Infrastructure for scalable parallel multidimensional analysis

Sanjay Goil*, Alok Nidhi Choudhary

*Corresponding author for this work

Research output: Contribution to conferencePaper

2 Scopus citations

Abstract

Scalability in multi-dimensional systems is addressed for analysis in Scientific and statistical databases (SSDB) and On-Line Analytical Processing (OLAP) applications. The Parallel and Scalable Infrastructure for Multidimensional Online analytical processing (PARSIMONY) system is described. Sparsity of data sets is handled by using chunks to store data as a sparse set using a Bit encoded sparse structure. Performance results for high dimensional data sets on a distributed memory parallel machine (IBM SP-2) show good speedup and scalability.

Original languageEnglish (US)
Pages102-111
Number of pages10
StatePublished - Jan 1 1999
EventProceedings of the 1999 11th International Conference on Scientific and Statistical Database Management (SSDBM'99) - Cleveland, OH, USA
Duration: Jul 28 1999Jul 30 1999

Other

OtherProceedings of the 1999 11th International Conference on Scientific and Statistical Database Management (SSDBM'99)
CityCleveland, OH, USA
Period7/28/997/30/99

ASJC Scopus subject areas

  • Software
  • Applied Mathematics

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    Goil, S., & Choudhary, A. N. (1999). Infrastructure for scalable parallel multidimensional analysis. 102-111. Paper presented at Proceedings of the 1999 11th International Conference on Scientific and Statistical Database Management (SSDBM'99), Cleveland, OH, USA, .