BarraCUDA - a fast short read sequence aligner using graphics processing units
- Equal contributors
1 University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Hill's Road, Cambridge CB2 0QQ, UK
2 Genomics CoreLab, NIHR-Cambridge Biomedical Research Centre, Box 232, Addenbrooke's Hospital, Hill's Road, Cambridge CB2 0QQ, UK
3 Department of Microbiology, University College Cork, College Road, Cork, Ireland
4 The Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge CB2 1QN, UK
5 Whittle Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0DY, UK
BMC Research Notes 2012, 5:27 doi:10.1186/1756-0500-5-27Published: 13 January 2012
With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence.
Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput.
BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.