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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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Detalles Bibliográficos
Autores principales: Wilton, Richard, Szalay, Alexander S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676696/
https://www.ncbi.nlm.nih.gov/pubmed/33166275
http://dx.doi.org/10.1371/journal.pcbi.1008383
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author Wilton, Richard
Szalay, Alexander S.
author_facet Wilton, Richard
Szalay, Alexander S.
author_sort Wilton, Richard
collection PubMed
description 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.
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spelling pubmed-76766962020-12-02 Arioc: High-concurrency short-read alignment on multiple GPUs Wilton, Richard Szalay, Alexander S. PLoS Comput Biol Research Article 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. Public Library of Science 2020-11-09 /pmc/articles/PMC7676696/ /pubmed/33166275 http://dx.doi.org/10.1371/journal.pcbi.1008383 Text en © 2020 Wilton, Szalay http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wilton, Richard
Szalay, Alexander S.
Arioc: High-concurrency short-read alignment on multiple GPUs
title Arioc: High-concurrency short-read alignment on multiple GPUs
title_full Arioc: High-concurrency short-read alignment on multiple GPUs
title_fullStr Arioc: High-concurrency short-read alignment on multiple GPUs
title_full_unstemmed Arioc: High-concurrency short-read alignment on multiple GPUs
title_short Arioc: High-concurrency short-read alignment on multiple GPUs
title_sort arioc: high-concurrency short-read alignment on multiple gpus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676696/
https://www.ncbi.nlm.nih.gov/pubmed/33166275
http://dx.doi.org/10.1371/journal.pcbi.1008383
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