From dbe471a6cb0ab5f0f202f57200c0b785ad3dd6dc Mon Sep 17 00:00:00 2001 From: Avik Pal Date: Wed, 30 Oct 2024 10:40:27 -0400 Subject: [PATCH] docs: remove NonlinearSolve refactoring Already near completion in https://github.com/SciML/NonlinearSolve.jl/pull/483 --- small_grants.md | 28 ---------------------------- 1 file changed, 28 deletions(-) diff --git a/small_grants.md b/small_grants.md index 13a099f1..0cc7d8e3 100644 --- a/small_grants.md +++ b/small_grants.md @@ -269,34 +269,6 @@ would be helpful for debugging. **Reviewers**: Chris Rackauckas -## Refactor NonlinearSolve.jl to use Sub-Packages of Solvers (\$300) - -With the successful splitting of [OrdinaryDiffEq.jl](https://sciml.ai/news/2024/08/10/sciml_small_grants_successes/), -we suspect that similar installation and loading time improvements can be had by -splitting NonlinearSolve.jl and BoundaryValueDiffEq.jl in such a way that the solvers -can precompile in parallel and allow for depending on only a portion of the algorithms. -In particular, OrdinaryDiffEq.jl only needs to depend on a trust region method, meaning -that other sets of methods can be fully discarded from its dependency stack. - -**Information to Get Started**: The OrdinaryDiffEq.jl solvers are all found in -[the Github repository](https://github.com/SciML/OrdinaryDiffEq.jl) and -the format of the package is docmented in the -[developer documentation](https://docs.sciml.ai/DiffEqDevDocs/stable/). [https://github.com/SciML/OrdinaryDiffEq.jl/issues/2177](https://github.com/SciML/OrdinaryDiffEq.jl/issues/2177) -documents the process on OrdinaryDiffEq.jl to - -**Related Issues**: - -**Success Criteria**: The independent solver packages are registered and released, -and a breaking update to OrdinaryDiffEq.jl is released which reduces the loading -time by not including all solvers by default. This success also requires updating -package documentation to reflect these changes. - -**Recommended Skills**: Since all of the code for the solvers exists and this a refactor, -no prior knowledge of numerical differential equations is required. Only standard software -development skills and test-driven development of a large code base is required. - -**Reviewers**: Chris Rackauckas, Avik Pal - ## Refactor OrdinaryDiffEq.jl Solver Sets to Reuse perform_step! Implementations via Tableaus (\$100/solver set) **In Progress**: Claimed by Param Umesh Thakkar for the time period of August 11th, 2024 - September 11th 2024.