cumulator 0.0.6

a tool to quantify and communicate the carbon footprint of machine learning methods

CUMULATOR — a tool to quantify and report the carbon footprint of Machine Learning computations and communication in academia and healthcare

Aim

Raise awareness about the carbon footprint of machine learning methods and to encourage further optimization and the rationale use of AI-powered tools. This work advocates for sustainable AI and the rational use of IT systems.

Installation

Use the following command:

pip install cumulator

Project Structure

├── src/cumulator <- code base for CUMULATOR

├── base.py <- implementation of the Cumulator class ├── bonus.py <- Impact Statement Protocol

Use cases

Cumulator was integrated within the Alg-E platform

ChangeLog

• 07.06.2020: 0.0.2 added communication costs and cleaned src/

• 21.05.2020: 0.0.1 deployment on PypI and integration with Alg-E

Links

• Project’s material: https://drive.google.com/file/d/1saRzSZ_bDqN85a7OoU5611v6BZpz1arx/view?usp=sharing

• GitHub: https://github.com/tristantreb/cumulator

• PyPI: https://pypi.org/project/cumulator/

• Free software: MIT license

Changelog

0.0.0 (2020-05-14)

• First release on PyPI.