Fast parallel memetic algorithm for vector quantization based for reconfigurable hardware and softcore processor

Authors:
Tsung-Yi Yu;Wen-Jyi Hwang;Tsung-Che Chiang
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei, Taiwan
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2010

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Abstract

A novel parallel memetic algorithm (MA) architecture for the design of vector quantizers is presented in this paper The architecture contains a number of modules operating memetic optimization concurrently Each module uses steady-state genetic algorithm (GA) for global search, and K-means algorithm for local refinement A shift register based circuit for accelerating mutation and crossover operations for steady state GA operations is adopted in the design A pipeline architecture for the hardware implementation of K-means algorithm is also used The proposed architecture is embedded in a softcore CPU, and implemented on a field programmable logic array (FPGA) device for physical performance measurement.