Re:NASA: High Performance Fast Computing Challenge
by rspeer on Friday May 05, 2017 @03:17AM
(#14271681)
Eh. It's not too much of a strawman. I was under the apparently incorrect impression that there's some Fortran in NumPy, as the NumPy codebase is where f2py comes from. But it could very well not be used in any NumPy operations.
It's still rather important in SciPy.
Re:NASA: High Performance Fast Computing Challenge
by AstralStorm on Friday May 05, 2017 @03:02PM
(#14275981)
It was replaced specifically because people were complaining that they had to install gfortran. Not for any performance reasons.
Fortran is not the same in 17 as it was in 77. They are different languages.
> I don't have a hatred for Fortran. I just don't see any job where I'd prefer using Fortran over a more-sane alternative. Fortran was great for 77 but isn't great for 17.
Others do. Plenty of scientific programmers consider Fortran to be a perfectly sane language.
> I mean... when people use Fortran they usually don't even make use of Fortran 90's abstraction features. It's insane.
False. My group does.
> > Of course people like to use Python, but you don't get to use Python instead of Fortran. That would be incredibly slow. You use Python and Fortran. For example, you use NumPy and SciPy, which make Python a great high-level platform for numerical computing because they wrap large amounts of Fortran code.
> You are mistaken. NumPy does not contain Fortran in it's code base. SciPy does but it only makes up 25% of the SciPy code base. I have no doubt that within the next 20-50 years that will slowly be removed bit by bit. Wrapping a legacy library is the first step to replacing it. Once you remove the hard dependancy you will remove
GP never said numpy contained Fortran in its code base, that was a strawman you added. Of course, that is what it means for numpy to provide a high-level platform for numerical computing: it means wrapping current code.