[AMD] Qwen3.5-FP8 MI355X SGLang disagg perf tuning: Docker image update / Qwen3.5-FP8 MI355X SGLang disagg 性能调优 更新Docker image#2094
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…pool, concurrency sweep - Bump image from sglang-rocm:v0.5.11-rocm700 to sglang:v0.5.14-rocm720 - Add mia1-p01-g09 to disagg SLURM exclude list (broken pyxis) - Expand mi355x-disagg runner pool from 3 to 9 nodes - Set 1K1K and 8K1K concurrency to [ 8, 16, 32, 64, 128 ] Co-authored-by: Cursor <cursoragent@cursor.com>
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Claude finished @ChangLiu0709's task in 1m 52s —— View job PR Review
SummaryOne 🟡 warning, no blocking issues. The changelog entry's Everything else checks out:
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Co-authored-by: Cursor <cursoragent@cursor.com>
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see unofficial run visualizer at https://inferencex.semianalysis.com/inference?unofficialRun=28795797050 |
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/reuse-sweep-run |
Updated pull request link in the changelog.
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Hi, @ChangLiu0709 |
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Hi @1am9trash can sync up to SGLang cookbook soon. |
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Hi @1am9trash, PR to sglang cookbook created: sgl-project/sglang#31454. |
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Hi @1am9trash, PR to sglang cookbook got merged: sgl-project/sglang#31454. Wondering if we can have this PR merged as well : ) |
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As a PR reviewer and CODEOWNER, I have reviewed this and have:
- Verified that as of the moment of typing this, this is the latest version of PR_REVIEW_CHECKLIST.md
- Verified that the general code quality meets the InferenceX standard and does not make the code quality any worse.
- Verified that this PR has passed PR validation. Please link to GitHub Action workflow that shows this. Link: https://github.com/SemiAnalysisAI/InferenceX/actions/runs/28795797050?pr=2094
- Verified that this PR passes evals. Please link to GitHub Action workflow that shows this. Link: https://github.com/SemiAnalysisAI/InferenceX/actions/runs/28795797050?pr=2094
- Verified that speculative decoding PRs uses chat templates to align the AL distribution to real world
- For agentic workloads: verified that speculative-decoding configs (EAGLE / MTP / draft models) run with simulated synthetic acceptance, with the acceptance-length value taken from the committed golden AL curve in golden_al_distribution/ for that model, thinking mode, and draft length. A submission may choose any supported draft length, but it may not substitute a different acceptance target.
- Verified that the model architecture isn't changed with benchmark hacks like using --hf-overrides to skipping indexer for every x layers on models that don't natively support this. As a general rule, we won't accept optimizations that reduces the number of model architecture FLOPs. Anything that makes that same computation run faster is fair game; FLOPs at lower precisions is fine, given that the config passes private evals. As an general north star princple, we should only use optimizations which is used in production by customers that care about accuracy
- If an company claims that they support vLLM/SGLang as first class LLM inference engines on their hardware, I have verified that the respective vLLM submission made using upstream https://hub.docker.com/u/vllm docker repo, upstream SGLang https://hub.docker.com/u/lmsysorg docker repo. The only exceptions are for new hardware, such as MI455X UALoE72, Vera Rubin NVL72, Rubin NVL8, etc., and for new model architectures where there is an actual reason why vLLM/SGLang does not fundamentally support them yet as supported by vLLM/SGLang community maintainers
- If an company claims that they support vLLM/SGLang as first class upstream in-tree LLM inference engines on their hardware, I have have verified that the respective vLLM/SGLang submission has been made before additional frameworks (TRT-LLM, ATOM, etc.). The only exceptions are for new hardware, such as MI455X UALoE72, Vera Rubin NVL72, Rubin NVL8, etc., and for new model architectures where there is an actual reason why vLLM/SGLang does not fundamentally support them yet.
- Verified that every single-node vLLM/SGLang recipe in this PR is documented in the official vLLM recipes and/or the SGLang cookbook:
- I linked the corresponding upstream PR in the vLLM recipe repo or SGLang repo and verified that it is MERGED before this InferenceX PR merges. An opened, draft, or closed-without-merge upstream PR does not satisfy this requirement. If the matching recipe was already published, I linked the published recipe/cookbook page in the additional detail section below.
- Verified that this PR does not patch the inference engine or serving stack — the pinned image must run as shipped. This covers .patch files / git apply / patch, inline patches embedded in benchmark scripts (e.g. a python3/sed heredoc that rewrites installed engine sources before serving), in-place edits of site-packages, monkey-patching, overwriting container files, and installing forked/rebuilt engine wheels on top of the pinned image. The only exception is a patch covered by a filled-out waiver at docs/waiver/
<PR_NUMBER>.md— named after the PR that introduces the patch and filed in that same PR, stating what is patched, why the unmodified upstream image cannot run this benchmark, the upstream PR/issue link, and the removal plan — which I have linked below in the additional detail section. - If any of the above criteria cannot reasonably be satisfied, I have provided additional reasoning below.
Additional detail section:
- Cookbook PR: sgl-project/sglang#31454
Signed: @1am9trash
✅✅✅ Verdict: PASS ✅✅✅✅ Check 0 (CODEOWNER): PASS — @1am9trash is a named owner of |
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Changes
qwen3.5-fp8-mi355x-sglang-disaggimage fromlmsysorg/sglang-rocm:v0.5.11-rocm700-mi35x-20260511tolmsysorg/sglang:v0.5.14-rocm720-mi35x(ROCm 7.0 → 7.2, sglang v0.5.11 → v0.5.14).[ 8, 16, 32, 64, 128 ].Authors
@ChangLiu0709
@chunfangamd
中文说明
Qwen3.5-FP8 MI355X SGLang 分离式推理性能调优：
lmsysorg/sglang:v0.5.14-rocm720-mi35x（ROCm 7.0 → 7.2，sglang v0.5.11 → v0.5.14）。[ 8, 16, 32, 64, 128 ]。Made with Cursor