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

## TL;DR

This paper demonstrates how combining OpenMP and OpenACC can significantly accelerate molecular docking applications on heterogeneous HPC nodes, achieving up to 36% throughput improvement over traditional CPU/GPU data splitting methods.

## Contribution

The paper introduces a hybrid OpenMP and OpenACC approach for optimizing molecular docking on heterogeneous HPC systems, outperforming pure CPU or GPU data splitting strategies.

## Key findings

- Up to 36% throughput improvement with the hybrid approach
- Better node utilization compared to pure CPU/GPU methods
- Effective acceleration of molecular docking tasks

## Abstract

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.