[2024 Fall] Embedded Systems and Labs
Course Information
| Course | Embedded Systems and Labs | Department | Computer Science and Engineering |
|---|---|---|---|
| Office Hours | TBA | Course No. and Class | 37271-02 |
| Hours | 3.0 | Academic Credit | 3.0 |
| Professor | Yoon, Myung Kuk | Office | Jinseonmi-Gwan, 213 |
| Telephone | (82)-2-3277-3819 | myungkuk.yoon at ewha.ac.kr | |
| Value of Competence | Pursuit of Knowledge(70), Creative Convergence(30) | Keyword | Computer System, System Software, Real-Time System |
| Class Time | (Wed) 12:30 ~ 15:15 |
Course Description
-
This course explores the fundamentals and advanced techniques of embedded systems using the Jetson Nano platform. It is designed to provide students with a strong foundation in embedded systems while delving into advanced C programming and the CUDA language for leveraging the power of NVIDIA GPUs. * The primary syllabus used for this course is from the website rather than the traditional school system. Consequently, any significant updates or changes will be made exclusively to the web syllabus. * Due to the use of the new board in this course, the syllabus may be updated throughout the semester. * Some lecture materials may contain Korean; however, the primary language for this course is English. Most materials and exams will be predominantly provided in English. * Due to limited seats and available embedded boards, the number of students for this course is strictly capped. This count will not change, even if you send an email. PLEASE DO NOT REQUEST AN INCREASE IN THE NUMBER OF SEATS FOR THIS COURSE.
Prerequisites
- Basic knowledge of the C/C++ programming language is required.
- Strongly recommended only for students who have completed the Digital Logic Design and Computer Architecture course to take this class.
Course Format
| Lecture | Discussion/Presentation | Experiment/Practicum | Field Study | Other |
|---|---|---|---|---|
| 40% | 0% | 60% | 0% | 0% |
Course Objectives
In this class, students will be introduced to:
- Embedded Systems
- Linux
- CUDA Programming
- Neural Network
- And more topics if time permits
Evaluation System
Evaluation: Relative + Absolute
| Midterm Exam | Final Exam | Quizzes | Presentations | Projects | Assignment | Participation | Other |
|---|---|---|---|---|---|---|---|
| 35% | 35% | 0% | 0% | 0% | 30% | 0% | 0% |
- About 40% of students: A (Including A+/A/A-)
- About 40% of students: B (Including B+/B/B-)
- About 20% of students: C and below
- If your total score does not exceed 30%, you will get an "F" regardless of the percentage above.
- If you are absent more than three times, you will get an "F."
- If you are late twice, you are considered absent once.
- The course is specifically designed for sophomore and junior students; hence, absences related to job positions or interviews cannot be accepted as excuses.
- Complete your assignments and exams independently. Any instances of plagiarism, whether from fellow students or online sources, will result in an automatic 'F' in this course, regardless of your current standing.
Required Materials
The lecture material will be made available on Cyberampus.
Supplementary Materials
NONE
Optional Additional Readings
NONE
Course Contents
| Week | Date | Topics & Materials | Assignement & Quiz & Etc. |
|---|---|---|---|
| Week #01 | 2024/09/04 (Wed) | Lecture #01: Introduction to the Course | |
| Week #02 | 2024/09/11 (Wed) | Lecture #02: Overview of Embedded Systems | |
| Week #03 | 2024/09/18 (Wed) | NO CLASS (Thanksgiving) | |
| Week #04 | 2024/09/25 (Wed) | Lecture #03: Development of Nvidia Jetson Embedded Software in C on Linux Operating System | |
| Week #05 | 2024/10/02 (Wed) | Lecture #04: Development of Nvidia Jetson Embedded Software in C on Linux Operating System | |
| Week #06 | 2024/10/09 (Wed) | NO CLASS (Hangul Proclamation Day) | |
| Week #07 | 2024/10/16 (Wed) | Lecture #05: Structure of Embedded Software | |
| Week #08 | 2024/10/23 (Wed) | Lecture #06: Structure of Embedded Software | |
| 2024/10/26 (Sat) | Lecture #07: Midterm Exam (11:00AM ~ 12:30PM) [Asan 107] | ||
| Week #09 | 2024/10/30 (Wed) | Lecture #08: NVIDIA GPU Architecture | |
| Week #10 | 2024/11/06 (Wed) | Lecture #09: How to Use NVIDIA CUDA | |
| Week #11 | 2024/11/13 (Wed) | Lecture #10: Relationship Between Convolutional Neural Networks (CNN) and Matrix Multiplication | |
| Week #12 | 2024/11/20 (Wed) | Lecture #11: Thread Hierarchy | |
| Week #13 | 2024/11/27 (Wed) | Lecture #12: Memory Hierarchy Structure | |
| Week #14 | 2024/12/04 (Wed) | Lecture #13: NVIDIA Profiling | |
| Week #15 | 2024/12/11 (Wed) | Lecture #14: NVIDIA Profiling | |
| 2024/12/14 (Sat) | Lecture #15: FINAL EXAM (11:00AM ~ 12:30PM) [Asan 107] | ||
| Week #16 | 2024/12/20 (Fri) | Final Exam Review (Nonmandatory) |
Course Policies
For laboratory courses, all students are required to complete lab safety training.
Special Accommodations
According to the University regulation #57, students with disabilities can request special accommodation related to attendance, lectures, assignments, and/or tests by contacting the course professor at the beginning of semester. Based on the nature of the students’ requests, students can receive support for such accommodations from the course professor and/or from the Support Center for Students with Disabilities (SCSD).
Extra Information
The contents of this syllabus are not final—they may be updated.