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CelerisLab/docs/validation/refined_dfg_timing.md
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ClaudeandClaude Opus 5.5 6c53d2e74a test: fix flat uniform DDF masking and clarify harness labels
Simulation.get_ddf() is flat (9*ny*nx); view it as (Q, cells) before
applying the fluid mask, with a flat-DDF regression. Label A/E as
runner-like force-read workloads (values discarded, no aggregation or
validation; no macro/probe/CSV cost; not benchmark throughput) and split
status lines into CONSTRUCTED and WARM_READY. Test/doc only.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-18 12:33:07 +00:00

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3.0 KiB
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# 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 reads |
|---|---|---|
| A | refined `step(1)` + `read_raw_exchange` per base step | runner-like force-read workload (values discarded) |
| 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` | runner-like force-read workload (values discarded) |
| E' | uniform single `sim.run(2N)` | timing-only; at most a whole-window average, different summation order |
- No variant retains a valid force history; A/E omit the runner's interval aggregation and
validation, and no variant includes macro/probe/CSV costs. Results are not full benchmark
throughput.
- Status lines: `CONSTRUCTED` (construction/JIT complete) and `WARM_READY` (first warm-up and
health check passed) per case.
- Equal simulated duration: N refined base steps vs 2N uniform D80 steps.
- Every repeat starts from the same fresh state (refined `initialize`, uniform `snapshot/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-seconds` is 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.