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Code for "Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP", which appeared at SOSP 2021

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Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP

This repository contains the source code implementation of the SOSP paper "Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP".

Directory Structure

Code in this repository is organized by allocation problem type.

  • cluster_scheduling contains code for the cluster scheduling problem formulations (max-min fairness, proportional fairness, minimize makespan).

  • load_balancing contains code for the load balancing problem formulation.

  • traffic_engineering contains code for the traffic engineering problem formulations (both maximum total flow and maximum concurrent flow).

Getting Started

For detailed instructions on how to reproduce results from the SOSP paper, see EXPERIMENTS.md.

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Code for "Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP", which appeared at SOSP 2021

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