Return
Process variation-aware gate sizing with fuzzy geometric programming
DOI:10.1016/j.compeleceng.2019.07.015.png)
Abstract
En 中文
Limitations of manufacturing process in nanometer dimensions have led to large discrepancies between the circuit design and the manufactured chip known as process variation. In this paper, a new gate sizing method based on fuzzy geometric optimization approach is introduced for power minimization of digital circuits subjected to timing constraints under process variations. In the proposed geometric optimization approach, an accurate gate delay model is applied in which the delay variation is represented by fuzzy numbers; therefore, the subsequent optimization problem is a fuzzy geometric programing problem. In order to efficiently solve the fuzzy geometric programing problem, firstly, the problem is converted into a fuzzy linear programming problem and then, using the expected value and Mellin transform, it is converted into a non-fuzzy problem which is solved by traditional solution techniques. Experimental results show that, the proposed technique achieve more power reduction compared to a fuzzy linear programming method. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords:
Digital circuit
Gate sizing
Fuzzy geometric optimization
Power consumption
Process variation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
4.9
Papers:
6.7K
Citations:
1.3W
Organization
Cited Papers
Design and characterization of guided mode resonance filters with the improved structure for facile fabrication
Optik
IF0

