Authors:
Yang Liu
;
Jiang-Yu Li
;
Yi-Qing Mao
;
Xiao-Lei Wang
and
Dong-Sheng Zhao
Affiliation:
Academy of Military Medical Sciences, China
Keyword(s):
CUDA, Sequence Aligner, Performance per Watt, Price-performance, Programming Complexity
Related
Ontology
Subjects/Areas/Topics:
Algorithms and Software Tools
;
Bioinformatics
;
Biomedical Engineering
;
Next Generation Sequencing
;
Sequence Analysis
Abstract:
The rapidly accumulating biological data generated by next-generation sequencer motivate the development of improved tools for sequence alignment. Many technologies have been proposed for this purpose, and one of them is GPU computing. Existing acceleration of sequence aligners using GPU computing overemphasize speed. However, other factors such as accuracy, performance per watt, price-performance and programming complexity are also important and need to be considered. Based on the existing literatures of GPU-based sequence aligners, this paper gives a literature evaluation of these sequence aligners from the above perspectives, in order to determine the usability of the tremendous GPU-based sequence aligners.