Abstract
Current methodologies for software-level power and energy estimation use a microprocessor's power model combined with specialized tools that profile the program under study. These tools commonly rely on real-time program execution or simulations to gather the information needed, a process that usually requires a full set of real run-time data. This work proposes the use of static code simulation as an alternative to analyze and predict the program's behavior. This, in combination with a microprocessor's power model, allows to estimate power and energy with only a small amount of run-time data. Furthermore, the low execution time of the proposed method allows for its use as in iterative power optimizers. We present results obtained for a set of representative benchmark programs applied ran on a PowerPC 603e microprocessor. Power and energy estimates with mean absolute errors below 7% and 15%, respectively, are reported for the analyzed test cases.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
