GPU - minimum requirements?

Hi,

I’m running the gpu-x3-beta container and I get 400 errors from the API when an image is posted. If I use the CPU version, it works fine and returns results as expected. But, the CPU version is slow for my hardware and I was hoping I could use the GPU.

Is there a minimum GPU or version of CUDA that is required for this? I’m running a Geforce 710 and I am able to run the nvidia cuda runtime through docker and get an output from nvidia-smi. But, I have to run version 10 and not version 11.

 docker run --runtime=nvidia --rm nvidia/cuda:10.1-runtime nvidia-smi
Tue Sep 15 22:37:11 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.59       Driver Version: 440.59       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GT 710      Off  | 00000000:01:00.0 N/A |                  N/A |
| 40%   36C    P0    N/A /  N/A |      0MiB /  2001MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0                    Not Supported                                       |
+-----------------------------------------------------------------------------+

So - is there a minimum GPU or CUDA version that is needed for this to work?

Hello, I tested the same config many times with a gt 710 with 2gb of ram, never worked.

Thanks for chiming in and letting me know. Ok, I guess I’ll try another GPU. Cheers!

Welcome, but I am still looking for a solution, I am not an expert, I hope a solution /confirmation from deepstack team…, maybe it is possible to run it with gt710…

Well, based on what you said, i swapped out the GT 710 with a spare GTX 970 that I had around. I put that in just now and it works well. So, it seems the minimum version GPU required is Maxwell. The GT 710 is the generation before it, Kepler. :frowning:

My previous times were 3 seconds for object analysis. With GPU, it is now max about 300ms. WOW!

Sun Oct 11 22:59:42 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.66       Driver Version: 450.66       CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Quadro K2200        Off  | 00000000:00:07.0 Off |                  N/A |
| 42%   51C    P8     1W /  39W |    757MiB /  4043MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      8125      C   python3                           754MiB |
+-----------------------------------------------------------------------------+

[GIN] 2020/10/12 - 05:31:37 | 200 |  250.343745ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:31:42 | 200 |  241.107745ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:32:43 | 200 |  254.230065ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:32:48 | 200 |  246.060867ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:32:53 | 200 |  240.459923ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:32:58 | 200 |  255.665306ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:33:03 | 200 |  242.005577ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:34:15 | 200 |   257.00856ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:34:20 | 200 |  240.914136ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:34:25 | 200 |  235.695141ms |      172.17.0.1 | POST     /v1/vision/detection
[GIN] 2020/10/12 - 05:34:30 | 200 |  242.854151ms |      172.17.0.1 | POST     /v1/vision/detection

I’m using a NVIDIA Quadro K2200 with deepquestai/deepstack:gpu-x3-beta. Works fine so far, but had stability problems with deepquestai/deepstack:gpu.

Got it off eBay for like $80 delivered. I picked this card specifically because it has a low power footprint and requires no extra power supply cables, plus being a Quadro there’s no hackery needed to pass it through to a VM.