3. 강의목표
This class will explore key concepts in hardware and software supports for parallel and distributed computing workloads. The primary objectives of this class are:
- Learn the foundations of parallel and distributed computing
- Gain hands-on knowledge of the fundamentals of parallel programming
- Learn algorithms and runtime built for modern large-scale data processing
4. 강의선수/수강필수사항
Operating Systems, Computer Architecture
5. 성적평가
Attendance (10%), Midterm (25%), Final (25%), Project & assignments (40%)
Be aware that these weights are subject to changes.
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Introduction to Parallel Computing, 2nd Ed / Ananth Grama, Anshul Gupta, George Karypis, Vipin Kumar / Addison-Wesley/ 2003 / 0201648652
|
|
|
0000
|
|
7. 참고문헌 및 자료
Introduction to Parallel Computing (2018) / Roman Trobec, Bostjan Slivnik, Patricio Bulic, Borut Robic/ https://link.springer.com/book/10.1007/978-3-319-98833-7#about
8. 강의진도계획
Week 1: Principles of parallel algorithm design
Week 2: Principles of parallel algorithm design
Week 3: Programming shared-address space systems
Week 4: Programming shared-address space systems
Week 5: Parallel computer architectures
Week 6: Programming scalable systems
Week 7: Analytical modeling of program performance
Week 8: Midterm
Week 9: Collective communication
Week 10: Synchronization
Week 11: Performance measurement and analysis of parallel programs
Week 12: Clusters, Cloud, Serverless
Week 13: Fault tolerance
Week 14: Machine Learning scalability on GPUs
Week 15: Problem solving on clusters
Week 16: Final
9. 수업운영
This course will be based on regular offline lectures. Each student is expected to perform programming assignments individually over the semester.
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청