GreenSoftwareDirectory

GitHub's Green Software Directory is a simple and easy-to-use resource that all developers can use to adopt green software tools. This list aims to help any developer find green software projects available on GitHub.

What is “Green Software”?

Green software meets all of our modern needs while being carbon aware and efficient. Only three activities reduce the carbon emissions of software: energy efficiency, carbon awareness, and hardware efficiency.

As technology industry energy use grows, we believe we have a responsibility to help support sustainable practices and reduce the environmental impact of software we build.

Image source: Open access climate visuals on GitHub from Ed Hawkins.

Our Directory

We reviewed all repositories on GitHub that self-identified being green software tools as their primary purpose. We compiled these into a directory of resources built by our community, for our community.

We were particularly inspired by the Green Software Foundation's awesome-green-software list, a valuable resource that has been developed by the Green Software Foundation community over the past few years, and the Open Sustainable Technology directory.

This list is managed by GitHub Sustainability with the Social Impact Team.

Categories:

• Measurement
• Carbon Efficiency
• Carbon Awareness
• Special Tools

Do you know of an incredible green software repository that we missed? Let us know! This list is meant to continually grow and develop, so we welcome any suggestions from our community on how we can improve it. Create a pull request with a brief explanation to add a new project.

Measurement

Help measure and interpret the impact of emissions and the environmental impact of software use.

• Scaphandre: Scaphandre [skafɑ̃dʁ] is a metrology agent dedicated to electric power and energy consumption metrics. Use it to measure the power consumption of your tech services and get this data in a convenient form, sending it through any monitoring or data analysis toolchain.
• Kepler: Kepler (Kubernetes-based Efficient Power Level Exporter) uses eBPF to probe performance counters and other system stats, uses ML models to estimate workload energy consumption based on these stats, and then exports them as Prometheus metrics. Use it to learn about energy consumption of Kubernetes components such as Pods and Nodes.
• Codecarbon: A Python package that estimates your hardware electricity power consumption (GPU + CPU + RAM) and then applies to it the carbon intensity of the region where the computing is done.
• Cloud-carbon-footprint: A tool to estimate energy use (kilowatt-hours) and carbon emissions (metric tons CO2e) from public cloud usage.
• Carbon-aware-sdk: A toolset to help you measure the carbon emissions of your software, in turn helping you measure and reduce your software's carbon emissions, and choose when and where you run your software to make it greener.
• CO2.js: An open-source JavaScript library that enables you to estimate the carbon emissions produced by transferring bytes of data on the internet, get different forms of grid intensity data such as annual average and marginal data by country, and make automated queries against Green Web Foundation’s Green Domain’s dataset.
• Carbontracker: Track and predict the energy consumption and carbon footprint of training deep learning models.
• Experiment-impact-tracker: A simple drop-in method to track energy usage, carbon emissions, and compute utilization of your system.
• Eco2AI: The Eco2AI is a Python library for CO2 emission tracking. It monitors energy consumption of CPU & GPU devices and estimates equivalent carbon emissions taking into account the regional emission coefficient. The Eco2AI is applicable to all Python scripts and all you need is to add the couple of strings to your code. All emissions data and information about your devices are recorded in a local file.
• Greenframe-cli: Estimate carbon footprint of a user scenario on a web application.
• Impact: ML has an impact on the climate, but not all models are born equal. Calculate machine learning emissions and add the results to your paper with this generated latex template.
• Zeus: Zeus is a library for (1) measuring the energy consumption of Deep Learning workloads and (2) optimizing their energy consumption.
• Powerapi: PowerAPI is a middleware toolkit for building software-defined power meters. Software-defined power meters are configurable software libraries that can estimate the power consumption of software in real-time. PowerAPI supports the acquisition of raw metrics from a wide diversity of sensors (eg., physical meters, processor interfaces, hardware counters, OS counters) and the delivery of power consumptions via different channels (including file system, network, web, graphical). As a middleware toolkit, PowerAPI offers the capability of assembling power meters «à la carte» to accommodate user requirements.
• Green-cost-explorer: See how much of your cloud bill is spent on fossil fuels, so you can do the right thing and switch. We're in a climate crisis, remember? This will show you your climate-related spend analysis for AWS.
• Green Metrics Tool: Measures the energy and CO2 consumption of software through a software life cycle analysis (SLCA).
• Carbonalyser: The add-on "Carbonalyser" allows you to visualize the electricity consumption and greenhouse gases (GHG) emissions that your Internet browsing leads to.
• GreenIT-Analysis: GreenIT-Analysis est une extension pour navigateur qui vous permet de quantifier les impacts environnementaux d'un parcours utilisateur complet, même derrière un firewall et / ou une authentification applicative. L'outil vérifie également l'utilisation de bonnes pratiques visant à diminuer ces impacts.
• Tracarbon: Tracarbon tracks your device's energy consumption and calculates your carbon emissions using your location.
• Carbonifer: Command Line Tool to control carbon emission of your cloud infrastructure. Reading Terraform files, carbonifer plan will estimate future Carbon Emissions of infrastructure and help make the right choices to reduce Carbon footprint.
• PyJoules: A Python library to capture the energy consumption of code snippets.
• Powerjoular: PowerJoular is a command line software to monitor, in real time, the power consumption of software and hardware components.
• Eco CI Energy Estimation: A project aimed at estimating energy consumption in continuous integration (CI) environments.
• Perun: Perun is a Python package that calculates the energy consumption of Python scripts by sampling usage statistics from your Intel, Nvidia or AMD hardware components. It can handle MPI applications, gather data from hundreds of nodes, and accumulate it efficiently. perun can be used as a command-line tool or as a function decorator in Python scripts.
• Cloud-scanner: Get Boavizta impact data for your aws cloud account usage.
• E-footprint: The current perimeter is the carbon footprint associated with the fabrication and usage of servers, storage, network (usage only) and end-user devices necessary for the existence of a digital service. Other environmental impacts (water, rare earth metals, etc.) will be added soon through an integration with the Boavizta API, and the lifecycle phases of device transportation and end of life are currently considered negligible.
• Carbon-tools: A set of CO2 footprint tools to measure the impact of the code we ship.
• Ecoinfra: Ecoinfra is a powerful tool that helps you predict, asses, and reduce the environmental impact of your cloud infrastructure. By integrating your existing or new IaC project you can harness predictive sustainability into your cloud operations.
• PSElectricityMaps: This PowerShell module is intended for retrieving emissions data from CO2 Signal for a supplied Azure Region during resource deployments. This is a lightweight solution making use of non-commercial functionality available with a free account at