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The Resource Massively Parallel Evolutionary Computation on GPGPUs, (electronic resource)

Massively Parallel Evolutionary Computation on GPGPUs, (electronic resource)

Label
Massively Parallel Evolutionary Computation on GPGPUs
Title
Massively Parallel Evolutionary Computation on GPGPUs
Creator
Contributor
Subject
Language
eng
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
Member of
http://library.link/vocab/creatorName
Tsutsui, Shigeyoshi
Dewey number
006.3
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Collet, Pierre
Series statement
Natural Computing Series,
http://library.link/vocab/subjectName
  • Computer science
  • Computer network architectures
  • Information theory
  • Artificial intelligence
  • Engineering
  • Computer engineering
  • Artificial Intelligence (incl. Robotics)
  • Computational intelligence
  • Theory of Computation
  • Computer Systems Organization and Communication Networks
  • Electrical engineering
Label
Massively Parallel Evolutionary Computation on GPGPUs, (electronic resource)
Instantiates
Publication
Note
9783642379581
Contents
  • Generic Local Search (Memetic) Algorithm on a Single GPGPU Chip
  • Frédéric Krüger ... [et al.]
  • arGA: Adaptive Resolution Micro-genetic Algorithm with Tabu Search to Solve MINLP Problems Using GPU
  • Asim Munawar ... [et al.]
  • An Analytical Study of Parallel GA with Independent Runs on GPUs
  • Shigeyoshi Tsutsui, Noriyuki Fujimoto
  • Many-Threaded Differential Evolution on the GPU
  • Pavel Krömer ... [et al.]
  • Scheduling Using Multiple Swarm Particle Optimization with Memetic Features on Graphics Processing Units
  • Steven Solomon, Parimala Thulasiraman, Ruppa K. Thulasiram
  • Tutorials.
  • 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
  • Why GPGPUs for Evolutionary Computation?
  • 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 ... [et al.]
  • Using Large-Scale Parallel Systems for Complex Crystallographic Problems in Materials Science
  • Laurent A. Baumes, Frédéric Krüger, Pierre Collet
  • Artificial Chemistries on GPU
  • Pierre Collet
  • Lidia Yamamoto, Pierre Collet, Wolfgang Banzhaf
  • Acceleration of Genetic Algorithms for Sudoku Solution on Many-Core Processors
  • Yuji Sato, Naohiro Hasegawa, Mikiko Sato
  • 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.
Control code
ocn868638847
Extent
1 online resource (XII, 453 pages 199 illustrations, 95 illustrations in color.)
Form of item
online
Isbn
9783642379598
Isbn Type
(electronic bk.)
Other control number
10.1007/978-3-642-37959-8
Other physical details
online resource
Specific material designation
remote
System control number
(OCoLC)868638847
Label
Massively Parallel Evolutionary Computation on GPGPUs, (electronic resource)
Publication
Note
9783642379581
Contents
  • Generic Local Search (Memetic) Algorithm on a Single GPGPU Chip
  • Frédéric Krüger ... [et al.]
  • arGA: Adaptive Resolution Micro-genetic Algorithm with Tabu Search to Solve MINLP Problems Using GPU
  • Asim Munawar ... [et al.]
  • An Analytical Study of Parallel GA with Independent Runs on GPUs
  • Shigeyoshi Tsutsui, Noriyuki Fujimoto
  • Many-Threaded Differential Evolution on the GPU
  • Pavel Krömer ... [et al.]
  • Scheduling Using Multiple Swarm Particle Optimization with Memetic Features on Graphics Processing Units
  • Steven Solomon, Parimala Thulasiraman, Ruppa K. Thulasiram
  • Tutorials.
  • 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
  • Why GPGPUs for Evolutionary Computation?
  • 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 ... [et al.]
  • Using Large-Scale Parallel Systems for Complex Crystallographic Problems in Materials Science
  • Laurent A. Baumes, Frédéric Krüger, Pierre Collet
  • Artificial Chemistries on GPU
  • Pierre Collet
  • Lidia Yamamoto, Pierre Collet, Wolfgang Banzhaf
  • Acceleration of Genetic Algorithms for Sudoku Solution on Many-Core Processors
  • Yuji Sato, Naohiro Hasegawa, Mikiko Sato
  • 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.
Control code
ocn868638847
Extent
1 online resource (XII, 453 pages 199 illustrations, 95 illustrations in color.)
Form of item
online
Isbn
9783642379598
Isbn Type
(electronic bk.)
Other control number
10.1007/978-3-642-37959-8
Other physical details
online resource
Specific material designation
remote
System control number
(OCoLC)868638847

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