Over the last two decades, the field of computational science has seen a dramatic shift towards incorporating high-throughput computation and big-data analysis as fundamental pillars of the scientific discovery process. This has necessitated the development of tools and techniques to deal with the generation, storage and processing of large amounts of data. In this work we present an in-depth look at the workflow engine powering AiiDA, a widely adopted, highly flexible and database-backed informatics infrastructure with an emphasis on data reproducibility. We detail many of the design choices that were made which were informed by several important goals: the ability to scale from running on individual laptops up to high-performance supercomputers, managing jobs with runtimes spanning from fractions of a second to weeks and scaling up to thousands of jobs concurrently, and all this while maximising robustness. In short, AiiDA aims to be a Swiss army knife for high-throughput computational science. As well as the architecture, we outline important API design choices made to give workflow writers a great deal of liberty whilst guiding them towards writing robust and modular workflows, ultimately enabling them to encode their scientific knowledge to the benefit of the wider scientific community.

中文翻译：

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AiiDA 中的工作流：为强大的模块化计算工作流设计一个高吞吐量、基于事件的引擎

在过去的二十年里，计算科学领域发生了巨大的转变，将高通量计算和大数据分析作为科学发现过程的基本支柱。这就需要开发工具和技术来处理大量数据的生成、存储和处理。在这项工作中，我们深入研究了支持 AiiDA 的工作流引擎，AiiDA 是一种广泛采用、高度灵活且由数据库支持的信息学基础架构，重点是数据可再现性。我们详细介绍了根据几个重要目标做出的许多设计选择：从在单个笔记本电脑上运行扩展到高性能超级计算机的能力，管理运行时间从几分之一秒到几周不等的作业，并同时扩展到数千个作业，同时最大限度地提高鲁棒性。简而言之，AiiDA 旨在成为高通量计算科学的瑞士军刀。除了架构之外，我们还概述了重要的 API 设计选择，这些选择旨在为工作流编写者提供极大的自由，同时指导他们编写强大的模块化工作流，最终使他们能够对科学知识进行编码，以造福于更广泛的科学界。