Skip to content
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
28 changes: 0 additions & 28 deletions small_grants.md
Original file line number Diff line number Diff line change
Expand Up @@ -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.
Expand Down