[marmalade2413]

The key elements that I consistently see missing when comparing languages is the cost/effort of maintenance and how easy is to write fast/slow code.

The former boils down to, there's little point saving time in the writing of new code when new versions of the language hinder the use of old codes. Julia, being a very young language, simply does not have the legacy of backwards compatibility that Fortran has and as a result libraries written today are unlikely to work in 10 years time. Partly because of Julia's age and partly because backwards compatibility is not valued as much as it is in Fortran. The GNU Fortran compiler can still compile code written nearly 50 years ago (https://gcc.gnu.org/fortran/).

The second point is that benchmarks like this seem to focus on tuned implementations, which is really important, but another important aspect is how easy is it write fast code. With Fortran, it is very easy to write very fast code as a lot is abstracted away from the programmer so they can focus on FORmula TRANslation. My experience with Julia has not been the same and thus for people don't have the time to perform such optimisations, Fortran may still be the better choice.

I do look forward to watching the development of Julia but for now I'll stick with using Fortran as the high performance numerical language in my tech stack.

I'll finish with something I've read but I can't remember from where:

Over the years there have been many examples of "X with replace Fortran" and the only thing that ends up getting replaced is X.