Runtime data mapping scheme for irregular problems

Ravi Ponnusamy*, Joel Saltz, Raja Das, Charles Koelbel, Alok Choudhary

*Corresponding author for this work

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

9 Scopus citations


The authors study the the problem of automatically choosing data distributions for irregular problems, which are programs where the data access patterns cannot be determined during compiliation. They describe a method by which data arrays can be automatically mapped at runtime. The mapping is based on the computational patterns in one or more user specified loops. A distributed memory compiler generates code that at runtime generates a distributed data structure to represent the computational pattern of the chosen loop. This computational pattern is used to determine how data arrays are to be partitioned. The compiler generates code to pass the distributed data structure to a partitioner.

Original languageEnglish (US)
Title of host publicationProccedings of the Scalable High Performance Computing Conference-SHPCC-92
PublisherPubl by IEEE
Number of pages4
ISBN (Print)0818627751
StatePublished - Dec 1 1992

Publication series

NameProccedings of the Scalable High Performance Computing Conference-SHPCC-92

ASJC Scopus subject areas

  • Engineering(all)


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