The algo cache serialized heuristic-selected algo bytes to disk with
GPU name + CUDA version validation. This created a divergent code path
between dev (RTX 3050) and prod (H100) — different machines would get
different cached algos, producing different but "frozen" results.
Determinism should come from the algorithm itself being deterministic,
not from caching one machine's non-deterministic output. The proper
fix is routing evaluation through the trainer's CUDA-Graphed forward
pass (which IS deterministic by design).
Kept: COMPUTE_32F_PEDANTIC on all cublasLt matmul descriptors (disables
TF32, universal across GPUs). Kept: IQN + attention backward determinism,
single-stream eval, evaluator reuse.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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