  Using a realistic molecular catalyst system, we conduct scaling studies of ab
initio molecular dynamics simulations using the CP2K code on both Intel Xeon
CPU and NVIDIA V100 GPU architectures. We explore using process placement and
affinity to gain additional performance improvements. We also use statistical
methods to understand performance changes in spite of the variability in
runtime for each molecular dynamics timestep. We found ideal conditions for CPU
runs included at least four MPI ranks per node, bound evenly across each
socket, and fully utilizing processing cores with one OpenMP thread per core,
no benefit was shown from reserving cores for the system. The CPU-only
simulations scaled at 70% or more of the ideal scaling up to 10 compute nodes,
after which the returns began to diminish more quickly. Simulations on a single
40-core node with two NVIDIA V100 GPUs for acceleration achieved over 3.7x
speedup compared to the fastest single 36-core node CPU-only version, and
showed 13% speedup over the fastest time we achieved across five CPU-only
nodes.
