CUDA-Based Genetic Algorithm on Traveling Salesman Problem

被引：0
|
作者：
Chen, Su [1 ]
Davis, Spencer [1 ]
Jiang, Hai [1 ]
Novobilski, Andy [1 ]
机构：
[1] Arkansas State Univ, Dept Comp Sci, Jonesboro, AR 72467 USA
来源：
COMPUTER AND INFORMATION SCIENCE 2011 | 2011年 / 364卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Genetic algorithm is a widely used tool for generating searching solutions in NP-hard problems. The genetic algorithm on a particular problem should be specifically designed for parallelization and its performance gain might vary according to the parallelism hidden within the algorithm. NVIDIA CPUs that support the CUDA programming paradigm provide many processing units and a shared address space to ease the parallelization process. A heuristic genetic algorithm on the traveling salesman problem is specially designed to run on CPU. Then a corresponding CUDA program is developed for performance comparison. The experimental results indicate that a sequential genetic algorithm with intensive interactions can be accelerated by being translated into CUDA code for CPU execution.
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页码：241 / 252
页数：12
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