Hey all, I realize that this is not a hardware forum, but I’m not aware of any Nvidia hardware forums so I’m posting here in hopes that someone has some information. I’ve been trying to run some deep learning models on an GTX 1070 in the MXM form factor (Aetina M3N1070-NN) and their accompanying PCIe to MXM conversion board.
The problem that we are having is huge instantaneous power consumption when we run our deep learning models. The user manual states that the MXM GPU is 115W, but we see peak power consumption of 240W and an average consumption of around 180W. We’re running this in a reasonably constrained environment (hence the MXM board) so we’d like to see if this is expected behavior and if anyone has any experience with the real power consumption on Nvidia GPUs.
- We are using a 12V benchtop power supply for the GPU auxiliary power that is capable of 50A
- We are running inference using tensorflow's SSD model on 640x640 images
- nvidia-smi reports GPU power usage of 80W during the high usage time. I'm guessing I can't trust this because the high power draw we're seeing is somewhat instantaneous (20ms)
Does anyone know what kind of power consumption I should expect? Even experiences from normal desktop cards would be helpful.
Any information is appreciated