[FFmpeg-user] When using h264_cuvid, memory allocation differs between different nvidia GPUs

[Panagiotis Malakoudis]

Lowering surfaces in GTX 1070 Ti to 2 only reduces memory to 129MB, so it
is still not the same as GTX 1050 Ti. Also, 2 surfaces are not enough for
correct decoding, decoding has errors.
Using nvdec with command:
ffmpeg -hwaccel nvdec -f mpegts -i
https://samples.ffmpeg.org/V-codecs/h264/HD-h264.ts -vcodec libx264 -preset
veryfast -crf 23 -c:a copy -f mpegts -y output.ts
uses even more memory, 321MB on GTX 1070 Ti compared to 153MB with
h264_cuvid.
-surfaces is not applicable on -hwaccel nvdec




Στις Πέμ, 13 Σεπ 2018 στις 1:28 μ.μ., ο/η Dennis Mungai <dmngaie at gmail.com>
έγραψε:

> Hello there,
>
> On the system using more VRAM, can you lower the -surfaces value from 8 to
> ~6?
>
> Also, in place of h264_cuvid, use nvdec instead.
>
> Example:
>
> ffmpeg -c:v nvdec -surfaces 8 -f mpegts -i
> https://samples.ffmpeg.org/V-codecs/h264/HD-h264.ts -vcodec libx264
> -preset
> veryfast -crf 23 -c:a copy -f mpegts transcoded.ts
>
> On Thu, 13 Sep 2018 at 11:31, Panagiotis Malakoudis <malakudi at gmail.com>
> wrote:
>
> > I am using h264_cuvid in some systems. GTX10xx cards have the power to
> > decode many full hd streams concurrently.
> > I have found that memory allocated in the GPU differs between GTX 1050 Ti
> > and GTX 1070 Ti. With the same command, same settings, ffmpeg allocates
> > only 87MB in GTX 1050 Ti while it allocates 153MB in GTX 1070 Ti. There
> is
> > an exact 66MB difference which is critical in my application if it can be
> > avoided. Is there any reason why this happens and can it be avoided?
> >
> > Example command:
> > ffmpeg -c:v h264_cuvid -surfaces 8 -f mpegts -i
> > https://samples.ffmpeg.org/V-codecs/h264/HD-h264.ts -vcodec libx264
> > -preset
> > veryfast -crf 23 -c:a copy -f mpegts transcoded.ts
> > In GTX 1050 Ti, nvidia-smi output:
> >
> >
> +-----------------------------------------------------------------------------+
> > | Processes:                                                       GPU
> > Memory |
> > |  GPU       PID   Type   Process name                             Usage
> >   |
> >
> >
> |=============================================================================|
> > |    0     28243      C   ffmpeg
> > 87MiB |
> >
> >
> +-----------------------------------------------------------------------------+
> > In GTX 1070 Ti, nvidia-smi output:
> >
> >
> +-----------------------------------------------------------------------------+
> > | Processes:                                                       GPU
> > Memory |
> > |  GPU       PID   Type   Process name                             Usage
> >   |
> >
> >
> |=============================================================================|
> > |    0     10291      C   ffmpeg
> >  153MiB |
> >
> >
> +-----------------------------------------------------------------------------+
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