A Highly-Parallel TSP Solver for a GPU Computing Platform

被引:0
|
作者
Fujimoto, Noriyuki [1 ]
Tsutsui, Shigeyoshi [2 ]
机构
[1] Osaka Prefecture Univ, Naka Ku, 1-1 Gakuen Cho, Sakai, Osaka 5998531, Japan
[2] Hannan Univ, Matsubara, Osaka 5808502, Japan
来源
关键词
parallel metaheuristic; genetic algorithm; GPGPU;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The traveling salesman problem (TSP) is probably the most, widely studied combinatorial optimization problem and has become! a standard testbed for new algorithmic ideas. Recently the use of it CPU (Graphics Processing Unit) to accelerate non-graphics computations has attracted much attention due to its high performance and low cost. This paper presents a novel method to solve TSP with a GPC based on the CUDA architecture. The proposed method highly parallelizes a serial metaheuristic algorithm which is a genetic algorithm with the OX (order crossover) operator and the 2-opt local search. The experiments with an NVIDIA CePorce GTX285 GPU and a single core of 3.0 GHz Intel Core2 Duo E6850 CPU show that (air GPU: implementation is about up to 24.2 times faster than the corresponding CPU implementation.
引用
收藏
页码:264 / +
页数:3
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