# XCCL: Scaling PyTorch Collectives to Exascale on Intel GPUs with TorchComms

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

- **Session ID:** 1258012
- **When:** Tuesday, October 20, 2026 5:10 pm - 5:20 pm (Pacific Standard Time, UTC-08)
- **Room:** LL21A (Lower Level)
- **Speakers:** Panagiotis Kourdis, Tanima Dey

## Description

At the 2025 PyTorch Conference, TorchComms was introduced as a next-generation distributed communication library for scalable, fault-tolerant, heterogeneous AI training. XCCL extends that vision with native Intel GPU support through a new in-tree backend built on Intel’s oneCCL library. This talk covers XCCL’s journey from backend integration to validation on Aurora, Argonne National Laboratory’s exascale supercomputer. Running TorchTitan and other AI workloads, XCCL achieved over 90% scaling efficiency across thousands of nodes, demonstrating reliable large-scale PyTorch training on Intel GPUs. We will highlight key engineering innovations, including a stream-ordered asynchronous execution model that overlaps computation and communication for improved scalability and utilization. We will also discuss bridging gaps between PyTorch collective semantics and oneCCL, plus the CI and testing strategies combining mock-based validation with real Intel hardware testing.  Attendees will gain practical insight into building a production-grade PyTorch accelerator backend. We will also compare XCCL with NCCL and RCCL and share lessons learned from deploying XCCL at exascale on Aurora.

## Speakers

- [Panagiotis Kourdis](https://sessionize.com/api/v2/s2rq62nk/view/markdown/speaker/d7cf2f41-f774-4701-b76d-f8329bbdcc73) — AI Frameworks Engineer, Intel
- [Tanima Dey](https://sessionize.com/api/v2/s2rq62nk/view/markdown/speaker/ea8dcaa8-51ac-4b72-94ae-b9f3ca2ec499) — AI Frameworks Engineer, Intel