  Due to their highly parallel multi-cores architecture, GPUs are being
increasingly used in a wide range of computationally intensive applications.
Compared to CPUs, GPUs can achieve higher performances at accelerating the
programs' execution in an energy-efficient way. Therefore GPGPU computing is
useful for high performance computing applications and in many scientific
research fields. In order to bring further performance improvements, GPU
clusters are increasingly adopted. The energy consumed by GPUs cannot be
neglected. Therefore, an energy-efficient time scheduling of the programs that
are going to be executed by the parallel GPUs based on their deadline as well
as the assigned priorities could be deployed to face their energetic avidity.
For this reason, we present in this paper a model enabling the measure of the
power consumption and the time execution of some elementary operations running
on a single GPU using a new developed energy measurement protocol.
Consequently, using our methodology, energy needs of a program could be
predicted, allowing a better task scheduling.
