| Call Number | 19983 |
|---|---|
| Day & Time Location |
W 1:10pm-3:40pm 644 Seeley W. Mudd Building |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Zoran Kostic - homepage |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | Advanced-level lab-based course. Build and experiment with deep-learning models implemented on low-power GPU edge computing device. Topics: architectures of low-power GPU devices, algorithms and DL models suitable for edge implementation, CUDA language, pre-processing of data, labeling for ground-truth annotation, profiling techniques, connectivity between edge devices and cloud computing servers, real-life data for experimentation, comparison of performance for a variety of methods, comparison of performance of edge-computing and cloud computing approaches. |
| Web Site | Vergil |
| Department | Electrical Engineering |
| Enrollment | 21 students (25 max) as of 1:06PM Tuesday, January 20, 2026 |
| Subject | Electrical Engineering and Computer Science |
| Number | E6792 |
| Section | 001 |
| Division | School of Engineering and Applied Science: Graduate |
| Open To | Engineering:Graduate, GSAS |
| Section key | 20261EECS6792E001 |