Abstract
The annual Workshop on Workflows in Support of Large-Scale Science (WORKS) is a premier venue for the scientific workflow community to present the latest advances in research and development on the many facets of scientific workflows throughout their life-cycle. The Lightning Talks at WORKS focus on describing a novel tool, scientific workflow, or concept, which are work-in-progress and address emerging technologies and frameworks to foster discussion in the community. This paper summarizes the lightning talks at the 2023 edition of WORKS, covering five topics: leveraging large language models to build and execute workflows; developing a common workflow scheduler interface; scaling uncertainty workflow applications on exascale computing systems; evaluating a transcriptomics workflow for cloud vs. HPC systems; and best practices in migrating legacy workflows to workflow management systems.
| Original language | English |
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| Title of host publication | Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 |
| Publisher | Association for Computing Machinery |
| Pages | 2097-2108 |
| Number of pages | 12 |
| ISBN (Electronic) | 9798400707858 |
| DOIs | |
| State | Published - Nov 12 2023 |
| Event | 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 - Denver, United States Duration: Nov 12 2023 → Nov 17 2023 |
Publication series
| Name | ACM International Conference Proceeding Series |
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Conference
| Conference | 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 11/12/23 → 11/17/23 |
Funding
The materials this work is based upon are supported by NSF award 2050195; the German Research Foundation (DFG) CRC 1404: "FONDA: Foundations of Workflows for Large-Scale Scientific Data Analysis;" the Office of Science of the U.S. Department of Energy (DOE) under Contract No. DE-AC05-00OR22725; the Exascale Computing Project (ECP, 17-SC-20-SC) ExaWorks project under DOE Contract No. DE-SC0012704; Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344; DOE INCITE awards for allocations on Summit, Crusher, and Frontier; the European Union (EU) Horizon 2020 research and innovation programme under grant agreement Sano No. 857533 within the International Research Agendas programme of the Foundation for Polish Science, co-financed by the EU under the European Regional Development Fund; the EU Horizon 2020 research and innovation programme under grant agreement NEARDATA No. 101092644; the PLGrid Infrastructure and the Ares supercomputer at ACC Cyfronet AGH; and DOE Joint Genome Institute under Contract No. DE-AC02-05CH11231.
Keywords
- Scientific workflows
- cloud computing
- high-performance computing
- large language models
- legacy workflows
- workflow scheduling