Adding Cascade Infer to FlashInfer

[raywanb]

This draft pr is a work in progress aiming to add cascade inference to vllm. This is supposed to speedup inference when there are multiple requests that share the same prefix with a cold cache. Currently, this is still not working entirely: the output differs when not using cascade inference.

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[pavanimajety]

I am interested in looking at the perf improvement in attention layer compute before and after this change especially since we are removing the dependence on individual Prefill and Decode Wrappers.

I suggest keeping them separate to allow us to (1) use different kernels if required in future based on model or use-case and (2) to continue to have support for cuda graphs.

[comaniac]

I suggest keeping them separate to allow us to (1) use different kernels if required in future based on model or use-case and (2) to continue to have support for cuda graphs.

We intentionally want to use a single kernel for all to simply the implementation. Meanwhile, we of course want to make sure there won't be performance regression. For the CUDA graph support, @yzh119 is planning to support it in FlashInfer in these 2 days and will make a new release, so we ideally will have CUDA graph support before merging this PR.

[comaniac]

Overall LGTM. Waiting for CUDA graph support from @yzh119
Meanwhile, could you run end to end serving and throughput benchmarks on H100 to make sure there's no performance regression (without CUDA graph for now)?