Abstract
This contribution describes the implementation of a fine-grained parallel genetic algorithm ‘MPGA’ on the MasPar MP-1, a massively parallel mesh connected array processor with global router and 1024 (up to 16384) 4-bit processing elements. The implementation uses object oriented methods to provide a large set of standard strategies which can be adapted for a given application. Report modules support the investigation of the performance of the GA. The Implementation shows a good performance compared to other implementations on parallel hardware.
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© 1993 Springer-Verlag/Wien
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Schwehm, M. (1993). A Massively Parallel Genetic Algorithm on the MasPar MP-1. In: Albrecht, R.F., Reeves, C.R., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7533-0_73
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DOI: https://doi.org/10.1007/978-3-7091-7533-0_73
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82459-7
Online ISBN: 978-3-7091-7533-0
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