The Error-Energy Tradeoff in Molecular and Molecular-Continuum Fluid Simulations

Energy consumption plays a crucial role when designing simulation studies. In this work, we take a step towards modelling the relationship between statistical error and energy consumption for molecular and molecular-continuum flow simulations. After revisiting statistical error analysis and run time complexities for molecular dynamics (MD) simulations, we verify the respective relationships in stand-alone short-range MD simulations. We then extend the analysis to coupled molecular-continuum simulations, including the multi-instance (i.e., MD ensemble averaging) case, and additionally analyse the impact of noise filters. Our findings suggest that Gauss filters can reduce the statistical error to a similar degree as doubling the number of MD instances would. We further use regression to derive an analytical energy consumption model that predicts energy consumption on our HPC-cluster HSUper, to achieve simulation results at a prescribed statistical error (or gain in signal-to-noise ratio, respectively). All simulations were carried out using the MD software ls1 mardyn and the molecular-continuum coupling tool MaMiCo. However, the derived models are easily transferable to other pieces of software and other HPC platforms.