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@nvpohanh nvpohanh commented Sep 2, 2025

Purpose

Mainly to get the GPT-OSS MXFP4 trtllm-gen MoE autotuning and the bug fix in: flashinfer-ai/flashinfer#1573

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  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
  • (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.

@mergify mergify bot added the ci/build label Sep 2, 2025
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Code Review

This pull request upgrades FlashInfer to v0.3.0, which is reflected consistently in both the Dockerfile and setup.py. This is a welcome update that should bring in new features and bug fixes.

My review includes two main points regarding opportunities to clean up obsolete code and workarounds related to previous FlashInfer versions. Addressing these would make the upgrade more complete and improve maintainability and potentially performance. Please see the detailed comments.

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high

With this upgrade to FlashInfer v0.3.0, it's worth investigating if the workarounds for the 'FlashInfer AOT wheel' issue are still necessary. There are TODOs on lines 18 and 428 in this file related to this. If the issue is resolved in v0.3.0, those sections could be cleaned up as part of this upgrade to simplify the Dockerfile.

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high

This upgrade to flashinfer-python==0.3.0 is great. The release notes for this version mention that dynamic tile size for MoE kernels is now enabled. This likely resolves the TODO on line 28 of vllm/model_executor/layers/quantization/utils/flashinfer_utils.py, which hardcodes tile_tokens_dim = 8 due to issues in a previous FlashInfer version. It would be beneficial to update that logic to take advantage of the new version's capabilities and potentially improve performance.

@WoosukKwon WoosukKwon added the ready ONLY add when PR is ready to merge/full CI is needed label Sep 2, 2025
@WoosukKwon WoosukKwon enabled auto-merge (squash) September 2, 2025 14:55
auto-merge was automatically disabled September 3, 2025 01:08

Head branch was pushed to by a user without write access

@nvpohanh nvpohanh force-pushed the dev/nvpohanh/upgrade-flashinfer-v0.3.0 branch 2 times, most recently from 5b14725 to 4858c46 Compare September 3, 2025 12:52
Mainly to get the GPT-OSS MXFP4 trtllm-gen MoE autotuning and the bug
fix in: flashinfer-ai/flashinfer#1573

Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
@nvpohanh nvpohanh force-pushed the dev/nvpohanh/upgrade-flashinfer-v0.3.0 branch from 4858c46 to e7e16d8 Compare September 4, 2025 01:45
@simon-mo simon-mo added this to the v0.10.2 milestone Sep 4, 2025
@simon-mo simon-mo enabled auto-merge (squash) September 4, 2025 04:58
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simon-mo commented Sep 4, 2025

@simon-mo simon-mo disabled auto-merge September 4, 2025 16:49
@simon-mo simon-mo merged commit 78336a0 into vllm-project:main Sep 4, 2025
68 of 71 checks passed
eicherseiji pushed a commit to eicherseiji/vllm that referenced this pull request Sep 9, 2025
Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
skyloevil pushed a commit to skyloevil/vllm that referenced this pull request Sep 13, 2025
Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
FeiDaLI pushed a commit to FeiDaLI/vllm that referenced this pull request Sep 25, 2025
Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
xuebwang-amd pushed a commit to xuebwang-amd/vllm that referenced this pull request Oct 10, 2025
Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
Signed-off-by: xuebwang-amd <xuebwang@amd.com>
xuebwang-amd pushed a commit to xuebwang-amd/vllm that referenced this pull request Oct 24, 2025
Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
Signed-off-by: xuebwang-amd <xuebwang@amd.com>
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4 participants