The cuBLAS documentation (fetched 2026-10-21) limits bitwise reproducibility to the same toolkit version, same architecture and same SM count, and excludes multiple active streams and fixed-point emulation; cuBLASXt adds tile-size and CPU-hybrid...
Corrected 2026-10-23 - see C3-B684-04; the original statements below are kept for history and are superseded where the correction says so. The cuBLAS documentation (fetched 2026-10-21) limits bitwise reproducibility to the same toolkit version, same architecture and same SM count, and excludes multiple active streams and fixed-point emulation; cuBLASXt adds tile-size and CPU-hybrid conditions.
The cuBLAS documentation (fetched 2026-10-21) limits bitwise reproducibility to the same toolkit version, same architecture and same SM count, and excludes multiple active streams and fixed-point emulation; cuBLASXt adds tile-size and CPU-hybrid conditions.
Curator correction 2026-10-23 (discovery audit record C3-B684-04; sources re-fetched 2026-10-23, excerpts re-located by curator GET): Problem. Candidate T3-02 says batch invariance is experimental and opt-in so batch-size changes can change bits 'unless it is enabled', implying enabling it fixes the problem. Nature: (c) missing an important limitation. Conditions. Current cuBLAS documentation (latest URL, fetched 2026-10-23). Method. The same section limits the mode to GPUs with compute capability 10.x; on other GPUs matmul and heuristics queries return CUBLAS_STATUS_NOT_SUPPORTED when it is requested. It also requires an alignment promise through CUBLASLT_BATCH_INVARIANCE_ALIGN_* values, and disables split-K, which may reduce performance. Failure modes. An agent that sets the attribute on an Ampere, Ada or Hopper card gets an error, not invariance; one that omits the alignment promise cannot rely on bitwise slices. Limitations. Which GPUs count as '10.x' was not mapped here. Version and date. Latest cuBLAS page at 2026-10-23.
Curator qualifications: cuDNN and cuFFT statements, version drift between cuBLAS 12.x and 13.4, batch-invariance and cuDNN attention determinism (F1, F2, F4-F7) not reinspected. PyTorch PR #161749 removal context belongs to T3-01 (unreviewed). Live NVIDIA docs page fetched 2026-10-21 (unversioned URL); re-pin before reuse. Static reading only; no GPU, model or pipeline run.
Limitations: Static reading only; no GPU, model or pipeline run.
Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.
Structured fields
{
"citations": [
{
"url": "https://docs.nvidia.com/cuda/cublas/index.html#results-reproducibility",
"note": "cuBLAS docs 2.1.4 Results Reproducibility; 4.1.3 cuBLASXt"
},
{
"url": "https://docs.nvidia.com/cuda/cublas/index.html",
"note": "correction source (record C3-B684-04): 3.1.5 Experimental: Batch Invariance; 3.1.5 Experimental: Batch Invariance"
}
]
}Evidence claims
- [sourced_fact] The cuBLAS documentation (fetched 2026-10-21) limits bitwise reproducibility to the same toolkit version, same architecture and same SM count, and excludes multiple active streams and fixed-point emulation; cuBLASXt adds tile-size and CPU-hybrid conditions. · locator: cuBLAS docs 2.1.4 Results Reproducibility; 4.1.3 cuBLASXt source
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |