Parallel Genetic Algorithms with Dynamic Topology using Cluster Computing

Efficient Hierarchical Parallel Genetic Algorithms using Grid computing

In this paper, we present an efficient Hierarchical Parallel Genetic Algorithm framework using Grid computing (GE-HPGA). The framework is developed using standard Grid technologies and has two distinctive features, 1) an extended GridRPC API to conceal the high complexity of Grid environment, and 2) a metascheduler for seamless resource discovery and selection. To assess the practicality of the...

Planar character animation using genetic algorithms and GPU parallel computing

Dynamic Task Scheduling Using Parallel Genetic Algorithms For Heterogeneous Distributed Computing

A parallel genetic algorithm has been developed to dynamically schedule heterogeneous tasks to heterogeneous processors in a distributed environment. The scheduling problem is known to be NP complete. Genetic algorithms, a meta-heuristic search technique, have been used successfully in this field. The proposed algorithm uses multiple processors with centralized control for scheduling. Tasks are...

Heterogeneous Computing and Parallel Genetic Algorithms

This paper analyzes some technical and practical issues concerning the heterogeneous execution of parallel genetic algorithms (PGAs). In order to cope with a plethora of different operating systems, security restrictions, and other problems associated to multi-platform execution, we use Java to implement a distributed PGA model. The distributed PGA runs at the same time on different machines li...

Generating Parallel Algorithms for Cluster and Grid Computing

We revisit and use the dependence transformation method to generate parallel algorithms suitable for cluster and grid computing. We illustrate this method in two applications: to obtain a systolic matrix product algorithm, and to compute the alignment score of two strings. The product of two n × n matrices is viewed as multiplying two p × p matrices whose elements are n/p × n/p submatrices. For...