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High-level language bindings that map to low-level GPU communication primitives for high-bandwidth data exchange.
Distinct from Python-C Interfaces: Distinct from Python-C Interfaces by specifically targeting GPU collective and P2P communication primitives rather than general numerical processing.
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NCCL is a high-performance communication library and distributed GPU computing framework designed for executing collective and point-to-point data exchanges across multiple GPUs in single or multi-node systems. It serves as an RDMA GPU transport layer and memory orchestrator, facilitating high-bandwidth synchronization of data and model gradients for distributed GPU training and inference. The library is distinguished by its ability to execute communication primitives directly from GPU kernels, removing the host CPU from the critical path. It utilizes topology-aware path selection to optimize
Exposes core high-performance communication primitives through a Python interface for easier integration into ML workflows.