EFFECTIVE GPU ACCELERATION OF LARGE SCALE, ASYNCHRONOUS SIMULATIONS ON GRAPHS

Dustin Arendt () and Yang Cao ()
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Dustin Arendt: Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States
Yang Cao: Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States

Advances in Complex Systems (ACS), 2012, vol. 15, issue 08, 1-20

Abstract: The recent emergence of GPGPU programming has resulted in a number of very efficient, but ultimately ad-hoc implementations of GPU accelerated simulations of complex systems. Because developing applications for the GPU is still a difficult and time consuming task, efficient GPU parallelizations of general purpose modeling frameworks are very useful. The dimer automaton is a stochastic modeling and simulation framework with a good balance of robustness, generality, and simplicity with capacity to model a wide range of phenomena. A major advantage of dimer automata is the ease in which they can be applied to any space that can be represented as a graph. Therefore, we have developed an efficient GPU implementation of dimer automata that runs up to 80 times faster than the serial implementation.

Keywords: GPGPU; maximal matching; asynchronous cellular automata; non-uniform lattice; Hilbert curve (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1142/S021952591250035X

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