John Cavazos

Not registered as user yet

Name: John Cavazos

Bio: 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.

Affiliation: University of Delaware

Personal website:


GPGPU 2018Committee Member in Organizing Committee within the GPGPU 2018-track
GPGPU-9Committee Member in Organizing Committee within the GPGPU-9-track
PLDI 2015Committee Member in External Review Committee within the Research Papers-track
SPLASH 2014Committee Member in External Review Committee within the OOPSLA-track
SPLASH 2012Author of Mitigating the compiler optimization phase-ordering problem using machine learning within the OOPSLA Research Papers-track