Automatic data layout with read-only replication and memory constraints

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


The memory requirement characteristics of a data layout are particularly important for applications that are executed on a parallel machine mainly because of the amount of main memory that the machine provides, rather than its computation power. It may not be feasible to execute such a memory intensive program on a conventional uniprocessor due to the lack of the necessary memory resources. Data layouts that specify arrays with multiple read-only copies — each copy with a different data mapping — can significantly reduce the overall execution time of a program since otherwise necessary communication is avoided. However, read-only replication increases a program’s memory requirements and therefore should only be applied selectively, in particular for memory intensive applications. This short paper discusses an extension to our previous framework for automatic data layout that considers read-only data replication and minimizes the overall execution time under given memory constraints.

Original languageEnglish (US)
Title of host publicationLanguages and Compilers for Parallel Computing - 10th International Workshop, LCPC 1997, Proceedings
EditorsPen-Chung Yew, Chua-Huang Huang, P. Sadayappan, Zhiyuan Li, Siddharta Chatterjee, David Sehr
PublisherSpringer Verlag
Number of pages4
ISBN (Print)3540644725, 9783540644729
StatePublished - 1998
Event10th Annual International Workshop on Languages and Compilers for Parallel Computing, LCPC 1997 - Minneapolis, United States
Duration: Aug 7 1997Aug 9 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other10th Annual International Workshop on Languages and Compilers for Parallel Computing, LCPC 1997
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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