[Feature] Add tile-based method of supporting large VPT in moe_fused_gate kernel by ltaodream · Pull Request #6946 · sgl-project/sglang

ltaodream · 2025-06-07T09:45:57Z

Motivation

The kimi-vl supported at #5383 and kimi-k2 model cannot use the fuse moe gate operator. This operator currently does not support the case where the group expert is greater than 32. The group expert of kimi-vl is 64, the group expert of kimi-k2 is 384, and this operator cannot be used at present.

Modifications

@ttaohe @Misaka9468 The three of us completed the PR "Add tile-based method of supporting large VPT in moe_fused_gate kernel" together.

Checklist

Format your code according to the Code Formatting with Pre-Commit.
Add unit tests as outlined in the Running Unit Tests.
Update documentation / docstrings / example tutorials as needed, according to Writing Documentation.
Provide throughput / latency benchmark results and accuracy evaluation results as needed, according to Benchmark and Profiling and Accuracy Results.
For reviewers: If you haven't made any contributions to this PR and are only assisting with merging the main branch, please remove yourself as a co-author when merging the PR.
Please feel free to join our Slack channel at https://slack.sglang.ai to discuss your PR.

…plemented with tilling

gemini-code-assist

Hello @ltaodream, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

Summary of Changes

Hello! Gemini here, providing a summary of this pull request to help everyone quickly understand the changes. This PR, authored by @ltaodream, aims to address a limitation in the moe_fused_gate kernel which currently only supports a maximum of 32 experts per group. This limitation prevents models like kimi-vl, which use 64 experts per group, from utilizing the fused gate operator. The core change involves increasing this limit to 128 by implementing a tiling approach within the CUDA kernel.

Highlights

Increase MoE Expert Group Limit: The primary goal is to raise the maximum number of experts per group supported by the moe_fused_gate kernel from 32 to 128. This is necessary for compatibility with models requiring a higher number of experts per group.
Implement Tiling in CUDA Kernel: The CUDA kernel (moe_fused_gate.cu) has been modified to process the expert data in smaller chunks (tiling). This allows the kernel to handle the increased MAX_VPT (experts per group) by iterating through tiles of data rather than processing the entire VPT in a single unrolled loop.
Update Python-side Check: The Python code (topk.py) that checks the eligibility for using the moe_fused_gate kernel has been updated to reflect the new maximum limit of 128 experts per group.

Changelog

python/sglang/srt/layers/moe/topk.py
- Updated the condition for using the moe_fused_gate kernel to allow up to 128 experts per group (changed <= 32 to <= 128).
- Updated the associated comment to reflect the new maximum supported limit of 128.
sgl-kernel/csrc/moe/moe_fused_gate.cu
- Increased the static constexpr int MAX_VPT from 32 to 128.
- Added a comment indicating that tiling is used to handle the increased limit.
- Refactored the moe_fused_gate_impl kernel to process expert data in tiles of 32, allowing it to handle params.VPT up to MAX_VPT=128.

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Code Review

This pull request successfully extends the capability of the moe_fused_gate operator to support up to 128 experts per group, up from 32, by implementing a tiling mechanism in the CUDA kernel. This change is crucial for supporting models like kimi-vl.

The core logic in the CUDA kernel appears sound, and the tiling approach is well-implemented. The corresponding update in the Python code is also correct.

A few points for consideration:

Clarity of Tiling Constant: The CUDA kernel uses the number 32 for tiling. Clarifying its origin or using a named constant could improve maintainability.
Performance Benchmarks: It would be beneficial to see benchmark results, especially to confirm that there's no performance regression for cases where the number of experts per group (VPT) was already within the old limit (<= 32), and to understand the performance characteristics with the new VPT up to 128.
PR Title Typo: There's a small typo in the PR title: "tilling" should be "tiling".

Overall, good work on implementing this feature enhancement!

Summary of Findings

CUDA Kernel Tiling Constant: The CUDA kernel uses a hardcoded 32 for tiling. Using a named constant like WARP_SIZE (if applicable) or PROCESSING_TILE_SIZE could improve code clarity and maintainability.
Performance Benchmarking: The introduction of tiling in the CUDA kernel might affect performance. It's important to benchmark this change, especially for cases previously supported (VPT <= 32) and for the newly supported larger VPT values, to ensure no regressions and understand new performance characteristics.
Clarity of Ceiling Division: In sgl-kernel/csrc/moe/moe_fused_gate.cu, the expression (params.VPT + 31) / 32 is used for ceiling division. While common, a helper function or a comment could slightly improve readability for developers less familiar with this pattern. (Not commented due to review settings: low severity)

Merge Readiness

The pull request implements an important feature enhancement. The core logic seems correct. However, before merging, it would be ideal to address the point about the magic number 32 for better maintainability and to provide benchmark results to confirm the performance implications of the tiling mechanism. I am requesting changes to encourage addressing these points. As a reviewer, I am not authorized to approve the pull request; other maintainers should review and approve the changes before merging.

gemini-code-assist · 2025-06-07T09:47:25Z

sgl-kernel/csrc/moe/moe_fused_gate.cu

The constant 32 is used here for the tile size and in the calculation of the number of tiles (params.VPT + 31) / 32. This value is also WARP_SIZE.

Is the choice of 32 specifically tied to WARP_SIZE or another hardware characteristic? If so, would it be clearer to use the WARP_SIZE constant or define a new named constant (e.g., PROCESSING_TILE_SIZE = 32) for this purpose? This could enhance readability and make it easier to understand the rationale behind this value if it needs to be adjusted in the future.

gemini-code-assist · 2025-06-07T09:47:25Z

sgl-kernel/csrc/moe/moe_fused_gate.cu

The introduction of tiling is a key change to support MAX_VPT = 128. The PR description checklist mentions providing throughput/latency benchmark results.

Could you share any benchmark data for this new implementation? Specifically, it would be interesting to see:

Performance for params.VPT values that were previously supported (e.g., VPT <= 32) to ensure no significant regressions.

Performance for new larger params.VPT values (e.g., 64, 128) to understand the characteristics of the tiled approach.

This information would be valuable for assessing the impact of these changes.

…erflow

Alcanderian · 2025-06-07T12:51:44Z

sgl-kernel/csrc/moe/moe_fused_gate.cu

+          } else if (cmp_gt(val, global_max_val_second)) {
+            global_max_val_second = val;
+            global_max_second_idx = global_idx;
+          }


I cannot see the difference between these two block

Agree, there are a lot of duplicated code which can be refactored.

Alcanderian · 2025-06-07T12:54:12Z

Please extend the unittest and present a performance report about this PR and before, thanks!

… to 384 implemented with tilling

BBuf · 2025-07-23T14:08:56Z

sgl-kernel/csrc/moe/moe_fused_gate.cu

  switch (num_experts) {
+    case 384:
+      if (num_expert_group == 1)
+        // Kimi K2 配置: VPT = 384/1 = 384, ROWS_PER_WARP = 32/1 = 32


// Kimi K2 config:

[Fix] Modify tile-based method of supporting large VPT in moe_fused_gate kernel

ltaodream · 2025-08-12T11:04:37Z

@ttaohe @Misaka9468 The three of us completed the PR "Add tile-based method of supporting large VPT in moe_fused_gate kernel" together.

MoE Fused Gate: add tiled path and static specializations for large VPT (64/384), unify switch-case dispatch, and provide multi-dtype benchmarking.

Added a tiled implementation for large VPT and two static specializations for THREADS_PER_ROW=1: (num_experts=64, group=1) and (num_experts=384, group=1). These are exposed via consistent switch-case dispatch using LAUNCH_MOE_GATE_TILED_CONFIG.
Kept existing template fast paths for small VPT (e.g., 128/256), and route all other large-VPT cases to the generic tiled kernel.
Refactored tiled declarations/macros into moe_fused_gate_tiled.h to keep moe_fused_gate.cu clean.
Added a benchmark (bf16/fp16/fp32) comparing Original (eager, compile-static, compile-dynamic) vs SGL Kernel on representative large-VPT configs.

Results of kimi-vl and kimi-k2

Benchmmmu result of kimi-vl

Bench_hf result of kimi-vl

python benchmark/mmmu/bench_hf.py --model-path moonshotai/Kimi-VL-A3B-Instruct

answers saved to: moonshotai/Kimi-VL-A3B-Instruct_val_hf.json
Evaluating...
{'Accounting': {'acc': 0.4, 'num': 30},
 'Agriculture': {'acc': 0.562, 'num': 16},
 'Architecture_and_Engineering': {'acc': 0.367, 'num': 30},
 'Art': {'acc': 0.5, 'num': 30},
 'Art_Theory': {'acc': 0.3, 'num': 30},
 'Basic_Medical_Science': {'acc': 0.667, 'num': 30},
 'Biology': {'acc': 0.333, 'num': 30},
 'Chemistry': {'acc': 0.2, 'num': 30},
 'Clinical_Medicine': {'acc': 0.4, 'num': 30},
 'Computer_Science': {'acc': 0.6, 'num': 30},
 'Design': {'acc': 0.533, 'num': 30},
 'Diagnostics_and_Laboratory_Medicine': {'acc': 0.367, 'num': 30},
 'Economics': {'acc': 0.533, 'num': 30},
 'Electronics': {'acc': 0.333, 'num': 30},
 'Energy_and_Power': {'acc': 0.4, 'num': 30},
 'Finance': {'acc': 0.4, 'num': 30},
 'Geography': {'acc': 0.533, 'num': 30},
 'History': {'acc': 0.5, 'num': 30},
 'Literature': {'acc': 0.828, 'num': 29},
 'Manage': {'acc': 0.333, 'num': 30},
 'Marketing': {'acc': 0.6, 'num': 30},
 'Materials': {'acc': 0.367, 'num': 30},
 'Math': {'acc': 0.4, 'num': 30},
 'Mechanical_Engineering': {'acc': 0.467, 'num': 30},
 'Music': {'acc': 0.267, 'num': 30},
 'Overall': {'acc': 0.44, 'num': 885},
 'Overall-Art and Design': {'acc': 0.4, 'num': 120},
 'Overall-Business': {'acc': 0.453, 'num': 150},
 'Overall-Health and Medicine': {'acc': 0.453, 'num': 150},
 'Overall-Humanities and Social Science': {'acc': 0.563, 'num': 119},
 'Overall-Science': {'acc': 0.353, 'num': 150},
 'Overall-Tech and Engineering': {'acc': 0.434, 'num': 196},
 'Pharmacy': {'acc': 0.467, 'num': 30},
 'Physics': {'acc': 0.3, 'num': 30},
 'Psychology': {'acc': 0.367, 'num': 30},
 'Public_Health': {'acc': 0.367, 'num': 30},
 'Sociology': {'acc': 0.567, 'num': 30}}
eval out saved to moonshotai/Kimi-VL-A3B-Instruct_val_hf.json
Overall accuracy: 0.44

Summary MMMU Benchmark on Kimi-VL-A3B-Instruct Model.
Results as follows:
[bench_sglang.py]: 0.512
[bench_hf.py]: 0.44

ttaohe · 2025-08-12T12:54:07Z

@ttaohe @Misaka9468 The three of us completed the PR "Add tile-based method of supporting large VPT in moe_fused_gate kernel" together.

MoE Fused Gate: add tiled path and static specializations for large VPT (64/384), unify switch-case dispatch, and provide multi-dtype benchmarking.

Added a tiled implementation for large VPT and two static specializations for THREADS_PER_ROW=1: (num_experts=64, group=1) and (num_experts=384, group=1). These are exposed via consistent switch-case dispatch using LAUNCH_MOE_GATE_TILED_CONFIG.

Kept existing template fast paths for small VPT (e.g., 128/256), and route all other large-VPT cases to the generic tiled kernel.

Refactored tiled declarations/macros into moe_fused_gate_tiled.h to keep moe_fused_gate.cu clean.

Added a benchmark (bf16/fp16/fp32) comparing Original (eager, compile-static, compile-dynamic) vs SGL Kernel on representative large-VPT configs.

Results of kimi-vl and kimi-k2

Benchmmmu result of kimi-vl

Bench_hf result of kimi-vl
python benchmark/mmmu/bench_hf.py --model-path moonshotai/Kimi-VL-A3B-Instruct

answers saved to: moonshotai/Kimi-VL-A3B-Instruct_val_hf.json
Evaluating...
{'Accounting': {'acc': 0.4, 'num': 30},
 'Agriculture': {'acc': 0.562, 'num': 16},
 'Architecture_and_Engineering': {'acc': 0.367, 'num': 30},
 'Art': {'acc': 0.5, 'num': 30},
 'Art_Theory': {'acc': 0.3, 'num': 30},
 'Basic_Medical_Science': {'acc': 0.667, 'num': 30},
 'Biology': {'acc': 0.333, 'num': 30},
 'Chemistry': {'acc': 0.2, 'num': 30},
 'Clinical_Medicine': {'acc': 0.4, 'num': 30},
 'Computer_Science': {'acc': 0.6, 'num': 30},
 'Design': {'acc': 0.533, 'num': 30},
 'Diagnostics_and_Laboratory_Medicine': {'acc': 0.367, 'num': 30},
 'Economics': {'acc': 0.533, 'num': 30},
 'Electronics': {'acc': 0.333, 'num': 30},
 'Energy_and_Power': {'acc': 0.4, 'num': 30},
 'Finance': {'acc': 0.4, 'num': 30},
 'Geography': {'acc': 0.533, 'num': 30},
 'History': {'acc': 0.5, 'num': 30},
 'Literature': {'acc': 0.828, 'num': 29},
 'Manage': {'acc': 0.333, 'num': 30},
 'Marketing': {'acc': 0.6, 'num': 30},
 'Materials': {'acc': 0.367, 'num': 30},
 'Math': {'acc': 0.4, 'num': 30},
 'Mechanical_Engineering': {'acc': 0.467, 'num': 30},
 'Music': {'acc': 0.267, 'num': 30},
 'Overall': {'acc': 0.44, 'num': 885},
 'Overall-Art and Design': {'acc': 0.4, 'num': 120},
 'Overall-Business': {'acc': 0.453, 'num': 150},
 'Overall-Health and Medicine': {'acc': 0.453, 'num': 150},
 'Overall-Humanities and Social Science': {'acc': 0.563, 'num': 119},
 'Overall-Science': {'acc': 0.353, 'num': 150},
 'Overall-Tech and Engineering': {'acc': 0.434, 'num': 196},
 'Pharmacy': {'acc': 0.467, 'num': 30},
 'Physics': {'acc': 0.3, 'num': 30},
 'Psychology': {'acc': 0.367, 'num': 30},
 'Public_Health': {'acc': 0.367, 'num': 30},
 'Sociology': {'acc': 0.567, 'num': 30}}
eval out saved to moonshotai/Kimi-VL-A3B-Instruct_val_hf.json
Overall accuracy: 0.44
Summary MMMU Benchmark on Kimi-VL-A3B-Instruct Model. Results as follows: [bench_sglang.py]: 0.512 [bench_hf.py]: 0.44

Test Results: test_vlm_models.py [#4491 ] (Overall Acc: 0.5244)

Summary Results

The overall accuracy on the MMMU validation set is 0.5244.

Tasks	Version	Filter	n-shot	Metric		Value		Stderr
mmmu_val	0	none	0	mmmu_acc	↑	0.5244	±	N/A

Click to view detailed scores by category

{
    "Overall-Art and Design": { "num": 120, "acc": 0.7 },
    "Art": { "num": 30, "acc": 0.7 },
    "Art_Theory": { "num": 30, "acc": 0.83333 },
    "Design": { "num": 30, "acc": 0.8 },
    "Music": { "num": 30, "acc": 0.46667 },
    "Overall-Business": { "num": 150, "acc": 0.47333 },
    "Accounting": { "num": 30, "acc": 0.5 },
    "Economics": { "num": 30, "acc": 0.5 },
    "Finance": { "num": 30, "acc": 0.36667 },
    "Manage": { "num": 30, "acc": 0.4 },
    "Marketing": { "num": 30, "acc": 0.6 },
    "Overall-Science": { "num": 150, "acc": 0.47333 },
    "Biology": { "num": 30, "acc": 0.56667 },
    "Chemistry": { "num": 30, "acc": 0.36667 },
    "Geography": { "num": 30, "acc": 0.63333 },
    "Math": { "num": 30, "acc": 0.36667 },
    "Physics": { "num": 30, "acc": 0.43333 },
    "Overall-Health and Medicine": { "num": 150, "acc": 0.47333 },
    "Basic_Medical_Science": { "num": 30, "acc": 0.4 },
    "Clinical_Medicine": { "num": 30, "acc": 0.5 },
    "Diagnostics_and_Laboratory_Medicine": { "num": 30, "acc": 0.36667 },
    "Pharmacy": { "num": 30, "acc": 0.53333 },
    "Public_Health": { "num": 30, "acc": 0.56667 },
    "Overall-Humanities and Social Science": { "num": 120, "acc": 0.65833 },
    "History": { "num": 30, "acc": 0.6 },
    "Literature": { "num": 30, "acc": 0.83333 },
    "Sociology": { "num": 30, "acc": 0.56667 },
    "Psychology": { "num": 30, "acc": 0.63333 },
    "Overall-Tech and Engineering": { "num": 210, "acc": 0.45714 },
    "Agriculture": { "num": 30, "acc": 0.56667 },
    "Architecture_and_Engineering": { "num": 30, "acc": 0.46667 },
    "Computer_Science": { "num": 30, "acc": 0.53333 },
    "Electronics": { "num": 30, "acc": 0.36667 },
    "Energy_and_Power": { "num": 30, "acc": 0.46667 },
    "Materials": { "num": 30, "acc": 0.53333 },
    "Mechanical_Engineering": { "num": 30, "acc": 0.26667 },
    "Overall": { "num": 900, "acc": 0.52444 }
}

ttaohe · 2025-08-23T08:43:43Z

cc @BBuf @yuan-luo

FlamingoPg · 2025-08-23T12:03:35Z

Cool, maybe need rebase master.

ltaodream · 2025-08-25T05:15:09Z

Cool, maybe need rebase master.

@FlamingoPg Hi, I’ve rebased my branch onto the latest main. Since the old branch had a long chain of merge commits from the original main, the history is now completely rewritten and GitHub can’t update PR #6946 cleanly. Would you prefer that I close #6946 and open a fresh PR with the single squash commit, or do you have another way you’d like to handle it?

FlamingoPg · 2025-08-25T06:01:21Z

@FlamingoPg Hi, I’ve rebased my branch onto the latest main. Since the old branch had a long chain of merge commits from the original main, the history is now completely rewritten and GitHub can’t update PR #6946 cleanly. Would you prefer that I close #6946 and open a fresh PR with the single squash commit, or do you have another way you’d like to handle it?

Maybe you can reopen a new PR

ltaodream · 2025-08-25T06:57:28Z

The original PR link has been closed. New PR link: [Feature] Add tile-based method of supporting large VPT in moe_fused_gate kernel by ltaodream · Pull Request #9579 · sgl-project/sglang

ltaodream · 2025-08-25T06:58:27Z

@FlamingoPg Hi, I’ve rebased my branch onto the latest main. Since the old branch had a long chain of merge commits from the original main, the history is now completely rewritten and GitHub can’t update PR #6946 cleanly. Would you prefer that I close #6946 and open a fresh PR with the single squash commit, or do you have another way you’d like to handle it?

Maybe you can reopen a new PR

New PR link: [Feature] Add tile-based method of supporting large VPT in moe_fused_gate kernel by ltaodream · Pull Request #9579

ltaodream added 2 commits June 7, 2025 16:13

add support the number of group expert from the original 32 to 128 im…

21c9497

…plemented with tilling

modify the MAX_VPT limit in topk.py

93e5ad1

ltaodream requested review from BBuf, FlamingoPg, HaiShaw, HandH1998, Ying1123, ch-wan, ispobock, merrymercy, yizhang2077 and zhyncs as code owners June 7, 2025 09:45

gemini-code-assist bot reviewed Jun 7, 2025

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zhyncs assigned Alcanderian and BBuf Jun 7, 2025

Fix the size of row_chunk and bias_chunk to 32 to prevent register ov…

68ff1d3

…erflow

ltaodream force-pushed the main branch from fd36918 to 68ff1d3 Compare June 7, 2025 12:26

Alcanderian reviewed Jun 7, 2025

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ltaodream and others added 3 commits June 9, 2025 12:28

add test and cycle fusion Optimization

5fbde7f

add bench_moe_fused_gate for kimi-vl

92f418b

Merge branch 'main' into main

17d13a6

BBuf mentioned this pull request Jul 22, 2025

[Kimi K2] num_experts extends to 384 #8007

Open

ltaodream and others added 5 commits July 23, 2025 12:21

Merge branch 'sgl-project:main' into main

46a93f4

[Kimi K2] add support the number of group expert from the original 32…

0f908a6

… to 384 implemented with tilling

Merge branch 'main' into main

3c36fa3

fix prefetch_global、fix alignment error with cutlass alignedarray

8126d99

Merge branch 'main' of ssh://github.com/ltaodream/sglang

8672b60

BBuf reviewed Jul 23, 2025

View reviewed changes

ttaohe and others added 13 commits August 12, 2025 00:18

upd moe_fuse_gate_tiling_more_experts v1

cf186d8

upd

2c4b629

fix grouptopk only set 1-shared_experts problem

22545d4

upd

d26f836

add tiled dynamic benchmark

6c0bddb

upd pytest style

17f6813

add bench_moe_fused_gate_tiled script

71f42c3

add specific examples like kimi-vl and kimi-k2 moe config

4530634

add kimi-vl 64

5fe73f8

bench tile add more test case

bdec8b3

change specific style

11b9570

commit last bench test

fef21b5

Merge pull request #1 from ttaohe/main

29ed296

[Fix] Modify tile-based method of supporting large VPT in moe_fused_gate kernel

ltaodream changed the title ~~[Feature] add support the number of group expert from the original 32 to 128 implemented with tilling~~ [Feature] Add tile-based method of supporting large VPT in moe_fused_gate kernel Aug 12, 2025

pre-commit run --all-files

08752c9

ltaodream requested a review from BBuf August 13, 2025 02:08

Merge branch 'main' into main

82f6f48

ltaodream force-pushed the main branch from 97f3e1f to 82f6f48 Compare August 25, 2025 05:11

ltaodream mentioned this pull request Aug 25, 2025

[Feature] Add tile-based method of supporting large VPT in moe_fused_gate kernel #9579

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ltaodream closed this Aug 25, 2025

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