GPU Accelerated API for Alignment of Genomics Sequencing Data

Nauman Ahmed; Hamid Mushtaq; Koen Bertels; Zaid Al-Ars

doi:10.1109/BIBM.2017.8217699

GPU Accelerated API for Alignment of Genomics Sequencing Data

Nauman Ahmed, Hamid Mushtaq, Koen Bertels, Zaid Al-Ars

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

7 Citations (Scopus)

Abstract

Sequence alignment is a core step in the processing of DNA and RNA sequencing data. In this paper, we present a high performance GPU accelerated library (GASAL) for pairwise sequence alignment of DNA and RNA sequences. The GASAL library provides accelerated kernels for local, global as
well as semi-global alignment, allowing the computation of the alignment score, and optionally the start and end positions of the alignment. GASAL outperforms the fastest CPU-optimized SIMD implementations such as SSW and Parasail. It also outperforms NVBIO, NVIDIA’s own CUDA library for sequence analysis of high-throughput sequencing data. GASAL uses the unique approach of also performing the sequence packing on GPU, which is over 200x faster than the NVBIO approach. Overall on Tesla K40c GASAL is 10-14x faster than 28 Intel Xeon cores and 3-4x faster than NVBIO with a query length of 100 bases. The library provides easy to use APIs to allow integration into various bioinformatics tools.

Original language	English
Title of host publication	2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Editors	X. Hu, C.R. Shyu, Y. Bromberg, J. Gao, Y. Gong, D. Korkin, I. Yoo, J.H. Zheng
Place of Publication	Danvers
Publisher	IEEE
Pages	510-515
Number of pages	6
ISBN (Electronic)	978-1-5090-3050-7
ISBN (Print)	978-1-5090-3051-4
DOIs	https://doi.org/10.1109/BIBM.2017.8217699
Publication status	Published - Nov 2017
Event	2017 IEEE International Conference on Bioinformatics and Biomedicine - Kansas City, United States Duration: 13 Nov 2017 → 16 Nov 2017

Conference

Conference	2017 IEEE International Conference on Bioinformatics and Biomedicine
Abbreviated title	IEEE BIBM 2017
Country/Territory	United States
City	Kansas City
Period	13/11/17 → 16/11/17

Keywords

sequence alignment
GPU acceleration
software API
NGS

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10.1109/BIBM.2017.8217699

Cite this

@inproceedings{095c65aeaeae4a82b999181a71f38599,

title = "GPU Accelerated API for Alignment of Genomics Sequencing Data",

abstract = "Sequence alignment is a core step in the processing of DNA and RNA sequencing data. In this paper, we present a high performance GPU accelerated library (GASAL) for pairwise sequence alignment of DNA and RNA sequences. The GASAL library provides accelerated kernels for local, global aswell as semi-global alignment, allowing the computation of the alignment score, and optionally the start and end positions of the alignment. GASAL outperforms the fastest CPU-optimized SIMD implementations such as SSW and Parasail. It also outperforms NVBIO, NVIDIA{\textquoteright}s own CUDA library for sequence analysis of high-throughput sequencing data. GASAL uses the unique approach of also performing the sequence packing on GPU, which is over 200x faster than the NVBIO approach. Overall on Tesla K40c GASAL is 10-14x faster than 28 Intel Xeon cores and 3-4x faster than NVBIO with a query length of 100 bases. The library provides easy to use APIs to allow integration into various bioinformatics tools.",

keywords = "sequence alignment, GPU acceleration, software API, NGS",

author = "Nauman Ahmed and Hamid Mushtaq and Koen Bertels and Zaid Al-Ars",

year = "2017",

month = nov,

doi = "10.1109/BIBM.2017.8217699",

language = "English",

isbn = "978-1-5090-3051-4 ",

pages = "510--515",

editor = "X. Hu and C.R. Shyu and Y. Bromberg and J. Gao and Y. Gong and D. Korkin and I. Yoo and J.H. Zheng",

booktitle = "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",

publisher = "IEEE",

address = "United States",

note = "2017 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2017 ; Conference date: 13-11-2017 Through 16-11-2017",

}

Ahmed, N, Mushtaq, H, Bertels, K & Al-Ars, Z 2017, GPU Accelerated API for Alignment of Genomics Sequencing Data. in X Hu, CR Shyu, Y Bromberg, J Gao, Y Gong, D Korkin, I Yoo & JH Zheng (eds), 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, Danvers, pp. 510-515, 2017 IEEE International Conference on Bioinformatics and Biomedicine, Kansas City, Missouri, United States, 13/11/17. https://doi.org/10.1109/BIBM.2017.8217699

GPU Accelerated API for Alignment of Genomics Sequencing Data. / Ahmed, Nauman; Mushtaq, Hamid; Bertels, Koen et al.
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). ed. / X. Hu; C.R. Shyu; Y. Bromberg; J. Gao; Y. Gong; D. Korkin; I. Yoo; J.H. Zheng. Danvers: IEEE, 2017. p. 510-515.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - GPU Accelerated API for Alignment of Genomics Sequencing Data

AU - Ahmed, Nauman

AU - Mushtaq, Hamid

AU - Bertels, Koen

AU - Al-Ars, Zaid

PY - 2017/11

Y1 - 2017/11

N2 - Sequence alignment is a core step in the processing of DNA and RNA sequencing data. In this paper, we present a high performance GPU accelerated library (GASAL) for pairwise sequence alignment of DNA and RNA sequences. The GASAL library provides accelerated kernels for local, global aswell as semi-global alignment, allowing the computation of the alignment score, and optionally the start and end positions of the alignment. GASAL outperforms the fastest CPU-optimized SIMD implementations such as SSW and Parasail. It also outperforms NVBIO, NVIDIA’s own CUDA library for sequence analysis of high-throughput sequencing data. GASAL uses the unique approach of also performing the sequence packing on GPU, which is over 200x faster than the NVBIO approach. Overall on Tesla K40c GASAL is 10-14x faster than 28 Intel Xeon cores and 3-4x faster than NVBIO with a query length of 100 bases. The library provides easy to use APIs to allow integration into various bioinformatics tools.

AB - Sequence alignment is a core step in the processing of DNA and RNA sequencing data. In this paper, we present a high performance GPU accelerated library (GASAL) for pairwise sequence alignment of DNA and RNA sequences. The GASAL library provides accelerated kernels for local, global aswell as semi-global alignment, allowing the computation of the alignment score, and optionally the start and end positions of the alignment. GASAL outperforms the fastest CPU-optimized SIMD implementations such as SSW and Parasail. It also outperforms NVBIO, NVIDIA’s own CUDA library for sequence analysis of high-throughput sequencing data. GASAL uses the unique approach of also performing the sequence packing on GPU, which is over 200x faster than the NVBIO approach. Overall on Tesla K40c GASAL is 10-14x faster than 28 Intel Xeon cores and 3-4x faster than NVBIO with a query length of 100 bases. The library provides easy to use APIs to allow integration into various bioinformatics tools.

KW - sequence alignment

KW - GPU acceleration

KW - software API

KW - NGS

U2 - 10.1109/BIBM.2017.8217699

DO - 10.1109/BIBM.2017.8217699

M3 - Conference contribution

SN - 978-1-5090-3051-4

SP - 510

EP - 515

BT - 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

A2 - Hu, X.

A2 - Shyu, C.R.

A2 - Bromberg, Y.

A2 - Gao, J.

A2 - Gong, Y.

A2 - Korkin, D.

A2 - Yoo, I.

A2 - Zheng, J.H.

PB - IEEE

CY - Danvers

T2 - 2017 IEEE International Conference on Bioinformatics and Biomedicine

Y2 - 13 November 2017 through 16 November 2017

ER -

GPU Accelerated API for Alignment of Genomics Sequencing Data

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Keywords

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