Many scientific and engineering applications involve inverting large matrices or solving
systems of linear algebraic equations. Solving these problems with proven algorithms for …

Simulation studies of grid scheduling strategies require representative workloads to produce
dependable results. Real production grid workloads have shown diverse correlation …

Purpose: This paper investigated a framework to efficiently compute and merge Monte Carlo
simulations with new technique development in cancer treatment. A newly designed 3-D …

In this paper we present a stochastic SPAI pre-conditioner. In contrast to the standard
deterministic SPAI pre-conditioners that use the Frobenius norm, we present a Monte Carlo …

Traditionally, solving the adjoint equation for unsteady problems involves solving a large,
structured linear system. This paper presents a variation on this technique and uses a Monte …

In this paper we present a new Monte Carlo algorithm for finding the solution of Dirichlet
partial differential equations (DPDE). Here, we show the solution of a given DPDE, can be …

Solving systems of linear algebraic equations (SLAE) is a problem often encountered in
fields like engineering, physics, computer science and economics. As the number of …

This paper presents an extension of the classical Ulan-von Neumann Markov chain Monte-
Carlo algorithm for the computation of the matrix inverse. The algorithm presented in this …

In this paper we consider mixed (fast stochastic approximation and deterministic refinement)
algorithms for Matrix Inversion (MI) and Solving Systems of Linear Equations (SLAE). Monte …

The problem of solving systems of linear algebraic equations by parallel Monte Carlo
numerical methods is considered. A parallel Monte Carlo method with relaxation is …