nccl

What problem does it solve?

Facilitates high-efficiency communication among multiple GPUs in distributed systems, enabling scalable parallel training and computing tasks.

Core Features & Use Cases

• Collective Operations: Provides routines like AllReduce, Broadcast, and ReduceScatter for synchronized data sharing.
• Multi-Node Support: Efficiently handles communication across multiple nodes with high bandwidth interconnects such as NVLink and InfiniBand.
• Use Case: Accelerate deep learning training across multiple GPUs by seamlessly coordinating gradient updates and parameter synchronization.

Quick Start

Use the NCCL library in your CUDA-enabled application to perform scalable multi-GPU communication tasks by initializing communicators and invoking collective APIs.