Probabilistic Iterative Compilation for Source Optimization of Embedded Programs
Naeem Zafar Azeemi · 2006
This paper focuses on source-level code transformation methods for low energy consumption in architectures employing high end processors. Successive energy/cycle cost guarded parametric optimization are applied in proposed iterative compilation environment to evaluate an application expression profile. The optimization is based on a multi-objective function. The constraints of this objective function are formulated using a penalty method; a genetic algorithm finds solutions eventually. The proposed new code transformation methodology determines appropriate parameters for compiler optimization in order to satisfy user constraints on code size, energy, execution time and optimal target architecture usage. The set of experiments presented here characterize the newly introduced approach, while giving an idea about the architecture-aware energy/cycle performance issues. Experimental results show that our approach reduces cache misses by an average of 33% (max. 67%), improves typically energy dissipation up to 23 % and CPU performance up to 80 % for an MPEGdec video algorithm. The approach is general and can easily be integrated in multimedia processor compilers.