nccl

Why we included this project

NCCL is the de-facto communication backbone for large-scale distributed training on NVIDIA GPUs. Most deep learning frameworks lean on it internally, so anyone who builds or maintains training infrastructure will want to understand it even if they never touch its C source. The library implements the standard collective operations: all-reduce, all-gather, broadcast, reduce-scatter, and arbitrary send/receive patterns, which frameworks invoke constantly to keep gradients and weights in sync across devices. Its real value is being topology-aware. NCCL picks different algorithms and routes depending on whether GPUs are talking over NVLink, PCIe, NVSwitch, or InfiniBand and TCP across nodes, so the same code runs on a single workstation and a multi-node cluster without manual tuning. Packaging covers deb, rpm, tarball, and Python wheel outputs, which makes it easy to slot into custom GPU environments rather than relying on a framework's bundled copy.