[FFmpeg-user] When using h264_cuvid, memory allocation differs between different nvidia GPUs
Dennis Mungai
dmngaie at gmail.com
Thu Sep 13 13:27:50 EEST 2018
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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