Parallel Computing: Principles, Systems, and Programming

The increasing demand for AI, genomics, real-time data analytics, and other emerging applications has made parallel computing indispensable-from multi-core CPUs/GPUs in local environments to cloud infrastructures and the largest supercomputers.This course aims to develop a fundamental understanding of the principles of parallelism and design trade-offs in modern computing systems, covering hardware architecture, software efficiency, and algorithm optimization. Students will acquire practical parallel programming techniques (including GPU programming) and explore key performance metrics beyond speed, such as scalability and energy efficiency.