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6
Commits
| Author | SHA1 | Date | |
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104f74632f | ||
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452eaf32de | ||
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3716b16555 | ||
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ce393fa468 | ||
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2ccd7d576e | ||
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2469af70d0 |
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@@ -109,7 +109,7 @@ class ExchangeWindowGPU(unittest.TestCase):
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from test_raw_exchange_gpu import BOUNDS as RB, CFG, circle as rc, jet, state
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from CelerisLab.cuda.context import CudaContext
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with CudaContext(0) as ctx:
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kw = dict(context=ctx, refinements=[RB], level_blocks=[None, (16, 20)],
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kw = dict(context=ctx, refinements=[RB], level_blocks=[(12, 8), (16, 20)],
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level_objects=[(), (rc(),)], level_jets=[(), (jet(),)],
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observe_raw_exchange=True)
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with FixedPatchStepper(CFG, observe_window_exchange=True, **kw) as windowed, \
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@@ -279,6 +279,61 @@ def test_fine_surface_four_hops(speed):
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np.testing.assert_array_equal(got, wanted)
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def run_blocked_patch(speed):
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"""All-blocked run (whole-level tiles) of the same case; fine ROI after each fine hop."""
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cfg = LBMConfig(nx=24, ny=24, viscosity=.05, velocity=0, rho=1)
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source = object_spec(speed)
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with CudaContext(0) as context:
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with implementation.FixedPatchStepper(cfg, context=context, refinements=[BOUNDS],
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level_blocks=[(24, 24), (40, 40)],
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level_objects=[(), (source,)],
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observe_raw_exchange=True) as backend:
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c, f = backend._levels
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flags = backend.fine_boundary.flags.reshape(40, 40)
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active = np.zeros((40, 40), bool)
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active[4:-4, 4:-4] = True
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active &= ((flags & FLUID) != 0) & ((flags & SOLID) == 0)
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yy, xx = np.mgrid[:40, :40]
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roi = active & ((xx-20)**2+(yy-20)**2 <= 9**2)
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backend.initialize(rest((24, 24)), rest((40, 40)))
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traces, original = [], f.kernel
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def fine(*args, **kwargs):
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original(*args, **kwargs)
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backend._stream.synchronize()
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advanced = f.layout.to_dense(read(args[1], f.layout.blocked_shape))
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assert np.isfinite(advanced[:, active]).all()
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assert np.isnan(advanced[:, (flags & SOLID) != 0]).all()
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traces.append(advanced[:, roi].copy())
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with patch.object(f, "kernel", fine):
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backend.step(2)
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assert len(traces) == 4 and backend.step_count == 2
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mass = backend.read_raw_exchange(0)["total"]["mass_into_fluid"]
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return traces, roi, backend.download(), float(mass)
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@pytest.mark.parametrize("speed", [0., .002, -.002])
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def test_fine_surface_blocked_matches_uniform_four_hops(speed):
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"""Blocked storage: fine ROI after each of four hops against the uniform 48^2 solver
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(same tolerances as the dense test); blowing/suction drives mass with its sign;
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zero actuation equals the passive circle bit for bit."""
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actual, roi, final, mass = run_blocked_patch(speed)
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reference = uniform_reference(speed, roi)
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for got, wanted in zip(actual, reference):
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np.testing.assert_allclose(got, wanted, atol=3e-6, rtol=0)
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np.testing.assert_allclose(MOMENTS@got.astype(float), MOMENTS@wanted.astype(float),
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atol=2e-5, rtol=0)
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if speed:
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assert speed*mass > 0
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else:
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passive, passive_roi, passive_final, _ = run_blocked_patch(None)
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np.testing.assert_array_equal(passive_roi, roi)
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for got, wanted in zip(actual+list(final), passive+list(passive_final)):
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np.testing.assert_array_equal(got, wanted)
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print(f"blocked speed={speed} four hops vs uniform PASS mass_into_fluid={mass:+.9g}", flush=True)
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@pytest.mark.parametrize("missing", ["surface_velocity_gpu", "link_exchange_gpu"])
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def test_missing_surface_device_buffer_rejects_before_launch(missing):
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backend = implementation.FixedPatchStepper.__new__(implementation.FixedPatchStepper)
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@@ -328,6 +383,7 @@ def test_cross_interface_donor_rejects_before_cuda():
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with patch.object(cuda, "mem_alloc") as allocate:
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with pytest.raises(ValueError, match="donor crosses"):
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implementation.FixedPatchStepper(cfg, context=context, refinements=[BOUNDS],
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level_blocks=[(24, 24), (40, 40)],
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level_objects=[(), (source,)])
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context.activate.assert_not_called()
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allocate.assert_not_called()
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@@ -92,8 +92,9 @@ def census(run, index, buffer):
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def fine(block):
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"""Two-level circle+jet construction on BOUNDS; block None keeps the dense fine level."""
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return dict(refinements=[BOUNDS], level_blocks=[None, block],
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"""Two-level circle+jet construction on BOUNDS, all-blocked with a (12, 8) root tile;
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block None is the dense route (dense reference test only, retired with the dense route)."""
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return dict(refinements=[BOUNDS], level_blocks=[None if block is None else (12, 8), block],
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level_objects=[(), (circle(),)], level_jets=[(), (jet(),)])
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class RawExchangeGPU(unittest.TestCase):
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@@ -23,13 +23,16 @@ Route capabilities (rejections checked before CUDA by test_route_capability_matr
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channel root rejected rejected yes
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several L1 rectangles rejected rejected yes
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depth >= 3 with a dense level rejected rejected yes
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MRT, periodic root, circle/actuation/Jet yes yes yes (parity gate)
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two fine bodies (Jet + passive, two actuated) yes yes yes (parity gate)
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MRT with slot/reservoir root rejected on every route (on_site_velocity is SRT-only)
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Slot/reservoir walls are compile-time WALL_* macros on a dense root and the
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d_block_wall constant on a blocked root: BC-encoding parity, bit-identical by
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this gate. Dense fine bodies use CurvedLinkSoA + CurvedBoundaryKernel
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(n_objects > 0), blocked ones BlockCurvedBoundary; same links and physics,
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compared through the population rows. Parked here: MRT (covered by
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test_refinement_mrt_gpu::test_dense_versus_blocked_mrt_two_level), shifted and
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depth >= 3 (no dense route to compare), several bodies (later slice).
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compared through the population rows. MRT body-free is also covered by
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test_refinement_mrt_gpu::test_dense_versus_blocked_mrt_two_level. Parked:
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shifted and depth >= 3 (no dense route to compare).
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"""
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from contextlib import ExitStack, contextmanager, nullcontext
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from dataclasses import replace
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@@ -354,6 +357,25 @@ class BlockedBaseGPU(unittest.TestCase):
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ROUTES = (("D/D", [None, None]), ("D/B", [None, FINE_BLOCK]), ("B/B", [(12, 8), FINE_BLOCK]))
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# Two-body rows: patch (4, 4, 28, 20) gives a 40 x 56 fine window, tiled (8, 8).
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WIDE_BOUNDS = (4, 4, 28, 20)
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WIDE_ROUTES = (("D/D", [None, None]), ("D/B", [None, (8, 8)]), ("B/B", [(12, 8), (8, 8)]))
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LEFT, RIGHT, RADIUS = (12.0, 12.0), (20.0, 12.0), 2.15
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def body(ident, center, spec=None):
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from CelerisLab.body.geometry.circle import CircleGeometry
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from CelerisLab.body.objects import SimObject
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return SimObject(ident, geometry=CircleGeometry(*center, RADIUS), center=center, radius=RADIUS,
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surface_actuation=spec)
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TWO_BODY_CASES = (
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("jet + passive", lambda: [body(0, LEFT), body(1, RIGHT)],
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lambda: [actuation(SPEED).as_jet(LEFT, RADIUS)], -SPEED),
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("actuated +/-", lambda: [body(0, LEFT, actuation(SPEED)), body(1, RIGHT, actuation(-SPEED))],
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lambda: [], None),
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)
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def same_summary(a, b):
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@@ -414,17 +436,18 @@ def replace_value(tree, path, value=None):
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class DenseBlockedRouteParity(unittest.TestCase):
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"""D/D vs D/B vs B/B, unshifted SRT, one circle or one velocity Jet; see module docstring."""
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def run_routes(self, mode, objects=(), jets=(), switch=None):
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def run_routes(self, mode, objects=(), jets=(), switch=None, cfg=None, bounds=BOUNDS, routes=ROUTES):
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from CelerisLab.cuda.context import CudaContext
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cfg = config(mode)
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p = FixedPatch2D.from_config(cfg, BOUNDS)
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cfg = cfg or config(mode)
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p = FixedPatch2D.from_config(cfg, bounds)
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arrays = state(NY, NX, 1), state(*p.fine_shape, 2)
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bodies = sorted({obj.obj_id for obj in objects})
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results = {}
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with CudaContext(0) as context:
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for name, blocks in ROUTES:
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for name, blocks in routes:
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observe = bool(objects) and blocks[1] is not None
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snapshots, ledgers = [], []
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with FixedPatchStepper(cfg, context=context, coarse_boundary=mode, refinements=[BOUNDS],
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with FixedPatchStepper(cfg, context=context, coarse_boundary=mode, refinements=[bounds],
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level_blocks=blocks, level_objects=[(), tuple(objects)],
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level_jets=[(), tuple(jets)],
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observe_raw_exchange=observe) as backend:
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@@ -435,7 +458,8 @@ class DenseBlockedRouteParity(unittest.TestCase):
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backend.step(step - backend.step_count)
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snapshots.append(backend.download() + raw(backend))
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if observe and step:
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ledgers.append(tuple(backend.read_raw_exchange(0, window=window)
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ledgers.append(tuple(backend.read_raw_exchange(body, window=window)
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for body in bodies
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for window in ("last_base_step", "last_substep")))
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backend.initialize(*arrays)
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snapshots.append(backend.download() + raw(backend))
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@@ -475,6 +499,24 @@ class DenseBlockedRouteParity(unittest.TestCase):
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self.check(f"{mode} jet switch",
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self.run_routes(mode, objects=[circle()], jets=[jet()], switch=-SPEED))
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def test_mrt_bodies(self):
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"""MRT, periodic root (on_site_velocity slot/reservoir is SRT-only on every route)."""
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cfg = replace(config("periodic"), collision="MRT")
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for label, objects, jets, switch in (("circle", [circle()], (), None),
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("actuated +", [circle(actuation(SPEED))], (), None),
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("actuated -", [circle(actuation(-SPEED))], (), None),
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("jet switch", [circle()], [jet()], -SPEED)):
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self.check(f"MRT periodic {label}",
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self.run_routes("periodic", objects, jets, switch, cfg=cfg))
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def test_two_bodies(self):
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"""Two circles on a wider patch (same tiles on every route): Jet + passive, two actuated."""
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for mode in ("periodic", "slot_reservoir"):
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for label, objects, jets, switch in TWO_BODY_CASES:
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self.check(f"{mode} two bodies {label}",
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self.run_routes(mode, objects(), jets(), switch, bounds=WIDE_BOUNDS,
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routes=WIDE_ROUTES))
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if __name__ == "__main__":
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unittest.main()
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@@ -88,15 +88,13 @@ def seam_cells(layout, mapped):
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def raw(backend):
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"""Unmasked device arrays; blocked fine storage unpacked from owner cores."""
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coarse, fine = backend._levels
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out = [np.empty(coarse.shape, np.float32)]
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out.append(np.empty(fine.shape if backend.fine_layout is None
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else backend.fine_layout.blocked_shape, np.float32))
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cuda.memcpy_dtoh(out[0], coarse.current)
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cuda.memcpy_dtoh(out[1], fine.current)
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if backend.fine_layout is not None:
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out[1] = backend.fine_layout.to_dense(out[1])
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"""Unmasked device arrays of every level; blocked storage unpacked from owner cores."""
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out = []
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for level in backend._levels:
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array = np.empty(level.shape if level.layout is None else level.layout.blocked_shape,
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np.float32)
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cuda.memcpy_dtoh(array, level.current)
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out.append(array if level.layout is None else level.layout.to_dense(array))
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return out
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@@ -17,6 +17,7 @@ import pycuda.driver as cuda
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import CelerisLab
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from CelerisLab.lbm import refinement_stepper as implementation
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from CelerisLab.lbm.blocks import BlockLayout2D
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from test_refinement_gpu import (ROOT, POP_ATOL, MOMENT_ATOL, ref, postcollision,
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totals, LBMConfig, CudaContext, compiler,
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PeriodicPatchStepper)
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@@ -83,6 +84,21 @@ def scalar_interval(coarse, fine, bounds, slot=None):
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return result, current
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def whole_tiles(cfg, bounds):
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"""One whole-level tile per level: (ny, nx) at the root, the fine window below."""
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return [(cfg.ny, cfg.nx), implementation.FixedPatch2D.from_config(cfg, bounds).fine_shape]
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def owner_arrays(backend):
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"""Raw owner storage of every level as dense (9, ny, nx), before public masking."""
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arrays = []
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for level in backend._levels:
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blocked = np.empty(level.layout.blocked_shape, np.float32)
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cuda.memcpy_dtoh(blocked, level.current)
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arrays.append(level.layout.to_dense(blocked))
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return arrays
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class FaultGuardsCPU(unittest.TestCase):
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def test_boundary_mode_and_margin_contract(self):
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cfg = LBMConfig(nx=32, ny=24, viscosity=.1, velocity=0, wall_normal_velocity=.001,
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@@ -95,7 +111,7 @@ class FaultGuardsCPU(unittest.TestCase):
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with self.subTest(mode=mode, bounds=bounds):
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with self.assertRaises(ValueError):
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implementation.FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
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refinements=[bounds])
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refinements=[bounds], level_blocks=[(1, 1)] * 2)
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context.activate.assert_not_called()
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# Both exact channel limits and the original periodic two-cell margin
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# must reach context activation, with no allocation or device required.
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@@ -104,18 +120,19 @@ class FaultGuardsCPU(unittest.TestCase):
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with self.subTest(mode=mode, bounds=bounds):
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with self.assertRaisesRegex(RuntimeError, "validated before CUDA"):
|
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implementation.FixedPatchStepper(cfg, context=context, coarse_boundary=mode,
|
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refinements=[bounds])
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refinements=[bounds], level_blocks=[(1, 1)] * 2)
|
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|
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def fake_backend(self):
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backend = PeriodicPatchStepper.__new__(PeriodicPatchStepper)
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backend._layouts = [None, None] # dense storage on both levels
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layout = BlockLayout2D.build(1, 1, 1, 1, periodic=(False, False))
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backend._layouts = [layout, layout] # blocked storage on both levels
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backend._ddf_shifting = False # unshifted on every level, as _check_storage expects
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backend._level_cfgs = [LBMConfig(nx=16, ny=16, viscosity=.1)] * 2 # ddf_shifting off
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backend.ctx = Mock(activate=nullcontext)
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backend._lock = RLock()
|
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backend._status = "ready"
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backend._stream = Mock()
|
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backend._levels = [Mock(shape=(9, 1, 1), layout=None), Mock(shape=(9, 1, 1), layout=None)]
|
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backend._levels = [Mock(shape=(9, 1, 1), layout=layout), Mock(shape=(9, 1, 1), layout=layout)]
|
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backend._allocations = [Mock(), Mock()]
|
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return backend
|
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@@ -158,7 +175,8 @@ class FaultGuardsCPU(unittest.TestCase):
|
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context = Mock(activate=nullcontext, sm_arch="sm_70")
|
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with patch.object(implementation, "HALO", 2):
|
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with self.assertRaisesRegex(RuntimeError, "four-cell"):
|
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PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)])
|
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PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)],
|
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level_blocks=[(16, 16), (24, 24)])
|
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p = implementation.FixedPatch2D.from_config(cfg, (4, 4, 12, 12))
|
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from CelerisLab.lbm import hierarchy
|
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bad = patch.object(implementation.FixedPatch2D, "from_config",
|
||||
@@ -169,10 +187,12 @@ class FaultGuardsCPU(unittest.TestCase):
|
||||
with patch.object(cuda, "Stream"), patch.object(cuda, "mem_get_info", return_value=(1 << 40, 1 << 40)), bad, patch.object(cuda, "mem_alloc") as alloc, \
|
||||
patch.object(cuda, "memcpy_htod") as upload:
|
||||
with self.assertRaisesRegex(RuntimeError, "config chain is inconsistent"):
|
||||
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds])
|
||||
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds],
|
||||
level_blocks=[(16, 16), (24, 24)])
|
||||
with patch.object(hierarchy, "_check_chain"), \
|
||||
self.assertRaisesRegex(RuntimeError, "omega/tau"):
|
||||
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds])
|
||||
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds],
|
||||
level_blocks=[(16, 16), (24, 24)])
|
||||
alloc.assert_not_called()
|
||||
upload.assert_not_called()
|
||||
module = Mock()
|
||||
@@ -182,7 +202,8 @@ 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, context=context, refinements=[p.bounds])
|
||||
PeriodicPatchStepper(cfg, context=context, refinements=[p.bounds],
|
||||
level_blocks=[(16, 16), (24, 24)])
|
||||
upload.assert_not_called()
|
||||
|
||||
|
||||
@@ -250,23 +271,27 @@ class NormalBuildGPU(unittest.TestCase):
|
||||
parts = line.split()
|
||||
if len(parts) == 3 and parts[0] == "#define":
|
||||
definitions[parts[1]] = parts[2]
|
||||
generated.append((metadata["config"], definitions))
|
||||
generated.append((metadata["config"], definitions, metadata))
|
||||
return build
|
||||
|
||||
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, context=context, refinements=[bounds],
|
||||
coarse_boundary="slot_reservoir")
|
||||
coarse_boundary="slot_reservoir",
|
||||
level_blocks=whole_tiles(cfg, bounds))
|
||||
with backend:
|
||||
self.assertEqual(len(generated), 2)
|
||||
fine_config, fine_defines = generated[1]
|
||||
self.assertEqual((fine_config["nx"], fine_config["ny"]), (fx, fy))
|
||||
fine_config, fine_defines, _ = generated[1]
|
||||
# Blocked kernels see one tile window including the 1-cell halo.
|
||||
self.assertEqual((fine_config["nx"], fine_config["ny"]), (fx+2, fy+2))
|
||||
for name in ("Y_WALL_BC", "TOP_WALL_BC", "WALL_SLOT_WIDTH",
|
||||
"WALL_NORMAL_VELOCITY", "TOP_WALL_NORMAL_VELOCITY"):
|
||||
self.assertEqual(float(fine_defines[name].removesuffix("f")), 0, name)
|
||||
self.assertEqual(int(generated[0][1]["Y_WALL_BC"]), 2)
|
||||
self.assertEqual(int(generated[0][1]["TOP_WALL_BC"]), 1)
|
||||
# The root's physical slot/reservoir walls come from BLOCK_ROOT_BC=1
|
||||
# (module constant d_block_wall); the fine level has none.
|
||||
root_meta, fine_meta = generated[0][2], generated[1][2] # read before cleanup
|
||||
self.assertEqual((root_meta["block_root_bc"], fine_meta["block_root_bc"]), (1, 0))
|
||||
# Independently derive all target links, including the eight
|
||||
# whose coarse sources are uncovered, from physical midpoints.
|
||||
targets, corners = set(), set()
|
||||
@@ -286,9 +311,7 @@ class NormalBuildGPU(unittest.TestCase):
|
||||
expected = scalar_interval(*expected, bounds, slot=(amplitude, width))
|
||||
backend.step()
|
||||
self.assertEqual(backend.step_count, step)
|
||||
raw = [np.empty(a.shape, np.float32) for a in initial]
|
||||
for level, array in zip(backend._levels, raw):
|
||||
cuda.memcpy_dtoh(array, level.current)
|
||||
raw = owner_arrays(backend)
|
||||
# Read raw storage before masking: active NaNs cannot be
|
||||
# hidden by the public download's non-leaf cleanup.
|
||||
self.assertTrue(np.isfinite(raw[0][:, coarse_leaf]).all())
|
||||
@@ -327,7 +350,7 @@ class NormalBuildGPU(unittest.TestCase):
|
||||
max_pop = max_drift = max_moment = 0.0
|
||||
with CudaContext(0) as context, PeriodicPatchStepper(
|
||||
LBMConfig(nx=16, ny=16, viscosity=.1), context=context,
|
||||
refinements=[(4, 4, 12, 12)]) as backend:
|
||||
refinements=[(4, 4, 12, 12)], level_blocks=[(16, 16), (24, 24)]) as backend:
|
||||
backend.initialize(*postcollision(state, spec, maps))
|
||||
before = totals(backend.download(), maps)
|
||||
for step in range(1, 9):
|
||||
@@ -358,17 +381,17 @@ 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, context=context, refinements=[bounds]) as backend:
|
||||
with CudaContext(0) as context, PeriodicPatchStepper(cfg, context=context, refinements=[bounds],
|
||||
level_blocks=[(13, 17), (14, 16)]) 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
|
||||
(p.ghost_fine, p.ghost_coarse, p.coalesce_coarse, p.coalesce_fine))
|
||||
allocated = 2 * 4 * sum(int(np.prod(level.layout.blocked_shape)) for level in backend._levels) \
|
||||
+ sum(a.nbytes for a in (p.ghost_fine, p.ghost_coarse, p.coalesce_coarse, p.coalesce_fine))
|
||||
self.assertLess(allocated, 128*1024)
|
||||
backend.initialize(*initial)
|
||||
backend.step()
|
||||
coarse, fine = backend.download()
|
||||
raw_fine = np.empty((9, 14, 16), np.float32)
|
||||
cuda.memcpy_dtoh(raw_fine, backend._levels[1].current)
|
||||
raw_fine = owner_arrays(backend)[1]
|
||||
max_error = 0.0
|
||||
for got, want in zip((coarse, raw_fine), expected):
|
||||
np.testing.assert_array_equal(np.isnan(got), np.isnan(want))
|
||||
|
||||
@@ -52,6 +52,17 @@ def totals(arrays, maps):
|
||||
return np.array([populations.sum(), populations @ ref.CX, populations @ ref.CY])
|
||||
|
||||
|
||||
def level_storage(level):
|
||||
"""Raw device storage of one level as dense (9, ny, nx), dense or blocked."""
|
||||
if level.layout is None:
|
||||
raw = np.empty(level.shape, np.float32)
|
||||
cuda.memcpy_dtoh(raw, level.current)
|
||||
return raw
|
||||
blocked = np.empty(level.layout.blocked_shape, np.float32)
|
||||
cuda.memcpy_dtoh(blocked, level.current)
|
||||
return level.layout.to_dense(blocked)
|
||||
|
||||
|
||||
def global_array(module, name, shape):
|
||||
out = np.empty(shape, dtype=np.uint32)
|
||||
ptr, size = module.get_global(name)
|
||||
@@ -82,7 +93,7 @@ class CoupledGPU(unittest.TestCase):
|
||||
expected = postcollision(next_state, spec, maps)
|
||||
arrivals = (next_state.coarse_f, next_state.fine_f)
|
||||
|
||||
cases = (("dense_unshifted", False, {}),
|
||||
cases = (("blocked_unshifted", False, dict(level_blocks=[(16, 16), (24, 24)])),
|
||||
("blocked_shifted", True,
|
||||
dict(level_blocks=[(4, 4), (6, 6)])))
|
||||
with CudaContext(0) as context:
|
||||
@@ -148,7 +159,8 @@ class CoupledGPU(unittest.TestCase):
|
||||
maps = ref.build_maps(spec)
|
||||
with CudaContext(0) as context:
|
||||
with PeriodicPatchStepper(LBMConfig(nx=16, ny=16, viscosity=.1),
|
||||
context=context, refinements=[(4, 4, 12, 12)]) as backend:
|
||||
context=context, refinements=[(4, 4, 12, 12)],
|
||||
level_blocks=[(16, 16), (24, 24)]) as backend:
|
||||
backend.initialize(*postcollision(ref.make_state(spec), spec, maps))
|
||||
coarse, fine = backend._levels
|
||||
|
||||
@@ -164,12 +176,94 @@ class CoupledGPU(unittest.TestCase):
|
||||
for operation in (backend.download, backend.step):
|
||||
with self.assertRaisesRegex(RuntimeError, "failed"):
|
||||
operation()
|
||||
raw = np.empty(fine.shape, np.float32)
|
||||
cuda.memcpy_dtoh(raw, fine.current)
|
||||
raw = level_storage(fine)
|
||||
self.assertTrue(np.isfinite(raw.ravel()[backend.patch.coalesce_fine]).all())
|
||||
self.assertFalse(context.is_closed)
|
||||
print("partial failure: two fine hops completed, no coarse step published; cleanup PASS", flush=True)
|
||||
|
||||
def eight_steps(self, backend, spec, maps, audit):
|
||||
"""Rest and seeded nonequilibrium, 8 steps against the scalar reference.
|
||||
|
||||
audit=True also checks the dense CELERIS_REFINEMENT_AUDIT ownership counters.
|
||||
"""
|
||||
p = backend.patch
|
||||
for case in ("rest", "nonequilibrium_seed1"):
|
||||
with self.subTest(case=case):
|
||||
state = ref.make_state(spec, velocity=(0, 0) if case == "rest" else (.03, -.02))
|
||||
if case != "rest":
|
||||
rng = np.random.default_rng(1)
|
||||
state = ref.State(*(a * (1 + 1e-3 * rng.standard_normal(a.shape))
|
||||
for a in (state.coarse_f, state.fine_f)))
|
||||
initial = postcollision(state, spec, maps)
|
||||
backend.initialize(*initial)
|
||||
if audit: # dense audit build only
|
||||
for level in backend._levels:
|
||||
for name in ("collision_counts", "explosion_counts", "incoming_counts"):
|
||||
ptr, size = level.module.get_global(name)
|
||||
cuda.memset_d8(ptr, 0, size)
|
||||
before = totals(backend.download(), maps)
|
||||
max_error = max_drift = max_moment_error = max_corner = 0.0
|
||||
for step in range(1, 9):
|
||||
state, diagnostic = ref.advance_coarse_once(spec, maps, state)
|
||||
backend.step()
|
||||
actual = backend.download()
|
||||
expected = postcollision(state, spec, maps)
|
||||
self.assertEqual(backend.step_count, step)
|
||||
p.check_synchronization(step, state.tick, phase="postcollision_g")
|
||||
for got, want in zip(actual, expected):
|
||||
np.testing.assert_array_equal(np.isnan(got), np.isnan(want))
|
||||
error = float(np.nanmax(np.abs(got - want)))
|
||||
self.assertLessEqual(error, POP_ATOL)
|
||||
max_error = max(max_error, error)
|
||||
drift = float(np.max(np.abs(totals(actual, maps) - before)))
|
||||
moment_error = float(np.max(np.abs(totals(actual, maps) - totals(expected, maps))))
|
||||
self.assertLessEqual(drift, MOMENT_ATOL)
|
||||
self.assertLessEqual(moment_error, MOMENT_ATOL)
|
||||
max_drift, max_moment_error = max(max_drift, drift), max(max_moment_error, moment_error)
|
||||
c, f = backend._levels
|
||||
if audit:
|
||||
np.testing.assert_array_equal(global_array(c.module, "collision_counts", (16, 16)),
|
||||
step * maps.coarse_active)
|
||||
np.testing.assert_array_equal(global_array(f.module, "collision_counts", (24, 24)),
|
||||
2 * step * maps.fine_active)
|
||||
np.testing.assert_array_equal(global_array(f.module, "explosion_counts", (24, 24)),
|
||||
step * ~maps.fine_active)
|
||||
owners = np.zeros((9, 16, 16), np.uint32)
|
||||
owners.ravel()[p.coalesce_coarse] = step
|
||||
np.testing.assert_array_equal(global_array(c.module, "incoming_counts", owners.shape), owners)
|
||||
raw = level_storage(f)
|
||||
np.testing.assert_array_equal(np.isfinite(raw), diagnostic["hop2_valid"])
|
||||
self.assertTrue(np.isfinite(raw.ravel()[p.coalesce_fine]).all())
|
||||
self.assertEqual(len(diagnostic["corner_packets"]), 8)
|
||||
for packet in diagnostic["corner_packets"].values():
|
||||
sx, sy = packet["source_coarse_xy"]
|
||||
self.assertTrue(maps.coarse_active[sy, sx])
|
||||
values = [raw[packet["direction"], y, x]
|
||||
for y, x in packet["children_fine_yx"]]
|
||||
error = float(np.max(np.abs(np.array(values) - packet["packets"])))
|
||||
self.assertLessEqual(error, POP_ATOL)
|
||||
max_corner = max(max_corner, error)
|
||||
print(f"{case}: steps=8 max_population={max_error:.9g} "
|
||||
f"max_leaf_drift={max_drift:.9g} max_leaf_error={max_moment_error:.9g} "
|
||||
f"max_corner_packet={max_corner:.9g}; ownership/counts PASS", flush=True)
|
||||
|
||||
def test_bounded_equivalence_blocked(self):
|
||||
"""The same eight-step reference and launch-failure checks on whole-level tiles."""
|
||||
spec = ref.make_spec(collision="srt")
|
||||
maps = ref.build_maps(spec)
|
||||
cfg = LBMConfig(nx=16, ny=16, viscosity=.1)
|
||||
with CudaContext(0) as context:
|
||||
with PeriodicPatchStepper(cfg, context=context, refinements=[(4, 4, 12, 12)],
|
||||
level_blocks=[(16, 16), (24, 24)]) as backend:
|
||||
self.eight_steps(backend, spec, maps, audit=False)
|
||||
with patch.object(backend._pairs[0], "explode", side_effect=RuntimeError("injected launch failure")):
|
||||
with self.assertRaisesRegex(RuntimeError, "injected"):
|
||||
backend.step()
|
||||
for operation in (backend.download, backend.step):
|
||||
with self.assertRaisesRegex(RuntimeError, "failed"):
|
||||
operation()
|
||||
self.assertFalse(context.is_closed)
|
||||
|
||||
def test_bounded_equivalence_and_ownership(self):
|
||||
self.assertEqual(Path(CelerisLab.__file__).resolve(), ROOT / "src/CelerisLab/__init__.py")
|
||||
self.assertEqual(Path(compiler._KERNEL_DIR).resolve(), ROOT / "src/CelerisLab/lbm/kernels")
|
||||
@@ -198,64 +292,7 @@ class CoupledGPU(unittest.TestCase):
|
||||
for level in backend._levels)
|
||||
self.assertLess(device_bytes + audit_bytes, 128 * 1024)
|
||||
print(f"device_arrays={device_bytes} audit_arrays={audit_bytes} bytes", flush=True)
|
||||
for case in ("rest", "nonequilibrium_seed1"):
|
||||
with self.subTest(case=case):
|
||||
state = ref.make_state(spec, velocity=(0, 0) if case == "rest" else (.03, -.02))
|
||||
if case != "rest":
|
||||
rng = np.random.default_rng(1)
|
||||
state = ref.State(*(a * (1 + 1e-3 * rng.standard_normal(a.shape))
|
||||
for a in (state.coarse_f, state.fine_f)))
|
||||
initial = postcollision(state, spec, maps)
|
||||
backend.initialize(*initial)
|
||||
for level in backend._levels:
|
||||
for name in ("collision_counts", "explosion_counts", "incoming_counts"):
|
||||
ptr, size = level.module.get_global(name)
|
||||
cuda.memset_d8(ptr, 0, size)
|
||||
before = totals(backend.download(), maps)
|
||||
max_error = max_drift = max_moment_error = max_corner = 0.0
|
||||
for step in range(1, 9):
|
||||
state, diagnostic = ref.advance_coarse_once(spec, maps, state)
|
||||
backend.step()
|
||||
actual = backend.download()
|
||||
expected = postcollision(state, spec, maps)
|
||||
self.assertEqual(backend.step_count, step)
|
||||
p.check_synchronization(step, state.tick, phase="postcollision_g")
|
||||
for got, want in zip(actual, expected):
|
||||
np.testing.assert_array_equal(np.isnan(got), np.isnan(want))
|
||||
error = float(np.nanmax(np.abs(got - want)))
|
||||
self.assertLessEqual(error, POP_ATOL)
|
||||
max_error = max(max_error, error)
|
||||
drift = float(np.max(np.abs(totals(actual, maps) - before)))
|
||||
moment_error = float(np.max(np.abs(totals(actual, maps) - totals(expected, maps))))
|
||||
self.assertLessEqual(drift, MOMENT_ATOL)
|
||||
self.assertLessEqual(moment_error, MOMENT_ATOL)
|
||||
max_drift, max_moment_error = max(max_drift, drift), max(max_moment_error, moment_error)
|
||||
c, f = backend._levels
|
||||
np.testing.assert_array_equal(global_array(c.module, "collision_counts", (16, 16)),
|
||||
step * maps.coarse_active)
|
||||
np.testing.assert_array_equal(global_array(f.module, "collision_counts", (24, 24)),
|
||||
2 * step * maps.fine_active)
|
||||
np.testing.assert_array_equal(global_array(f.module, "explosion_counts", (24, 24)),
|
||||
step * ~maps.fine_active)
|
||||
owners = np.zeros((9, 16, 16), np.uint32)
|
||||
owners.ravel()[p.coalesce_coarse] = step
|
||||
np.testing.assert_array_equal(global_array(c.module, "incoming_counts", owners.shape), owners)
|
||||
raw = np.empty(f.shape, np.float32)
|
||||
cuda.memcpy_dtoh(raw, f.current)
|
||||
np.testing.assert_array_equal(np.isfinite(raw), diagnostic["hop2_valid"])
|
||||
self.assertTrue(np.isfinite(raw.ravel()[p.coalesce_fine]).all())
|
||||
self.assertEqual(len(diagnostic["corner_packets"]), 8)
|
||||
for packet in diagnostic["corner_packets"].values():
|
||||
sx, sy = packet["source_coarse_xy"]
|
||||
self.assertTrue(maps.coarse_active[sy, sx])
|
||||
values = [raw[packet["direction"], y, x]
|
||||
for y, x in packet["children_fine_yx"]]
|
||||
error = float(np.max(np.abs(np.array(values) - packet["packets"])))
|
||||
self.assertLessEqual(error, POP_ATOL)
|
||||
max_corner = max(max_corner, error)
|
||||
print(f"{case}: steps=8 max_population={max_error:.9g} "
|
||||
f"max_leaf_drift={max_drift:.9g} max_leaf_error={max_moment_error:.9g} "
|
||||
f"max_corner_packet={max_corner:.9g}; ownership/counts PASS", flush=True)
|
||||
self.eight_steps(backend, spec, maps, audit=True)
|
||||
|
||||
# Fail before any additional time step; no stale synchronized export.
|
||||
with patch.object(backend._pairs[0], "explode", side_effect=RuntimeError("injected launch failure")):
|
||||
|
||||
@@ -3,11 +3,13 @@
|
||||
Jets use the same coarse cell-edge frame as fine_objects. The equivalent jet
|
||||
of Astra's actuated fixture is SurfaceActuation(0.7, 0.85, U).as_jet((16, 12),
|
||||
2.15). Frozen GPU gates (8 coarse steps, both coarse boundary modes):
|
||||
G1 jet run: dense vs 1x1/2x2/4x2 fine blocks bit-identical (values + NaN masks);
|
||||
G2 jet vs legacy actuation (dense): max |dG| over finite fine ACTIVE fluid
|
||||
G1 jet run: 1x1/2x2/4x2 fine blocks (blocked (12, 8) root) bit-identical to the
|
||||
FINE_BLOCKS[0] reference (values + NaN masks); dense leg kept until dense retirement;
|
||||
G2 jet vs legacy actuation (blocked reference): max |dG| over finite fine ACTIVE fluid
|
||||
populations <= 1e-6 (velocity rows differ only by FP32 rounding; reported);
|
||||
G3 amplitude change after 4 steps (+U -> -U), 4 more steps: dense vs blocked
|
||||
bit-identical and the run differs from the unchanged run.
|
||||
G3 amplitude change after 4 steps (+U -> -U), 4 more steps: blocked layouts
|
||||
bit-identical to the FINE_BLOCKS[0] reference (dense leg until retirement) and the
|
||||
run differs from the unchanged run.
|
||||
"""
|
||||
from contextlib import nullcontext
|
||||
import unittest
|
||||
@@ -26,6 +28,11 @@ from test_refinement_blocked_fine import (BOUNDS, FINE_BLOCKS, NX, NY, STEPS, ac
|
||||
SPEED = .002
|
||||
|
||||
|
||||
def root_and(fine_block):
|
||||
"""All-blocked levels with a (12, 8) root tile; fine_block None is the dense route."""
|
||||
return [None if fine_block is None else (12, 8), fine_block]
|
||||
|
||||
|
||||
def jet(speed=SPEED):
|
||||
return actuation(speed).as_jet((16.0, 12.0), 2.15)
|
||||
|
||||
@@ -42,7 +49,7 @@ def mocked(objects, jets, fine_block):
|
||||
patch.object(cuda, "mem_alloc", side_effect=lambda size: Mock()), \
|
||||
patch.object(cuda, "memcpy_htod", htod):
|
||||
backend = FixedPatchStepper(config("periodic"), context=context, refinements=[BOUNDS],
|
||||
level_blocks=[None, fine_block], level_objects=[(), tuple(objects)],
|
||||
level_blocks=root_and(fine_block), level_objects=[(), tuple(objects)],
|
||||
level_jets=[(), tuple(jets)])
|
||||
return backend, htod
|
||||
|
||||
@@ -161,7 +168,7 @@ def run(mode, fine_block, *, objects, jets, switch=None):
|
||||
patch_ = FixedPatch2D.from_config(cfg, BOUNDS)
|
||||
with CudaContext(0) as context, FixedPatchStepper(
|
||||
cfg, context=context, coarse_boundary=mode, refinements=[BOUNDS],
|
||||
level_blocks=[None, fine_block], level_objects=[(), tuple(objects)],
|
||||
level_blocks=root_and(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:
|
||||
@@ -179,29 +186,32 @@ class JetStepperGPU(unittest.TestCase):
|
||||
patch_, boundary = fine_circle(mode)
|
||||
fluid = (patch_.fine_kind == ACTIVE) & (
|
||||
(boundary.flags.reshape(patch_.fine_shape) & SOLID) == 0)
|
||||
dense = run(mode, None, objects=[circle()], jets=[jet()])
|
||||
self.assertTrue(np.isfinite(dense[1][1][:, fluid]).all(), mode)
|
||||
for fine_block in FINE_BLOCKS:
|
||||
reference = run(mode, FINE_BLOCKS[0], objects=[circle()], jets=[jet()])
|
||||
self.assertTrue(np.isfinite(reference[1][1][:, fluid]).all(), mode)
|
||||
for fine_block in FINE_BLOCKS[1:]:
|
||||
public, raw_arrays = run(mode, fine_block, objects=[circle()], jets=[jet()])
|
||||
for a, b in zip(public + tuple(raw_arrays), dense[0] + tuple(dense[1])):
|
||||
for a, b in zip(public + tuple(raw_arrays), reference[0] + tuple(reference[1])):
|
||||
np.testing.assert_array_equal(a, b, err_msg=f"G1 {mode} {fine_block}")
|
||||
legacy = run(mode, None, objects=[circle(actuation(SPEED))], jets=())
|
||||
diff = np.abs(dense[1][1][:, fluid] - legacy[1][1][:, fluid]).max()
|
||||
dense = run(mode, None, objects=[circle()], jets=[jet()]) # dense leg (D2 retires)
|
||||
for a, b in zip(dense[0] + tuple(dense[1]), reference[0] + tuple(reference[1])):
|
||||
np.testing.assert_array_equal(a, b, err_msg=f"G1 {mode} dense")
|
||||
legacy = run(mode, FINE_BLOCKS[0], objects=[circle(actuation(SPEED))], jets=())
|
||||
diff = np.abs(reference[1][1][:, fluid] - legacy[1][1][:, fluid]).max()
|
||||
print(f"G2 {mode}: jet vs legacy fine max |dG| = {diff:.3e}", flush=True)
|
||||
self.assertLessEqual(diff, 1e-6, mode)
|
||||
|
||||
def test_g3_amplitude_switch_layouts_identical(self):
|
||||
for mode in ("periodic", "slot_reservoir"):
|
||||
dense = run(mode, None, objects=[circle()], jets=[jet()], switch=-SPEED)
|
||||
steady = run(mode, None, objects=[circle()], jets=[jet()])
|
||||
self.assertFalse(np.array_equal(dense[1][1], steady[1][1], equal_nan=True), mode)
|
||||
for fine_block in FINE_BLOCKS:
|
||||
reference = run(mode, FINE_BLOCKS[0], objects=[circle()], jets=[jet()], switch=-SPEED)
|
||||
steady = run(mode, FINE_BLOCKS[0], objects=[circle()], jets=[jet()])
|
||||
self.assertFalse(np.array_equal(reference[1][1], steady[1][1], equal_nan=True), mode)
|
||||
for fine_block in (*FINE_BLOCKS[1:], None): # None: dense leg (D2 retires)
|
||||
public, raw_arrays = run(mode, fine_block, objects=[circle()], jets=[jet()],
|
||||
switch=-SPEED)
|
||||
for a, b in zip(public + tuple(raw_arrays), dense[0] + tuple(dense[1])):
|
||||
for a, b in zip(public + tuple(raw_arrays), reference[0] + tuple(reference[1])):
|
||||
np.testing.assert_array_equal(a, b, err_msg=f"G3 {mode} {fine_block}")
|
||||
print(f"G3 {mode}: amplitude switch dense vs {len(FINE_BLOCKS)} layouts identical",
|
||||
flush=True)
|
||||
print(f"G3 {mode}: amplitude switch, {len(FINE_BLOCKS) - 1} layouts + dense "
|
||||
f"identical to {FINE_BLOCKS[0]}", flush=True)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
Reference in new issue
Block a user