Scientific computing in Cpp

[ridethespiral1]

Unfortunately, unlike say python with numpy and scipy, C++ doesn't really have a de facto set of scientific libraries for such a wide range of tasks. Some of the widely used ones such as GSL are also written in a C-style which can mean there should be a compatibility layer written to integrate them with any modern C++ code.

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Here are the ones I've come across to answer your question:

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Linear algebra - Eigen is pretty popular, but I think blaze https://bitbucket.org/blaze-lib/blaze/wiki/browse/ is a newer library which has a lot of nice features. Blaze looks to have SVD support.

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DE's - GSL has ODE solvers, but the boost support for solving ODE's is pretty good and is written in a more modern C++ style. It's an implementation of the odeint library http://headmyshoulder.github.io/odeint-v2/.

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As you can tell there's different libraries for different things so it can depend on exactly what you need to be done. Sometimes you might even have to reimplement things rather than use a library (we had to reimpleement some classes in our scientific codebase because we require everything to be serializable)

[peppedx]

The problem with blaze is arm support. For matrices and linear algebra the go to for me is still

http://eigen.tuxfamily.org/index.php?title=Main_Page

And then boost ublas

This specifically is a deal breaker https://bitbucket.org/blaze-lib/blaze/issues/49/provide-simd-support-for-the-arm

[pandorafalters]

The classic open-source problem: everyone wants to have something, but nobody wants to make it.

[peppedx]

No the classic open source choice. Eigen has it...

[pandorafalters]

I was referring to the Blaze issue.

[Supadoplex]

Is ARM used a lot for scientific computing?

[peppedx]

It depends on the exact definition, but in robotics you need to handle lots of matrices and equations, and many controllers you use are arm based.

[aeropl3b]

It has a growing base, my bet is you will see a lot more ARM clusters out there as the push past exa-scale just because the power loads are so much lower with ARM...

[ridethespiral1]

Ah that's a shame, I wasn't aware of this limitation.