On Scaling Modes and Balancing Stochastic, Discretization, and Modeling Error

Abstract:

We consider accuracy-cost tradeoffs and the problem of finding Pareto optimal configurations for stochastic forward and inverse problems. As the target accuracy is changed, we should use different physical models, stochastic models, discretizations, and solution algorithms. In this spectrum, we see different scientifically-relevant scaling modes, thus different opportunities and limitations on parallel computers and emerging architectures.