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BarraCUDA - a fast short read sequence aligner using graphics processing units.

Klus P, Lam S, Lyberg D, Cheung MS, Pullan G, McFarlane I, Yeo GSh, Lam BY - BMC Res Notes (2012)

Bottom Line: 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.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.BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Hill's Road, Cambridge CB2 0QQ, UK. yhbl2@cam.ac.uk.

ABSTRACT

Background: 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.

Findings: 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.

Conclusions: 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.BarraCUDA is currently available from http://seqbarracuda.sf.net.

No MeSH data available.


A comparison of alignment throughput of BWA and BarraCUDA in align real-life sequencing reads to the human genome. Two whole-genome shotgun libraries from the 1000 Genomes Project were used to compare the paired-end alignment throughput between BWA and BarraCUDA. A. 11.3 million pairs of 37 bp reads (ENA accession: ERR003014) were aligned to the human genome (NCBI 36.54) using BWA v0.5.8 with a server class Intel Xeon 5670 (utilising 1 or 6 threads) and BarraCUDA with an NVIDIA Tesla M2090, both with default options. The figure shows the time taken for 'aln' core (in blue) and 'sampe' core (in red); B. The time taken with gap opening disabled using the option '-o 0'; C. The time taken to align 14.5 million pairs of 76 bp reads (ENA accession: SRR032215) using the same set of hardware; D. The timings with gap opening disabled.
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Figure 3: A comparison of alignment throughput of BWA and BarraCUDA in align real-life sequencing reads to the human genome. Two whole-genome shotgun libraries from the 1000 Genomes Project were used to compare the paired-end alignment throughput between BWA and BarraCUDA. A. 11.3 million pairs of 37 bp reads (ENA accession: ERR003014) were aligned to the human genome (NCBI 36.54) using BWA v0.5.8 with a server class Intel Xeon 5670 (utilising 1 or 6 threads) and BarraCUDA with an NVIDIA Tesla M2090, both with default options. The figure shows the time taken for 'aln' core (in blue) and 'sampe' core (in red); B. The time taken with gap opening disabled using the option '-o 0'; C. The time taken to align 14.5 million pairs of 76 bp reads (ENA accession: SRR032215) using the same set of hardware; D. The timings with gap opening disabled.

Mentions: Figure 3a and 3b depicts the relative alignment throughputs (including the alignment 'aln' core in blue and SAM output 'sampe' core in red) for the 37 bp read library of BWA and BarraCUDA respectively. For gapped alignments, running BWA alignment core with an Intel Westmere-based Xeon X5670 2.93 GHz CPU and 8 GB DDR3 memory with 1 thread took 67 m 56 s to map all the 11.3 million pairs of reads in the library, while the time taken was reduced to 11 m 51 s when the same task was performed using all 6 cores on the CPU (Figure 3a). On the other hand, BarraCUDA took 10 m 51 s to perform the same task using an NVIDIA Tesla M2090, which was on a par with BWA using all 6 cores on the X5670.


BarraCUDA - a fast short read sequence aligner using graphics processing units.

Klus P, Lam S, Lyberg D, Cheung MS, Pullan G, McFarlane I, Yeo GSh, Lam BY - BMC Res Notes (2012)

A comparison of alignment throughput of BWA and BarraCUDA in align real-life sequencing reads to the human genome. Two whole-genome shotgun libraries from the 1000 Genomes Project were used to compare the paired-end alignment throughput between BWA and BarraCUDA. A. 11.3 million pairs of 37 bp reads (ENA accession: ERR003014) were aligned to the human genome (NCBI 36.54) using BWA v0.5.8 with a server class Intel Xeon 5670 (utilising 1 or 6 threads) and BarraCUDA with an NVIDIA Tesla M2090, both with default options. The figure shows the time taken for 'aln' core (in blue) and 'sampe' core (in red); B. The time taken with gap opening disabled using the option '-o 0'; C. The time taken to align 14.5 million pairs of 76 bp reads (ENA accession: SRR032215) using the same set of hardware; D. The timings with gap opening disabled.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3278344&req=5

Figure 3: A comparison of alignment throughput of BWA and BarraCUDA in align real-life sequencing reads to the human genome. Two whole-genome shotgun libraries from the 1000 Genomes Project were used to compare the paired-end alignment throughput between BWA and BarraCUDA. A. 11.3 million pairs of 37 bp reads (ENA accession: ERR003014) were aligned to the human genome (NCBI 36.54) using BWA v0.5.8 with a server class Intel Xeon 5670 (utilising 1 or 6 threads) and BarraCUDA with an NVIDIA Tesla M2090, both with default options. The figure shows the time taken for 'aln' core (in blue) and 'sampe' core (in red); B. The time taken with gap opening disabled using the option '-o 0'; C. The time taken to align 14.5 million pairs of 76 bp reads (ENA accession: SRR032215) using the same set of hardware; D. The timings with gap opening disabled.
Mentions: Figure 3a and 3b depicts the relative alignment throughputs (including the alignment 'aln' core in blue and SAM output 'sampe' core in red) for the 37 bp read library of BWA and BarraCUDA respectively. For gapped alignments, running BWA alignment core with an Intel Westmere-based Xeon X5670 2.93 GHz CPU and 8 GB DDR3 memory with 1 thread took 67 m 56 s to map all the 11.3 million pairs of reads in the library, while the time taken was reduced to 11 m 51 s when the same task was performed using all 6 cores on the CPU (Figure 3a). On the other hand, BarraCUDA took 10 m 51 s to perform the same task using an NVIDIA Tesla M2090, which was on a par with BWA using all 6 cores on the X5670.

Bottom Line: 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.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.BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Hill's Road, Cambridge CB2 0QQ, UK. yhbl2@cam.ac.uk.

ABSTRACT

Background: 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.

Findings: 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.

Conclusions: 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.BarraCUDA is currently available from http://seqbarracuda.sf.net.

No MeSH data available.