Fortran is back on the top 20 TIOBE index list

Post by enriquto » Tue, Apr 06, 2021, 8:48 PM UTC

leephillips wrote: post #31

enriquto wrote: post #27

Earlier quoted context omitted.

None of them seems "tailored" to the job of numerical computation (mostly linear algebra algorithms) like Fortran seems to be. C: it is mostly alright, especially since C99 with VLA and complex numbers. Yet the aliasing rules are a bit annoying, and multi-dimensional arrays, while possible, do not really feel natural. C++: an unholy clusterfuck... I almost ended crazy trying to use it properly. With extreme disciplin…

Have you tried the recently released v.1.6.0 of Julia? Precompilation is dramatically faster. Also, for serious numerical work, startup time is eclipsed by run time, so it tends not to be relevant. I did most of my physics simulations in Fortran, which is a great language for the task, but if I were writing a new simulation code today I would use Julia. It is the only language in the petaflop club that is actually be…

Post by enriquto » Tue, Apr 06, 2021, 9:13 PM UTC

leephillips wrote: post #33

enriquto wrote: post #32

Earlier quoted context omitted.

> Have you tried the recently released v.1.6.0 of Julia? Precompilation is dramatically faster. Yes, I tried it upon its release and, while much faster, the startup time is still dramatically sub-par, especially when loading packages. This means that when I call Julia scripts from makefiles, etc., a considerable amount of running time is spent in re-compiling over and over the same packages. I agree that my usage pat…

I understand. I haven’t tried this myself, but others have had luck, for this use case, in using sysimages: https://julialang.github.io/PackageCompiler.jl/dev/sysimages...

Post by leephillips » Wed, Apr 07, 2021, 6:49 PM UTC

TheRealKing wrote: post #35

leephillips wrote: post #31

Earlier quoted context omitted.

Have you tried the recently released v.1.6.0 of Julia? Precompilation is dramatically faster. Also, for serious numerical work, startup time is eclipsed by run time, so it tends not to be relevant. I did most of my physics simulations in Fortran, which is a great language for the task, but if I were writing a new simulation code today I would use Julia. It is the only language in the petaflop club that is actually be…

Can you elaborate on why it "is actually better to program in than Fortran"?

Post by leephillips » Thu, Apr 08, 2021, 3:07 AM UTC

enriquto wrote: post #37

leephillips wrote: post #36

Earlier quoted context omitted.

The type system and dispatch paradigm provide a powerful method of code and project organization, and facilitate a type of code reuse that you don’t get with Fortran: the ability to pull other people packages into my project and use their types and methods. That’s one thing. EDIT: Also, having a REPL, and a nice one, is a big deal.

Can you expand a bit on the need for "types" in numerical computation? They sort of seem like overkill to me. The only types I use are float and double, but I could really do with just doubles. OK, admittedly I also need complex numbers (two floats) and ad numbers (however they are represented, typically by two floats also). But that's it . They are numbers after all, associative and commutative. The "dispatch paradi…

Post by ChrisRackauckas » Thu, Apr 08, 2021, 5:22 PM UTC

leephillips wrote: post #38

enriquto wrote: post #37

Earlier quoted context omitted.

Can you expand a bit on the need for "types" in numerical computation? They sort of seem like overkill to me. The only types I use are float and double, but I could really do with just doubles. OK, admittedly I also need complex numbers (two floats) and ad numbers (however they are represented, typically by two floats also). But that's it . They are numbers after all, associative and commutative. The "dispatch paradi…

I think I have a pretty good answer to your question in this article: https://lwn.net/Articles/834571/ It’s not that other types are “needed”, but that they let you do some pretty powerful things with surprising ease. And the nice thing is that in Julia, you can ignore them. You can just compute with floats or doubles as if the type system doesn’t exist. But it’s there in case you would like, for example, to apply th…