Introduction to CUDA Programming for Physicists - Lecture 4

Delve into the final installment of a four-part course on CUDA programming tailored for physicists. Explore advanced concepts in GPU computing, including reduction operations and specialized CUDA libraries. Learn about the architecture of GPUs, their computing units, memory structure, and interaction with host computers. Discover the types of tasks best suited for GPU acceleration. Master memory operations, including allocation and data transfer between host and GPU, as well as the use of GPU shared memory. Gain proficiency in writing CUDA kernels and managing streams for task synchronization. Investigate reduction operations on GPUs and familiarize yourself with essential CUDA libraries such as cuFFT, cuBLAS, cuSPARSE, and cuRAND. Enhance your ability to leverage GPU computing power for complex numerical computations in physics, potentially achieving substantial speed improvements through parallelization.