What networking technology is best for minimizing communication latency between multiple NVIDIA GPUs during model training?

InfiniBand is the most suitable networking technology for minimizing communication latency between multiple NVIDIA GPUs during model training due to its design and performance characteristics specifically tailored for high-performance computing (HPC) and data-intensive tasks.

InfiniBand offers several advantages: it supports high bandwidth and low latency communication, which is critical in the context of training machine learning models where data moves rapidly between GPUs. With a dedicated switching architecture and efficient data transfer protocols, InfiniBand reduces the time it takes for GPUs to exchange information, allowing for faster convergence during model training.

In contrast, Ethernet, while widely used for network communication, generally introduces higher latencies and lower throughput compared to InfiniBand, especially under heavy loads. Fibre Channel, primarily used for storage networking, doesn't have the same optimization for general-purpose GPU communications and tends to be less flexible. Wi-Fi, although convenient for wireless connectivity, has inherently higher latencies and lower reliability in communication compared to wired solutions like InfiniBand, making it unsuitable for performance-critical GPU applications.

Thus, the outstanding performance metrics of InfiniBand make it the optimal choice for minimizing communication latency in scenarios involving multiple NVIDIA GPUs.