NCCL EP: Towards a Unified Expert Parallel Communication API for NCCL
Mixture-of-Experts (MoE) architectures have become essential for scaling large language models, driving the development of specialized device-initiated communication libraries such as DeepEP, Hybrid-EP, and others. These libraries demonstrate the performance benefits of GPU-initiated RDMA for MoE dispatch and combine operations. This paper presents NCCL EP (Expert Parallelism), a ground-up MoE communication library built entirely on NCCL's Device API. NCCL EP provides unified ncclEpDispatch and ncclEpCombine primitives with both C and Python interfaces, supporting Low-Latency (LL) mode for inference decoding and High-Throughput (HT) mode for training and inference prefill. LL targets smal...
| Authors | Amos Goldman, Nimrod Boker, Maayan Sheraizin et al. |
|---|---|
| Primary category | cs.DC |
| Published | 13 March 2026 |
| Last updated at source | 2 April 2026 |
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