Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

International audienceSince the recent advance in microprocessor design, the optimization of computing software becomes more and more technical. One of the difficulties is to transform sequential algorithms into parallel ones. A possible solution is the task-based design. In this approach, it is possible to describe the parallelization possibilities of the algorithm automatically. The task-based design is also a good strategy to optimize software in an incremental way. The objective of this paper is to describe a practical experience of a task-based parallelization of a Discontinuous Galerkin method in the context of electromagnetic simulations. The task-based description is managed by the StarPU runtime. Additional acceleration is obtained by OpenCL

Algorithmic Differentiation for an effcient CFD solver

We illustrate the benefits of Algorithmic Differentiation (AD) for the development of aerodynamic flow simulation software. In refining the architecture of the elsA CFD solver, developed jointly by ONERA and Safran, we consider AD as a key technology to cut development costs of some derivatives of interest, namely the tangent, adjoint, and Jacobian. We first recall the mathematical background of CFD applications which involve these derivatives. Then, we briefly present the software architecture of elsA (Cambier et al. [12]) and the design choices which give it its HPC capability while highlighting how these choices strongly constrain the applicability of AD. To meet our efficiency requirements, we select the Source-Transformation approach to AD through the Tapenade tool which is justified by a series of experiments and benchmarks. Finally, we present results on large scale configurations

Étude d’une stratégie d’effacement de la consommation électrique de pointe dans le bâtiment par l’application de la programmation dynamique

International audienceIn France, 70% of new buildings are heated with electrical devices causing very high peak loads in winter. In this publication, we study the possibility to shift a part of electricity consumption for heating using the thermal mass of the building. Dynamic programming has been used to minimize a cost function, accounting for a high peak electricity tariff, under constraints related to comfort (minimal temperature, maximal temperature variation) and the maximum heating power. The proposed energy management consists in over-heating the building in the hours before the peak knowing in advance the weather, occupation and internal gains for the next 7 days. The method has been tested on a case study corresponding to a single family house with two performance levels: high (new construction, and poorly insulated old house.En France, 70% des bâtiments neufs sont chauffés avec des équipements électriques, entrainant des pointes de consommation hivernales très importantes. Dans cette publication, nous étudions la possibilité de décaler une partie de la consommation du chauffage en utilisant la masse thermique du bâtiment. La méthode de programmation dynamique a été utilisée pour minimiser une fonction de coût, tenant compte d’une tarification différenciée (heures creuses, pleines et pointes), sous des contraintes associées au confort (température minimale, variation de température maîtrisée) et à la puissance maximale de l’équipement. La régulation proposée surchauffe le bâtiment les heures précédant la pointe, connaissant à l’avance les conditions climatiques, l’occupation et les gains internes pour les 7 prochains jours. Une étude de cas a été menée sur une maison individuelle, en considérant deux configurations : maison neuve performante et maison ancienne non isolée

Application of dynamic programming to study load shifting in buildings

International audienceBeing increasingly insulated, new buildings are more and more sensitive to variations of solar and internal gains. Due to an important use of electrical heating systems, especially in housing, France is facing a growing problem of peak load on its electricity grid. Controlling the heating system often constitutes an efficient solution to shift heating loads while maintaining indoor comfort. The proposed energy management is a predictive set of optimal commands issued from a dynamic programming optimization knowing in advance the weather, occupancy and internal gains for the next 7 days. This method is tested on a low energy house situated in France with an annual heating demand of 14 kWh/m2. In this paper, load shifting according to utility rate incentives and carbon emissions are studied. The importance of building models as well as envelope insulation and thermal mass on energy management results is shown

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

International audienceSince the recent advance in microprocessor design, the optimization of computing software becomes more and more technical. One of the difficulties is to transform sequential algorithms into parallel ones. A possible solution is the task-based design. In this approach, it is possible to describe the parallelization possibilities of the algorithm automatically. The task-based design is also a good strategy to optimize software in an incremental way. The objective of this paper is to describe a practical experience of a task-based parallelization of a Discontinuous Galerkin method in the context of electromagnetic simulations. The task-based description is managed by the StarPU runtime. Additional acceleration is obtained by OpenCL

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Since the recent advance in microprocessor design, the optimization of computing software becomes more and more technical. One of the difficulties is to transform sequential algorithms into parallel ones. A possible solution is the task-based design. In this approach, it is possible to describe the parallelization possibilities of the algorithm automatically. The task-based design is also a good strategy to optimize software in an incremental way. The objective of this paper is to describe a practical experience of a task-based parallelization of a Discontinuous Galerkin method in the context of electromagnetic simulations. The task-based description is managed by the StarPU runtime. Additional acceleration is obtained by OpenCL

Investigating the ability of various building in handling load shiftings

Abstract—In modern constructions, several insulation configurations and technologies exist for residential buildings. Therefore, during renovation of these buildings, various investments can be considered. In this article, we consider building equipped with electric heaters. The contribution of this article is a method for evaluating the ability of each configuration to keep the inhabitants comfortable during load shifting periods. This question is of importance in the relationship, and then in the price setting, between the user (inhabitant of the house) and the energy provider who uses these load shifting periods to optimize his production on a regional or national scale. We proceed as follows: an optimization method is used to compute, in a dynamical context, the best heating strategy. The weather conditions and the comfort constraints define (through the solution of the dynamical optimization problem) the actual ability of the building to guarantee a satisfying comfort during load shifting periods independently on the regulation strategy. The conclusion is that for poorly insulated building ( ≈ 58 % of the french stock) it is impossible to achieve load shifting superior to 20 minutes in winter time, even when using advanced regulation strategy of the heating system. I

Mesure de l'indice de microfissuration du béton par traitement d'images

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