Pre-characterization free, efficient power/performance analysis of embedded and general purpose software applications

This paper presents a novel approach for an efficient, yet accurate estimation technique for power consumption and performance of embedded and general purpose applications. Our approach is adaptive in nature and is based on detecting sections of code characterized by high temporal locality (also called hotspots) in the execution profile of the benchmark being executed on a target processor. The technique itself is architecture and input independent and can be used for both embedded, as well as for general purpose processors. We have implemented a hybrid simulation engine which can significantly shorten the simulation time by using on-the-fly profiling for critical sections of the code and by reusing this information during power/performance estimation for the rest of the code. By using this strategy, we were able to achieve up to 20X better accuracy compared to a flat, non-adaptive sampling scheme and a simulation speed-up of up to 11.84X with a maximum error of 1.03% for performance and 1.92% for total energy on a wide variety of media and general purpose applications.