High Performance Biological Pairwise Sequence Alignment : FPGA versus GPU versus Cell BE versus GPP
Joint Authors
Liu, Ying
Akoglu, Ali
Tian, Xiang
Ling, Cheng
Song, Yang
Benkrid, Khaled
Source
International Journal of Reconfigurable Computing
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-16
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper explores the pros and cons of reconfigurable computing in the form of FPGAs for high performance efficient computing.
In particular, the paper presents the results of a comparative study between three different acceleration technologies, namely, Field Programmable Gate Arrays (FPGAs), Graphics Processor Units (GPUs), and IBM’s Cell Broadband Engine (Cell BE), in the design and implementation of the widely-used Smith-Waterman pairwise sequence alignment algorithm, with general purpose processors as a base reference implementation.
Comparison criteria include speed, energy consumption, and purchase and development costs.
The study shows that FPGAs largely outperform all other implementation platforms on performance per watt criterion and perform better than all other platforms on performance per dollar criterion, although by a much smaller margin.
Cell BE and GPU come second and third, respectively, on both performance per watt and performance per dollar criteria.
In general, in order to outperform other technologies on performance per dollar criterion (using currently available hardware and development tools), FPGAs need to achieve at least two orders of magnitude speed-up compared to general-purpose processors and one order of magnitude speed-up compared to domain-specific technologies such as GPUs.
American Psychological Association (APA)
Benkrid, Khaled& Akoglu, Ali& Ling, Cheng& Song, Yang& Liu, Ying& Tian, Xiang. 2012. High Performance Biological Pairwise Sequence Alignment : FPGA versus GPU versus Cell BE versus GPP. International Journal of Reconfigurable Computing،Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-495995
Modern Language Association (MLA)
Benkrid, Khaled…[et al.]. High Performance Biological Pairwise Sequence Alignment : FPGA versus GPU versus Cell BE versus GPP. International Journal of Reconfigurable Computing No. 2012 (2012), pp.1-15.
https://search.emarefa.net/detail/BIM-495995
American Medical Association (AMA)
Benkrid, Khaled& Akoglu, Ali& Ling, Cheng& Song, Yang& Liu, Ying& Tian, Xiang. High Performance Biological Pairwise Sequence Alignment : FPGA versus GPU versus Cell BE versus GPP. International Journal of Reconfigurable Computing. 2012. Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-495995
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-495995