Root-caused the decode non-determinism: matmul's m==1 custom-GEMV fast path
reduces over K with a grid-split atomicAdd, whose float accumulation order
is non-deterministic. Negligible for attention's stable pre-transposed
weights, but for gpt-oss's wide expert GEMMs (K=2880, N up to 5760) over
freshly-dequantized MXFP4 weights it produced visibly different results
run-to-run (and a wrong argmax). Added gemm::matmul_dense (plain cublasGemmEx,
no GEMV shortcut) and route the expert GEMMs through it.
Now decode_step (KV cache + GPU sink-attention + MXFP4 experts) is:
- deterministic: 3/3 identical runs
- correct: top-1 token 12650 = " Paris" for "The capital of France is",
MATCH_TOP1 with the host-attention reference forward
- end-to-end: gptoss-gen generates 32 tokens at ~6.85 tok/s on one 5090.
Removed the temporary A/B debug dumps. gptoss-logits runs both paths and
asserts the top-1 match; gptoss-gen times greedy generation.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Gahow Wang
603b6eb270