TY - GEN
T1 - Efficient Bioinformatics Computations through GPU Accelerated Web Services
AU - Mallawaarachchi, Vijini
AU - Wickramarachchi, Anuradha
AU - Welivita, Anuradha
AU - Perera, Indika
AU - Meedeniya, Dulani
PY - 2018/7/27
Y1 - 2018/7/27
N2 - Web services have become a common means of addressing distributed task execution. There are several such services available at present that cater to the requirements in the domain of bioinformatics. However, it is challenging to find efforts made to utilize Graphics Processing Unit (GPU) accelerated binaries to optimize web services for bioinformatics analyses. Most of the bioinformatics related algorithms are compute-intensive due to their exponential time complexities. Corresponding execution times are further increased as the sequence databases grow rapidly. However, harnessing parallel computational power gives us a pathway to execute these algorithms and allows us to obtain results from web services more efficiently. The work presented in this paper demonstrates the utilization of web services to provide GPU accelerated bioinformatics computations for analytical purposes. A unified service platform is developed in the form of a collection of web services. It utilizes both GPU and CPU processing in order to perform compute-intensive tasks related to biological data analysis. Furthermore, the evaluation results show gains in speed over three folds with improving performance as the length of queries increases.
AB - Web services have become a common means of addressing distributed task execution. There are several such services available at present that cater to the requirements in the domain of bioinformatics. However, it is challenging to find efforts made to utilize Graphics Processing Unit (GPU) accelerated binaries to optimize web services for bioinformatics analyses. Most of the bioinformatics related algorithms are compute-intensive due to their exponential time complexities. Corresponding execution times are further increased as the sequence databases grow rapidly. However, harnessing parallel computational power gives us a pathway to execute these algorithms and allows us to obtain results from web services more efficiently. The work presented in this paper demonstrates the utilization of web services to provide GPU accelerated bioinformatics computations for analytical purposes. A unified service platform is developed in the form of a collection of web services. It utilizes both GPU and CPU processing in order to perform compute-intensive tasks related to biological data analysis. Furthermore, the evaluation results show gains in speed over three folds with improving performance as the length of queries increases.
KW - Bioinformatics
KW - Biological data analysis
KW - GPU computing
KW - Web services
UR - http://www.scopus.com/inward/record.url?scp=85055447728&partnerID=8YFLogxK
U2 - 10.1145/3242840.3242848
DO - 10.1145/3242840.3242848
M3 - Conference contribution
AN - SCOPUS:85055447728
T3 - ACM International Conference Proceeding Series
SP - 94
EP - 98
BT - Proceedings of 2018 2nd International Conference on Algorithms, Computing and Systems, ICACS 2018
PB - Association for Computing Machinery
T2 - 2nd International Conference on Algorithms, Computing and Systems, ICACS 2018
Y2 - 27 July 2018 through 29 July 2018
ER -