Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
A bridging model for parallel computation
Communications of the ACM
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Outlier analysis for gene expression data
Journal of Computer Science and Technology - Special issue on bioinformatics
A massively parallel architecture for distributed genetic algorithms
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
Markov chain models of parallel genetic algorithms
IEEE Transactions on Evolutionary Computation
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Genetic algorithms (GAs) is a kind of powerful method for solving complex problems. Generally, parallel computing is used together with GAs to achieve better execution time and there exist several models for Parallel Genetic Algorithms (PGAs), such as master-salve model and island model. Currently, PC cluster is the common architecture for parallel computing with high performance-price-ratio. In this paper, we choose island model for implement PGA on PC cluster and present a novel framework for PGAs (FPGA-Cluster) using updated island model on PC cluster. A GA program can be translated to a PGA program on PC cluster by FPGA-Cluster easily and efficiently, and an application for FPGA-Cluster is also demonstrated.