Julia Language Seeks To Be the C For Numerical Computing

concealment writes in with an interview with a creator of the (fairly) new language Julia designed for number crunching. Quoting Infoworld: "InfoWorld: When you say technical computing, to what type of applications are you specifically referring? Karpinski: It's a broad category, but it's pretty much anything that involves a lot of number-crunching. In my own background, I've done a lot of linear algebra but a fair amount of statistics as well. The tool of choice for linear algebra tends to be Matlab. The tool of choice for statistics tends to be R, and I've used both of those a great deal. But they're not really interchangeable. If you want to do statistics in Matlab, it's frustrating. If you want to do linear algebra in R, it's frustrating. InfoWorld: So you developed Julia with the intent to make it easier to build technical applications? Karpinski: Yes. The idea is that it should be extremely high productivity. To that end, it's a dynamic language, so it's relatively easy to program, and it's got a very simple programming model. But it has extremely high performance, which cuts out [the need for] a third language [C], which is often [used] to get performance in any of these other languages. I should also mention NumPy, which is a contender for these areas. For Matlab, R, and NumPy, for all of these options, you need to at some point drop down into C to get performance. One of our goals explicitly is to have sufficiently good performance in Julia that you'd never have to drop down into C." The language implementation is licensed under the GPL. Lambda the Ultimate has a bit of commentary on the language, and an R programmer gives his two cents on the language.

Comments

Sage

[donaggie03]

I use Sage quite a bit. It's basically a wrapper for almost all the mathematics software available. http://www.sagemath.org/ While you still need to drop down to C for great performance, it solves a lot of the interoperability issues discussed. In other words, take the example from the summary: from Sage, you can call Matlab commands and then immediately use the results with R commands. Sage works through a web browser, and it's based on Python, which is a plus.

Numerical Python

[Dr. Tom]

Robust, mature, fast, easy to use, side-by-side with .m it wins hands down, really no comparison, use Python.
Cython if you need to make it faster for the %5 of code that is too slow.

import numpy
import pylab

Re:Fortress

[dougmc]

The weakness of FORTRAN is that it entirely misses out of 50+ years of research and innovation in programming languages.

OK, maybe the original version of Fortran, the one made 50+ years ago, missed out on "50+ years of research and innovation in programming languages", but you are aware that Fortran has been updated since then, right?

Fortran now includes a great number of the improvements to programming languages made since then. But don't take my word for it -- check out Wikipedia's page on it. I picked Fortran 90 as a starting point, but there's been many versions of Fortran made since the first, with new features (often coming from other languages) being added all the time.

And not only is Fortran still being actively developed, but the library of well tested and optimized numerical computing code already written it it is massive.

I'm not saying that there's not room for a new language, and certainly, Fortran doesn't have all the features of some new languages, but your claim that Fortran "entirely misses out of 50+ years of research and innovation in programming languages" is completely and utterly wrong.

I should also mention that they stopped calling it FORTRAN in all caps back in 1990 or so when Fortran 90 came out. Now it's just Fortran. But even the venerable FORTRAN 77 benefited greatly from programing language developments available at the time.

Re:FORTRAN?

[gl4ss]

well.. apparently this "language" has modern fortran built in.

just open the link. there's some stats there. I don't envision huge popularity for this though.. unless he integrates/develops it into a fullblown mathlab competitor(that javascript does mandelbrot almost as fast is kind if peculiar though..). not as peculiar as "pi sum" bench being faster on javascript and julia than c++.

"The library, mostly written in Julia itself, also integrates mature, best-of-breed C and Fortran libraries for linear algebra, random number generation, FFTs, and string processing. "

Re:FORTRAN?

[plopez]

Ummmm..... Fortran has supported free form format since ummmm..... 1993. All modern Fortran compilers I know of support both the old and the new formats. Cast off your old prejudices and learn what a modern programming language Fortran '08 really is.

BTW, I believe using the "FORTRAN" has been deprecated since the 70's. It is now "Fortran".