On a Foundation Model for Operating Systems
Abstract
This paper lays down the research agenda for a domain-specific foundation model for operating systems (OSes). Our case for a foundation model revolves around the observations that several OS components such as CPU, memory, and network subsystems are interrelated and that OS traces offer the ideal dataset for a foundation model to grasp the intricacies of diverse OS components and their behavior in varying environments and workloads. We discuss a wide range of possibilities that then arise, from employing foundation models as policy agents to utilizing them as generators and predictors to assist traditional OS control algorithms. Our hope is that this paper spurs further research into OS foundation models and creating the next generation of operating systems for the evolving computing landscape.
Cite
@article{arxiv.2312.07813,
title = {On a Foundation Model for Operating Systems},
author = {Divyanshu Saxena and Nihal Sharma and Donghyun Kim and Rohit Dwivedula and Jiayi Chen and Chenxi Yang and Sriram Ravula and Zichao Hu and Aditya Akella and Sebastian Angel and Joydeep Biswas and Swarat Chaudhuri and Isil Dillig and Alex Dimakis and P. Brighten Godfrey and Daehyeok Kim and Chris Rossbach and Gang Wang},
journal= {arXiv preprint arXiv:2312.07813},
year = {2023}
}
Comments
Machine Learning for Systems Workshop at 37th NeurIPS Conference, 2023, New Orleans, LA, USA