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Why Scientists Are Still Using FORTRAN in 2014
New submitter InfoJunkie777 (1435969) writes "When you go to any place where 'cutting edge' scientific research is going on, strangely the computer language of choice is FORTRAN, the first computer language commonly used, invented in the 1950s. Meaning FORmula TRANslation, no language since has been able to match its speed. But three new contenders are explored here. Your thoughts?"
A: Legacy code.
Scientists work in formulas. Fortran was designed to do things naturally that don't fit into C/C++, Python, whatever.
Why not?
Actually that is a serious question, for these sorts of applications there seems to be no significant downside.
When you go to any place where 'cutting edge' scientific research is going on, strangely the computer language of choice is FORTRAN, the first computer language commonly used, invented in the 1950s.
Perhaps it's still the best tool for the job. Why is that strange? Old(er) doesn't necessarily mean obsolete -- and new(er) doesn't necessarily mean better.
It must have been something you assimilated. . . .
Legacy code that has been carefully checked to give correct results under a wide range of conditions.
A: Legacy code.
AKA battle hardened libraries that work as advertised.
And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
Precision is important in scientific discourse. Latin isn't a language with creeping grammar and jargon. It's sorta what Esperanto only wished it could ever be.
A big problem is that C and C++ don't have real multidimensional arrays. There are arrays of arrays, and fixed-sized multidimensional arrays, but not general multidimensional arrays.
FORTRAN was designed from the beginning to support multidimensional arrays efficiently. They can be declared, passed to subroutines, and iterated over efficiently along any axis. The compilers know a lot about the properties of arrays, allowing efficient vectorization, parallization, and subscript optimization.
C people do not get this. There have been a few attempts to bolt multidimensional arrays as parameters or local variables onto C, (mostly in C99) but they were incompatible with C++, Microsoft refused to implement them, and they're deprecated in the latest revision of C.
Go isn't any better. I spent some time trying to convince the Go crowd to support multdimensional arrays properly. But the idea got talked to death and lost under a pile of little-used nice features.
Firstly... 10^-15 is WAY beyond what most scientific codes care about. Most nonlinear finite-element codes generally shoot for convergence tolerances between 1e-5 and 1e-8. Most of the problems are just too hard (read: incredibly nonlinear) to solve to anything beyond that. Further, 1e-8 is generally WAY beyond the physical engineering parameters for the problem. Beyond that level we either can't measure the inputs, have uncertainty about material properties, can't perfectly represent the geometry, have discretization error etc., etc. Who cares if you can reproduce the exact same numbers down to 1e-15 when your inputs have uncertainty above 1e-3??
Secondly... lots of the best computational scientists in the world would disagree:
http://www.openfoam.org/docs/u...
http://libmesh.sourceforge.net...
http://www.dealii.org/
http://eigen.tuxfamily.org/ind...
http://trilinos.sandia.gov/
I could go on... but you're just VERY wrong... and there's no reason to spend more time on you...
People using existing Fortran code are interested in the RESULTS of the computation, not whether the code is modern or has the latest bells and whistles. Programmers forget that the ultimate goal is for someone to USE the program. I wrote a program in CDC Fortran 77 in 1978 that's still being used, Why? Because it does the job.
My previous supervisor decided to fork our Fortran code for performing quantum mechanical calculations. We'd worked on it for more than half a decade and it was world-class.
.xml .xml), and it only compiles after a lot of work
... and I feel the same way about CS graduates and Fortran. They have no idea about the physics or maths involved (which is the difficult part), so the do the only thing they know which is to 'modernize' everything, making it into an incomprehensible, ungodly mess.
He handed it over to a computer science graduate (i.e. a non-physicist) who really liked all the modern trends in CS. Now, five years later:
1. the tarball is an order of magnitude larger
2. the input files are now all impenetrable
3. the code requires access to the outside (not possible on many superclusters)
4. he re-indented everything for no apparent reason
5. the variable names were changed, made into combined types and are much longer
6. as a result, the code is basically unreadable and nearly impossible to compare to the original formulae
7. code is duplicated all over the place
8. it now depends on unnecessary libraries (like the ones required to parse
9. it's about four times slower and crashes randomly
10. it generates wrong results in basic cases
To quote Linus Torvalds: "I've come to the conclusion that any programmer that would prefer the project to be in C++ over C is likely a programmer that I really *would* prefer to piss off, so that he doesn't come and screw up any project I'm involved with."
Fortran, apart from being a brilliant language for numerical math, has the added benefit of keeping CS graduates at bay. I'd rather have a physicist who can't program, than a CS type who can.
(Apologies to any mathematically competent computer scientists out there)