CS 217: GRAPHICS PROCESSING UNIT ARCHITECTURE AND PARALLEL PROGRAMMING
University of California, Riverside
4 Units, Lecture, 3 hours; consultation, 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 EE 217.
Average GPA: 3.71
Grade distribution records: 502 students across 7 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 38 | 7.6% |
| A | 234 | 46.6% |
| A- | 109 | 21.7% |
| B+ | 70 | 13.9% |
| B | 34 | 6.8% |
| B- | 4 | 0.8% |
| C+ | 5 | 1.0% |
| C | 2 | 0.4% |
| C- | 1 | 0.2% |
| F | 2 | 0.4% |
| NP | 1 | 0.2% |
| S | 2 | 0.4% |
Based on 502 student grade records across 7 terms and 2 professors.
Instructors
- Daniel Wong 464 students, Average GPA 3.72
- Nael Abu-Ghazaleh 38 students, Average GPA 3.67