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A Massively Parallel Lattice Monte Carlo Algorithm in CUDA for Thermal Conduction Simulations
SESSION: Research Poster Reception
EVENT TYPE: ACM Student Research Competition Poster, Poster, Electronic Poster
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Bernd Mohr
AUTHOR(S):Michael P. Wang, Paul J. Mignone, Daniel P. Riley, George V. Franks, Thomas Fiedler, Graeme E. Murch
ROOM:WSCC North Galleria 2nd/3rd Floors
ABSTRACT: This work seeks to enhance and modernize the field of ultra-high temperature composites development by providing industry and research a novel, rapid simulation technique that harnesses the massively parallel computing power of modern GPUs.
The development of cutting-edge materials systems for ultra-high temperature applications such as hypersonics and power generation requires the evaluation of an immensely large parameter space. At the microstructural level, this involves a complex interplay between chemical (e.g. elemental or alloy content) and physical (e.g. pore morphology and distribution) properties . Modelling represents one of the most cost-effective tools for rapidly optimizing of the processing and fabrication parameters required to achieve the desired results.
A highly parallel micro-level thermal transport code has been developed in CUDA, which, to date, has achieved more than 100x increase in simulation speed. Co-simulation with the commercial FEA package Abaqus is envisaged, which will provide a coupled, macro-level structural analysis capability.
Chair/Author Details:
Bernd Mohr (Chair) - Juelich Supercomputing Centre
Michael P. Wang - University of Melbourne
Paul J. Mignone - University of Melbourne
Daniel P. Riley - Australian Nuclear Science and Technology Organisation