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A GPGPU Framework for High Performance Evolutionary Computation

A GPGPU Framework for High Performance Evolutionary Computation
用于高性能进化计算的 GPGPU 框架
批准号:
23500285
负责人:
FUJIMOTO Noriyuki
金额:
$3.33万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
2011
资助国家:
日本
项目状态:
已结题
起止时间:
2011 至 2013

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中文摘要
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英文摘要
A combinatorial optimization problem is a problem to find the best one of various choices. One of promising methods to solve combinatorial optimization problems is evolutionary computation, which was inspired by biological evolution. In this study, how GPUs can accelerate evolutionary computation has been studied. A GPU is a electronic part equipped with common PCs. Consequently, a maximum of 101 times speedup was achieved for problems such as the quadratic assignment problem, the traveling salesman problem, and so on.
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会议论文
Parallel Fuzzy Rule Generation Using GPGPU
使用 GPGPU 并行模糊规则生成
DOI: --
发表时间: 2011
期刊: Artificial Life and Robotics
影响因子: 0.9
作者: [Takesuke Uenishi, Tomoharu Nakasima, Noriyuki Fujimoto]
通讯作者: Noriyuki Fujimoto
DOI: --
发表时间: 2012-07
期刊:
影响因子: --
作者: [H. Fujii;N. Fujimoto]
通讯作者: H. Fujii;N. Fujimoto
On the Effect of Using Multiple GPUs in Solving QAPs with CUDA
关于使用多个 GPU 通过 CUDA 解决 QAP 的效果
DOI: --
发表时间: 2012
期刊: Genetic and Evolutionary Computation Conference (GECCO)
影响因子: --
作者: [Shigeyoshi Tsutsui, Noriyuki Fujimoto]
通讯作者: Noriyuki Fujimoto
Parallelizing a Genetic Operator for GPUs
GPU 并行化遗传算子
DOI: --
发表时间: 2013
期刊: IEEE Congress on Evolutionary Computation
影响因子: --
作者: [Noriyuki Fujimoto, Shigeyoshi Tsutsui]
通讯作者: Shigeyoshi Tsutsui
15
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