https://github.com/MachineLearningSystem/Muri

Artifacts for our SIGCOMM'22 paper Muri
https://github.com/MachineLearningSystem/Muri

Last synced: about 1 month ago
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Artifacts for our SIGCOMM'22 paper Muri

• Host: GitHub
• URL: https://github.com/MachineLearningSystem/Muri
• Owner: MachineLearningSystem
• License: apache-2.0
• Fork: true (Rivendile/Muri)
• Created: 2022-08-24T00:24:05.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-06-30T08:35:56.000Z (over 2 years ago)
• Last Synced: 2024-08-02T19:36:30.068Z (5 months ago)
• Size: 1.82 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-AI-system - Multi-Resource Interleaving for Deep Learning Training SIGCOMM'22

README

        
# 0. Introduction

This repository contains the source code for our SIGCOMM'22 paper "Multi-Resource Interleaving for Deep Learning Training".

# 1. Content

- **simulator/** contains code for simulation and is adapted from [Tiresias](https://github.com/SymbioticLab/Tiresias). Please refer to ```/simulator/README.md``` for detailed information.

- **cluster_exp/** contains code for real-cluster experiment. Please refer to ```/cluster_exp/README.md``` for detailed information.

# 2. Reproduce results (for SIGCOMM'22 artifact evaluation)

Please refer to ```/simulator/README.md``` and ```/cluster_exp/README.md``` for details.

Note: Due to the execution scripts of testbed experiments are highly related to intracompany platform, we only demonstrate the functionality and show the pseudocode of the related scripts (e.g., run.sh, prepare_env.sh). Please adjust to your platform if you would like to execute the testbed experiment.

# 3. Contact

For any question, please contact ```zhaoyh98 at pku dot edu dot cn```