Selecting the right compiler optimizations is known to have huge impacts on application performance. However, optimization options constantly increase and their effect is highly dependent on the specific program, preventing a manual approach.

This paper by Akamas Research and Politecnico di Milano was presented at the 2020 ACM International Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES).

Highlights:

  • How traditional characterization techniques based on workload metrics may mislead the compiler auto-tuning task;
  • A novel methodology and algorithm to optimize compiler flags by using Collaborative Filtering techniques already validated in recommender;
  • This new autotuning algorithm outperforms previously proposed techniques, thus representing the new state-of-the-art.