Makie.jl VS oneAPI.jl

Just look at this lotenz attractor https://docs.makie.org/stable/

There does exist some code for reading glyph geometry from fonts - you can find some of it in the Makie source directory: eg https://github.com/MakieOrg/Makie.jl/blob/master/src/bezier.jl - you can see that there's quite a lot though...

You'll want Makie.

Thanks! Looks like the Julia Makie library can do graphics and gui widgets as well -https://github.com/JuliaPlots/Makie.jl

There was also this recent thread where some folks were talking up Makie.jl, for which there is apparently also a Grammar-of-Graphics-style wrapper called AlgebraOfGraphics.jl.

If you're looking for native then Makie.jl is probably your best bet. It's still a little underdocumented and the integrations with the rest of the ecosystem are still incomplete, but it's a pretty amazing plotting library. Fast with easy GPU acceleration, good interactivity and animations (great for making GUIs), and easy to extend.

How tricky or hard would it be to create nice looking plots from that? Something like https://github.com/JuliaPlots/Makie.jl but more low level.

https://github.com/JuliaGPU/oneAPI.jl

As for syntax, Julia syntax scales from a scripting language to a fully typed language. You can write valid and performant code without specifying any types, but you can also specialize methods for specific types. The type notation uses `::`. The types also have parameters in the curly brackets. The other aspect that makes this specific example complicated is the use of Lisp-like macros which starts with `@`. These allow for code transformation as I described earlier. The last aspect is that the author is making extensive use of Unicode. This is purely optional as you can write Julia with just ASCII. Some authors like to use `ε` instead of `in`.

https://github.com/JuliaGPU/AMDGPU.jl

https://github.com/JuliaGPU/oneAPI.jl

These are both less mature than CUDA.jl, but are in active development.

OpenCL and various other solutions basically require that one writes kernels in C/C++. This is an unfortunate limitation, and can make it hard for less experienced users (researchers especially) to write correct and performant GPU code, since neither language lends itself to writing many mathematical and scientific models in a clean, maintainable manner (in my opinion).

What oneAPI (the runtime), and also AMD's ROCm (specifically the ROCR runtime), do that is new is that they enable packages like oneAPI.jl [1] and AMDGPU.jl [2] to exist (both Julia packages), without having to go through OpenCL or C++ transpilation (which we've tried out before, and it's quite painful). This is a great thing, because now users of an entirely different language can still utilize their GPUs effectively and with near-optimal performance (optimal w.r.t what the device can reasonably attain).

[1] https://github.com/JuliaGPU/oneAPI.jl