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CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research [article]

Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
<span title="2021-12-22">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We introduce CompilerGym, a set of environments for real world compiler optimization tasks, and a toolkit for exposing new optimization tasks to compiler researchers.  ...  Interest in applying Artificial Intelligence (AI) techniques to compiler optimizations is increasing rapidly, but compiler research has a high entry barrier.  ...  There is a growing body of research that applies AI techniques to compilers optimizations [2] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2109.08267v2">arXiv:2109.08267v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s2a3qrrk7zczflszoeta3ztl7q">fatcat:s2a3qrrk7zczflszoeta3ztl7q</a> </span>
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