vllm-project/vllm

[Feature]: Extract KV-Cache update from all attention backends

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#32,335 建立於 2026年1月14日

 (51 則留言) (0 個反應) (9 位負責人)Python (16,816 個分叉)batch import
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描述

🚀 The feature, motivation and pitch

Similar to how https://github.com/vllm-project/vllm/pull/25954 extracts it from FlashAttn. Ideally, we want to cover all backends with kv-cache update from v1/attention/backends.

Backends:

  • FlashAttention
  • FlashInfer
  • AiterFlashAttention (in progress)
  • RocmAiterUnifiedAttention
  • RocmAttention
  • TritonAttention
  • FlashAttentionDiffKV
  • FlexAttention
  • TreeAttention

MLA Backends:

  • FlashAttnMLA
  • FlashInferMLA
  • FlashMLASparse
  • FlashMLA
  • AiterMLA
  • ROCMAiterMLASparse
  • CutlassMLA
  • TritonMLA

After all backends are supported, we can remove slot_mapping from attention metadata.

Alternatives

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Additional context

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