Identifying Compiler Options to Minimize Energy Consumption for Embedded Platforms

Thispaperpresentsananalysisoftheenergyconsumptionofanextensivenumberoftheoptimizations a modern compiler can perform. Using GCC as a test case, we evaluate a set of 10 carefully selected benchmarksfor5differentembeddedplatforms.Afractionalfactorialdesignisusedtosystematically explore the large optimization space (2 82 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 compilersettings.Weexploretherelationshipbetweenrun-timeandenergyconsumption,andidentify 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.

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