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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7676696 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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