Re:Why physicists still use Fortran
by m_mueller on Monday December 19, 2016 @07:21PM
(#13216272)
I'm in a similar situation as you, albeit with a large Fortran codebase that needs to stay - therefore I chose to write a transpiler in python that enables a Fortran codebase to be parallelised on CPU and GPU - see my profile link.
[ Parent
| on HN ]
Hybrid-Fortran looks like an elegant workaround for an ugly problem, kudos for dealing with the storage order as well.
Ultimately, it seems to me the only way to justify using Fortran for scientific computing nowadays (apart from legacy issues, of course) is if you have no intention of ever using accelerators and absolutely must have optimal CPU performance. NVidia and, to a lesser extent, Intel/AMD could have maintained the language advantages Fortran offers in the accelerator space as well, but chose not to, and now you need solutions like this coupled with proprietary compilers just to approach CUDA C / OpenCL performance. Legacy projects will be around for decades, of course, but for new things I think C++ is/will increasingly be the default choice.