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[Bugfix][ROCm] Preserve config during GPU memory profiling - #58014
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WoosukKwon merged 2 commits intoOct 5, 2026
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This pull request has merge conflicts that must be resolved before it can be |
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Signed-off-by: Thiago Mota Martins <thiagomota510@gmail.com> Assisted-by: OpenAI Codex
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✅ @Thiago4532, CI is now available for this PR.
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LGTM, thanks @Thiago4532 ! |
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✅ Triggered Buildkite CI #92736 for commit |
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Hi @njhill can you take a look at this PR? On ROCm path missing the context could leads to very conservative mem allocation for indexer, and eventually lead to a waste of GPU mem. A more detailed explaination from my coding agent is PR #58014 wraps both profile_run() calls in set_current_vllm_config(self.vllm_config), so the cap applies. In our probes the workspace fell to about 1.7–2.25 GiB, and |
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…bytes-profiling The only conflict is the pinned-KV early return this branch removes. vllm-project#58411 and vllm-project#58014 changed the profile_run call inside it, and both changes are already on the surviving call in the memory_profiling block, so the removal stands. Signed-off-by: lesj0610 <lesj0610@users.noreply.github.com>
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That point capped the chunk at 8192 to buy KV room. The room was taken by a profiling bug, not by the chunk: the ROCm paged MXFP4 indexer reserves its decode logits workspace as (rows, max-model-len), and with no ambient vLLM config in scope during the profiling run the row count fell back to the batched-token count, so at this recipe's 1M context the reservation scaled linearly with the chunk. vllm-project/vllm#58014 restores the config, bounding rows by max-num-seqs x (1 + 5 drafts), which is far below either chunk value. The repinned image carries the fix, so the chunk no longer moves the KV budget and all 14 points can sit on the upstream 16384. #3735 caps the chunk from c32 up on an A/B taken before that fix, and is the side-by-side arm for re-measuring it on this image. Co-authored-by: Cursor Agent <cursoragent@cursor.com>
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Repin the MI355X DeepSeek-V4.1-Flash DSpark recipe to nightly-rocm100-21d93d0d and retune the ladder around it. - Leave VLLM_ROCM_USE_AITER_MOE_A4W4_DSV4 unset. The a4w4 opt-in faults during graph capture at TP=2; all nine TP=2 points failed and all nine TP=4 points passed in run 37424787697. vllm-project/vllm#60273 tracks the fix, so the experts stay on the generic AITER CK a8w4 selector. - Enable VLLM_ROCM_QUICK_REDUCE_QUANTIZATION=INT4 so tensor-parallel all-reduces above the quick-reduce size threshold use the INT4 codec. - Hold both TP rows at concurrency 64. Run 37510565585 measured TP=2 c128 at 150,683 tok/s/chip against 151,896 at c64 with prompt tokens within 0.5%, so the extra concurrency bought real prefill rather than scored tokens. - Set VLLM_SHARED_EXPERTS_STREAM_TOKEN_THRESHOLD=1024. Upstream caps the shared-expert overlap at 256 tokens, which predates speculative decoding: five DSpark drafts make a decode step CONC x 6 tokens, so c64 submits 384 and the overlap never engages above c42. 1024 covers the ladder and matches the ATOM default, and stays below the prefill chunk so memory profiling never takes the overlap. - Restore the upstream 16384 prefill chunk at TP2 c64, making the chunk uniform across all 14 points. That point had capped it at 8192 to buy KV room, but the room was taken by a profiling bug rather than by the chunk: the ROCm paged MXFP4 indexer sizes its decode logits workspace as (rows, max-model-len), and with no ambient vLLM config in scope the row count fell back to the batched-token count, so at this recipe's 1M context the reservation scaled linearly with the chunk. vllm-project/vllm#58014 bounds rows by max-num-seqs x (1 + 5 drafts), and the repinned image carries that fix. Rebased onto main: the configuration-procedure guides this branch had edited were removed by #3789, so those edits are dropped. Co-authored-by: Cursor Agent <cursoragent@cursor.com>
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Purpose
Make the vLLM config available during both GPU
profile_run()paths. Without it, the ROCm sparse-MLA indexer can fall back tomax_num_batched_tokenswhen sizing its decode-logits workspace. The regression test checks that a configuration withmax_num_seqs=16and five speculative tokens uses 96 rows instead of 32768.Related to #55132; complementary to the pre-capture warmup fix in #55341, which does not provide the config context during memory profiling. The current main still calls both memory-profiling paths without this context, and the V2 runner does not establish it internally. Searches for existing profiling-context fixes found no replacement for this change.
Validation
Rebased on main
ab5266769e702434a0968d47319d0731d8ccac35on October 1, 2026. The conflict resolution preserves the new upstreamrandomize_inputsargument; the regression test also checks that it reaches both profiling paths..venv/bin/python -m pytest -q tests/v1/worker/test_gpu_worker.py: 13 passed, 9 skipped, 14 PyTorch deprecation warnings on macOS Apple Silicon. Both regression-test cases passed..venv/bin/python -m pre_commit run --files vllm/v1/worker/gpu_worker.py tests/v1/worker/test_gpu_worker.py: passed.git diff origin/main --check: passed.AMD CI, including the MI300 V1 Executor + Worker step, remains desirable when permitted by the project workflow. This update does not claim a new GPU or model-evaluation run.
AI-assisted contribution: OpenAI Codex assisted with the implementation, regression test, and rebase. The human submitter owns the contribution.