GPU Accelerated API for Alignment of Genomics Sequencing Data

Conference paper (2017)

Authors

N. Ahmed Computer Engineering - EEMCS
H. Mushtaq Computer Engineering - EEMCS
K.L.M. Bertels FTQC/Bertels Lab , Quantum & Computer Engineering
Z. Al-Ars Computer Engineering - EEMCS
Research Group
Computer Engineering (EEMCS) (TU Delft)
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Published Date

2017-11

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Quantum & Computer Engineering

Research Group

Computer Engineering

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.

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