The construction of a wind power generation center starts by the selection of a suitable wind farm location. The selection includes six factors, namely wind speed, slope, land use, distance from the power lines, distance from the roads, and distance from populated areas which have been integrated into QGIS by weights calculated using the Analytical Hierarchy Process (AHP) approach. As a result of this study, the areas having very high wind potentiality have been identified and a best wind farm location map has been prepared. The map, using the overlay function in GIS, exhibits the most and least suitable areas for the location of wind farms in Morocco. The approach could help identify suitable wind farm locations in other areas using their geographic information.

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Abstract-This paper aims to propose a new massively distributed virtual machine with scalable and efficient parallel computing models for High Performance Computing (HPC). The message passing paradigm of the Processing Units has a significant impact on HPC with high communication cost that penalizes the performance of these models. Accordingly, the proposed micro-services model allows the HPC applications to enhance the processing power with low communication cost. Thus, the model based Micro-services Virtual Processing Units (MsVPUs) cooperate using asynchronous communication mechanism through the Advanced Message Queuing Protocol (AMQP) protocol in order to maintain the scalability of the Single Program Multiple Data (SPMD) applications. Additionally, this mechanism enhances also the efficiency of the model based load balancing service with time optimized load balancing strategy. The proposed virtual machine is tested and validated through an application of fine grained parallel programs for big data classification. Experimental results present reduced execution time compared to the virtual machine based mobile agent's model.