Title :
Large-Scale Pairwise Sequence Alignments on a Large-Scale GPU Cluster
Author :
Savran, Ibrahim ; Yang Gao ; Bakos, Jason D.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Carolina, Columbia, SC, USA
Abstract :
The paper describes a graphics processing unit (GPU) kernel that performs batch Needleman-Wunsch (N-W) global alignments. For each alignment, the kernel returns an alignment score divided by the total alignment length. When used with its MPI-based host software, the kernel is scalable and is capable of achieving high-throughput alignment when run on a CPU-GPU cluster. The host software includes a load balancing technique for data sets having sequences of nonuniform lengths.
Keywords :
application program interfaces; biology computing; graphics processing units; message passing; molecular biophysics; resource allocation; CPU-GPU cluster; GPU kernel; MPI-based host software; Needleman-Wunsch global alignments; alignment length; alignment score; graphics processing unit; high-throughput alignment; large-scale GPU cluster; large-scale pairwise sequence alignments; load balancing technique; message passing interface; Accelerators; Clustering methods; Computational biology; DNA; Genomics; Graphics processing units; Hardware; Message systems; Sequential analysis; GPU; Needleman-Wunsch sequence alignment; genomics heterogeneous computing; high performance computing;
Journal_Title :
Design & Test, IEEE
DOI :
10.1109/MDAT.2013.2290116
