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On the Use of Cloud Computing for Scientific Workflows
Abstract
This paper explores the use of cloud computing for scientific workflows, focusing on a widely used astronomy application-Montage. The approach is to evaluate from the point of view of a scientific workflow the tradeoffs between running in a local environment, if such is available, and running in a virtual environment via remote, wide-area network resource access. Our results show that for Montage, a workflow with short job runtimes, the virtual environment can provide good compute time performance but it can suffer from resource scheduling delays and widearea communications.
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Cited by
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Self-citationDistributed and cloud computing: from parallel processing to the Internet of things
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Marwick, B. (2017) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-015-9272-9 · Cited by 179
Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses
Liu, B., Madduri, R. K., Sotomayor, B., Chard, K., Lacinski, L., Dave, U. J., Li, J., Liu, C., & Foster, I. T. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.01.005 · Cited by 81
Metadata
- Authors
- Hoffa, C., Mehta, G., Freeman, T., Deelman, E., Keahey, K., Berriman, B., & Good, J.
- Venue
- 2008 IEEE Fourth International Conference on eScience
- Publisher
- IEEE
- Published
- 2008-12
- Pages
- 640-645
- OpenAlex
- W2111895701
- Cited by
- 359
- References
- 0
- FWCI
- 24.92
- Type
- conference paper
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
