# Introducing NCCL Extensions: Communication Patterns for Modern AI

PyTorch Conference North America 2026 · [All sessions](https://sessionize.com/api/v2/s2rq62nk/view/markdown)

- **Session ID:** 1257023
- **When:** Wednesday, October 21, 2026 4:55 pm - 5:20 pm (Pacific Standard Time, UTC-08)
- **Room:** 210A (Concourse Level)
- **Speakers:** Sreeram Potluri, Artem Polyakov

## Description

Sparse MoE, disaggregated inference, and RL weight rollout require communication patterns that collective libraries were never designed for. NCCL domain extensions are NCCL's answer: a family of specialized libraries built on NCCL's Device APIs --designed for customization, kernel fusion, and rapid prototyping of emerging communication patterns -- while inheriting NCCL's topology awareness and transport stack.

We debut two extensions. NCCL-EP brings MoE dispatch and combine natively into NCCL: a single, automatically tuned API spanning latency-optimized inference decode and throughput-optimized training, bringing GPU-initiated RDMA and NVLink to MoE workloads out of the box. NCCL-M2N enables zero-copy resharding between disjoint device meshes -- moving weight snapshots from trainers to inference replicas for RL rollout with no CPU staging.

We walk through the design rationale, API, and performance results. Together, these extensions signal a new direction: NCCL as a platform for the real and diverse communication demands of modern AI, not just a collective library.

## Speakers

- [Sreeram Potluri](https://sessionize.com/api/v2/s2rq62nk/view/markdown/speaker/1d07c761-325e-4979-908d-ccda20fc7b61) — NVIDIA, Distinguished Software Architect
- [Artem Polyakov](https://sessionize.com/api/v2/s2rq62nk/view/markdown/speaker/38de4619-189d-4cc3-bb0d-0ef3166f0637) — Sr. SW Engineer at NVIDIA