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.

FORTRAN?

[TWX]

From wikipedia: "FORTRAN is a general-purpose, procedural, imperative programming language that is especially suited to numeric computation and scientific computing." Sounds to me like unless there's a particular weakness in FORTRAN that doesn't lend itself to workarounds or repair in newer versions of the language, there's already a numeric computation and scientific programming language that's well documented, mature, and widely distributed.

It's the packages stupid!

[Hatta]

What will make or break this language is the availability of addon packages for it. A lot of people who use R don't do much coding themselves. They read in data, preprocess it a little bit, and then apply one of the packages found in CRAN.

CRAN is like CPAN, but for R instead of Perl. And we can expect similar behavior from them. Perl probably wouldn't be anyone's first choice for a project these days, but the size and scope of CPAN makes it really really easy to benefit from the work of others. This is a lot of inertia, and a big reason why Perl is still used when newer languages have significant advantages.

There's so much software, particularly academic software, implemented in R that I just don't see it going away. e.g. the entire Bioconductor suite is implemented in R. Just about any bioinformatics paper you pick at random will refer to, if not contain R code.

How much work are we going to have to reimplement if we want everyone to use the one true numerical programming language? And if we don't want that, isn't it just contributing to fragmentation?

Re:FORTRAN?

[Anonymous Coward]

Second that. Modern FORTRAN kicks some serious butt and has a huge user and support base. Language snobs dismiss it as antiquated but they're usually referring to versions of the language that haven't been used since the 1980's. There are good reasons that current HPC developers use mostly FORTRAN and C, like good support for parallalization, global memory functions for clustering, and efficient compilers.

It's great that people make new tools and share them with others, but many times that effort could be put into making existing good tools even better.

Fortress

[l00sr]

The weakness of FORTRAN is that it entirely misses out of 50+ years of research and innovation in programming languages. My gripe with Julia is that it seems to be based on Common Lisp, which itself is pretty old at this point. Fortress [wikipedia.org] seems like a better Fortran replacement to me, since it is actually based on modern functional programming languages. I mean, really, what's the point of releasing a new language based on outdated tech when better alternatives are available?

Re:The "C" for some field?

[jythie]

It could be argued that Ada not only had a huge effect (many language features we now thing of as standard came from Ada), but is still in use in many places, so I would call it pretty successful.

Re:FORTRAN?

[ahoffer0]

I attended SC11 (sc11.supercomputing.org) last year. FORTRAN is still the work horse of (large-scale) numerical computing. C/C++ are popular. So are MATLAB and R. They was even a NumPy tutorial and some sessions on emerging languages like Chapel. But FORTRAN was king.

I thought this was an interesting thread about FORTRAN v. C -- http://www.physicsforums.com/showthread.php?t=169974 [physicsforums.com]

Off-topic:When it came to programming, the general drift of the conference was not toward new languages, but toward adding meta-information, vis-a-vi compiler directives.