Energy-optimizing source code transformations for OS-driven embedded software

The increasing software content of battery-powered embedded systems has fueled much interest in techniques for developing energy-efficient embedded software. Source code transformations have previously been considered for application software to reduce its energy consumption. For complex embedded software applications, which consist of multiple concurrent processes running with the support of an embedded operating system (OS), it is known that the OS and the application-OS interaction significantly affect energy consumption. However, source code transformations explicitly targeting these effects have not been sufficiently studied. This paper proposes novel transformations for the source code of OS-driven multi-process embedded software programs in order to reduce their energy consumption. The key features of our optimizations are that they span process boundaries, and that they minimize the energy consumed in the execution of OS functions and services-opportunities which are beyond the reach of conventional compiler optimizations and source code transformation techniques. We propose four types of transformations, namely process-level concurrency management, message vectorization, computation migration and inter-process communication mechanism selection. We discuss how to systematically identify opportunities for the proposed transformations and apply them directly to the program source code. We have applied the proposed techniques to several multi-process software benchmark programs, and evaluated their applicability in the context of an embedded system containing an Intel StrongARM processor and embedded Linux OS. Our techniques achieve up to 37.9% (23.8% on an average) energy reduction compared to highly compiler-optimized implementations.