Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers (2nd Edition)
Principles of Parallel Programming
Principles of Parallel Programming
GPU computation in bioinspired algorithms: a review
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
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Genetic Algorithm (GA) is a powerful tool for science computing, while Parallel Genetic Algorithm (PGA) further promotes the performance of computing. However, the traditional parallel computing environment is very difficult to set up, much less the price. This gives rise to the appearance of moving dense computing to graphics hardware, which is inexpensive and more powerful. The paper presents a hierarchical parallel genetic algorithm, implemented by NVIDIA's Compute Unified Device Architecture (CUDA). Mixed with master-slave parallelization method and multiple-demes parallelization method, this algorithm has contributed to better utilization of threads and high-speed shared memory in CUDA.