Show simple item record

dc.contributor.authorZidan, Mohammed A.
dc.contributor.authorBonny, Talal
dc.contributor.authorSalama, Khaled N.
dc.date.accessioned2012-07-28T10:21:58Z
dc.date.available2012-07-28T10:21:58Z
dc.date.issued2012-07-28
dc.identifier.citationZidan MA, Bonny T, Salama KN (2011) High performance technique for database applicationsusing a hybrid GPU/CPU platform. Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI - GLSVLSI 11:85-90. doi:10.1145/1973009.1973027.
dc.identifier.doi10.1145/1973009.1973027
dc.identifier.urihttp://hdl.handle.net/10754/236114
dc.descriptionMany database applications, such as sequence comparing, sequence searching, and sequence matching, etc, process large database sequences. we introduce a novel and efficient technique to improve the performance of database applications by using a Hybrid GPU/CPU platform. In particular, our technique solves the problem of the low efficiency resulting from running short-length sequences in a database on a GPU. To verify our technique, we applied it to the widely used Smith-Waterman algorithm. The experimental results show that our Hybrid GPU/CPU technique improves the average performance by a factor of 2.2, and improves the peak performance by a factor of 2.8 when compared to earlier implementations.
dc.description.abstractMany database applications, such as sequence comparing, sequence searching, and sequence matching, etc, process large database sequences. we introduce a novel and efficient technique to improve the performance of database applica- tions by using a Hybrid GPU/CPU platform. In particular, our technique solves the problem of the low efficiency result- ing from running short-length sequences in a database on a GPU. To verify our technique, we applied it to the widely used Smith-Waterman algorithm. The experimental results show that our Hybrid GPU/CPU technique improves the average performance by a factor of 2.2, and improves the peak performance by a factor of 2.8 when compared to earlier implementations. Copyright © 2011 by ASME.
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.urlhttp://portal.acm.org/citation.cfm?doid=1973009.1973027
dc.titleHigh performance technique for database applicationsusing a hybrid GPU/CPU platform
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentSensors Lab
dc.identifier.journalProceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI - GLSVLSI '11
dc.conference.date2 May 2011 through 4 May 2011
dc.conference.name21st Great Lakes Symposium on VLSI, GLSVLSI 2011
dc.conference.locationLausanne
kaust.personZidan, Mohammed A.
kaust.personBonny, Mohamed Talal
kaust.personSalama, Khaled N.
refterms.dateFOA2018-06-13T20:12:41Z


Files in this item

Thumbnail
Name:
High_Performance_Technique_for_Database_Applications_Using_a_Hybrid_GPUCPU_Platform.pdf
Size:
473.3Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record