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Energy consumption has become one of the greatest challenges in the field of high performance computing (HPC). The energy cost produced by supercomputers during the lifetime of the installation is similar to acquisition. Thus, besides its impact on the environment, energy is a limiting factor for the HPC. Our research aims to reduce the energy consumption of computer systems to run parallel HPC applications. In this article we analyse the possible influence on the energy consumption of parallel programming paradigms of shared memory (OpenMP) and message passing (MPI), and the behaviour of systems at different clock frequencies of CPUs. The results show that the programming model has a major impact on the energy consumption of computer systems. It was found that the impact of reduced clock frequencies on the execution time, energy efficiency, and maximum power consumption depends not only on the type of application but also on its implementation in a specific programming model. We believe that another criteria to consider when choosing a parallel programming model is the impact on energy consumption.