Preserve exact float32 via explicit nvcc compilation and audited binary loading

2026-10-01 14:41:59 +08:00
parent 5abb3e6463
commit 221e1f13f7
4 changed files with 326 additions and 13 deletions
@@ -23,3 +23,9 @@ Budget: at most 15 minutes of candidate benchmark execution after dependencies/c
 Passing this benchmark means only ELIGIBILITY-UPDATE-REPLAY-EQUIVALENCE for the tested inputs. It does not establish full-brain event equivalence, end-to-end acceleration, learning success, resumability, or completion of Phase 4AR. Integration, persistent brain workers and independent-seed multi-GPU scheduling require separately validated execution/audit changes. Stop before installing any update or starting learning.

 Keep source, configuration, environment installation report, fixed input manifest, raw timing samples, comparisons, failures and SHA-256 manifest. Check Phase 4AR registration/source and the prior saved-file inventory before/after; report the exact scope (not a new Phase 1–4AQ numerical regression).
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+## Recorded implementation correction (before successful GPU execution)
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+The first candidate installation attempted pip's `--report` with the new venv's inherited pip 22.0.2, which does not support it. Only the candidate venv was upgraded to pip 25.2; both logs remain preserved.
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+GPU attempt `v100a-01` failed before running kernels because CuPy 13.6's RawKernel cache compiler appends `-ftz=true`, conflicting with the required `--ftz=false`. Do not remove the precision requirement. The corrected candidate compiles the same CUDA recurrence with installed nvcc 12.6, explicit separate rounding and `--ftz=false`, then loads the precompiled module through CuPy. Compiler commands, sources, output and binary hashes are preserved in candidate-only caches. The original scientific recurrence and all predeclared fixtures remain unchanged; failed attempt records are not replaced.