Beyond Performance Hacks: A First-Principles Guide to Deep Learning Optimization

Instead of relying on ad-hoc performance tweaks, understanding your system's bottleneck—whether compute, memory bandwidth, or overhead—allows you to focus optimization efforts where they matter most. This first-principles approach transforms deep learning optimization from trial-and-error alchemy into systematic engineering. As compute growth increasingly outpaces memory bandwidth, developers who master this framework will unlock significant efficiency gains in GPU-accelerated workloads.