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How many people are writing new Fortran code? I know it has its niches, and is used in some popular numerical Python packages, but what about outside that? I've

How many people are writing new Fortran code? I know it has its niches, and is used in some popular numerical Python packages, but what about outside that? I've seen it mentioned in a few job postings for government contractors or "scientific programmer" (more of a PhD scientist who happens to program) roles, but typically listed in a way that makes it look like an HR person took a list of the tech a company used in the last few decades and make them all listed as requirements.

zwieback 6y ago
I wonder about the same thing. When I graduated in 1985 Fortran was already described more or less like you just did. However, when I recently dug down through the NumPy/SciPy stack to understand some details I saw a lot of Fortran code. Some popular algorithms seem to exist only as Fortran with various language interfaces on top. So I don't think there are very many new projects being started but the presence of so much critical code in Fortran will extend its lifetime some more.
jarvist 6y ago
The vast majority of time on research supercomputers is used in running Fortran codes. (Click on 'languages' https://www.archer.ac.uk/status/codes/ https://www.archer.ac.uk/status/codes/ , this is the UK national facility.) And yes, as you've noticed almost all linear algebra is written in Fortran (BLAS, LAPACK, ScaLAPACK), so no matter what language you've written something to do some useful computation in, it's likely that most of the cycles are spent in Fortran!
atrettel 6y ago
I'm writing new Fortran right now, actually. I know a lot of people who still write Fortran, though all of them work in scientific or engineering fields. I view Fortran as only good for number crunching, but for that purpose it is difficult to beat in many respects. Fortran is very common in supercomputing applications, though C and C++ are also very common. I know a lot of people who view Fortran as antiquated, and I understand their criticisms. I prefer other programming languages in general, but all programming languages are just tools and Fortran is a good tool in some circumstances.
Koshkin 6y ago
The niche is numerical calculations. The strict semantics of the language allows for extremely good optimization of the generated machine code.
ojnabieoot 6y ago
I have not kept up with recent developments, but Fortran has historically been noticeably faster than even C/C++ for numerical computations. This difference used to be quite stark due to limitations in C itself: http://www.ibiblio.org/pub/languages/fortran/ch1-2.html http://www.ibiblio.org/pub/languages/fortran/ch1-2.html (see " b) The design of FORTRAN allows maximal speed of execution:") I think things have gotten better in C, e.g. with C99's "restrict" keyword, along with general improvements in C compilers, but for a long while Fortran had a clear upper hand when it came to allocating and manipulating large arrays of floats. Outside of the language specification, I would wager that many supercomputers have better-optimized Fortran compilers than C compilers for this reason. And even if in principle C and Fortran can execute equally performant numeric code, Fortran's historic superiority has created a great deal of high-quality legacy Fortran code that nobody feels an urgent need to port into C (which would be tedious, expensive, and risky work). In the modern day: R uses a standard Fortran BLAS implementation, as do many other libraries and platforms (NumPy, Numerics.NET, etc). LAPACK is also widely used for low-level numerical linear algebra: https://github.com/Reference-LAPACK/lapack https://github.com/Reference-LAPACK/lapack Intel also maintains a BLAS implementation. So there's still a healthy need for a (small) community of Fortran programmers, it's not all about maintaining 70s legacy code. Very different than the situation with COBOL.
- gnufx 6y ago
  If you use the reference BLAS routines that ship with R, you're losing an order of magnitude serial performance on relevant operations. (The majority of Intel MKL surely isn't written in Fortran, like OpenBLAS and BLIS.)
- gnufx 6y ago
  Aspects of Fortran favour it over C even when restrict is used, e.g. as mentioned in https://news.ycombinator.com/item?id=23124451 https://news.ycombinator.com/item?id=23124451
- jjdredd 6y ago
  > Fortran has historically been noticeably faster than even C/C++ for numerical computations Nowadays: faster - maybe, noticeably - I doubt it. > supercomputers have better-optimized Fortran compilers than C compilers I don't know about supercomputer compilers but mainstream compilers usually have the same backend for FORTRAN and C (as well as other implemented languages). > created a great deal of high-quality legacy Fortran code that nobody feels an urgent need to port into C Optimized and tested FORTRAN code - maybe, but not high-quality. I've seen some of it, FORTRAN makes it difficult to write readable, maintainable code. For this reason even scientist are rewriting their tools and libraries (that also require good performance) in C++: for example see Pythia, GEANT, cern root.
leephillips 6y ago
Good replies already. Also note that modern Fortran is an array language like Julia or Numpy, with parallel processing built in.
haiguise 6y ago
See for example MESA http://mesa.sourceforge.net/index.html http://mesa.sourceforge.net/index.html an open source set of modules for software experiments in stellar astrophysics, which is still actively developed.
chris1993 6y ago
It's used quite widely in bioinformatics, at least in Australia. Over the last ten years I've written numerous web apps for scientists to provide user-friendly interfaces to their fortran command-line programs.
- itcrowd 6y ago
  What library or framework do you use to interface between the web service and Fortran?
  - chris1993 6y ago
    Mostly it's been Perl with IPC::Run3 which handles forking the Fortran executable and all the plumbing of stdout, stdin, stderr.
neurostimulant 6y ago
People in meteorological community still pretty much use fortran for everything, from input data processing, the atmospheric models themselves, to visualization. They already did distributed computing with fortran decades before kubernetes is a thing. Same with air pollution modeling (which is a subset of meteorology but handled by environmental engineers). I used to dabble with those models when I was studying environmental engineering.
jabirali 6y ago
When I did a PhD in theoretical/numerical physics, I wrote most of my code in Fortran. That was started ~5 years ago. Basically, I was starting to port some some Matlab code I had written to C/C++ to speed it up, but the most convenient solver for the differential equations I was dealing with outside of Matlab turned out to be a Fortran library. So I started learning basic Fortran in order to write a small C++ wrapper around that library, but ended up liking Fortran much better than C++, so I kept using it throughout my PhD. Note that modern Fortran (2008+) is not at all like the infamous Fortran 77. There's no reason to write GOTO spaghetti; you have object-orientation, built-in support for complex numbers and matrices, array slicing, pointers, polymorphism, pure functions, vectorized ("elementary") functions and subroutines, and other modern features. There are even some unique features like the "associate" keyword that I sorely miss when doing mathematical programming in any other language (mostly Python these days). Because e.g. the built-in arrays "know how big they are", error messages are typically more helpful than debugging numerical C++ too.
xioxox 6y ago
We're writing it for the ground processing for data from a new space telescope. Personally, I wish I was writing C++ or Python, but it does allow scientists to start writing code much more easily than C/C++ does, though Python is now more familiar to younger scientists than Fortran. Python has the downside of a lack of stability, however. Fortan is pretty painful to write in. The lack of an STL means writing algorithms yourself. There is no good set of libraries, so you have to write more stuff yourself. The string support is horrendous. Most of the language is based around clumsy fixed size strings. I wish they would add a new flexible string type. The compiler quality is not up to C++ standards. My code currently has some nasty workarounds for problems in gfortran. It's not good to keep discovering compiler bugs. I also find it's much vaulted numerical capabilities overstated. Vectorization only works in simple cases. You can't drop down to using SIMD wrappers to fix this. It's nice to be able to pass arrays around more easily than C, however. A good C++ array library would be better, but that would require everyone to agree on one.
- pjmlp 6y ago
  That is you problem right there, gfortran instead of something like Intel or PGI.
  - xioxox 6y ago
    That might fix the compiler quality and vectorization, but it doesn't fix the lack of library and terrible string support. Edit: plus to ship our code to others requires a free good quality compiler. In the C/C++ world, that is standard. In fortran, that is not the case.
    - pjmlp 6y ago
      Sure it does, because they also come with high quality libraries. Regarding C and C++ compilers, for the same reasons most high performance HPC computers use Intel, IBM, PGI compilers instead of plain gcc or clang.
      - atsider 6y ago

zwieback 6y ago

I wonder about the same thing. When I graduated in 1985 Fortran was already described more or less like you just did. However, when I recently dug down through the NumPy/SciPy stack to understand some details I saw a lot of Fortran code. Some popular algorithms seem to exist only as Fortran with various language interfaces on top. So I don't think there are very many new projects being started but the presence of so much critical code in Fortran will extend its lifetime some more.

jarvist 6y ago

The vast majority of time on research supercomputers is used in running Fortran codes. (Click on 'languages' https://www.archer.ac.uk/status/codes/ https://www.archer.ac.uk/status/codes/ , this is the UK national facility.) And yes, as you've noticed almost all linear algebra is written in Fortran (BLAS, LAPACK, ScaLAPACK), so no matter what language you've written something to do some useful computation in, it's likely that most of the cycles are spent in Fortran!

atrettel 6y ago

I'm writing new Fortran right now, actually. I know a lot of people who still write Fortran, though all of them work in scientific or engineering fields. I view Fortran as only good for number crunching, but for that purpose it is difficult to beat in many respects. Fortran is very common in supercomputing applications, though C and C++ are also very common. I know a lot of people who view Fortran as antiquated, and I understand their criticisms. I prefer other programming languages in general, but all programming languages are just tools and Fortran is a good tool in some circumstances.

Koshkin 6y ago

The niche is numerical calculations. The strict semantics of the language allows for extremely good optimization of the generated machine code.

ojnabieoot 6y ago

I have not kept up with recent developments, but Fortran has historically been noticeably faster than even C/C++ for numerical computations. This difference used to be quite stark due to limitations in C itself: http://www.ibiblio.org/pub/languages/fortran/ch1-2.html http://www.ibiblio.org/pub/languages/fortran/ch1-2.html (see " b) The design of FORTRAN allows maximal speed of execution:") I think things have gotten better in C, e.g. with C99's "restrict" keyword, along with general improvements in C compilers, but for a long while Fortran had a clear upper hand when it came to allocating and manipulating large arrays of floats. Outside of the language specification, I would wager that many supercomputers have better-optimized Fortran compilers than C compilers for this reason. And even if in principle C and Fortran can execute equally performant numeric code, Fortran's historic superiority has created a great deal of high-quality legacy Fortran code that nobody feels an urgent need to port into C (which would be tedious, expensive, and risky work). In the modern day: R uses a standard Fortran BLAS implementation, as do many other libraries and platforms (NumPy, Numerics.NET, etc). LAPACK is also widely used for low-level numerical linear algebra: https://github.com/Reference-LAPACK/lapack https://github.com/Reference-LAPACK/lapack Intel also maintains a BLAS implementation. So there's still a healthy need for a (small) community of Fortran programmers, it's not all about maintaining 70s legacy code. Very different than the situation with COBOL.

gnufx 6y ago
If you use the reference BLAS routines that ship with R, you're losing an order of magnitude serial performance on relevant operations. (The majority of Intel MKL surely isn't written in Fortran, like OpenBLAS and BLIS.)
gnufx 6y ago
Aspects of Fortran favour it over C even when restrict is used, e.g. as mentioned in https://news.ycombinator.com/item?id=23124451 https://news.ycombinator.com/item?id=23124451
jjdredd 6y ago
> Fortran has historically been noticeably faster than even C/C++ for numerical computations Nowadays: faster - maybe, noticeably - I doubt it. > supercomputers have better-optimized Fortran compilers than C compilers I don't know about supercomputer compilers but mainstream compilers usually have the same backend for FORTRAN and C (as well as other implemented languages). > created a great deal of high-quality legacy Fortran code that nobody feels an urgent need to port into C Optimized and tested FORTRAN code - maybe, but not high-quality. I've seen some of it, FORTRAN makes it difficult to write readable, maintainable code. For this reason even scientist are rewriting their tools and libraries (that also require good performance) in C++: for example see Pythia, GEANT, cern root.

leephillips 6y ago

Good replies already. Also note that modern Fortran is an array language like Julia or Numpy, with parallel processing built in.

haiguise 6y ago

See for example MESA http://mesa.sourceforge.net/index.html http://mesa.sourceforge.net/index.html an open source set of modules for software experiments in stellar astrophysics, which is still actively developed.

chris1993 6y ago

It's used quite widely in bioinformatics, at least in Australia. Over the last ten years I've written numerous web apps for scientists to provide user-friendly interfaces to their fortran command-line programs.

itcrowd 6y ago
What library or framework do you use to interface between the web service and Fortran?
- chris1993 6y ago
  Mostly it's been Perl with IPC::Run3 which handles forking the Fortran executable and all the plumbing of stdout, stdin, stderr.

neurostimulant 6y ago

People in meteorological community still pretty much use fortran for everything, from input data processing, the atmospheric models themselves, to visualization. They already did distributed computing with fortran decades before kubernetes is a thing. Same with air pollution modeling (which is a subset of meteorology but handled by environmental engineers). I used to dabble with those models when I was studying environmental engineering.

jabirali 6y ago

When I did a PhD in theoretical/numerical physics, I wrote most of my code in Fortran. That was started ~5 years ago. Basically, I was starting to port some some Matlab code I had written to C/C++ to speed it up, but the most convenient solver for the differential equations I was dealing with outside of Matlab turned out to be a Fortran library. So I started learning basic Fortran in order to write a small C++ wrapper around that library, but ended up liking Fortran much better than C++, so I kept using it throughout my PhD. Note that modern Fortran (2008+) is not at all like the infamous Fortran 77. There's no reason to write GOTO spaghetti; you have object-orientation, built-in support for complex numbers and matrices, array slicing, pointers, polymorphism, pure functions, vectorized ("elementary") functions and subroutines, and other modern features. There are even some unique features like the "associate" keyword that I sorely miss when doing mathematical programming in any other language (mostly Python these days). Because e.g. the built-in arrays "know how big they are", error messages are typically more helpful than debugging numerical C++ too.

xioxox 6y ago

We're writing it for the ground processing for data from a new space telescope. Personally, I wish I was writing C++ or Python, but it does allow scientists to start writing code much more easily than C/C++ does, though Python is now more familiar to younger scientists than Fortran. Python has the downside of a lack of stability, however. Fortan is pretty painful to write in. The lack of an STL means writing algorithms yourself. There is no good set of libraries, so you have to write more stuff yourself. The string support is horrendous. Most of the language is based around clumsy fixed size strings. I wish they would add a new flexible string type. The compiler quality is not up to C++ standards. My code currently has some nasty workarounds for problems in gfortran. It's not good to keep discovering compiler bugs. I also find it's much vaulted numerical capabilities overstated. Vectorization only works in simple cases. You can't drop down to using SIMD wrappers to fix this. It's nice to be able to pass arrays around more easily than C, however. A good C++ array library would be better, but that would require everyone to agree on one.

pjmlp 6y ago
That is you problem right there, gfortran instead of something like Intel or PGI.
- xioxox 6y ago
  That might fix the compiler quality and vectorization, but it doesn't fix the lack of library and terrible string support. Edit: plus to ship our code to others requires a free good quality compiler. In the C/C++ world, that is standard. In fortran, that is not the case.
  - pjmlp 6y ago
    Sure it does, because they also come with high quality libraries. Regarding C and C++ compilers, for the same reasons most high performance HPC computers use Intel, IBM, PGI compilers instead of plain gcc or clang.
    - atsider 6y ago