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I was wondering, is it possible to use Artificial Intelligence to make compilers better?

Things I could imagine if it was possible -

  • More specific error messages

  • Improving compiler optimizations, so the compiler could actually understand what you're trying to do, and do it better

If it is possible, are there any research projects on this subject?

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MILEPOST GCC is the first attempt that is practically possible to build a machine learning algorithm that enabled open-source self-tuning production (and research) compiler that has the ability to adapt to any architecture with the help of iterative feedback-directed compilation, machine learning, and collective optimization.

 MILEPOST GCC is currently a part of the community-driven Collective Tuning Initiative (cTuning) to enable self-tuning computing systems based on collaborative open-source R&D infrastructure with unified interfaces and improve the quality and reproducibility of the research on code and architecture optimization. MILEPOST GCC is connected to Collective Optimization Database to collect and reuse profitable optimization cases from the community and predict good optimizations based on a statistical analysis of optimization data. You can refer the following link for more information:

http://ctuning.org/wiki/index.php/CTools:MilepostGCC

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