[Fix] Fix backend selection after flashinfer version update

[DarkSharpness]

Motivation

#15551
#17411

After flashinfer is upgraded to 0.6, the default decode attention backend "auto" will select "fa3" instead of "fa2" on hopper GPUs. This might has been the root cause of some performance regression.

https://github.com/flashinfer-ai/flashinfer/blob/57ef44b9d7ada00cb50ca26310f9c3a3bfbc0dd2/flashinfer/utils.py#L455-L462

Modifications

We fix the prefill/decode backends of flashinfer to "fa2". Interestingly, I don't know why some prefill backends are fixed to "fa2", while others are left as none (which means "auto"), so I just fix all prefill backends to "fa2".

Detailed Changes in this PR:

1. Paged Prefill: no change ("fa2")
2. Paged Decode: "auto" -> "fa2"
3. Paged Prefill Verify: "auto" -> "fa2"
4. Paged Draft Extend: no change ("fa2")
5. Paged DLLM Extend: no change ("fa2")

On Hopper GPUs, "auto" will fallback to "fa3".

Maybe after this PR, we can revert some workaround PRs like #17425 cc @Fridge003

NOTE that this PR does not necessarily bring performance gain in every cases.

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[gemini-code-assist]

Summary of Changes

Hello @DarkSharpness, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves a potential performance regression introduced by a recent FlashInfer version update (0.6), which altered the default attention backend selection on Hopper GPUs from "fa2" to "fa3". By explicitly configuring both prefill and decode operations to use the "fa2" backend, the change ensures consistent and potentially improved performance, circumventing the new default behavior.

Highlights

• FlashInfer Backend Fix: Explicitly sets the FlashInfer decode attention backend to "fa2" to prevent automatic selection of "fa3" on Hopper GPUs after a FlashInfer version update.
• Consistent Prefill Backend: Standardizes all FlashInfer prefill operations to use the "fa2" backend, ensuring consistent behavior across different prefill types (paged, verify, draft extend, DLLM extend).
• Performance Regression Mitigation: Addresses a potential performance regression identified after FlashInfer 0.6 started defaulting to "fa3" on Hopper GPUs, which might have been less optimal for certain workloads.

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Changelog

• python/sglang/srt/layers/attention/flashinfer_backend.py
  • Initialized self.prefill_backend and self.decode_backend attributes to the string value "fa2" within the FlashInferAttention class constructor.
  • Modified the instantiation of BatchPrefillWithPagedKVCacheWrapper and BatchDecodeWithPagedKVCacheWrapper across various methods (including __init__ and init_forward_metadata_capture_cuda_graph) to dynamically use self.prefill_backend and self.decode_backend respectively, instead of hardcoded values or implicit defaults.

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[gemini-code-assist]

Code Review

This pull request addresses a performance regression on Hopper GPUs caused by a recent flashinfer update, which changed the default attention backend. The fix involves explicitly setting the flashinfer backend to "fa2" for paged KV cache operations, overriding the new default of "fa3".

The changes are correct and consistently applied. By centralizing the backend choice into self.prefill_backend and self.decode_backend, the code is also more maintainable.

I have one suggestion to make the backend selection configurable via environment variables for better future flexibility. This would make it easier to adapt to different hardware or future flashinfer updates without modifying the code.

[gemini-code-assist]

While hardcoding the backends to "fa2" fixes the immediate performance regression, it might be beneficial for future flexibility to make these configurable. This would allow easier tuning or adaptation to new hardware or flashinfer versions without code changes.

Consider using environment variables to control the backend selection, with "fa2" as the default. This can be managed through the envs module. You would need to add SGLANG_FLASHINFER_PREFILL_BACKEND and SGLANG_FLASHINFER_DECODE_BACKEND to sglang/srt/environ.py with a default value of "fa2".

Suggested change

	self.prefill_backend = "fa2"
	self.decode_backend = "fa2"
	self.prefill_backend = envs.SGLANG_FLASHINFER_PREFILL_BACKEND.get()
	self.decode_backend = envs.SGLANG_FLASHINFER_DECODE_BACKEND.get()

[b8zhong]

QQ: will this select the right backend under SM100

[DarkSharpness]

QQ: will this select the right backend under SM100

Yes (at least for now). Currently, the default "auto" backend will only fallback to "fa3" or "fa2", and "fa3" will not be chosen by "auto" under SM100. The behavior after this PR should be the same as before this PR.

reference link: https://github.com/flashinfer-ai/flashinfer/blob/57ef44b9d7ada00cb50ca26310f9c3a3bfbc0dd2/flashinfer/utils.py#L455-L462

[Fridge003]

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