SLANG.D as differentiable renderer for Warp
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feature request
- Dominant language
- Python
- Stars
- 7.1k
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- Avg merge
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- Merged PRs (30d)
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Description
Hello,
I have just come across https://research.nvidia.com/labs/rtr/publication/bangaru2023slangd/ and it instantly got me thinking whether SLANG.D could be used as a lightweight differentiable rasterizer or raytracer (RT-Cores accelerated?) for simulation in Warp? Some example integration would be great. Cheers!
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
The issue names no repository files, tests, or entry points. Start by reading the linked SLANG.D publication and the Warp repository to determine whether a SLANG.D-based differentiable rasterizer or raytracer integration is feasible. Done would require a demonstrated example integration, if supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-graphics, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100