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

Mohammed A. Zidan; Mohamed Talal Bonny; Khaled N. Salama

doi:10.1145/1973009.1973027

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

Mohammed A. Zidan, Mohamed Talal Bonny, Khaled N. Salama

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI - GLSVLSI '11
Publisher	Association for Computing Machinery (ACM)
Pages	85-90
Number of pages	6
ISBN (Print)	9781450306676
DOIs	https://doi.org/10.1145/1973009.1973027
State	Published - May 3 2011

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10.1145/1973009.1973027

https://repository.kaust.edu.sa/bitstream/10754/236114/1/High_Performance_Technique_for_Database_Applications_Using_a_Hybrid_GPUCPU_Platform.pdf

Cite this

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title = "High performance technique for database applicationsusing a hybrid GPU/CPU platform",

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 {\textcopyright} 2011 by ASME.",

author = "Zidan, {Mohammed A.} and Bonny, {Mohamed Talal} and Salama, {Khaled N.}",

note = "KAUST Repository Item: Exported on 2020-10-01",

year = "2011",

month = may,

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doi = "10.1145/1973009.1973027",

language = "English (US)",

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address = "United States",

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High performance technique for database applicationsusing a hybrid GPU/CPU platform. / Zidan, Mohammed A.; Bonny, Mohamed Talal; Salama, Khaled N.
Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI - GLSVLSI '11. Association for Computing Machinery (ACM), 2011. p. 85-90.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - High performance technique for database applicationsusing a hybrid GPU/CPU platform

AU - Zidan, Mohammed A.

AU - Bonny, Mohamed Talal

AU - Salama, Khaled N.

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2011/5/3

Y1 - 2011/5/3

N2 - 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.

AB - 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.

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BT - Proceedings of the 21st edition of the great lakes symposium on Great lakes symposium on VLSI - GLSVLSI '11

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

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