Massively Parallel Evolutionary Computation on GPGPUs (Record no. 98170)

000 -LEADER
fixed length control field 05464nam a22005655i 4500
001 - CONTROL NUMBER
control field 978-3-642-37959-8
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220082910.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642379598
-- 978-3-642-37959-8
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-642-37959-8
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TJ210.2-211.495
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJFM1
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Tsutsui, Shigeyoshi.
Relator term editor.
245 10 - TITLE STATEMENT
Title Massively Parallel Evolutionary Computation on GPGPUs
Medium [electronic resource] /
Statement of responsibility, etc edited by Shigeyoshi Tsutsui, Pierre Collet.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 453 p. 199 illus., 95 illus. in color.
Other physical details online resource.
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-- text
-- txt
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-- computer
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-- rdamedia
338 ## -
-- online resource
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347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement Natural Computing Series,
International Standard Serial Number 1619-7127
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Chap. 1 Why GPGPUs for Evolutionary Computation? -- Chap. 2 Understanding NVIDIA GPGPU Hardware -- Chap. 3 Automatic Parallelization of EC on GPGPUs and Clusters of GPGPU Machines with EASEA and EASEA-CLOUD -- Chap. 4 Generic Local Search (Memetic) Algorithm on a Single GPGPU Chip -- Chap. 5 arGA: Adaptive Resolution Micro-genetic Algorithm with Tabu Search to Solve MINLP Problems Using GPU -- Chap. 6 An Analytical Study of GPU Computation by Parallel GA with Independent Runs -- Chap. 7 Many-Threaded Differential Evolution on the GPU -- Chap. 8 Scheduling Using Multiple Swarm Particle Optimization with Memetic Features on Graphics Processing Units -- Chap. 9 ACO with Tabu Search on GPUs for Fast Solution of the QAP -- Chap. 10 New Ideas in Parallel Metaheuristics on GPU: Systolic Genetic Search -- Chap. 11 Genetic Programming on GPGPU Cards Using EASEA -- Chap. 12 Cartesian Genetic Programming on the GPU -- Chap. 13 Implementation Techniques for Massively Parallel Multi-objective Optimization -- Chap. 14 Data Mining Using Parallel Multi-objective Evolutionary Algorithms on Graphics Processing Units -- Chap. 15 Large-Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units -- Chap. 16 GPU-Accelerated High-Accuracy Molecular Docking Using Guided Differential Evolution -- Chap. 17 Using Large-Scale Parallel Systems for Complex Crystallographic Problems in Materials Science -- Chap. 18 Artificial Chemistries on GPU -- Chap. 19 Acceleration of Genetic Algorithms for Sudoku Solution on Many-Core Processors.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer network architectures.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information theory.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer engineering.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Theory of Computation.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Systems Organization and Communication Networks.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Electrical Engineering.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Collet, Pierre.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642379581
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Natural Computing Series,
-- 1619-7127
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-37959-8
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