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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Vydané v:	Proceedings of the 56th Annual Design Automation Conference 2019 s. 1 - 6
Hlavní autori:	Zhou, Yuan, Ren, Haoxing, Zhang, Yanqing, Keller, Ben, Khailany, Brucek, Zhang, Zhiru
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	ACM 01.06.2019
Predmet:	Analytical models Encoding Estimation Integrated circuit modeling Logic gates machine learning Power estimation Registers Solid modeling
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