Learning Triton One Kernel at a Time: Matrix Multiplication

Matrix multiplication (GEMM) is a fundamental operation for GPUs in fields like machine learning, but naive implementations are highly inefficient due to redundant memory access. An optimization technique called tiling breaks large matrices into smaller blocks to improve data reuse and reduce memory loads. This approach leverages the GPU's memory hierarchy, loading data tiles into fast shared memory to minimize costly access to slower global High Bandwidth Memory (HBM). Understanding concepts like tiling, the memory hierarchy, and memory coalescing is essential for writing high-performance GPU kernels in frameworks like Triton.