High performance technique for database applicationsusing a hybrid GPU/CPU platform

Handle URI:
http://hdl.handle.net/10754/236114
Title:
High performance technique for database applicationsusing a hybrid GPU/CPU platform
Authors:
Zidan, Mohammed A. ( 0000-0003-3843-814X ) ; Bonny, Talal; Salama, Khaled N. ( 0000-0001-7742-1282 )
Abstract:
Many 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Sensors Lab
Citation:
Zidan 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.
Conference/Event name:
21st Great Lakes Symposium on VLSI, GLSVLSI 2011
Issue Date:
28-Jul-2012
DOI:
10.1145/1973009.1973027
Type:
Conference Paper
Description:
Many 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.
Additional Links:
http://portal.acm.org/citation.cfm?doid=1973009.1973027
Appears in Collections:
Conference Papers; Sensors Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorZidan, Mohammed A.en
dc.contributor.authorBonny, Talalen
dc.contributor.authorSalama, Khaled N.en
dc.date.accessioned2012-07-28T10:21:58Z-
dc.date.available2012-07-28T10:21:58Z-
dc.date.issued2012-07-28en
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.en
dc.identifier.doi10.1145/1973009.1973027en
dc.identifier.urihttp://hdl.handle.net/10754/236114en
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.en
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.en
dc.language.isoenen
dc.relation.urlhttp://portal.acm.org/citation.cfm?doid=1973009.1973027en
dc.titleHigh performance technique for database applicationsusing a hybrid GPU/CPU platformen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentSensors Laben
dc.conference.date2 May 2011 through 4 May 2011en
dc.conference.name21st Great Lakes Symposium on VLSI, GLSVLSI 2011en
dc.conference.locationLausanneen
kaust.authorZidan, Mohammed A.en
kaust.authorBonny, Mohamed Talalen
kaust.authorSalama, Khaled N.en
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.