International audienceThe parallelization of numerical simulation algorithms, i.e., their adaptation to parallel processing architectures, is an aim to reach in order to hinder exorbitant execution times. The parallelism has been imposed at the level of processor architectures and graphics cards are now used for general-purpose calculation, also known as " General-Purpose computation on Graphics Processing Unit (GPGPU) ". The clear benefit is the excellent performance over price ratio. Besides hiding the low level programming, software engineering leads to a faster and more secure application development. This paper presents the real interest of using GPU processors to increase performance of larger problems which concern electrical machines simulation. Indeed, we show that our auto-generated code applied to several models allows achieving speedups of the order of 10
Currently, electricity distributors make use of various types of equipment divided into levels of automation. This automation enables the integration of elements such as Intelligent Electronic Devices (IEDs) to the supervision of the distribution electrical system, but there is not an appropriate environment to increase the scale of these elements. In this context, the smart grid comes with specifications that allow adding new elements to the intelligence of the power grid operation. However, the cost of communication is still an impediment to the scalability of the integration of these elements into the current structure. In this paper, we propose a middleware that optimizes the communication of this integration using wireless sensor networks (WSN). The goal is to ensure a gradual integration of new elements taking advantage of the increase in the number of sensor nodes in the network due to the scalability of the system itself. The conversion solutions have been used to allow easy communication between the WSN and the smart grid system, and we also have used data aggregation and compression techniques to increase the lifetime of the wireless sensor network.
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