High-performance computing and deep learning workloads are extremely sensitive to latency. Packet loss forces retransmission or stalls in the communication…
High-performance computing and deep learning workloads are extremely sensitive to latency. Packet loss forces retransmission or stalls in the communication pipeline, which directly increases latency and disrupts the synchronization between GPUs. This can degrade the performance of collective operations such as all-reduce or broadcast, where every GPU’s participation is required before progressing.
