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Julia 1.0

julialang.org

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Re: Julia 1.0

#301

Post by ChrisRackauckas »

mlthoughts2018 wrote: post #242
ChrisRackauckas wrote: post #188

Earlier quoted context omitted.

The points that you mentioned are not relevant to what's in the article. Cython fused types are required to be known at the package's compile time, and that's exactly the point that makes it less composible. Not requiring this is exactly the advantage of Julia which is demonstrated. The article doesn't say Numba cannot do huge scale projects. It just talks about the difference in the compilation strategies. If you re…

The first and second paragraphs under “Point 1” are specifically saying Cython & numba work just as well as Julia for single functions, then saying the problem where they are inferior to Julia is large code bases.

No, I say that Cython and Numba made an engineering tradeoff that reduces their performance and flexibility in exchange for the ability to compile their codes separately, whereas Julia needs to compile dependently. You are the one that is inferring that means it's inferior. There are cases where this ability to easily reduce compile time can be useful, and there are cases where the improved flexibility and performance is useful. But this is the tradeoff that is made in a concrete form, and the value judgement of whether it's a good one is for you to make.

Besides, please show me that 10 lines of Cython that shows it can AD and throw numbers with uncertainties through SciPy's ODE solvers since it's just as flexible as Julia. It should take less characters to write than your previous response!

Re: Julia 1.0

#302

Post by 3rdAccount »

celrod wrote: post #251
StefanKarpinski wrote: post #166

Earlier quoted context omitted.

I do think we should add a code sample prominently on the page, however. I've always find it really frustrating when I look at a programming language and can't get a quick sense of how it looks. If a language looked like, say, APL, I'd be reluctant to use it even if it had an impressive ecosystem. Issue filed: https://github.com/JuliaLang/www.julialang.org/issues/115 .

Racket sounds like a really exciting language, but every time I look at some code...

Racket is having its runtime replaced with the now open-source chez scheme, so it should get faster (my limited understanding) even though it is already faster than a lot of dynamic languages.

Lisp languages do take a long time to get used to.

Re: Julia 1.0

#303

Post by jhayward »

sampo wrote: post #270
jhayward wrote: post #252

Earlier quoted context omitted.

Industry gets professional programmers by hiring people who have been hammering out shipping code in paying products for years, and years, doing support, maintenance, and new product development and research. Grad students may be brilliant but that does not help give them any insight in to what makes a good ecosystem, toolchain, and feature set good.

How was it with the origin and design with Python, NumPy, Matplotlib, Pandas? Were the people who originated these projects in their time any more professional and seasoned than Julia people are currently?

Well, if they'd been as brilliant as the GP indicates there would be no need for Julia, would there?

Re: Julia 1.0

#304

Post by ChrisRackauckas »

Accipitriform wrote: post #182
Svenskunganka wrote: post #168

Earlier quoted context omitted.

The blog mentions that Julia is supposed to be a general purpose language, and not a language built specifically for scientific computing. Is that wrong? The first impression does leave me thinking that using Julia for different programming domains like distributed internet-facing servers or web services is not something it was built for.

> The blog mentions that Julia is supposed to be a general purpose language, and not a language built specifically for scientific computing. Is that wrong? No. Julia is a general purpose language that has so far been mainly focused on scientific and mathematical programming. It's design is probably least friendly to the real-time programming domain (GC based) but it can apparently be used there as well: http://www.ju…

Fun fact, the GC really isn't an issue and instead the opposite issue was found. There had to be callbacks built to slow down the computations for the robotics simulations in order to get it to run at real-time because it was too fast.

https://github.com/JuliaRobotics/RigidBodySim.jl/blob/34ac43...

Notice that this function is purposefully sleeping the differential equation solver in order to slow it down to the exact amount to get the simulation back to real-time.

Re: Julia 1.0

#305

Post by jimbokun »

ChrisRackauckas wrote: post #153
athenot wrote: post #147

As an outsider, I'd like to see somewhere near the home page a few short snippets of code to get a feel for Julia and hopefully show the kind of uses for which it is a natural choice. Nim's home page¹ shows a piece of sample code right at the top. Perl6's page² has a few tabs quickly showing some patterns it's good at. Golang³ has a dynamic interpreter prepopulated with a Hello World. Julia's home page shows a nice f…

For scientific computing, showing the package ecosystem is the most important thing. When you look at this thread, people are asking about dataframes and differential equations. Julia's site reflects this: yes there are things like Pandas, and for plotting, etc.

So show code samples using dataframes and differential equations.

Re: Julia 1.0

#306

Post by KenoFischer »

civility wrote: post #187
KenoFischer wrote: post #156

Earlier quoted context omitted.

Which is why julia doesn't make any assumptions on how your axes are indexed. If you're working in a numerical domain where 0-indexed arrays, or symmetric arrays about the origin, or arbitrarily other transformed axes make sense, just use those.

I understand the argument, but when the default disagrees with your override, there's almost always an impedance mismatch and some pain. It's like being left handed when 99% of the interfaces in the world assume you're right handed. People argue that zero-based is incidental, and that 1-based is the right way because of it's long history in mathematics notation. I would argue that 1-based is incidental, and that zero…

I can understand why you might get the impression, but I'd encourage you to try out julia and see that we're really quite good at using index-agnostic abstractions, so most code doesn't care what your arrays are indexed with. If a certain set of indices make sense in your domain (0-based for FFTs as you say, symmetric indices about the original for image filters, 1-based for just regular lists of things, etc), just use it, and it'll be convenient interactively, but most library code doesn't really think about it that much.

Re: Julia 1.0

#307

Post by stellalo »

kazinator wrote: post #268
pjmlp wrote: post #130

Earlier quoted context omitted.

Some of those folks started when Fortran, Basic, Clipper, Pascal, Modula-2, Ada were relevant. 1 based indexes were just fine.

Vectors are zero based in Common Lisp; the 1960 Lisp 1 manual describes arrays; they are zero based. Zero based is much more sane. If the array is regarded as being made up of larger groups of elements, say groups of 8, then ⌊index/8⌋ gives us the group and group x 8 gives us the base element of group. Not so if index is one-based. Zero based multi-dimensional coordinates are easy to convert to a flat address. E.g. 3…

I haven’t, so far, encountered a single occasion in which I would need to manually flatten-deflatten indices: Julia has multidimensional arrays of any dimension N, and you can access their content in a linear fashion without any effort (simply provide one index instead of N)

Re: Julia 1.0

#308

Post by jimbokun »

Svenskunganka wrote: post #168
ChrisRackauckas wrote: post #153

Earlier quoted context omitted.

For scientific computing, showing the package ecosystem is the most important thing. When you look at this thread, people are asking about dataframes and differential equations. Julia's site reflects this: yes there are things like Pandas, and for plotting, etc.

The blog mentions that Julia is supposed to be a general purpose language, and not a language built specifically for scientific computing. Is that wrong? The first impression does leave me thinking that using Julia for different programming domains like distributed internet-facing servers or web services is not something it was built for.

My sense has been it's designed specifically to be the best language for scientific and mathematical computing, but also a general purpose language in the sense you don't have to switch languages when you need to incorporate into a web service or a GUI tool or text munging.

So like Python, you have SciPy Pandas etc. but don't have to leave Python when you need to do a bunch of text processing or whatever.

Re: Julia 1.0

#309

Post by KenoFischer »

wuschel wrote: post #289

Does Julia have Tail Call Optimization for recursion? I know it is not necessary, I was just curious, as thr language seems to have a lot of metaprogramming options, and Femto-Lisp being part of the compiler.

No, but it'd be fairly easy to activate, since LLVM supports it in code generation. The primary reason we don't is that it messes with stack traces too much.

Re: Julia 1.0

#310

Post by danso »

kgwgk wrote: post #73
peatmoss wrote: post #62

Earlier quoted context omitted.

> 1-based indexing now seems like a poor choice since Julia has become something more than the original mission of a better MATLAB or Octave. It’s a, admittedly, minor tragedy of Julia’s success. I’m curious as to why this is a problem outside numerical computing. From my perspective, this is consistent with a long history of mathematics dealing with matrices that predates electronic computers. 0-based arrays are pop…

> the technical reason we started counting arrays at zero is that in the mid-1960’s, you could shave a few cycles off of a program’s compilation time on an IBM 7094. The social reason is that we had to save every cycle we could, because if the job didn’t finish fast it might not finish at all and you never know when you’re getting bumped off the hardware because the President of IBM just called and fuck your thesis,…

This was a fantastic (and relevant) read, thank you for sharing it.
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