Modern LLVM-based Compiler Autotuning for WCET Optimization

The problem of compiler optimization selection and ordering, known in the literature as compiler autotuning, has been tackled many times for average-case execution time reduction. Optimizing the WCET is becoming a prominent problem for modern hard real-time systems, where the difficulties in accurate WCET estimation hinder the full exploitation of computing platform capabilities. In this article, we propose a novel methodology and a tool based on LLVM for iterative WCET-driven compiler autotuning, which is the first strategy to operate at function-level granularity and to consider not only the selection of optimization passes, but also their ordering. Our findings show that standard optimization levels O0, O1, O2, and O3 are suboptimal when targeting the WCET, and that a per-function selection and ordering of the transformations is necessary. Experimental results show that our approach outperforms the standard optimizations and opens up new directions for future research.