dc.contributor.author | Liu, Junhong | |
dc.contributor.author | He, Xin | |
dc.contributor.author | Liu, Weifeng | |
dc.contributor.author | Tan, Guangming | |
dc.date.accessioned | 2018-04-09T08:18:02Z | |
dc.date.available | 2018-04-09T08:18:02Z | |
dc.date.created | 2018-04-06T09:27:32Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | ACMSIGPLAN Symposium on Principles and Practice of Parallel Programming. 2018, . | nb_NO |
dc.identifier.issn | 1542-0205 | |
dc.identifier.uri | http://hdl.handle.net/11250/2493148 | |
dc.description.abstract | General sparse matrix-matrix multiplication (SpGEMM) is an essential building block in a number of applications. In our work, we fully utilize GPU registers and shared memory to implement an efficient and load balanced SpGEMM in comparison with the existing implementations. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Association for Computing Machinery (ACM) | nb_NO |
dc.title | Register-based Implementation of the Sparse General Matrix-matrix Multiplication on GPUs | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.pagenumber | 2 | nb_NO |
dc.source.journal | ACMSIGPLAN Symposium on Principles and Practice of Parallel Programming | nb_NO |
dc.identifier.doi | https://doi.org/10.1145/3178487.3178529 | |
dc.identifier.cristin | 1577872 | |
dc.relation.project | EC/H2020/752321 | nb_NO |
dc.description.localcode | © 2018 Copyright held by the owner/author(s). | nb_NO |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |