nccl

NumPy & SciPy for GPU

Safe rust wrapper around CUDA toolkit

Best practices & guides on how to write distributed pytorch training code

An open collection of methodologies to help with successful training of large language models.

An open collection of implementation tips, tricks and resources for training large language models

Efficient Distributed GPU Programming for Exascale, an SC/ISC Tutorial

Distributed and decentralized training framework for PyTorch over graph

Federated Learning Utilities and Tools for Experimentation

NCCL Fast Socket is a transport layer plugin to improve NCCL collective communication performance on Google Cloud.

Experimental Explicit Communications API for Kokkos

N-Ways to Multi-GPU Programming

Sample examples of how to call collective operation functions on multi-GPU environments. A simple example of using broadcast, reduce, allGather, reduceScatter and sendRecv operations.

A Julia wrapper for the NVIDIA Collective Communications Library.

Python Distributed Non Negative Matrix Factorization with custom clustering

🎹 Instruct.KR 2025 Summer Meetup: 오픈소스 LLM, vLLM으로 Production까지 🎹

NCCL Examples from Official NVIDIA NCCL Developer Guide.

A Reliable and Resilient Collective Communication Library for NCCL and others

GPU-accelerated linear solvers based on the conjugate gradient (CG) method, supporting NVIDIA and AMD GPUs with GPU-aware MPI, NCCL, RCCL or NVSHMEM

High performance NCCL plugin for Bagua.

Build NCCL-Tests and configure SSHD in PyTorch container to help you test NCCL faster!