Run your Python code on Golem with Ray on Golem

This documentation is designed for developers wanting to run their Python code on Golem. We will use Ray to parallelize the code and Ray on Golem to execute it.

Quickstart - quick and easy, copy and run instructions on launching and decommissioning the Ray on Golem cluster
Concept - guide on what Ray and Ray on Golem is, listing all pieces needed to use them
Setup tutorial - step-by-step explanation of the quickstart instructions
Basic Ray tasks usage tutorial - anatomy of Ray application based on a simple code showcasing Ray tasks
Converting a real-life use case to Ray on Golem - example of a little bit more practical Ray on Golem usage
Cluster yaml reference - details of every configuration option of Ray on Golem cluster yaml
Supported versions & other limitations - list of supported python & ray versions, and other known issues
Troubleshooting - hopefully helpful tips on what to do when something goes wrong

Check out the Ray overview to get a feeling of how cool Ray is in general. Specifically, we are focusing on the Ray Core mechanisms that are the foundation of all Ray libraries.

If you have any questions, comments insights, praises, or doubts about these docs and Ray on Golem in general please don't hesitate to reach out to us either on