Software Automatic Tuning

From Concepts to State-of-the-Art Results

  • Ken Naono
  • Keita Teranishi
  • John Cavazos
  • Reiji Suda

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Reiji Suda, Ken Naono, Keita Teranishi, John Cavazos
      Pages 3-15
  3. Achievements in Scientific Computing

    1. Front Matter
      Pages 17-17
    2. R. Clint Whaley
      Pages 19-32
    3. Daisuke Takahashi
      Pages 49-67
    4. Yusuke Ishikawa, Junichi Tamura, Yutaka Kuwajima, Takaomi Shigehara
      Pages 87-101
    5. Serban Georgescu, Hiroshi Okuda
      Pages 103-119
    6. Ken Naono, Takao Sakurai, Masashi Egi
      Pages 121-133
    7. Sanjukta Bhowmick, Victor Eijkhout, Yoav Freund, Erika Fuentes, David Keyes
      Pages 153-173
    8. Tamito Kajiyama, Akira Nukada, Reiji Suda, Hidehiko Hasegawa, Akira Nishida
      Pages 175-192
    9. Lakshminarasimhan Seshagiri, Meng-Shiou Wu, Masha Sosonkina, Zhao Zhang
      Pages 193-208
    10. Katsuto Sato, Hiroyuki Takizawa, Kazuhiko Komatsu, Hiroaki Kobayashi
      Pages 209-228
    11. Hidehiro Kanemitsu, Gilhyon Lee, Hidenori Nakazato, Takashige Hoshiai, Yoshiyori Urano
      Pages 229-252
  4. Evolution to a General Paradigm

    1. Front Matter
      Pages 253-253
    2. Charles Audet, Cong-Kien Dang, Dominique Orban
      Pages 255-274
    3. Gennady Pekhimenko, Angela Demke Brown
      Pages 335-351
    4. Jaewook Shin, Mary W. Hall, Jacqueline Chame, Chun Chen, Paul D. Hovland
      Pages 353-370
  5. Back Matter
    Pages 371-377

About this book


Software Automatic Tuning: From Concepts to State-of-the-Art Results Ken Naono Keita Teranishi John Cavazos Reiji Suda It is well known that carefully tuned programs run much faster than ones consisting of simply written code, and sometimes the difference of speed is more 100X. To make things more complex, well-tuned code for some machines performs badly on others. "Automatic Performance Tuning" is a technology paradigm that enables software to tune itself to its environments so that it performs well on any computer, even on computers unknown to the programmer. This book summarizes the research efforts to date and state of the art of automatic performance tuning. Software developers and researchers in the area of scientific and technical computing, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm. •Presents the first English collaboration on the powerful, new software paradigm of Automatic Performance Tuning; •Offers a comprehensive survey of fundamental concepts and state-of-the-art results from the field; •Enables programmers to create software that will tune itself to its environments so that it performs well on any computer.


Adaptive algorithms Computing with GPGPU and accelators Multicore Processors Parallel and distributed computing Performance Debugging algorithms automatically-tuned code generation autonomic computing and context-aware computing computer-aided design (CAD) debugging hybrid systems low-power computing performance tuning simulation

Editors and affiliations

  • Ken Naono
    • 1
  • Keita Teranishi
    • 2
  • John Cavazos
    • 3
  • Reiji Suda
    • 4
  1. 1.Central Research LaboratoryHitachi Ltd.Kokubunji-shi, TokyoJapan
  2. 2.Cray, Inc.St PaulUSA
  3. 3.Dept. Computer & Information SciencesUniversity of DelawareNewarkUSA
  4. 4.Dept. Computer ScienceUniversity of TokyoTokyoJapan

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media LLC 2010
  • Publisher Name Springer, New York, NY
  • eBook Packages Engineering
  • Print ISBN 978-1-4419-6934-7
  • Online ISBN 978-1-4419-6935-4
  • Buy this book on publisher's site