patrick-kidger / patrick-kidger/diffrax
Understand diffrax.diffeqsolve
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- Dominant language
- Python
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Description
Hi,
Thanks for the nice package. I have a question regarding the implementation of diffrax.diffeqsolve. Specifically, I want to know a bit more details about the ODE solver, especially on what are the key factors driving diffeqsolve to be faster. In a nutshell, can you list several bulletpoints on the code implementation optimizations that have been done to accelerate ODE solving in diffrax?
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 implementation of diffrax.diffeqsolve and trace the main ODE-solving path. Identify the implementation optimizations that affect speed, then document them as several concise bullet points; done means the package has a clear explanation addressing the question.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100