NDLI: Relay-Race Algorithm: A Novel Heuristic Approach to VLSI/PCB Placement

Content Provider	IEEE Xplore Digital Library
Author	Yiqiang Sheng Takahashi, A. Ueno, S.
Copyright Year	2011
Abstract	In this paper, we present a novel heuristic approach, called relay-race algorithm (RRA), with motivation to improve solution quality and reduce computational time for VLSI/PCB placement. RRA is to simulate the relay-race game, in which each runner participates in a part of race and then is relayed by another member of the team. RRA is designed to overcome the shortcomings of simulated annealing (SA) and genetic algorithm (GA). The basic idea is to use a guide to adjust running methods according to the experience of past runs and a relay to escape local optimum in only one step. Based on the experimental results, RRA improved the placement for both interconnect and area optimization, comparing with SA. For interconnect optimization using ami49_X benchmarks, RRA obtained stable improvement for the Pareto frontier of two conflicting objectives: power and performance. In several cases, we got more than 30% improvement of interconnect power consumption without any degradation of performance. For area minimization using MCNC benchmarks, RRA reduced at least 40% computational time with better solution quality. With respect to its impact, RRA has potential to improve the existing approaches for more NP-hard problems in different fields.
Starting Page	96
Ending Page	101
File Size	239791
Page Count	6
File Format	PDF
ISBN	9781457708039
ISSN	21592477
DOI	10.1109/ISVLSI.2011.8
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-04
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Relays Focusing Genetic algorithms Very large scale integration Optimization Layout Delay small area relay-race algorithm heuristic approach multi-objective optimization VLSI/PCB placement low power high performance
Content Type	Text
Resource Type	Article

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