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DTSTART:19700308T020000
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DTSTAMP:20210402T160010Z
LOCATION:Track 10
DTSTART;TZID=America/New_York:20201119T103000
DTEND;TZID=America/New_York:20201119T110000
UID:submissions.supercomputing.org_SC20_sess388_cov103@linklings.com
SUMMARY:High-Throughput Virtual Laboratory for Drug Discovery Using Massiv
 e Datasets
DESCRIPTION:ACM Gordon Bell COVID Finalist, Awards Presentation\n\nHigh-Th
 roughput Virtual Laboratory for Drug Discovery Using Massive Datasets\n\nG
 laser, Vermaas, Rogers, Larkin, LeGrand...\n\nTime-to-solution for structu
 re-based screening of massive chemical databases for COVID-19 drug discove
 ry has been decreased by an order of magnitude, and a virtual laboratory h
 as been deployed at scale on up to 27,612 GPUs on the Summit supercomputer
 , allowing an average molecular docking of 19,028 compounds per second. Ov
 er one billion compounds were docked to two SARS-CoV-2 protein structures 
 with full optimization of ligand position and 20 poses per docking, each i
 n under 24 hours. GPU acceleration and high-throughput optimizations of th
 e docking program produced 350x mean speedup over the CPU version (50x spe
 edup per node). GPU acceleration of both feature calculation for machine-l
 earning based scoring and distributed database queries reduced processing 
 of the 2.4 TB output by orders of magnitude.\n\nThe resulting 58x speedup 
 for the full pipeline reduces an initial 51 day runtime to 21 hours per pr
 otein for providing high-scoring compounds to experimental collaborators f
 or validation assays.\n\nRegistration Category: Tech Program Reg Pass
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