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High performance calculation is increasingly used within society. Previouslyreserved for an elite, based on large computing and storage infrastructures, itis now a core module for many companies. Indeed, high performance calculationmakes it possible to design and optimize many elements for a limited cost,compared to the production of prototypes or tests in situ. It is also widelyused in big data and artificial intelligence.It seems essential to ask abouttheenvironmental impact of these digital practices. A number of actions havealready been initiated in this community: GREEN500; European CoCeco-responsibility label for Data centres... but these actions generally lookat specific or even idealised situations and/or software.The softwarequalification process in the field of high performance calculation consists inlooking at the scalability of the software. The originality of this study is tofocus on energy scalability (calculation return time depending on the powerconsumed), by considering several architectures (three TOP500 machines and alaboratory cluster).The energy cost of an example calculation could beestimated, which shows that the most efficient machine in terms of calculationtime is not necessarily the most energy efficient, and depending on the numberof cores/processes chosen, it is not always the same architecture that is themost energy-efficient. It was therefore possible to show that the longer theuser is prepared to wait, the less energy is used by the calculation.

High performance computing and energy efficiency: focus on OpenFOAM