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.

翻译：虚拟筛选是药物发现过程的早期阶段，旨在筛选最具潜力的候选分子。在紧急计算场景下，在短时间内找到解决方案至关重要。本文针对实际虚拟筛选应用，评估了基于输入与架构特征的核外优化方法，以提升GPU上的计算效率。在现代超级计算机节点上的实验结果表明，该方法可使性能提升近一倍。此外，我们使用SYCL实现了优化方案，其性能增益与CUDA优化方案保持一致。虚拟筛选活动可借助这一性能提升增加候选分子的评估数量，从而提高发现药物的概率。