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Workshop: Machine Learning for Systems

On a Foundation Model for Operating Systems

Divyanshu Saxena · Nihal Sharma · Donghyun Kim · Rohit Dwivedula · Jiayi Chen · Chenxi Yang · Sriram Ravula · Zichao Hu · Aditya Akella · Joydeep Biswas · Swarat Chaudhuri · Isil Dillig · Alex Dimakis · Daehyeok Kim · Christopher J. Rossbach


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.

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