Arioc: High-concurrency short-read alignment on multiple GPUs

In large DNA sequence repositories, archival data storage is often coupled with computers that provide 40 or more CPU threads and multiple GPU (general-purpose graphics processing unit) devices. This presents an opportunity for DNA sequence alignment software to exploit high-concurrency hardware to...

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Bibliographic Details
Published in:	PLoS computational biology 2020-11, Vol.16 (11), p.e1008383-e1008383
Main Authors:	Wilton, Richard, Szalay, Alexander S
Format:	Article
Language:	eng
Subjects:	Algorithms Base Sequence Biology and Life Sciences Computational Biology Computer and Information Sciences Computer Graphics Computers Databases, Nucleic Acid Engineering and Technology Humans Information Storage and Retrieval Research and Analysis Methods Sequence Alignment - methods Sequence Alignment - statistics & numerical data Sequence Analysis, DNA Software Whole Genome Sequencing
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Summary:	In large DNA sequence repositories, archival data storage is often coupled with computers that provide 40 or more CPU threads and multiple GPU (general-purpose graphics processing unit) devices. This presents an opportunity for DNA sequence alignment software to exploit high-concurrency hardware to generate short-read alignments at high speed. Arioc, a GPU-accelerated short-read aligner, can compute WGS (whole-genome sequencing) alignments ten times faster than comparable CPU-only alignment software. When two or more GPUs are available, Arioc's speed increases proportionately because the software executes concurrently on each available GPU device. We have adapted Arioc to recent multi-GPU hardware architectures that support high-bandwidth peer-to-peer memory accesses among multiple GPUs. By modifying Arioc's implementation to exploit this GPU memory architecture we obtained a further 1.8x-2.9x increase in overall alignment speeds. With this additional acceleration, Arioc computes two million short-read alignments per second in a four-GPU system; it can align the reads from a human WGS sequencer run-over 500 million 150nt paired-end reads-in less than 15 minutes. As WGS data accumulates exponentially and high-concurrency computational resources become widespread, Arioc addresses a growing need for timely computation in the short-read data analysis toolchain.
ISSN:	1553-7358 1553-734X 1553-7358