GPU-based parallel implementation of swarm intelligence algorithms / (Record no. 247319)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 05966cam a2200481Ii 4500 |
| 001 - CONTROL NUMBER | |
| control field | ocn946997805 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OCoLC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20190328114815.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
| fixed length control field | m o d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr cnu---unuuu |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 160420s2016 ne ob 001 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | N$T |
| Language of cataloging | eng |
| Description conventions | rda |
| -- | pn |
| Transcribing agency | N$T |
| Modifying agency | YDXCP |
| -- | N$T |
| -- | OCLCF |
| -- | OCLCA |
| -- | UIU |
| -- | OPELS |
| -- | EBLCP |
| -- | IDEBK |
| -- | DEBSZ |
| -- | FEM |
| -- | IDB |
| -- | CNCGM |
| -- | VGM |
| -- | OCLCQ |
| -- | MFS |
| -- | B3G |
| -- | NRC |
| -- | MERUC |
| -- | AU@ |
| -- | OCLCQ |
| -- | LVT |
| -- | TKN |
| -- | STF |
| -- | DEBBG |
| -- | ESU |
| 066 ## - CHARACTER SETS PRESENT | |
| Alternate G0 or G1 character set | (Q |
| 019 ## - | |
| -- | 950462235 |
| -- | 968003164 |
| -- | 969092685 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780128093641 |
| Qualifying information | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 0128093641 |
| Qualifying information | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 9780128093627 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 0128093625 |
| 024 8# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 40026057148 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC)946997805 |
| Canceled/invalid control number | (OCoLC)950462235 |
| -- | (OCoLC)968003164 |
| -- | (OCoLC)969092685 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q337.3 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM |
| Subject category code subdivision | 000000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3/824 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Tan, Ying, |
| Dates associated with a name | 1964- |
| Relator term | author. |
| 245 10 - TITLE STATEMENT | |
| Title | GPU-based parallel implementation of swarm intelligence algorithms / |
| Medium | [electronic resource] |
| Statement of responsibility, etc. | Ying Tan. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Amsterdam : |
| Name of producer, publisher, distributor, manufacturer | Elsevier, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2016. |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | �2016 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Source | rda |
| 588 0# - SOURCE OF DESCRIPTION NOTE | |
| Source of description note | Online resource; title from PDF title page (EBSCO, viewed April 25, 2016). |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Introduction -- GPGPU: general purpose computing on the GPU -- Parallel models -- Performance metrics -- Implementation considerations -- GPU-based particle swarm optimization -- GPU-based fireworks algorithm -- Attract-repulse fireworks algorithm using dynamic parallelism -- Other typical swarm intelligence algorithms based on GPUs -- GPU-based random number generators -- Applications -- A CUDA-based test suit. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | GPU-based Parallel Implementation of Swarm Intelligence Algorithms combines and covers two emerging areas attracting increased attention and applications: graphics processing units (GPUs) for general-purpose computing (GPGPU) and swarm intelligence. This book not only presents GPGPU in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the GPU platform. GPU-based implementations of several typical swarm intelligence algorithms such as PSO, FWA, GA, DE, and ACO are presented and having described the implementation details including parallel models, implementation considerations as well as performance metrics are discussed. Finally, several typical applications of GPU-based swarm intelligence algorithms are presented. This valuable reference book provides a unique perspective not possible by studying either GPGPU or swarm intelligence alone. This book gives a complete and whole picture for interested readers and new comers who will find many implementation algorithms in the book suitable for immediate use in their projects. Additionally, some algorithms can also be used as a starting point for further research. Presents a concise but sufficient introduction to general-purpose GPU computing which can help the layman become familiar with this emerging computing technique Describes implementation details, such as parallel models and performance metrics, so readers can easily utilize the techniques to accelerate their algorithmic programs Appeals to readers from the domain of high performance computing (HPC) who will find the relatively young research domain of swarm intelligence very interesting Includes many real-world applications, which can be of great help in deciding whether or not swarm intelligence algorithms or GPGPU is appropriate for the task at hand. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Swarm intelligence. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS |
| General subdivision | General. |
| Source of heading or term | bisacsh |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Swarm intelligence. |
| Source of heading or term | fast |
| Authority record control number | (OCoLC)fst01139953 |
| 655 #4 - INDEX TERM--GENRE/FORM | |
| Genre/form data or focus term | Electronic books. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Print version: |
| Main entry heading | Tan, Ying. |
| Title | GPU-based Parallel Implementation of Swarm Intelligence Algorithms. |
| Place, publisher, and date of publication | San Francisco : Elsevier Science, �2016 |
| International Standard Book Number | 9780128093627 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | ScienceDirect |
| Uniform Resource Identifier | http://www.sciencedirect.com/science/book/9780128093627 |
| 880 0# - ALTERNATE GRAPHIC REPRESENTATION | |
| Linkage | 505-00 |
| a | Front Cover -- GPU-based Parallel Implementation of Swarm Intelligence Algorithms -- Copyright -- Dedication -- Contents -- Preface -- Acknowledgments -- Acronyms -- Chapter 1: Introduction -- 1.1 Swarm Intelligence Algorithms (SIAs) -- 1.2 Graphics Processing Units (GPUs) -- 1.3 SIAs and GPUs -- 1.4 Some Perspectives -- 1.5 Organization -- Chapter 2: GPGPU: General-Purpose Computing on the GPU -- 2.1 Introduction -- 2.2 GPGPU Development Platforms -- 2.3 Compute Unified Device Architecture (CUDA) -- 2.4 Open Computing Language (OpenCL) -- 2.5 Programming Techniques -- 2.6 Some Discussions -- 2.7 Summary -- Chapter 3: Parallel Models -- 3.1 Previous Work -- 3.2 Basic Guide for Parallel Programming -- 3.3 GPU-Oriented Parallel Models -- 3.4 Naїve Parallel Model -- 3.5 Multi-Kernel Parallel Model -- 3.6 All-GPU Parallel Model -- 3.7 Island Parallel Model -- 3.8 Summary -- Chapter 4: Performance Metrics -- 4.1 Parallel Performance Metrics -- 4.2 Algorithm Performance Metrics -- 4.3 Rectified Efficiency -- 4.4 Case Study -- 4.5 Summary -- Chapter 5: Implementation Considerations -- 5.1 Float-Point -- 5.2 Memory Accesses -- 5.3 Random Number Generation -- 5.4 Branch Divergence -- 5.5 Occupancy -- 5.6 Summary -- Chapter 6: GPU-Based Particle Swarm Optimization -- 6.1 Introduction -- 6.2 Particle Swarm Optimization -- 6.3 GPU-Based PSO for Single-Objective Optimization -- 6.4 GPU-Based PSO for Multiple-Objective Optimization -- 6.5 Remarks -- 6.6 Summary -- Chapter 7: GPU-Based Fireworks Algorithm -- 7.1 Introduction -- 7.2 Fireworks Algorithms (FWA) -- 7.3 GPU-Based Fireworks Algorithm -- 7.4 Summary -- Chapter 8: Attract-Repulse Fireworks Algorithm Using Dynamic Parallelism -- 8.1 Introduction -- 8.2 Attract-Repulse Fireworks Algorithm (AR-FWA) -- 8.3 Implementation -- 8.4 Experiments and Analysis -- 8.5 Summary. |
No items available.