Unleashing Flexibility of ML-based Power Estimators Through Efficient Development Strategies-Reference-Cited by-同舟云学术

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Unleashing Flexibility of ML-based Power Estimators Through Efficient Development Strategies

Published:2024-08-05 Issue: Volume: Page:1-6
ISSN:
Container-title:Proceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design
language:
Short-container-title:

Author:

Lu Yao¹^ORCID,Zhang Qijun¹^ORCID,Xie Zhiyao¹^ORCID

Affiliation:

1. Hong Kong University of Science and Technology, Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3665314.3670823

Reference20 articles.

1. 2008. TSMC 40nm LP process technology. https://www.tsmc.com/english/dedicatedFoundry/technology/logic/l_40nm.

2. 2021. Design Compiler® RTL Synthesis. https://www.synopsys.com/implementation-and-signoff/rtl-synthesis-test/design-compiler-nxt.html.

3. 2021. PowerPro® RTL Low-Power. https://www.mentor.com/hls-lp/powerpro-rtl-low-power/.

4. 2021. VCS® functional verification solution. https://www.synopsys.com/verification/simulation/vcs.html.

5. 2022. RISC-V Tests. https://github.com/riscv-software-src/riscv-tests.

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