Automatic Differentiation with Julia • Hacker News Board

Re: Automatic Differentiation with Julia

#81

Post by FridgeSeal » Tue, Oct 23, 2018, 10:44 PM UTC

geezerjay wrote: post #18

lucozade wrote: post #15

Earlier quoted context omitted.

> This is too often the attitude of Julia people And it's a good attitude for the Julia people to have. Their target audience is not just (or even mainly) full time developers. They're targeting scientists, statisticians etc. As such, it makes sense for Julia to use conventions that are appropriate to their audience. This pervades the whole of Julia, not just indexing although the latter is exceptionally rich for thi…

> And it's a good attitude for the Julia people to have. Their target audience is not just (or even mainly) full time developers. They're targeting scientists, statisticians etc. I don't see how scientists or staticians would be unable to understand a basic knowledge like zero-based indexing. In fact, zero-based indexing already is widely used in basic areas such as series and sequences. Why are freshmen quite capabl…

Do you know how much easier it is for me to look at the mathematical definition of something and transcribe it (almost) quite literally directly into Julia code because of it's 1 based indexing?

I'll tell you: it's very, very, very easy. And when a language makes things easy, people tend to like it (that's one of the reasons people like Python after all).

Re: Automatic Differentiation with Julia

#82

Post by StefanKarpinski » Tue, Oct 23, 2018, 10:48 PM UTC

mkborregaard wrote: post #34

0-_-0 wrote: post #29

Earlier quoted context omitted.

Contrary to your summary, the quote makes a good case for 0-based indexing, both theoretical and practical. How can an argument based on reason become an argument from authority just because someone well known said it?

That is in fact how an argument becomes an argument from authority. Also, it has become an HN meme to post the Dijkstra comment every single time there's a post mentioning Julia. It's not like it's news to anyone.

Also Dijkstra's arguments are pretty weak and unconvincing. If anyone else had made the same arguments, no one would ever refer to it.

Re: Automatic Differentiation with Julia

#83

Post by ska » Wed, Oct 24, 2018, 6:38 PM UTC

byt143 wrote: post #80

ska wrote: post #76

Earlier quoted context omitted.

Julia is hardly the first (cf some common lisp environments, 20+ years ago). To really get near (say within 2x) of c you need some sort of type annotation or inference of course, and (more importantly) you have to structure your code such that this works, but it's quite do-able. Your code does tend to end up a bit c-like in those performance critical sections, but that's hardly surprising.

>Your code does tend to end up a bit c-like in those performance critical sections, but that's hardly surprising. That isn't true. Closures, higher order functions and fused broadcast array expressions are all very fast except in some corner cases.

I'm not sure we disagree. In my experience you can get "pretty fast" but not "c-like fast" while keeping many language features. The more you chase c-like performance (or even better fortran), the more you start restructuring things in a c-like way. This isn't universal of course, and I don't think it has anything specific to do with c language, just that it is a semi reasonable proxy for hardware architecture (ignoring SIMD).

Anyway, this isn't really Julia specific, and I haven't tried with Julia recently so I may be wrong :)