Scalar and parallel optimized implementation of the direct simulation Monte Carlo method
Journal of Computational Physics
Fast, minimum storage ray-triangle intersection
Journal of Graphics Tools
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Fast 3D triangle-box overlap testing
Journal of Graphics Tools
Parallel Programming in C with MPI and OpenMP
Parallel Programming in C with MPI and OpenMP
Designing efficient sorting algorithms for manycore GPUs
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Preliminary work on graphics processing unit based direct simulation Monte Carlo
Proceedings of the 2010 Conference on Grand Challenges in Modeling & Simulation
Hi-index | 0.00 |
The direct simulation Monte Carlo (DSMC) is a computational method for fluid mechanics simulation in the regime of rarefied gas flow. It is a numerical solution of the Boltzmann equation based on an individual particle basis. Accurate simulations typically require particle numbers in the range of hundreds of thousands to millions. Such large simulations require an inordinate amount of time for processing using serial computing on central processing units (CPUs). In this paper we investigate data-parallel techniques on graphics processing units (GPUs) to execute very large scale DSMC simulations. We have designed and implemented Bird's method on a three-dimensional simulation domain that includes complex geometry interactions. We also have tested and verified the statistical and theoretical accuracy of our implementation. Our results show substantial performance improvements (nearly two orders of magnitude) over Bird's serial implementation without loss of accuracy.