Monte Carlo methods rely on sequences of random numbers to obtain solutions to many
problems in science and engineering. In this work, we evaluate the performance of different …

There is an increasing interest in the distribution of parallel random number streams in the
high‐performance computing community particularly, with the manycore shift. Even if we …

We developed a computer noise simulation model for cone beam computed tomography
imaging using a general purpose PC cluster. This model uses a mono-energetic x-ray …

We present a parallel algorithm for solving backward stochastic differential equations. We
improve the algorithm proposed by Gobet and Labart (2010) based on an adaptive Monte …

In this paper, we propose ThundeRiNG, a resource-efficient and high-throughput system for
generating multiple independent sequences of random numbers (MISRN) on FPGAs …

Random number generators are necessary in every simulation which includes stochastic
aspects. For High Performance Computing, there is an increasing interest in the distribution …

RNA is central in several stages of protein synthesis, and also has structural and functional
roles in the cell. The shape of organic molecules such as RNA largely determines their …

Currently, the most efficient numerical techniques for evaluating high-dimensional integrals
are based on Monte Carlo and quasi-Monte Carlo techniques. These tasks require a …

Monte Carlo (MC) methods have proved to be flexible, robust and very useful techniques in
computational finance. Several studies have investigated ways to achieve greater efficiency …

В работе рассматривается новый метод модификации многомерной псевдослучайной
последовательности точек, основанный на использовании пары двойственных …