UnicornTranscoder
nvidia-patch
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UnicornTranscoder | nvidia-patch | |
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37 | 309 | |
682 | 2,959 | |
0.0% | - | |
0.0 | 8.5 | |
about 1 year ago | 10 days ago | |
JavaScript | Python | |
MIT License | - |
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UnicornTranscoder
- outsource transcoding to GPU in another machine
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The Dim Media Manager is still active - Help us by filling out our survey!
Just having support for a remote transcoder, along the lines of unicorn transcoder or rffmpeg would be a good first step to let us start homebrewing a solution.
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Two servers, same data
There's this project - https://github.com/UnicornTranscoder/UnicornTranscoder That lets you use a remote transcoder, but idk if the project is maintained anymore.
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Secondary Plex Server
There are some projects to distribute transcoding jobs like the Unicorn Transcoder (last activity in 2021), Remote Transcoder (last activity in 2017) or the Kubernetes project (last activity in 2020)
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Tonemapping Dolby Vision - Is it possible to achieve by replacing the ffmpeg binary?
Interesting, I wasn't aware they tweaked it so much. Projects like Unicorn Transcoder made it seem like you could just drop-in replace it with a different binary.
- Plex Raspberry Pi 4B and Windows PC with RTX 3080?
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Is it possible to run the "Optimize" functionality standalone? I want to run it on my powerful PC instead of my weak NAS CPU
There was/is a Project for remote transcoding, the Unicorn Trancoder which might help but the last commit in that project was made in Oct. 2021.
- Who is currently running two or more plex servers?
- Different encoders for different sessions
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Can I let my Plex Server convert files on another machine?
On the other hand, there is a Project called Unicorn Transcoder which is to offload the transcoding job on a different machine. If that works with plex optimization or just the "on-the-fly" transcoder, I don't know.
nvidia-patch
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Do I need to have a beefy PC to transcode 4k? Or can I just buy my brother an Nvidia shield pro and setup a cheap server on my end?
This can be patched out. https://github.com/keylase/nvidia-patch
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Transcoding 4K HDR tone mapping
NVIDIA Corporation GA106 [GeForce RTX 3060] and I applied the patch here https://github.com/keylase/nvidia-patch
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Linux 6.6 to Protect Against Illicit Behavior of Nvidia Proprietary Driver
> CUDA, and pretty much all optimization(hacks) done to run games better
And arbitrary limitations implemented at the driver level to force you to purchase their enterprise GPUs, see https://github.com/keylase/nvidia-patch#nvenc-and-nvfbc-patc...
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GPU Guide (For AI Use-Cases)
Nvidia has no motivation to make a consumer card with lots of VRAM, that's basically the only (relevant) separator between the GeForce family and the Quadro lineup.
There are restrictions on NVENC streams with consumer cards, but that has been a solved problem for a while [0].
If they were to make a consumer card with more VRAM, it would immediately undercut their own Quadro/Tesla lineup, which cost substantially more. I don't see a reason for them to do it.
0: https://github.com/keylase/nvidia-patch
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Can't hardware transcode mor than 5 at a time even after all the required changes
I have never had to do the session limit bump thing from the last link. I have a 3090 as well and simply did the initial unlock, which worked fine. I would reinstall fresh drivers from Nvidia, making sure you install the newest one that is supported by the unlock tool (536.40 as of this post, the GitHub for the patch has links to the drivers - https://github.com/keylase/nvidia-patch/tree/master/win)
- Can you flash any consumer version Nvidia card to remove the streaming limits?
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Can my GPU transcode?
Aren't these Quadro versions. The patch here. https://github.com/keylase/nvidia-patch supports Quadro versions of you click on the win clickable.
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Let's have a talk - Guide to Choosing the Best Plex Server for You
Second, the GPU. The GPU is probably as important as the CPU, and in some cases more important, and when we talk about GPUs we will primarily talk about Nvidia GPUs as they are officialy supported by the Plex team. NVIDIA GPUs are important for Plex hardware transcoding due to their dedicated video encoding/decoding units, superior performance, wide codec support, improved video quality, reduced CPU load, power efficiency. They offer a powerful hardware acceleration solution that can greatly enhance the transcoding capabilities of a Plex server. It's also important to note that Nvidia GPUs require a patch to unlock the number of HW transcoding streams. Dedicated GPUs are large pieces of hardware and have their place in desktop PCs. However, they can also be used with mini-PCs by using an external GPU enclosure.
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What does this Max. 3 concurrent stream cap mean anway?
As there's no NVENC patch available (yet) for the Beta driver branch - referring to this one: https://github.com/keylase/nvidia-patch - which can lift the limits of HW transcoding, I was now wondering a little, as I can see 5 (hw) streams on Plex, which actually shouldn't/cannot be the case no?
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Is there somewhere that lists Nvidia GPUs.
I haven’t done this yet but there is a patch on GitHub that removes the limitation for consumer GPUs. Makes lower end cards more attractive for this type of work
What are some alternatives?
kube-plex - Scalable Plex Media Server on Kubernetes -- dispatch transcode jobs as pods on your cluster!
vgpu_unlock - Unlock vGPU functionality for consumer grade GPUs.
Plex-Remote-Transcoder - A distributed transcoding backend for Plex
nvlax - Future-proof NvENC & NvFBC patcher (Linux/Windows)
clusterplex - ClusterPlex is an extended version of Plex, which supports distributed Workers across a cluster to handle transcoding requests.
Sunshine - Self-hosted game stream host for Moonlight.
sabnzbd - SABnzbd - The automated Usenet download tool
wlroots - A modular Wayland compositor library
k8s-mediaserver-operator - Repository for k8s Mediaserver Operator project
unmanic - Unmanic - Library Optimiser
Exoplayer - An extensible media player for Android
Proxmox-Nvidia-LXC- - how to create an Proxmox LXC in 6.2-1