Your question is Distributed GPU Memory Optimization. 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 you optimize memory allocation and prevent fragmentation when training large-scale models on distributed GPU clusters?