GPU-based Parallel Implementation of Swarm Intelligence Algorithms

Ying Tan

  • 出版商: Morgan Kaufmann
  • 出版日期: 2016-04-05
  • 售價: $3,260
  • 貴賓價: 9.5$3,097
  • 語言: 英文
  • 頁數: 256
  • 裝訂: Paperback
  • ISBN: 0128093625
  • ISBN-13: 9780128093627
  • 相關分類: GPUAlgorithms-data-structures
  • 立即出貨 (庫存=1)

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商品描述

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

商品描述(中文翻譯)

《基於GPU的並行群體智能演算法實作》結合並涵蓋了兩個引起越來越多關注和應用的新興領域:通用圖形處理器(GPU)用於通用計算(GPGPU)和群體智能。本書不僅詳細介紹了GPGPU,還提供了在GPU平台上適當實作群體智能演算法的指導。

本書介紹了幾種典型的基於GPU的群體智能演算法,如粒子群優化(PSO)、火焰蟻演算法(FWA)、遺傳演算法(GA)、差分進化(DE)和螞蟻演算法(ACO),並描述了實作細節,包括並行模型、實作考慮因素以及性能指標。最後,還介紹了幾個基於GPU的群體智能演算法的典型應用。這本寶貴的參考書提供了一個獨特的視角,單獨研究GPGPU或群體智能無法達到。

本書為感興趣的讀者和新手提供了一個完整的圖景,其中包含許多適合立即應用於他們項目中的實作演算法。此外,一些演算法還可以作為進一步研究的起點。

本書具有以下特點:
- 提供了簡潔但足夠的通用GPU計算介紹,有助於非專業人士熟悉這種新興計算技術。
- 描述了實作細節,如並行模型和性能指標,讓讀者能夠輕鬆利用這些技術加速他們的演算法程序。
- 吸引了高性能計算(HPC)領域的讀者,他們會對相對年輕的群體智能研究領域非常感興趣。
- 包含許多實際應用,對於決定群體智能演算法或GPGPU是否適合當前任務非常有幫助。