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CENG5030 Energy Efficient (Deep Neural Network) Computing – Fall 2023
| Lecture: | W 14:30-18:15 | Venue: ERB404 |
| T 16:30-18:15 | Venue: LSK208 | |
| Zoom link: | https://cuhk.zoom.us/j/99214718595 | |
| Course Instructor: | Prof. Bei Yu | byu@cse.cuhk.edu.hk |
| Course Tutors: | Chaozheng Wang | czwang23@cse.cuhk.edu.hk |
Announcements
Aug. 31, 2023: Course webpage is built up and the teaching schedule is online.
Nov. 29, 2023: Group presentation is scheduled on Dec. 06 & 07.
Description:
This course is an intensive and research oriented course, discussing some practical and fundamental techniques, skills, and tools for deep neural network acceleration, in particular inference acceleration. The students selecting this course are assumed to have solid DNN experience and some programming skills (e.g, C/C++).
Course Requirements
Lab (30%), in-class quiz (30%), final presentations (40%), and extra bonus.
Please submit your lab reports through blackboard (link).
All in-class quizzes are closed-book.
Schedule
| Week | Date | Topic | Remark | |
| 1 | Sep. 06 | Lec1 Introduction (slides) | ||
| Sep. 07 | continue on Lec1 | |||
| 2 | Sep. 13 | Im1 GEMM (slides) | Zoom | |
| Sep. 14 | Lab1 GEMM | by Tutor | ||
| 3 | Sep. 20 | Im2 Direct Conv (slides) | ||
| Sep. 21 | Mo1 Pruning (slides) | |||
| 4 | Sep. 27 | continue on Im2 & Mo1 | ||
| Sep. 28 | Mo2 Decomposition (slides) | Quiz-1 | ||
| 5 | Oct. 04 | continue on Mo2 | ||
| Oct. 05 | continue on Mo2 | |||
| 6 | Oct. 11 | Im3 Winograd (slides) | ||
| Oct. 12 | Mo3 Quantization (slides) | |||
| 7 | Oct. 18 | continue on Mo3 | ||
| Oct. 19 | Mo4 BNN (slides) | |||
| 8 | Oct. 25 | Im4 Sparse Conv (slides) | ||
| Oct. 26 | continue on Im4 | Quiz-2 | ||
| 9 | Nov. 01 | — | 92nd Degree Congregation | |
| Nov. 02 | Lab2 | by Tutor | ||
| 10 | Nov. 08 | Mo5 KD (slides) | ||
| Nov. 09 | — | Lecturer in travel | ||
| 11 | Nov. 15 | Mo6 NAS (slides) | ||
| Nov. 16 | Im6 TVM (slides) | |||
| 12 | Nov. 22 | Lab3 | Quiz-3 | |
| Nov. 23 | — | Lecturer in travel | ||
| 13 | Nov. 29 | Im5 CUDA (slides) | ||
| Nov. 30 | — | |||
| 14 | Dec. 06 | Group presentations | ERB 401 | |
| Dec. 07 | Group presentations | LSK 206 |
References
All papers mentioned in lecture slides.
Sze, Vivienne, et al., “Efficient processing of deep neural networks”, Synthesis Lectures on Computer Architecture, 2020.
Erwei Wang et al., “Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going”, CSUR, 2019.
Qianru Zhang et al., “Recent Advances in Convolutional Neural Network Acceleration”, NeuroComputing, 2019.
Bing Li et al., “Running Sparse and Low-Precision Neural Network: When Algorithm Meets Hardware”, ASPDAC, 2018.
Group Presentation Schedule:
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Knowledge Graph
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