Show simple item record

dc.contributor.authorKotlyar, Vladimiren_US
dc.contributor.authorPingali, Keshaven_US
dc.contributor.authorStodghill, Paulen_US
dc.date.accessioned2007-04-23T18:09:28Z
dc.date.available2007-04-23T18:09:28Z
dc.date.issued1997-03en_US
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR97-1627en_US
dc.identifier.urihttps://hdl.handle.net/1813/7282
dc.description.abstractWe present a relational algebra based framework for compiling efficient sparse matrix code from dense DO-ANY loops and a specification of the representation of the sparse matrix. We present experimental data that demonstrates that the code generated by our compiler achieves performance competitive with that of hand-written codes for important computational kernels.en_US
dc.format.extent245091 bytes
dc.format.extent193754 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleA Relational Approach to the Compilation of Sparse Matrix Programsen_US
dc.typetechnical reporten_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

Statistics