Profile Guided Optimization without Profiles: A Machine Learning Approach

24 December 2021

Papers citing "Profile Guided Optimization without Profiles: A Machine Learning Approach"

8 / 8 papers shown

Title
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research Chris Cummins Bram Wasti Jiadong Guo Brandon Cui Jason Ansel ... Jia-Wei Liu O. Teytaud Benoit Steiner Yuandong Tian Hugh Leather 49 72 0 17 Sep 2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework Mircea Trofin Yundi Qian E. Brevdo Zinan Lin K. Choromanski Didong Li 60 64 0 13 Jan 2021
Ansor: Generating High-Performance Tensor Programs for Deep Learning Lianmin Zheng Chengfan Jia Minmin Sun Zhao Wu Cody Hao Yu ... Jun Yang Danyang Zhuo Koushik Sen Joseph E. Gonzalez Ion Stoica 126 398 0 11 Jun 2020
NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning Ameer Haj-Ali Nesreen Ahmed Theodore L. Willke Sophia Shao Krste Asanović Ion Stoica 47 101 0 20 Sep 2019
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks Charith Mendis Alex Renda Saman P. Amarasinghe Michael Carbin 37 153 0 21 Aug 2018
Neural Code Comprehension: A Learnable Representation of Code Semantics Tal Ben-Nun Alice Shoshana Jakobovits Torsten Hoefler 48 242 0 19 Jun 2018
A Survey on Compiler Autotuning using Machine Learning Amir H. Ashouri W. Killian John Cavazos G. Palermo Cristina Silvano 63 200 0 13 Jan 2018
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 769 38,735 0 09 Mar 2016