工作流程
计算机科学
接口
可扩展性
插件
数据库
软件工程
关系数据库
数据共享
分布式计算
模块化设计
可重用性
元数据
工作流管理系统
数据管理
信息基础设施
数据存取
接口(物质)
互操作性
数据集成
数据建模
数据科学
数据类型
数据模型(GIS)
重新使用
世界信息峰会大奖
分布式数据库
可发现性
作者
Sebastiaan P. Huber,Spyros Zoupanos,Martin Uhrin,Leopold Talirz,Leonid Kahle,Rico Häuselmann,Dominik Gresch,Tiziano Müller,Aliaksandr V. Yakutovich,Casper W. Andersen,Francisco F. Ramirez,Carl S. Adorf,Fernando Gargiulo,Snehal Kumbhar,Elsa Passaro,Conrad Johnston,Andrius Merkys,Andrea Cepellotti,Nicolas Mounet,Nicola Marzari
出处
期刊:Scientific Data
[Nature Portfolio]
日期:2020-09-08
卷期号:7 (1): 300-300
被引量:279
标识
DOI:10.1038/s41597-020-00638-4
摘要
The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.
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