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[Feature] Add DoSA prefill indexer on SM100 - #63381

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llm-sys:dosa-main

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@fangtaosong fangtaosong commented Oct 23, 2026 •

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Overview

Add an opt-in DoSA indexer for DSA prefill on SM100. It scores a seed subset,
screens keys with score bounds, and refines the surviving candidates.

Depends on #64749. This PR contains the DoSA operator and serving integration;
the shared fixes are reviewed separately in that prerequisite PR.

Claims

  • Supports 32/64 index heads with FP8 index keys on SM100 and CUDA 13.
  • At near-1M context, GLM-5.2 TTFT improves by 2.40× with Q16K and
    2.45× with Q32K. Previously published DeepSeek-V3.2 results reach 1.83×.

Validation

Rebased onto upstream 8a2a5e4c40f9. GLM-5.2 was remeasured across all six
contexts with both stock and DoSA on the same eight SM100 GPUs, client host,
NICs and communication settings. All 96 requests completed successfully.

TTFT uses SQLite 3.53.4 source prefixes, FP8 KV and TP8/EP8. Each speedup is
stock / DoSA, using the median of three formal requests after one warmup.
Requests use fresh IDs, a prefix-cache reset, a two-token output budget and
default EOS. Here 1K = 1024 tokens.

Context GLM Q16K GLM Q32K DeepSeek Q16K DeepSeek Q32K
128K 1.0076× 1.0035× 0.93× 0.88×
256K 1.1238× 1.1166× — —
384K 1.2155× 1.2168× 0.97× 0.97×
512K 1.3668× 1.3762× 1.02× 1.02×
768K 1.8033× 1.8235× 1.33× 1.35×
~1M 2.3992× 2.4463× 1.80× 1.83×

DeepSeek rows retain the previously published latency measurements. Requests
above its 163840-token context use a 1048576-token server limit for
extrapolation. These source prefixes measure latency, not independent agent tasks.

image
Near-1M TTFT in seconds: median [min, max]
Model Chunk Stock DoSA Speedup
GLM-5.2 16K 188.954 [188.594, 188.963] 78.758 [78.722, 78.768] 2.40×
GLM-5.2 32K 189.598 [189.459, 189.631] 77.505 [77.466, 77.512] 2.45×
DeepSeek-V3.2 (published) 16K 538.713 [538.525, 539.122] 299.713 [299.518, 299.868] 1.80×
DeepSeek-V3.2 (published) 32K 540.997 [539.089, 541.948] 295.277 [295.253, 295.830] 1.83×

The published evaluation on our fixed 100-request LongBench-v2 subset reports
GLM-5.2 54% with stock → 58% with DoSA (+4 percentage points).
The answer differences come from choosing different valid keys at equal
indexer scores. The LongBench-v2 evaluation guide
provides the cohort, protocol, A/A control and reproduction commands.

The rebased stack passes 107 focused tests, including all 10 retained DoSA GPU
cases covering H32/H64 native scoring, capacity recovery, cross-stream reuse,
strided output and packed batch/fallback, plus the affected upstream SM100 GLM
projection and graph paths.

Re-run commands:

.venv/bin/python -m pytest -q tests/kernels/attention/test_dosa.py
.venv/bin/pre-commit run --from-ref df80a82c2492c94e650a8ae6725ebbf17463ba11 --to-ref HEAD

Details

Enable with --attention-config '{"indexer_dosa": true}'. The existing indexer
remains the default. Scratch and private graphs are owned and accounted for by
the workspace manager; selection state is local to each invocation. Capacity
and numerical admission failures use exhaustive recovery.

Shared RoPE cache-capacity, manual-fusion budget/range and worker-startup fixes
are submitted separately in #64749. Both benchmark arms include these fixes.

The DoSA-only diff
contains 5,894 changed lines across 24 files. The prerequisite contains
226 changed lines; the combined stack is 2,782 changed lines smaller than the
original PR. Once #64749 merges, this PR will be rebased onto main to retain
only the DoSA feature commit.

Related PRs #60618 and
#48726 fuse scoring and
selection. DoSA adds a seed threshold and certified screening before sparse
refinement; the existing dense scorer and TopK remain available for fallback.

Complete TTFT reproduction: installation, inputs, servers and client.


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.

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@mergify

mergify Bot commented Oct 23, 2026

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Documentation preview: https://vllm--63381.org.readthedocs.build/en/63381/

@mergify mergify Bot added the documentation Improvements or additions to documentation label Oct 23, 2026
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@mergify mergify Bot added ci/build deepseek Related to DeepSeek models performance Performance-related issues torch.compile labels Oct 23, 2026
@fangtaosong fangtaosong changed the title Dosa main [Feature] Add DoSA prefill indexer on SM100 Oct 23, 2026
@LopezCastroRoberto LopezCastroRoberto self-assigned this Oct 26, 2026
@mergify

mergify Bot commented Oct 27, 2026

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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

@mergify mergify Bot added the needs-rebase label Oct 27, 2026
Signed-off-by: fangtaosong <fangtaosong@xiaohongshu.com>
Signed-off-by: fangtaosong <fangtaosong@xiaohongshu.com>
@mergify

mergify Bot commented Oct 30, 2026

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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

@mergify mergify Bot added the needs-rebase label Oct 30, 2026

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