How to Optimize a CUDA Matmul Kernel for cuBLAS-like Performance: a Worklog
In this post, I’ll iteratively optimize an implementation of matrix multiplication written in CUDA. My goal is not to build a cuBLAS replacement, but to deeply understand the most important performance characteristics of the GPUs that are used for modern deep learning. This includes coalescing global memory accesses, shared memory caching and occupancy optimizations, among others.
Read more →