Paper Info
Title
Field-Coupled Nanocomputing Placement and Routing With Genetic and A* Algorithms
Abstract
Field-Coupled Nanocomputing technologies have great potential to surpass CMOS technology because of their lower power consumption and higher device concentration. To ease the burden of placement and routing (P&R) problems for FCN circuits, many delicate two-dimensional clocking schemes have been proposed, upon which algorithms can solve the P&R problems more strategically. In this paper, we propose a two-level optimization strategy by using a genetic algorithm (GA) combined with an enhanced A* algorithm. Some circuit design requirements, such as clock synchronization, layout area, etc., are cleverly designed in the fitness value function of the GA. Numerical results demonstrate the effectiveness of the hybrid algorithm. In particular, compared to current tools, such as fiction and Ropper, the proposed algorithm can achieve an optimal solution with a higher success rate and a sizeable applicable circuit scale. In addition, the concept of design rule checking (DRC) was proposed in FCN and integrated into the algorithm, making the P&R results mapping from gate-level to cell-level more smoothly. Besides, the number of cross wires is significantly reduced, and the distribution of IO ports can be more effectively controlled.
Year
DOI
Venue
2022
10.1109/TCSI.2022.3197450
IEEE Transactions on Circuits and Systems I: Regular Papers
Keywords
DocType
Volume
Field-coupled nanocomputing,electronic design automation,placement and routing (P&R) algorithms,heuristic algorithm
Journal
69
Issue
ISSN
Citations 
11
1549-8328
0
PageRank 
References 
Authors
0.34
12
7
Name
Order
Citations
PageRank
Yangshuai Li100.34
Guangjun Xie287.32
Qian Han300.34
Xiaoshuai Li400.34
Gaisheng Li500.34
Bing Zhang600.34
Fei Peng736038.79