
lambda b:b.transit.__setitem__((0,0),1)):
bad=copy.deepcopy(p); change(bad)
with self.assertRaises(ValueError): validate_ownership(bad)
bad=copy.deepcopy(p); direction,slot,_=p.transit[0]
y,x=divmod(slot,p.nf); cy,cx=ref.cpu.CY[direction],ref.cpu.CX[direction]
covered_target=((y+2*cy)//2)*p.n+(x+2*cx)//2
bad.outgoing[0]=np.vstack((bad.outgoing[0],[direction,slot,covered_target]))
with self.assertRaises(ValueError): validate_ownership(bad)
def test_Fig13_first_entry_and_wrong_crossing(self):
p=UnionPlan(pair(CASES['concave_L'][0]))
g=next(g for g in p.groups if g.source==4*16+5 and g.q==8)
self.assertEqual(g.kind,'corner')
self.assertEqual(sorted(point[-1] for point in g.points),[-.25,-.25,-.25,.25])
# For a concave T first entry is min, not the frozen convex max.
damaged=copy.deepcopy(p); wrong=next(x for x in damaged.groups if x.source==g.source and x.q==g.q)
origin=np.array((4,5)); c=np.array((ref.cpu.CY[g.q],ref.cpu.CX[g.q])); points=[]
for child in ((0,0),(0,1),(1,0),(1,1)):
position=origin+(np.array(child)+.5)/2
time=max((origin+ (c>0)-position)/c); offset=position+c*time-(origin+.5+c*.5)
points.append((float(offset[1]),float(offset[0]),float(time-.5)))
wrong.points=tuple(points)
with self.assertRaises(ValueError): validate_ownership(damaged)
def test_all_511_small_masks(self):
counts=dict(masks=0,with_transit=0,transit_paths=0)
for bits in range(1,512):
rectangles=[(4+x,4+y,5+x,5+y) for y in range(3) for x in range(3) if bits & (1<<(3*y+x))]
p=UnionPlan(pair(rectangles)); counts['masks']+=1
counts['with_transit']+=bool(len(p.transit)); counts['transit_paths']+=len(p.transit)
# Independent first-entry check: fine-cell membership before/after
# each quarter crossing, without the plan's plane min/max helper.
for g in p.groups:
c=np.array((ref.cpu.CY[g.q],ref.cpu.CX[g.q])); origin=np.array(divmod(g.source,p.n))
for k,child in enumerate(((0,0),(0,1),(1,0),(1,1))):
start=2*origin+child; hits=[]
for t4 in (1,3):
before=(4*start+2+c*(2*t4-1))//4
after=(4*start+2+c*(2*t4+1))//4
if not p.maps.fine_active[tuple(before)] and p.maps.fine_active[tuple(after)]: hits.append(t4/4)
if hits: self.assertEqual(g.points[k][-1]+.5,hits[0])
self.assertEqual(counts,dict(masks=511,with_transit=384,transit_paths=2048)); ENUMERATION.update(counts)
def test_ordered_provenance_and_packet_mutations_fail(self):
baseline=UnionPlan(pair(CASES['two_separated'][0]))
def reject(change):
bad=copy.deepcopy(baseline); change(bad)
with self.assertRaises((ValueError,KeyError)): validate_ownership(bad)
reject(lambda p:setattr(p.groups[0],'source',p.groups[0].source+1))
reject(lambda p:setattr(p.groups[0],'samples',p.groups[0].samples+1))
reject(lambda p:setattr(p.groups[0],'events',tuple(reversed(p.groups[0].events))))
reject(lambda p:setattr(p.groups[0],'receiver',p.groups[0].receiver+1))
reject(lambda p:p.outgoing.__setitem__(0,p.outgoing[0][1:]))
reject(lambda p:p.outgoing.__setitem__(1,np.vstack((p.outgoing[1],p.outgoing[1][0]))))
reject(lambda p:setattr(p,'receivers',p.receivers[1:]))
def balanced(p):
p.groups[0].weights[:2,:2]+=1e-5*np.array([[1,-1],[-1,1]])
reject(balanced) # Preserves row/column sums, corrupts the actual operator.
def test_coefficients_and_directional_transfer_budget(self):
rng=np.random.default_rng(31)
for name in CASES:
p=UnionPlan(pair(CASES[name][0])); total=np.zeros(9)
receiver={tuple(row):[] for row in p.receivers}; first_leftover=None
for g in p.groups:
samples,a,e,coeff=ref.interpolation(g.kind,g.points)
np.testing.assert_allclose(g.weights,exact_weights(g.kind,g.points),rtol=0,atol=2e-14)
np.testing.assert_allclose(g.weights@np.ones(len(samples)),1,rtol=0,atol=2e-14)
if g.kind=='face': beta=np.array([1.,.03,.02,0.])
else:
beta=np.array([1.,.03,.02,-ref.cpu.CX[g.q]*.03-ref.cpu.CY[g.q]*.02])
self.assertLess(abs((coeff@(a@np.array([1.,.03,.02,0.])))[3]),2e-14)
np.testing.assert_allclose(g.weights@(a@beta),e@beta,rtol=0,atol=2e-14)
values=rng.normal(size=len(samples)); h=g.weights@values
origin=values[0 if g.kind=='corner' else 1]
# Fine incoming plus coarse leftovers must exactly split one
# coarse directional source budget, regardless of sample values.
incoming=sum(h[k] for k,event in enumerate(g.events) if event is not None)
leftover=sum(h[k] for k,event in enumerate(g.events) if event is None)
self.assertLess(abs(.25*(incoming+leftover)-origin),2e-14)
total[g.q]+=.25*incoming-origin
for k,event in enumerate(g.events):
if event is None:
receiver[(g.q,g.receiver)].append(h[k])
if first_leftover is None: first_leftover=(g.q,h[k])
# Tagged collision-free boundary-flux ledger, not a solver trajectory:
# every outgoing fine debit is credited to its actual receiver.
for rows in p.outgoing:
for q,slot,target in rows:
value=float(rng.normal()); total[q]-=.25*value
receiver[(q,target)].append(value)
for (q,target),values in receiver.items():
self.assertEqual(len(values),4); total[q]+=.25*sum(values)
np.testing.assert_allclose(total,0,rtol=0,atol=2e-14)
damaged=total.copy(); q,value=first_leftover; damaged[q]-=.25*value
self.assertGreater(float(abs(damaged).max()),1e-5)
self.assertEqual(validate_ownership(p)['topology'],'supported')
def test_existing_block_addressing_and_sparse_holes(self):
geometry=pair(CASES['two_separated'][0]); p=UnionPlan(geometry)
layouts=(BlockLayout2D.build(16,16,4,4),geometry.fine_layout((4,4)))
for fine,layout in enumerate(layouts):
cells=layout.shape[0]*layout.shape[1]
dense=np.arange(9*cells,dtype=np.float64).reshape(9,*layout.shape)
blocked=layout.to_blocked(dense).ravel()
refs=[]
if not fine:
refs=[(g.q,int(k)) for g in p.groups for k in [g.source,g.receiver,*g.samples]]
else:
refs=[(g.q,slot) for g in p.groups for event in g.events if event is not None for _,slot in [event]]
refs += [(int(q),int(slot)) for rows in p.outgoing for q,slot,_ in rows]
q,k=np.array(refs).T
np.testing.assert_array_equal(blocked[owned_slots(layout,q,k)],dense.reshape(9,-1)[q,k])
holes=np.flatnonzero(~layouts[1].owned)
self.assertGreater(len(holes),0)
with self.assertRaises(UnresolvedTopology): owned_slots(layouts[1],np.array([1]),holes[:1])
def test_deferred_layouts_and_phase_are_explicit(self):
with self.assertRaises(UnresolvedTopology) as caught: UnionPlan(pair([(3,3,8,8)],16,12))
self.assertEqual(caught.exception.code,'requires_level_wide_square_pair')
cfg=LBMConfig(nx=16,ny=16,viscosity=.0192,velocity=0.)
scalar=FixedPatch2D.from_config(cfg,(4,4,8,8))
with self.assertRaises(UnresolvedTopology): UnionPlan(scalar)
self.assertEqual(UnionPlan.phase,'arrival_f'); self.assertFalse(UnionPlan.runtime_supported)
# Restriction and collision do not commute, even at omega=1. This is
# why postcollision G storage cannot be relabeled/inverted into this F contract.
w=ref.cpu.W; cx,cy=ref.cpu.CX,ref.cpu.CY
def equilibrium(u):
cu=cx*u;return w*(1+3*cu+4.5*cu*cu-1.5*u*u)
children=np.array([equilibrium(u) for u in (.03,-.03,.03,-.03)])
self.assertAlmostEqual(float(abs(w-children.mean(axis=0)).max()),.0006,places=14)
if __name__=='__main__':
result=unittest.TextTestRunner(verbosity=2).run(unittest.defaultTestLoader.loadTestsFromTestCase(UnionContract))
print(json.dumps(dict(passed=result.wasSuccessful(),tests=result.testsRun,
scope='host-only topology/provenance/coefficient checks; no runtime or accuracy admission',matrix=MATRIX,
enumeration=ENUMERATION),indent=2))
sys.exit(not result.wasSuccessful())
+222
View File
@@ -0,0 +1,222 @@
"""Steady DFG 2D-1 (Re 20): refined and uniform runs against the official reference intervals.
Not a full benchmark certification. Declared deviations from the official setup:
pressure-NEQ outlet (``neq_extrap``) instead of do-nothing, local Zou-He inlet.
Geometry, inflow profile, initial state, refined layout and observation reuse the
pinned Re100 runner (``run_refined_dfg``) and ``re100_helpers`` unchanged; only the
lattice viscosity is set for Re 20 (nu = U_lattice * D / 20 at the root level).
Units. The helpers use scaled DFG units with mean inflow speed 1, so
Cd = 2 Fx / (rho U^2 D) and Cl = 2 Fy / (rho U^2 D) are scale-free, and
``pressure_probes`` returns dp / (rho U^2). The official p_diff = p(0.15, 0.2) -
p(0.25, 0.2) uses U = 0.2 m/s, rho = 1, so p_diff = dp * 0.04. Both are reported;
only p_diff is compared with the official interval. Forces use the existing sign
convention: F is the force of the fluid on the cylinder, i.e. the refined raw
exchange impulse (window ledger, ``total.impulse``) or the uniform ``read_force``,
with x along the inflow and y up from the bottom wall. Cd must be positive, and the
official Cl is positive (centre 0.20 below the centreline 0.205), so a flipped sign
shows up as Cl outside its interval.
Sampling. One sample every SAMPLE_TSTAR (t* = U t / D; 0.25 s), taken at the end of
a completed root step with all levels synchronized; the step index is recorded. Cd
and Cl are means over the sample interval (window exchange ledger refined, per-batch
forces uniform), which filters acoustic and step-parity oscillation; p_diff is the
end-of-interval value at the exact surface points.
Steady rule (our engineering choice, frozen before any run; not official). Over the
trailing WINDOW_TSTAR (t* 50..60 inclusive, 21 samples), for each of Cd, Cl and
p_diff: range (max - min) <= 10 % and |least-squares slope * window| <= 2 % of the
width of its official interval. Absolute limits, so the small Cl is never a divisor;
the slope term bounds slow monotone drift that the range alone would pass. If the
rule fails at TSTAR_MAX the run reports "not steady" and gives no interval verdict;
limits are never relaxed after a run. The verdict uses the window mean, and the
distance of each mean to its nearest interval edge is reported (negative outside).
"""
import argparse
import json
import math
import os
from pathlib import Path
import sys
import time
from tempfile import TemporaryDirectory
import numpy as np
HERE = Path(__file__).resolve().parent
sys.path.insert(0, str(HERE))
import run_refined_dfg as rr # noqa: E402
RE = 20.0
U_PHYS = 0.2 # m/s mean inflow; rho = 1
TSTAR_MAX = 60.0 # 30 s physical
SAMPLE_TSTAR = 0.5 # 0.25 s
WINDOW_TSTAR = 10.0 # trailing 5 s, 21 samples
# Schaefer & Turek (1996), 2D-1 lower/upper bounds.
BANDS = dict(cd=(5.57, 5.59), cl=(0.0104, 0.0110), p_diff=(0.1172, 0.1176))
STEADY_RANGE = {k: (hi - lo) / 10 for k, (lo, hi) in BANDS.items()}
STEADY_SLOPE = {k: (hi - lo) / 50 for k, (lo, hi) in BANDS.items()}
DEVIATIONS = ("pressure-NEQ outlet (neq_extrap), not do-nothing", "local Zou-He inlet")
_re100_config = rr.config
def config(h, diameter, collision="SRT", jet_scenario="none"):
"""The pinned Re100 configuration with the lattice viscosity set for Re 20."""
if jet_scenario != "none":
raise ValueError("DFG 2D-1 runs have no Jets")
cfg, body, p = _re100_config(h, diameter, collision, jet_scenario)
nu = p["mean_speed"] * p["diameter"] / RE
cfg["physics"]["viscosity"] = nu
return cfg, body, dict(p, viscosity=nu, re=RE)
def lattice_parameters(diameter, speed=rr.SPEED):
nu = speed * diameter / RE
return dict(viscosity=nu, tau=0.5 + 3 * nu, steps=math.ceil(TSTAR_MAX * diameter / speed),
interval=round(SAMPLE_TSTAR * diameter / speed))
def sample(impulse, n, diameter, dp):
den = rr.SPEED**2 * diameter / 2
return dict(cd=float(impulse[0] / n / den), cl=float(impulse[1] / n / den),
dp_scaled=float(dp), p_diff=float(dp) * U_PHYS**2)
def summarize(rows):
"""Steady rule over the trailing window, then the interval verdict (or none)."""
if not rows or rows[-1]["tstar"] < TSTAR_MAX - 1e-9:
return dict(status="INCOMPLETE", steady=False, verdict=None)
window = [r for r in rows if r["tstar"] >= TSTAR_MAX - WINDOW_TSTAR - 1e-9]
t = np.array([r["tstar"] for r in window])
ranges = {k: max(r[k] for r in window) - min(r[k] for r in window) for k in BANDS}
drifts = {k: abs(np.polyfit(t, [r[k] for r in window], 1)[0]) * WINDOW_TSTAR for k in BANDS}
steady = all(ranges[k] <= STEADY_RANGE[k] and drifts[k] <= STEADY_SLOPE[k] for k in BANDS)
final = {k: float(np.mean([r[k] for r in window])) for k in BANDS}
edge = {k: min(final[k] - BANDS[k][0], BANDS[k][1] - final[k]) for k in BANDS}
result = dict(window_samples=len(window), ranges=ranges, drifts=drifts,
range_limits=STEADY_RANGE, slope_limits=STEADY_SLOPE, steady=steady,
window_mean=final, edge_distance=edge, bands=BANDS,
deviations=DEVIATIONS, cd_positive=final["cd"] > 0)
if not steady:
return dict(result, status="NOT_STEADY", verdict=None)
inside = {k: BANDS[k][0] <= final[k] <= BANDS[k][1] for k in BANDS}
return dict(result, status="WITHIN_INTERVALS" if all(inside.values()) else "OUTSIDE_INTERVALS",
verdict=inside)
def healthy(row):
return row["max_mach"] <= 0.2 and row["rho_min"] >= 0.5 and row["rho_max"] <= 1.5
def run_case(a, h, case):
from contextlib import ExitStack
from CelerisLab.cuda.context import CudaContext
from CelerisLab.lbm.descriptors import FLUID
from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
from CelerisLab.simulation import Simulation
refined = case == "refined"
cfgdict, bodydict, p = config(h, 40 if refined else 80, a.collision)
lp = lattice_parameters(p["diameter"])
rows = []
with ExitStack() as stack:
if refined:
cfg, pair, body, host = rr.host_geometry(a.source, h, a.collision)
context = stack.enter_context(CudaContext(0))
backend = stack.enter_context(FixedPatchStepper(
cfg, context=context, coarse_boundary="channel", refinements=[rr.PLACEMENTS["wide"]],
level_blocks=[rr.BASE_BLOCK, rr.FINE_BLOCK], level_objects=[(), (body,)],
observe_raw_exchange=True, observe_window_exchange=True))
from CelerisLab.lbm.channel import channel_masks
from CelerisLab.lbm.refinement import ACTIVE
from CelerisLab.lbm.descriptors import SOLID
masks = [channel_masks(pair.coarse_shape)[0] & ~pair.covered,
(pair.fine_kind == ACTIVE)
& ((host.flags.reshape(pair.fine_shape) & SOLID) == 0)]
backend.initialize(rr.initial_state(pair.coarse_shape, (0.0, 0.0), 1.0, root=True),
rr.initial_state(pair.fine_shape, pair.fine_origin, 0.5))
probe_p = dict(p, center=[(80.5 - pair.fine_origin[0]) / 0.5 - 0.5,
(81.0 - pair.fine_origin[1]) / 0.5 - 0.5], radius=40.0)
else:
tmp = Path(stack.enter_context(TemporaryDirectory()))
(tmp / "lbm.json").write_text(json.dumps(cfgdict))
(tmp / "body.json").write_text(json.dumps(bodydict))
sim = stack.enter_context(Simulation(str(tmp / "lbm.json"), str(tmp / "body.json"),
device_id=0))
sim.initialize()
probe_p = p
fluid = (sim.field.flag.reshape(p["ny"], p["nx"]) & FLUID) != 0
begin = 0
while begin < lp["steps"]:
rr.check_deadline(a.deadline)
n = min(lp["interval"], lp["steps"] - begin)
if refined:
impulse = rr.advance_refined_interval(backend, n, a.deadline, "window")
fields = [rr.macros(g) for g in backend.download()]
rho, ux, uy = fields[1]
fluid = masks[1]
vals = [tuple(v[m] for v in f) for m, f in zip(masks, fields)]
else:
impulse, done = np.zeros(2), 0
while done < n:
batch = min(100, n - done)
sim.run(batch)
impulse += sim.read_force(0).astype(np.float64) * batch
done += batch
m = sim.get_macroscopic()
rho, ux, uy = [np.asarray(m[k], np.float64).reshape(p["ny"], p["nx"])
for k in ("rho", "ux", "uy")]
vals = [(rho[fluid], ux[fluid], uy[fluid])]
begin += n
row = dict(step=begin, tstar=begin * rr.SPEED / p["diameter"],
**sample(impulse, n, p["diameter"],
h.pressure_probes(rho, fluid, probe_p)["dp"]),
rho_min=float(min(v[0].min() for v in vals)),
rho_max=float(max(v[0].max() for v in vals)),
max_mach=float(max(np.sqrt(3 * (v[1]**2 + v[2]**2)).max() for v in vals)))
rr.ensure_finite(row)
rows.append(row)
if not healthy(row):
break
summary = summarize(rows) if healthy(rows[-1]) else dict(status="UNHEALTHY", steady=False,
verdict=None)
return dict(case=case, collision=a.collision, lattice=lp, rows=rows, **summary)
def plan(collision="SRT"):
return dict(re=RE, collision=collision, tstar_max=TSTAR_MAX, sample_tstar=SAMPLE_TSTAR,
window_tstar=WINDOW_TSTAR, bands=BANDS, range_limits=STEADY_RANGE, slope_limits=STEADY_SLOPE,
deviations=DEVIATIONS, pressure_scale=U_PHYS**2,
refined_root=lattice_parameters(40), refined_fine_tau=0.5 + 3 * 2 * rr.SPEED * 40 / RE,
uniform=lattice_parameters(80),
label="compared against the official reference bands (non-canonical neq_extrap outlet, zou_he_local inlet); not a full benchmark certification")
def main():
parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
parser.add_argument("--case", choices=["refined", "uniform", "both"], default="refined")
parser.add_argument("--collision", choices=["SRT", "MRT"], default="SRT")
parser.add_argument("--source", type=Path, default=rr.DEFAULT_SOURCE)
parser.add_argument("--output", type=Path, required=True)
parser.add_argument("--plan", action="store_true", help="Write the frozen plan; no CUDA")
parser.add_argument("--max-wall-seconds", type=float)
a = parser.parse_args()
a.source = a.source.resolve()
a.output.mkdir(parents=True, exist_ok=False)
(a.output / "plan.json").write_text(json.dumps(plan(a.collision), indent=2, allow_nan=False))
if a.plan:
return
if not a.max_wall_seconds or a.max_wall_seconds <= 0 or not os.environ.get("CUDA_VISIBLE_DEVICES"):
raise SystemExit("GPU run needs --max-wall-seconds > 0 and explicit CUDA_VISIBLE_DEVICES")
h, _ = rr.helpers(a.source)
rr.config = config # host_geometry builds its root configuration through this name
a.deadline = time.monotonic() + a.max_wall_seconds
cases = ["refined", "uniform"] if a.case == "both" else [a.case]
results = [run_case(a, h, case) for case in cases]
(a.output / "result.json").write_text(json.dumps(results, indent=2, allow_nan=False))
if __name__ == "__main__":
main()
+23 -6
View File
@@ -74,7 +74,25 @@ def cv(g, fluid, origin, rectangle, nu, h=0.5):
Cauchy stress from centred velocity gradients, NOT postcollision non-equilibrium.
Rectangle faces lie on cell edges; fluid mask excludes the staircase cylinder.
"""
rho, mom, vel = moments(g)
return _cv_quantities(*moments(g), fluid, origin, rectangle, nu, h)
def cv_from_macros(rho, ux, uy, fluid, origin, rectangle, nu, h=0.5):
"""Same CV calculation from public macros, in one common length/time frame.
``origin`` is the lower cell edge, ``h`` the cell width, and ``nu`` uses
that frame. Returns [mass, Px, Py] inventory and outward total flux.
Crop fields/mask together and translate origin before calling if desired.
No boundary-exchange observation enters this independent estimator.
"""
rho = np.asarray(rho, np.float64)
if rho.ndim != 2 or any(np.shape(v) != rho.shape for v in (ux, uy, fluid)):
raise ValueError("CV macros and fluid mask must have matching 2D shapes")
vel = np.asarray([ux, uy], np.float64)
return _cv_quantities(rho, rho[None] * vel, vel, fluid, origin, rectangle, nu, h)
def _cv_quantities(rho, mom, vel, fluid, origin, rectangle, nu, h):
x0, y0, x1, y1 = np.rint((np.array(rectangle) - np.tile(origin, 2)) / h).astype(int)
np.testing.assert_allclose(
np.array([x0, y0, x1, y1]) * h + np.tile(origin, 2), rectangle, atol=1e-12
@@ -261,12 +279,11 @@ def run_case(c, ctx, output, provenance, continuation=False):
PeriodicBlockStepper(fine_cfg, layout, context=ctx, objects=[fobj]) as uniform,
FixedPatchStepper(
cfg,
c["bounds"],
context=ctx,
base_block=(8, 8),
fine_block=(8, 8),
fine_objects=[obj],
jets=jets,
refinements=[c["bounds"]],
level_blocks=[(8, 8), (8, 8)],
level_objects=[(), (obj,)],
level_jets=[(), tuple(jets)],
observe_raw_exchange=True,
) as amr,
):
+278 -41
View File
@@ -17,8 +17,109 @@ HERE = Path(__file__).resolve().parent
DEFAULT_SOURCE = HERE.parents[1]
BOUNDS = (40, 24, 320, 140)
BASE_BLOCK = (2, 881) # Exact 166 x 881 domain; no geometric padding.
FINE_BLOCK = (8, 8) # 240 x 568 including four fine halo cells.
FINE_BLOCK = (8, 8) # Wide 240 x 568 or compact 168 x 168, including fine halos.
SPEED = 0.01
JET_PEAK = 0.001
JET_WINDOWS = [(t, t + 10) for t in range(250, 300, 10)]
CV_CONTOURS = np.array([(48., 44., 160., 120.), (44., 36., 180., 128.)])
PLACEMENTS = {"wide": BOUNDS, "compact": (48, 48, 128, 128)}
COMPACT_CV_CONTOURS = np.array([(52., 52., 112., 112.), (50., 50., 120., 120.)])
def selected_cases(selection="both", uniform_diameter=80):
return [(case, diameter) for case, diameter in (("uniform", uniform_diameter), ("refined", 40))
if selection in ("both", case)]
def uniform_origin(diameter):
h = 40 / diameter
return (.5 - .5*h, 1 - h)
def cv_contours(refined, diameter, placement="wide"):
contours = CV_CONTOURS if placement == "wide" else COMPACT_CV_CONTOURS
return contours if refined else contours + [20/diameter, 0., 20/diameter, 0.]
def cv_selected(step, diameter, mode):
return mode == "pilot" or round(290 * diameter / SPEED) <= step <= round(300 * diameter / SPEED)
def cv_snapshot(rho, ux, uy, fluid, origin, refined, begin, n, diameter, impulse, placement="wide"):
"""Cropped public macros only; all inventories, fluxes and impulses use root units."""
from run_jet_circle_cv import cv_from_macros
rectangles = cv_contours(refined, diameter, placement)
h_cell = .5 if refined else 40 / diameter
origin = np.asarray(origin, dtype=float)
x0, y0, x1, y1 = np.rint((rectangles[-1] - np.tile(origin, 2)) / h_cell).astype(int)
selection = np.s_[y0-2:y1+2, x0-2:x1+2]
cropped_origin = origin + h_cell * np.array([x0-2, y0-2])
fields = [v[selection] for v in (rho, ux, uy, fluid)]
values = [cv_from_macros(*fields, cropped_origin, rect, .004, h=h_cell)
for rect in rectangles]
h_native = 1.0 if refined else 40 / diameter
return dict(step=begin+n, tstar=(begin+n)*SPEED/diameter,
time_root=(begin+n)*h_native, interval_start_root=begin*h_native,
interval_dt_root=n*h_native,
interval_impulse_root=(np.asarray(impulse)*h_native**2).tolist(),
inventory=[inventory.tolist() for inventory, _ in values],
outward_flux=[flux.tolist() for _, flux in values])
def public_jets(center, radius, scenario):
"""Same physical apertures; caller supplies its public geometry frame."""
if scenario == "none":
return ()
from CelerisLab.body.jets import Jet, Sector, Radial
peak = 0.0 if scenario == "zero" else JET_PEAK
return tuple(
Jet(Sector(center, angle, math.pi / 12, radius * 1.005),
Radial(center, inward=False), "parabolic", amplitude)
for angle, amplitude in ((math.pi / 2, peak), (3 * math.pi / 2, -peak))
)
def jet_interval(handle, scenario, begin, n, diameter):
"""Apply a reversal only at a completed interval boundary, before advancing."""
if scenario != "none":
boundaries = [round(t * diameter / SPEED) for t in (250, 260, 270, 280, 290, 300, 305)]
n = min([n] + [step - begin for step in boundaries if step > begin])
if scenario != "reverse":
return n, None
switch = round(300 * diameter / SPEED)
if begin < switch:
return min(n, switch - begin), None
if begin == switch:
handle.set_jet_amplitude(0, -JET_PEAK)
handle.set_jet_amplitude(1, JET_PEAK)
return n, dict(step=begin, tstar=300.0, amplitudes=[-JET_PEAK, JET_PEAK])
return n, None
def jet_diagnostics(rows, scenario):
"""Raw interval-weighted diagnostics only; no driven-flow qualification gate."""
windows = JET_WINDOWS + ([(300, 305)] if scenario == "reverse" else [])
result = []
for start, end in windows:
selected = [r for r in rows if start <= r["tstar_force"] < end]
if not selected:
continue
if any(2 * r["tstar_force"] - r["tstar"] < start - 1e-9
or r["tstar"] > end + 1e-9 for r in selected):
raise ValueError("Jet diagnostic interval crosses a window boundary")
weights = np.array([2 * (r["tstar"] - r["tstar_force"]) for r in selected])
record = dict(start_tstar=start, end_tstar=end, samples=len(selected),
covered_tstar=float(weights.sum()),
complete=bool(np.isclose(weights.sum(), end - start, rtol=0, atol=1e-9)))
for key in ("cd", "cl"):
values = np.array([r[key] for r in selected])
record[key] = dict(mean=float(np.average(values, weights=weights)),
min=float(values.min()), max=float(values.max()),
rms=float(np.sqrt(np.average(values**2, weights=weights))))
result.append(record)
return result
def helpers(source):
@@ -39,26 +140,34 @@ def helpers(source):
return h, periodic
def config(h, diameter, collision="SRT"):
def config(h, diameter, collision="SRT", jet_scenario="none"):
cfg, body, p = h.make_config(diameter, SPEED, collision, "neq_extrap", "zou_he_local")
cfg["method"]["outlet"]["srt_neq_damp"] = 0.5
if jet_scenario != "none":
if collision != "MRT":
raise ValueError("Public Jet scenarios require MRT")
cfg["method"]["ddf_shifting"] = False
return cfg, body, p
def plan(h, collision="SRT", observation_mode="last_base_step"):
_, _, c = config(h, 40, collision)
_, _, f = config(h, 80, collision)
x0, y0, x1, y1 = BOUNDS
def plan(h, collision="SRT", observation_mode="last_base_step", jet_scenario="none", uniform_diameter=80, placement="wide"):
_, _, c = config(h, 40, collision, jet_scenario)
_, _, f = config(h, uniform_diameter, collision, jet_scenario)
bounds = PLACEMENTS[placement]
x0, y0, x1, y1 = bounds
fine_active = 4 * (x1 - x0) * (y1 - y0)
coarse_uncovered = c["nx"] * c["ny"] - fine_active // 4
return dict(
status="prepared_not_run",
collision=collision,
jet_scenario=jet_scenario,
ddf_shifting=jet_scenario == "none",
observation_mode=observation_mode,
root_gpu_gates_required=True,
root=c,
uniform=f,
bounds_root_edge=list(BOUNDS),
bounds_root_edge=list(bounds),
fine_origin_root_edge=[x0 - 2, y0 - 2],
physical_patch_m=[
(x0 - 0.5) * c["dx"],
(y0 - 1) * c["dx"],
@@ -78,19 +187,31 @@ def plan(h, collision="SRT", observation_mode="last_base_step"):
physical_viscosity_m2_s=0.001,
finest_dx_m=f["dx"],
finest_dt_s=f["dt"],
refined_finest_dx_m=c["dx"]/2,
refined_finest_dt_s=c["dt"]/2,
approximate_leaf_cell_ratio=(coarse_uncovered + fine_active)
/ (f["nx"] * f["ny"]),
approximate_collision_work_ratio=(coarse_uncovered + 2 * fine_active)
/ (2 * f["nx"] * f["ny"]),
/ ((uniform_diameter/40) * f["nx"] * f["ny"]),
cost_caveat="Geometry-only estimates include ghosts/solids; exclude block halos, transfers, observation and launch overhead. Not measured speedup.",
sampling_offset="For origin (38,22), fine physical x=(j+75.5)*dx80 versus uniform i*dx80: half-fine-cell x offset. Fine physical y=(k+42.5)*dx80 equals uniform (l-.5)*dx80 at l=k+43: y samples align. Body, wall and source planes coincide.",
sampling_offset="Uniform nodes map to root edges X=.5+i*(40/D), Y=1+(j-.5)*(40/D). Refined centers are fine_origin_root_edge+(index+.5)*.5. Body, wall and source planes coincide; compare observables, not pointwise arrays.",
outlet=(
"SRT pressure NEQ, all nine fneq damped by .5, no backflow clamp; noncanonical DFG outlet"
if collision == "SRT" else
"MRT pressure NEQ, unknowns q2/6/8 extrapolated; no backflow clamp; noncanonical DFG outlet"
),
modes={"pilot_tstar": 5.0, "full_tstar": 300.0},
modes={"pilot_tstar": 5.0, "full_tstar": 305.0 if jet_scenario == "reverse" else 300.0},
observation_dense_tstar=0.02,
**(dict(jets=dict(
uniform_origin_node=f["center"], refined_origin_root_edge=[80.5, 81.0],
angles_rad=[math.pi / 2, 3 * math.pi / 2], half_width_rad=math.pi / 12,
radial_extent_over_radius=[0.0, 1.005],
field="Radial(outward)", profile="parabolic", condition="velocity",
initial_amplitudes=[0.0, 0.0] if jet_scenario == "zero" else [JET_PEAK, -JET_PEAK],
reversal_tstar=300.0 if jet_scenario == "reverse" else None,
diagnostic_windows_tstar=JET_WINDOWS + ([(300, 305)] if jet_scenario == "reverse" else []),
transfer="constant", driven_qualification="not assessed",
)) if jet_scenario != "none" else {}),
)
@@ -126,7 +247,7 @@ def initial_state(shape, origin, spacing, height=164.0, speed=SPEED, root=False)
return w * (1 + 3 * cu + 4.5 * cu * cu - 1.5 * velocity * velocity)
def host_geometry(source, h, collision="SRT"):
def host_geometry(source, h, collision="SRT", jet_scenario="none", placement="wide"):
"""Production donor/transfer and complete cut-link checks, without CUDA."""
from CelerisLab.config import load_lbm_config
from CelerisLab.lbm.refinement import FixedPatch2D, prepare_fine_boundary
@@ -139,12 +260,12 @@ def host_geometry(source, h, collision="SRT"):
from CelerisLab.body.geometry.circle import CircleGeometry
from CelerisLab.body.objects import SimObject
cfgdict, _, _ = config(h, 40, collision)
cfgdict, _, _ = config(h, 40, collision, jet_scenario)
with TemporaryDirectory() as tmp:
p = Path(tmp) / "cfg.json"
p.write_text(json.dumps(cfgdict))
cfg = load_lbm_config(str(p))
pair = FixedPatch2D.from_config(cfg, BOUNDS)
pair = FixedPatch2D.from_config(cfg, PLACEMENTS[placement])
layout = BlockLayout2D.build(cfg.ny, cfg.nx, *BASE_BLOCK)
validate_channel_config(cfg, [BASE_BLOCK, FINE_BLOCK])
targets = blocked_base_tables(pair, layout, np.argsort(pair.coalesce_coarse))[1]
@@ -153,18 +274,41 @@ def host_geometry(source, h, collision="SRT"):
body = SimObject(
0, geometry=CircleGeometry(80.5, 81.0, 20.0), center=(80.5, 81.0), radius=20.0
)
host = prepare_fine_boundary(cfg, pair, (body,), _shifted_blocked=True)
host = prepare_fine_boundary(
cfg, pair, (body,), jets=public_jets((80.5, 81.0), 20.0, jet_scenario),
_shifted_blocked=jet_scenario == "none",
)
return cfg, pair, body, host
def verify_source(source, collision="SRT", observation_mode="last_base_step"):
def verify_source(source, collision="SRT", observation_mode="last_base_step", jet_scenario="none", observe_cv=False):
if collision not in ("SRT", "MRT"):
raise ValueError("Matched collision must be SRT or MRT")
if observation_mode not in ("last_base_step", "window"):
raise ValueError("Unknown refined observation mode")
if observe_cv and jet_scenario == "none":
raise ValueError("--observe-cv requires an explicit public Jet scenario")
name = ("source_manifest_window.json" if observation_mode == "window" else
"source_manifest.json" if collision == "SRT" else "source_manifest_mrt.json")
expected = json.loads((HERE / "data/refined_dfg" / name).read_text())
if jet_scenario != "none":
if collision != "MRT" or observation_mode != "window":
raise ValueError("Public Jet scenarios require MRT and --exchange-window")
import subprocess
sys.path.insert(0, str(HERE))
from source_provenance import checkout_provenance
paths = set(expected["sha256"])
if observe_cv:
paths.add("tests/validation/run_jet_circle_cv.py")
paths.update(subprocess.check_output(
["git", "-C", str(source), "ls-files", "src"], text=True).splitlines())
return dict(
source_capture="current checkout, not historical DFG qualification",
**checkout_provenance(source), observation_mode=observation_mode,
sha256={name: hashlib.sha256((source / name).read_bytes()).hexdigest()
for name in sorted(paths)},
)
for name, digest in expected["sha256"].items():
if hashlib.sha256((source / name).read_bytes()).hexdigest() != digest:
raise RuntimeError("Source mismatch: " + name)
@@ -219,29 +363,32 @@ def run_case(a, h, periodic, case):
from contextlib import ExitStack
refined = case == "refined"
cfgdict, bodydict, p = config(h, 40 if refined else 80, a.collision)
cap = 5.0 if a.mode == "pilot" else 300.0
cfgdict, bodydict, p = config(h, 40 if refined else a.uniform_diameter, a.collision, a.jet_scenario)
cap = 5.0 if a.mode == "pilot" else (305.0 if a.jet_scenario == "reverse" else 300.0)
max_steps = math.ceil(cap * p["diameter"] / SPEED)
rows = []
healthy = True
step_seconds = 0.0
cv_seconds, cv_samples = 0.0, 0
amplitude_changes = []
started = time.monotonic()
check_deadline(a.deadline)
dest = a.output / case
dest.mkdir()
with ExitStack() as stack:
cv_out = stack.enter_context((dest / "cv_history.jsonl").open("w")) if a.observe_cv else None
if refined:
cfg, pair, body, host = host_geometry(a.source, h, a.collision)
cfg, pair, body, host = host_geometry(a.source, h, a.collision, a.jet_scenario, a.placement)
context = stack.enter_context(CudaContext(0))
backend = stack.enter_context(
FixedPatchStepper(
cfg,
BOUNDS,
context=context,
coarse_boundary="channel",
base_block=BASE_BLOCK,
fine_block=FINE_BLOCK,
fine_objects=(body,),
refinements=[PLACEMENTS[a.placement]],
level_blocks=[BASE_BLOCK, FINE_BLOCK],
level_objects=[(), (body,)],
level_jets=[(), public_jets((80.5, 81.0), 20.0, a.jet_scenario)],
observe_raw_exchange=True,
**({"observe_window_exchange": True} if a.observation_mode == "window" else {}),
)
@@ -274,6 +421,9 @@ def run_case(a, h, periodic, case):
sim = stack.enter_context(
Simulation(str(tmp / "lbm.json"), str(tmp / "body.json"), device_id=0)
)
for index, jet in enumerate(public_jets(p["center"], p["radius"], a.jet_scenario)):
if sim.add_jet(jet) != index:
raise RuntimeError("Unexpected public Jet registration index")
sim.initialize()
probe_p = p
fluid = (sim.field.flag.reshape(p["ny"], p["nx"]) & FLUID) != 0
@@ -290,6 +440,10 @@ def run_case(a, h, periodic, case):
else 0.5
)
n = min(max(1, round(width * p["diameter"] / SPEED)), max_steps - begin)
n, change = jet_interval(backend if refined else sim, a.jet_scenario,
begin, n, p["diameter"])
if change is not None:
amplitude_changes.append(change)
impulse = np.zeros(2)
tick = time.monotonic()
if refined:
@@ -359,6 +513,19 @@ def run_case(a, h, periodic, case):
/ SPEED,
**h.pressure_probes(rho, fluid, probe_p),
)
if a.jet_scenario != "none":
row.update(step_start=begin, tstar_start=begin * SPEED / p["diameter"],
interval_steps=n, impulse_x=float(impulse[0]),
impulse_y=float(impulse[1]))
if a.observe_cv and cv_selected(begin+n, p["diameter"], a.mode):
tick = time.monotonic()
record = cv_snapshot(rho, ux, uy, fluid,
pair.fine_origin if refined else uniform_origin(p["diameter"]),
refined, begin, n, p["diameter"], impulse, a.placement)
cv_out.write(json.dumps(record, allow_nan=False) + "\n")
cv_out.flush()
cv_samples += 1
cv_seconds += time.monotonic() - tick
check_deadline(a.deadline)
ensure_finite(row)
rows.append(row)
@@ -402,14 +569,24 @@ def run_case(a, h, periodic, case):
steps=begin,
startup_seconds=startup,
step_seconds=step_seconds,
observation_and_overhead_seconds=time.monotonic() - started - startup - step_seconds,
wall_seconds=time.monotonic() - started,
force="raw stationary-body link momentum reaction, per-unit-depth; average over entire observation interval; normalized in each base lattice",
mass_units="rho_reference * m^2 per unit depth",
flux_units="rho_reference * m^2/s per unit depth",
pressure="postcollision end-sample; physical pressure difference / (rho_reference * 1 m/s squared)",
suite_validated=False,
**periodic.assess(rows),
**(periodic.assess(rows) if a.jet_scenario in ("none", "zero") else
dict(periodic=False, checks={}, cycles=[])),
)
if a.jet_scenario != "none":
result.update(jet_diagnostic_windows=jet_diagnostics(rows, a.jet_scenario),
amplitude_changes=amplitude_changes,
pressure_classification=("DFG reference verdict retained, including pressure"
if a.jet_scenario == "zero" else "diagnostic only; no official DFG reference gate"))
if a.observe_cv:
result.update(cv_observation_seconds=cv_seconds, cv_samples=cv_samples,
cv_qualification="not assessed; scalar observations only")
if not healthy:
result["periodic"] = False
reference = json.loads(
@@ -425,7 +602,8 @@ def run_case(a, h, periodic, case):
else (
"pilot_complete"
if a.mode == "pilot"
else ("periodic" if result["periodic"] else "incomplete_periodicity")
else ("driven_diagnostics_complete" if a.jet_scenario in ("fixed", "reverse") else
"periodic" if result["periodic"] else "incomplete_periodicity")
)
)
(dest / "summary.json").write_text(json.dumps(result, indent=2, allow_nan=False))
@@ -464,27 +642,39 @@ def check_deadline(deadline):
)
def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_step"):
def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_step", jet_scenario="none", observe_cv=False,
case_selection="both", uniform_diameter=80, placement="wide"):
if path is None:
raise ValueError(
"Full comparison requires --pilot-results from a completed matched pilot"
)
previous = read_finite_json(path / "plan.json")
options = dict(case_selection=(case_selection, "both"), uniform_diameter=(uniform_diameter, 80), placement=(placement, "wide"))
if any(previous.get(k, default) != expected for k, (expected, default) in options.items()):
raise ValueError("Pilot case, resolution or placement differs")
if previous.get("observe_cv", False) != observe_cv:
raise ValueError("Pilot CV observation mode differs")
if previous.get("jet_scenario", "none") != jet_scenario:
raise ValueError("Pilot Jet scenario differs")
if previous.get("observation_mode") != observation_mode:
raise ValueError("Pilot observation mode differs")
if previous.get("collision") != collision:
raise ValueError("Pilot collision differs")
if previous["source_manifest"] != manifest or previous["bounds_root_edge"] != list(
BOUNDS
PLACEMENTS[placement]
):
raise ValueError("Pilot source or frozen geometry differs")
if previous.get("runner_sha256") != runner_hash():
raise ValueError("Pilot runner differs")
calibrated_seconds = 0.0
for case, diameter in (("uniform", 80), ("refined", 40)):
for case, diameter in selected_cases(case_selection, uniform_diameter):
summary = read_finite_json(path / case / "summary.json")
if (
summary.get("observation_mode") != observation_mode
any(summary.get(k, default) != expected for k, (expected, default) in options.items())
or summary.get("observe_cv", False) != observe_cv
or (observe_cv and summary.get("cv_samples") != 250)
or summary.get("jet_scenario", "none") != jet_scenario
or summary.get("observation_mode") != observation_mode
or summary.get("collision") != collision
or summary.get("case") != case
or summary.get("mode") != "pilot"
@@ -537,7 +727,10 @@ def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_st
raise ValueError("Unhealthy pilot observations")
ready = read_finite_json(path / case / "ready.json")
if (
ready.get("observation_mode") != observation_mode
any(ready.get(k, default) != expected for k, (expected, default) in options.items())
or ready.get("observe_cv", False) != observe_cv
or ready.get("jet_scenario", "none") != jet_scenario
or ready.get("observation_mode") != observation_mode
or ready.get("collision") != collision
or ready.get("case") != case
or ready.get("mode") != "pilot"
@@ -555,9 +748,9 @@ def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_st
or not 0 < stepping <= wall
):
raise ValueError("Invalid pilot calibration timings")
# Full physical duration is 60 times pilot; dense pilot sampling makes
# Full duration is 60 (or 61 with reversal) times pilot; dense sampling makes
# this conservative for the sparser early full observations. Not a guarantee.
calibrated_seconds += startup + 60 * (wall - startup)
calibrated_seconds += startup + (61 if jet_scenario == "reverse" else 60) * (wall - startup)
return 3 * calibrated_seconds
@@ -566,6 +759,13 @@ def main():
parser.add_argument("--exchange-window", action="store_true",
help="Opt in to refined window-ledger observations on the pinned candidate")
parser.add_argument("--collision", choices=["SRT", "MRT"], default="SRT")
parser.add_argument("--case", choices=["both", "uniform", "refined"], default="both")
parser.add_argument("--uniform-diameter", type=int, choices=[80, 160], default=80)
parser.add_argument("--placement", choices=list(PLACEMENTS), default="wide")
parser.add_argument("--jet-scenario", choices=["none", "zero", "fixed", "reverse"],
default="none", help="Opt in to public unshifted MRT Jets; reverse switches at t*=300 and ends at 305")
parser.add_argument("--observe-cv", action="store_true",
help="Record independent cropped-macro CV samples during pilot or full t*=290..300")
parser.add_argument("--source", type=Path, default=DEFAULT_SOURCE)
parser.add_argument("--output", type=Path, required=True)
parser.add_argument("--mode", choices=["plan", "pilot", "full"], default="plan")
@@ -577,15 +777,26 @@ def main():
help="Required explicit campaign wall-time ceiling for GPU execution",
)
a = parser.parse_args()
if a.uniform_diameter == 160 and a.case != "uniform":
raise ValueError("D160 requires --case uniform; no matched-resolution claim")
if a.placement == "compact" and a.case != "refined":
raise ValueError("Compact placement requires --case refined")
if (a.uniform_diameter != 80 or a.placement != "wide") and a.jet_scenario == "none":
raise ValueError("Resolution/placement variants require an explicit public Jet scenario")
a.source = a.source.resolve()
a.observation_mode = "window" if a.exchange_window else "last_base_step"
manifest = verify_source(a.source, a.collision, a.observation_mode)
manifest = verify_source(a.source, a.collision, a.observation_mode, a.jet_scenario, a.observe_cv)
h, periodic = helpers(a.source)
from source_provenance import checkout_provenance
a.provenance = checkout_provenance(a.source)
a.provenance.update(jet_scenario=a.jet_scenario, ddf_shifting=a.jet_scenario == "none")
a.provenance.update(case_selection=a.case, uniform_diameter=a.uniform_diameter, placement=a.placement)
if a.observe_cv:
a.provenance["observe_cv"] = True
calibration = (
verify_pilot(a.pilot_results, manifest, a.collision, a.observation_mode)
verify_pilot(a.pilot_results, manifest, a.collision, a.observation_mode, a.jet_scenario, a.observe_cv,
a.case, a.uniform_diameter, a.placement)
if a.mode == "full" else None
)
if a.mode != "plan" and (
@@ -602,17 +813,31 @@ def main():
if a.output.exists() and any(a.output.iterdir()):
raise ValueError("Output must be empty/new")
a.output.mkdir(parents=True, exist_ok=True)
specification = plan(h, a.collision, a.observation_mode)
specification = plan(h, a.collision, a.observation_mode, a.jet_scenario, a.uniform_diameter, a.placement)
specification.update(
source_manifest=manifest,
**a.provenance,
gates=periodic.GATES,
reference_gates=periodic.REFERENCE_GATES,
gates=periodic.GATES if a.jet_scenario in ("none", "zero") else None,
reference_gates=periodic.REFERENCE_GATES if a.jet_scenario in ("none", "zero") else None,
runner_sha256=runner_hash(),
wall_time_budget_seconds=budget,
full_pilot_calibration_seconds=calibration,
)
host_geometry(a.source, h, a.collision)
if a.observe_cv:
specification["cv_observation"] = dict(
full_tstar=[290, 300], pilot_tstar=[.02, 5], spacing_tstar=.02,
refined_contours_root=cv_contours(True, 40, a.placement).tolist(),
uniform_contours_root=cv_contours(False, a.uniform_diameter, a.placement).tolist(),
uniform_grid_origin_root=uniform_origin(a.uniform_diameter),
refined_grid_origin_root=specification["fine_origin_root_edge"],
cell_width_root={"uniform": 40/a.uniform_diameter, "refined": .5},
viscosity_root=.004, components=["mass", "Px", "Py"],
units="root lattice per unit depth; outward flux per root time",
interval="Impulse belongs to the interval ending at each snapshot; first retained endpoint (pilot .02, full 290) supplies initial inventory only: exclude its preceding impulse",
qualification="not assessed; trapezoidal integration and time-coarsening are offline",
)
if a.case != "uniform":
host_geometry(a.source, h, a.collision, a.jet_scenario, a.placement)
(a.output / "plan.json").write_text(json.dumps(specification, indent=2))
if a.mode == "plan":
return 0
@@ -621,8 +846,9 @@ def main():
"GPU execution blocked: root GPU gates approval and explicit device selection required"
)
results = []
cases = selected_cases(a.case, a.uniform_diameter)
a.deadline = time.monotonic() + budget
for case in ("uniform", "refined"):
for case, _ in cases:
try:
result = run_case(a, h, periodic, case)
except TimeoutError as exc:
@@ -650,7 +876,12 @@ def main():
status="pilot_only" if a.mode == "pilot" else "incomplete",
matched_case_pass=False,
)
if len(results) == 2 and all(r["healthy"] and r["periodic"] for r in results):
if a.jet_scenario in ("fixed", "reverse"):
comparison.update(status=("pilot_only" if a.mode == "pilot" else "driven_diagnostics_complete")
if len(results) == len(cases) and all(r["healthy"] for r in results) else "invalid_state",
qualification="not assessed; execution completion is not physical acceptance",
jet_diagnostic_windows={r["case"]: r["jet_diagnostic_windows"] for r in results})
if a.case == "both" and len(results) == 2 and all(r["healthy"] and r["periodic"] for r in results):
comparison.update(
status="periodic_comparison",
refined_vs_uniform=periodic.compare(
@@ -660,14 +891,20 @@ def main():
comparison["matched_case_pass"] = comparison["refined_vs_uniform"][
"reference_agreement"
]
if a.case != "both":
comparison.update(status="single_case_" + results[0]["status"],
own_reference_comparison=results[0].get("reference_comparison"))
(a.output / "comparison.json").write_text(
json.dumps(comparison, indent=2, allow_nan=False)
)
return (
0
if len(results) == 2
if len(results) == len(cases)
and all(r["healthy"] for r in results)
and (a.mode == "pilot" or comparison["matched_case_pass"])
and (a.mode == "pilot" or comparison["matched_case_pass"]
or a.jet_scenario in ("fixed", "reverse")
or (a.case != "both" and results[0]["periodic"]
and results[0].get("reference_comparison", {}).get("reference_agreement", False)))
else 2
)
+5 -5
View File
@@ -62,6 +62,7 @@ def decode_macros(data, w, cx, cy):
EXPERIMENTS = {
"historical": "source_pins.json",
"dev8403956": "source_pins_dev8403956.json",
"a135252": "source_pins_a135252.json",
}
@@ -69,11 +70,10 @@ def source_guard(root, variant, experiment="historical"):
manifest_path = HERE / "data/les_flow" / EXPERIMENTS[experiment]
manifest = json.loads(manifest_path.read_text())
for name, sha in manifest["sources"].items():
expected = (
manifest["candidate_header_sha256"]
if name == HEADER and variant == "corrected"
else sha
)
expected = sha
if name == HEADER:
expected = (manifest["candidate_header_sha256"] if variant == "corrected"
else manifest.get("baseline_header_sha256", sha))
if hashlib.sha256((root / name).read_bytes()).hexdigest() != expected:
raise RuntimeError("Source pin mismatch: " + name)
identity = dict(
@@ -0,0 +1,208 @@
"""New-source four-case repeat of 11901a7; frozen oracle and gates are unchanged."""
import argparse
import json
import math
from pathlib import Path
from assess import BASELINE_FACTOR, FLOORS
from oracle import LIMITS, TIMES, U, rectangles
from run_case import (INITIALIZATION, sample_steps, NUMERICAL_REVISION, SOURCE_SHA256,
BUILD_CAPTURE_SHA256, REFERENCE_HARNESS)
# Host-generated snapshots of a135252 at the frozen two local configurations.
# These describe expected inputs; actual sidecars are captured before cleanup.
BUILD_SOURCES = {
128: "803177416b7599ab89cc5afd35cf4a28a673b2f4bb8e8a6a1abc0b6d77610873",
256: "17ec5e60f87b840d3d13b8778bc8a3aecf485469c5a061af46c5cc19b73396cf",
}
CASES = ((100, 128, 1, "constant"), (100, 256, 1, "constant"),
(100, 128, 2, "constant"), (100, 128, 2, "projected_linear"))
NUMERICS = dict(lattice_model="D2Q9", collision="SRT", store_precision="FP32",
ddf_shifting=True, streaming="double_buffer", les_enabled=False,
boundary="periodic", block_shape=[8, 8],
sample_phase="postcollision G at root synchronization")
def finite(value):
return isinstance(value, (int, float)) and not isinstance(value, bool) and math.isfinite(value)
def finite_tree(value):
if isinstance(value, dict):
return all(finite_tree(v) for v in value.values())
if isinstance(value, list):
return all(finite_tree(v) for v in value)
return not isinstance(value, float) or math.isfinite(value)
def at_steps(rows, steps, n):
return len(rows) == len(steps) and all(
type(r.get("step")) is int and r["step"] == step and finite(r.get("tstar"))
and abs(r["tstar"] - step * U / n) <= 3e-17
for r, step in zip(rows, steps)
)
def maximum(rows, metric):
values = [r.get(metric) for r in rows]
return max(values) if values and all(finite(v) and v >= 0 for v in values) else None
def valid_builds(record, n, depth):
builds = record.get("actual_build_sidecars", [])
if not isinstance(builds, list) or len(builds) != depth:
return False
for level, build in enumerate(builds):
if not isinstance(build, dict):
return False
size = n * 2**level
cfg = build.get("config", {})
expected = dict(nx=10, ny=10, nz=1, lattice_model="D2Q9", collision="SRT",
store_precision="FP32", streaming="double_buffer", ddf_shifting=True,
les_enabled=False, velocity=0.0, viscosity=U*size/100, rho=1.0,
omega=1/(.5+3*U*size/100), threads_per_block=256)
ptx = build.get("ptx_sha256", "")
if (build.get("source_sha256") != BUILD_SOURCES[size]
or build.get("arch") != "sm_70" or build.get("flags") != ["--use_fast_math"]
or build.get("n_objects") != 0 or not isinstance(cfg, dict)
or any(cfg.get(k) != value for k, value in expected.items())
or not isinstance(ptx, str) or len(ptx) != 64
or any(c not in "0123456789abcdef" for c in ptx)):
return False
return True
def assess(records, expected_revision=None):
indexed, duplicates = {}, []
for record in records:
key = tuple(record.get(k) for k in ("re_L", "n", "depth", "explosion"))
if key in indexed:
duplicates.append(str(key))
else:
indexed[key] = record
missing = [str(k) for k in CASES if k not in indexed]
checks = dict(complete_matrix=not missing, no_extra_cases=set(indexed) <= set(CASES),
no_duplicate_cases=not duplicates, finite_receipts=finite_tree(records))
sources = [r.get("source", {}) for r in records]
checks["same_source_and_harness"] = bool(sources) and len({
json.dumps(s, sort_keys=True) for s in sources}) == 1
checks["clean_a135252_numerical_source"] = bool(sources) and all(
s.get("dirty") is False and s.get("source_tree_sha256") == SOURCE_SHA256
and bool(s.get("revision")) and bool(s.get("harness_sha256"))
and s.get("build_capture_sha256") == BUILD_CAPTURE_SHA256
and (expected_revision is None or s.get("revision") == expected_revision) for s in sources)
runtimes = [r.get("runtime_identity") for r in records]
checks["same_recorded_runtime"] = bool(runtimes) and all(
isinstance(v, dict) and all(v.get(k) for k in
("device", "nvcc_path", "nvcc_version", "python", "numpy", "pycuda"))
and isinstance(v["device"], dict) and v["device"].get("capability") == [7, 0]
and all(v["device"].get(k) for k in ("name", "pci_bus_id", "driver", "runtime"))
for v in runtimes
) and len({json.dumps(v, sort_keys=True) for v in runtimes}) == 1
devices = [r.get("cuda_visible_devices") for r in records]
checks["same_explicit_device"] = bool(devices) and all(
isinstance(d, str) and d and "," not in d and d != "-1" for d in devices
) and len(set(devices)) == 1
enabled = [r.get("early_pressure", {}).get("enabled") for r in records]
checks["same_early_sampling"] = bool(enabled) and all(type(v) is bool for v in enabled) and len(set(enabled)) == 1
shared_valid = all(checks.values())
complete, case_valid, early = {}, {}, []
for key in CASES:
if key not in indexed:
continue
r = indexed[key]
_, n, depth, scheme = key
label = f"{n}/{depth}/{scheme}"
rows = r.get("rows", [])
main_steps, early_steps = sample_steps(n, True)
complete[key] = r.get("completed") is True and at_steps(rows, main_steps, n)
checks[label + " complete_times"] = complete[key]
checks[label + " scales"] = (
r.get("U") == U and finite(r.get("viscosity"))
and abs(r["viscosity"] - U * n / 100) < 1e-15
and r.get("tau_by_level") == [0.5 + 3 * U * n / 100 * 2**l for l in range(depth)]
and r.get("mach") == U * math.sqrt(3)
)
checks[label + " actual_builds"] = valid_builds(r, n, depth)
checks[label + " reference"] = (r.get("numerical_revision") == NUMERICAL_REVISION
and r.get("reference_harness") == REFERENCE_HARNESS)
checks[label + " numerics"] = r.get("numerics") == NUMERICS and r.get("initialization") == INITIALIZATION
runtime = r.get("runtime_source", {})
package = Path(runtime.get("checkout", "")) / "src/CelerisLab"
checks[label + " runtime_source"] = bool(runtime.get("checkout")) and all(
runtime.get(k) == str(package / tail) for k, tail in
(("module", "__init__.py"), ("compiler", "cuda/compiler_v2.py"), ("kernel_root", "lbm/kernels")))
expected_patch = [] if depth == 1 else rectangles(n, depth)
checks[label + " patch"] = json.dumps(r.get("refinements")) == json.dumps(expected_patch)
cells = [n*n] if depth == 1 else [8704, 30720]
hops = [16*n * 2**l for l in range(depth)]
work = r.get("workload", {})
checks[label + " workload"] = (
work.get("active_cells_by_level") == cells and work.get("level_hops") == hops
and work.get("root_intervals") == 16*n
and work.get("active_collision_updates_by_level") == [c*h for c, h in zip(cells, hops)]
and work.get("active_collision_updates") == sum(c*h for c, h in zip(cells, hops))
)
checks[label + " absolute"] = bool(rows) and all(
finite(row.get(metric)) and 0 <= row[metric] <= limit
for row in rows for metric, limit in LIMITS.items())
trace = r.get("early_pressure", {})
trace_rows = trace.get("rows", [])
peak = maximum(trace_rows, "pressure_l2")
trace_complete = at_steps(trace_rows, early_steps, n) and peak is not None
checks[label + " early_trace"] = (
trace_complete and trace.get("sampled_max_pressure_l2") == peak
and len(rows) >= 2 and all(trace_rows[i]["pressure_l2"] == rows[j].get("pressure_l2")
for i, j in ((0, 0), (-1, 1)))
if trace.get("enabled") is True else
trace.get("enabled") is False and trace_rows == [] and trace.get("sampled_max_pressure_l2") is None
)
early.append(dict(n=n, depth=depth, explosion=scheme, enabled=trace.get("enabled"),
samples=len(trace_rows), complete=trace_complete,
sampled_max_pressure_l2=peak))
case_valid[key] = all(value for name, value in checks.items() if name.startswith(label + " "))
def worst(key, metric):
return maximum(indexed[key]["rows"][1:], metric) if complete.get(key) else None
comparisons, scheme_results = [], {}
for scheme in ("constant", "projected_linear"):
key = (100, 128, 2, scheme)
for metric, floor in FLOORS.items():
amr, coarse, fine = (worst(k, metric) for k in (key, CASES[0], CASES[1]))
budget = None if coarse is None else max(BASELINE_FACTOR * coarse, floor)
budget = budget if finite(budget) else None
ratio = None if amr is None or fine is None else amr / max(fine, 1e-30)
passed = amr is not None and budget is not None and amr <= budget
checks[f"baseline {scheme}/{metric}"] = passed
comparisons.append(dict(explosion=scheme, metric=metric, amr=amr,
uniform128=coarse, baseline_budget=budget, passed=passed,
uniform256=fine, amr_to_uniform256=ratio if finite(ratio) else None))
baseline_passed = all(checks[f"baseline {scheme}/{metric}"] for metric in FLOORS)
valid = shared_valid and all(case_valid.get(k, False) for k in (CASES[0], CASES[1], key))
scheme_results[scheme] = dict(passed=valid and baseline_passed,
valid_case_and_controls=valid, baseline_passed=baseline_passed)
return dict(passed=all(checks.values()), missing=missing, duplicates=duplicates, checks=checks,
comparisons=comparisons, scheme_results=scheme_results, early_pressure=early,
numerical_revision=NUMERICAL_REVISION, source_tree_sha256=SOURCE_SHA256,
reference_harness=REFERENCE_HARNESS, expected_revision=expected_revision,
floors=FLOORS, baseline_factor=BASELINE_FACTOR,
main_statistic="maximum of four post-initial samples at t*=.12,.24,.36,.48",
early_statistic="sampled pressure maximum only, t*=k*.001875, k=0..64; not an all-step or continuous maximum",
finest_control="uniform256 and AMR/ uniform256 ratios are descriptive, not acceptance gates",
scope="2D periodic Re100 smooth-decay diagnostic; no new algorithm, convergence-order or general AMR qualification")
if __name__ == "__main__":
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("files", type=Path, nargs="+")
p.add_argument("--output", type=Path, required=True)
p.add_argument("--expected-revision", required=True)
args = p.parse_args()
if args.output.exists():
p.error("Output already exists; choose a new path to retain prior evidence")
result = assess([json.loads(path.read_text()) for path in args.files], args.expected_revision)
args.output.write_text(json.dumps(result, indent=2, allow_nan=False) + "\n")
print(json.dumps(result, indent=2, allow_nan=False))
raise SystemExit(0 if result["passed"] else 1)
+134 -21
View File
@@ -1,9 +1,10 @@
"""One bounded GPU case. No production edits, plots, checkpoints or field dumps."""
"""One bounded GPU case, with explicit opt-in experimental explosion."""
import argparse
import hashlib
import json
import os
import shutil
from pathlib import Path
import subprocess
import sys
@@ -12,6 +13,35 @@ import time
import numpy as np
from oracle import U, TIMES, LIMITS, initial, metrics, rectangles
NUMERICAL_REVISION = "a135252ae78b47b57d7e77d19001700b3bedac8b"
SOURCE_SHA256 = "a5dbfd804befce868067d79a23e5fd47dce7f505b3f9b1bb2145fb57cb5f2178"
BUILD_CAPTURE_SHA256 = "3dbaa6547cb0a4cb1541054f3b64ad8b6e18cc70527ac6166e56b944e9bd464a"
REFERENCE_HARNESS = "11901a7f77557a901e017a171eeae1758d584fa5"
INITIALIZATION = "physical FP64 equilibrium G at actual cell centers; rho=1+3p"
def sample_steps(n, early_pressure=False):
"""Root synchronization steps; early ladder matches the 707afe6 diagnostic."""
main = [round(tstar * n / U) for tstar in TIMES]
early = list(range(0, 4 * n + 1, n // 16)) if early_pressure else []
return main, early
def runtime_source(repo):
"""Fail before CUDA if Python or the compiler snapshot comes from another tree."""
import CelerisLab
from CelerisLab.cuda import compiler_v2
paths = dict(module=Path(CelerisLab.__file__).resolve(),
compiler=Path(compiler_v2.__file__).resolve(),
kernel_root=Path(compiler_v2.kernel_path("blocks.cu")).resolve().parent)
package = repo / "src/CelerisLab"
expected = dict(module=package / "__init__.py", compiler=package / "cuda/compiler_v2.py",
kernel_root=package / "lbm/kernels")
if paths != expected:
raise RuntimeError("Wrong imported source or CUDA source/include root")
return dict(checkout=str(repo), **{key: str(path) for key, path in paths.items()})
def provenance(repo):
git = lambda *a: subprocess.check_output(
@@ -34,6 +64,46 @@ def provenance(repo):
)
def verify_source(repo, revision):
"""Exact clean harness commit, fixed production tree, and reviewed capture helper."""
import oracle
from tests.validation.multigrid import check_projected_pairs as gate
harness = repo / "tests/validation/taylor_green"
if (Path(__file__).resolve() != harness / "run_case.py"
or Path(oracle.__file__).resolve() != harness / "oracle.py"):
raise RuntimeError("Wrong runner or oracle checkout")
helper = repo / "tests/validation/multigrid/check_projected_pairs.py"
if (Path(gate.__file__).resolve() != helper
or hashlib.sha256(helper.read_bytes()).hexdigest() != BUILD_CAPTURE_SHA256):
raise RuntimeError("Wrong build-capture helper")
if gate.preflight(repo, revision, "candidate") != NUMERICAL_REVISION:
raise RuntimeError("Wrong production revision")
result = provenance(repo)
if result["source_tree_sha256"] != SOURCE_SHA256:
raise RuntimeError("Wrong numerical source fingerprint")
result["build_capture_sha256"] = BUILD_CAPTURE_SHA256
return result
def build_capture(report, save):
from tests.validation.multigrid.check_projected_pairs import capture_builds
return capture_builds(report, save)
def runtime_identity(ctx):
import pycuda
import pycuda.driver as cuda
nvcc = shutil.which("nvcc") or "/usr/local/cuda/bin/nvcc"
return dict(device=dict(name=ctx.device.name(), pci_bus_id=ctx.device.pci_bus_id(),
capability=list(ctx.device.compute_capability()),
driver=cuda.get_driver_version(), runtime=list(cuda.get_version())),
nvcc_path=str(Path(nvcc).resolve()),
nvcc_version=subprocess.check_output([nvcc, "--version"], text=True).strip(),
python=sys.version, numpy=np.__version__, pycuda=pycuda.VERSION_TEXT)
def config(n, re):
from CelerisLab.config import LBMConfig
@@ -71,19 +141,31 @@ def workload(masks, base_steps):
def main():
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("--repo", type=Path, required=True)
p.add_argument("--expected-revision", required=True)
p.add_argument("--run-gpu", action="store_true")
p.add_argument("--dry-run", action="store_true")
p.add_argument("--re", type=int, choices=[100, 1000], required=True)
p.add_argument("--n", type=int, choices=[32, 64, 128, 256], required=True)
p.add_argument("--depth", type=int, choices=[1, 2, 3], required=True)
p.add_argument("--output", type=Path, required=True)
p.add_argument("--explosion", choices=["constant", "projected_linear"], default="constant")
p.add_argument("--early-pressure", action="store_true",
help="also save 65 scalar pressure samples at t*=k*.001875, k=0..64")
args = p.parse_args()
if not os.environ.get("CUDA_VISIBLE_DEVICES"):
p.error("Explicit physical CUDA_VISIBLE_DEVICES selection required")
if args.output.exists():
p.error("Output already exists; choose a new path to retain prior evidence")
if args.explosion != "constant" and args.depth != 2:
p.error("projected_linear requires depth 2")
selected = os.environ.get("CUDA_VISIBLE_DEVICES", "")
if not args.dry_run and (not args.run_gpu or not selected or "," in selected or selected == "-1"):
p.error("--run-gpu and exactly one explicit CUDA_VISIBLE_DEVICES are required")
repo = args.repo.resolve()
sys.path.insert(0, str(repo / "src"))
import CelerisLab
if Path(CelerisLab.__file__).resolve() != repo / "src/CelerisLab/__init__.py":
raise RuntimeError("Wrong imported source checkout")
sys.path[:0] = [str(repo / "src"), str(repo)]
source = verify_source(repo, args.expected_revision)
runtime = runtime_source(repo)
if args.dry_run:
print(json.dumps(dict(source=source, runtime_source=runtime, dry_run=True)))
return 0
from CelerisLab.cuda.context import CudaContext
from CelerisLab.lbm.blocks import BlockLayout2D
from CelerisLab.lbm.block_stepper import PeriodicBlockStepper
@@ -96,9 +178,17 @@ def main():
h = build_hierarchy(cfg, refinements)
np.testing.assert_array_equal(leaf_partition(h), np.ones((args.n, args.n)))
masks = [k == ACTIVE for k in h.kinds]
main_steps, early_steps = sample_steps(args.n, args.early_pressure)
report = dict(
schema=1,
source=provenance(repo),
source=source,
numerical_revision=NUMERICAL_REVISION,
reference_harness=REFERENCE_HARNESS,
actual_build_sidecars=[],
runtime_identity=None,
runtime_source=runtime,
historical_baseline_revision="9805383f9c50d867e8555471baf5dbda8333a652",
explosion=args.explosion,
n=args.n,
re_L=args.re,
depth=args.depth,
@@ -107,21 +197,35 @@ def main():
mach=U * np.sqrt(3),
viscosity=cfg.viscosity,
tau_by_level=[0.5 + 3 * c.viscosity for c in h.configs],
initialization="physical FP64 equilibrium G at actual cell centers; rho=1+3p",
cuda_visible_devices=os.environ["CUDA_VISIBLE_DEVICES"],
initialization=INITIALIZATION,
numerics=dict(lattice_model=cfg.lattice_model, collision=cfg.collision,
store_precision=cfg.store_precision, ddf_shifting=cfg.ddf_shifting,
streaming=cfg.streaming, les_enabled=cfg.les_enabled,
boundary="periodic", block_shape=[8, 8],
sample_phase="postcollision G at root synchronization"),
cuda_visible_devices=selected,
device_id=0,
limits=LIMITS,
workload=workload(masks, round(TIMES[-1] * args.n / U)),
rows=[],
early_pressure=dict(enabled=args.early_pressure, rows=[],
sampled_max_pressure_l2=None),
completed=False,
)
args.output.parent.mkdir(parents=True, exist_ok=True)
save = lambda: args.output.write_text(
json.dumps(report, indent=2, allow_nan=False) + "\n"
)
def save():
temporary = args.output.with_suffix(args.output.suffix + ".tmp")
text = json.dumps(report, indent=2, allow_nan=False) + "\n"
if len(text.encode()) > 1024 * 1024:
raise RuntimeError("Scalar receipt exceeds 1 MiB cap")
temporary.write_text(text)
temporary.replace(args.output)
save()
started = time.monotonic()
with CudaContext(0) as ctx:
with CudaContext(0) as ctx, build_capture(report, save):
report["runtime_identity"] = runtime_identity(ctx)
save()
if args.depth == 1:
layout = BlockLayout2D.build(args.n, args.n, 8, 8, periodic=(True, True))
run = PeriodicBlockStepper(cfg, layout, context=ctx)
@@ -132,6 +236,7 @@ def main():
coarse_boundary="periodic",
refinements=refinements,
level_blocks=[(8, 8)] * args.depth,
explosion=args.explosion,
)
with run:
run.initialize(
@@ -141,24 +246,30 @@ def main():
]
)
initial_mass = None
for tstar in TIMES:
step = round(tstar * args.n / U)
for step in sorted(set(main_steps + early_steps)):
run.step(step - run.step_count)
arrays = (run.download(),) if args.depth == 1 else run.download()
row = metrics(arrays, masks, step, args.n, cfg.viscosity, initial_mass)
if not all(np.isfinite(value) for value in row.values()):
raise FloatingPointError("nonfinite sample diagnostics")
row["step"] = step
if initial_mass is None:
initial_mass = row["mass"]
report["rows"].append(row)
if step in main_steps:
report["rows"].append(row)
if step in early_steps:
trace = report["early_pressure"]
trace["rows"].append({key: row[key] for key in ("step", "tstar", "pressure_l2")})
trace["sampled_max_pressure_l2"] = max(r["pressure_l2"] for r in trace["rows"])
save()
print(
json.dumps(
dict(
event="PROGRESS",
event="PROGRESS" if step in main_steps else "EARLY_PRESSURE",
n=args.n,
re_L=args.re,
depth=args.depth,
**row,
**(row if step in main_steps else report["early_pressure"]["rows"][-1]),
)
),
flush=True,
@@ -168,7 +279,9 @@ def main():
# This is the first measured trajectory step, not discarded warmup.
run.step(1)
probe = (run.download(),) if args.depth == 1 else run.download()
metrics(probe, masks, 1, args.n, cfg.viscosity, initial_mass)
probe_metrics = metrics(probe, masks, 1, args.n, cfg.viscosity, initial_mass)
if not all(np.isfinite(value) for value in probe_metrics.values()):
raise FloatingPointError("nonfinite READY diagnostics")
report["ready_after_step"] = 1
save()
print(
@@ -0,0 +1,450 @@
"""Host geometry, receipt-corruption tests and mocked scheduling; no CUDA/flow."""
from contextlib import nullcontext, redirect_stdout
from copy import deepcopy
from dataclasses import asdict, replace
import hashlib
import io
import json
from pathlib import Path
import subprocess
import sys
import tempfile
from types import SimpleNamespace
import unittest
from unittest.mock import patch
import numpy as np
import run_case
from assess_projected_pairs import (BUILD_SOURCES, CASES, NUMERICS, NUMERICAL_REVISION,
SOURCE_SHA256, assess)
from oracle import LIMITS, TIMES, U, rectangles
REPO = Path(__file__).resolve().parents[3]
OLD_REVISION = "519473a61c7b319183aa54e55b9f097499dde0bf"
MOCK_REVISION = "f" * 40
RUNTIME = dict(device=dict(name="host mock", pci_bus_id="mock", capability=[7, 0],
driver=12040, runtime=[12, 4, 0]), nvcc_path="/mock/nvcc",
nvcc_version="mock nvcc", python="mock Python", numpy=np.__version__, pycuda="mock")
def source():
return dict(revision=MOCK_REVISION, dirty=False, source_tree_sha256=SOURCE_SHA256,
harness_sha256={"run_case.py": "a" * 64},
build_capture_sha256=run_case.BUILD_CAPTURE_SHA256)
def build_metadata(size):
cfg = replace(run_case.config(size, 100), nx=10, ny=10)
cfg.validate()
return dict(source_sha256=BUILD_SOURCES[size], config=asdict(cfg), n_objects=0,
arch="sm_70", flags=["--use_fast_math"], ptx_sha256="b" * 64)
def records(early=False):
from CelerisLab.lbm.hierarchy import build_hierarchy
from CelerisLab.lbm.refinement import ACTIVE
out = []
for re, n, depth, scheme in CASES:
cfg = run_case.config(n, re)
refinements = [] if depth == 1 else rectangles(n, depth)
h = build_hierarchy(cfg, refinements)
main_steps, early_steps = run_case.sample_steps(n, early)
out.append(dict(
re_L=re, n=n, depth=depth, explosion=scheme, U=U, mach=float(U*np.sqrt(3)),
viscosity=cfg.viscosity, tau_by_level=[0.5+3*c.viscosity for c in h.configs],
refinements=refinements, numerics=NUMERICS.copy(), initialization=run_case.INITIALIZATION,
source=source(), numerical_revision=NUMERICAL_REVISION,
reference_harness=run_case.REFERENCE_HARNESS,
actual_build_sidecars=[build_metadata(n * 2**level) for level in range(depth)],
runtime_identity=deepcopy(RUNTIME), cuda_visible_devices="0",
runtime_source=run_case.runtime_source(REPO), completed=True,
workload=run_case.workload([k == ACTIVE for k in h.kinds], 16*n),
rows=[dict(step=s, tstar=s*U/n, **{k: 0.0 for k in LIMITS}) for s in main_steps],
early_pressure=dict(enabled=early, rows=[
dict(step=s, tstar=s*U/n, pressure_l2=.01 if s not in main_steps else 0.0) for s in early_steps],
sampled_max_pressure_l2=.01 if early else None)))
return out
class ProjectedPairsTests(unittest.TestCase):
def test_exact_geometry_work_and_samples(self):
from CelerisLab.lbm.hierarchy import build_hierarchy, leaf_partition
data = records(True)
self.assertEqual(sum(r["workload"]["active_collision_updates"] for r in data), 589299712)
for r in data:
n, depth = r["n"], r["depth"]
h = build_hierarchy(run_case.config(n, 100), r["refinements"])
np.testing.assert_array_equal(leaf_partition(h), np.ones((n, n)))
main, early = run_case.sample_steps(n, True)
self.assertEqual(main, [0, 4*n, 8*n, 12*n, 16*n])
self.assertEqual(early, [k*(n//16) for k in range(65)])
np.testing.assert_allclose(np.array(early)*U/n, np.arange(65)*.001875, rtol=0, atol=3e-17)
if depth == 2:
self.assertEqual(r["refinements"], [[(16, 16, 112, 96)]])
self.assertTrue(assess(data)["passed"])
self.assertTrue(assess(records())["passed"])
def test_exact_old519_geometry_and_table_parity(self):
from CelerisLab.lbm.blocks import BlockLayout2D
from CelerisLab.lbm.hierarchy import build_hierarchy
from CelerisLab.lbm.refinement_tables import projected_explosion_tables
# Frozen from executing exact 519473a61c7b319183aa54e55b9f097499dde0bf
# geometry and table definitions, after checking unchanged config,
# descriptors and blocks. No historical Git object is needed at runtime.
# Historical source SHA256, refinement.py then refinement_tables.py:
# 08c2a0557276a98cbcaa459d9bb7a9735d8bbbf64a6114c57af2fda61481a687
# dabff948bb30496384d1a52c666b0edbc2085f9c61ed1bbc39f748502629113d
frozen = {
"covered": ("|b1", (128, 128), "14a1b5be54e3309bea825a00a653105951f0c805622b877a86dd453d65556df3"),
"fine_kind": ("|u1", (256, 256), "891ff72c3d60686c62b1f35ffe59d054ac23b8f9d59aeb5782bc941202794cc0"),
"ghost_fine": ("<u8", (2880,), "2d0311ac0feb1c0e1e2b6bcf806fe616b8217513de218407267dcd7652287579"),
"ghost_coarse": ("<u4", (2880,), "5a3b305a0f841c8d05a13f105fda02b43ef875ab1321f9bca579f2b8ae313233"),
"coalesce_coarse": ("<u8", (1060,), "a1d88c60f282153dcf2bb497c59d777968b6db773d061d8fea08163c98155967"),
"coalesce_fine": ("<u8", (1060, 4), "08914c5d17c1ec8e2bfd234f581e4b3283de26296ae7d80403385feed7b89532"),
"neighbors": ("<u8", (2880, 4), "cfef3a07103241e3dfff24fd65ab967afcf20520f699574b191044d47cf5d1f4"),
"offsets": ("<f4", (2880, 2), "c98ba658d5f2cc18605e029fbe1da448ded3fd2436edcaf8ea097fa46aeb1f2d"),
}
hierarchy = build_hierarchy(run_case.config(128, 100), rectangles(128, 2))
pair = hierarchy.pairs[0]
self.assertEqual((pair.coarse_shape, pair.fine_shape, pair.fine_origin),
((128, 128), (256, 256), (0.0, 0.0)))
self.assertEqual(len(np.unique(pair.ghost_coarse)), 720)
self.assertTrue((hierarchy.kinds[0].ravel()[pair.ghost_coarse] == 0).all())
layout = BlockLayout2D.build(128, 128, 8, 8, periodic=(True, True))
neighbors, offsets = projected_explosion_tables(pair, layout, hierarchy.kinds[0])
arrays = dict(neighbors=neighbors, offsets=offsets)
arrays.update({name: getattr(pair, name) for name in frozen if name not in arrays})
for name, array in arrays.items():
with self.subTest(array=name):
self.assertEqual((array.dtype.str, array.shape, hashlib.sha256(array.tobytes()).hexdigest()),
frozen[name])
def test_actual_build_capture_rejects_tampered_ptx_and_sidecar(self):
from CelerisLab.cuda import compiler_v2
from tests.validation.multigrid.check_projected_pairs import capture_builds
for tamper in (None, "ptx", "sidecar"):
with self.subTest(tamper=tamper), tempfile.TemporaryDirectory() as tmp:
path = Path(tmp) / "blocks.ptx"
path.write_bytes(b"host-only mock PTX")
metadata = dict(ptx_sha256=hashlib.sha256(path.read_bytes()).hexdigest())
if tamper == "ptx":
path.write_bytes(b"tampered")
if tamper == "sidecar":
metadata["ptx_sha256"] = "0" * 64
Path(str(path) + ".json").write_text(json.dumps(metadata))
report = {"actual_build_sidecars": []}
with patch.object(compiler_v2, "load_module", return_value="mock-module") as load:
with capture_builds(report, lambda: None):
if tamper:
with self.assertRaisesRegex(AssertionError, "PTX and build sidecar"):
compiler_v2.load_module(str(path))
load.assert_not_called()
self.assertEqual(report["actual_build_sidecars"], [])
else:
self.assertEqual(compiler_v2.load_module(str(path)), "mock-module")
self.assertEqual(report["actual_build_sidecars"], [metadata])
self.assertIs(compiler_v2.load_module, load)
def test_frozen_formula_and_finest_control(self):
data = records(True)
data[0]["rows"][2]["velocity_l2"] = .002
data[0]["rows"][0]["velocity_l2"] = .04 # retained absolute gate, excluded from worst
for r in data[2:]:
for row in r["rows"][1:]:
row.update(velocity_l2=.0039, pressure_l2=.02, energy_relative=.004)
r["early_pressure"]["rows"][-1]["pressure_l2"] = .02
r["early_pressure"]["sampled_max_pressure_l2"] = .02
data[1]["rows"][2]["velocity_l2"] = .00001
data[3]["early_pressure"]["rows"][7]["pressure_l2"] = .9
data[3]["early_pressure"]["sampled_max_pressure_l2"] = .9
result = assess(data)
self.assertTrue(result["passed"])
velocity = result["comparisons"][0]
self.assertEqual(velocity["baseline_budget"], .004)
self.assertAlmostEqual(velocity["amr_to_uniform256"], 390)
self.assertEqual(result["early_pressure"][-1]["sampled_max_pressure_l2"], .9)
data[3]["rows"][-1]["pressure_l2"] = .02001
result = assess(data)
self.assertFalse(result["passed"])
self.assertEqual(result["comparisons"][4]["amr"], .02001)
def test_scheme_verdicts_are_independent(self):
data = records()
data[2]["rows"][-1]["pressure_l2"] = .03
result = assess(data)
self.assertFalse(result["passed"])
self.assertFalse(result["scheme_results"]["constant"]["passed"])
self.assertTrue(result["scheme_results"]["projected_linear"]["passed"])
def test_corruptions_cannot_pass(self):
good = records(True)
corruptions = [
lambda r: r.update(completed=False),
lambda r: r["rows"].pop(),
lambda r: r["rows"][-1].update(pressure_l2=float("nan")),
lambda r: r["rows"][-1].update(energy_relative=float("inf")),
lambda r: r["rows"][-1].update(pressure_l2=1e308),
lambda r: r["rows"][-1].update(velocity_l2=-1),
lambda r: r["rows"][-1].update(step=2047),
lambda r: r["rows"][-1].update(tstar=.4801),
lambda r: r["source"].update(dirty=True),
lambda r: r["source"].update(source_tree_sha256="wrong"),
lambda r: r["source"].update(revision=OLD_REVISION),
lambda r: r["source"].pop("build_capture_sha256"),
lambda r: r.update(numerical_revision=OLD_REVISION),
lambda r: r.update(reference_harness="wrong"),
lambda r: r.pop("runtime_identity"),
lambda r: r["runtime_identity"].pop("nvcc_version"),
lambda r: r["runtime_identity"].update(device="wrong"),
lambda r: r["runtime_identity"]["device"].update(capability=[8, 0]),
lambda r: r.update(cuda_visible_devices="0,1"),
lambda r: r.pop("actual_build_sidecars"),
lambda r: r["actual_build_sidecars"].pop(),
lambda r: r["actual_build_sidecars"].reverse(),
lambda r: r["actual_build_sidecars"][0].update(source_sha256="c" * 64),
lambda r: r["actual_build_sidecars"][0].update(arch="sm_80"),
lambda r: r["actual_build_sidecars"][0].update(flags=[]),
lambda r: r["actual_build_sidecars"][0].update(ptx_sha256="not-a-hash"),
lambda r: r["actual_build_sidecars"][0]["config"].update(ddf_shifting=False),
lambda r: r["source"]["harness_sha256"].update(extra="mixed"),
lambda r: r.update(viscosity=.01),
lambda r: r["tau_by_level"].reverse(),
lambda r: r["numerics"].update(ddf_shifting=False),
lambda r: r.update(initialization="different equilibrium"),
lambda r: r.update(refinements=[[(16, 16, 112, 104)]]),
lambda r: r["workload"].update(active_collision_updates=0),
lambda r: r["runtime_source"].update(kernel_root="/wrong/installed/tree"),
lambda r: r["early_pressure"]["rows"].pop(),
lambda r: r["early_pressure"]["rows"][8].update(step=65),
lambda r: r["early_pressure"]["rows"][-1].update(pressure_l2=.005),
lambda r: r["early_pressure"]["rows"][8].update(pressure_l2=float("nan")),
lambda r: r["early_pressure"].update(sampled_max_pressure_l2=.5),
lambda r: r["early_pressure"].update(enabled=False),
]
for mutation in corruptions:
bad = deepcopy(good)
mutation(bad[-1])
with self.subTest(mutation=mutation):
result = assess(bad)
self.assertFalse(result["passed"])
json.dumps(result, allow_nan=False) # failure summary itself remains serializable
self.assertTrue(assess(good, expected_revision=MOCK_REVISION)["passed"])
self.assertFalse(assess(good, expected_revision=OLD_REVISION)["passed"])
old = deepcopy(good)
for record in old:
record["source"].update(revision=OLD_REVISION,
source_tree_sha256="766e173df81d2881d3871007f15d5e321f5c7205ae578b0f80b43d1e7fe3e220")
self.assertFalse(assess(old)["passed"])
self.assertFalse(assess(good[:-1])["passed"])
self.assertFalse(assess(good + [good[-1]])["passed"])
self.assertFalse(assess([])["passed"])
incomplete = deepcopy(good)
incomplete[-1]["completed"] = False
self.assertFalse(assess(incomplete)["comparisons"][3]["passed"])
def test_pinned_build_sources_match_host_generated_inputs(self):
"""The pinned fingerprints are what today's compiler generates from the qualified
NUMERICAL_REVISION kernels; the current kernels may legitimately differ."""
import tarfile
from CelerisLab.cuda import compiler_v2
kernels = "src/CelerisLab/lbm/kernels"
if subprocess.run(["git", "-C", str(REPO), "cat-file", "-e",
f"{NUMERICAL_REVISION}^{{commit}}"], capture_output=True).returncode:
self.fail(f"{NUMERICAL_REVISION} is not in this clone; the pinned build "
"sources cannot be checked")
archive = subprocess.run(["git", "-C", str(REPO), "archive", "--format=tar",
NUMERICAL_REVISION, kernels],
capture_output=True, check=True).stdout
with tempfile.TemporaryDirectory() as snapshot:
with tarfile.open(fileobj=io.BytesIO(archive)) as tar:
tar.extractall(snapshot)
with patch.object(compiler_v2, "_KERNEL_DIR", str(Path(snapshot) / kernels)):
for size in (128, 256):
with self.subTest(size=size):
cfg = replace(run_case.config(size, 100), nx=10, ny=10)
cfg.validate()
root = compiler_v2.generate_config(cfg)
try:
actual = json.loads((Path(root) / ".celeris-build").read_text())
expected = build_metadata(size)
self.assertEqual(actual, {key: expected[key] for key in
("source_sha256", "config", "n_objects")})
finally:
compiler_v2.cleanup_build_dir(root)
def test_source_preflight_requires_clean_exact_revision_and_tree(self):
import oracle
from tests.validation.multigrid import check_projected_pairs as gate
for module in (run_case, oracle):
with self.subTest(imported_module=module.__name__), \
patch.object(module, "__file__", "/wrong/checkout/" + Path(module.__file__).name), \
patch.object(gate, "preflight") as preflight:
with self.assertRaisesRegex(RuntimeError, "Wrong runner or oracle checkout"):
run_case.verify_source(REPO, MOCK_REVISION)
preflight.assert_not_called()
for expected, status, diff, fingerprint in (
(MOCK_REVISION, "", 0, SOURCE_SHA256),
(OLD_REVISION, "", 0, SOURCE_SHA256),
(MOCK_REVISION, " M tracked.py", 0, SOURCE_SHA256),
(MOCK_REVISION, "", 1, SOURCE_SHA256),
(MOCK_REVISION, "", 0, "wrong")):
provenance = dict(source(), source_tree_sha256=fingerprint)
with self.subTest(expected=expected, status=status, diff=diff, fingerprint=fingerprint), \
patch.object(gate.subprocess, "check_output", side_effect=[MOCK_REVISION, status]), \
patch.object(gate.subprocess, "call", return_value=diff), \
patch.object(run_case, "provenance", return_value=provenance):
if expected != MOCK_REVISION or status or diff or fingerprint != SOURCE_SHA256:
with self.assertRaises((ValueError, RuntimeError)):
run_case.verify_source(REPO, expected)
else:
self.assertEqual(run_case.verify_source(REPO, expected), source())
def test_explicit_opt_in_selector_and_dry_run_without_cuda(self):
with tempfile.TemporaryDirectory() as tmp:
output = Path(tmp) / "case.json"
base = ["run_case.py", "--repo", str(REPO), "--re", "100", "--n", "128",
"--depth", "1", "--output", str(output)]
pinned = base + ["--expected-revision", MOCK_REVISION]
for argv, device in ((base + ["--run-gpu"], "0"), (pinned, "0"),
(pinned + ["--run-gpu"], ""), (pinned + ["--run-gpu"], "0,1"),
(pinned + ["--run-gpu"], "-1"),
(pinned + ["--run-gpu", "--explosion", "projected"], "0"),
(pinned + ["--run-gpu", "--explosion", "projected_linear"], "0")):
with self.subTest(argv=argv, device=device), patch.object(sys, "argv", argv), \
patch.dict("os.environ", CUDA_VISIBLE_DEVICES=device), \
patch.object(run_case, "verify_source") as verify, patch("sys.stderr", io.StringIO()):
with self.assertRaises(SystemExit) as caught:
run_case.main()
self.assertEqual(caught.exception.code, 2)
verify.assert_not_called()
self.assertFalse(output.exists())
stdout = io.StringIO()
cuda_modules = {name: None for name in ("pycuda", "CelerisLab.cuda.context",
"CelerisLab.lbm.block_stepper", "CelerisLab.lbm.refinement_stepper")}
with patch.object(sys, "argv", pinned + ["--dry-run"]), \
patch.dict(sys.modules, cuda_modules), patch.dict("os.environ", CUDA_VISIBLE_DEVICES=""), \
patch.object(run_case, "verify_source", return_value=source()) as verify, \
patch.object(run_case, "runtime_identity", side_effect=AssertionError("CUDA reached")), \
redirect_stdout(stdout):
self.assertEqual(run_case.main(), 0)
verify.assert_called_once_with(REPO, MOCK_REVISION)
self.assertTrue(json.loads(stdout.getvalue())["dry_run"])
self.assertFalse(output.exists())
def test_runtime_rejects_installed_kernel_tree(self):
from CelerisLab.cuda import compiler_v2
with patch.object(compiler_v2, "_KERNEL_DIR", "/other/CelerisLab/lbm/kernels"):
with self.assertRaisesRegex(RuntimeError, "CUDA source/include root"):
run_case.runtime_source(REPO)
def test_existing_output_is_never_overwritten(self):
with tempfile.TemporaryDirectory() as tmp:
output = Path(tmp) / "failed.json"
output.write_text('{"completed": false}\n')
argv = ["run_case.py", "--repo", str(REPO), "--re", "100", "--n", "128",
"--depth", "1", "--output", str(output),
"--expected-revision", MOCK_REVISION, "--run-gpu"]
with patch.object(sys, "argv", argv), patch("sys.stderr", io.StringIO()):
with self.assertRaises(SystemExit) as caught:
run_case.main()
self.assertEqual(caught.exception.code, 2)
self.assertEqual(output.read_text(), '{"completed": false}\n')
result = subprocess.run([sys.executable, str(Path(__file__).with_name("assess_projected_pairs.py")),
"unused.json", "--expected-revision", MOCK_REVISION,
"--output", str(output)], capture_output=True)
self.assertEqual(result.returncode, 2)
self.assertEqual(output.read_text(), '{"completed": false}\n')
def test_mocked_runner_default_early_and_failure(self):
# Replace the GPU context and steppers before import. No CUDA module or flow is used.
for early, depth, fail in ((False, 1, None), (False, 2, None), (True, 2, None),
(True, 2, "resource"), (True, 2, "nonfinite"),
(True, 2, "probe_nonfinite")):
calls, selectors = [], []
class FakeRun:
def __init__(self, *args, **kwargs):
self.step_count = 0
if "coarse_boundary" in kwargs:
selectors.append(kwargs["explosion"])
def __enter__(self):
return self
def __exit__(self, *args):
pass
def initialize(self, *arrays):
pass
def step(self, count):
self.assertion = count >= 0
if not self.assertion:
raise AssertionError("backward step")
if fail == "resource" and self.step_count >= 16:
raise MemoryError("mock resource failure")
self.step_count += count
calls.append(self.step_count)
def download(self):
return None
modules = {
"CelerisLab.cuda.context": SimpleNamespace(CudaContext=FakeRun),
"CelerisLab.lbm.block_stepper": SimpleNamespace(PeriodicBlockStepper=FakeRun),
"CelerisLab.lbm.refinement_stepper": SimpleNamespace(FixedPatchStepper=FakeRun),
}
def metric(arrays, masks, step, n, nu, mass):
return dict(step=step, tstar=step*U/n, mass=16384.,
**{k: float("nan") if ((fail == "nonfinite" and step == 16)
or (fail == "probe_nonfinite" and step == 1))
and k == "energy_relative" else 0.0 for k in LIMITS})
with tempfile.TemporaryDirectory() as tmp:
output = Path(tmp) / "case.json"
argv = ["run_case.py", "--repo", str(REPO), "--re", "100", "--n", "128",
"--depth", str(depth), "--output", str(output),
"--expected-revision", MOCK_REVISION, "--run-gpu"]
if early:
argv += ["--early-pressure", "--explosion", "projected_linear"]
with patch.dict(sys.modules, modules), patch.object(sys, "argv", argv), \
patch.dict("os.environ", CUDA_VISIBLE_DEVICES="mock"), \
patch.object(run_case, "verify_source", return_value=source()) as verify, \
patch.object(run_case, "runtime_identity", return_value=deepcopy(RUNTIME)), \
patch.object(run_case, "build_capture", return_value=nullcontext()), \
patch.object(run_case, "metrics", side_effect=metric), redirect_stdout(io.StringIO()):
if fail:
with self.assertRaises(MemoryError if fail == "resource" else FloatingPointError):
run_case.main()
else:
self.assertEqual(run_case.main(), 0)
receipt = json.loads(output.read_text())
verify.assert_called_once_with(REPO, MOCK_REVISION)
self.assertEqual(selectors, ["projected_linear" if early else "constant"] if depth == 2 else [])
self.assertEqual(receipt["source"], source())
self.assertEqual(receipt["runtime_identity"], RUNTIME)
self.assertEqual(receipt["completed"], not fail)
self.assertEqual(calls[:2], [0, 1]) # READY probe is part of this trajectory
if not fail:
self.assertEqual([r["tstar"] for r in receipt["rows"]], TIMES)
self.assertEqual(len(receipt["early_pressure"]["rows"]), 65 if early else 0)
self.assertEqual(calls[-1], 2048)
else:
self.assertEqual(len(receipt["rows"]), 1)
self.assertEqual(len(receipt["early_pressure"]["rows"]),
{"resource": 3, "nonfinite": 2, "probe_nonfinite": 1}[fail])
if fail == "probe_nonfinite":
self.assertNotIn("ready_after_step", receipt)
if __name__ == "__main__":
unittest.main()
+3 -2
View File
@@ -173,8 +173,9 @@ def time_refined(a, h, sched):
cfg, pair, body, host = r.host_geometry(a.source, h, "MRT")
context = stack.enter_context(CudaContext(0))
backend = stack.enter_context(FixedPatchStepper(
cfg, r.BOUNDS, context=context, coarse_boundary="channel", base_block=r.BASE_BLOCK,
fine_block=r.FINE_BLOCK, fine_objects=(body,), observe_raw_exchange=True))
cfg, context=context, coarse_boundary="channel", refinements=[r.BOUNDS],
level_blocks=[r.BASE_BLOCK, r.FINE_BLOCK], level_objects=[(), (body,)],
observe_raw_exchange=True))
masks = [channel_masks(pair.coarse_shape)[0] & ~pair.covered, # as run_refined_dfg
(pair.fine_kind == ACTIVE) & ((host.flags.reshape(pair.fine_shape) & SOLID) == 0)]
fresh = (r.initial_state(pair.coarse_shape, (0.0, 0.0), 1.0, root=True),
+2 -2
View File
@@ -130,8 +130,8 @@ def main():
cfg, pair, body, host = r.host_geometry(a.source, h, "MRT")
context = stack.enter_context(CudaContext(0))
backend = stack.enter_context(FixedPatchStepper(
cfg, r.BOUNDS, context=context, coarse_boundary="channel", base_block=r.BASE_BLOCK,
fine_block=r.FINE_BLOCK, fine_objects=(body,), observe_raw_exchange=True,
cfg, context=context, coarse_boundary="channel", refinements=[r.BOUNDS],
level_blocks=[r.BASE_BLOCK, r.FINE_BLOCK], level_objects=[(), (body,)], observe_raw_exchange=True,
observe_window_exchange=True))
masks = [channel_masks(pair.coarse_shape)[0] & ~pair.covered,
(pair.fine_kind == ACTIVE) & ((host.flags.reshape(pair.fine_shape) & SOLID) == 0)]