ICGST- AIML Journal

AIML Volume 06 - Issue (II) ICGST

HYBRID PARTICLE SWARM OPTIMIZATION FOR VLSI MACRO CELL PLACEMENT

1Ms.D.Jackuline Moni, 2Dr.S.Arumugam, 3 Ms. S.Sherine.
1,3Electronics and Communication Engineering Department, Karunya Deemed University,
2 Additional Director, Director of Technical Education, Tamil Nadu.
1,3Coimbatore, 2chennai, Tamil Nadu,, India.Abstract
:

Abstract

This paper presents a novel approach to solve the VLSI (Very Large Scale Integration) macro cell placement problems. The approach is based
on a Hybrid Particle swarm Optimization (HPSO) which optimizes both chip area and total wire length without overlaps in VLSI macro cell placement. Results employing MCNC/GSRC benchmarks revealed that the proposed HPSO exhibited rapidly convergence features and led to
more optimal solutions than other approaches.

Keywords: HPSO, Macro cell placement,Overlap removal, Gaussian mutation, Cauchy Mutation.

(Full Paper 459KB)

BibTex:

@ARTICLE{P1120617001,

 AUTHOR = {Ms.D.Jackuline Moni and  Ms.S.Sherine and Dr.S.Arumugam},

TITLE = {HYBRID PARTICLE SWARM OPTIMIZATION FOR VLSI MACRO CELL PLACEMENT },

JOURNAL =  {The International Journal of Artificial Intelligence and Machine Learning},

YEAR = {2006},

VOLUME = {6},

ISSUE ={2},

PAGES={43--49}

}

(Full Paper 459KB)