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High-performance computing increasingly occurs on "computational grids"
composed of heterogeneous and geographically distributed systems of
computers, networks, and storage devices that collectively act as a
single "virtual" computer. A key challenge in this environment is to
provide efficient access to data distributed across remote data
servers. This dissertation explores some of the issues associated
with I/O for wide-area distributed computing and describes an I/O
system, called Armada, with the following features: a framework to
allow application and dataset providers to flexibly compose graphs
of processing modules that describe the distribution, application
interfaces, and processing required of the dataset before or after
computation; an algorithm to restructure application graphs to
increase parallelism and to improve network performance in a wide-area
network; and a hierarchical graph-partitioning scheme that deploys
components of the application graph in a way that is both beneficial
to the application and sensitive to the administrative policies of
the different administrative domains. Experiments show that
applications using Armada perform well in both low- and high-bandwidth
environments, and that our approach does an exceptional job of
hiding the network latency inherent in grid computing.
This is a reformatted version of Ron Oldfield's Ph.D. dissertation.
Unlike the dissertation submitted to Dartmouth College, this version
is single-spaced, uses 11pt fonts, and is formatted specifically for
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
Or copy and paste:
Ron A. Oldfield, "Efficient I/O for Computational Grid Applications." Dartmouth Computer Science Technical Report TR2003-459, May 2003.
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