Solution Space Reduction of Simulated Evolution Algorithm for Solving Standard Cell Placement Problem

Shiraishi, Yasuyuki; Ono, Tetsuya; Dahb, Mona Abo El

doi:10.1109/icnc.2009.681

Cited by 1 publication

(1 citation statement)

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“…There are other methods that have been used to solve the SCP problem, using genetic algorithms (parallel genetic algorithm (PGA) [19] and genetic algorithm for placement (GAP) [20]), simulated evolution (force-directed simulated evolution [21] and distributed parallelized SE algorithm (SimE) [22]) in addition to some hybridized methods (parallel simulated annealing/genetic algorithm (PSAGA) [23] and SimE-GA [24]); however, these methods are not as competitive, being tested on older benchmarks. Although simulated evolution was used to solve instances of the PEKO suite in [25], it is not included in the experimental results as it was uncompetitive, with quality ratios ranging from 6.33 to 8.52.…”

Section: Related Workmentioning

confidence: 99%

A Swarm Random Walk Based Method for the Standard Cell Placement Problem

Altwaijry

Menaï

2014

Mathematical Problems in Engineering

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The standard cell placement (SCP) problem is a well-studied placement problem, as it is an important step in the VLSI design process. In SCP, cells are placed on chip to optimize some objectives, such as wirelength or area. The SCP problem is solved using mainly four basic methods: simulated annealing, quadratic placement, min-cut placement, and force-directed placement. These methods are adequate for small chip sizes. Nowadays, chip sizes are very large, and hence, hybrid methods are employed to solve the SCP problem instead of the original methods by themselves. This paper presents a new hybrid method for the SCP problem using a swarm intelligence-based (SI) method, called SwarmRW (swarm random walk), on top of a min-cut based partitioner. The resulting placer, called sPL (swarm placer), was tested on the PEKU benchmark suite and compared with several related placers. The obtained results demonstrate the effectiveness of the proposed approach and show that sPL can achieve competitive performance.

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