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Genome Biol DOI:10.1186/s13059-019-1836-7

Scaling computational genomics to millions of individuals with GPUs.

Publication TypeJournal Article
Year of Publication2019
AuthorsTaylor-Weiner, A, Aguet, F, Haradhvala, NJ, Gosai, S, Anand, S, Kim, J, Ardlie, K, Van Allen, EM, Getz, G
JournalGenome Biol
Volume20
Issue1
Pages228
Date Published2019 Nov 01
ISSN1474-760X
Abstract

Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we show that high efficiency at low cost can be achieved by leveraging general-purpose libraries for computing using graphics processing units (GPUs), such as PyTorch and TensorFlow. We demonstrate > 200-fold decreases in runtime and ~ 5-10-fold reductions in cost relative to CPUs. We anticipate that the accessibility of these libraries will lead to a widespread adoption of GPUs in computational genomics.

DOI10.1186/s13059-019-1836-7
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/31675989?dopt=Abstract

Alternate JournalGenome Biol.
PubMed ID31675989
PubMed Central IDPMC6823959