DeepEP (DeepEveryParallel) is a high-performance communication library for modern machine learning training and inference. The library currently focuses on expert parallelism (EP) — providing high-throughput and low-latency all-to-all GPU kernels (MoE dispatch and combine) with low-precision support including FP8 — while also offering experimental primitives for pipeline parallelism (PP), context parallelism (CP), an
功能特性
- Fully JIT (Just-In-Time compilation)
- NCCL Gin backend
- Header-only & lightweight
- Able to reuse existing NCCL communicators
- High-throughput and low-latency APIs unified into a single ElasticBuffer interface, with a new GEMM layout
- Larger scale-up & scale-out domain support (up to EP2048)