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Lecture 17: NCCL
NCCL: High-Speed Inter-GPU Communication for Large-Scale Training - Sylvain Jeaugey, NVIDIA
GPU-GPU Communication: Boosting HPC with Peer-to-Peer Access & RCCL/NCCL
MultiGPU + NCCL from the authors
📚 Advanced NCCL Tutorial: Beyond Collectives - Jeff Hammond & Hanyue He & Ke Wen, NVIDIA
Demystifying NVSHMEM: A System-Level Analysis on Symmetric Memory and Device-Initiated Operations...
NCCL Explained - NVIDIA Collective Communications Library for Multi-GPU AI Training
Multi-GPU Communication Libraries for Scaling HPC and AI Workloads | NVIDIA GTC 2025
Lecture 113: Every Microsecond Matters: Achieving Near Speed-of-Light Latency in GPU Collectives
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Last Updated: October 3, 2026
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This webinar provides an introduction to high-performance Code and Slides: github.com/cuda-mode/lectures/tree/main/lecture_017. Sylvain Jeaugey explores the mechanics of NVIDIA's NCCL library, detailing how it optimizes inter-GPU communication across diverse hardware configurations. The presentation covers the underlying architecture, efficient topology detection, and key strategies for accelerating deep learning training processes in multi-GPU and multi-node environments. In this tutorial, we will teach you how to use the newest features in Don't miss out! Join us at our next KubeCon + CloudNativeCon events in Mumbai, India (18-19 June, 2026), Yokohama, Japan ... In this AI Research Roundup episode, Alex discusses the paper: 'Collective Want to scale beyond the limits of a single
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