Project-Based Learning: Bridging the Gap Between Algorithm and Architecture in Neural Network Course

Heming Sun, Lu Yu

研究成果: Conference contribution

抄録

Neural network has shown its powerful ability in many research fields in the recent years. By using different network structures, many new algorithms are developed to enhance the accuracy. Along with the algorithm development, corresponding architectures are also proposed for the acceleration. However, pure algorithm may not be hardware friendly. As a result, we need to find an optimal trade-off between algorithmic accuracy and architectural efficiency. To help students build the gap between algorithm and architecture, this paper introduces a project-based learning. The project is called learned image compression, which is composed of three phases: algorithm design, architecture mapping and algorithm-architecture co-optimization. Through the project, the students are expected to develop a neural network with high image compression ratio and hardware performance. Furthermore, these kind of knowledge can be extended to any neural network applications.

本文言語English
ホスト出版物のタイトルIEEE International Symposium on Circuits and Systems, ISCAS 2022
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2127-2131
ページ数5
ISBN(電子版)9781665484855
DOI
出版ステータスPublished - 2022
イベント2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 - Austin, United States
継続期間: 2022 5月 272022 6月 1

出版物シリーズ

名前Proceedings - IEEE International Symposium on Circuits and Systems
2022-May
ISSN(印刷版)0271-4310

Conference

Conference2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022
国/地域United States
CityAustin
Period22/5/2722/6/1

ASJC Scopus subject areas

  • 電子工学および電気工学

フィンガープリント

「Project-Based Learning: Bridging the Gap Between Algorithm and Architecture in Neural Network Course」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル