[Kernel] Use FlashInfer CUDA BGMV MoE Kernel for Multi-LoRA MoE dispatch#44147
[Kernel] Use FlashInfer CUDA BGMV MoE Kernel for Multi-LoRA MoE dispatch#44147taehokim20 wants to merge 1 commit into
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Does the latest FI release contain this kernel? |
| """Return `True` if FlashInfer BGMV MoE (multi-LoRA) kernel is available.""" | ||
| if not has_flashinfer(): | ||
| return False | ||
| mod = _get_submodule("flashinfer.fused_moe.bgmv_moe") |
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I am curious if this kernel can beat _fused_moe_lora_small_batch_kernel
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I found _fused_moe_lora_small_batch_kernel in #42290. I'll check it. Thank you for letting me know!
It's not included in the latest FI release (https://github.com/flashinfer-ai/flashinfer/releases/tag/v0.6.12). This kernel is merged in the late Friday to FlashInfer main. We can wait for the next FI release. |
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Co-authored-by: Claude
Purpose
This PR connects vLLM's MoE LoRA dispatch path to FlashInfer's BGMV MoE CUDA kernel (merged in flashinfer-ai/flashinfer#3249). When FlashInfer with BGMV MoE support is installed, vLLM uses it via the
flashinfer.fused_moeAPI. The Triton SGMV kernel remains as a fallback, selectable via environment variables.This is the recommended integration path: kernel lives in FlashInfer, vLLM consumes it through the existing FlashInfer interface.
Changes
has_flashinfer_bgmv_moe()detection and lazy wrappers forbgmv_moe_shrink/bgmv_moe_expandVLLM_MOE_LORA_BACKENDenv vars (default: CUDA)_init_moe_bgmv_buffers) for zero-allocation kernel callsadd_lora_fused_moe_cudamethod that dispatches to FlashInfer'sbgmv_moe_shrink/bgmv_moe_expandadd_lora_fused_moebetween CUDA (FlashInfer) and Triton paths based on backend configRelated PRs
Test Plan
Correctness verified by running vLLM's existing MoE LoRA kernel tests with FlashInfer dispatch enabled:
Test Result
Performance results are documented in the FlashInfer PR (flashinfer-ai/flashinfer#3249) and the original vLLM PR (#40670).