Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows
[Display omitted] 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...
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| Published in | Computational materials science Vol. 187; p. 110086 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.02.2021
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| Subjects | |
| Online Access | Get full text |
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| Abstract | [Display omitted]
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. |
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| AbstractList | [Display omitted]
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. |
| ArticleNumber | 110086 |
| Author | Pizzi, Giovanni Huber, Sebastiaan P. Uhrin, Martin Yu, Jusong Marzari, Nicola |
| Author_xml | – sequence: 1 givenname: Martin orcidid: 0000-0001-6902-1289 surname: Uhrin fullname: Uhrin, Martin email: martin.uhrin.10@ucl.ac.uk organization: Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland – sequence: 2 givenname: Sebastiaan P. orcidid: 0000-0001-5845-8880 surname: Huber fullname: Huber, Sebastiaan P. email: mail@sphuber.net organization: Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland – sequence: 3 givenname: Jusong surname: Yu fullname: Yu, Jusong organization: Department of Physics, South China University of Technology, Guangzhou 510640, China – sequence: 4 givenname: Nicola surname: Marzari fullname: Marzari, Nicola organization: Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland – sequence: 5 givenname: Giovanni orcidid: 0000-0002-3583-4377 surname: Pizzi fullname: Pizzi, Giovanni organization: Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland |
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| Keywords | High-throughput Provenance Data management Computational workflows Data sharing Robust computation Database Event-based |
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