Distributed computing by the Monte Carlo method
Automation and Remote Control
Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Fast and reliable random number generators for scientific computing
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Parallel pseudorandom number generator for large-scale monte carlo simulations
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
| Hi-index | 0.00 |
In this paper, the software library PARMONC that was developed for the massively parallel simulation by Monte Carlo method on supercomputers is presented. The "core" of the library is a well tested, fast and reliable long-period parallel random numbers generator. Routines from the PARMONC can be called in the user-supplied programs written in C, C++ or in FORTRAN without explicit usage of MPI instructions. Routines from the PARMONC automatically calculate sample means of interest and the corresponding computation errors. A computational load is automatically distributed among processors in an optimal way. The routines enable resuming the simulation that was previously performed and automatically take into account its results. The PARMONC is implemented on high-performance clusters of the Siberian Supercomputer Center.