[FlashInfer v0.6.4] [RL] Integrate FlashInfer mxfp8 gemm, MoE, and routed MoE (#19537)

This commit is contained in:
Ziang Li
2026-03-10 15:37:57 -07:00
committed by GitHub
parent bd460e9565
commit 76ee4bb98c
14 changed files with 671 additions and 86 deletions

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@@ -32,6 +32,7 @@ Currently, DeepEP, Mooncake, `ascend_fuseep` and MORI only support cases where `
| `deep_gemm` | DeepGEMM backend optimized for MoE matrix multiplications, supporting contiguous layouts for prefill and masked layouts for decode; often JIT-compiled for performance. | Large-scale EP deployments with FP8 block-wise quantization. |
| `cutlass` | CUTLASS-based backend for efficient GEMMs. | NVIDIA architectures with CUTLASS support. |
| `flashinfer_trtllm` | FlashInfer integrated with TensorRT-LLM for accelerated MoE computations, supporting FP4 communication operators and high-performance GEMMs. | Blackwell with TRT-LLM. |
| `flashinfer_trtllm_routed` | FlashInfer integrated with TensorRT-LLM for accelerated routed MoE computations, consuming SGLang-computed top-k expert assignments and weights. | Blackwell with TRT-LLM. |
| `flashinfer_cutlass` | FlashInfer combined with CUTLASS for high-performance grouped GEMMs in MoE layers, handling FP4/FP8 quantization efficiently. | Blackwell with FP4/FP8 models. |
| `flashinfer_mxfp4` | FlashInfer variant optimized for MXFP4 (mixed FP4) quantization in MoE runners, focusing on memory-efficient low-precision inference. | Low-precision models with MXFP4. |
| `flashinfer_cutedsl` | FlashInfer with a custom DSL for flexible and efficient MoE kernel generation, integrated with ModelOpt FP4 quantization. | Low-precision models with NVFP4. |

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@@ -312,7 +312,7 @@ Please consult the documentation below and [server_args.py](https://github.com/s
| --- | --- | --- | --- |
| `--expert-parallel-size`<br>`--ep-size`<br>`--ep` | The expert parallelism size. | `1` | Type: int |
| `--moe-a2a-backend` | Select the backend for all-to-all communication for expert parallelism. | `none` | `none`, `deepep`, `mooncake`, `mori`, `ascend_fuseep`|
| `--moe-runner-backend` | Choose the runner backend for MoE. | `auto` | `auto`, `deep_gemm`, `triton`, `triton_kernel`, `flashinfer_trtllm`, `flashinfer_cutlass`, `flashinfer_mxfp4`, `flashinfer_cutedsl`, `cutlass` |
| `--moe-runner-backend` | Choose the runner backend for MoE. | `auto` | `auto`, `deep_gemm`, `triton`, `triton_kernel`, `flashinfer_trtllm`, `flashinfer_trtllm_routed`, `flashinfer_cutlass`, `flashinfer_mxfp4`, `flashinfer_cutedsl`, `cutlass` |
| `--flashinfer-mxfp4-moe-precision` | Choose the computation precision of flashinfer mxfp4 moe | `default` | `default`, `bf16` |
| `--enable-flashinfer-allreduce-fusion` | Enable FlashInfer allreduce fusion with Residual RMSNorm. | `False` | bool flag (set to enable) |
| `--enable-aiter-allreduce-fusion` | Enable aiter allreduce fusion with Residual RMSNorm. | `False` | bool flag (set to enable) |