DHPC Technical Report DHPC-009
Distributed High-Performance Computation for Remote Sensing
K.A.Hawick and H.A.James
Archived: 16 May 1997
Published in Proc. of Supercomputing '97, San Jose, November 1997
Abstract
We describe distributed and parallel algorithms for processing
remotely sensed data such as geostationary satellite imagery. We have
built a distributed data repository based around the client-server
computing model across wide-area ATM networks, with embedded parallel
and high-performance processing modules. We focus on algorithms for
classification, geo-rectification, correlation and histogram analysis
of the data. We consider characteristics of image data collected from
the Japanese GMS5 geostationary meteorological satellite, and some
analysis techniques we have applied to it. As well as providing a
browsing interface to our data collection, our system provides
processing and analysis services on-demand. We are developing our
system to carry out processing and data reduction services
at-a-distance, enabling remote users with limited bandwidth, access to
our system, to obtain useful derived data products at the resolution
they require.
Our target hardware consists of a heterogeneous collection of
distributed workstations, multi-processor servers and massively
parallel computers at locations throughout Australia. These platforms
are connected by ATM-based LANs and also through ATM switches across
long distance WANs such as Telstra's Experimental Broadband Network,
connecting Adelaide, Melbourne and Canberra. Our particular interest
in constructing remote data access and processing services is the
potential to utilise such resources as are available to a given user,
yielding the best performance compromise of data processing and data
delivery. To this end, we are building a set of resource scheduling
and management utilities that will integrate the processing modules we
describe. We have considered a number of software frameworks for
building our integrated system and are focussing on a distributed
object model using WWW protocols and the Java language.
PDF version
HTML version at the SC97 Web site
PostScript version (gzip compressed)
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