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GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics

Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, View ORCID ProfileJames J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
doi: https://doi.org/10.1101/2022.10.10.511571
Maxim Zvyagin
1Argonne National Laboratory
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Alexander Brace
1Argonne National Laboratory
2University of Chicago
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Kyle Hippe
1Argonne National Laboratory
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Yuntian Deng
3NVIDIA Inc.
4Harvard University
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Bin Zhang
5Cerebras Inc.
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Cindy Orozco Bohorquez
5Cerebras Inc.
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Austin Clyde
1Argonne National Laboratory
2University of Chicago
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Bharat Kale
6Northern Illinois University
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Danilo Perez-Rivera
1Argonne National Laboratory
7New York University
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Heng Ma
1Argonne National Laboratory
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Carla M. Mann
1Argonne National Laboratory
2University of Chicago
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Michael Irvin
1Argonne National Laboratory
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J. Gregory Pauloski
2University of Chicago
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Logan Ward
1Argonne National Laboratory
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Valerie Hayot-Sasson
1Argonne National Laboratory
2University of Chicago
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Murali Emani
1Argonne National Laboratory
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Sam Foreman
1Argonne National Laboratory
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Zhen Xie
1Argonne National Laboratory
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Diangen Lin
1Argonne National Laboratory
2University of Chicago
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Maulik Shukla
1Argonne National Laboratory
2University of Chicago
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Weili Nie
3NVIDIA Inc.
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Josh Romero
3NVIDIA Inc.
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Christian Dallago
3NVIDIA Inc.
9Technical University of Munich
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Arash Vahdat
3NVIDIA Inc.
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Chaowei Xiao
8Arizona State University
3NVIDIA Inc.
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Thomas Gibbs
3NVIDIA Inc.
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Ian Foster
1Argonne National Laboratory
2University of Chicago
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James J. Davis
1Argonne National Laboratory
2University of Chicago
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  • ORCID record for James J. Davis
Michael E. Papka
1Argonne National Laboratory
10University of Illinois Chicago
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Thomas Brettin
1Argonne National Laboratory
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Rick Stevens
1Argonne National Laboratory
2University of Chicago
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Anima Anandkumar
3NVIDIA Inc.
11California Institute of Technology
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  • For correspondence: anima@caltech.edu
Venkatram Vishwanath
1Argonne National Laboratory
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  • For correspondence: venkat@anl.gov
Arvind Ramanathan
1Argonne National Laboratory
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  • For correspondence: ramanathana@anl.gov
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ABSTRACT

We seek to transform how new and emergent variants of pandemiccausing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pretraining on over 110 million prokaryotic gene sequences and finetuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵† Joint first authors

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    Supercomputing ‘22, November 14-19, 2022, Dallas, TX

    © 2020 Association for Computing Machinery.

    ACM ISBN ISBN...$15.00

    https://doi.org/finalDOI

  • Fixed minor typos, fixed performance numbers that were requested by reviewers and editors.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 23, 2022.
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GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics
Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
bioRxiv 2022.10.10.511571; doi: https://doi.org/10.1101/2022.10.10.511571
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GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics
Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
bioRxiv 2022.10.10.511571; doi: https://doi.org/10.1101/2022.10.10.511571

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