Energy consumption is a growing concern. On the verge of Exascale computing, a machine reaching 10^18 operations per seconds, it became a crucial focus. With the multiplication of connected devices per person around the world, reducing the energy consumption of large scale computing system is a mandatory step to address in order to build a sustainable digital society.
Several techniques, that we call leverages, have been developed in order to lower the electrical consumption of computing facilities. It is urgent to embrace energy efficiency as a major concern of our modern computing facilities. Using these leverages is mandatory to better energy efficiency. A lot of leverages are available on large scale computing centers. In spite of their potential gains, users and administrators don't fully use them or don't use them at all to better energy efficiency. Although, using these techniques, alone and combined, could be complicated and counter productive if not wisely used.
This thesis defines and investigates the discovery, understanding and smart usage of leverages available on a large scale data center or supercomputer. We focused on various single leverages. We then combine them to other leverages and propose a generic solution to the dynamic usage of combined leverages. Through numerous energy leverages, we showed that it is possible to use such techniques (alone or combined) to have a consequent energy benefit. Our studies and researches focused on leverages that modulate the energy used by components of supercomputers and data-centers. We studied widely used energy leverages, like shutdown techniques, but also narrowly used techniques such as precision of computation or OpenMP middlewares.
Gratuit
Disciplines