SEA: fast power estimation for micro-architectures

Various approaches for micro-architectural power/energy estimation have been introduced, mainly driven by the need to obtain fast power/energy estimates during early phases of complex SOC designs. In contrast to previous approaches, we study power/energy estimation for highly optimized synthesizable descriptions of microprocessor cores. Under this real-world design scenario, we found, unlike related previous research, that power can hardly be estimated closer than around 15% using an instruction level model. However, we can estimate the energy as close as 5%. Our research has resulted in the SEA framework that estimates energy/power consumed by a software program, taking specific micro-architectural features of the underlying programmable hardware core into consideration. With this high accuracy in energy estimation, we achieve around 5 orders of magnitude faster estimations compared to state-of-the art high-level (RTL) commercial energy/power estimation tool suites. Thus, our framework is capable of reliably estimating the energy/power consumption of future complex SOCs.