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Tdlr, Fortran is low level-ish, compiled, but otherwise almost identical to numpy syntax wise.

It supports all the common array and matrix operations and it doesn't need memory and pointer management the way C does. But it still compiles down to something very fast, you can link in BLAS and GPU libraries, supports easy parallelism...

When I compare with e.g. Karpathy's llama2.c, I think Fortran is easy to work with implementing basic transformer inference because of how it handles arrays.

The downside is that while there are efforts to modernize it, I find it more cumbersome for non-numerical stuff, particularly strings. But I think for the actual linear algebra implementation, it can't be beat.

I should add, I know it's a bit of an uphill battle, I expect fewer people will use code that I write in Fortran vs basically anything else. But I'm hoping to pull some people in and get a critical mass of interest because I think it has a lot of promise. That's actually one of the reasons I wanted to get a Mamba implementation quickly (though now that there's a basic python one I think I'll have lost some potential users to it :)




Thanks for the thoughtful response.

Unfortunately, I too think it will be a bit of an uphill battle for you.

If you haven't already, take a look at Mojo and Julia. Both offer many of the benefits of Fortran, but unlike it, they are seeing growing adoption.


An uphill battle is fine




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