Hardware Acceleration for Jellyfin: On the EliteDesk, I’d like to enable hardware acceleration for a VM running Jellyfin (in Docker) using the i7-9700’s UHD 630 iGPU. Can anyone recommend a clear guide specific to this CPU? The Proxmox documentation isn’t very detailed for Intel GPUs.
I feel like I’ve done this, but it was a VERY long time ago. It certainly wasn’t from a guide specific for this, but from adapting other instructions. Whole idea with a home lab - learn stuff, break stuff, figure stuff out! :-)
Wish I could be more helpful! But iirc, once you understand the gist of passing the hardware through, blocking kernel models on the host, and installing the required drivers in the guest, it’s applicable to basically everything.
As for Backblaze for ‘home lab’ backups, that sounds expensive? I run PBS on a container on my NAS for my backups - keeps it all local and effectively ‘free’. Only the things I REALLY care about - like my git server with all the code I’ve written for the lab, and even some of the more complex/outside the box configurations get backed up to the public cloud. Simple ‘cattle’ VMs do not justify additional expenses for me.
It’s fun as hell! I’ve been running Proxmox for many years now and still enjoy it VERY much. I’ve recently added 3x 12GB bus-powered A2000s to my Dell workstations. Having oodles of fun running things like piper, whisper, ollama and frigate models on them in a new k8s cluster I spun up just for ML workloads.
I feel like I’ve done this, but it was a VERY long time ago. It certainly wasn’t from a guide specific for this, but from adapting other instructions. Whole idea with a home lab - learn stuff, break stuff, figure stuff out! :-)
Wish I could be more helpful! But iirc, once you understand the gist of passing the hardware through, blocking kernel models on the host, and installing the required drivers in the guest, it’s applicable to basically everything.
As for Backblaze for ‘home lab’ backups, that sounds expensive? I run PBS on a container on my NAS for my backups - keeps it all local and effectively ‘free’. Only the things I REALLY care about - like my git server with all the code I’ve written for the lab, and even some of the more complex/outside the box configurations get backed up to the public cloud. Simple ‘cattle’ VMs do not justify additional expenses for me.
It’s fun as hell! I’ve been running Proxmox for many years now and still enjoy it VERY much. I’ve recently added 3x 12GB bus-powered A2000s to my Dell workstations. Having oodles of fun running things like piper, whisper, ollama and frigate models on them in a new k8s cluster I spun up just for ML workloads.