High Performance Computing

Catalog description

An introduction to High Performance Computing (HPC), with an emphasis on the programming and analysis aspects of HPC for the practicing scientist, engineer or technologist. This course will prepare students to analyze, design, implement and evaluate parallel algorithms and computer codes. This course will cover the motivation for parallel programming, a description and analysis of Amdahl’s Law, and parallel-programming methodology. Shared-memory and distributed-memory concepts will be compared, and current programming application programming interfaces (APls) will be covered. General knowledge of undergraduate mathematics, science, engineering or technology required. Course may be offered in traditional classroom-based, distance, or blended formats. Typically offered Fall Spring Summer. Course Learning Outcomes 1. Students will be able to apply fundamental concepts in parallel computing: e.g. Amdahls Law, load balancing, domain decomposition, etc. 2. Students will gain experience with distributed-memory parallelism and programming skill with the Message-Passing Interface (MPI) programming API. 3. Students will gain experience with shared-memory parallelism and programming skill with the Pthreads and OpenMP programming APIs. 4. Students will learn to develop, analyze and optimize parallel algorithms for peak performance characteristics. 5. Students will gain research experience in the implementation of parallel programming techniques through unique projects individually designed by the student and instructor. View Class Schedule