Domain knowledge specification for energy tuning

To overcome the challenges of energy consumption of HPC systems, the European Union Horizon 2020 READEX (Runtime Exploitation of Application Dynamism for Energy-efficient Exascale computing) project uses an online auto-tuning approach to improve energy efficiency of HPC applications. The READEX methodology pre-computes optimal system configurations at design-time, such as the CPU frequency, for instances of program regions and switches at runtime to the configuration given in the tuning model when the region is executed. READEX goes beyond previous approaches by exploiting dynamic changes of a region's characteristics by leveraging region and characteristic specific system configurations. While the tool suite supports an automatic approach, specifying domain knowledge such as the structure and characteristics of the application and application tuning parameters can significantly help to create a more refined tuning model. This paper presents the means available for an application expert to provide domain knowledge and presents tuning results for some benchmarks.Web of Science316art. no. E465

Domain Knowledge Specification for Energy Tuning

The European Horizon 2020 project READEX is developing a tool suite for dynamic energy tuning of HPC applications. While the tool suite supports an automatic approach, domain knowledge can significantly help in the analysis and the runtime tuning phase. This paper presents the means available in READEX for the application expert to provide his expert knowledge to the tool suite

Instabilités 3D de Convection Thermocapillaire en Zone-Flottante

We study numerically the stability, with respect to 3D perturbations, of the 2D flow of a laterally heated liquid maintained thanks to capillarity between two coaxial isothermal rods. The numerical solutions are calculated with spectral collocation method. Stationary flows are obtained with Newton method and their stability is determined through an Arnoldi method. The study has been performed over a large range of Prandtl number values, from 0.001 to 100 with an aspect ration equal to 2. We analyze the destabilization mechanism through the perturbation energy growth rate. A new tool, the adjoint system, allows us to localize the most sensitive regions of the flow with respect to impulse perturbations. The most sensitive structures of the 2D stationary flows are identified. The 3D structure of weakly non linear flows has also been described.Nous étudions numériquement la stabilité vis-à-vis de perturbations 3D d'un écoulement 2D d'un liquide maintenu par capillarité entre deux barreaux cylindriques coaxiaux isothermes et soumis à un flux thermique latéral. Les solutions numériques sont obtenues par méthode de collocation spectrale. Les écoulements stationnaires sont obtenus par méthode de Newton et une méthode d'Arnoldi est utilisée pour l'étude de la stabilité linéaire. La recherche a été menée sur une large gamme de nombres de Prandtl, allant de 0.001 à 100 et pour un rapport d'aspect égal à 2. Le mécanisme de déstabilisation est analysé en observant le taux de croissance de l'énergie de la perturbation. L'utilisation d'un nouvel outil d'analyse, le système adjoint, permet d'identifier les zones sensibles de l'écoulement à des perturbations impulsionnelles. La localisation des zones sensibles permet d'identifier les structures sensibles des écoulements stationnaires 2D. La structure d'écoulements 3D faiblement non linéaires a aussi été décrite

Instabilités 3D de convection thermocapillaire en zone-flottante

Nous étudions numériquement la stabilité d'un écoulement 2D en zone-flottante vis-à-vis de perturbations 3D. La zone- flottante est une partie liquide mantenue par capillarité entre deux barreaux cylindriques coaxiaux isothermes et est soumise à un flux thermique latéral dont le profil est fixe. Sa surface libre est ici considérée comme plane et indéformable. Les solutions numériques sont obtenues par méthode de collocation spectrale. Les écoulements stationnaires sont obtenus par méthode de Newton et une méthode d'Arnoldi est utilisée pour l'étude de la stabilité linéaire. La recherche a été menée sur une large gamme de nombres de Prandtl (Pr), allant de 0.001 à 100. Le mode stabilisant est le mode 2 aux faibles Pr et le mode 1 pour les grands Pr. Le mécanisme de déstabilisation est analysé en observant le taux de croissance de l'énergie de la perturbation, mettant en évidence le caractère hydrodynamique de la perturbation aux faibles Pr et hydrothermal aux grands Pr. L'utilisation d'un nouvel outil d'analyse, le système adjoint, permet d'identifier les zones sensibles de l'écoulement à des perturbations impulsionnelles. Cet outil a été utilisé pour étudier les perturbations bidimensionnelles. La localisation des zones sensibles permet d'identifier des structures dans l'écoulement qui, à bas Pr, répondent au critère de Fjørtøft. Cependant ce critère ne s'applique, comme tous les critères de stabilité, qu'à des écoulements non visqueux. A hauts Pr, le lieu sensible à une perturbation thermique se situe dans les zones de fort gradient thermique sur la surface libre, proche des fronts solides. La structure d'écoulements 3D faiblements non linéaires a aussi été décrite.We study numerically the stability of the 2D flow in floating-zone with respect to 3D perturbations. The floating-zone is a liquid bridge maintained thanks to capillarity between two coaxial isothermal rods and is laterally heated. The free surface is straight and non-deformable. The numerical solutions are calculated with spectral collocation method. Stationary flows are obtained with Newton method and their stability is determined through an Arnoldi method. The study has been performed over a large range of Prandtl (Pr) number values, from 0.001 to 100. The mode 2 is the most dangerous at low Pr whereas the mode 1 is the most dangerous at high Pr. We analyze the destabilisation mechanism through the perturbation energy growth rate. It appears that the perturbation is hydrodynamical at low Pr and hydrothermal at high Pr. A new tool, the adjoint system, allows us to localize the most sensitive regions of the flow with respect to impulse perturbations. It was used to study the 2D stationary flows. The low Pr stationary flow structure in the most sensitive regions satisfies the Fjørtøft stability criteria. Nevertheless, this criteria is, like the other stability criteria, only for inviscid fluids. For high Pr, the most sensitive region to temperature disturbance is located on the free surface, near the walls where thermal gradients is strong. The 3D structure of weakly non linear flows has also been described.ORSAY-PARIS 11-BU Sciences (914712101) / SudocNANCY/VANDOEUVRE-INPL (545472102) / SudocSudocFranceF

Cross-architecture Kalman filter benchmarks on modern hardware platforms

The 2020 upgrade of the LHCb detector will vastly increase the rate of collisions the online system needs to process in software in order to filter events in real-time. 30 million collisions per second will pass through a selection chain where each step is executed conditional to its prior acceptance.The Kalman filter is a process of the event reconstruction that, due to its time characteristics and early execution in the selection chain, consumes 40% of the whole reconstruction time in the current trigger software. This makes it a time-critical component as the LHCb trigger evolves into a full software trigger in the upgrade.The algorithm Cross Kalman allows performance tests across a variety of architectures, including multi and many-core platforms, and has been successfully integrated and validated in the LHCb codebase. Since its inception, new hardware architectures have become available exposing features that require fine-grained tuning in order to fully utilize their resources.In this paper we present performance benchmarks and explore the Intel(R) Skylake and Intel(R) Knights Landing architectures in depth. We determine the performance gain over previous architectures and show that the efficiency of our implementation is close to the maximum attainable given the mathematical formulation of our problem

The READEX formalism for automatic tuning for energy efficiency

Energy efficiency is an important aspect of future exascale systems, mainly due to rising energy cost. Although High performance computing (HPC) applications are compute centric, they still exhibit varying computational characteristics in different regions of the program, such as compute-, memory-, and I/O-bound code regions. Some of today’s clusters already offer mechanisms to adjust the system to the resource requirements of an application, e.g., by controlling the CPU frequency. However, manually tuning for improved energy efficiency is a tedious and painstaking task that is often neglected by application developers. The European Union’s Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing) aims at developing a tools-aided approach for improved energy efficiency of current and future HPC applications. To reach this goal, the READEX project combines technologies from two ends of the compute spectrum, embedded systems and HPC, constituting a split design-time/runtime methodology. From the HPC domain, the Periscope Tuning Framework (PTF) is extended to perform dynamic auto-tuning of fine-grained application regions using the systems scenario methodology, which was originally developed for improving the energy efficiency in embedded systems. This paper introduces the concepts of the READEX project, its envisioned implementation, and preliminary results that demonstrate the feasibility of this approach