ON two-dimensional sparse matrix partitioning: models, methods, and a recipe
buir.contributor.author | Aykanat, Cevdet | |
dc.citation.epage | 683 | en_US |
dc.citation.issueNumber | 2 | en_US |
dc.citation.spage | 656 | en_US |
dc.citation.volumeNumber | 32 | en_US |
dc.contributor.author | Çatalyürek, U. V. | en_US |
dc.contributor.author | Aykanat, Cevdet | en_US |
dc.contributor.author | Uçar, A. | en_US |
dc.date.accessioned | 2016-02-08T09:58:59Z | |
dc.date.available | 2016-02-08T09:58:59Z | |
dc.date.issued | 2010 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | We consider two-dimensional partitioning of general sparse matrices for parallel sparse matrix-vector multiply operation. We present three hypergraph-partitioning-based methods, each having unique advantages. The first one treats the nonzeros of the matrix individually and hence produces fine-grain partitions. The other two produce coarser partitions, where one of them imposes a limit on the number of messages sent and received by a single processor, and the other trades that limit for a lower communication volume. We also present a thorough experimental evaluation of the proposed two-dimensional partitioning methods together with the hypergraph-based one-dimensional partitioning methods, using an extensive set of public domain matrices. Furthermore, for the users of these partitioning methods, we present a partitioning recipe that chooses one of the partitioning methods according to some matrix characteristics. © 2010 Society for Industrial and Applied Mathematics. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T09:58:59Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2010 | en |
dc.identifier.doi | 10.1137/080737770 | en_US |
dc.identifier.issn | 1064-8275 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/22351 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Society for Industrial and Applied Mathematics | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1137/080737770 | en_US |
dc.source.title | SIAM Journal on Scientific Computing | en_US |
dc.subject | Combinatorial scientific computing | en_US |
dc.subject | Hypergraph partitioning | en_US |
dc.subject | Parallel matrix-vector multiplication | en_US |
dc.subject | Sparse matrix partitioning | en_US |
dc.subject | Two-dimensional partitioning | en_US |
dc.subject | Experimental evaluation | en_US |
dc.subject | Hypergraph | en_US |
dc.subject | Matrix vector multiplication | en_US |
dc.subject | One-dimensional partitioning | en_US |
dc.subject | Partitioning methods | en_US |
dc.subject | Public domains | en_US |
dc.subject | Scientific computing | en_US |
dc.subject | Single processors | en_US |
dc.subject | Sparse matrices | en_US |
dc.subject | Matrix algebra | en_US |
dc.title | ON two-dimensional sparse matrix partitioning: models, methods, and a recipe | en_US |
dc.type | Article | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- ON two-dimensional sparse matrix partitioning Models, methods, and a recipe.pdf
- Size:
- 4.25 MB
- Format:
- Adobe Portable Document Format
- Description:
- Full printable version