doc: distributed computing with ray
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Description
Use cases, pain points, and background
The Ray documentation in reference/faq.md has several issues:
- Wrong location — Buried in FAQ, hard to discover for users hitting scale issues
- Unclear audience — Mixes what's automatic (Ray init) with what's optional (using
@ray.remotein your code) - Missing decision criteria — Doesn't explain when you need Ray
- Generic example — Shows standalone function, not integrated with resource server patterns
Description:
Relocate documentation from FAQ into standalone docs page and improve the content for clarity
Design:
# Distributed Computing with Ray
## Overview
<!-- What Ray does in NeMo Gym, that it's auto-initialized -->
## When You Need Ray
<!-- Decision criteria: CPU-bound verification, 1000s of concurrent requests -->
## Using Ray in Your Code
<!-- How to add @ray.remote to your functions -->
## Configuration
<!-- ray_head_node_address for training framework integration -->
Out of scope:
- General Ray tutorials or Ray cluster administration (link to Ray docs instead)
- Changes to Ray initialization logic in NeMo Gym code
- Performance benchmarking or profiling guidance (covered in separate profiling docs)
- Troubleshooting Ray-specific errors (e.g., serialization issues, memory limits)
- Multi-node cluster setup instructions (training framework responsibility)
Acceptance Criteria:
- New docs page created at
docs/infrastructure/distributed-computing.md - Page covers all 4 sections: Overview, When You Need Ray, Using Ray, Configuration
- Example code shows integration with a resource server
verify()method (not standalone function) - Decision criteria section includes concrete thresholds (e.g., "CPU-bound tasks taking >Xms at >Y concurrent requests")
- FAQ entry removed entirely
- Toctree updated in
docs/index.mdwith new Infrastructure section - Docs build successfully (
make htmlin docs/)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the Ray-related content in reference/faq.md, then inspect docs/index.md and nearby pages under docs/infrastructure/. Create docs/infrastructure/distributed-computing.md with the four specified sections and resource-server verify() example, remove the FAQ entry, update the toctree, and run make html in docs/ to confirm the build succeeds.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, documentation
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 58/100