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Merge pull request #126 from SciML/smallgrants
Refresh the SciML Small Grants program
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@@ -24,17 +24,26 @@ be considered in the approval evaluations. | |
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| ## Declaring for a Project | ||
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| To declare for a small grant program, send an email to [email protected] with: | ||
| To declare for a small grant program, open a pull request on the Github repo for | ||
| [https://github.com/SciML/sciml.ai](https://github.com/SciML/sciml.ai) in the | ||
| `small_grants.md` file with a declaration for the grant in the section of the | ||
| project of interest. For example: | ||
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| > **In Progress**: Claimed by XXXXXX for the time period of (today) - (one month later). | ||
| In your pull request, please share: | ||
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| * Full legal name | ||
| * CV | ||
| * Link to Github account | ||
| * Short bio / background about your experience in the topic | ||
| * Description of which project you're interested in | ||
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| The potential reviewers will then get in touch to clarify details of the project and | ||
| establish a clear work statement. Once clarifed, steering council will then respond with | ||
| whether the application is accepted and commence the work under the supervision of the | ||
| If some anonymity is requested, you may instead send this information to [email protected]. | ||
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| The potential reviewers will discuss the current-ness of the small grant project, the | ||
| availability of reviewers, and the willingness to review. The small grant project | ||
| is accepted when a majority of the steering council approves of the project and the PR | ||
| is merged. At that point the work will commence under the supervision of the | ||
| reviewer. When the reviewer accepts and merges the appropriate PRs, the grant will be | ||
| determined as completed and the payout will commence. The grants are project based and | ||
| payout will only occur upon acceptance by the reviewer. | ||
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@@ -43,6 +52,29 @@ Note that information about ongoing projects will be tracked as public informati | |
| below in order to give clear information to other contributors about what projects | ||
| are taken. Completed projects will be added to a projects archive. | ||
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| ## Going Over the One-Month Time Budget | ||
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| Each project is given a one month exclusive period for the purpose of decreasing competition. | ||
| The difference between the small grants program and a standard bounty program is that we wish | ||
| to discourage "sniping" bounties from others, i.e. someone working for a few weeks on a project | ||
| before suddenly someone else appears with a complete solution and takes the payout. While this | ||
| is not impossible to prevent, as an open source community there may be others who happen to | ||
| be working the same project independently, to reduce the occurrences of this phonomena we have | ||
| a policy that payouts will only occur for declared projects. This policy can be overriden on | ||
| special circumstances by a majority vote of the steering council. | ||
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| In order to discourage "spotting", i.e. claiming projects to sit on them indefinitely and thus | ||
| blocking other contributors, only one month exclusive periods are granted. If the project seems | ||
| to be going beyond this one month timeframe, the contributor should ask for an extension by | ||
| making a new pull request to bump the time window, which would then need to pass by a majority | ||
| vote of the steering council. If a new claim PR is opened after the time window has passed | ||
| without the contributor formally bumping the time window, then the new claim PR will be reviewed | ||
| under the assumption that the project is not currently active. | ||
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| Note that unsuccessful small grants projects, i.e. claims of potential projects where the | ||
| contributor disappears and does not end up with a PR, will be used in the criteria of whether | ||
| further requests are accepted. | ||
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| ## Donating to the Program | ||
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| If you wish to donate to the SciML Small Grants Program, | ||
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@@ -60,6 +92,18 @@ process and proper maintanance beyond the timeframe of the project. For this rea | |
| we suggest discussing with maintainers in the official Slack/Zulip before making | ||
| an earmarked donation. | ||
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| ## Adding Projects to the List | ||
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| If you wish to add a project to the small grants list, open a pull request in the | ||
| [https://github.com/SciML/sciml.ai](https://github.com/SciML/sciml.ai) in the | ||
| `small_grants.md` file with a full description of the project and the suspected monetary | ||
| payout. New projects require approval by a steering committee member. The justification | ||
| for the funding is required. If it is a personal donation, it is recommended that personal | ||
| donation is made prior to the PR, though for known members of the community this requirement | ||
| can be waived. Some of the projects can be covered through prior grant funds and other | ||
| donations made to the SciML project, though it should not be assumed that this will be the | ||
| case for any project without review by a steering committee member. | ||
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| ## Commitments from Reviewers | ||
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| Reviewers are committed to giving timely feedback and reviews. It is expected that you keep | ||
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| **Reviewers**: Avik Pal, Chris Rackauckas | ||
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| ## Fix and Update the "Simple Handwritten PDEs as ODEs" Benchmark Set (\$200) | ||
| ## Rewrite the NeuralPDE parser (\$300) | ||
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| NeuralPDE is a package for training Physics Informed Neural Networks (PINNs) uses a | ||
| symbolic representation for problems which are then lowered into generated code for | ||
| the user, fully automating the PINN experience. However, the previous formulation of the | ||
| codegen process used pre-built kernels that can be difficult to debug. The goal of this | ||
| project is to rewrite the loss function generator to instead generate a Symbolics.jl | ||
| expression, which can be analyzed an generate code through `build_function`. | ||
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| **Information to Get Started**: A partial uncompleted pull request https://github.com/SciML/NeuralPDE.jl/pull/877 can be used as a starting point. | ||
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| **Recommended Skills**: Basic (undergrad-level) knowledge of Physics Informed Neural | ||
| Networks, and symbolic computing. | ||
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| **Reviewers**: Chris Rackauckas | ||
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| ## Update SciMLOperators.jl to allow for different defining vectors from actions (\$500) | ||
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| **In Progress**: Claimed by Criston Hyett for the time period of September 21st, 2024 - October 20th 2024. | ||
| SciMLOperators.jl is a package for defining lazy operators `A(u,p,t)*v` which can be used | ||
| throughout the ecosystem. However, many of the operators incorrectly make the assumption | ||
| that `u = v`, i.e. `A(u,p,t)*u` is the operation. While this is the only case required | ||
| for some ODE integrators, this oversimplification limits the full usage of the library. | ||
| It is expected that this is a breaking change (with a major release bump) and is the | ||
| major change required for the v1.0 release. | ||
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| **Information to Get Started**: The documentation of https://github.com/SciML/SciMLOperators.jl | ||
| should be sufficient. | ||
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| **Recommended Skills**: Basic (undergrad-level) knowledge of linear operators and multiple dispatch | ||
| in Julia. | ||
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| **Reviewers**: Chris Rackauckas | ||
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| ## Fix and Update the "Simple Handwritten PDEs as ODEs" Benchmark Set (\$200) | ||
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| The "Simple Handwritten PDEs as ODEs" benchmarks have been failing for awhile. | ||
| They need to be updated to the "new" linear solve syntax introduced in 2022. | ||
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@@ -163,22 +238,6 @@ These bumps are done in subsets. The currently identified subsets are: | |
| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/876](https://github.com/SciML/SciMLBenchmarks.jl/pull/876) | ||
| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/605](https://github.com/SciML/SciMLBenchmarks.jl/pull/605) | ||
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| #### ComplicatedPDE | ||
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| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/793](https://github.com/SciML/SciMLBenchmarks.jl/pull/793) | ||
| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/868](https://github.com/SciML/SciMLBenchmarks.jl/pull/868) | ||
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| #### DynamicalODE | ||
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| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/1025](https://github.com/SciML/SciMLBenchmarks.jl/pull/1025) | ||
| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/870](https://github.com/SciML/SciMLBenchmarks.jl/pull/870) | ||
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| #### BayesianInference | ||
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| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/797](https://github.com/SciML/SciMLBenchmarks.jl/pull/797) | ||
| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/866](https://github.com/SciML/SciMLBenchmarks.jl/pull/866) | ||
| * [https://github.com/SciML/SciMLBenchmarks.jl/pull/1038](https://github.com/SciML/SciMLBenchmarks.jl/pull/1038) | ||
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| **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 | ||
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@@ -324,8 +383,6 @@ development skills and test-driven development of a large code base is required. | |
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| ## Update LoopVectorization to Support Changes in Julia v1.12 (\$200) | ||
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| **In Progress**: Claimed by Miguel Raz Guzman for the time period of May 10th, 2024 - June 10th 2024. | ||
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| [LoopVectorization.jl](https://github.com/JuliaSIMD/LoopVectorization.jl) is a | ||
| central package for the performance of many Julia packages. Its internals make | ||
| use of many low-level features and manual SIMD that can make it require significant | ||
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