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PYTORCH SHIPS BUILD FIX WHILE HELION TUNES H100 KERNELS TO DEFAULT
By RepoJournal · Filed · About PyTorch
A critical build regression in cusparselt.cpp is now patched, while the kernel autotuner promotes its pointwise seed heuristic to production defaults on H100 and B200.
PyTorch's core build pipeline had a lurking fault: #178737 removed the file-level guard around cusparselt.cpp but left the function registration unprotected, causing compilation to fail on systems without cuSPARSELt or HIP support [1]. That's fixed. Meanwhile, Helion's autotuner is maturing its pointwise seed heuristic from experimental to default behavior on sm90 and sm100 architectures [2], a validation that the bandwidth-tile constants actually work at scale on H100 and B200. The move stays conservative elsewhere, keeping block_size=32 as the safe baseline for older hardware. On the attention front, Helion shipped a stacked PR series hardening its CuTe flash attention benchmark tooling [5] and adding FA4 runtime helpers [4], setting the stage for dense attention tuning [6]. Back in core, test infrastructure continues cleaning house: the S1/S2 decoupling strategy landed for AotAutogradFallbackTests [3], separating accelerator-agnostic tests from device-specific ones. Docs are purging decade-old Caffe2 references that no longer exist [7], and fast-mode gradcheck now handles zero-element inputs without crashing on forward AD [8].
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Action items
- → Rebuild PyTorch on systems without cuSPARSELt or HIP to verify the cusparselt.cpp fix compiles cleanly pytorch/pytorch [plan]
- → If targeting H100 or B200, verify pointwise kernel defaults are now active by checking autotune-off behavior pytorch/helion [monitor]
- → Run gradcheck tests with zero-element tensors to ensure forward AD no longer crashes pytorch/pytorch [plan]
References
- [1] Fix cusparselt.cpp build when neither USE_CUSPARSELT nor USE_HIPSPARSELT is defined (#190496) pytorch/pytorch
- [2] [autotuner] promote pointwise seed to default on sm90/sm100 ↗ pytorch/helion
- [3] [Test][Refactor] Decouple AotAutogradFallbackTests and HooksTests (#189373) pytorch/pytorch
- [4] [cutedsl] Add FA4 flash runtime helpers ↗ pytorch/helion
- [5] [cutedsl] Harden attention benchmark tooling ↗ pytorch/helion
- [6] [cutedsl] Tune dense CuTe flash attention ↗ pytorch/helion
- [7] Remove stale Caffe2 references from docs (#190430) pytorch/pytorch
- [8] Fix fast-mode gradcheck forward AD crash for zero-element inputs (#190437) pytorch/pytorch