Towards a holistic approach to auto-parallelization: integrating profile-driven parallelism detection and machine-learning based mapping

@inproceedings{Tournavitis2009TowardsAH,
  title={Towards a holistic approach to auto-parallelization: integrating profile-driven parallelism detection and machine-learning based mapping},
  author={Georgios Tournavitis and Zheng Wang and Bj{\"o}rn Franke and Michael F. P. O'Boyle},
  booktitle={PLDI},
  year={2009}
}
Compiler-based auto-parallelization is a much studied area, yet has still not found wide-spread application. This is largely due to the poor exploitation of application parallelism, subsequently resulting in performance levels far below those which a skilled expert programmer could achieve. We have identified two weaknesses in traditional parallelizing compilers and propose a novel, integrated approach, resulting in significant performance improvements of the generated parallel code. Using… CONTINUE READING
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