Opportunities for Machine Learning in Electronic Design Automation

被引:21
作者
Beerel, Peter A. [1 ]
Pedram, Massoud [1 ]
机构
[1] Univ Southern Calif, Ming Hsieh Dept Elect Engn, Los Angeles, CA 90089 USA
来源
2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2018年
关键词
POWER MANAGEMENT; CIRCUITS; SYSTEM; BLADE;
D O I
10.1109/ISCAS.2018.8351731
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The rise of machine learning (ML) has introduced many opportunities for computer-aided-design, VLSI design, and their intersection. Related to computer-aided design, we review several classical CAD algorithms which can benefit from ML, outline the key challenges, and discuss promising approaches. In particular, because some of the existing ML accelerators have used asynchronous design, we review the state-of-the-art in asynchronous CAD support, and identify opportunities for ML within these flows.
引用
收藏
页数:5
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