High-throughput molecular docking is a data-driven simulation methodology to estimate millions of molecules’ position and interaction strength (ligands) when interacting with a given protein site. Because of its data-driven nature, the highthroughput molecular docking performance depends on how fast we can ingest data into the processing pipeline and how efficiently we can write molecular docking results to a shared file. This work characterizes the I/O performance of a high-performance, high-throughput molecular docking application, called DockerHT, running on a supercomputer up to 512 computing nodes with two different parallel I/O configurations. We show that a tuned I/O configuration can improve the overall parallel efficiency from 71% to 90% on 512 nodes and identify and solve a performance degradation observed when running on 16 and 32 nodes.

Understanding the I/O Impact on the Performance of High-Throughput Molecular Docking

Markidis, Stefano;Gadioli, Davide;Vitali, Emanuele;Palermo, Gianluca
2021-01-01

Abstract

High-throughput molecular docking is a data-driven simulation methodology to estimate millions of molecules’ position and interaction strength (ligands) when interacting with a given protein site. Because of its data-driven nature, the highthroughput molecular docking performance depends on how fast we can ingest data into the processing pipeline and how efficiently we can write molecular docking results to a shared file. This work characterizes the I/O performance of a high-performance, high-throughput molecular docking application, called DockerHT, running on a supercomputer up to 512 computing nodes with two different parallel I/O configurations. We show that a tuned I/O configuration can improve the overall parallel efficiency from 71% to 90% on 512 nodes and identify and solve a performance degradation observed when running on 16 and 32 nodes.
2021
IEEE/ACM Sixth International Parallel Data Systems Workshop (PDSW)
978-1-6654-1837-9
High-Throughput Molecular Docking, Parallel I/O, Darshan, I/O Profiling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1198330
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