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[PD] Optimize transfer queue forward logic for dummy rank #6922

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Merged
merged 1 commit into from
Jun 7, 2025

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ShangmingCai
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Motivation

There is no need to run self.update_status(bootstrap_room, KVPoll.WaitingForInput) in each add_transfer_request call, when a request leave the bootstrap queue, it has already been marked as the KVPoll.WaitingForInput status, so we should stop setting this.

A dummy rank will mark the request as KVPoll.Success early when it processes the first chunk, so we don't have to process further chunks anymore.

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Hello @ShangmingCai, 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 team,

Gemini here, providing a summary of this pull request to help everyone quickly understand the changes.

This PR focuses on optimizing the transfer queue logic within the disaggregation component, specifically targeting behavior related to 'dummy ranks'. The primary goals are to eliminate redundant status updates and prevent unnecessary processing of data chunks for requests that have already been completed on these dummy ranks.

Highlights

  • Remove Redundant Status Update: The call to self.update_status(bootstrap_room, KVPoll.WaitingForInput) within the add_transfer_request function has been removed. As noted in the PR description, this status is already set when a request leaves the bootstrap queue, making the subsequent update redundant.
  • Skip Processing for Dummy Ranks: A new check is introduced at the beginning of add_transfer_request. If the current rank is identified as a dummy rank for a given request (indicated by the absence of bootstrap_room in self.transfer_infos) and the request is already marked as successful, the function now returns early. This avoids adding further data chunks to the transfer queue for these completed requests on dummy ranks.

Changelog

  • python/sglang/srt/disaggregation/mooncake/conn.py
    • Added a check at the start of add_transfer_request (around line 565) to exit early if the rank is a dummy rank and the request is already complete.
    • Removed the redundant self.update_status(bootstrap_room, KVPoll.WaitingForInput) call from add_transfer_request (around line 581).
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Code Review

This pull request introduces optimizations for the transfer queue forwarding logic, specifically targeting dummy ranks in the Mooncake backend. The changes aim to avoid redundant status updates and prevent unnecessary processing for dummy ranks that have already completed their tasks. The motivations are clear, and the changes are concise.

One area for clarification is the condition used to identify an already-successful dummy rank to ensure its robustness.

Summary of Findings

  • Condition for dummy rank optimization: The condition bootstrap_room not in self.transfer_infos is used to skip processing for dummy ranks. It's important to ensure this condition robustly identifies dummy ranks that have already completed successfully and doesn't inadvertently affect other scenarios.
  • Redundant status update removal: The removal of self.update_status(bootstrap_room, KVPoll.WaitingForInput) appears justified by the PR's motivation that this status is already set when a request leaves the bootstrap queue. This is a good cleanup.

Merge Readiness

The optimizations proposed in this PR are logical. However, there's a medium-severity point regarding the robustness of the condition for the dummy rank optimization (as detailed in the review comment). It would be beneficial to get clarification on the lifecycle of self.transfer_infos to ensure this optimization behaves as expected under all conditions and doesn't mask other potential issues.

Once this clarification is provided and any potential concerns are addressed, the PR should be in a better state for merging. As a reviewer, I am not authorized to approve pull requests; further review and approval by authorized maintainers will be necessary.

@ShangmingCai
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image This PR should fix this potential problem.

@whybeyoung
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LGTM

@zhyncs zhyncs merged commit 132dad8 into sgl-project:main Jun 7, 2025
75 of 81 checks passed
jianan-gu pushed a commit to jianan-gu/sglang that referenced this pull request Jun 12, 2025
walker-ai pushed a commit to walker-ai/sglang that referenced this pull request Jul 8, 2025
Merge branch 'sgl_20250610_sync_tag047 of [email protected]:Theta/SGLang.git into main

https://code.alipay.com/Theta/SGLang/pull_requests/52


Reviewed-by: 剑川 <[email protected]>


* [Bugfix] Fix slice operation when chunk size mismatch (sgl-project#6697)
* [Bugfix] Fix ChatCompletion endpoint of mini_lb when stream is set (sgl-project#6703)
* [CI] Fix setup of disaggregation with different tp (sgl-project#6706)
* [PD] Remove Unnecessary Exception Handling for FastQueue.get() (sgl-project#6712)
* Fuse routed_scaling_factor in DeepSeek (sgl-project#6710)
* Overlap two kernels in DeepSeek with communication (sgl-project#6711)
* Minor refactor two-batch overlap (sgl-project#6682)
* Speed up when having padding tokens two-batch overlap (sgl-project#6668)
* [Feature] Support Flashinfer fp8 blockwise GEMM kernel on Blackwell (sgl-project#6479)
* Fix LoRA bench (sgl-project#6719)
* temp
* Fix PP for Qwen3 MoE (sgl-project#6709)
* [feat] triton kernel for get_last_loc (sgl-project#6676)
* [fix] more mem for draft_extend cuda_graph (sgl-project#6726)
* [PD] bug fix:  Update status if nixl receiver send a a dummy req. (sgl-project#6720)
* Tune memory arguments on B200 (sgl-project#6718)
* Add DeepSeek-R1-0528 function call chat template (sgl-project#6725)
* refactor(tool call): Fix BaseFormatDetector tool_index issue and refactor `parse_streaming_increment` (sgl-project#6715)
* Add draft extend CUDA graph for Triton backend (sgl-project#6705)
* refactor apply_w8a8_block_fp8_linear in fp (sgl-project#6545)
* [PD] Support completion endpoint (sgl-project#6729)
* PD Rust LB (PO2) (sgl-project#6437)
* Super tiny enable sole usage of expert distribution metrics and update doc (sgl-project#6680)
* Support picking variants of EPLB algorithms (sgl-project#6728)
* Support tuning DeepEP configs (sgl-project#6742)
* [test] add ut and bm for get_last_loc (sgl-project#6746)
* Fix mem_fraction_static for AMD CI (sgl-project#6748)
* [fix][RL] Fix DeepSeekV3ForCausalLM.post_load_weights for multiple update weight (sgl-project#6265)
* Improve EPLB logical to physical dispatch map (sgl-project#6727)
* Update DeepSeek-R1-0528 function call chat template (sgl-project#6765)
* [PD] Optimize time out logic and add env var doc for mooncake (sgl-project#6761)
* Fix aiohttp 'Chunk too big' in bench_serving (sgl-project#6737)
* Support sliding window in triton backend (sgl-project#6509)
* Fix shared experts fusion error (sgl-project#6289)
* Fix one bug in the grouped-gemm triton kernel (sgl-project#6772)
* update llama4 chat template and pythonic parser (sgl-project#6679)
* feat(tool call): Enhance Llama32Detector for improved JSON parsing in non-stream (sgl-project#6784)
* Support token-level quantization for EP MoE (sgl-project#6782)
* Temporarily lower mmlu threshold for triton sliding window backend (sgl-project#6785)
* ci: relax test_function_call_required (sgl-project#6786)
* Add intel_amx backend for Radix Attention for CPU (sgl-project#6408)
* Fix incorrect LoRA weight loading for fused gate_up_proj (sgl-project#6734)
* fix(PD-disaggregation): Can not get local ip (sgl-project#6792)
* [FIX] mmmu bench serving result display error (sgl-project#6525) (sgl-project#6791)
* Bump torch to 2.7.0 (sgl-project#6788)
* chore: bump sgl-kernel v0.1.5 (sgl-project#6794)
* Improve profiler and integrate profiler in bench_one_batch_server (sgl-project#6787)
* chore: upgrade sgl-kernel v0.1.5 (sgl-project#6795)
* [Minor] Always append newline after image token when parsing chat message (sgl-project#6797)
* Update CI tests for Llama4 models (sgl-project#6421)
* [Feat] Enable PDL automatically on Hopper architecture (sgl-project#5981)
* chore: update blackwell docker (sgl-project#6800)
* misc: cache is_hopper_arch (sgl-project#6799)
* Remove contiguous before Flashinfer groupwise fp8 gemm (sgl-project#6804)
* Correctly abort the failed grammar requests & Improve the handling of abort (sgl-project#6803)
* [EP] Add cuda kernel for moe_ep_pre_reorder (sgl-project#6699)
* Add draft extend CUDA graph for flashinfer backend  (sgl-project#6805)
* Refactor CustomOp to avoid confusing bugs (sgl-project#5382)
* Tiny log prefill time (sgl-project#6780)
* Tiny fix EPLB assertion about rebalancing period and recorder window size (sgl-project#6813)
* Add simple utility to dump tensors for debugging (sgl-project#6815)
* Fix profiles do not have consistent names (sgl-project#6811)
* Speed up rebalancing when using non-static dispatch algorithms (sgl-project#6812)
* [1/2] Add Kernel support for Cutlass based Fused FP4 MoE (sgl-project#6093)
* [Router] Fix k8s Service Discovery (sgl-project#6766)
* Add CPU optimized kernels for topk and rope fusions  (sgl-project#6456)
* fix new_page_count_next_decode (sgl-project#6671)
* Fix wrong weight reference in dynamic EPLB (sgl-project#6818)
* Minor add metrics to expert location updater (sgl-project#6816)
* [Refactor] Rename `n_share_experts_fusion` as `num_fused_shared_experts` (sgl-project#6735)
* [FEAT] Add transformers backend support  (sgl-project#5929)
* [fix] recover auto-dispatch for rmsnorm and rope (sgl-project#6745)
* fix ep_moe_reorder kernel bugs (sgl-project#6858)
* [Refactor] Multimodal data processing for VLM (sgl-project#6659)
* Decoder-only Scoring API (sgl-project#6460)
* feat: add dp-rank to KV events (sgl-project#6852)
* Set `num_fused_shared_experts` as `num_shared_experts` when shared_experts fusion is not disabled (sgl-project#6736)
* Fix one missing arg in DeepEP (sgl-project#6878)
* Support LoRA in TestOpenAIVisionServer and fix fused kv_proj loading bug. (sgl-project#6861)
* support 1 shot allreduce  in 1-node and 2-node using mscclpp (sgl-project#6277)
* Fix Qwen3MoE missing token padding optimization (sgl-project#6820)
* Tiny update error hints (sgl-project#6846)
* Support layerwise rebalancing experts (sgl-project#6851)
* Tiny allow profiler API to auto create directory (sgl-project#6865)
* Support Blackwell DeepEP docker images (sgl-project#6868)
* [EP] Add cuda kernel for moe_ep_post_reorder (sgl-project#6837)
* [theta]merge 0605
* oai: fix openAI client error with single request via batch api (sgl-project#6170)
* [PD] Fix potential perf spike caused by tracker gc and optimize doc (sgl-project#6764)
* Use deepgemm instead of triton for fused_qkv_a_proj_with_mqa (sgl-project#6890)
* [CUTLASS-FP4-MOE]  Introduce CutlassMoEParams class for easy initialization of Cutlass Grouped Gems Metadata (sgl-project#6887)
* bugfix(OAI): Fix image_data processing for jinja chat templates (sgl-project#6877)
* [CPU] enable CI for PRs, add Dockerfile and auto build task (sgl-project#6458)
* AITER backend extension and workload optimizations (sgl-project#6838)
* [theta]merge
* [theta]merge
* [Feature] Support Flashinfer fmha on Blackwell (sgl-project#6930)
* Fix a bug in abort & Improve docstrings for abort (sgl-project#6931)
* Tiny support customize DeepEP max dispatch tokens per rank (sgl-project#6934)
* Sync the changes on cuda graph runners (sgl-project#6932)
* [PD] Optimize transfer queue forward logic for dummy rank (sgl-project#6922)
* [Refactor] image data process in bench_serving (sgl-project#6879)
* [fix] logical_to_all_physical_map index 256 is out of bounds in EP parallel. (sgl-project#6767)
* Add triton fused moe kernel config for E=257 on B200 (sgl-project#6939)
* [sgl-kernel] update deepgemm (sgl-project#6942)
* chore: bump sgl-kernel v0.1.6 (sgl-project#6943)
* Minor compile fused topk (sgl-project#6944)
* [Bugfix] pipeline parallelism and Eagle Qwen2 (sgl-project#6910)
* Tiny re-introduce profile id logging (sgl-project#6912)
* Add triton version as a fused_moe_triton config search key to avoid performace decrease in different Triton version (sgl-project#5955)
* reduce torch.zeros overhead in moe align block size kernel (sgl-project#6369)
* chore: upgrade sgl-kernel v0.1.6 (sgl-project#6945)
* add fbgemm moe grouped gemm kernel benchmark (sgl-project#6924)
* [Docker] Add docker file for SGL Router (sgl-project#6915)
* Disabling mixed chunked prefill when eagle is enabled (sgl-project#6874)
* Add canary for EPLB rebalancing (sgl-project#6895)
* Refactor global_server_args_dict (sgl-project#6866)
* Fuse routed scaling factor in topk_reduce kernel (sgl-project#6220)
* Update server timeout time in AMD CI. (sgl-project#6953)
* [misc] add is_cpu() (sgl-project#6950)
* Add H20 fused MoE kernel tuning configs for DeepSeek-R1/V3 (sgl-project#6885)
* Add a CUDA kernel for fusing mapping and weighted sum for MoE. (sgl-project#6916)
* chore: bump sgl-kernel v0.1.6.post1 (sgl-project#6955)
* chore: upgrade sgl-kernel v0.1.6.post1 (sgl-project#6957)
* [DeepseekR1-FP4] Add Support for nvidia/DeepSeekR1-FP4 model (sgl-project#6853)
* Revert "Fuse routed scaling factor in topk_reduce kernel (sgl-project#6220)" (sgl-project#6968)
* [AMD] Add more tests to per-commit-amd (sgl-project#6926)
* chore: bump sgl-kernel v0.1.7 (sgl-project#6963)
* Slightly improve the sampler to skip unnecessary steps (sgl-project#6956)
* rebase h20 fused_moe config (sgl-project#6966)
* Fix CI and triton moe Configs (sgl-project#6974)
* Remove unnecessary kernels of num_token_non_padded (sgl-project#6965)
* Extend cuda graph capture bs for B200 (sgl-project#6937)
* Fuse routed scaling factor in deepseek (sgl-project#6970)
* Sync cuda graph runners (sgl-project#6976)
* Fix draft extend ut stability with flush cache (sgl-project#6979)
* Fix triton sliding window test case (sgl-project#6981)
* Fix expert distribution dumping causes OOM (sgl-project#6967)
* Minor remove one kernel for DeepSeek (sgl-project#6977)
* [perf][sgl-kernel] extend cutlass_mla_decode to support num_head < 128 (sgl-project#6929)
* Enable more unit tests for AMD CI. (sgl-project#6983)
* Use torch.compile to fuse flash attention decode metadata preparation (sgl-project#6973)
* Eliminate stream sync to speed up LoRA batch init  (sgl-project#6960)
* support qwen3 emebedding (sgl-project#6990)
* Fix torch profiler bugs for bench_offline_throughput.py (sgl-project#6557)
* chore: upgrade flashinfer v0.2.6.post1 jit (sgl-project#6958)
* cleanup tmp dir (sgl-project#7007)
* chore: update pr test xeon (sgl-project#7008)
* Fix cutlass MLA gets almost zero accuracy (sgl-project#6998)
* Update amd nightly models CI. (sgl-project#6992)
* feat: add direct routing strategy to DP worker (sgl-project#6884)
* Fallback to lower triton version for unfound fused moe configs (sgl-project#7013)
* Fix torchvision version for Blackwell (sgl-project#7015)
* Simplify prepare_extend_after_decode (sgl-project#6987)
* Migrate to assertEqual (sgl-project#6741)
* Fix torch version in blackwell dockerfile (sgl-project#7017)
* chore: update pr test xeon (sgl-project#7018)
* Update default settings for blackwell (sgl-project#7023)
* Support both approximate and exact expert distribution collection (sgl-project#6964)
* Add decode req pool (sgl-project#6980)
* [theta]merge 0610
* [theta]merge 0610
* [CI] Add CI workflow for sgl-router docker build (sgl-project#7027)
* Fix fused_moe triton configs (sgl-project#7029)
* CPU: map changes from developing branch in sgl-kernel (sgl-project#6833)
* chore: bump v0.4.7 (sgl-project#7038)
* Update README.md (sgl-project#7040)
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