Eclipse Graphene

The goal of Eclipse Graphene™ is to make AI and machine learning accessible to a wide audience by creating an extensible marketplace of reusable solutions, sourced from a variety of AI toolkits and languages that ordinary developers, who are not machine-learning experts or data scientists, can easily use to create their own applications.

Eclipse Graphene is not a centralized execution environment for AI solutions. It is a design and distribution framework for integrating solutions from modular components. It provides a launchpad for training and validating both individual components and integrated, or composite, solutions, and then securely distributing the results to targeted communities through an electronic catalogue, from which components can be selected. Graphene also provides the deployment interfaces that allow solutions to be trained or executed on many popular runtime environments, including several commercial cloud services, mostly Kubernetes-based.

Eclipse Graphene includes a graphical tool, called AcuCompose, for chaining together multiple models, data translation tools, filters and output adapters into a full end-to-end solution that can be deployed into the aforementioned runtime environments. Eclipse Graphene only requires a container management facility, like Kubernetes, to deploy and execute portable general purpose applications. At the very core of interoperability is the Eclipse Graphene container specification:

Eclipse Graphene also has the means for collaboration in closed groups on dedicated projects in mixed teams (i.e. building a pipeline together, or working through an auditing process by building pipelines and store audit documentation and execution results)

Eclipse Graphene supports many hardware infrastructures in order to maximize the utility of the solutions being deployed. This makes Graphene-compatible solutions portable and flexible. Eclipse Graphene offers a mechanism for packaging, sharing, licensing, and deploying AI models in the form of portable, containerized microservices, which are interoperable with one another. It provides a publication mechanism for creating shared, secure catalogues and a mechanism for deployment onto any suitable runtime infrastructure.

Latest Releases

From 2023-10-05 to 2022-11-24

Name Date Review
1.1 2023-10-05
1.0 2022-11-24
Apache License, Version 2.0

The content of this open source project is received and distributed under the license(s) listed above. Some source code and binaries may be distributed under different terms. Specific license information is provided in file headers and in NOTICE files distributed with the project's binaries.

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