PPAM 2019: Parallel Processing and Applied Mathematics. Lecture Notes in Computer Science
This volume comprises the proceedings of the 13th International Conference on Parallel Processing and Applied Mathematics (PPAM 2019), which was held inBiałystok, Poland, September 8–11, 2019. It was organized by the Department of Computer and Information Science of the Częstochowa University of Technology together with Białystok University of Technology, under the patronage of the Committee of Informatics of the Polish Academy of Sciences, in technical cooperation with the IEEE Computer Society and IEEE Computational Intelligence Society. The main organizer was Roman Wyrzykowski.PPAM is a biennial conference. 12 previous events have been held in different places in Poland since 1994, when the first PPAM took place in Częstochowa. Thus, the event in Białystok was an opportunity to celebrate the 25th anniversary of PPAM. The proceedings of the last nine conferences have been published by Springer in theLecture Notes in Computer Science series (Nałęczów, 2001, vol. 2328; Częstochowa,2003, vol. 3019; Poznań, 2005, vol. 3911; Gdańsk, 2007, vol. 4967; Wrocław, 2009, vols. 6067 and 6068; Toruń, 2011, vols. 7203 and 7204; Warsaw, 2013, vols. 8384 and8385; Kraków, 2015, vols. 9573 and 9574; and Lublin, 2017, vols. 10777 and 10778). The PPAM conferences have become an international forum for the exchange of the ideas between researchers involved in parallel and distributed computing, including theory and applications, as well as applied and computational mathematics. The focus of PPAM 2019 was on models, algorithms, and software tools that facilitate the efficient and convenient utilization of modern parallel and distributed computing architectures, as well as on large-scale applications, including artificial intelligence and machine learning problems. This meeting gathered more than 170 participants from 26 countries. A strict refereeing process resulted in the acceptance of 91 contributed papers for publication in these conference proceedings. For regular tracks of the conference, 41 papers were selected from 89 submissions, thus resulting in an acceptance rate of about 46%. The regular tracks covered important fields of parallel/distributed/cloud computing and applied mathematics.
Classical molecular dynamics (MD) calculations represent a significant part of utilization time of high performance computing systems. As usual, efficiency of such calculations is based on an interplay of software and hardware that are nowadays moving to hybrid GPU-based technologies. Several well-developed MD packages focused on GPUs differ both in their data management capabilities and in performance. In this paper, we present our results for the porting of the CUDA backend of LAMMPS to ROCm HIP that shows considerable benefits for AMD GPUs comparatively to the existing OpenCL backend. We consider the efficiency of solving the same physical models using different software and hardware combinations. We analyze the performance of LAMMPS, HOOMD, GROMACS and OpenMM MD packages with different GPU back-ends on modern Nvidia Volta and AMD Vega20 GPUs.