Identifying compiler options to minimize energy consumption for embedded platforms

Abstract

This paper presents an analysis of the energy consumption of anextensive number of the optimizations a modern compiler can perform. Using GCC as a test case, we evaluate a set of 10 carefully selected benchmarks for 5 different embedded platforms. A fractional factorial design is used to systematically explore the large optimization space (282 possible combinations), while still accurately determining the effects of optimizations and optimization combinations. Hardware power measurements on each platform are taken to ensure all architectural effects on the energy consumption are captured. We show that fractional factorial design can find more optimal combinations than relying on built-in compiler settings. We explore the relationship between run-time and energy consumption, and identify scenarios where they are and are not correlated. A further conclusion of this study is the structure of the benchmark has a larger effect than the hardware architecture on whether the optimization will be effective, and that no single optimization is universally beneficial for execution time or energy consumption.