Your question is Batching and Mixed Precision Effects. 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).
How do batching, mixed precision, and memory coalescing affect GPU performance?
Answer this as a practical GPU training investigation. Use a representative PyTorch training workload and explain the mechanisms behind observed changes in throughput, GPU utilization, memory consumption, numerical behavior, and end-to-end latency. Compare multiple batch sizes, FP32 against mixed precision, and coalesced against deliberately non-coalesced memory access. State how you would benchmark fairly, identify bottlenecks, and decide whether an optimization is safe for production.
