Issues in the Design of High Performance SIMD Architectures
IEEE Transactions on Parallel and Distributed Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Combinatorial Optimization Using Electro-Optical Vector by Matrix Multiplication Architecture
OSC '09 Proceedings of the 2nd International Workshop on Optical SuperComputing
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We have been investigating the efficiency of Genetic Algorithms (GA) for solving for a variety of real problems. During our investigations we have concluded that the large amount computational time required to find GA based solutions on conventional computers is restrictive. We are therefore developing an innovative new computer architecture, suitable for the solution of large scale problems using GAs. In this paper we introduce the SIMD-GA (Single Instruction stream Multiple Data stream Genetic Algorithm), and discuss its' hardware design and implementation. By taking advantage of the recent advances is HDLs (Hardware Description Language) and FPGA's (Field Programmable Gate Array) we have been able to quickly develop and prototype a PE (Processing Element) for a SIMD-GA. This approach allows us to build a cost-effective parallel processing architecture to overcome the problem of the computational time required for traditional sequential GA implementation.