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Software Automatic Tuning

From Concepts to State-of-the-Art Results

  • Book
  • © 2010

Overview

Editors:
  1. Ken Naono

    1. Central Research Laboratory, Hitachi Ltd., Kokubunji-shi, Tokyo, Japan

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  2. Keita Teranishi

    1. Cray, Inc., St Paul, USA

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  3. John Cavazos

    1. Dept. Computer & Information Sciences, University of Delaware, Newark, USA

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  4. Reiji Suda

    1. Dept. Computer Science, University of Tokyo, Tokyo, Japan

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  • 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 environment(s) so that it performs well on any computer
  • Includes supplementary material: sn.pub/extras

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Table of contents (20 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    1. Front Matter

      Pages 1-1
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    2. Software Automatic Tuning: Concepts and State-of-the-Art Results

      • Reiji Suda, Ken Naono, Keita Teranishi, John Cavazos
      Pages 3-15

  3. Achievements in Scientific Computing

    1. Front Matter

      Pages 17-17
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    2. ATLAS Version 3.9: Overview and Status

      • R. Clint Whaley
      Pages 19-32

    3. Autotuning Method for Deciding Block Size Parameters in Dynamically Load-Balanced BLAS

      • Yuta Sawa, Reiji Suda
      Pages 33-48

    4. Automatic Tuning for Parallel FFTs

      • Daisuke Takahashi
      Pages 49-67

    5. Dynamic Programming Approaches to Optimizing the Blocking Strategy for Basic Matrix Decompositions

      • Yusaku Yamamoto, Takeshi Fukaya
      Pages 69-85

    6. Automatic Tuning of the Division Number in the Multiple Division Divide-and-Conquer for Real Symmetric Eigenproblem

      • Yusuke Ishikawa, Junichi Tamura, Yutaka Kuwajima, Takaomi Shigehara
      Pages 87-101

    7. Automatically Tuned Mixed-Precision Conjugate Gradient Solver

      • Serban Georgescu, Hiroshi Okuda
      Pages 103-119

    8. Automatically Tuned Sparse Eigensolvers

      • Ken Naono, Takao Sakurai, Masashi Egi
      Pages 121-133

    9. Systematic Performance Evaluation of Linear Solvers Using Quality Control Techniques

      • Shoji Itoh, Masaaki Sugihara
      Pages 135-152

    10. Application of Alternating Decision Trees in Selecting Sparse Linear Solvers

      • Sanjukta Bhowmick, Victor Eijkhout, Yoav Freund, Erika Fuentes, David Keyes
      Pages 153-173

    11. Toward Automatic Performance Tuning for Numerical Simulations in the SILC Matrix Computation Framework

      • Tamito Kajiyama, Akira Nukada, Reiji Suda, Hidehiko Hasegawa, Akira Nishida
      Pages 175-192

    12. Exploring Tuning Strategies for Quantum Chemistry Computations

      • Lakshminarasimhan Seshagiri, Meng-Shiou Wu, Masha Sosonkina, Zhao Zhang
      Pages 193-208

    13. Automatic Tuning of CUDA Execution Parameters for Stencil Processing

      • Katsuto Sato, Hiroyuki Takizawa, Kazuhiko Komatsu, Hiroaki Kobayashi
      Pages 209-228

    14. Static Task Cluster Size Determination in Homogeneous Distributed Systems

      • 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
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    2. Algorithmic Parameter Optimization of the DFO Method with the OPAL Framework

      • Charles Audet, Cong-Kien Dang, Dominique Orban
      Pages 255-274

    3. A Bayesian Method of Online Automatic Tuning

      • Reiji Suda
      Pages 275-293
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Keywords

About this book

Automatic Performance Tuning is a new software paradigm which enables software to be high performance in any computing environment. Its methodologies have been developed over the past decade, and it is now rapidly growing in terms of its scope and applicability, as well as in its scientific knowledge and technological methods. Software developers and researchers in the area of scientific and technical computing, high performance database systems, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm.

Editors and Affiliations

  • Central Research Laboratory, Hitachi Ltd., Kokubunji-shi, Tokyo, Japan

    Ken Naono

  • Cray, Inc., St Paul, USA

    Keita Teranishi

  • Dept. Computer & Information Sciences, University of Delaware, Newark, USA

    John Cavazos

  • Dept. Computer Science, University of Tokyo, Tokyo, Japan

    Reiji Suda

Bibliographic Information

  • Book Title: Software Automatic Tuning

  • Book Subtitle: From Concepts to State-of-the-Art Results

  • Editors: Ken Naono, Keita Teranishi, John Cavazos, Reiji Suda

  • DOI: https://doi.org/10.1007/978-1-4419-6935-4

  • Publisher: Springer New York, NY

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Science+Business Media LLC 2010

  • Hardcover ISBN: 978-1-4419-6934-7

  • Softcover ISBN: 978-1-4899-9884-2

  • eBook ISBN: 978-1-4419-6935-4

  • Edition Number: 1

  • Number of Pages: XIV, 377

  • Topics: Circuits and Systems, Computer-Aided Engineering (CAD, CAE) and Design

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