Information Sciences: an International Journal
A novel parallel clustering algorithm based on artificial immune network using nVidia CUDA framework
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: design and development approaches - Volume Part I
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
Expert Systems with Applications: An International Journal
Solving very large instances of the scheduling of independent tasks problem on the GPU
Journal of Parallel and Distributed Computing
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Fine-grained parallel immune algorithm (FGIA), though a popular and robust strategy for solving complicated optimization problems, is sometimes inconvenient to use as its population size is restricted by heavy data communication and the parallel computers are relatively difficult to use, manage, maintain and may not be accessible to most researchers. In this paper, we propose a FGIA method based on GPUacceleration, which maps parallel IA algorithm to GPU through the CUDA. We implement the IA on the base of the framework of genetic algorithm (GA), the analytical results demonstrate that the proposed method increases the population size, speeds up its execution and provides ordinary users with a feasible FGIA solution.