Files
CelerisLab/tests/validation/taylor_green/run_case.py
T
ClaudeandClaude Opus 5.5 ffff742b69 test: add oblique (2,1) shear-wave diagnostic with composite modal fit
Test-only. New shear_wave.py (exact field, equilibrium initializer reusing
frozen oracle constants/geometry, area-weighted composite metrics with a
2x2 Gram-matrix modal fit, late-time rate fit, preregistered assess with
max(2*control, floor) budgets). run_case.py gains --flow (default
taylor_green, unchanged receipt). oracle.py byte-identical (pinned by test).
CPU manufactured checks in test_shear_wave.py; docs record caveats.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 00:16:21 +00:00

338 lines
14 KiB
Python

"""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
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 flow_functions(flow="taylor_green"):
"""(initial, metrics, limits, initialization); the default is the frozen TG oracle."""
if flow == "taylor_green":
return initial, metrics, LIMITS, INITIALIZATION
if flow == "shear_wave":
import shear_wave
return shear_wave.initial, shear_wave.metrics, shear_wave.LIMITS, shear_wave.INITIALIZATION
raise ValueError(f"unknown flow {flow!r}")
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(
["git", "-C", str(repo), *a], text=True
).strip()
source_hash = hashlib.sha256()
for path in sorted((repo / "src").rglob("*")):
if path.is_file() and "__pycache__" not in path.parts and path.suffix != ".pyc":
source_hash.update(
str(path.relative_to(repo)).encode() + b"\0" + path.read_bytes() + b"\0"
)
return dict(
revision=git("rev-parse", "HEAD"),
dirty=bool(git("status", "--porcelain")),
source_tree_sha256=source_hash.hexdigest(),
harness_sha256={
p.name: hashlib.sha256(p.read_bytes()).hexdigest()
for p in Path(__file__).parent.glob("*.py")
},
)
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
cfg = LBMConfig(
nx=n,
ny=n,
viscosity=U * n / re,
velocity=0.0,
rho=1.0,
lattice_model="D2Q9",
collision="SRT",
streaming="double_buffer",
store_precision="FP32",
ddf_shifting=True,
les_enabled=False,
)
cfg.validate()
return cfg
def workload(masks, base_steps):
cells = [int(np.count_nonzero(m)) for m in masks]
hops = [base_steps * 2**level for level in range(len(masks))]
updates = [count * hop for count, hop in zip(cells, hops)]
return dict(
active_cells_by_level=cells,
level_hops=hops,
active_collision_updates_by_level=updates,
active_collision_updates=sum(updates),
root_intervals=base_steps,
excludes="ghost streaming, halo copies, transfers, initialization and diagnostics",
)
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")
p.add_argument("--flow", choices=["taylor_green", "shear_wave"], default="taylor_green")
args = p.parse_args()
if args.flow == "shear_wave" and (args.re != 100 or args.depth == 3 or args.early_pressure):
p.error("shear_wave requires --re 100, depth 1 or 2 and no --early-pressure")
initial, metrics, limits, initialization = flow_functions(args.flow)
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[: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
from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
from CelerisLab.lbm.refinement import ACTIVE
from CelerisLab.lbm.hierarchy import build_hierarchy, leaf_partition
cfg = config(args.n, args.re)
refinements = [] if args.depth == 1 else rectangles(args.n, args.depth)
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=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,
refinements=refinements,
U=U,
mach=U * np.sqrt(3),
viscosity=cfg.viscosity,
tau_by_level=[0.5 + 3 * c.viscosity for c in h.configs],
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,
)
if args.flow != "taylor_green":
import shear_wave
report.update(flow=args.flow, mode=list(shear_wave.MODE),
polarization=shear_wave.E.tolist(), angle_deg=shear_wave.ANGLE_DEG,
phase=shear_wave.PHI, eps=shear_wave.eps(args.n))
args.output.parent.mkdir(parents=True, exist_ok=True)
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, 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)
else:
run = FixedPatchStepper(
cfg,
context=ctx,
coarse_boundary="periodic",
refinements=refinements,
level_blocks=[(8, 8)] * args.depth,
explosion=args.explosion,
)
with run:
run.initialize(
*[
initial(m.shape, level, args.n, cfg.viscosity)
for level, m in enumerate(masks)
]
)
initial_mass = None
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"]
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" if step in main_steps else "EARLY_PRESSURE",
n=args.n,
re_L=args.re,
depth=args.depth,
**(row if step in main_steps else report["early_pressure"]["rows"][-1]),
)
),
flush=True,
)
if step == 0:
# Exercise real kernels/halos/transfers on every level before READY.
# This is the first measured trajectory step, not discarded warmup.
run.step(1)
probe = (run.download(),) if args.depth == 1 else run.download()
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(
json.dumps(
dict(
event="READY",
step=1,
n=args.n,
re_L=args.re,
depth=args.depth,
workload=report["workload"],
)
),
flush=True,
)
report.update(
completed=True,
seconds=time.monotonic() - started,
screening_pass=all(
row[key] <= limit for row in report["rows"] for key, limit in limits.items()
),
)
save()
print(
json.dumps(
{k: report[k] for k in ("n", "re_L", "depth", "screening_pass", "seconds")}
),
flush=True,
)
return 0 if report["screening_pass"] else 1
if __name__ == "__main__":
raise SystemExit(main())