[Attention] FA3 Attention Sinks Perf Boost

[LucasWilkinson]

Purpose

vLLM side of vllm-project/flash-attention#78 (merge that first)

Shout-out to @jayhshah (the performance wizard 🪄) for the implementation

Co-authored-by: Jay Shah jayhshah@gmail.com

Test Plan

Test Result

vllm bench serve --dataset-name random --random-input-len=1000 --random-output-len=100 --num-prompts 1000 --port 3333 --model openai/gpt-oss-20b --request-rate 100

## PR

============ Serving Benchmark Result ============
Successful requests:                     1000      
Request rate configured (RPS):           100.00    
Benchmark duration (s):                  11.17     
Total input tokens:                      998750    
Total generated tokens:                  98124     
Request throughput (req/s):              89.54     
Output token throughput (tok/s):         8785.70   
Total Token throughput (tok/s):          98210.51  
---------------Time to First Token----------------
Mean TTFT (ms):                          48.26     
Median TTFT (ms):                        47.00     
P99 TTFT (ms):                           66.62     
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms):                          14.87     
Median TPOT (ms):                        15.27     
P99 TPOT (ms):                           15.52     
---------------Inter-token Latency----------------
Mean ITL (ms):                           14.87     
Median ITL (ms):                         15.05     
P99 ITL (ms):                            19.59     
==================================================

## Main

============ Serving Benchmark Result ============
Successful requests:                     1000      
Request rate configured (RPS):           100.00    
Benchmark duration (s):                  11.38     
Total input tokens:                      998750    
Total generated tokens:                  98134     
Request throughput (req/s):              87.84     
Output token throughput (tok/s):         8619.95   
Total Token throughput (tok/s):          96348.73  
---------------Time to First Token----------------
Mean TTFT (ms):                          69.56     
Median TTFT (ms):                        56.66     
P99 TTFT (ms):                           472.49    
-----Time per Output Token (excl. 1st token)------
Mean TPOT (ms):                          18.57     
Median TPOT (ms):                        17.07     
P99 TPOT (ms):                           25.69     
---------------Inter-token Latency----------------
Mean ITL (ms):                           18.49     
Median ITL (ms):                         17.36     
P99 ITL (ms):                            27.75     
==================================================

(Optional) Documentation Update

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[gemini-code-assist]

Code Review

This pull request updates the flash-attention dependency to a newer commit. Based on the PR description and the commit hash, this update is intended to bring in support for FlashAttention v3. The provided patch only reflects this dependency change in the CMake configuration. The full file contents suggest there are other related changes in the Python source code to support FA3 and also to introduce a new FlashMLA backend. Since I can only comment on the provided patch, my review is limited to the dependency update itself, which seems correct.

However, while reviewing the full code for context, I found a critical issue in vllm/attention/backends/flashmla.py that I believe is part of this change.

In vllm/attention/backends/flashmla.py, the __init__ method of FlashMLAImpl has the following assertion:

assert is_flashmla_supported(), \
    "FlashMLA is not supported on this device"

The function is_flashmla_supported() returns a tuple (bool, Optional[str]). If FlashMLA is not supported, it returns (False, "reason string"). In Python, a non-empty tuple is truthy, so assert (False, "reason") will pass silently. This will lead to a runtime error later. This is a critical bug.

I suggest changing it to:

supported, reason = is_flashmla_supported()
if not supported:
    raise NotImplementedError(f"FlashMLA is not supported on this device: {reason}")

This will correctly check for support and provide a helpful error message.