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The primary goal of the EuroHPC JU project SCALABLE is to develop an industrial Lattice Boltzmann Method (LBM)-based computational fluid dynamics (CFD) solver capable of exploiting current and future extreme scale architectures, expanding current capabilities of existing industrial LBM solvers by at least two orders of magnitude in terms of processor cores and lattice cells, while preserving its accessibility from both the end-user and software developer's point of view. This is accomplished by transferring technology and knowledge between an academic code (waLBerla) and an industrial code (LaBS). This paper briefly introduces the characteristics and main features of both software packages involved in the process. We also highlight some of the performance achievements in scales of up to tens of thousand of cores presented on one academic and one industrial benchmark case.

The diversity of the structures recently observed in protoplanetary discs (PPDs) with the new generation of high-resolution instruments have made more acute the challenging questions that planet-formation models must answer. The challenge is in the theoretical side but also in the numerical one with the need to significantly improve the performances of the codes and to stretch the limit of PPD simulations. Multi-physics, fast, accurate, high-resolution, modular, and reliable 3D codes are needed to explore the mechanisms at work in PPDs and to try explaining the observed features. We present RoSSBi3D the 3D extension of the 2D code Rotating-System Simulations for Bi-fluids (RoSSBi) which was specifically developed to study the evolution of PPDs. This is a new code, even if based on the 2D version, that we describe in detail explaining its architecture and specificity but also its performances against test cases. This grid-based, FORTRAN code solves the fully compressible inviscid continuity, Euler and energy conservation equations for an ideal gas in non-homentropic conditions and for pressureless particles in a fluid approximation. It is a finite volume code which is second order in time and accounts for discontinuities thanks to an exact Riemann solver. The spatial scheme accounts for the equilibrium solution and is improved thanks to parabolic interpolation. The code is developed in 3D and structured for high-performance parallelism. The optimised version of the code works on high-performance computers with excellent scalability. We checked its reliability against a 2D analogue of the sod shock tube test and a series of tests. We release this code under the terms of the CeCILL2 Licence and make it publicly available., Comment: 13 pages, 10 figures

This paper defines a methodology for the oracle selection of the monitors and knobs to use to configure an HPC system running a scientific application while satisfying the application's requirements and not violating any system constraints. This methodology relies on a heuristic correlation analysis between requirements, monitors and knobs to determine the minimum subset of monitors to observe and knobs to explore, to determine the optimal system configuration for the HPC application. At the end of this analysis, we reduce an 11-dimensional space to a 3-dimensional space for monitors and a 6-dimensional space to a 3-dimensional space for knobs. This reduction shows the potential and highlights the need for a realistic methodology to help identify such minimum set of monitors and knobs.

Power consumption is a critical consideration in high performance computing systems and it is becoming the limiting factor to build and operate Petascale and Exascale systems. When studying the power consumption of existing systems running HPC workloads, we find that power, energy and performance are closely related which leads to the possibility to optimize energy consumption without sacrificing (much or at all) the performance. In this paper, we propose a HPC system running with a GNU/Linux OS and a Real Time Resource Manager (RTRM) that is aware and monitors the healthy of the platform. On the system, an application for disaster management runs. The application can run with different QoS depending on the situation. We defined two main situations. Normal execution, when there is no risk of a disaster, even though we still have to run the system to look ahead in the near future if the situation changes suddenly. In the second scenario, the possibilities for a disaster are very high. Then the allocation of more resources for improving the precision and the human decision has to be taken into account. The paper shows that at design time, it is possible to describe different optimal points that are going to be used at runtime by the RTOS with the application. This environment helps to the system that must run 24/7 in saving energy with the trade-off of losing precision. The paper shows a model execution which can improve the precision of results by 65% in average by increasing the number of iterations from 1e3 to 1e4. This also produces one order of magnitude longer execution time which leads to the need to use a multi-node solution. The optimal trade-off between precision vs. execution time is computed by the RTOS with the time overhead less than 10% against a native execution., Comment: Presented at HIP3ES, 2015 (arXiv: 1501.03064)

Proceedings of the Workshop on High Performance Energy Efficient Embedded Systems (HIP3ES) 2015. Amsterdam, January 21st. Collocated with HIPEAC 2015 Conference.