Graphics processing units (GPU) can be programmed like a coprocessor to solve non-graphics problems, including voice recognition, computational physics, convolutional neural networks, and machine learning. The many processing cores of a GPU support a high-degree of parallelism. Course topics include hardware architecture, algorithmic design, programming languages (e.g., CUDA, OpenCL), and principles of programming for GPUs for high performance. Prerequisites: CMPUT 201 or 275, and one of CMPUT 229, E E 380, or ECE 212.
Section | Capacity | Class times | Login to view Instructor(s) and Location |
---|---|---|---|
LECTURE A1
(51239) |
100 |
2024-09-03 - 2024-12-09 (MWF)
14:00 - 14:50
|
|
Section | Capacity | Class times | Login to view Instructor(s) and Location |
---|---|---|---|
LAB D01
(51240) |
23 |
2024-09-03 - 2024-12-09 (T)
14:00 - 16:50
|
|
LAB D02
(51241) |
77 |
2024-09-03 - 2024-12-09 (T)
17:00 - 19:50
|
|