Parallelization of genetic operations that takes building-block linkage into account

Authors:
Yuji Sato;Hazuki Inoue;Mikiko Sato
Affiliations:
Graduate School of Computer and Information Sciences, Hosei University, Koganei, Japan 184-8584;Graduate School of Computer and Information Sciences, Hosei University, Koganei, Japan 184-8584;The Graduate School of Engineering, Tokyo University of Agriculture and Technology, Koganei, Japan 184-8588
Venue:
Artificial Life and Robotics
Year:
2012

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Abstract

We propose a performance enhancement using parallelization of genetic operations that takes highly fit schemata (building-block) linkages into account. Previously, we used the problem of solving Sudoku puzzles to demonstrate the possibility of shortening processing times through the use of many-core processors for genetic computations. To increase accuracy, we proposed a genetic operation that takes building-block linkages into account. Here, in an evaluation using very difficult problems, we show that the proposed genetic operations are suited to fine-grained parallelization; processing performance increased by approximately 30 % (four times) with fine-grained parallel processing of the proposed mutation and crossover methods on Intel Core i5 (NVIDIA GTX5800) compared with non-parallel processing on a CPU. Increasing GPU resources will diminish the conflicts with thread usage in coarse-grained parallelization of individuals and will enable faster processing.