GPU-based Parallel Implementation of Swarm Intelligence Algo

Erscheinungsjahr 2016
ISBN: 978-0-12-809362-7
Verlag: Morgan Kaufmann

Buch, Englisch, 256 Seiten, Format (B × H): 189 mm x 233 mm, Gewicht: 550 g

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.

Zielgruppe

Researchers, engineers, graduates and senior undergraduates with interests in parallel implementation of novel swarm intelligence algorithms like particle swarm optimization, fireworks algorithms, genetic algorithms, and their applications.

Autoren/Hrsg.

Tan, Ying

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Technische Informatik Grid-Computing & Paralleles Rechnen

Inhaltsverzeichnis

Preface1 Introduction2 GPGPU: General Purpose Computing on the GPU3 Parallel Models4 Performance Measurements5 Implementation Considerations6 GPU-based Particle Swarm Optimization7 GPU-based Fireworks Algorithm8 Attract-Repulse Fireworks Algorithm Using Dynamic Parallelism9 Other Typical Swarm Intelligence Algorithms based on GPUs 10 GPU-based Random Number Generators11 Applications12 A CUDA-Based Test SuitAppendices

Über Autor(innen)

Tan, Ying
Ying Tan is a professor and PhD advisor at the School of Electronics Engineering and Computer Science of Peking University, and director of Computational Intelligence Laboratory at Peking University (PKU). He received his BEng from the EEI, MSc from Xidian Univ., and PhD from Southeast Univ., in 1985, 1988, and 1997, respectively. From 1997, he was a postdoctoral fellow then an associate professor at University of Science and Technology of China (USTC), then served as director of Institute of Intelligent Information Science and a full professor since 2000. He worked with the Chinese University of Hong Kong (CUHK) in 1999 and 2004-2005. He was elected for the 100 talent program of the Chinese Academy of Science (CAS) in 2005