[fangtaosong]

Overview

Extract the shared fixes from #63381: honor the configured manual fusion budget,
extend the DeepSeek RoPE cache to the requested capacity, and serialize worker
startup when NUMA binding is selected automatically.

The DoSA operator and serving integration remain in a separate PR.

Claims

• Explicit zero disables manual AllReduce/RMSNorm fusion; positive limits control its workspace budget.
• Compilation ranges exclude zero-sized endpoints.
• Extending the RoPE cache preserves the values at existing positions.
• Automatic NUMA selection uses serialized worker startup; explicitly disabled binding keeps concurrent startup.

Validation

All 12 focused regression cases pass:

• Six cases cover zero/positive fusion budgets, configuration replacement,
  explicit workspace sizing and the public RoPE factory.
• Six cases cover concurrent worker startup and NUMA configuration.

The RoPE regression requests a 512-position cache with a 256-position training
range. Before the fix, the factory returns only 256 positions. After the fix,
the cache contains 512 positions and its original 256-position prefix is
exactly unchanged.

The worker-startup regression also reproduces the original failure:
automatic NUMA binding incorrectly permits concurrent startup before the fix.

.venv/bin/python -m pytest -q \
  tests/compile/test_config.py::test_config_replace_accepts_disabled_allreduce_fusion \
  tests/kernels/core/test_rotary_embedding.py::test_deepseek_yarn_cache_capacity_preserves_existing_positions \
  tests/kernels/core/test_fused_allreduce_gemma_rms_norm.py::test_explicit_flashinfer_workspace_budget \
  tests/v1/executor/test_multiproc_executor.py::test_can_start_workers_concurrently

GLM-5.2 stock serving also completes all six contexts from 128K to near 1M
with Q16K and Q32K on eight SM100 GPUs, using FP8 KV and TP8/EP8.

Details

The manual fusion path previously used platform defaults independently of the
configured budget. It now respects the configured limit, including zero.
Zero-sized compilation endpoints are excluded when normalizing ranges.

RoPE cache capacity is separated from the training range used to calculate
YaRN frequencies. Increasing the serving context therefore extends the cache
without changing existing positional values.

Worker startup accounts for automatic NUMA selection when deciding whether
workers can initialize concurrently.

The existing logits-upcast utility moves into the shared indexer TopK module.
Sparse indexing retains its original import path through a re-export; the
function body and launch remain unchanged.

This prerequisite contains 226 changed lines across 16 files, with no
DoSA imports or feature-flag dependency.

---

Pull Request Checklist

• I used vLLM's /pr-checklist skill.
• AI assistance was used during the creation of this PR.
• Design Fit: Minimizes impact on core components, reuses existing functionality, and justifies added complexity.
• Testing and Validation: Validates the change and ensures tests are meaningful, with CI coverage or documented external validation.
• Code Quality and Style: Keeps code and comments concise and updates relevant documentation.
• Pull Request Contents: Supports claims with evidence, explains tradeoffs, and follows the contributing guide.

The human submitter must review every changed line and the validation results
before filing the PR.

[claude]

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[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @fangtaosong.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[LopezCastroRoberto]

could you also compare against the fused single-launch indexer in vllm-project/vllm#60618. Maybe with indexer-only kernel times for 16K-row chunks, 128K–1M keys and top-2048 for now. Both PRs target the same stage, so it would help to know where DoSA’s gain comes from on top of fusing scoring and selection. Also, is the top-k output exact?

sorry, crossed PRs, I wanted to post this in #63381 :)