Advanced I/O for large-scale scientific applications.

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Description

As scientific simulations scale to use petascale machines and beyond, the data volumes generated pose a dual problem. First, with increasing machine sizes, the careful tuning of IO routines becomes more and more important to keep the time spent in IO acceptable. It is not uncommon, for instance, to have 20% of an application's runtime spent performing IO in a 'tuned' system. Careful management of the IO routines can move that to 5% or even less in some cases. Second, the data volumes are so large, on the order of 10s to 100s of TB, that trying to discover the ... continued below

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38 p.

Creation Information

Klasky, Scott (Oak Ridge National Laboratory, Oak Ridge, TN); Schwan, Karsten (Georgia Institute of Technology, Atlanta, GA); Oldfield, Ron A. & Lofstead, Gerald F., II (Georgia Institute of Technology, Atlanta, GA) January 1, 2010.

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Description

As scientific simulations scale to use petascale machines and beyond, the data volumes generated pose a dual problem. First, with increasing machine sizes, the careful tuning of IO routines becomes more and more important to keep the time spent in IO acceptable. It is not uncommon, for instance, to have 20% of an application's runtime spent performing IO in a 'tuned' system. Careful management of the IO routines can move that to 5% or even less in some cases. Second, the data volumes are so large, on the order of 10s to 100s of TB, that trying to discover the scientifically valid contributions requires assistance at runtime to both organize and annotate the data. Waiting for offline processing is not feasible due both to the impact on the IO system and the time required. To reduce this load and improve the ability of scientists to use the large amounts of data being produced, new techniques for data management are required. First, there is a need for techniques for efficient movement of data from the compute space to storage. These techniques should understand the underlying system infrastructure and adapt to changing system conditions. Technologies include aggregation networks, data staging nodes for a closer parity to the IO subsystem, and autonomic IO routines that can detect system bottlenecks and choose different approaches, such as splitting the output into multiple targets, staggering output processes. Such methods must be end-to-end, meaning that even with properly managed asynchronous techniques, it is still essential to properly manage the later synchronous interaction with the storage system to maintain acceptable performance. Second, for the data being generated, annotations and other metadata must be incorporated to help the scientist understand output data for the simulation run as a whole, to select data and data features without concern for what files or other storage technologies were employed. All of these features should be attained while maintaining a simple deployment for the science code and eliminating the need for allocation of additional computational resources.

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38 p.

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  • Report No.: SAND2009-7763
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/1004371 | External Link
  • Office of Scientific & Technical Information Report Number: 1004371
  • Archival Resource Key: ark:/67531/metadc837954

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • January 1, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • Nov. 22, 2016, 3:57 p.m.

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Klasky, Scott (Oak Ridge National Laboratory, Oak Ridge, TN); Schwan, Karsten (Georgia Institute of Technology, Atlanta, GA); Oldfield, Ron A. & Lofstead, Gerald F., II (Georgia Institute of Technology, Atlanta, GA). Advanced I/O for large-scale scientific applications., report, January 1, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc837954/: accessed June 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.