Abstract
Lightning talks of the Workflows in Support of Large-Scale Science (WORKS) workshop are a venue where the workflow community (researchers, developers, and users) can discuss work in progress, emerging technologies and frameworks, and training and education materials. This paper summarizes the WORKS 2021 lightning talks, which cover four broad topics: (i) libEnsemble, a Python library to coordinate the concurrent evaluation of dynamic ensembles of calculations; (ii) Edu WRENCH, a set of online pedagogic modules that provides simulation-driven hands-on activity in the browser; (iii) VisDict, an envisioned visual dictionary framework that will translate terms, jargon, and concepts between research domains and workflow providers; and (iv) Pegasus Kickstart, a lightweight tool for capturing workflow tasks' performance, including performance metrics from Nvidia GPUs.
Original language | English |
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Title of host publication | Proceedings of WORKS 2021 |
Subtitle of host publication | 16th Workshop on Workflows in Support of Large-Scale Science, Held in conjunction with SC 2021: The International Conference for High Performance Computing, Networking, Storage and Analysis |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 74-80 |
Number of pages | 7 |
ISBN (Electronic) | 9781665411363 |
DOIs | |
State | Published - 2021 |
Event | 16th IEEE Workshop on Workflows in Support of Large-Scale Science, WORKS 2021 - St. Louis, United States Duration: Nov 15 2021 → … |
Publication series
Name | Proceedings of WORKS 2021: 16th Workshop on Workflows in Support of Large-Scale Science, Held in conjunction with SC 2021: The International Conference for High Performance Computing, Networking, Storage and Analysis |
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Conference
Conference | 16th IEEE Workshop on Workflows in Support of Large-Scale Science, WORKS 2021 |
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Country/Territory | United States |
City | St. Louis |
Period | 11/15/21 → … |
Funding
Acknowledgments. This work is funded by NSF contracts #1923539 and #1923621; and partly funded by NSF contracts #2103489, and #2103508. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Acknowledgments. This work is funded by DOE contract #DESC0012636 and NSF contract #1664162. Acknowledgments. This work is funded by NSF contracts #2100561 and #2100636.
Keywords
- Concurrent computing
- Ensembles
- GPU
- Monitoring
- Numerical optimization
- Nvidia
- Python
- Scientific workflows
- Simulation
- Training and education