The Cost of Doing Science on the Cloud: The Montage Example
Abstract
Utility grids such as the Amazon EC2 cloud and Amazon S3 offer computational and storage resources that can be used on-demand for a fee by compute and data-intensive applications. The cost of running an application on such a cloud depends on the compute, storage and communication resources it will provision and consume. Different execution plans of the same application may result in significantly different costs. Using the Amazon cloud fee structure and a real-life astronomy application, we study via simulation the cost performance tradeoffs of different execution and resource provisioning plans. We also study these trade-offs in the context of the storage and communication fees of Amazon S3 when used for long-term application data archival. Our results show that by provisioning the right amount of storage and compute resources, cost can be significantly reduced with no significant impact on application performance.
Additional Information
© 2008 IEEE. This work was funded by the National Science Foundation under Cooperative Agreement OCI-0438712 and grant # CCF-0725332. This research made use of Montage, funded by NASA's Earth Science Technology Office, Computation Technologies Project, under Cooperative Agreement Number NCC5-626 between NASA and the California Institute of Technology. Montage is maintained by the NASA/IPAC Infrared Science Archive.Attached Files
Published - 05217932.pdf
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Additional details
- Eprint ID
- 70910
- Resolver ID
- CaltechAUTHORS:20161005-173223566
- NSF
- OCI-0438712
- NSF
- CCF-0725332
- NASA
- NCC5-626
- Created
-
2016-10-06Created from EPrint's datestamp field
- Updated
-
2023-10-23Created from EPrint's last_modified field
- Caltech groups
- Infrared Processing and Analysis Center (IPAC), Infrared Processing and Analysis Center (IPAC)