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dc.contributor.authorSojka, Radim
dc.contributor.authorŘíha, Lubomír
dc.contributor.authorHorák, David
dc.contributor.authorKružík, Jakub
dc.contributor.authorBeseda, Martin
dc.contributor.authorČermák, Martin
dc.date.accessioned2017-05-31T05:53:57Z
dc.date.available2017-05-31T05:53:57Z
dc.date.issued2017
dc.identifier.citationIn: Simos, Theodore and Charalambos Tsitouras, eds. Proceedings of International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2016), 19-25 September 2016, Rhodes, Greece. AIP conference proceedings, no. 1863. Meville, N.Y.: AIP Publishing, 2017, art. no. 340015.
dc.identifier.urihttp://hdl.handle.net/10084/117099
dc.description.abstractThe paper deals with the energy consumption evaluation of selected Sparse and Dense BLAS Level 1, 2 and 3 routines. Authors employed AXPY, Sparse Matrix-Vector, Sparse Matrix-Matrix, Dense Matrix-Vector, Dense Matrix-Matrix and Sparse Matrix-Dense Matrix multiplication routines from Intel Math Kernel Library (MKL). The measured characteristics illustrate the different energy consumption of BLAS routines, as some operations are memory-bounded and others are compute-bounded. Based on their recommendations one can explore dynamic frequency switching to achieve significant energy savings up to 23%.en
dc.format.extent262506 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.relation.ispartofseriesAIP Conference Proceedings
dc.relation.urihttps://doi.org/10.1063/1.4992522
dc.subjectREADEXen
dc.subjectCPU frequencyen
dc.subjectBLASen
dc.subjectenergy consumptionen
dc.titleThe energy consumption optimization of the BLAS routinesen
dc.typeconferenceObjecten
dc.identifier.doi10.1063/1.4992522
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/671657/EU//READEX
dc.rights.accessopenAccess
dc.type.versionpublishedVersionen
dc.type.statusPeer-revieweden
dc.identifier.wos000410159800349


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