"At present, no language can rival, let alone surpass, Fortran when it comes to implementing long-lived, large-scale, massively-parallel scientific and engineering applications; not even C and C++."

Huh??? A tremendous amount of scientific computing happens in C, C++, and many other languages. I have worked with Fortran, worked with Fortran-heavy labs in academia, and this is just a nonsensical thing to say.

I think the OP's thoughts are really deep, but I disagree on some points.Personally, I think the suggestion in the OP about switching Fortran to row-major is a separate issue. I have doubts about whether scientific languages should make such a switch. Rather, I consider it Fortran's competitive advantage. You can directly bring mathematical thinking into it. There are also cache related concerns.

Because it's an array oriented language, I think the need for a tracing GC is relatively low. The advantage of GC comes into play when object graphs are complex, but looking at old Fortran code, arrays mostly operate outside that domain.

In reality, the biggest problem is that Python has become too mainstream, and hardware performance has improved too much. Old numerical computation books were mostly in Fortran, but now they're in Python. The reason is simpler than you might think. Python has a strong ecosystem for visualization packages. Beyond just interfacing with Fortran, Python is more powerful as a working environment. And most scientists, who prioritize building their careers around papers with smaller scale computations rather than large scale Fortran dominated calculations requiring massive equipment, have gravitated toward Python, which lets them quickly sketch ideas.

And realistically, Python's greatest strength is that while it's inadequate in almost every area, it can do almost everything. I think that's the most important factor in language choice. Once you learn Python, you can do EDA, ETL, numerical computation, build websites, create apps with Qt, and much more. There are performance bottlenecks due to the GIL, but most tasks don't actually require that level of performance.

Fortran can push hardware to its limits when used well, but as such hardware intensive tasks increasingly shift toward large scale collaborative work, I think it's been losing its competitive edge.

It's not that Fortran is bad, but realistically, being able to do many things matters more. Before Python became widely used, programming books had too many languages for each domain. Math had Maple, and so on. But Python, honestly, just works because you can do a lot with it if you're willing to sacrifice a bit of performance. Many people say 'performance is important,' but I question whether there are really that many tasks where performance matters that much

p.s This is my post about the difference between row-major and column-major order.(https://www.makonea.com/en-US/blog/why-c-family-nested-for-l...)

Ctran and Fortran look similar if you ignore much of the flexibility of C and help the optimizer out re memory overlap. Wave the checkbook and you’ll have programmers. Way easier than COBOL.