The utilization method of idle PC resources
Proceedings of the 3rd International Universal Communication Symposium
Structural and Multidisciplinary Optimization
Inverse kinematics solution for robotic manipulators using a CUDA-Based parallel genetic algorithm
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Search based software engineering: techniques, taxonomy, tutorial
Empirical Software Engineering and Verification
The use of reputation as noise-resistant selection bias in a co-evolutionary multi-agent system
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Using genetic algorithm in reconstructing single individual haplotype with minimum error correction
Journal of Biomedical Informatics
Automated repair of binary and assembly programs for cooperating embedded devices
Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems
Hi-index | 0.00 |
This paper gives a survey about the impact of modern parallel/distributed computing paradigms over Parallel Genetic Algorithms (PGAs). Helping the GA community to feel more comfortable with the evolving parallel paradigms, and marking some areas of research for the High-Performance Computing (HPC) community is the major inspiration behind this survey. In the modern parallel computing paradigms we have considered only two major areas that have evolved very quickly during the past few years, namely, multicore computing and Grid computing. We discuss the challenges involved, and give potential solutions for these challenges. We also propose a hierarchical PGA suitable for Grid environment with multicore computational resources.