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[b200] support trt-llm allreduce fuse rms_norm_add kernel #7621
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Summary of Changes
Hello @BBuf, 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!
This pull request focuses on optimizing the performance of distributed inference by integrating a fused allreduce and RMS normalization kernel. By leveraging the FlashInfer library, it aims to reduce latency for these common operations, particularly beneficial in multi-GPU environments for large language models.
Highlights
- Performance Optimization: Introduced a new fused kernel for
allreduce
andRMSNorm
operations, leveraging the FlashInfer library to improve performance in Tensor Parallelism setups, as demonstrated by a reported latency reduction from 13.5us to 8.7us. - FlashInfer Integration: Added a new module (
flashinfer_fusion.py
) to manage FlashInfer workspace and expose the fusedallreduce_add_rmsnorm
function, which utilizes FlashInfer'strtllm_allreduce_fusion
API. - Conditional Execution: Modified the
communicator
andlayernorm
modules to conditionally utilize the new fused operation when FlashInfer is available and a multi-GPU environment is detected, falling back to existing implementations otherwise.
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Code Review
This pull request introduces a performance optimization by leveraging a fused all-reduce and RMS norm kernel from FlashInfer. The changes are well-structured, with a new flashinfer_fusion.py
module to handle the integration and workspace management, and modifications in communicator.py
and layernorm.py
to enable this new path. The implementation looks promising, but a critical correctness issue in the fallback logic and a high-severity issue related to workspace management have been identified. Once these issues are addressed, this will be a great addition to improve performance.
|
||
return self.forward(x, residual) |
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The fallback logic in forward_with_allreduce_fusion
skips the tensor_model_parallel_all_reduce
operation when the fused kernel is not available, leading to incorrect results in multi-GPU environments. The all-reduce operation must be performed before applying the layer norm to maintain correctness.
if is_flashinfer_available() and residual is not None:
from sglang.srt.layers.flashinfer_fusion import flashinfer_allreduce_add_rmsnorm
from sglang.srt.distributed import get_tensor_model_parallel_world_size, tensor_model_parallel_all_reduce
# Only use fusion operation in multi-GPU environment
if get_tensor_model_parallel_world_size() > 1:
fused_result = flashinfer_allreduce_add_rmsnorm(
input_tensor=x,
residual=residual,
weight=self.weight,
eps=self.variance_epsilon,
)
if fused_result[0] is not None:
return fused_result
x = tensor_model_parallel_all_reduce(x)
return self.forward(x, residual)
if (not _workspace_manager.initialized or | ||
_workspace_manager.world_size != world_size): | ||
_workspace_manager.initialize( |
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The condition to check if the workspace needs re-initialization should also include a check for max_token_num
and hidden_dim
to ensure the workspace is re-initialized if these values change. If these parameters change without re-initialization, it could lead to memory corruption or crashes.
if (not _workspace_manager.initialized or
_workspace_manager.world_size != world_size or
_workspace_manager.max_token_num != max_token_num or
_workspace_manager.hidden_dim != hidden_dim):
if hasattr(layernorm, 'forward_with_allreduce_fusion'): | ||
hidden_states, residual = layernorm.forward_with_allreduce_fusion(hidden_states, residual) | ||
else: | ||
hidden_states = tensor_model_parallel_all_reduce(hidden_states) | ||
hidden_states, residual = layernorm(hidden_states, residual) |
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if self.initialized and self.ipc_handles is not None: | ||
try: | ||
_flashinfer_comm.trtllm_destroy_ipc_workspace_for_all_reduce( | ||
self.ipc_handles, | ||
group=dist.group.WORLD | ||
) | ||
except Exception as e: | ||
logger.warning(f"Failed to cleanup FlashInfer workspace: {e}") | ||
finally: | ||
self.workspace_tensor = None | ||
self.ipc_handles = None | ||
self.initialized = False |
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Consider adding a check to ensure self.initialized
is False before attempting to clean up the workspace. This could prevent potential issues if cleanup
is called multiple times without a corresponding initialize
call.
if self.initialized and self.ipc_handles is not None:
if not self.initialized:
return
try:
Refer to trt-llm , I change sglang python3 test/srt/parse_results.py dsv3_main.jsonl
Saved summary to: dsv3_main_summary.csv
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
| | max_concurrency | input_throughput | output_throughput | mean_ttft_ms | median_ttft_ms | p99_ttft_ms | mean_tpot_ms | median_tpot_ms | p99_tpot_ms | per_user_throughput |
+====+===================+====================+=====================+================+==================+===============+================+==================+===============+=======================+
| 0 | 1.000 | 133.166 | 133.166 | 176.653 | 153.561 | 226.394 | 7.337 | 7.599 | 8.060 | 133.166 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
| 1 | 4.000 | 390.269 | 390.269 | 254.178 | 207.857 | 646.446 | 9.880 | 9.689 | 11.796 | 97.567 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
| 2 | 16.000 | 1018.889 | 1018.889 | 275.613 | 179.920 | 643.978 | 14.551 | 14.247 | 20.015 | 63.681 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
➜ sglang python3 test/srt/parse_results.py dsv3_pr.jsonl
Saved summary to: dsv3_pr_summary.csv
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
| | max_concurrency | input_throughput | output_throughput | mean_ttft_ms | median_ttft_ms | p99_ttft_ms | mean_tpot_ms | median_tpot_ms | p99_tpot_ms | per_user_throughput |
+====+===================+====================+=====================+================+==================+===============+================+==================+===============+=======================+
| 0 | 1.000 | 137.713 | 137.713 | 167.537 | 153.134 | 219.778 | 7.098 | 6.992 | 7.747 | 137.713 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
| 1 | 4.000 | 409.847 | 409.847 | 208.332 | 156.417 | 537.090 | 9.388 | 9.090 | 11.284 | 102.462 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
| 2 | 16.000 | 1055.758 | 1055.758 | 269.626 | 164.852 | 643.074 | 13.910 | 13.589 | 18.392 | 65.985 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+ bs=1, 3.4%+ |
and is_flashinfer_available() | ||
and hasattr(layernorm, "forward_with_allreduce_fusion") | ||
and global_server_args_dict["enable_flashinfer_allreduce_fusion"] | ||
and hidden_states.shape[0] <= 1024 |
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hidden_state.numel() * hidden_state.element_size() < THRESHOLD
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Make sense, I'll update it.
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I think this feature could also be applied to other models. However, since different models may have varying hidden_size values, directly checking max_token_num
seems more general. Regarding the token number 1024: This value was estimated based on the workspace threshold in trt_llm, using ds-v3's hidden_size as a reference. With 1024 tokens, it only allocates an additional ~10MB buffer, so the memory overhead is minimal.
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Hi,
I think the max_workspace settings in trt-llm are not for these flashinfer kernels (allreduce_fusion_xxx).
The max_token_number should be set as the actual max token number.
The default value of use_oneshot should be False. In these two cases it could be set as True. (https://github.com/NVIDIA/TensorRT-LLM/blob/a1235ee9781050e562bbce2c86f714c38d434dbe/cpp/tensorrt_llm/thop/allreduceOp.cpp#L416-L429)
<!-- .github/pull_request_template.md --> ## 📌 Description ref sgl-project/sglang#7621 <!-- What does this PR do? Briefly describe the changes and why they’re needed. --> ## 🔍 Related Issues <!-- Link any related issues here --> ## 🚀 Pull Request Checklist Thank you for contributing to FlashInfer! Before we review your pull request, please make sure the following items are complete. ### ✅ Pre-commit Checks - [x] I have installed `pre-commit` by running `pip install pre-commit` (or used your preferred method). - [x] I have installed the hooks with `pre-commit install`. - [x] I have run the hooks manually with `pre-commit run --all-files` and fixed any reported issues. > If you are unsure about how to set up `pre-commit`, see [the pre-commit documentation](https://pre-commit.com/). ## 🧪 Tests - [x] Tests have been added or updated as needed. - [x] All tests are passing (`unittest`, etc.). ## Reviewer Notes <!-- Optional: anything you'd like reviewers to focus on, concerns, etc. -->
…-project/sglang into support_allreduce_rmsnorm_add_fusion
<!-- .github/pull_request_template.md --> ## 📌 Description <!-- What does this PR do? Briefly describe the changes and why they’re needed. --> We add some notes on each api to help integration to vllm/sgl. And we try to fix the error in issues. To avoid workspace size overflow, the max lamport communication size MAX_COMM_SIZE (computed as hidden * max_token) should be less than round_down(INT_32_MAX, 2MB). For any larger size, it would be rewritten to this value with a warning "warning: lamport_comm_size 2147483648 is greater than MAX_COMM_SIZE 2145386496, set to MAX_COMM_SIZE". If the actual lamport communication size (computed as hidden * token_num) exceeds this MAX_COMM_SIZE, always set use_oneshot to be False. Otherwise, you could set use_oneshot on your preference; and for the min-latency case, set it to be (token_num <= 128). ## 🔍 Related Issues #1223 sgl-project/sglang#7621 ## 🚀 Pull Request Checklist Thank you for contributing to FlashInfer! Before we review your pull request, please make sure the following items are complete. ### ✅ Pre-commit Checks - [x] I have installed `pre-commit` by running `pip install pre-commit` (or used your preferred method). - [x] I have installed the hooks with `pre-commit install`. - [x] I have run the hooks manually with `pre-commit run --all-files` and fixed any reported issues. > If you are unsure about how to set up `pre-commit`, see [the pre-commit documentation](https://pre-commit.com/). ## 🧪 Tests - [x] Tests have been added or updated as needed. - [x] All tests are passing (`unittest`, etc.). ## Reviewer Notes <!-- Optional: anything you'd like reviewers to focus on, concerns, etc. --> --------- Co-authored-by: averyh <averyh@nvidia.com>
* Use seq_len_fill_value in the cuda graph runners (sgl-project#7233) * support custom weight loader for model runner (sgl-project#7122) Co-authored-by: kavioyu <kavioyu@tencent.com> * Fix AMD speculative decoding (sgl-project#7252) * [Refactor] OAI Server components (sgl-project#7167) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * OAI Server Skeleton & Core Utility Endpoints (sgl-project#7179) * [amd] Opt dsv3 moe (sgl-project#7160) Co-authored-by: wunhuang <wunhuang@amd.com> * update ci node for xeon (sgl-project#7265) * feat: mtp support dp-attention (sgl-project#6081) Co-authored-by: austindeng <austindeng@tencent.com> Co-authored-by: tianqilin.99 <tianqilin.99@bytedance.com> Co-authored-by: Qiaolin Yu <liin1211@outlook.com> Co-authored-by: ch-wan <cwan39@gatech.edu> * support qwen2 running on ascend npu device (sgl-project#7022) Co-authored-by: 刁莹煜 <diaoyingyu1@hisilicon.com> * Fix Deepseek R1 0528 FP4 tensor name mismatch issue during weights loading. (sgl-project#7164) * bugfix(tool call ebnf): Fix EBNF generation for optional function parameters (sgl-project#7283) * Fix AWQ Dequant and Weight Loading of deepseek v2 (sgl-project#6842) * fix: resolve b200 dsv3 mtp issue (sgl-project#7286) * ci: Fix test_ebnf_generate_all_optional_function_params (sgl-project#7288) * fix: only enable flash_attn test on sm80 sm90 (sgl-project#7289) * [PD] Support get local ip from NIC for PD disaggregation (sgl-project#7237) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * [PD] Add custom memory pool option to support Mooncake PD with NVLink (sgl-project#7264) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * Upstreaming hicache bug fixes (sgl-project#7267) * Update python API of activation, topk, norm and rope and remove vllm dependency (sgl-project#6614) Co-authored-by: Wu, Chunyuan <chunyuan.wu@intel.com> Co-authored-by: jianan-gu <jianan.gu@intel.com> Co-authored-by: sdp <sdp@gnr799219.jf.intel.com> * Fix hicache benchmark script bug - some sampled input_request is [] (sgl-project#7300) * chore: change logs from`INFO` to `DEBUG` for dp and add force quit for tokenizer manager (sgl-project#7251) * update invalid link in doc (sgl-project#7297) * Fix mini_lb for PD with long output: limit chunk size of decode response (sgl-project#7301) Signed-off-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com> Co-authored-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com> * Fix profiler error when there are idle passes (sgl-project#7003) * [pd] optimize dockerfile for pd disaggregation (sgl-project#7319) Co-authored-by: zhyncs <me@zhyncs.com> * Merge PDLB (Prefill-Decode Load Balancer) into SGLang Router (sgl-project#7096) * Add more refactored openai test & in CI (sgl-project#7284) * fix: resolve blackwell deepep image issue (sgl-project#7331) * add seed in CPU UTs to avoid flaky failure (sgl-project#7333) * Multi-Stage Awake: Support Resume and Pause KV Cache and Weights separately (sgl-project#7099) * Reintroduce tiny fix sampler error when prob is not contiguous (sgl-project#7354) * [Refactor] Clean up radix cache related API (sgl-project#7303) Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu> * Put `_normalize_rid` before other normalization in `io_struct` (sgl-project#7363) * [PD] Transfer hidden states for mtp when disaggregation (sgl-project#7242) * [Bugfix][PD] Set conclude state before clear when failure happens (sgl-project#7362) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * docs: update installation (sgl-project#7366) * [Docker] optimize dockerfile remove deepep and blackwell merge it to… (sgl-project#7343) Co-authored-by: Yineng Zhang <me@zhyncs.com> * Clean unused import for mimo mtp model (sgl-project#7370) * [Bugfix]Fix hang bug using dp attention with HiRadixCache (sgl-project#7159) Signed-off-by: huanglong <huanglong@linux.alibaba.com> * [Doc] add embedding rerank doc (sgl-project#7364) * Fix judgment condition for enabling Deepseek V3/R1 shared expert fusion optimization (sgl-project#7371) * Feat/refactor embedding server (sgl-project#7322) * Purge VerlEngine (sgl-project#7326) Signed-off-by: Ata Fatahi <immrata@gmail.com> * support return logprobs for pipeline (sgl-project#7356) Co-authored-by: Zhang Kaihong <zhangkaihong.zkh@alibaba-inc.com> * [PD] Optimize custom mem pool usage and bump mooncake version (sgl-project#7393) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * Support THUDM/GLM-4-0414 (GLM-Z1) Glm4ForCausalLM architecture. (sgl-project#5485) * Refine OpenAI serving entrypoint to remove batch requests (sgl-project#7372) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> Co-authored-by: Chang Su <csu272@usc.edu> * [Feature] Comprehensive Hybrid Parallelism Support (sgl-project#6389) * [DeepSeekNextN] fix: residual of head norm can be None (sgl-project#7398) * [OAI refactor] Add rerank and score serving (sgl-project#7399) Co-authored-by: Chang Su <chang.s.su@oracle.com> * [OAI Server Refactor] [ChatCompletions & Completions] Implement UsageInfo Processor (sgl-project#7360) Co-authored-by: Chang Su <chang.s.su@oracle.com> * Fix All-Gather under world size one (sgl-project#7219) * Optimize DP attn scheduling for speculative decoding (sgl-project#7285) * Update usage_processor.py (sgl-project#7402) * Fix 7285 Merge Conflicts (sgl-project#7403) * chore: upgrade mooncake-transfer-engine 0.3.4 (sgl-project#7401) * [OAI Server Refactor] [ChatCompletions & Completions] Support Return Hidden State (sgl-project#7329) Signed-off-by: keru <rukeyang@gmail.com> * Remove batches api in docs & example (sgl-project#7400) * [BugFix]: fix EmbeddingReqInput single input error (sgl-project#7396) * [BugFix]fix qwen25 invoke function call streaming responses with curly braces as the starting indicator (sgl-project#7394) * fix overlap pagecount (sgl-project#6984) Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu> * fix: Fix CI test_function_call_parser.py (sgl-project#7425) * Fix CPU offloading for MLA memory pool (sgl-project#7409) * [fix] PD disaggregation when enable mtp and tp!=dp (sgl-project#7420) * feat(oai refactor): Replace `openai_api` with `entrypoints/openai` (sgl-project#7351) Co-authored-by: Jin Pan <jpan236@wisc.edu> * Refactor LoRAManager and LoRAMemoryPool state management logic for dynamic LoRA loading support (sgl-project#7412) * refactor(test): reorganize OpenAI test file structure (sgl-project#7408) * [minor] simplify the `TokenToKVPoolAllocator` (sgl-project#7414) * Tiny add logging for GC (sgl-project#7406) * FlashInfer NVFP4 MoE with EP & 2-stream shared expert (sgl-project#7327) Co-authored-by: JieXin Liang <Alcanderian@users.noreply.github.com> Co-authored-by: alcanderian <alcanderian@gmail.com> * Remove copy after bmm (sgl-project#7441) * Fix torch compile run (sgl-project#7391) Co-authored-by: wunhuang <wunhuang@amd.com> Co-authored-by: Sai Enduri <saimanas.enduri@amd.com> * [misc] Add PD service discovery support in router (sgl-project#7361) * add fused moe config for qwen3 in triton3.3.1 (sgl-project#7445) * Fix CUDA Graph Check under Deepep with DP FFN (sgl-project#7451) * Update hyperparameter_tuning.md (sgl-project#7454) * feat: integrate deepgemm into EPMoE (sgl-project#6821) Co-authored-by: tianqilin.99 <tianqilin.99@bytedance.com> Co-authored-by: TianQiLin666666 <1834987979@qq.com> Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com> * Solve docker build failed in the virtual machine (sgl-project#7290) Co-authored-by: wunhuang <wunhuang@amd.com> Co-authored-by: Sai Enduri <saimanas.enduri@amd.com> Co-authored-by: HAI <hixiao@gmail.com> * Fix a bug in BatchTokenIDOut & Misc style and dependency updates (sgl-project#7457) * [CI] Upgrade mooncake to 0.3.4.post1 to fix 8 gpu tests (sgl-project#7472) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * Fix prefill OOM due to wrong token calculation when page > 1 (sgl-project#7397) * feat(func_call): Add more check in `BaseFormatDetector.parse_streaming_increment` (sgl-project#7479) * Fix dtype for idle input in spec decoding (sgl-project#7456) * update mooncake in dockerfile (sgl-project#7480) * kvcache io kernels and test case (sgl-project#7382) * [perf] slightly imporve DeepSeek-R1-FP4 TP8 (sgl-project#7481) * Quick fix for DeepGemm requant to also cover MTP. (sgl-project#7378) * Support weight loading without mmap (sgl-project#7469) * ci: Revert openai_server related tests in AMD suites (sgl-project#7449) * Perormance: Enable cuda graph for dp idle batch (sgl-project#7269) Co-authored-by: austindeng <austindeng@tencent.com> Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com> Co-authored-by: ch-wan <cwan39@gatech.edu> * bugfix: Prevent global mutation of conv.stop_str across requests (sgl-project#7347) Co-authored-by: Chang Su <chang.s.su@oracle.com> * Fix RequestValidationError response format (sgl-project#7487) * Fix MTP with Deepseek R1 Fp4 (sgl-project#7376) * chore: bump sgl-kernel v0.2.0 (sgl-project#7490) * chore: bump v0.4.8 (sgl-project#7493) * [AMD] add aiter fused moe in DeepEP path (sgl-project#7268) * enable aiter_biased_grouped_topk kernel (sgl-project#7423) * [PD Disaggregation] replace transfer with batch transfer for better performance (sgl-project#7236) * Remove cumsum_buffer initilization (sgl-project#7439) * [benchmark] fbgemm benchmark support bandwidth report and support fbgemm_cutlass_gmm (sgl-project#7422) * Support multi-thread model weight loading (sgl-project#7277) * [PD] NIXL: Register kv args in advance and cleanup finished requests (sgl-project#6717) * fix: Add `--model` as an alias for `--model-path` in server_args (sgl-project#7505) * misc: Improvement to serving_chat.py and add more ut (sgl-project#7489) * Fuse sorted_token_ids padding to moe_align_block_size kernel (sgl-project#7437) * [OAI] patch origin request_id logic (sgl-project#7508) * [PD][Spec] Fix hidden state transfer for spec decode (sgl-project#7516) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * EPLB support for MTP (sgl-project#7510) * clean duplicate code (sgl-project#7512) * [ci] add router benchmark script and CI (sgl-project#7498) * fix: force synchronization between TP workers when update_weights (sgl-project#6626) Co-authored-by: dangkai.dk <dangkai.dk@alibaba-inc.com> * [CPU] [BF16] Call fused_experts_cpu, weight_packed_linear and bmm_cpu kernel in DeepSeek model (sgl-project#6641) Co-authored-by: Thien Tran <gau.nernst@yahoo.com.sg> * [CI] Upgrade mooncake to v0.3.4.post2 to fix potential slice failed bug (sgl-project#7522) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * npu fused op (sgl-project#7386) Co-authored-by: Li Junwen <lijunwen13@hisilicon.com> * feat: send kvmetrics from sglang scheduler (sgl-project#6721) * [PD] Add different TP sizes support for no-MLA models (sgl-project#6793) Co-authored-by: shangmingc <csmthu@gmail.com> Co-authored-by: Shangming Cai <caishangming@linux.alibaba.com> * enable aiter fp8 blockscale quant (sgl-project#7520) * take aiter get_rope back (sgl-project#7521) * Fix typo of flash_cache (sgl-project#7513) * feat: add return hidden_states at async generation (sgl-project#7507) * minor: 'role' must be system/assistant/tool, but case insensitive for now (sgl-project#7499) * Fix FP8 KV Cache Support in FA3 Backend (sgl-project#7148) * Fix gathered_buffer issues in tbo (sgl-project#7531) * [PD] Raise error for incompatible mooncake version and some minor fixes (sgl-project#7527) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * [CMake] Fix sgl-kernel CMakeLists for Blackwell (sgl-project#7543) * Add Tencent HunYuanMoEV1 model support (sgl-project#7549) * Update seed in CPU UTs to avoid flaky failure with single test (sgl-project#7544) * chore: improve ci bug reporting (sgl-project#7542) * chore: remove vlm unnecessary import (sgl-project#7541) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> Co-authored-by: yhyang201 <yhyang201@gmail.com> Co-authored-by: Mick <mickjagger19@icloud.com> * chore: bump v0.4.8.post1 (sgl-project#7559) * [PD][NIXL] Set is_sorted=False to fix NIXL_ERR_NOT_FOUND (sgl-project#7330) * [Fix] incorrect assert in EPLB (sgl-project#7575) * Updates Gemma3n MLP layer to adapt latest transformers version (sgl-project#7573) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * Fix MTP error when enabling two-batch overlap (sgl-project#7569) * Add e2e test for multi instance multi stage memory release/resume occupuation (sgl-project#7208) Signed-off-by: Ata Fatahi <immrata@gmail.com> * [CI] Add CI Testing for Prefill-Decode Disaggregation with Router (sgl-project#7540) * Updates transformers and timm dependencies (sgl-project#7577) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * feat: support compatibility between MTP and two-batch-overlap (sgl-project#7225) Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com> * Move multimodal processors into a separate folder (sgl-project#7581) * Fix broken CI TestVILAServer (sgl-project#7610) * [router] add centralized configuration module for sgl-router (sgl-project#7588) * Fix: Minicpm (sgl-project#7612) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * Hybrid kv cache for LLaMA4 (sgl-project#6563) Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com> Co-authored-by: tarinkk <rt572@physics.rutger.edu> Co-authored-by: tarinkk <rt572@rutgers.physics.edu> Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com> * [CPU] add optimizations for INT8 and FP8 DeepSeek (sgl-project#6769) Co-authored-by: Zheng, Beilei <beilei.zheng@intel.com> * Tiny add logs for expert location updater (sgl-project#7308) * Fix flakiness in LoRA batch test. (sgl-project#7552) * [BUG] fix local_rank in initialize_dp_attention (sgl-project#7584) * Support dynamic LoRA loading / unloading in engine/server API (sgl-project#7446) * [PD] Respect sampling_params.max_new_tokens when PD disaggregation is activated (sgl-project#7598) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * fix unit tests (sgl-project#7618) * Let ep_scatter support arbitrary strides / ue8m0 format (sgl-project#7309) * Let EP prefill support new DeepGEMM (sgl-project#7310) * docs: add gb200 nvl72 and a16z grant (sgl-project#7620) * oai: Adds support for OpenAI chat completions API in bench_serving (sgl-project#7036) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> Co-authored-by: yhyang201 <47235274+yhyang201@users.noreply.github.com> Co-authored-by: Mick <mickjagger19@icloud.com> * [bugfix] Remove PR comment posting from Rust benchmark workflow (sgl-project#7625) * [Minor] clean up multimodal processor and tokenizer manager (sgl-project#7624) * Add dsv3 fused a gemm to sgl-kernel (sgl-project#7630) * Add @mickqian as the CODEOWNERS of multimodal (sgl-project#7636) * Fix stream reasoning parser and Adds Kimi reasoning parser (sgl-project#7432) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * Fix sgl-router startup crash (sgl-project#7619) * [bugfix] fix runtime dropping panic in editable (sgl-project#7628) * Move files related to EPLB (sgl-project#7580) * [misc] reduce weird rope_scaling_factor warning (sgl-project#7176) * [AMD] Add unit-test-sgl-kernel-amd to AMD CI (sgl-project#7539) * Update CODEOWNERS (sgl-project#7640) * [EAGLE] remove a wrong adjustment for page_size > 1 & topk > 1 in server_args.py (sgl-project#7643) * [CPU] add c++ kernel to bind CPU cores and memory node (sgl-project#7524) * Improve streaming, log_level, memory report, weight loading, and benchmark script (sgl-project#7632) Co-authored-by: Kan Wu <wukanustc@gmail.com> * Add dsv3 router gemm kernel (sgl-project#7627) * chore: upgrade flashinfer v0.2.7 jit (sgl-project#7663) * [doc] update lws doc for pd (sgl-project#7318) * Fix: sync prepare_fp8_layer_for_marlin with latest vllm changes (sgl-project#7648) * Add small requirements for benchmark/parse_result tools (sgl-project#7671) * [CPU] remove process_group from inputs of shm_allreduce and shm_allgather (sgl-project#7486) * chore: bump sgl-kernel v0.2.1 (sgl-project#7675) * support llama4 eagle3 (sgl-project#6985) Co-authored-by: shuaills <shishuaiuoe@gmail.com> Co-authored-by: Shenggui Li <somerlee.9@gmail.com> Co-authored-by: Yingyi Huang <yingyihuang2000@outlook.com> Co-authored-by: yizhang2077 <1109276519@qq.com> * Refactor mm processors and Enable mixed modality processing (sgl-project#7629) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * upgrade sgl kernel to 0.2.1 for main (sgl-project#7676) * add description for llama4 eagle3 (sgl-project#7688) * fix(model loader): use safe_open to prevent file handle leaks. (sgl-project#7684) * chore: upgrade flashinfer v0.2.7.post1 (sgl-project#7698) * Improve error handling for requests with unloaded LoRA path(s) (sgl-project#7642) * Apply dsv3_fused_a_gemm kernel (sgl-project#7635) * Fix GPTQMarlinMoE (sgl-project#7697) * [1/n] apply wna16marlin kernel in moe weight only quantization (sgl-project#7683) Co-authored-by: 晟海 <huangtingwei.htw@antgroup.com> Co-authored-by: yych0745 <1398089567@qq.com> Co-authored-by: HandH1998 <1335248067@qq.com> Co-authored-by: 弋云 <yiyun.wyt@antgroup.com> Co-authored-by: walker-ai <2398833647@qq.com> * Apply dsv3 router gemm kernel for deepseek-r1 fp4 (sgl-project#7677) * [AMD] Temporarily disable test_no_overlap_scheduler and test_vision_chunked_prefill (sgl-project#7717) * [RL] add --skip-warmup (sgl-project#7416) * [RL] support update_weights_from_distributed with different group and multiple weights (sgl-project#7292) * [router] add --log-level to sgl-router (sgl-project#6512) * [b200] support trt-llm allreduce fuse rms_norm_add kernel (sgl-project#7621) * [CPU] Bind threads and numa node for each TP rank (sgl-project#6549) Co-authored-by: srinarayan-srikanthan <srinarayan.srikanthan@intel.com> * Support non-contiguous query input for extend/decode attention (sgl-project#7462) * Support updating weights at once by stopping all requests (sgl-project#6698) Signed-off-by: Tianyu Zhou <albert.zty@antgroup.com> Co-authored-by: Zilin Zhu <zhuzilinallen@gmail.com> * Fix num_tokens_pre_allocated in disaggregation log (sgl-project#7714) * [CPU] [sgl-kernel] set dispatch key of initialize to CatchAll (sgl-project#7734) * [CPU] fix all_reduce and all_gather (sgl-project#6770) Co-authored-by: blzheng <beilei.zheng@intel.com> * fix awq and dsv3 fused gemm compatible (sgl-project#7735) * [CI][Router] Fix bench_one_batch_server for pd router test (sgl-project#7731) Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> * Add CUTLASS FP8 Blockscale MoE kernel for Hopper architecture (sgl-project#7278) Co-authored-by: HydraQYH <QYH820@Outlook.com> Co-authored-by: TianQiLin666666 <1834987979@qq.com> * fix dsv3 fused proj check (sgl-project#7738) * Ascend attention backend(PA&MLA) (sgl-project#7722) Co-authored-by: Maksim <makcum888e@mail.ru> Co-authored-by: VDV1985 <vladdv85@mail.ru> * [fix] fix dsv3_router_gemm filter (sgl-project#7750) * [CPU] refine CPU integration code (sgl-project#7647) * [CPU] support the case where num_attention_heads or intermediate_size is not divisible by the TP size (sgl-project#6771) * support qwen3 dense model dp attention (sgl-project#7681) * [optimize] add two stream norm for qwen3 (sgl-project#7740) Co-authored-by: ispobock <ispobaoke@gmail.com> * feat: use D2D instead of H2H in pp (sgl-project#7673) Co-authored-by: alpha-baby <fujianhao1997@qq.com> * [Bug] add flashinfer bool check for fusedmoe in Qwen moe models (sgl-project#7723) * [fix] put cpu in the first priority in get_device() (sgl-project#7752) * [optimize] fuse renormalize into moe_topk_softmax (sgl-project#7744) Co-authored-by: ispobock <ispobaoke@gmail.com> * chore: bump sgl-kernel 0.2.2 (sgl-project#7755) * fix CI: update native api ipynb (sgl-project#7754) Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> * fuse renormal into moe topk softmax kernel python code (sgl-project#7751) Co-authored-by: ispobock <ispobaoke@gmail.com> Co-authored-by: zhyncs <me@zhyncs.com> * Remove type conversion and fix id map in topk (sgl-project#7759) * Add V2-lite model test (sgl-project#7390) Co-authored-by: DiweiSun <105627594+DiweiSun@users.noreply.github.com> * refactor llama4 dp attention logic (sgl-project#7729) * fix(docs): fix the broken link in `docs/references/production_metrics.md` (sgl-project#7741) Signed-off-by: rudeigerc <rudeigerc@gmail.com> * [fix] update bench_speculative.py for compatibility (sgl-project#7764) Signed-off-by: Kay Yan <kay.yan@daocloud.io> * Move mem_fraction_static adjustment for multimodal models to `server_args.py` & Fix session control & Other cleanups (sgl-project#7748) * [RL] Add --nccl-port to prevent port conflict (sgl-project#7418) * [RL] add pause and continue generation for async rl training (sgl-project#7419) * [Fix] Alloc return type error (sgl-project#7778) Signed-off-by: Capronir <839972205@qq.com> * [feat] Support EAGLE3 for Qwen (sgl-project#7745) Co-authored-by: 纬杭 <ximing.wxm@antgroup.com> Co-authored-by: zyksir <zyksir@outlook.com> * saving hidden_states.clone() (sgl-project#7705) * [1/n]: add cutlass W4A8 moe kernel for hopper architecture (sgl-project#7772) Signed-off-by: yangsijia.614 <yangsijia.614@bytedance.com> Co-authored-by: yicwang <yichen.wang@bytedance.com> * add model: qwen2-audio (sgl-project#7596) * Optimize Hopper CUTLASS FP8 Blockwise Grouped GEMM Kernel in Small K Scenario (sgl-project#7782) * Embedding parallel by attn_tp (sgl-project#7623) * fix: fix apply_shuffle_mul_sum (sgl-project#7444) * chore: bump sgl-kernel v0.2.3 (sgl-project#7784) * fix: use nvidia-nccl-cu12 2.27.5 (sgl-project#7787) * DP Attention with Auto DeepEP Dispatch (sgl-project#7222) * chore: upgrade sgl-kernel v0.2.3 (sgl-project#7786) * Fix incorrect spec_num_draft_tokens in draft_extend (sgl-project#7757) * [fix] fix misusing of is_cuda (sgl-project#7790) * Add treemask mode to build_eagle_tree & release sgl-kernel 0.2.3 (sgl-project#7756) Co-authored-by: Pranjal Shankhdhar <pranjal.ssh@gmail.com> * chore: bump sgl-kernel v0.2.4 (sgl-project#7800) * ci: fix port args (sgl-project#7792) * Fix CI test OOM issue. (sgl-project#7799) * chore: upgrade sgl-kernel v0.2.4 (sgl-project#7801) * chore: bump v0.4.9 (sgl-project#7802) * fix merge conflict issue * fix hpu attention nonetyep issue * fix alignment * fix alignment2 * Ci failure fixes * fix attention-backend choices --------- Signed-off-by: Xinyuan Tong <justinning0323@outlook.com> Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com> Signed-off-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com> Signed-off-by: huanglong <huanglong@linux.alibaba.com> Signed-off-by: Ata Fatahi <immrata@gmail.com> Signed-off-by: keru <rukeyang@gmail.com> Signed-off-by: Tianyu Zhou <albert.zty@antgroup.com> Signed-off-by: rudeigerc <rudeigerc@gmail.com> Signed-off-by: Kay Yan <kay.yan@daocloud.io> Signed-off-by: Capronir <839972205@qq.com> Signed-off-by: yangsijia.614 <yangsijia.614@bytedance.com> Signed-off-by: Mohit Sinha <msinha@habana.ai> Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com> Co-authored-by: KavioYu <67678385+yukavio@users.noreply.github.com> Co-authored-by: kavioyu <kavioyu@tencent.com> Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com> Co-authored-by: yhyang201 <47235274+yhyang201@users.noreply.github.com> Co-authored-by: kk <43161300+kkHuang-amd@users.noreply.github.com> Co-authored-by: wunhuang <wunhuang@amd.com> Co-authored-by: DiweiSun <105627594+DiweiSun@users.noreply.github.com> Co-authored-by: u4lr451 <u4lr451@gmail.com> Co-authored-by: austindeng <austindeng@tencent.com> Co-authored-by: tianqilin.99 <tianqilin.99@bytedance.com> Co-authored-by: Qiaolin Yu <liin1211@outlook.com> Co-authored-by: ch-wan <cwan39@gatech.edu> Co-authored-by: Yijie Zhu <762412795@qq.com> Co-authored-by: 刁莹煜 <diaoyingyu1@hisilicon.com> Co-authored-by: Charles Chen <pychen96@gmail.com> Co-authored-by: Chang Su <chang.s.su@oracle.com> Co-authored-by: AniZpZ <zhuangsen.zp@antgroup.com> Co-authored-by: Yineng Zhang <me@zhyncs.com> Co-authored-by: shangmingc <caishangming@linux.alibaba.com> Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu> Co-authored-by: YanbingJiang <yanbing.jiang@intel.com> Co-authored-by: Wu, Chunyuan <chunyuan.wu@intel.com> Co-authored-by: jianan-gu <jianan.gu@intel.com> Co-authored-by: sdp <sdp@gnr799219.jf.intel.com> Co-authored-by: Binyao Jiang <byjiang1996@gmail.com> Co-authored-by: ishandhanani <82981111+ishandhanani@users.noreply.github.com> Co-authored-by: linzhuo <15313137931lz@gmail.com> Co-authored-by: ch-tiger1 <tiger@ch-tech.ip-ddns.com> Co-authored-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com> Co-authored-by: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com> Co-authored-by: ybyang <10629930+whybeyoung@users.noreply.github.com> Co-authored-by: Simo Lin <linsimo.mark@gmail.com> Co-authored-by: Jinn <47354855+jhinpan@users.noreply.github.com> Co-authored-by: Stefan He <hebiaobuaa@gmail.com> Co-authored-by: DarkSharpness <76582120+DarkSharpness@users.noreply.github.com> Co-authored-by: Atream <80757050+Atream@users.noreply.github.com> Co-authored-by: Li Hui <lambert80.ios@gmail.com> Co-authored-by: Huang Long <121648372+LLLL114@users.noreply.github.com> Co-authored-by: woodx <124784234+woodx9@users.noreply.github.com> Co-authored-by: Ata Fatahi <immrata@gmail.com> Co-authored-by: strgrb <zhangkaihong.zkh@antgroup.com> Co-authored-by: Zhang Kaihong <zhangkaihong.zkh@alibaba-inc.com> Co-authored-by: Wenbo Yang <solrex@users.noreply.github.com> Co-authored-by: Chang Su <csu272@usc.edu> Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com> Co-authored-by: Keyang Ru <rukeyang@gmail.com> Co-authored-by: ehuaa <ehuamail@163.com> Co-authored-by: pansicheng <sicheng.pan.chn@gmail.com> Co-authored-by: Liangsheng Yin <hnyls2002@gmail.com> Co-authored-by: Jin Pan <jpan236@wisc.edu> Co-authored-by: Lifu Huang <lifu.hlf@gmail.com> Co-authored-by: Trevor Morris <tmorris@nvidia.com> Co-authored-by: JieXin Liang <Alcanderian@users.noreply.github.com> Co-authored-by: alcanderian <alcanderian@gmail.com> Co-authored-by: Ke Bao <ISPObaoke@163.com> Co-authored-by: Sai Enduri <saimanas.enduri@amd.com> Co-authored-by: Yi Zhang <1109276519@qq.com> Co-authored-by: xutizhou <xutingz@nvidia.com> Co-authored-by: TianQiLin666666 <1834987979@qq.com> Co-authored-by: HAI <hixiao@gmail.com> Co-authored-by: Yuhong Guo <guoyuhong1985@outlook.com> Co-authored-by: huangtingwei <141888744+huangtingwei9988@users.noreply.github.com> Co-authored-by: Alex Sun <alex.s@amd.com> Co-authored-by: valarLip <103567126+valarLip@users.noreply.github.com> Co-authored-by: Francis <38564764+ssssnow@users.noreply.github.com> Co-authored-by: Xiaoyu Zhang <35585791+BBuf@users.noreply.github.com> Co-authored-by: xianzhiT <xianzhitang@tencent.com> Co-authored-by: yilian49 <43861414+yilian49@users.noreply.github.com> Co-authored-by: DangKai <dangkai4u@outlook.com> Co-authored-by: dangkai.dk <dangkai.dk@alibaba-inc.com> Co-authored-by: Thien Tran <gau.nernst@yahoo.com.sg> Co-authored-by: ll819214 <18801269230@163.com> Co-authored-by: Li Junwen <lijunwen13@hisilicon.com> Co-authored-by: zixuanzhang226 <zixuanzhang@bytedance.com> Co-authored-by: Hongbo Xu <1320612015@qq.com> Co-authored-by: shangmingc <csmthu@gmail.com> Co-authored-by: eigen <52445717+yyihuang@users.noreply.github.com> Co-authored-by: mlmz <54172054+minleminzui@users.noreply.github.com> Co-authored-by: Ruihang Lai <ruihangl@cs.cmu.edu> Co-authored-by: Meng, Peng <pengmeng@tencent.com> Co-authored-by: Mick <mickjagger19@icloud.com> Co-authored-by: yhyang201 <yhyang201@gmail.com> Co-authored-by: tarinkk <129432511+tarinkk@users.noreply.github.com> Co-authored-by: tarinkk <rt572@physics.rutger.edu> Co-authored-by: tarinkk <rt572@rutgers.physics.edu> Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com> Co-authored-by: Zheng, Beilei <beilei.zheng@intel.com> Co-authored-by: Sheng Qi <shengqi2018@pku.edu.cn> Co-authored-by: finetune <82650881+finetunej@users.noreply.github.com> Co-authored-by: Hubert Lu <55214931+hubertlu-tw@users.noreply.github.com> Co-authored-by: Kan Wu <wukanustc@gmail.com> Co-authored-by: Baizhou Zhang <sobereddiezhang@gmail.com> Co-authored-by: narutolhy <582909902@qq.com> Co-authored-by: lukec <118525388+sleepcoo@users.noreply.github.com> Co-authored-by: shuaills <shishuaiuoe@gmail.com> Co-authored-by: Shenggui Li <somerlee.9@gmail.com> Co-authored-by: Yingyi Huang <yingyihuang2000@outlook.com> Co-authored-by: Simon_CQK <cqk0100@gmail.com> Co-authored-by: Kyungmin Lee <30465912+lkm2835@users.noreply.github.com> Co-authored-by: 晟海 <huangtingwei.htw@antgroup.com> Co-authored-by: yych0745 <1398089567@qq.com> Co-authored-by: HandH1998 <1335248067@qq.com> Co-authored-by: 弋云 <yiyun.wyt@antgroup.com> Co-authored-by: walker-ai <2398833647@qq.com> Co-authored-by: Zilin Zhu <zhuzilinallen@gmail.com> Co-authored-by: srinarayan-srikanthan <srinarayan.srikanthan@intel.com> Co-authored-by: Albert <albert.zty@antgroup.com> Co-authored-by: Ziming Huang <1520787127@qq.com> Co-authored-by: ayrnb <70835312+ayrnb@users.noreply.github.com> Co-authored-by: HydraQYH <QYH820@Outlook.com> Co-authored-by: ronnie_zheng <zl19940307@163.com> Co-authored-by: Maksim <makcum888e@mail.ru> Co-authored-by: VDV1985 <vladdv85@mail.ru> Co-authored-by: ispobock <ispobaoke@gmail.com> Co-authored-by: TianyuZhang1214 <tianyuzhang1214@163.com> Co-authored-by: alpha-baby <fujianhao1997@qq.com> Co-authored-by: Yuchen Cheng <rudeigerc@gmail.com> Co-authored-by: Kay Yan <kay.yan@daocloud.io> Co-authored-by: Caproni <40862361+Capronir@users.noreply.github.com> Co-authored-by: Ximingwang-09 <72070413+Ximingwang-09@users.noreply.github.com> Co-authored-by: 纬杭 <ximing.wxm@antgroup.com> Co-authored-by: zyksir <zyksir@outlook.com> Co-authored-by: SijiaYang <yangsijia.614@bytedance.com> Co-authored-by: yicwang <yichen.wang@bytedance.com> Co-authored-by: Leng Yue <lengyue@lengyue.me> Co-authored-by: Qi Yuhang <45795032+HydraQYH@users.noreply.github.com> Co-authored-by: Gang Chen <13298548+MoonBall@users.noreply.github.com> Co-authored-by: Pranjal Shankhdhar <pranjal.ssh@gmail.com> Co-authored-by: jay <jthakur@habana.ai>
Motivation
I use flashinfer
27060628c32e1217e27564adf24e33273f4c8287
commit to test.In b200:
Acc:
main:
pr:
13.5us->8.7us.
end2end benchmark
Refer to trt-llm , I change
max_token_num
to 1024 and get a better result:bs=1, 3.4%+
bs=8, 5%+
bs=16, 3.6+%
Modifications
Checklist