Extending adaptive sparse grids for stochastic collocation to hybrid parallel architectures

Abstract

We are developing an adaptive sparse grid library tailored for emerging architectures that will allow the solution of stochastic problems of unprecedented size. This paper gives a brief overview of the problem at hand and presents initial results for a small GPU-based cluster. An outlook on large-scale distributed memory parallelization and our hybrid design approach is also included.