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[PyTorch-MPS][MRv2] Use upstream Triton sampling directly on MPS - #865
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Signed-off-by: Ranran <ranranhaoranzhang@gmail.com>
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Closing this draft because it depends on the unmerged Triton Apple backend, triton-lang/triton-ext#126. We’ll follow up after vllm-project/vllm#43048 reaches a vLLM release, using TileLang sampling kernels shared by the MLX and PyTorch MPS paths with small framework-specific adapters. |
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@WindChimeRan Thank you for getting this to run although I think it's gonna take some while until the backend gets to be released officially. Fixed the bad words kernel bug either way and now the system runs properly e2e for me (after some UVA related fixes in |
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Stacked on #859. Run vLLM's unchanged sampling kernels through Triton's Apple backend.
./install.sh --mpsinstalls the pinned Torch/Triton/Apple-backend dependencies in.venv-vllm-metal-mps, fetches the checksum-verified LLVM SDK, builds in dependency order, and verifies an upstream sampling kernel.Validated: clean install, repeat install, dependency consistency, Qwen3 sampling/logprobs and prefix reuse. The compiler backend is pinned to triton-ext #126; this remains an experimental draft.
Qwen3 FP16, T=0.6: 337.8 → 455.4 tokens/s (+34.8%) versus MLX, two-run means with the same Sonnet 1024/128, 100-request, 10/s, C32, 2,340-block, prefix-off settings as #858. MLX native sampling is enabled, including its mixed-step CPU fallback.