20. Efficiency

This section is about doing more with the GPUs you have: training and serving models faster and within tighter memory budgets. It covers training-side efficiency techniques (mixed precision, memory savings, faster kernels, and efficient fine-tuning), how to monitor a running job and diagnose its bottleneck, and how to deploy and serve models efficiently at inference time.