Scalar and parallel optimized implementation of the direct simulation Monte Carlo method
Journal of Computational Physics
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
Parallel Programming in C with MPI and OpenMP
Parallel Programming in C with MPI and OpenMP
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
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
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The Direct Simulation Monte Carlo (DSMC) method is used to simulate rarified fluid flow where the mean free path of molecules is of the same order of magnitude or greater than the representative physical length scale. The DSMC method models fluid flow by using particles which represent a large number of real molecules in a probabilistic simulation to solve the Boltzmann equation. Due to the large number of individual particles that must be represented, the computational complexity of the DSMC method is beyond the capabilities of desktop computing. In this paper we present data-parallel techniques to efficiently simulate large-scale DSMC models on graphics processing units (GPUs). We have designed and implemented the Nanbu DSMC method to simulate gas flow. Our results show a substantial gain in performance compared to the serial version running on a single CPU.