Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization

no code implementations • 28 Mar 2024 • Teodor V. Marinov, Alekh Agarwal, Mircea Trofin

This work studies a Reinforcement Learning (RL) problem in which we are given a set of trajectories collected with K baseline policies.

Compiler Optimization Imitation Learning +1

The Next 700 ML-Enabled Compiler Optimizations

1 code implementation • 17 Nov 2023 • S. VenkataKeerthy, Siddharth Jain, Umesh Kalvakuntla, Pranav Sai Gorantla, Rajiv Shailesh Chitale, Eugene Brevdo, Albert Cohen, Mircea Trofin, Ramakrishna Upadrasta

There is a growing interest in enhancing compiler optimizations with ML models, yet interactions between compilers and ML frameworks remain challenging.

MLGO: a Machine Learning Guided Compiler Optimizations Framework

1 code implementation • 13 Jan 2021 • Mircea Trofin, Yundi Qian, Eugene Brevdo, Zinan Lin, Krzysztof Choromanski, David Li

Leveraging machine-learning (ML) techniques for compiler optimizations has been widely studied and explored in academia.

BIG-bench Machine Learning