GPU Memory Hierarchy and Optimization

This lecture covers the GPU memory hierarchy, including global, local, shared memory, and caches, and discusses the challenges of SIMT execution. It delves into optimizing algorithms for GPUs by coalescing accesses, reducing bank conflicts, and eliminating warp divergence. The lecture also emphasizes the importance of understanding the algorithm's nature to optimize memory-intensive code efficiently.