What is the purpose of using NCCL in verifying East-West fabric in an NVIDIA AI...

NCCL is used to validate GPU communication behavior across the East-West fabric, so the correct answers are measuring latency between GPUs and measuring bandwidth between GPUs. NVIDIA describes NCCL as a topology-aware library of multi-GPU collective communication primitives, and NVIDIA GPU debug guidance specifically identifies NCCL performance tests, such as all_reduce_perf, as useful for establishing network performance between groups of nodes. In an AI Factory, East-West traffic is the server-to-server traffic used during distributed training. When models scale across many GPUs and nodes, operations such as all-reduce, broadcast, all-gather, and reduce-scatter depend on low latency and high bandwidth. NCCL testing helps confirm that GPU-to-GPU paths, GPUDirect RDMA, InfiniBand or Spectrum-X fabric behavior, routing, and collective communication performance are healthy before production workloads start. NCCL is not intended to measure storage performance; that requires storage benchmarks or GPUDirect Storage validation. It also does not measure GPU power consumption; that is handled by tools such as nvidia-smi, DCGM, or platform telemetry.