| Description |
1 online resource (XII, 453 pages) : 199 illustrations, 95 illustrations in color |
| Series |
Natural Computing Series, 1619-7127 |
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Natural computing series, 1619-7127
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| Contents |
Tutorials. Why GPGPUs for Evolutionary Computation? / Pierre Collet -- Understanding NVIDIA GPGPU Hardware / Ogier Maitre -- Automatic Parallelization of EC on GPGPUs and Clusters of GPGPU Machines with EASEA and EASEA-CLOUD / Pierre Collet, Frédéric Krüger, Ogier Maitre -- Implementations of Various EAs. Generic Local Search (Memetic) Algorithm on a Single GPGPU Chip / Frédéric Krüger [and others] -- arGA: Adaptive Resolution Micro-genetic Algorithm with Tabu Search to Solve MINLP Problems Using GPU / Asim Munawar [and others] -- An Analytical Study of Parallel GA with Independent Runs on GPUs / Shigeyoshi Tsutsui, Noriyuki Fujimoto -- Many-Threaded Differential Evolution on the GPU / Pavel Krömer [and others] -- Scheduling Using Multiple Swarm Particle Optimization with Memetic Features on Graphics Processing Units / Steven Solomon, Parimala Thulasiraman, Ruppa K. Thulasiram -- ACO with Tabu Search on GPUs for Fast Solution of the QAP / Shigeyoshi Tsutsui, Noriyuki Fujimoto -- New Ideas in Parallel Metaheuristics on GPU: Systolic Genetic Search / Martín Pedemonte, Francisco Luna, Enrique Alba -- Genetic Programming on GPGPU Cards Using EASEA / Ogier Maitre -- Cartesian Genetic Programming on the GPU / Simon Harding, Julian F. Miller -- Implementation Techniques for Massively Parallel Multi-objective Optimization / Deepak Sharma, Pierre Collet -- Data Mining Using Parallel Multi-objective Evolutionary Algorithms on Graphics Processing Units / Man Leung Wong, Geng Cui -- Applications. Large-Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units / William B. Langdon -- GPU-Accelerated High-Accuracy Molecular Docking Using Guided Differential Evolution / Martin Simonsen [and others] -- Using Large-Scale Parallel Systems for Complex Crystallographic Problems in Materials Science / Laurent A. Baumes, Frédéric Krüger, Pierre Collet -- Artificial Chemistries on GPU / Lidia Yamamoto, Pierre Collet, Wolfgang Banzhaf -- Acceleration of Genetic Algorithms for Sudoku Solution on Many-Core Processors / Yuji Sato, Naohiro Hasegawa, Mikiko Sato |
| Summary |
Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have been many attempts to develop platforms for running parallel EAs using multicore machines, massively parallel cluster machines, or grid computing environments. Recent advances in general-purpose computing on graphics processing units (GPGPU) have opened up this possibility for parallel EAs, and this is the first book dedicated to this exciting development. The three chapters of Part I are tutorials, representing a comprehensive introduction to the approach, explaining the characteristics of the hardware used, and presenting a representative project to develop a platform for automatic parallelization of evolutionary computing (EC) on GPGPUs. The ten chapters in Part II focus on how to consider key EC approaches in the light of this advanced computational technique, in particular addressing generic local search, tabu search, genetic algorithms, differential evolution, swarm optimization, ant colony optimization, systolic genetic search, genetic programming, and multiobjective optimization. The six chapters in Part III present successful results from real-world problems in data mining, bioinformatics, drug discovery, crystallography, artificial chemistries, and sudoku. Although the parallelism of EAs is suited to the single-instruction multiple-data (SIMD)-based GPU, there are many issues to be resolved in design and implementation, and a key feature of the contributions is the practical engineering advice offered. This book will be of value to researchers, practitioners, and graduate students in the areas of evolutionary computation and scientific computing |
| Notes |
9783642379581 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
| Subject |
Evolutionary computation.
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Parallel processing (Electronic computers)
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Graphics processing units -- Technological innovations
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Computer science.
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Computer network architectures.
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Information theory.
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Artificial intelligence.
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Engineering.
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Computer engineering.
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Computational intelligence.
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Theory of Computation
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Electrical engineering.
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Electronic data processing.
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Computer organization.
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computer science.
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data processing.
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artificial intelligence.
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engineering.
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electrical engineering.
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COMPUTERS -- General.
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Electronic data processing
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Computer organization
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Artificial intelligence
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Computational intelligence
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Computer engineering
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Computer network architectures
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Computer science
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Electrical engineering
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Engineering
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Evolutionary computation
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Information theory
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Parallel processing (Electronic computers)
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| Form |
Electronic book
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| Author |
Collet, Pierre.
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| ISBN |
9783642379598 |
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3642379591 |
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3642379583 |
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9783642379581 |
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