Speeding-up Bioinformatics Algorithms with Heterogeneous Architectures: Highly Heterogeneous Smith-Waterman (HHeterSW).
The Smith-Waterman algorithm has a great sensitivity when used for biological sequence-database searches, but at the expense of high computing-power requirements. To overcome this problem, there are implementations in literature that exploit the different hardware-architectures available in a standard PC, such as GPU, CPU, and coprocessors. We introduce an application that splits the original database-search problem into smaller parts, resolves each of them by executing the most efficient implementations of the Smith-Waterman algorithms in different hardware architectures, and finally unifies the generated results. Using non-overlapping hardware allows simultaneous execution, and up to 2.58-fold performance gain, when compared with any other algorithm to search sequence databases. Even the performance of the popular BLAST heuristic is exceeded in 78% of the tests. The application has been tested with standard hardware: Intel i7-4820K CPU, Intel Xeon Phi 31S1P coprocessors, and nVidia GeForce GTX 960 graphics cards. An important increase in performance has been obtained in a wide range of situations, effectively exploiting the available hardware.
1 Dep. Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga , Málaga, Spain .
Sergio
S
Gálvez
1 Dep. Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga , Málaga, Spain .
Adis
A
Ferusic
2 Servicio de Informática, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba , 14071 Córdoba, Spain .
Francisco J
FJ
Esteban
3 Instituto de Agricultura Sostenible (IAS-CSIC) , Alameda del Obispo s/n, Córdoba, Spain .
Pilar
P
Hernández
4 Dep. Estadística, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba , 14071 Córdoba, Spain .
Juan A
JA
Caballero
5 Dep. Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba , 14071 Córdoba, Spain .
Gabriel
G
Dorado
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003201:Computers; D016208:Databases, Factual; D004867:Equipment Design; D006801:Humans; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*
CUDA; Xeon Phi; balance load; bioinformatics; coarse-grained parallelization; many-core; non-overlapping hardware; sequence alignment