How do network solutions support machine learning training processes?

Networks support the high-performance demands of machine learning model training by providing efficient communication between processors or nodes. High-speed networks enable fast data transfer, which is crucial for distributing the computational workload of training large models across multiple devices or servers. This parallel processing capability helps reduce training time and accelerates the convergence of machine learning models. Furthermore, specialized network technologies, such as InfiniBand and RDMA (Remote Direct Memory Access), can further enhance performance by decreasing latency and increasing data throughput during model training processes.