The University of Tulsa
The tremendous increase in the complexity of graphics models have been supported by a similar increase in the computational resources available in Graphics Processing Units (GPUs). The inherently high parallelism of such systems has led to a significant increase in power dissipation, thereby necessitating expensive cooling solutions. In addition, general purpose processing on such specialized architectures poses new problems yet opens avenues for power optimizations at the architectural level. In this paper, the authors present a modular architectural power estimation framework that will help GPU designers with early power efficiency exploration.