[Attention] Blackwell FP8 MLA support with CUTLASS_MLA backend

[MatthewBonanni]

Purpose

Enable FP8 KV cache support on Blackwell in the CUTLASS_MLA backend.

Test Plan

Correctness

VLLM_ATTENTION_BACKEND=CUTLASS_MLA lm_eval --model vllm --model_args '{"pretrained": "deepseek-ai/DeepSeek-V2-Lite-Chat", "trust_remote_code": true, "kv_cache_dtype": "fp8"}' --tasks gsm8k --batch_size auto

Performance

V2 Lite
VLLM_ATTENTION_BACKEND=CUTLASS_MLA vllm bench throughput --model=deepseek-ai/DeepSeek-V2-Lite-Chat --dataset-name=random --input-len=8192 --output-len=1024 --num-prompts=1000 --kv-cache-dtype=fp8

V2 (with EP4)
VLLM_ATTENTION_BACKEND=CUTLASS_MLA vllm bench throughput --model=deepseek-ai/DeepSeek-V2 --dataset-name=random --input-len=8192 --output-len=1024 --num-prompts=1000 --kv-cache-dtype=fp8 --tensor-parallel-size 4 --enable-expert-parallel

Test Result

Correctness

With kv_cache_dtype=auto:

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.6664|±  | 0.013|
|     |       |strict-match    |     5|exact_match|↑  |0.6619|±  | 0.013|

With kv_cache_dtype=fp8:

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.6664|±  | 0.013|
|     |       |strict-match    |     5|exact_match|↑  |0.6611|±  | 0.013|

Performance

V2 Lite:
With --kv-cache-dtype=auto: Throughput: 4.20 requests/s, 38668.98 total tokens/s, 4296.91 output tokens/s
With --kv-cache-dtype=fp8: Throughput: 4.74 requests/s, 43678.48 total tokens/s, 4853.57 output tokens/s

V2:
With --kv-cache-dtype=auto: Throughput: 0.81 requests/s, 7509.07 total tokens/s, 834.41 output tokens/s
With --kv-cache-dtype=fp8: Throughput: 1.08 requests/s, 9971.05 total tokens/s, 1107.99 output tokens/s

(Optional) Documentation Update

---

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

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[mergify]

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

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

[MatthewBonanni]

@Mergifyio refresh

[mergify]

refresh

✅ Pull request refreshed

[celsowm]

Is it faster than fa3 ?

[elvischenv]

tests/kernels/test_cutlass_mla_decode.py::test_cutlass_mla_decode[torch_dtype1-False-True-64-512-576-1-16-4096-1-128] b=128, s_q=1, mean_sk=4096, h_q=16, h_kv=1, d=576, dv=512, causal=True, varlen=False, torch_dtype=torch.float8_e4m3fn
FAILED



        cos_diff = 1 - 2 * (x * y).sum().item() / max(
            (x * x + y * y).sum().item(), 1e-12)
        if (use_fp8):
>           assert cos_diff < 1e-4
E           assert 1.0 < 0.0001
tests/kernels/test_cutlass_mla_decode.py:22: AssertionError
======================================================================= warnings summary =======================================================================
../usr/local/lib/python3.12/dist-packages/schemathesis/generation/coverage.py:305
  /usr/local/lib/python3.12/dist-packages/schemathesis/generation/coverage.py:305: DeprecationWarning: jsonschema.exceptions.RefResolutionError is deprecated as of version 4.18.0. If you wish to catch potential reference resolution errors, directly catch referencing.exceptions.Unresolvable.
    ref_error: type[Exception] = jsonschema.RefResolutionError,
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
=================================================================== short test summary info ====================================================================
FAILED tests/kernels/test_cutlass_mla_decode.py::test_cutlass_mla_decode[torch_dtype1-False-True-64-512-576-1-16-4096-1-128] - assert 1.0 < 0.0001
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
=========================================================== 1 failed, 24 passed, 1 warning in 13.10s ===========================================================

@MatthewBonanni This test is failed on main. Seeing this in at least 2 recent PRs:
https://buildkite.com/vllm/ci/builds/29559/steps/canvas?sid=01991a6b-6773-4022-8ab6-32198efb2ff7
https://buildkite.com/vllm/ci/builds/29486/steps/canvas?jid=0199166b-7879-4618-adbb-75b54cb44bae

[MatthewBonanni]

@elvischenv hmm, thanks for bringing this up. It looks like it's passing on the most recent nightly:
https://buildkite.com/vllm/ci/builds/29529#
will investigate though

[MatthewBonanni]

Is it faster than fa3 ?

@celsowm Thanks for your question! This backend is Blackwell-specific, whereas the recently-merged FA3 backend (#14258) is for Hopper, so it's difficult to make a direct comparison