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[Harware][AMD][Model] Triton MoE tuning configs for GLM-4.5 for MI300X#25703

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vllm-bot merged 1 commit intovllm-project:mainfrom
xaguilar-amd:glm-triton-moe-tuning-mi300x
Sep 26, 2025
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[Harware][AMD][Model] Triton MoE tuning configs for GLM-4.5 for MI300X#25703
vllm-bot merged 1 commit intovllm-project:mainfrom
xaguilar-amd:glm-triton-moe-tuning-mi300x

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@xaguilar-amd xaguilar-amd commented Sep 25, 2025

Purpose

Triton MoE configs for AMD MI300 for GLM-4.5 model and other models that share the same dimensions in moe kernels.

Test Plan

Test Result


Essential Elements of an Effective PR Description Checklist
  • 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.

Signed-off-by: xaguilar <Xavier.AguilarFruto@amd.com>
@xaguilar-amd xaguilar-amd requested a review from mgoin as a code owner September 25, 2025 19:02
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@mergify mergify bot added the rocm Related to AMD ROCm label Sep 25, 2025
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Code Review

This pull request adds new Triton MoE tuning configurations for the AMD MI300X GPU, specifically for models with GLM-4.5 dimensions. While adding optimized hardware-specific configurations is valuable for performance, the pull request description lacks a test plan and, more importantly, test results. For performance-sensitive changes like this, it's crucial to provide benchmark data to validate that these new configurations indeed offer an improvement and do not introduce regressions. Please update the pull request with details on how these configurations were generated and the performance impact observed.

Comment on lines +60 to +61
"GROUP_SIZE_M": 4,
"num_warps": 1,
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high

The configuration for a batch size of 32 appears unusual, particularly when compared to the one for batch size 48, which uses identical block dimensions.

  • num_warps: 1: Using a single warp is often suboptimal as it limits parallelism and the ability to hide memory latency. For batch size 48, num_warps is set to 2.
  • GROUP_SIZE_M: 4: This enables grouping for better L2 cache reuse, which is generally more effective for larger batch sizes. However, for batch size 48, grouping is disabled (GROUP_SIZE_M: 1).

This combination for batch size 32 is counter-intuitive and might be a typo, potentially leading to performance degradation. Could you please verify these parameters and provide benchmark data? I'd suggest aligning it with the configuration for batch size 48 if this was an oversight.

Suggested change
"GROUP_SIZE_M": 4,
"num_warps": 1,
"GROUP_SIZE_M": 1,
"num_warps": 2,

@vllm-bot vllm-bot merged commit 52621c8 into vllm-project:main Sep 26, 2025
15 of 17 checks passed
pdasigi pushed a commit to pdasigi/vllm that referenced this pull request Oct 2, 2025
yewentao256 pushed a commit that referenced this pull request Oct 3, 2025
#25703)

Signed-off-by: xaguilar <Xavier.AguilarFruto@amd.com>
Signed-off-by: yewentao256 <zhyanwentao@126.com>
choprahetarth pushed a commit to Tandemn-Labs/vllm that referenced this pull request Oct 11, 2025
lywa1998 pushed a commit to lywa1998/vllm that referenced this pull request Oct 20, 2025
alhridoy pushed a commit to alhridoy/vllm that referenced this pull request Oct 24, 2025
rtourgeman pushed a commit to rtourgeman/vllm that referenced this pull request Nov 10, 2025
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3 participants