Performance of MD-Algorithms on Hybrid Systems-on-Chip Nvidia Tegra K1 & X1

• Published in: Supercomputing Vol. 687; pp. 199 - 211
• Main Authors: Nikolskii, Vsevolod, Vecher, Vyacheslav, Stegailov, Vladimir
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: ARM; GPU; Kepler; LAMMPS; Maxwell; Roofline
• ISBN: 3319556681; 9783319556680
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-319-55669-7_16

In this paper we consider the efficiency of hybrid systems-on-a-chip for high-performance calculations. Firstly, we build Roofline performance models for the systems considered using Empirical Roofline Toolkit and compare the results with the theoretical estimates. Secondly, we use LAMMPS as an example of the molecular dynamic package to demonstrate its performance and efficiency in various configurations running on Nvidia Tegra K1 & X1. Following the Roofline approach, we attempt to distinguish compute-bound and memory-bound conditions for the MD algorithm using the Lennard-Jones liquid model. The results are discussed in the context of the LAMMPS performance on Intel Xeon CPUs and the Nvidia Tesla K80 GPU.