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High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

Berriman, Bruce and Deelman, Ewa and Juve, Gideon and Rynge, Mats and Vöckler, Jens-S. (2012) High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away. In: Astronomical Data Analysis Software and Systems XXI. ASP Conference Series. No.461. Astronomical Society of the Pacific , San Francisco, CA, pp. 91-94. ISBN 978-1-58381-804-6. https://resolver.caltech.edu/CaltechAUTHORS:20130410-103427171

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Abstract

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data, and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://www.aspbooks.org/a/volumes/article_details/?paper_id=34629PublisherArticle
ORCID:
AuthorORCID
Berriman, Bruce0000-0001-8388-534X
Additional Information:© 2012 Astronomical Society of the Pacific. G. B. Berriman is supported by the NASA Exoplanet Science Institute at the Infrared Processing and Analysis Center, operated by the California Institute of Technology in coordination with the Jet Propulsion Laboratory (JPL). USC/ISI researchers are funded by the National Science Foundation under Cooperative Agreement OCI-0438712 and grant CCF-0725332.
Group:Infrared Processing and Analysis Center (IPAC)
Funders:
Funding AgencyGrant Number
NASAUNSPECIFIED
NSFOCI-0438712
NSFCCF-0725332
Series Name:ASP Conference Series
Issue or Number:461
Record Number:CaltechAUTHORS:20130410-103427171
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20130410-103427171
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:37854
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:10 Apr 2013 18:14
Last Modified:28 Oct 2019 20:11

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