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[Kernel] sliding window support in paged_attention_v1/v2 kernels#4768

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mmoskal wants to merge 2 commits intovllm-project:mainfrom
mmoskal:sliding_window_decode
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[Kernel] sliding window support in paged_attention_v1/v2 kernels#4768
mmoskal wants to merge 2 commits intovllm-project:mainfrom
mmoskal:sliding_window_decode

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@mmoskal
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@mmoskal mmoskal commented May 11, 2024

The paged attention (v1 and v2) decode kernel does not support sliding window natively - the way it works now it just takes all the blocks passed in (up to seq_len). With v1 manager, the sliding window uses blocks in a "ring buffer" fashion, so this is not a problem. With the new block manager (see #4545) we need potentially to start attention computation in the middle of a block, otherwise we pay attention to a few tokens too many. It doesn't seem to affect this test though.

Related: #3385

This is just a rough draft - didn't even try to compile.

@cadedaniel is there another issue for this already?

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@rkooo567
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cc @zhuohan123 (great timing!)

@rkooo567
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btw, we need to make sure this can be compatible with this PR #4681, that we plan to merge soon.. I think this can make things much cleaner

@rkooo567 rkooo567 self-assigned this May 14, 2024
@hmellor hmellor closed this Feb 18, 2025
fadara01 added a commit to fadara01/vllm that referenced this pull request Oct 28, 2025
- Enables Sliding Window Attention (SWA) for the CPU backend.
- Enables models with hybrid local-global attention (i.e., those with multiple KV cache groups) for the CPU backend.
- Fixes a bug in `TorchSDPAMetadataBuilderV1` where `query_start_loc_cpu` was updated in-place despite being shared between multiple KV cache groups.
- Adds a unit test for the decode phase in the CPU attention backend.
- Adds reference implementations used to test paged attention to a common utils module and reuses it for the decode attention CPU test.

SWA is enabled by truncating full blocks/pages that are outside the window (similar to vllm-project#23010).
Hence, the implementation is block-granular and may attend to at most (block_size - 1) extra tokens; this did not affect the accuracy tests I ran.
This is the best we can do with the current paged-attention API/implementation, which does not support SWA natively
See: vllm-project#4768 for context and the attempt to enable native SWA support in paged_attn.

Signed-off-by: Fadi Arafeh <fadi.arafeh@arm.com>
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