godot-proposals VS kompute

Godot was fine, for the most part, it's a good engine for small games. The main issue was around working together and resolving conflicts with git (Godot isn't really working and constantly kept changing IDs in resource files), and it kept losing data in scenes when the code changed so we had to rebuild things several times. On previous test games we also ran into huge performance issues in the editor when we wanted to do too much work in scenes, so we had to switch to doing most of the work in code.

The worst part was when I had to rip out a bunch of testing code that used @tool for release as it seemed to cause issues when doing a release build. The engine is generally not great when you want to follow clean software engineering (e.g. dependency injection is not possible, I opened a proposal to that end here[1]).

[1]: https://github.com/godotengine/godot-proposals/issues/8850

If we had a Mask2D, this would be super easy and straight forward.

So if that's what OP meant, clip_children property won't work. Instead OP needs to use a CanvasGroup parent and the Line2D (with CanvasItem Material in Subtract mode) and TextureRect as siblings, or any of the other methods explained here until we have a Mask2D node.

There is an open proposal to have a compile option for a LibGodot, as a Library https://github.com/godotengine/godot-proposals/issues/6267

Yes, there could be the option to open at least 2 tabs at the same time, when working with scripts. This has probably already been suggested in: https://github.com/godotengine/godot-proposals

I cannot tell exactly where the jitter is from the video, but if it is what I'm thinking of, it is a known issue, see here. There is a proposal to fix this, with tons of discussion here. Try some of the workarounds mentioned in these two links. Game looks great by the way!

It's in the release notes. Here is a link to the pull request, based on this proposal.

Currently not possible: https://github.com/godotengine/godot-proposals/issues/7213

The two I know of are IREE and Kompute[1]. I'm not sure how much momentum the latter has, I don't see it referenced much. There's also a growing body of work that uses Vulkan indirectly through WebGPU. This is currently lagging in performance due to lack of subgroups and cooperative matrix mult, but I see that gap closing. There I think wonnx[2] has the most momentum, but I am aware of other efforts.

[1]: https://kompute.cc/

[2]: https://github.com/webonnx/wonnx

Great to see the positive momentum of this framework! Best wishes and upvotes from the Vulkan Kompute team :)

To a first approximation, Kompute[1] is that. It doesn't seem to be catching on, I'm seeing more buzz around WebGPU solutions, including wonnx[2] and more hand-rolled approaches, and IREE[3], the latter of which has a Vulkan back-end.

[1]: https://kompute.cc/

[2]: https://github.com/webonnx/wonnx

[3]: https://github.com/openxla/iree

I look in an example and see similar instructions, stating that the build should be quite simple. But again, it doesn't work. It generates a bunch of folders with Visual Studio stuff, but no executables, no libraries, or anything like that.

I can't figure out how, and there are no tutorials. According to https://kompute.cc/overview/build-system.html I should simply run "cmake -Bbuild". But this doesn't output what I need, and when I look in the Makefile I get the sense that this is more an example Makefile... but then that contradicts the above tutorial.

Kompute is in my opinion good example to take inspiration for abstractions.

Currently, there's a few Vulkan compute frameworks floating around (like Kompute). I would work with those. Kompute simplifies a lot of the biolerplate and seems like you could benefit from using it.

Try Kompute, a project from the Linux foundation. It is quite simple to use, and does not require deep knowledge of graphics API. It’s a bit painful to setup, but it kinda works well (and I have a project going on on it)

This so much.

This makes alot of sense considering the Linux Foundation is also in charge of Kompute which is likely to be the basis of vendor agnostic GPGPU, and thus the basis of vendor agnostic GPU-based machine learning.