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Mass Storage Systems and Technologies, IEEE / NASA Goddard Conference on (2011)
Denver, CO USA
May 23, 2011 to May 27, 2011
ISBN: 978-1-4577-0427-7
pp: 1-14
Philip Carns , Mathematics and Computer Science Division, Argonne National Laboratory, IL 60439, USA
Kevin Harms , Argonne Leadership Computing Facility, Argonne National Laboratory, IL 60439, USA
William Allcock , Argonne Leadership Computing Facility, Argonne National Laboratory, IL 60439, USA
Charles Bacon , Argonne Leadership Computing Facility, Argonne National Laboratory, IL 60439, USA
Samuel Lang , Mathematics and Computer Science Division, Argonne National Laboratory, IL 60439, USA
Robert Latham , Mathematics and Computer Science Division, Argonne National Laboratory, IL 60439, USA
Robert Ross , Mathematics and Computer Science Division, Argonne National Laboratory, IL 60439, USA
ABSTRACT
Computational science applications are driving a demand for increasingly powerful storage systems. While many techniques are available for capturing the I/O behavior of individual application trial runs and specific components of the storage system, continuous characterization of a production system remains a daunting challenge for systems with hundreds of thousands of compute cores and multiple petabytes of storage. As a result, these storage systems are often designed without a clear understanding of the diverse computational science workloads they will support.
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CITATION

R. Ross et al., "Understanding and improving computational science storage access through continuous characterization," 2011 IEEE 27th Symposium on Mass Storage Systems and Technologies (MSST), Denver, CO, 2011, pp. 1-14.
doi:10.1109/MSST.2011.5937212
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