Virtual screening is an early stage of the drug discovery process that selects the most promising candidates. In the urgent computing scenario it is critical to find a solution in a short time frame. In this paper, we focus on a real-world virtual screening application to evaluate out-of-kernel optimizations, that consider input and architecture features to improve the computation efficiency on GPU. Experiment results on a modern supercomputer node show that we can almost double the performance. Moreover, we implemented the optimization using SYCL and it provides a consistent benefit with the CUDA optimization. A virtual screening campaign can use this gain in performance to increase the number of evaluated candidates, improving the probability of finding a drug.
@article{arxiv.2303.06150,
title = {Improving computation efficiency using input and architecture features for a virtual screening application},
author = {Gianmarco Accordi and Emanuele Vitali and Davide Gadioli and Luigi Crisci and Biagio Cosenza and Mauro Bisson and Massimiliano Fatica and Andrea Beccari and Gianluca Palermo},
journal= {arXiv preprint arXiv:2303.06150},
year = {2023}
}