Table of contents

  1. Front Matter
    Pages i-vii
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Xuan Shi, Volodymyr Kindratenko, Chaowei Yang
      Pages 3-6
  3. Overview of Modern Accelerator Technologies (MAT) for Scientific Computation

    1. Front Matter
      Pages 7-7
    2. Richard Vuduc, Jee Choi
      Pages 9-23
    3. Jim Jeffers
      Pages 25-39
    4. Qunying Huang, Zhenlong Li, Jizhe Xia, Yunfeng Jiang, Chen Xu, Kai Liu et al.
      Pages 41-51
  4. MAT in GIScience Applications

  5. MAT in Remotely Sensed Data Processing and Analysis

    1. Front Matter
      Pages 131-131
    2. Bin Zhou, Chun-mao Yeh, Wen-wen Li, Wei-jie Zhang
      Pages 133-143
    3. Miaoqing Huang, Liang Men, Chenggang Lai
      Pages 157-166
  6. Multi-core Technology for Geospatial Services

    1. Front Matter
      Pages 167-167
    2. Huayi Wu, Xuefeng Guan, Tianming Liu, Lan You, Zhenqiang Li
      Pages 183-195

About this book

Introduction

This book explores the impact of augmenting novel architectural designs with hardware‐based application accelerators. The text covers comprehensive aspects of the applications in Geographic Information Science, remote sensing and deploying Modern Accelerator Technologies (MAT) for geospatial simulations and spatiotemporal analytics. MAT in GIS applications, MAT in remotely sensed data processing and analysis, heterogeneous processors, many-core and highly multi-threaded processors and general purpose processors are also presented. This book includes case studies and closes with a chapter on future trends. Modern Accelerator Technologies for GIS is a reference book for practitioners and researchers working in geographical information systems and related fields. Advanced-level students in geography, computational science, computer science and engineering will also find this book useful.

Keywords

Application Accelerators Emerging Computer Systems General Purpose Graphics Processing Units (GPGPUs) Geospatial Cyberinfrastructure Heterogeneous Computer Architecture MAT for Geospatial Modeling MAT in GIS Applications MAT in Remote Sensing Performance Optimization Spatiotemporal Data Analytics

Editors and affiliations

  • Xuan Shi
    • 1
  • Volodymyr Kindratenko
    • 2
  • Chaowei Yang
    • 3
  1. 1.Department of GeosciencesUniversity of ArkansasFayettevilleUSA
  2. 2.Department of Electrical and Computer EngineeringUniversity of IllinoisUrbanaUSA
  3. 3.Department of Geography and GeoInformation SciencesGeorge Mason UniversityFairfaxUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-8745-6
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-1-4614-8744-9
  • Online ISBN 978-1-4614-8745-6
  • About this book