kompute VS turbo-django

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.

Indicative of how marvelously stable Django is that none of these roadmap items have to do with the software.

I came back to the old workhorse for some experimentation recently and was delighted, delighted (!), I tell you, at how familiar, comfortable, and productive it was.

Started exploring a Turbolinks/Turboframes implementation (https://github.com/hotwire-django/turbo-django) that Just Worked. Amusingly, mid-hack, the repo owner marked it as unmaintained.

But it works! Nothing needs doing! Another victim of the cult of constant improvement.

Yes Turbo is created by the team behind Ruby on Rails and it's an evolution of Turbolinks with bunch of other functionality added. But Turbo can be adapted to other languages and backend frameworks (and already has!). This Turbo thing is not Rails specific.

If you would like to try something different, there is this new thing called hotwired: https://github.com/hotwire-django/turbo-django Basically, it's about generating HTML on the backend and pushing it to the frontend. thru WebSockets. It's not production-ready yet (for Django at least) so it's more like a fun fact for now.