2023년도 2학기 컴퓨터공학특강:이종 병렬 컴퓨팅 (CSED490C-01) 강의계획서

1. 수업정보

학수번호 CSED490C 분반 01 학점 3.00
이수구분 전공선택 강좌유형 강의실 강좌 선수과목
포스테키안 핵심역량
강의시간 화, 목 / 15:30 ~ 16:45 / 제2공학관 강의실 [107호] 성적취득 구분 G

2. 강의교수 정보

성효진 이름 성효진 학과(전공) 인공지능대학원
이메일 주소 hsung@postech.ac.kr Homepage
연구실 전화 054-279-2255
Office Hours

3. 강의목표

Heterogeneous parallel systems with a host CPU and various devices provide high performance and energy efficiency and are widely adopted from supercomputers to edge devices. In this course, you will learn common architectures and parallel algorithm patterns for heterogeneous systems, high-level programming interfaces for HPC and AI applications (OpenCL/OpenMP, TensorFlow), and performance optimization techniques, etc. and work on programming projects.

4. 강의선수/수강필수사항

Computer architectures and data structures are recommended prerequisite classes.

5. 성적평가

Midterm: 15%
Final exam: 20%
Programming assignments: 40%
Project: 20%
Attendance: 5%

6. 강의교재

도서명 저자명 출판사 출판년도 ISBN
Programming Massively Parallel Processors: A Hands-on Approach, 3rd edition David Kirk, Wen-mei Hwu Morgan Kaufmann 2016 9780128119877

7. 참고문헌 및 자료

8. 강의진도계획

Week 1
9/5 Introduction and overview
9/7 Parallel computing basics 1

Week 2
9/12 Parallel computing basics 2
9/14 GPU architectures 1

Week 3
9/19 GPU architectures 2
9/21 Intro to CUDA

Week 4
9/26 CUD programming model, Lab 0 out
9/28 No class (Chusuk holiday)


Week 5
10/3 No class (National foundation day)
10/5 Memory and data locality 1, Lab 0 due

Week 6
10/10 Memory and data locality 2, Lab 1 out
10/12 Thread execution efficiency

Week 7
10/17 Performance considerations 1, Lab 1 due, Lab 2 out
10/19 Performance considerations 2

Week 8
10/24 Parallel patterns: convolution 1, Lab 2 due, Lab 3 out
10/26 Parallel paterns: convolution 2

Week 9
10/31 Lab 3 due
11/2 Midterm 3:30pm-5:30pm

Week 10
11/7 Parallel patterns: histogram, Lab 4 out, Project out
11/9 Parallel patterns: reduction

Week 11
11/14 Parallel patterns: scan, Lab 4 due, Lab 5 out
11/16: Parallel patterns: sparse computation 1

Week 12
11/21 Parallel patterns: sparse computation 2, Lab 5 due, Lab 6 out
11/23 Related GPU programming models 1

Week 13
11/28 Related GPU programming models 2, Lab 6 due
11/30 Multi-GPU

Week 14
12/5 Libraries and framework support
12/7 Efficient deep learning

Week 15
12/12 DL accelerators
12/14 Project final presentations

Week 16
12/21 Final exam 3:30pm-5:30pm
12/23 Project due

9. 수업운영

10. 학습법 소개 및 기타사항

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