You are working on deploying a deep learning model that requires significant GPU resources across multiple nodes. You need to ensure that the model…

InfiniBand (C) is the most suitable networking technology for scalable, low-latency data transfer in

multi-node GPU training. It offers high throughput (up to 400 Gbps) and ultra-low latency (<1 µs),

ideal for synchronizing gradients and weights across nodes using NVIDIA NCCL. InfiniBand’s RDMA

(Remote Direct Memory Access) further enhances efficiency by bypassing CPU overhead, critical for

distributed deep learning.

Wi-Fi 6(A) lacks the reliability and bandwidth (max ~10 Gbps) for training clusters.

Fiber Channel(B) is for storage, not compute node interconnects.

Ethernet (1 Gbps)(D) is too slow for large-scale AI training demands.

NVIDIA’s DGX systems use InfiniBand for this purpose (C).

Reference:NVIDIA DGX Networking Guide; InfiniBand documentation on nvidia.com.