A graph-based model for build optimization sequences: A study of optimization sequence length impacts on code size and speedup

Abstract

Embedded Systems applications have several limitations, one of these limitations is the memory size. Modern compilers provide optimization sequences that reduce the code size, contributing to solve this memory issue. However, the optimization search space is very large, and the same optimization can be applied several times in the same program. Consequently, there is a need to determine the optimization sequence length. Furthermore, sometimes applying optimizations does not result in a significant speedup gain. In this paper, we present an evaluation of optimization sequence lengths, their impact on the code size reduction and speedup increase using a graph-based model to build optimization sequences. The results indicate that is possible to achieve about 15.1% of code size reduction over O0, and also obtain speedups better than O2 optimization level, while Oz achieves 15.5% of code size reduction but cannot reach the speedup of O2 optimization level.