Large Scale Problem Solving Using Automatic Code Generation and Distributed Visualization
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Abstract
Scientific computation faces multiple scalability challenges
in trying to take advantage of the latest generation compute,
network and graphics hardware. We present a comprehensive
approach to solving four important scalability challenges:
programming productivity, scalability to large numbers of
processors, I/O bandwidth, and interactive visualization of large
data. We describe a scenario where our integrated system is applied in the
field of numerical relativity. A solver for the governing
Einstein equations is generated and
executed on a large computational cluster; the simulation output is
distributed onto a distributed data server, and finally visualized
using distributed visualization methods and high-speed networks.
A demonstration of this system was awarded first place in the
IEEE SCALE 2009 Challenge.
in trying to take advantage of the latest generation compute,
network and graphics hardware. We present a comprehensive
approach to solving four important scalability challenges:
programming productivity, scalability to large numbers of
processors, I/O bandwidth, and interactive visualization of large
data. We describe a scenario where our integrated system is applied in the
field of numerical relativity. A solver for the governing
Einstein equations is generated and
executed on a large computational cluster; the simulation output is
distributed onto a distributed data server, and finally visualized
using distributed visualization methods and high-speed networks.
A demonstration of this system was awarded first place in the
IEEE SCALE 2009 Challenge.
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Issue
Section
Special Issue Papers