31–40 of 211 posts
No Windows support, really ?!
That's pretty common for new language implementations - Node.js was around for a couple of years before the Windows port was ready. To be honest, if you're targeting early adopters of a programming language Linux and Mac support is probably a lot more important than Windows. Smart Windows users can always run Linux in a VM.
It's about standards, but it still applies.
Much praise!! These guys have incredibly good taste. Almost every single thing I can think of that I want in a programming language, they have it. All in the one language! The fact that it has parametric types, parametric polymorphism, macros, performance almost as good as C, good C/Fortran interop, 64 bit integers and an interactive REPL all in the one language just blows my mind. I wasn't able to tell if it is poss…
I think they are aiming for smooth transition for MATLAB users. They also have 1-index based arrays as opposed to 0-index .
No Windows support, really ?!
I wonder what they think about or have learned from http://en.wikipedia.org/wiki/Fortress_(programming_language) , another recent-ish attempt to deliver a modern and powerful scientific programming language. Personally I'm a little wary of being ghettoised into something overly domain-specific for scientific/numerical computing. Really good interop may mitigate that -- something which can navigate the unholy mix of C…
From the article: "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."
Looks very much like a python without the legacy and a touch of ruby, ipython as the default shell, better multiprocessing, better os/system access, decorators and mathematics. Nice clear documentation too. Given how similar to python they are their main competitor is pypy, which isn't too far behind them in performance I'd suspect (absent from the benchmarks though). I was fully expecting someone to make a non-compa…
fib - roughly the same time as CPython
parse_int - 10x over CPython which is extrapolating to their python vs julia about 20% slower
quicksort - 4x faster than cpython much slower than julia.
pi_sum - 20x faster than cpython, a bit faster than julia?
On a slightly unrelated note - a modified lxml library runs on pypy albeit a lot slower right now.
Cheers, fijal
EDIT: updated formatting
I'm a little worried about some of those benchmarks. They appear to have benchmarked R from a few years back against 2011 Matlab, for instance. In addition, they provide no code used for the benchmarks. That being said, this looks really interesting, and I'm gonna bookmark it for when I have time to examine it properly (after the damn phd is finally submitted).
They do link to the code: https://github.com/JuliaLang/julia/tree/master/test/perf . It doesn't look like a very reliable microbenchmark - run test x 5 times - but it should provide a useful starting point if you want to run your own.
I wonder what they think about or have learned from http://en.wikipedia.org/wiki/Fortress_(programming_language) , another recent-ish attempt to deliver a modern and powerful scientific programming language. Personally I'm a little wary of being ghettoised into something overly domain-specific for scientific/numerical computing. Really good interop may mitigate that -- something which can navigate the unholy mix of C…
Earlier quoted context omitted.
I think they are aiming for smooth transition for MATLAB users. They also have 1-index based arrays as opposed to 0-index .
It would certainly be nice if there was an option to use 0 based indices in blocks of code. It's understandable in that they are pitching at the technical community, and many mathematical papers and books are written with 1 based indices. But I am a mathematician who prefers 0 based indices.