Tools for assessing and optimizing the energy requirements of high performance scientific computing software

Score-P is a measurement infrastructure originally designed for the analysis and optimization of the performance of HPC codes. Recent extensions of Score-P and its associated tools now also allow the investigation of energy-related properties and support the user in the implementation of corresponding improvements. Since it would be counterproductive to completely ignore performance issues in this connection, the focus should not be laid exclusively on energy. We therefore aim to optimize software with respect to an objective function that takes into account energy and run time. 1 The basic problem and static tuning approaches for its solution To satisfy the demands from the scientific computing community, the established high performance computing centers provide a large amount of massively parallel computing hardware. One of the main challenges that the HPC centers have to face today is the cost of the energy required to operate this hardware which already amounts to about 30% of the total cost of ownership of a current HPC system, with a rising tendency [1]. Thus HPC centers will likely force their users to optimize their software with respect to its energy requirements. In this paper, we provide a brief survey of recent developments in this area. An early strategy implemented by certain HPC centers [2] was to set the default CPU clock frequency of their systems to a value much lower than the highest possible frequency. This concept is based on the fact that the total power required by a compute job can be additively decomposed into a static ∗Corresponding author: e-mail [email protected] 1 ar X iv :1 60 5. 01 25 3v 1 [ cs .S E ] 4 M ay 2 01 6