I have referred to both of those links and read them already however they do not explain anything about typical use value and what I should expect to see.
I have already run these all the time:
$ sudo nvpmodel -m 0
$ sudo jetson_clocks
Is 921 a typical frequency because I have seen other (old) posts where people are stating value over 1100.
Is it normal to see such low GPU usage percentages.
My pipeline is:
rtsp --|-- decodebin (using nvv4l2h265dec) – streammux – pgie (interval 4) – tracker – streamdemux --|
After the streamdemux I have 4 tee’s with fakesinks linked (one for each corresponding source). Then I dynamically add other elements when a pgie detection is found in the meta.
So when I run this pipeline without any detections - so its all just streaming to fakesinks - I would still expect the gpu to be under load as we are inferencing on 4 streams continusouly… Buut mostly I just see a GR3D value of 0%. Occasionally I’ll see 60 and maybe once every 3 or 4 mins I’ll see 99.
Can you please provide some guidance on these number and what we should typically expect.
If I’m seeing low CPU and low GR3D values does that mean I should be increasing the number of surfaces used by the decoder (in the decodebin).
btw. My app is base don deepstream-test3.
Something else I’m interested to know is - the model engine file… I reuse an already generated one so that I don’t have to wait a couple of minutes while it generates every time - is this a bad practice? I’m wondering if that model engine file would be different depending on the batch size I specify? But I don’t know the batch size till runtime…