A Reinforcement Learning Environment for Polyhedral Optimizations

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A Reinforcement Learning Environment for Polyhedral Optimizations

28 April 2021

Alexander Brauckmann

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Papers citing "A Reinforcement Learning Environment for Polyhedral Optimizations"

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Title
A Deep Learning Based Cost Model for Automatic Code Optimization Riyadh Baghdadi Massinissa Merouani Mohamed-Hicham Leghettas K. Abdous T. Arbaoui K. Benatchba Saman P. Amarasinghe 71 71 0 11 Apr 2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework Mircea Trofin Yundi Qian E. Brevdo Zinan Lin K. Choromanski Didong Li 75 65 0 13 Jan 2021
Static Neural Compiler Optimization via Deep Reinforcement Learning Rahim Mammadli Ali Jannesari F. Wolf 53 31 0 20 Aug 2020
ProGraML: Graph-based Deep Learning for Program Optimization and Analysis Chris Cummins Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Hugh Leather 147 57 0 23 Mar 2020
NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning Ameer Haj-Ali Nesreen Ahmed Theodore L. Willke Sophia Shao Krste Asanović Ion Stoica 50 101 0 20 Sep 2019
Machine Learning in Compiler Optimisation Zheng Wang Michael F. P. O'Boyle VLM 51 77 0 09 May 2018
Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code Riyadh Baghdadi Jessica Ray Malek Ben Romdhane Emanuele Del Sozzo Abdurrahman Akkas Yunming Zhang Patricia Suriana Shoaib Kamil Saman P. Amarasinghe 50 259 0 27 Apr 2018
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions Nicolas Vasilache O. Zinenko Theodoros Theodoridis Priya Goyal Zach DeVito William S. Moses Sven Verdoolaege Andrew Adams Albert Cohen 74 436 0 13 Feb 2018
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 223 5,085 0 05 Jun 2016