Prerequisites: CS 160 with a grade of “C-” or better or consent of instructor
Description: Introduces the popular CUDA based parallel programming environments based on Nvidia GPUs. Covers the basic CUDA memory/ threading models. Also covers the common data- parallel programming patterns needed to develop a high-performance parallel computing applications. Examines computational thinking; a broader range of parallel execution models; and parallel programming principles. May be taken Satisfactory (S) or No Credit (NC) with consent of instructor and graduate advisor. May be taken Satisfactory (S) or No Credit (NC) by students advanced to candidacy for the Ph.D.
Cross-listing: Cross- listed with CS 217.