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Thank you for the feedback... i will do that


Yes they are not... we run the Nvidia drivers unmodified. Only thing we have done is make the guest driver think it's running on the host, talking to the host's GPU kernel.

It works really well with a ~2% performance penalty. Nvproxy by google/gvisor has been doing this for years.

You should try running it yourself and see how it goes :D


So you can share the GPU between multiple VMs? I can have 4 VMs simultaneously do work on the GPU?

And each one would have its own Nvidia driver? How do they not interfere with each other? I mean I am by no means an expert in GPU architecture or anything similar, but I thought the problems with sharing a GPU come from the differences between GPU vs CPU architecture. On the other hand, multiple processes on a host can run on the same GPU, but that is all using the same kernel. I am just very confused.


This has been a thing for AMD, Intel, and Qualcomm GPUs for a few years now. Search for "DRM native context". The only difference here is that you had to use mesa drivers before and now someone made it work with the Nvidia drivers.


How is this different (in effect, not technically) from just using PCI passthrough, apart from being less safe and less tested?


Fair point, we still have a long way to go in terms of security AND being suitable for everyday use.

However, nvgpu is meant to be used in PCI passthrough in scenarios where you would want to run and share your GPU across multiple KVM guests, or you don't want to detach the GPU from the host, and plug it into the VM you are running... you know, that little dance you do everytime you want to game inside a VM.


  > just using PCI passthrough
On a laptop, I never got a working setup where I could attach/detach a modern nvidia card from host linux. So something that can do without is better. But intel SRIOV is a thing as well, which should be the secure alternative.


I got it working on my laptop. It has an Intel integrated iGPU and an NVIDIA discrete dGPU. I was able to pass through the NVIDIA GPU and use it for CUDA/etc.

But the NVIDIA dGPU is muxless, so apparently all of the display outputs (laptop screen, HDMI outputs) are effectively hard wired to the iGPU. dGPU can render in a VM, it just has no where it can send it without trying to use Looking Glass or similar approach.


Does "how it goes" include the guest being able to DMA over the host kernel?


We encode with Vulkan Video, then stream to the client using QUIC. This is part of the larger project: Nestri [1] which is currently a work-in-progress.

[1] https://github.com/nestrilabs/nestri

Nesbox is just a VMM, a component of the whole stack.


Virtio? what virtio? virtio native drm native context, is that what you mean? We actually use it in nesbox[1] for AMD/Intel cards.

Venus is the only one we could directly compare to, as it is the only one that supports Nvidia GPUs. vDRM works only on AMD/Intel GPUs and has a similar performance (~98% baremetal performance) to virtio-nvgpu.

[1] https://github.com/nestrilabs/nesbox


I meant vfio-pci.


No not yet, but that is in the roadmap.


We borrowed a lot of the architectural design from nvproxy, then built it to support graphical workloads. Plus it is reusable in such a way you can hot plug it into any microVM, cloud-hypervisor, maybe even Firecracker


My bad, i am not a native English speaker... I did my best to try and brush it up. Terribly sorry if it did not match your flow.


LLMs are pretty good at translation, they're just pretty awful at generating natural-sounding English prose from scratch. In my opinion, probably the best solution is to simply write the README in your native tongue and use an LLM to translate it.


This! Claude word salad is worse than maybe subpar translations, with which I'm sure PRs can help.


All good friend! I'm as guilty as anyone. It's a super cool project though.

Now that I have you on the hook, is there any benefit to this over virtio for a single KVM passthrough situation? I previously ran a proxmox based gaming PC setup (docs here: https://github.com/mtrudel/rabble/tree/4d9329f3dd0fb09123a8f...), and was lucky enough that the GPU passthrough part of that build 'just worked'. I'd started down a path of trying to share the GPU between VMs based on a naive 'one VM owns it at a time' setup, but never really got it off the ground.


The benefit is that you do not have a limit to how many VMs you can run at the same time. However, virtio-nvgpu has no Windows support as of yet, please check back in a while :)

You should check out Nestri [1], another project we are working on, that helps you do exactly that. It helps run multiple gaming sessions for you and your friends on the same GPU, without anyone meddling in the other person's session. Everyone gets to stream their game to whatever desktop or device they want. It is still a work-in-progress though.

[1] https://github.com/nestrilabs/nestri


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Google Stadia

Stadia's shutdown was a great loss in the gaming world.

Its social elements were ahead of their time, allowing for unprecedented levels of interaction and connectivity.

Other platforms are still catching up to how easy it was to jump into a game with friends, share game states, or even stream your gameplay with the press of a button; no queuing.

Unfortunately, much of Stadia's potential was undercut by Google's marketing strategy :(


The extra tragic thing is that if Google had committed up front to refund users in the event of shutdown - AKA the thing they actually did - they might have mitigated the fears that kept people off the platform in the first place.


Project maintainer here.

Hi, thank you for taking an interest.

It is 'cross-platform' as long as you have docker installed and configured to use your gpus. You are good to go.

qwantify is still young and unstable to promise you, you will get a first good experience. But do tell how it goes :)


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