A GPGPU Framework for High Performance Evolutionary Computation
| Project/Area Number |
23500285
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Osaka Prefecture University |
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Principal Investigator |
FUJIMOTO Noriyuki 大阪府立大学, 理学(系)研究科(研究院), 教授 (90294165)
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| Co-Investigator(Renkei-kenkyūsha) |
TSUTSUI Shigeyoshi 阪南大学, 経営情報学部, 教授 (90188590)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2013: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2011: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | アルゴリズム / 超高速情報処理 / ソフトコンピューティング / 並列処理 / GPGPU / 進化計算 |
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| Research Abstract |
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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Report
(4 results)
Research Products
(52 results)
