Fr. 59.50

Scalable Input/Output

English · Paperback / Softback

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Informationen zum Autor Daniel A. Reed holds the Edward William and Jane Marr Gutgsell Professorship at the University of Illinois at Urbana-Champaign. He is also Director of the National Center for Supercomputing Applications (NCSA), Director of the National Computational Science Alliance, and Chief Architect, NSF TeraGrid. William Gropp is Director of the Parallel Computing Institute and Thomas M. Siebel Chair in Computer Science at the University of Illinois Urbana-Champaign. Ewing Lusk is Argonne Distinguished Fellow Emeritus at Argonne National Laboratory. Klappentext The major research results from the Scalable Input/Output Initiative, exploring software and algorithmic solutions to the I/O imbalance. 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. Zusammenfassung The major research results from the Scalable Input/Output Initiative, exploring software and algorithmic solutions to the I/O imbalance. 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. ...

Product details

Authors Daniel Reed, Daniel A. (University of Illinois) Reed
Assisted by William Gropp (Editor), William (Thomas M. Siebel Chair Gropp (Editor), Ewing Lusk (Editor), Ewing (Argonne Distinguished Fellow Emeritus Lusk (Editor), Daniel A. Reed (Editor), Daniel A. (University of Illinois) Reed (Editor)
Publisher The MIT Press
 
Languages English
Product format Paperback / Softback
Released 24.10.2003
 
EAN 9780262681421
ISBN 978-0-262-68142-1
No. of pages 392
Dimensions 175 mm x 227 mm x 20 mm
Series Scientific and Engineering Computation
Scientific and Engineering Com
Scalable Input/Output
Scientific and Engineering Computation
Scientific and Engineering Com
Subject Natural sciences, medicine, IT, technology > IT, data processing > Data communication, networks

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