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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Munawar, A. Wahib, M. Munetomo, M. Akama, K. |
| Copyright Year | 2011 |
| Description | Author affiliation: Graduate School of Information, Science and Technology, Hokkaido University, Sapporo, Japan (Munawar, A.; Wahib, M.) || Information Systems Design Laboratory, Information Initiative Center, Hokkaido University, Sapporo, Japan (Munetomo, M.; Akama, K.) |
| Abstract | In this paper we propose a many-core implementation of evolutionary computation for GPGPU (General-Purpose Graphic Processing Unit) to solve non-convex Mixed Integer Non-Linear Programming (MINLP) and non-convex Non Linear Programming (NLP) problems using a stochastic algorithm. Stochastic algorithms being random in their behavior are difficult to implement over GPU like architectures. In this paper we not only succeed in implementation of a stochastic algorithm over GPU but show considerable speedups over CPU implementations. The stochastic algorithm considered for this paper is an adaptive resolution approach to genetic algorithm (arGA), developed by the authors of this paper. The technique uses the entropy measure of each variable to adjust the intensity of the genetic search around promising individuals. Performance is further improved by hybridization with adaptive resolution local search (arLS) operator. In this paper, we describe the challenges and design choices involved in parallelization of this algorithm to solve complex MINLPs over a commodity GPU using Compute Unified Device Architecture (CUDA) programming model. Results section shows several numerical tests and performance measurements obtained by running the algorithm over an nVidia Fermi GPU. We show that for difficult problems we can obtain a speedup of up to 20× with double precision and up to 42× with single precision. |
| Starting Page | 318 |
| Ending Page | 325 |
| File Size | 1721564 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424478347 |
| e-ISBN | 9781424478354 |
| DOI | 10.1109/CEC.2011.5949635 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Graphics processing unit Genetic algorithms Kernel Stochastic processes Entropy Algorithm design and analysis Genetics Compute Unified Device Architecture (CUDA) Adaptive Resolution Genetic Algorithm Parallel Genetic Algorithms General-Purpose computation on Graphics Processing Units (GPGPU) |
| Content Type | Text |
| Resource Type | Article |
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