Integrating Loop and Data Transformations for Global Optimization

Michael F. P. O'Boyle, Peter M. W. Knijnenburg

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)563-590
Number of pages28
JournalJournal of Parallel and Distributed Computing
Volume62
Issue number4
DOIs
Publication statusPublished - Apr 2002

Fingerprint

Dive into the research topics of 'Integrating Loop and Data Transformations for Global Optimization'. Together they form a unique fingerprint.

Cite this