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 CMPUT 229.
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LECTURE A1
(86226) |
66 |
2023-09-05 - 2023-12-08 (MWF)
14:00 - 14:50
SAB 3-31
Final Exam: 2023-12-18
09:00 - 12:00
ONLINE -------
|
Primary Instructor: Pierre Boulanger
|
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LAB D01
(86227) |
22 |
2023-09-05 - 2023-12-08 (T)
14:00 - 16:50
CSC 1-67
|
|
|
LAB D02
(86228) |
22 |
2023-09-05 - 2023-12-08 (T)
17:00 - 19:50
CSC 1-67
|
|
|
LAB D03
(86229) |
22 |
2023-09-05 - 2023-12-08 (R)
14:00 - 16:50
CSC 1-67
|
|