High Performance Computing for Big Data: Methodologies and Applications (Chapman & Hall/CRC Big Data Series)
暫譯: 大數據的高效能計算:方法論與應用(Chapman & Hall/CRC 大數據系列)

  • 出版商: Chapman and Hall/CRC
  • 出版日期: 2017-10-10
  • 售價: $4,910
  • 貴賓價: 9.5$4,665
  • 語言: 英文
  • 頁數: 286
  • 裝訂: Hardcover
  • ISBN: 1498783996
  • ISBN-13: 9781498783996
  • 相關分類: 大數據 Big-data
  • 海外代購書籍(需單獨結帳)

商品描述

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering.

The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering.

Features

  • Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark
  • Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs
  • Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles
  • Describes advanced algorithms for different big data application domains
  • Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies

Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications.

About the Editor

Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.

 

商品描述(中文翻譯)

《高效能運算與大數據:方法論與應用》探討了針對數據密集型應用的新興高效能架構、新穎的高效分析策略以提升數據處理能力,以及在機器學習、生命科學、神經網絡和神經形態工程等多個領域的尖端應用。

本書分為兩個主要部分。第一部分涵蓋了大數據架構,包括雲計算系統和異構加速器。它還介紹了針對記憶體架構和設備的新興3D IC設計原則。第二部分則展示了大數據在多個領域的實用應用,包括生物信息學、深度學習和神經形態工程。

特點
- 涵蓋廣泛的大數據架構,包括像Hadoop/Spark這樣的分散式系統
- 包括基於加速器的大數據應用方法,如基於GPU的加速技術,以及FPGA/CGRA/ASIC等硬體加速
- 介紹新興的記憶體架構和設備,如NVM、STT-RAM、3D IC設計原則
- 描述不同大數據應用領域的先進算法
- 說明針對大數據應用的新穎分析技術、排程、映射和分區方法

本書匯集了領先專家的貢獻,呈現了高效能運算在大數據應用中的方法論與應用的最前沿研究。

編輯介紹
王超博士是中國科學技術大學計算機科學學院的副教授。他是《ACM電子系統設計自動化期刊》(TODAES)、《應用軟體計算》、《微處理器與微系統》、《IET計算機與數位技術》及《國際電子期刊》的副編輯。王超博士曾獲得中國科學院青年創新促進會獎、ACM中國新星榮譽提名(2016年)及DATE 2015最佳IP提名。他目前是中國計算機學會計算機架構技術委員會成員、形式方法工作組成員,並且是IEEE資深會員、中國計算機學會資深會員及ACM資深會員。