- MoE serving: expert parallelism, dispatch / combine, communication–compute overlap
- vLLM: MoE expert parallelism, dual-batch overlap (DBO) and NIXL dispatch in Model Runner V2
- GPU kernels: Triton fused kernels, CUDA Graph decode, tensor-core attention
- Engines: I read production inference engines closely, rebuild their core modules, and measure every change
I'm a contributor to vLLM. My work focuses on MoE expert parallelism in Model Runner V2 (MRV2): correctness fixes under dual-batch overlap (DBO), and the performance of NIXL-based dispatch. Two of my DBO correctness fixes have been merged into main.
| PR | What it does | Status |
|---|---|---|
| #63476 | [Bugfix][MRV2] Report the first failed DBO microbatch |
Merged |
| #63372 | [Bugfix][MRV2] Keep routed-expert rows of every DBO microbatch |
Merged |
| #63485 | [Perf][MoE] Size NIXL dispatch from synchronized execution slices |
In review |
|
A minimal, readable re-implementation of DeepInfer's core inference engine design. |
MoE expert parallelism: fused Triton kernels, NCCL all-to-all and CUDA Graph decode on B200. |
- DeepInfer-Lab: runs the real DeepSeek-V4.1-Flash on 4 × B200. Every optimization is written up in an issue with its baseline, profile, correctness tests and measured result. Roadmap.
- MoEFlow: fused Triton kernels, 2× NCCL all-to-all and CUDA Graph decode for MoE expert parallelism on B200.
My blog is now live! It brings together all my ideas, with posts about interesting open-source projects I discover and projects I build myself. Stay tuned.
- 知乎, series 解构 DeepInfer: https://www.zhihu.com/people/zhib1eiazpn
- X: @Chenxi_Ma_ai
- Blog: https://tech-blog-chi.vercel.app/


