simondanisch

7 ms·

31.
by simondanisch 3y ago
improving Julia's interpreter and code caching should get you pretty close to that dream language! and it's already a great, existing language with a nice ecosystem :)
32.
by simondanisch 3y ago
We're not using diffing! Diffing has a pretty big overhead for calculating the shadow dom and going through all values and seeing if they're the same, which can be very expensive for huge plots. We use signals that get wired throu
33.
by simondanisch 3y ago
Polishing the Docs will be a big thing we want to do with better funding :) Improving APIs and recipes is the other big thing planned for this year.
34.
by simondanisch 3y ago
Makie is almost 100% written in Julia and a pretty big library by now... So not so great ^^ But Julia 1.9 now supports caching binary and we also worked a lot on improving compile times, so after `precompiling` Makie (which, admittedly tak
35.
Makie, a modern and fast plotting library for Julia(makie.org)
260 points by simondanisch 3y ago|70 comments
36.
by simondanisch 3y ago
Makie is a modern plotting library for Julia. It is easy to use, fast and powerful. Packed with features, it is a general-purpose tool that makes as few compromises for specialized use cases as possible. Try it out today: install Julia and
37.
by simondanisch 3y ago
Using: https://github.com/facebookresearch/segment-anything/ https://github.com/MakieOrg/Tyler.jl https://docs.makie.org/
38.
Asteroid Impact 66M Years Ago visualized in 3D(twitter.com)
2 points by simondanisch 4y ago|1 comments
39.
by simondanisch 4y ago
Asteroid Impact - 66 Million Years Ago. The next 48 hours after impact. You can also explore this using JuliaLang and Makie.jl. See the code (simplified version) here: https://beautiful.makie.org/dev/extinction_event&#x
40.
by simondanisch 6y ago
This seems pretty relevant: >Watch how the ultra-wealthy in America gradually raised the taxes of the poor and eventually bent the curve downward until they paid the lowest tax rate of all https://twitter.com/nick_kapur&#
41.
Julia Employs Differentiable Programming to Do It Best(sinews.siam.org)
3 points by simondanisch 7y ago|0 comments
42.
Towards Model-Driven Authoring: What’s Missing?(nextjournal.com)
5 points by simondanisch 7y ago|0 comments
43.
by simondanisch 7y ago
In the case for Julia it's true though, since It's compiled at runtime very similarly to C via LLVM. In all my years I've never seen any C/C++ code, where Julia couldn't match performance after some tweaking - often
44.
Taking Your Robot for a Walk(nextjournal.com)
2 points by simondanisch 7y ago|0 comments
45.
by simondanisch 7y ago
Btw, the argument "If it compiles, I don't need to be afraid about run time errors anymore" is also pretty foreign to me. I just run my code in small batches while developing it, so at every point I already know that it works
46.
by simondanisch 7y ago
>Swift has clearly an advantage in that domain, as has C++, C#. In an enterprise setting such as Google no one actually wants speed and dynamism out of a language (C++ programmers are not allowed to use rtti for example), rather consiste
47.
by simondanisch 8y ago
https://nextjournal.com/ pretty much tries to establish this kind of paper writing - all fully reproducable and runnable in a docker container :) It also blurs the line between normal blog posts, jupyter like IDE and papers
48.
by simondanisch 8y ago
that may be your impression, because you dont know julia's powerful, no overhead indexing abstractions yet ;) i also write lots of graphics low level code, and i couldn't be more glad that i don't need to do those error ridde
49.
by simondanisch 8y ago
And sorry for hijacking your perfectly fine comment - of course it would help python to embrace modern compiler technologies! ;) It's just always a bit maddening to see how much effort and money is spent on creating imense projects for
50.
by simondanisch 8y ago
Yeah, I'm just trying to point out, that not much would be won by that. You either need to change the semantic of the language (CPython) or live with a slow JIT for some of the most used features of the language... And changing the sem
51.
by simondanisch 8y ago
They do, there have been several high profile projects to make a JIT for python... The problem isn't, that JITs aren't taken seriously - the problem is, that python isn't designed for a JIT, so it's very hard to get the
52.
by simondanisch 8y ago
Hey hacker news, I’m the author of the article. If you want to play with the article you can sign up for a nextjournal account using the invite code julia1.0 and remix the article. I'm happy to discuss any questions about how to compil
53.
How to run Julia in the Browser(nextjournal.com)
28 points by simondanisch 8y ago|1 comments
54.
by simondanisch 8y ago
That's how you do it: https://github.com/JuliaGPU/GPUArrays.jl/blob/master/src/lin... Or directly with cuda shfl intrinsics: https://github.com/JuliaGPU/CUDAnative.jl/
55.
by simondanisch 8y ago
Or just directly edit the article ;) That will also give you a K80 and you can directly run the code inside the article
56.
An Introduction to GPU Programming in Julia(nextjournal.com)
290 points by simondanisch 8y ago|46 comments
57.
How Fast Is R with FastR?(nextjournal.com)
3 points by simondanisch 8y ago|0 comments
58.
by simondanisch 8y ago
If anyone wants to reproduce the benchmarks, I put them into a reproducible article and added a Julia baseline: https://nextjournal.com/sdanisch/fastr-benchmark
59.
by simondanisch 8y ago
Guess I wrote my answer more ambiguous than I thought: the exact opposite is the case... Julia Base is huge and includes much more than most other languages I know - and that's what gets loaded on start, whether you like it or not ;)
60.
by simondanisch 8y ago
> if you didn't have the import from Base, what can you not do? So the part that gets loaded when you load the language/compiler is what is referred to as Base. So, it's kind of impossible to not have it and it is part of

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