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I was one of the first researchers to introduce the use of machine learning to optimize an optimizing compiler itself. Compilers typically contain many heuristics to solve hard problems approximately and efficiently. Finding heuristics that perform well on a broad range of applications and processors is one of the most complex tasks faced by compiler writers. My research involves using machine learning techniques to automatically construct compiler optimization heuristics. I have shown that this technique can completely eliminate the human from heuristic design. My research on applying machine learning to compiler optimizations received the NSF CAREER award.
|GPGPU 2018||Committee Member in Organizing Committee within the GPGPU 2018-track|
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