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Comment by endoftime5 | Hacker News Reader

We have taken a slight performance hit, but the code is cleaner and much easier to extend.

If there's any benchmarks on the DiffEq side, feel free to reach out to us with them and we can take a crack at optimizing it. If it's something that's allowed to be shared, we'd love to add it to our DiffEqBenchmarks.jl repository to track the performance over time and understand the performance characteristics of your domain.

Is there a general way to do this with many of the libraries in Julia?

Any chance ya'll could eventually use a test model and script from me in a benchmark test suite.

Ex: I have a large synthetic test model from a university and plan on writing some code that uses a bunch of the sparse matrix and linear solve functionality of the language. This would be on a sparse ~70k row/column square matrix.

At least with DiffEq we keep track of a lot of different benchmarks here: https://github.com/JuliaDiffEq/DiffEqBenchmarks.jl and it's always growing. Some of the best benchmarks have come from users who want us to track performance on their problem. Some other libraries have repos around, but not as formalized. We are getting things automated so that we can start helping others.

Your model sounds nice because it can use our automatic sparsity detection and matrix coloring. I'd love to give it a try.

https://github.com/JuliaDiffEq/SparseDiffTools.jl#automated-...

Awesome! I wish I could give you a real industry one (even bigger), but a synthetic model should adequately reflect the problem domain and they have been the primary models used by researchers in my field for the past twenty years or so.

Edit: which Julia group should I get into contact with over this?

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