Abstract
The convergence of edge computing, big data analytics, and AI with traditional scientific calculations is increasingly being adopted in HPC workflows. Workflow management systems are crucial for managing and orchestrating these complex computational tasks. However, it is difficult to identify patterns within the growing population of HPC workflows. Serverless has emerged as a novel computing paradigm, offering dynamic resource allocation, quick response time, fine-grained resource management and auto-scaling. In this paper, we propose a framework to enable HPC scientific workflows on serverless. Our approach integrates a widely used traditional HPC workflow generator with an HPC serverless workflow management system to create benchmark suites of scientific workflows with diverse characteristics. These workflows can be executed on different serverless platforms. We comprehensively compare executing workflows on traditional local containers and serverless computing platforms. Our results show that serverless can reduce CPU and memory usage respectively by 78.11% and 73.92% without compromising performance.
| Original language | English |
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| Title of host publication | Proceedings of SC 2024-W |
| Subtitle of host publication | Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 110-125 |
| Number of pages | 16 |
| ISBN (Electronic) | 9798350355543 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024 - Atlanta, United States Duration: Nov 17 2024 → Nov 22 2024 |
Publication series
| Name | Proceedings of SC 2024-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis |
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Conference
| Conference | 2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024 |
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| Country/Territory | United States |
| City | Atlanta |
| Period | 11/17/24 → 11/22/24 |
Funding
This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid up, irrevocable, worldwide license to publish or reproduce the published form of the manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Keywords
- HPC Serverless Workflows
- Scientific Workflows
- Serverless Computing