PRIMAL: Power Inference using Machine Learning

This paper introduces PRIMAL, a novel learning-based frame-work that enables fast and accurate power estimation for ASIC designs. PRIMAL trains machine learning (ML) models with design verification testbenches for characterizing the power of reusable circuit building blocks. The trained models can t...

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Bibliographic Details

Published in:	Proceedings of the 56th Annual Design Automation Conference 2019 pp. 1 - 6
Main Authors:	Zhou, Yuan, Ren, Haoxing, Zhang, Yanqing, Keller, Ben, Khailany, Brucek, Zhang, Zhiru
Format:	Conference Proceeding
Language:	English
Published:	ACM 01.06.2019
Subjects:	Analytical models Encoding Estimation Integrated circuit modeling Logic gates machine learning Power estimation Registers Solid modeling
Online Access:	Get full text
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