Time-to-solution for structure-based screening of massive chemical databases for COVID-19 drug discovery has been decreased by an order of magnitude, and a virtual laboratory has 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. Over one billion compounds were docked to two SARS-CoV-2 protein structures with full optimization of ligand position and 20 poses per docking, each in under 24 hours. GPU acceleration and high-throughput optimizations of the docking program produced 350× mean speedup over the CPU version (50× speedup per node). GPU acceleration of both feature calculation for machine-learning based scoring and distributed database queries reduced processing of the 2.4 TB output by orders of magnitude. The resulting 50× speedup for the full pipeline reduces an initial 43 day runtime to 21 hours per protein for providing high-scoring compounds to experimental collaborators for validation assays.

用于COVID-19药物发现的大规模化学数据库的结构化筛选所需的解决时间缩短了一个数量级，并且在Summit超级计算机上已在多达27,612个GPU上大规模部署了虚拟实验室，每秒平均19,028个化合物的分子对接。通过完全优化的配体位置和每个对接20个姿势，将超过十亿个化合物对接至两个SARS-CoV-2蛋白结构，每个在24小时内完成。GPU加速和对接程序的高吞吐量优化产生了CPU版本350倍的平均加速（每个节点50倍的加速）。基于机器学习的计分和分布式数据库查询的功能计算的GPU加速将2.4 TB输出的处理量减少了几个数量级。