Untimed physical-leaf/fluid health after warm-up and after each timed window using the existing runner limits (finite macros, rho in [0.5,1.5], max Mach <= 0.2); refined masks as in run_refined_dfg. Parity comparator rejects unequal level counts and any infinity; matching NaN stays allowed only as a storage mask. Regression tests for both. No numerical gate or production change. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2.6 KiB
2.6 KiB
Refined DFG MRT timing harness (measurement only)
tests/validation/time_refined_dfg.py times the matched MRT refined/uniform DFG Re100 setup of
run_refined_dfg.py (same configuration, geometry and initial state functions). No numerical,
physics-gate or production change; no force or accuracy result is produced.
| Variant | Loop | Force history |
|---|---|---|
| A | refined step(1) + read_raw_exchange per base step (as the runner) |
valid |
| B | refined step(1) only, no host reads (observe_raw_exchange stays on) |
timing-only |
| C | refined single step(N) |
timing-only; ledger keeps the final base interval only |
| E | uniform sim.run(<=100) + read_force (as the runner) |
valid |
| E' | uniform single sim.run(2N) |
timing-only; at most a whole-window average, different summation order |
- Equal simulated duration: N refined base steps vs 2N uniform D80 steps.
- Every repeat starts from the same fresh state (refined
initialize, uniformsnapshot/restore) and the same warm-up; construction/JIT, warm-up, downloads and parity checks are untimed. - The actual stepping stream is synchronized explicitly before and after each timed loop; the
wall timer (
time.perf_counter) is the only source. No CUDA-event span is called kernel time. --max-wall-secondsis required for GPU runs (outer timeout, checked between variants and every 100 steps in per-step loops).- Final populations and NaN masks must be bitwise identical to the first A repeat (A/B/C) or the first E repeat (E/E'); refined and uniform grids are never compared. Leaf/fluid populations must be finite. Physical health (finite leaf/fluid macros, rho in [0.5, 1.5], max Mach <= 0.2, the existing runner limits) is checked after warm-up and after each timed window. Matching NaN is accepted only as a storage mask; any infinity or level-count mismatch fails parity. All parity/health checks are untimed.
- Cases run sequentially (uniform, then refined) in one process with startup serialized; variants are interleaved within each repeat. A-B and B-C are measured comparative differences under GPU variability, not exact causal decompositions.
Usage (root selects one verified idle GPU):
PYTHONPATH=src python -m unittest tests/unit/test_time_refined_dfg.py
python tests/validation/time_refined_dfg.py --output <new> --plan
CUDA_VISIBLE_DEVICES=<gpu> python tests/validation/time_refined_dfg.py --output <new> --max-wall-seconds <s>
Defaults: 2000 base steps, 200 warm-up base steps, 3 repeats. Profiler capture and the
observe_raw_exchange=False variant are deferred until these measurements exist.