Monte Carlo methods are widely used for approximating complicated, multidimensional integrals Bayesian inference. Population (PMC) is an important class of methods, which adapts a population proposals to generate weighted samples that approximate the target distribution. When distribution expensive evaluate, PMC may encounter computational limitations since it requires many evaluations To addre...

Monte Carlo applications are widely perceived as computationally intensive but naturally parallel. Therefore, they can be effectively executed on the grid using the dynamic bag-of-work model. This paper concentrates on analyzing the characteristics of large-scale Monte Carlo computation for grid computing. Based on these analyses, we improve the efficiency of the subtask-scheduling scheme by im...