EE 217: GRAPHICS PROCESSING UNIT ARCHITECTURE AND PARALLEL PROGRAMMING
University of California, Riverside
4 Units, Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): CS 160 with a grade of "C-" or better; graduate standing; or consent of instructor. 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. Cross-listed with CS 217.
Average GPA: 3.62
Grade distribution records: 60 students across 4 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 8 | 13.3% |
| A | 27 | 45.0% |
| A- | 7 | 11.7% |
| B+ | 9 | 15.0% |
| B | 3 | 5.0% |
| B- | 1 | 1.7% |
| C | 3 | 5.0% |
| F | 1 | 1.7% |
| NP | 1 | 1.7% |
Based on 60 student grade records across 4 terms and 2 professors.
Instructors
- Daniel Wong 39 students, Average GPA 3.70
- Nael Abu-Ghazaleh 21 students, Average GPA 3.46