skiko VS magicl

All I know is that they use skiko.

It built on a render framework named skia, JetBrains create a kotlin mapping which named skiko for it.

I was curious to give it a go but unusable on Gnome 42.5; the window lags so much that simply trying to drag to reposition it on the screen is impossible seems related an issue with Skiko and OpenGL reported here: https://github.com/JetBrains/skiko/issues/494

Fleet does not use Compose, but it does use Skiko[1], which also provides binding for Skia[2] (the native graphics library also used by Chrome & Flutter).

The main difference between the libraries is that Skija provides Java/JVM bindings for Skia, whereas Skiko provides Kotlin bindings for Kotlin/JVM, Kotlin/JS, and Kotlin/Native targets. Of course Skiko's Kotlin/JVM bindings can be used with other JVM languages, not just with Kotlin.

[1] https://github.com/JetBrains/skiko

[2] https://skia.org/

How about skiko?

JetBrains is moving from skija to skiko, but it could be interesting either way!

They Merged today the functions that will be usaged on Compose for opening, closing and handling text inputs https://github.com/JetBrains/skiko/pull/455 (if I understand correctly). Currently, the examples rely on xcodegen file, based on the currently plugin that Compose has for Desktop, it provide alot of things including packaging for desktop, I think they will provide a xcodegen file automatically and use xcodegen behind the scenes to generate everything needed.

https://github.com/JetBrains/skiko (a Kotlin MPP binding for Skia). Skiko Does not contain build for iOS. Now Skiko contains build for iOS, MAC arm processor via Kotlin/Native. So we can use Skiko for pure canvas rendering in all platform. It is matter of time they release compose for iOS. So UI also goes multiplatform.

But it does seem like the solution they're using for Fleet is different. Skia is the same graphics library used by Chromium and Flutter. I'll remain cautiously optimistic for now, but the quality of the text rendering and customization options will make or break it for me personally.

(Link didn't work for me)

https://github.com/quil-lang/magicl/blob/master/src/high-lev...

use MAGICL. [1] It is optionally and transparently accelerated by BLAS/LAPACK.

[1] https://github.com/quil-lang/magicl/blob/master/doc/high-lev...

Maybe have a look at how magicl does this?

This is essentially the first option, which is already supported by MAGICL by loading MAGICL/EXT-LAPACK [1].

[1] https://github.com/quil-lang/magicl#extensions

I think what the magicl team has done is brilliant - allowing multiple implementations is awesome.

Second up is magicl, especially useful if performance is a concern. This might not be as extensive as numcl, but it's been battle tested in the industry over the last decade or so. Because this uses generic functions, so long as you are using not-very-small arrays, performance should not be a concern for you. And even if you are, you could write your own functions that use the low-level functions that magicl's backends define. Otherwise performance can be at par with numpy.

This Dev How-To describes (I hope in enough detail) how to add these specialized routines to MAGICL.

I agree... and I do don't want be the person who has not rallied. I just took a look at guicho's issue from 2019. And here, you yourself have admitted that the high level interface is less than ideal and needs more work. However, the very point that magicl is an industry standard could imply that potentially radical backward-incompatible changes can be hard. But, honestly, I want to discuss this, time permitting!

Common Lisp is a great language to build new tools for data science, but currently has pretty awful library support existing data science workflows. Common Lisp is sorely lacking in high-quality statistics, plotting, and sparse arrays. There’s been a long work-in-progress library to bring flexible and high-performance linear algebra to Lisp, but it needs more contributors.