The NVIDIA Collective Communications Library (NCCL) implements multi-GPU and multinode (MGMN) communication primitives optimized for NVIDIA GPUs and networking. NCCL is a central piece of software for multi-GPU deep learning training. It handles any kind of inter-GPU communication, be it over PCI, NVLink, or networking. It uses advanced topology detection, optimized communication graphs…
]]>The NVIDIA Collective Communications Library (NCCL) implements multi-GPU and multinode communication primitives optimized for NVIDIA GPUs and networking. NCCL is a central piece of software for multi-GPU deep learning training. It handles any kind of inter-GPU communication, be it over PCI, NVLink, or networking. It uses advanced topology detection, optimized communication graphs…
]]>For the past few months, the NVIDIA Collective Communications Library (NCCL) developers have been working hard on a set of new library features and bug fixes. In this post, we discuss the details of the NCCL 2.22 release and the pain points addressed. NVIDIA Magnum IO NCCL is a library designed to optimize inter-GPU and multi-node communication, crucial for efficient parallel computing…
]]>Collective communications are a performance-critical ingredient of modern distributed AI training workloads such as recommender systems and natural language processing. NVIDIA Collective Communication Library (NCCL), a Magnum IO Library, implements GPU-accelerated collective operations: NCCL is topology-aware and is optimized to achieve high bandwidth and low latency over PCIe…
]]>Imagine using tens of thousands of GPUs to train your neural network. Using multiple GPUs to train neural networks has become quite common with all deep learning frameworks, providing optimized, multi-GPU, and multi-machine training. Allreduce operations, used to sum gradients over multiple GPUs, have usually been implemented using rings [1] [2] to achieve full bandwidth. The downside of rings is…
]]>NVIDIA Collective Communications Library (NCCL) provides optimized implementation of inter-GPU communication operations, such as allreduce and variants. Developers using deep learning frameworks can rely on NCCL’s highly optimized, MPI compatible and topology aware routines, to take full advantage of all available GPUs within and across multiple nodes. NCCL is optimized for high bandwidth and…
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