Impact of source code optimizations on power consumption of embedded systems

Power consumption is an important constraint in the design of battery-operated embedded systems. Minimizing power dissipation may be handled in terms of hardware or software optimizations. Source code-level optimization techniques have been used as an alternative to achieve low power consumption when programming embedded systems. However these techniques should be analyzed with statistical sound methods in order to reach strong conclusions about their real impact on power consumption. In this work, source code optimizations were applied on a set of representative benchmarks for embedded processors (MiBench) to analyze whether the techniques have or not an effect on power dissipation of a set of microprocessor based platforms. Design of experiments techniques (DOE) and analysis of variance (ANOVA) were used to achieve statistical sound conclusions. Results showed that not all optimizations have a significant effect on power consumption, moreover some techniques depend on the target platform where they are run.