Monte Carlo methods. Vol. 1: basics
Monte Carlo methods. Vol. 1: basics
Synchronous relaxation for parallel simulations with applications to circuit-switched networks
ACM Transactions on Modeling and Computer Simulation (TOMACS)
LogP: a practical model of parallel computation
Communications of the ACM
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Synchronous relaxation for parallel Ising spin simulations
Proceedings of the fifteenth workshop on Parallel and distributed simulation
Performance optimization of numerically intensive codes
Performance optimization of numerically intensive codes
IEEE Computational Science & Engineering
IEEE Computational Science & Engineering
A Guide to Monte Carlo Simulations in Statistical Physics
A Guide to Monte Carlo Simulations in Statistical Physics
ACM/IEEE SC 2005 Conference - Cover
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms
Journal of Computational Physics
Massively parallel Monte Carlo for many-particle simulations on GPUs
Journal of Computational Physics
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A novel parallel kinetic Monte Carlo (kMC) algorithm formulated on the basis of perfect time synchronicity is presented. The algorithm is intended as a generalization of the standard n-fold kMC method, and is trivially implemented in parallel architectures. In its present form, the algorithm is not rigorous in the sense that boundary conflicts are ignored. We demonstrate, however, that, in their absence, or if they were correctly accounted for, our algorithm solves the same master equation as the serial method. We test the validity and parallel performance of the method by solving several pure diffusion problems (i.e. with no particle interactions) with known analytical solution. We also study diffusion-reaction systems with known asymptotic behavior and find that, for large systems with interaction radii smaller than the typical diffusion length, boundary conflicts are negligible and do not affect the global kinetic evolution, which is seen to agree with the expected analytical behavior. Our method is a controlled approximation in the sense that the error incurred by ignoring boundary conflicts can be quantified intrinsically, during the course of a simulation, and decreased arbitrarily (controlled) by modifying a few problem-dependent simulation parameters.