Question

A data science team is scaling a large deep learning training job across 8 GPUs inside a single server. They observe that as they add more GPUs, training throughput does not increase proportionally, and profiling shows significant time spent transferring gradient data between GPUs over the standard PCIe bus. Which NVIDIA technology is specifically designed to address this GPU-to-GPU communication bottleneck?

Accepted Answer

NVLink, a high-bandwidth interconnect for direct GPU-to-GPU data transfer

Answer

cuDNN, a library of optimized deep learning primitives

Answer

Triton Inference Server, for serving trained models at scale

Answer

MIG, which partitions a single GPU into isolated instances