Your question is Design GPU Direct Training Stack. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are building a distributed deep learning training platform for multi GPU jobs across several servers. Training throughput is limited by gradient synchronization and host side data movement, so the team is evaluating direct GPU to network transfers.
How does GPUDirect RDMA improve distributed training performance, and what hardware components must support it?