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Require PyTorch 2.8; build all CUDA 12 wheels against it - #313
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PyTorch 2.6 is old by now, and the v0.9.3rc4 cluster tests showed its NCCL (2.21) crashing the distributed tests on H100 (segfaults in the ring p2p tests, on every grid with more than one azimuth rank), which PyTorch 2.8 and later do not -- nothing to work around on our side. - build_wheels.yml: no cu126 row, plan entry, cp314 exclusion or 12.6 arch list; the matrix is 6 variants. - pyproject.toml: torch>=2.7.0. - README, docs/install.md, CONTRIBUTING.md: no cu126; examples use cu128. - Changelog: breaking entry. CUDA 12 users install torch-harmonics-cu128, which also runs on older CUDA 12 drivers (tested on driver 535 / CUDA 12.2). The section is relabelled v0.9.3rc5 for the next tag. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The rest of the v0.9.3rc4 eos results showed PyTorch 2.7 (NCCL 2.26.2) failing like 2.6: segfaults on 2x4 in the distributed primitives and quadrature tests -- the latter only uses collectives, no p2p -- and an abort on 4x1 on H100, while on B200 every distributed test process spent about six minutes in NCCL. PyTorch 2.8 (NCCL 2.27.3) passes every grid on both, also on eos' driver 535 (CUDA 12.2), so torch-harmonics-cu129 covers CUDA 12 users with older drivers just as cu128 did. Minimum PyTorch is now 2.8; the matrix is 5 variants (cu129, cu130, cu132, cuda-latest, cpu). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Instead of discontinuing cu126 and cu128 with PyTorch 2.6/2.7, build them against PyTorch 2.8 too, for the CUDA builds it ships: every CUDA 12 variant now runs on PyTorch 2.8 and its NCCL (2.27.3), which passed the distributed tests on H100 and B200, and each matches the torch build its users have -- plain `pip install torch==2.8.0` is the CUDA 12.8 build. The matrix is back to 7 variants, 24 build jobs; torch>=2.8.0 stays. README and docs/install.md tell users of older PyTorch or CUDA to use the Docker container or build from source with --no-deps -- without it, the torch>=2.8 requirement makes pip replace their PyTorch. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The note on older PyTorch/CUDA links to #docker and #building-from-source, but MyST heading anchors are not enabled, so the links had no target (myst.xref_missing in the docs build). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Oct 7, 2026
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On the v0.9.3rc4 cluster tests, the NCCL of PyTorch 2.6 (2.21.5) and 2.7 (2.26.2) failed the distributed tests:
test_distributed_primitivesandtest_distributed_quadrature(collectives only, no p2p), plus a sporadic abort on 4×1.PyTorch 2.8 (NCCL 2.27.3) and later pass every grid on both clusters, including on eos' driver 535 (CUDA 12.2).
Changes
pyproject.toml:torch>=2.8.0).pip install torch==2.8.0is the cu128 build. Still 7 variants, 24 build jobs.docs/install.md: users of PyTorch before 2.8 or CUDA before 12.6 are pointed to the Docker container, or to a source build with--no-deps. Without--no-deps, thetorch>=2.8requirement makes pip replace their PyTorch. Those combinations are untested.### v0.9.3rc5for the next tag.🤖 Generated with Claude Code