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Emerging Technology and Architecture for Big-data Analytics

  • Anupam Chattopadhyay
  • Chip Hong Chang
  • Hao Yu

Table of contents

  1. Front Matter
    Pages i-xi
  2. State-of-the-Art Architectures and Automation for Data-Analytics

    1. Front Matter
      Pages 1-1
    2. Karthik Ganesan, Yao-Min Chen, Xiaochen Pan
      Pages 3-24
    3. Guanwen Zhong, Alok Prakash, Tulika Mitra
      Pages 25-49
    4. Robert Karam, Somnath Paul, Swarup Bhunia
      Pages 77-101
    5. Wei Zuo, Swathi Gurumani, Kyle Rupnow, Deming Chen
      Pages 103-134
  3. Approaches and Applications for Data Analytics

    1. Front Matter
      Pages 135-135
    2. Gavin Xiaoxu Yao, Marc Stöttinger, Ray C. C. Cheung, Sorin A. Huss
      Pages 137-158
    3. Xin Li, Ronald D. (Shawn) Blanton, Pulkit Grover, Donald E. Thomas
      Pages 159-173
  4. Emerging Technology, Circuits and Systems for Data-Analytics

    1. Front Matter
      Pages 215-215
    2. Zheng Li, Chenchen Liu, Hai Li, Yiran Chen
      Pages 217-244
    3. Yu Wang, Tianqi Tang, Boxun Li, Lixue Xia, Huazhong Yang
      Pages 245-259
    4. Abhronil Sengupta, Aayush Ankit, Kaushik Roy
      Pages 261-274
    5. Debjyoti Bhattacharjee, Anupam Chattopadhyay
      Pages 275-291
    6. Arindam Basu, Chen Yi, Yao Enyi
      Pages 293-311
    7. Arpita Maitra, Subhamoy Maitra, Asim K. Pal
      Pages 313-330

About this book

Introduction

This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities.

  • Provides a single-source reference to hardware architectures for big-data analytics;
  • Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems;
  • Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.

Keywords

Big Data Analytics Real-Time Big Data Analytics next-generation data analytics exascale computing non-volatile memory based hardware

Editors and affiliations

  • Anupam Chattopadhyay
    • 1
  • Chip Hong Chang
    • 2
  • Hao Yu
    • 3
  1. 1.School of Computer Science and Engineering, School of Physical and Mathematical SciencesNanyang Technological UniversitySingaporeSingapore
  2. 2.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  3. 3.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-54840-1
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-54839-5
  • Online ISBN 978-3-319-54840-1
  • Buy this book on publisher's site
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