xffl

Cross-Facility Federated Learning

https://github.com/alpha-unito/xffl

Science Score: 44.0%

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CITATION.cff file
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Scientific vocabulary similarity
Low similarity (11.8%) to scientific vocabulary

Last synced: 10 months ago · JSON representation ·

Repository

Cross-Facility Federated Learning

Basic Info

Host: GitHub
Owner: alpha-unito
License: gpl-3.0
Language: Python
Default Branch: main
Size: 15.4 MB

Statistics

Stars: 7
Watchers: 4
Forks: 1
Open Issues: 0
Releases: 0

Created about 2 years ago · Last pushed 11 months ago

Metadata Files

Readme License Citation

Cross-Facility Federated Learning (xFFL)

Cross-Facility Federated Learning (xFFL) is a federated learning (FL) framework based on the StreamFlow workflow management system (WMS) developed in the Parallel Computing [Alpha] research group at the University of Turin, Italy.

xFFL is designed to be a research-oriented software, enabling FL workloads deployment on geographically distributed computing infrastructures including, but not limited to, high-performance computers (HPCs).

We aim to democratize extensive ML workload development, allowing researchers and SMEs to be competitive with big tech companies by exploiting sparse computing power.

University of Turin logo

Get started

Setup

Clone this repository on the computing infrastructure that will act as the federation orchestrator: bash git clone --depth 1 --branch main https://github.com/alpha-unito/xffl.git Note that this machine should have internet access and be capable of reaching the federation clients through SSH.

Create and activate a Python virtual environment (both venv and conda are valid options): bash python3 -m venv xFFL source xFFL/bin/activate

Install xFFL and its requirements: bash cd xffl/ python3 -m pip install .

Configuration creation

Create an xFFL configuration file in a guided way through the xFFL CLI: bash xffl config --w [workdir] --p [project] Where workdir is the name of the working directory to create (defaults to the local directory), and project is the name of the created deployment. This process will produce a directory containing the necessary StreamFlow and xFFL configuration files and the chosen model.

System requirements

Python>=3.9
Singularity/Docker
NodeJS

Architecture

xFFL implements a centralized FL schema in which a central server coordinates, distributes, and aggregates the learning tasks deployed on the clients. Such a process is orchestrated by StreamFlow, which handles the data movement between the computing infrastructures and the deployment of workloads.

xFFL

Contributors

Owner

Name: Parallel programming: Alpha group
Login: alpha-unito
Kind: organization
Location: Torino, IT

Website: http://alpha.di.unito.it
Repositories: 9
Profile: https://github.com/alpha-unito

Parallel Computing research cluster, Department of Computer Science, University of Torino

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you want to cite xFFL, please refer to the article below."
authors:
  - family-names: "Mittone"
    given-names: "Gianluca"
    orcid: "https://orcid.org/0000-0002-1887-6911"
  - family-names: "Mulone"
    given-names: "Alberto"
    orcid: "https://orcid.org/0009-0009-2600-613X"
  - family-names: "Colonnelli"
    given-names: "Iacopo"
    orcid: "https://orcid.org/0000-0001-9290-2017"
title: "Cross-Facility Federated Learning"
version: 0.1
url: "https://github.com/alpha-unito/xffl"
preferred-citation:
  type: article
  authors:
    - family-names: "Colonnelli"
      given-names: "Iacopo"
      orcid: "https://orcid.org/0000-0001-9290-2017"
    - family-names: "Birke"
      given-names: "Robert"
      orcid: "https://orcid.org/0000-0003-1144-3707"
    - family-names: "Malenza"
      given-names: "Giulio"
      orcid: "https://orcid.org/0009-0006-4862-7429"
    - family-names: "Mittone"
      given-names: "Gianluca"
      orcid: "https://orcid.org/0000-0002-1887-6911"
    - family-names: "Mulone"
      given-names: "Alberto"
      orcid: "https://orcid.org/0009-0009-2600-613X"
    - family-names: "Galjaard"
      given-names: "Jeroen"
      orcid: "https://orcid.org/0000-0003-3681-7226"
    - family-names: "Chen"
      given-names: "Lydia Y."
      orcid: "https://orcid.org/0000-0002-4228-6735"
    - family-names: "Bassini"
      given-names: "Sanzio"
    - family-names: "Scipione"
      given-names: "Gabriella"
      orcid: "https://orcid.org/0000-0001-7202-9994"
    - family-names: "Martinovič"
      given-names: "Jan"
      orcid: "https://orcid.org/0000-0001-7944-8956"
    - family-names: "Vondrák"
      given-names: "Vit"
      orcid: "https://orcid.org/0000-0002-7940-6323"
    - family-names: "Aldinucci"
      given-names: "Marco"
      orcid: "https://orcid.org/0000-0001-8788-0829"
  doi: 10.1016/j.procs.2024.07.003
  issn: 1877-0509
  journal: "Procedia Computer Science"
  publisher:
    name: Elsevier
    city: Amsterdam
    country: NL
  start: 3
  end: 12
  title: "Cross-Facility Federated Learning"
  volume: 240
  year: 2024

GitHub Events

Total

Watch event: 10
Delete event: 2
Issue comment event: 2
Push event: 162
Pull request review comment event: 11
Pull request review event: 18
Pull request event: 15
Fork event: 1
Create event: 7

Last Year

Watch event: 10
Delete event: 2
Issue comment event: 2
Push event: 162
Pull request review comment event: 11
Pull request review event: 18
Pull request event: 15
Fork event: 1
Create event: 7

Issues and Pull Requests

Last synced: 10 months ago

All Time

Total issues: 0
Total pull requests: 9
Average time to close issues: N/A
Average time to close pull requests: 9 days
Total issue authors: 0
Total pull request authors: 4
Average comments per issue: 0
Average comments per pull request: 0.11
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 9
Average time to close issues: N/A
Average time to close pull requests: 9 days
Issue authors: 0
Pull request authors: 4
Average comments per issue: 0
Average comments per pull request: 0.11
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 0

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