Comparative benchmarking of HPC systems for GSS applications: GSS applications in the HPC ecosystem

Abstract

The work undertaken in this paper was done in the Centre of Excellence for Global Systems Science (CoeGSS), an interdisciplinary project, funded by the European Commission. The project provides decision-support in the face of global challenges. It brings together HPC and global systems science. This paper presents a proposition of GSS benchmark with the aim to find the most suitable HPC architecture and the best HPC system which allows to run GSS applications effectively. The GSS provides evidence about global systems challenges, e.g. the network structure of the world economy, energy, water and food supply systems, the global financial system or the global city system, and the scientific community. The outcome of the analysis is defining a benchmark which represents the GSS environment in the best way. Three exemplary challenges were defined as pilot applications: Health Habits, Green Growth and Global Urbanisation extended with additional applications from GSS ecosystem: Iterative proportional fitting (IPF), Data rastering - a preprocessing process converting all vectorial representations of georeferenced data into raster files to be later used as simulation input, Weather Research and Forecasting (WRF) model, CMAQ/CCTM (Community Air Multiscale Quality Modelling System/The CMAQ Chemistry-Transport Mode), CM1 (Cloud Modelling), ABMS (Agent-based Modelling and Simulation), OpenSWPC (An Open-source Seismic Wave Propagation Code). The above list seems to be quite rich and reflects the real GSS world as much as possible, having in mind, for example the real-world applications availability. Additionally, the authors tested new HPC platforms based on Intel® Xeon® Gold 6140, AMD EpycTM, ARM Hi1616 and IBM Power8+. Due to the hardware availability, the testbed consisted of a limited number of nodes. This restricted the ability to provide full tests of scalability for given applications. However, this small number of available computational units (cores) can provide valuable outcome including architecture comparison for different applications based on execution times, TDPs1 and TCO2. These are the basic metrics used for providing a ranking of HPC architectures. Finally, this document is thought to be valuable information for the GSS community for future purposes and analysis to determine their specific demands as well as - in general - to help develop a mature final benchmark set reflecting the GSS environment requirements and specialty. As none of the existing benchmarks is dedicated to the GSS community, the authors decided to create one by calling it a GSS benchmark to serve and help GSS users in their future work.