Stochastic simulation
Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Random number generators: good ones are hard to find
Communications of the ACM
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Programming with POSIX threads
Programming with POSIX threads
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
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Initial Approaches to the Application of Islands-Based Parallel EDAs in Continuous Domains
ICPPW '05 Proceedings of the 2005 International Conference on Parallel Processing Workshops
Introduction to the cell multiprocessor
IBM Journal of Research and Development - POWER5 and packaging
Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence)
The equation for response to selection and its use for prediction
Evolutionary Computation
Evaluating the cell broadband engine as a platform to run estimation of distribution algorithms
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Parallel Implementation of EDAs Based on Probabilistic Graphical Models
IEEE Transactions on Evolutionary Computation
Estimation of distribution algorithms: from available implementations to potential developments
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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Current consumer-grade computers and game devices incorporate very powerful processors that can be used to accelerate many classes of scientific codes. In this paper we explore the ability of the Cell Broadband Engine to run two similar Estimation of Distribution Algorithms, one for the discrete domain and the other for the continuous domain. Starting from initial, sequential versions, we develop multi-threaded programs for symmetric multiprocessors that are afterwards reworked to run on a Cell-based system. In most cases, the parallel programs significantly accelerate execution times, compared with the sequential counterparts. Additional acceleration is achieved using vector (instead of scalar) operations, which are supported by all the tested platforms. We describe the process of parallelizing and porting the programs, and analyze the results obtained taking into account the EDAs under study, the problems solved with them, and the platform in which programs run. We conclude that EDAs are not right targets to be ported to the Cell Broadband Engine.