Scalable Input/Output: Achieving System Balance

Scalable Input/Output: Achieving System Balance

by Daniel A. Reed
     
 

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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

Overview

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

ISBN-13:
9780262681421
Publisher:
MIT Press
Publication date:
10/24/2003
Series:
Scientific and Engineering Computation Series
Edition description:
New Edition
Pages:
392
Product dimensions:
7.00(w) x 9.00(h) x 0.75(d)
Age Range:
18 Years

Meet the Author

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.

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