Jafari, Vahid

In the scope of the dtec.bw project hpc.bw, innovative HPC hardware resources were procured to investigate their performance for HSU-relevant compute-intensive software. Benchmarks for different software packages were conducted, and respective results are reported and documented in the following, considering the Intel Xeon architecture used in the HPC cluster HSUper, AMD EPYC 7763 and ARM FX700.

In coupled molecular-continuum flow simulations, molecular dynamics (MD) simulations exhibit thermal fluctuations. Finding a way to minimize the impact of these fluctuations on the CFD solver, e.g. in terms of stability, and to control the corresponding statistical error plays a key role in order to obtain reliable results. In this paper, statistical error analysis is employed for MD simulations to determine the statistical error in flow velocities and the number of MD data samples to bound this error. The corresponding error estimator is augmented by a dynamic ensemble handling approach, which allows to couple a variable number of MD simulation instances to a single CFD solver. The ensemble members can be simulated independently from each other over separate coupling time intervals, enabling a high level of (MPI-based) parallelism. Adding or removing MD simulations to/from the ensemble allows to regulate the error and keep it under a prescribed threshold. All functionality is implemented in the massively parallel macro-micro-coupling tool (MaMiCo). We validate our approach by coupled molecular-continuum Couette flow simulation for liquid argon and provide scalability tests on up to 131.072 cores. The computational overhead for handling the dynamic MD ensemble is found to be rather negligible.