Integrating loop and data transformations for global optimization

  • Authors:
  • M. F. P. O'Boyle;P. M. W. Knijnenburg

  • Affiliations:
  • Institute for Computing Systems Architecture, Division of Informatics, The University of Edinburgh, Edinburgh EH9 3JZ, United Kingdom;Leiden Institute of Advanced Computer Science, Leiden University, Niels Bohrweg 1, 2333 CA Leiden, The Netherlands

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2002

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Abstract

This paper is concerned with integrating global data transformations and local loop transformations in order to minimize overhead on distributed shared memory machines such as the SGi Origin 2000. By first developing an extended algebraic transformation framework, a new technique to allow the static application of global data transformations, such as partitioning, to reshaped arrays is presented, eliminating the need for expensive temporary copies and hence eliminating any communication and synchronization. In addition, by integrating loop and data transformations, poor spatial locality and expensive array subscripts that may have been introduced can be eliminated. A specific optimization algorithm is derived and applied to well-known benchmarks, where it is shown to give a significant improvement in execution time over existing approaches.