What's the point of this?

A single CPU core on a 9500T or a Ryzen V1500B is fast enough to real-time re-encode 60mbps 4K H264 to 1080p 5mbps h264, aka, for a core use case - transcoding for web for Jellyfin over cellular, for example - you haven't needed hardware video engines on PCs for 9 YEARS.

I have no idea why people are so hung up on hardware video encoding. It's completely wrong. The quality is worse. The efficiency is a red herring - you will still use every CPU core for IO threads in ffmpeg, if you don't configure that away, which you do not. And it requires really annoying setup and premium features on stuff like Plex. It just makes no sense!

If latency is important to you, well then hardware engines make sense. But you are throwing away the latency sending it over the network. The only use case (basically) is video game streaming, and in that case, you'll have a local GPU.

I have never read one of these ffmpeg network hardware encode innovations to have an actual benchmark comparison to single thread software transcoding tasks.

I know you mean well but really. It makes NO sense.

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GranPC 5 hours ago | parent | next [-]

> The efficiency is a red herring - you will still use every CPU core for IO threads in ffmpeg, if you don't configure that away, which you do not. And it requires really annoying setup and premium features on stuff like Plex. It just makes no sense!

I would love to learn more about this! What can I do to fully optimize ffmpeg hardware encoding?

My use case is transcoding a massive media library to AV1 for the space gains. I am aware this comes with a slight drop in quality (which I would also be keen to learn about how to minimize), but so far, in my testing, GPU encoding has been the fastest/most efficient, especially with Nvidia cards.

	▲	doctorpangloss 5 hours ago \| parent [-]
		You would use your full system, saturating the CPU and GPU, including unlocking the number of simultaneous video sessions for consumer NVIDIA GPUs. That said, software AV1 looks a lot better than hardware AV1 per bit.

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steelbrain 5 hours ago | parent | prev | next [-]

Thank you for sharing your experience. Seems like this is not relevant to your setup & usecase.

People who need this know who they are. Not everything is for everybody.

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doctorpangloss 5 hours ago | parent [-]

What is the use case?

I'd argue this is for nobody haha

Nobody using jellyfin plex or whatever needs it: they should just use software transcoding, it's better in pretty much every way.

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steelbrain 5 hours ago | parent [-]

I've traveled around a lot in the past couple years so my situation (read: homelab equipment) has been changing and my usecase has been changing with it. It started out as:

- I dont want to unplug the GPU from my gaming PC and plug it into my linux server

- Then: I dont want to figure out PCI forwarding, I'll just open a port and nfs to the containers/vms (ffmpeg-over-ip v4 needed shared filesystem)

- Now: I have a homelab of 4 mini PCs and one of them has an RTX 3090 over Oculink. I need it for local LLMs but also video encoding and I dont want to do both on the same machine.

But you've asked a more fundamental question, why would people need hardware accelerated video decoding in the first place? I need it because my TV doesn't support all the codecs and I still want to watch my movies at 4K without stuttering.

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doctorpangloss 5 hours ago | parent [-]

You can transcode in realtime in software to your TV. You don't need the GPU at all. Even on ancient USFF PCs.

	▲	selcuka 27 minutes ago \| parent \| next [-]
		> You can transcode in realtime in software Sometimes you want faster-than-realtime encoding, such as when backing up your video archive.
	▲	steelbrain 5 hours ago \| parent \| prev [-]
		I'll tell my TV you said that and I'll see if it stops buffering during playback :)

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ranger_danger 3 hours ago | parent | prev [-]

As a rule, strong feelings about issues do not emerge from deep understanding.