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Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Emanuele Vitali, Davide Gadioli, Gianluca Palermo, Andrea Beccari, Carlo Cavazzoni, Cristina Silvano
Dipartimento di Elettronica, Infomazione e Bioingegneria, Politecnico di Milano, Italy
arXiv:1901.06229 [cs.DC], (18 Jan 2019)

@article{vitali2019exploiting,

   title={Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes},

   author={Vitali, Emanuele and Gadioli, Davide and Palermo, Gianluca and Beccari, Andrea and Cavazzoni, Carlo and Silvano, Cristina},

   year={2019},

   month={jan},

   archivePrefix={"arXiv"},

   primaryClass={cs.DC}

}

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In drug discovery, molecular docking is the task in charge of estimating the position of a molecule when interacting with the docking site. This task is usually used to perform screening of a large library of molecules, in the early phase of the process. Given the amount of candidate molecules and the complexity of the application, this task is usually performed using High-Performance Computing (HPC) platforms. In modern HPC systems, heterogeneous platforms provide a better throughput with respect to homogeneous platforms. In this work, we ported and optimized a molecular docking application to a heterogeneous system, with one or more GPU accelerators, leveraging a hybrid OpenMP and OpenACC approach. We prove that our approach has a better exploitation of the node compared to pure CPU/GPU data splitting approaches, reaching a throughput improvement up to 36% while considering the same computing node.
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