Urrgh. This came through on my feed earlier today, and I left a comment on it. While javascript is fast (and can be used for many things), the real issue with using it for stats is the lack of libraries. More specifically, as far as I know it cannot interface with Fortran. That's a death knell for any statistical programming language, as it means no LAPACK, and no-one (sane) is going to rewrite all of those linear al…
Urrgh. This came through on my feed earlier today, and I left a comment on it. While javascript is fast (and can be used for many things), the real issue with using it for stats is the lack of libraries. More specifically, as far as I know it cannot interface with Fortran. That's a death knell for any statistical programming language, as it means no LAPACK, and no-one (sane) is going to rewrite all of those linear al…
> no-one (sane) is going to rewrite all of those linear algebra libraries
Is it because it would take a long time or because it's inherently hard?
Urrgh. This came through on my feed earlier today, and I left a comment on it. While javascript is fast (and can be used for many things), the real issue with using it for stats is the lack of libraries. More specifically, as far as I know it cannot interface with Fortran. That's a death knell for any statistical programming language, as it means no LAPACK, and no-one (sane) is going to rewrite all of those linear al…
> no-one (sane) is going to rewrite all of those linear algebra libraries Is it because it would take a long time or because it's inherently hard?
It's easy enough to do a basic implementation, but getting good numerical stability and good performance is hard (and in Javascript, it's pretty much impossible with current implementations). See also the matrix multiplication benchmarks in the post: JS is 60x slower than Matlab, even though it's already using typed arrays. A naive triply nested for loop in C would probably perform similarly to the JS, which is to say a lot slower than something optimized for the characteristics of the processor (number of registers, vectorized floating point and cache sizes mostly, I'm not sure if Matlab is using multiple cores here).
Urrgh. This came through on my feed earlier today, and I left a comment on it. While javascript is fast (and can be used for many things), the real issue with using it for stats is the lack of libraries. More specifically, as far as I know it cannot interface with Fortran. That's a death knell for any statistical programming language, as it means no LAPACK, and no-one (sane) is going to rewrite all of those linear al…
I don't know much about javascript implementations. Is there no foreign-function interface available ? If you can interface with C you can interface with Fortran (with a little extra work).
Urrgh. This came through on my feed earlier today, and I left a comment on it. While javascript is fast (and can be used for many things), the real issue with using it for stats is the lack of libraries. More specifically, as far as I know it cannot interface with Fortran. That's a death knell for any statistical programming language, as it means no LAPACK, and no-one (sane) is going to rewrite all of those linear al…
Ergo, JavaScript isn't the fasted language for that matters, because matrix multiplication is too important.
or there is no dedicated library for matrix multiplication compared to the other languages..
More to the point - who cares. All these languages are hopelessly slow. If performance matters do it in a performant language like C++, C or FORTRAN. If it does not matter - then it does not matter and so stop going on about it.