High performance technique for database applications using a hybrid GPU/CPU platform | Zendy

Mohammed A. Zidan | Zendy; Talal Bonny | Zendy; K. Saláma | Zendy

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High performance technique for database applications using a hybrid GPU/CPU platform

Author(s) -

Mohammed A. Zidan,

Talal Bonny,

K. Saláma

Publication year - 2011

Publication title -

king abdullah university of science and technology repository (king abdullah university of science and technology)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/1973009.1973027

Subject(s) - computer science , parallel computing , sequence (biology) , process (computing) , implementation , factor (programming language) , matching (statistics) , central processing unit , sequence database , computer hardware , operating system , programming language , biochemistry , statistics , genetics , chemistry , mathematics , gene , biology

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.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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