[btilly]

FORTRAN is faster for many tasks, and is probably more popular in high performance computing.

Also tasks that can be moved to the GPU go a lot faster. You can interact with those programs in C, but not natively. But some languages, like Julia, can easily move calculations to/from the GPU. And also can transparently take advantage of parallelism.

Julia is in the process of growing rapidly for high performance computing. I don't know if it has officially passed C there. But if not yet, it will.

[Leo_Verto]

To add onto your point: from what I've heard the split at HPC conferences is about 40% C to 60% Fortran.

[SubjectToChange]

In my limited experience, almost every language specific presentation at an HPC conference is about C++. New projects and initiatives like DPC++, SYCL/oneAPI, Ginkgo, etc are C++ based. And if you look at the open source libraries of the national laboratories, e.g. LLNL, C++ libraries are more common than C libraries, which in turn are more common than the Fortran libraries.

If anything I'd say that C++ is the default for HPC conferences.

[btilly]

That sounds right.

I wonder what the current split is. I'm not in HPC computing, but I see a lot of posts about how quickly Julia is being adopted.

[not2b]

Python users who use numpy and scipy are actually using a lot of Fortran code.