Low power embedded software optimization using symbolic algebra

The market demand for portable multimedia applications has exploded in recent years. Unfortunately for such applications, current compilers and software optimization methods often require designers to do part of the optimization manually. Specifically, the high-level arithmetic optimizations and the use of complex instructions are left to the designers' ingenuity. In this paper, we present a tool flow, SymSoft, that automates the optimization of power-intensive algorithmic constructs using symbolic algebra techniques combined with energy profiling. SymSoft is used to optimize and tune the algorithmic level description of an MPEG Layer III (MP3) audio decoder for the SmartBadge (Maguire et al, 1998) portable embedded system. We show that our tool lowers the number of instructions and memory accesses and thus lowers the system power consumption. The optimized MP3 audio decoder software meets real-time constraints on the SmartBadge system with low energy consumption. Furthermore, the performance improves by a factor of 7.27 and the energy consumption decreases by a factor of 4.45 over the original executable specification.