[tobmlt]

The barrier to entry to doing fast linear algebra from scratch is the lowest of any of c,c++,Fortran.

Python and matlab being to slow at “low barrier to entry level” for sure anyway.

I’m not going to comment on julia because I’m still drinking coffee. In theory… blah blah maybe it should fill this role.

Sit down, write stupid simple Fortran code to solve a large linear algebra problem (a discretized partial differential equation system) and things like matrix multiplication and numpy style mat(:) access are built in. (Numpy borrowed the syntax from fortran, actually)

For a scientist, this is way easier than wading into c++ and getting it right; or sticking with c, and avoiding the footguns.

Fortran gives you maximum serial speed with minimum effort… it is easy to write efficient serial code, while knowing almost nothing of programming. Memory management sure, but even there, there out of the box are no pointers to fumble and your allocations are going to be contiguous. Optimal Array Memory access comes down to knowing Fortran is column based.

Ah but then you need to go parallel, where the documentation more in c these days.

But you’re already comfy with Fortran now, so, scientist that you are, you dig and experiment until you get it running in openmp, mpi, and cuda, etc.