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Run you 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
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