Julia seems very attractive with clear syntax and really fast! I wish you best!
I think Julia should be very nice in server-side development.
Julia Computing Raises $4.6M in Seed Funding
51–60 of 134 posts
Re: Julia Computing Raises $4.6M in Seed Funding
#52Earlier quoted context omitted.
How do they sell the non-GPL version? Just replace the GPL libraries like FFTW with inferior replacements like FFTPACK?
The non-GPL version uses Intel's proprietary Math Kernel Library (MKL) for FFTs, linear algebra, etc.
Huh, so did MKL just reimplement FFTW? I see that they have an interface for it. Or maybe they bought a GPL exception to FFTW.
Re: Julia Computing Raises $4.6M in Seed Funding
#53I wish them all the best. Julia seems to a good idea -- a high performance language with easy syntax (easy for Python users to jump to Julia), very good features for threading/multiprogramming, good type system... ...here it seem like any other modern language, until you see that Julia has something that many other languages lack: true macros (true metaprogramming.) A big feature. And multiple dispatch on all functio…
Julia is a great language, but it is still focused on the numerical computing world and is not "1.0" (language and API's are not locked down). I wouldn't really compare it to Go or Rust at this point. Go is focused on building services at its core (e.g. external event driven workflows). Aka microservices. Rust is focused on being a "traditional" systems programming language. Things like web browsers (duh), office sui…
If you take a look at the features (esp. macros and multiple dispatch) you can see that is readily extensible for lots of applications. Thus the reason it is also sold as a "general purpose" language.
Additonally, the very good support for threading and multiprocessing means it has a good future with services, async IO, and with event-loop web servers (a la node.js and friends).
Finally, the focus on fast speed for numerical computation is particularly suited to games (as is the support for threading).
Re: Julia Computing Raises $4.6M in Seed Funding
#54I wish them all the best. Julia seems to a good idea -- a high performance language with easy syntax (easy for Python users to jump to Julia), very good features for threading/multiprogramming, good type system... ...here it seem like any other modern language, until you see that Julia has something that many other languages lack: true macros (true metaprogramming.) A big feature. And multiple dispatch on all functio…
For non-CS scientific computing users, "a high performance language with easy syntax" is a big feature.
Re: Julia Computing Raises $4.6M in Seed Funding
#55Julia frustrates me. I was in a mathematical modelling sphere, so I learned the language basics years ago and immediately fell in love (multiple dispatch, optional types, broadcasting, ...). But I couldn't get approvals at work to push it, because it was immature. Then a month later, all my code broke. I rewrote it using new APIs. It broke again. I know they reserved the right to make breaking changes up until 1.0, b…
An alternative would be getting your bosses approve for you to use Common Lisp.
It is mature (30+ years in use, rock solid ANSI standard), many compilers available for many plataforms, highly portable code, multiple dispatch (CLOS is arguably the most powerful object oriented system available), you can also very easily call C libraries with CFFI and there is portable support for threading...
...and well written CL code will approach Fortran and C in speed, at least with SBCL which is a free, popular compiler.
You can also compile to the JVM and to the LLVM, and if you need pro support for it, there is LispWorks and Franz Inc. Ah, and with ABCL you can also easily call java libraries, if you need to.
Re: Julia Computing Raises $4.6M in Seed Funding
#56Julia frustrates me. I was in a mathematical modelling sphere, so I learned the language basics years ago and immediately fell in love (multiple dispatch, optional types, broadcasting, ...). But I couldn't get approvals at work to push it, because it was immature. Then a month later, all my code broke. I rewrote it using new APIs. It broke again. I know they reserved the right to make breaking changes up until 1.0, b…
My girlfriend does incredibly complex modeling (she's a computational geneticist). From my limited understanding, it sounds like you may have some of the same challenges that she does. Do you think Python and Go are more suited to that domain than R or Julia?
R is very, very slow compared to all the other programming platforms (including Ruby, a nice language but with some of the slowest implementations out there).
R syntax is very unlike most programming languages so jumping to other languages can feel strange.
Python with Numpy, SciPy and Pandas, is the current widespread alternative to R and a good starting point. Recommended!!
Re: Julia Computing Raises $4.6M in Seed Funding
#57I've heard good reviews of the language here. So I've no doubt about its technical capabilities. However, funding might suppress the ability to make breaking changes.. which I believe are pretty good until 1.0 or so. On the business side, will we end up with (hopefully) a better, cheaper Matlab?
$1500 for JuliaPro - maybe not?
Re: Julia Computing Raises $4.6M in Seed Funding
#58I wish them all the best. Julia seems to a good idea -- a high performance language with easy syntax (easy for Python users to jump to Julia), very good features for threading/multiprogramming, good type system... ...here it seem like any other modern language, until you see that Julia has something that many other languages lack: true macros (true metaprogramming.) A big feature. And multiple dispatch on all functio…
For non-CS scientific computing users, "a high performance language with easy syntax" is a big feature.
Exactly, that's why I think Julia is a good idea.
For scientific users used to R or Python, the performance should knock their socks off. (But users doing their work in C, C++ or Fortran will probably see little or no improvement).
Re: Julia Computing Raises $4.6M in Seed Funding
#59Earlier quoted context omitted.
The non-GPL version uses Intel's proprietary Math Kernel Library (MKL) for FFTs, linear algebra, etc.
Huh, so did MKL just reimplement FFTW? I see that they have an interface for it. Or maybe they bought a GPL exception to FFTW.
They expose an FFTW-compatible API, but as far as I know it's an independent implementation.
Re: Julia Computing Raises $4.6M in Seed Funding
#60Any suggestions for learning Julia (detailed projects to follow) for fluent pythonistas?