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?
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.
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.
