Scalable input/output : achieving system balance / edited by Daniel A. Reed.
Contributor(s): Reed, Daniel A. (Daniel Allen)
| IEEE Xplore (Online Service) [distributor.] | MIT Press [publisher.].
Material type: 
BookSeries: Scientific and engineering computation: Publisher: Cambridge, Massachusetts : MIT Press, c2004Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2003]Description: 1 PDF (xv, 274 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9780262287869.Subject(s): Memory management (Computer science) | Parallel computers | Computer input-output equipmentGenre/Form: Electronic books.Additional physical formats: Print version: No titleOnline resources: Abstract with links to resource Also available in print.Summary: As we enter the "decade of data," the disparity between the vast amount of data storage capacity (measurable in terabytes and petabytes) and the bandwidth available for accessing it has created an input/output bottleneck that is proving to be a major constraint on the effective use of scientific data for research. Scalable Input/Output is a summary of the major research results of the Scalable I/O Initiative, launched by Paul Messina, then Director of the Center for Advanced Computing Research at the California Institute of Technology, to explore software and algorithmic solutions to the I/O imbalance. The contributors explore techniques for I/O optimization, including: I/O characterization to understand application and system I/O patterns; system checkpointing strategies; collective I/O and parallel database support for scientific applications; parallel I/O libraries and strategies for file striping, prefetching, and write behind; compilation strategies for out-of-core data access; scheduling and shared virtual memory alternatives; network support for low-latency data transfer; and parallel I/O application programming interfaces.
Includes bibliographical references.
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As we enter the "decade of data," the disparity between the vast amount of data storage capacity (measurable in terabytes and petabytes) and the bandwidth available for accessing it has created an input/output bottleneck that is proving to be a major constraint on the effective use of scientific data for research. Scalable Input/Output is a summary of the major research results of the Scalable I/O Initiative, launched by Paul Messina, then Director of the Center for Advanced Computing Research at the California Institute of Technology, to explore software and algorithmic solutions to the I/O imbalance. The contributors explore techniques for I/O optimization, including: I/O characterization to understand application and system I/O patterns; system checkpointing strategies; collective I/O and parallel database support for scientific applications; parallel I/O libraries and strategies for file striping, prefetching, and write behind; compilation strategies for out-of-core data access; scheduling and shared virtual memory alternatives; network support for low-latency data transfer; and parallel I/O application programming interfaces.
Also available in print.
Mode of access: World Wide Web
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