JOURNAL ARTICLE
Correction Method for Power Analysis of Digital Integrated Circuits Based on Standard Cells.
Published In: Journal of Circuits, Systems & Computers, 2025, v. 34, n. 7. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Li, Qunlin; Lyu, Zejia; Shen, Jizhong 3 of 3
Abstract
With the rise of digital integrated circuit technology and the prevalence of mobile smart devices, chip power consumption and heat generation have become critical concerns. Accurate and swift power analysis is vital in integrated circuit design to prevent redesign setbacks. PrimeTime PX (PTPX), a robust circuit simulation tool from Synopsys, offers power analysis capabilities, boasting speed advantages over the industry gold standard HSPICE but faces a certain level of accuracy loss. This work investigates the disparities between PTPX and HSPICE tools in digital circuit power analysis and proposes a correction algorithm based on standard cells. The algorithm conducts power simulations on the most commonly used standard cell circuits, analyzes the error correlation between PTPX and HSPICE via numerical regression, and derives correction factors that quantify these discrepancies. For a given circuit, once the PTPX power result is obtained, the error is promptly estimated using these correction factors. The summation of the PTPX result and the estimated error yields the corrected result. Experimental results show an average error between PTPX and HSPICE power results is 18.51%, reduced to 9.01% after correction. The proposed algorithm implementation scarcely incurs extra time, enhancing accuracy by an average of 9.50 percentage points. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Circuits, Systems & Computers. 2025/05, Vol. 34, Issue 7, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2025
- ISSN:0218-1266
- DOI:10.1142/S0218126625501324
- Accession Number:184767074
- Copyright Statement:Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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