Skip to content

Update Small Grants (Completion): "Simple Handwritten PDEs as ODEs" Benchmark Set" #171

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 3 commits into from
Aug 2, 2025
Merged

Update Small Grants (Completion): "Simple Handwritten PDEs as ODEs" Benchmark Set" #171

Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
166f0cf
Update small_grants.md
GodotMisogi Jul 30, 2025
5ca66de
Updated payout amount and dates
GodotMisogi Aug 2, 2025
6c3e630
Moved PDE project to completed section
GodotMisogi Aug 2, 2025
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
67 changes: 34 additions & 33 deletions small_grants.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -162,39 +162,6 @@ will "go the extra mile" to teach the contributor how the package or mathematics

# List of Current Projects

## Fix and Update the "Simple Handwritten PDEs as ODEs" Benchmark Set (\$200)

**In Progress**: Claimed by Arjit Seth from June 20, 2025, to July 20, 2025.

The "Simple Handwritten PDEs as ODEs" benchmarks have been failing for a while.
They need to be updated to the "new" linear solve syntax introduced in 2022.
When updated, these benchmarks should serve as a canonical development
point for PDE-specific methods, such as implicit-explicit (IMEX) and
exponential integrators.

**Information to Get Started**: The
[Contributing Section of the SciMLBenchmarks README](https://github.com/SciML/SciMLBenchmarks.jl?tab=readme-ov-file#contributing)
describes how to contribute to the benchmarks. The benchmark results are
generated using the benchmark server. Half of the benchmarks are set up
using hand-discretized finite difference stencils for the PDE, the other
half use ApproxFun.jl in order to do a pseudospectral discretization.
A direct pseudospectral discretization via manual FFTs and operator
construction would also be fine.

**Related Issues**: [https://github.com/SciML/SciMLBenchmarks.jl/issues/929](https://github.com/SciML/SciMLBenchmarks.jl/issues/929)

**Success Criteria**: Pull requests which [update the benchmarks in the
folder](https://github.com/SciML/SciMLBenchmarks.jl/tree/master/benchmarks/SimpleHandwrittenPDE)
to be successful with the current Julia and package version (v1.10) without
erroring, generating work-precision diagrams. In addition, these should be updated
to give a clearer definition of the PDE being solved, adding a LaTeX
description of the equations to the top of the file.

**Recommended Skills**: Basic (undergrad-level) knowledge of finite difference and pseudospectral
PDE discretizations.

**Reviewers**: Chris Rackauckas

## Update CUTEst.jl to the Optimization.jl Interface and Add to SciMLBenchmarks (\$200)

*In Progress: Claimed by Arnav Kapoor for the time period of July 5th 2025 - August 5th 2025.*
Expand Down Expand Up @@ -334,6 +301,40 @@ which SciML will help administer through the small grants program.

These are the previous SciML small grants projects which have successfully concluded and paid out.


## Fix and Update the "Simple Handwritten PDEs as ODEs" Benchmark Set (\$400)

>Completed by Arjit Seth on August 1, 2025.

The "Simple Handwritten PDEs as ODEs" benchmarks have been failing for a while.
They need to be updated to the "new" linear solve syntax introduced in 2022.
When updated, these benchmarks should serve as a canonical development
point for PDE-specific methods, such as implicit-explicit (IMEX) and
exponential integrators.

**Information to Get Started**: The
[Contributing Section of the SciMLBenchmarks README](https://github.com/SciML/SciMLBenchmarks.jl?tab=readme-ov-file#contributing)
describes how to contribute to the benchmarks. The benchmark results are
generated using the benchmark server. Half of the benchmarks are set up
using hand-discretized finite difference stencils for the PDE, the other
half use ApproxFun.jl in order to do a pseudospectral discretization.
A direct pseudospectral discretization via manual FFTs and operator
construction would also be fine.

**Related Issues**: [https://github.com/SciML/SciMLBenchmarks.jl/issues/929](https://github.com/SciML/SciMLBenchmarks.jl/issues/929)

**Success Criteria**: Pull requests which [update the benchmarks in the
folder](https://github.com/SciML/SciMLBenchmarks.jl/tree/master/benchmarks/SimpleHandwrittenPDE)
to be successful with the current Julia and package version (v1.10) without
erroring, generating work-precision diagrams. In addition, these should be updated
to give a clearer definition of the PDE being solved, adding a LaTeX
description of the equations to the top of the file.

**Recommended Skills**: Basic (undergrad-level) knowledge of finite difference and pseudospectral
PDE discretizations.

**Reviewers**: Chris Rackauckas

## Wrap PyCMA into the Optimization.jl Interface (\$100)

*Completed by Maximilian Pochapski June 25th, 2025*
Expand Down