Efficiency of the Tegra K1 and X1 systems-on-chip for classical molecular dynamics

Further development of high performance computing hardware and software is focused on energy and parallel efficiency that are both crucial for future exascale level of supercomputer performance. Real applications tests as well as small-scale benchmarks of new architectures are important for the choice of the best development strategies. ARM CPUs and NVIDIA GPUs are among the most energy efficient hardware. Recently both architectures have been combined in the NVIDIA Tegra systems-on-chip. In this work we benchmark the development boards with Tegra K1 and X1 both with the Roofline model toolkit as well as with different classical molecular dynamics algorithms implemented in LAMMPS. We consider the utilization of the single and double peak floating-point performance and the power and energy consumption of the corresponding Cortex-A15, Cortex-A57, Kepler and Maxwell cores.