I finally installed CUDA 9.0 and PyTorch 1.0 from *.whl file to make it work on GTX 1070 ( torch.cuda.is_available returns True).
I want to see if the installation itself was with cuda not if cuda is available. How do I check that?
seems conda list
works:
pytorch 1.7.0 py3.8_cuda10.2.89_cudnn7.6.5_0 pytorch
though I wonder why pytorch things there is no gpu…
(automl-meta-learning) miranda9~/automl-meta-learning $ nvidia-smi
Wed Dec 2 10:25:39 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.36.06 Driver Version: 450.36.06 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 TITAN Xp Off | 00000000:02:00.0 Off | N/A |
| 53% 83C P2 256W / 250W | 9121MiB / 12196MiB | 89% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 TITAN Xp Off | 00000000:03:00.0 Off | N/A |
| 45% 70C P2 70W / 250W | 4041MiB / 12196MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 TITAN Xp Off | 00000000:82:00.0 Off | N/A |
| 31% 45C P8 12W / 250W | 2MiB / 12196MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 TITAN Xp Off | 00000000:83:00.0 Off | N/A |
| 32% 46C P8 12W / 250W | 2MiB / 12196MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 32361 C python 9119MiB |
| 1 N/A N/A 24301 C python 4039MiB |
+-----------------------------------------------------------------------------+
(automl-meta-learning) miranda9~/automl-meta-learning $ python
Python 3.8.2 (default, Mar 26 2020, 15:53:00)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
torch>>> torch.cuda.is_available()
False
I will try to see if updating pytorch to use cuda 11 works since that seems to be a mistmatch.
update
that didn’t work…
pytorch 1.7.0 py3.8_cuda11.0.221_cudnn8.0.3_0 pytorch
...
torchvision 0.8.1 py38_cu110 pytorch
...
(automl-meta-learning) miranda9~/automl-meta-learning $ nvidia-smi
Wed Dec 2 10:38:47 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.36.06 Driver Version: 450.36.06 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 TITAN Xp Off | 00000000:02:00.0 Off | N/A |
| 53% 83C P2 255W / 250W | 9121MiB / 12196MiB | 97% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 TITAN Xp Off | 00000000:03:00.0 Off | N/A |
| 49% 79C P2 244W / 250W | 4041MiB / 12196MiB | 69% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 TITAN Xp Off | 00000000:82:00.0 Off | N/A |
| 23% 28C P8 9W / 250W | 2MiB / 12196MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 TITAN Xp Off | 00000000:83:00.0 Off | N/A |
| 23% 33C P8 9W / 250W | 2MiB / 12196MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 32361 C python 9119MiB |
| 1 N/A N/A 24301 C python 4039MiB |
+-----------------------------------------------------------------------------+
(automl-meta-learning) miranda9~/automl-meta-learning $ python
Python 3.8.2 (default, Mar 26 2020, 15:53:00)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
tor>>> torch.cuda.is_available()
False
>>>
1 Like
duh, need to get a interactive job indicating my interactive script:
condor_submit -i interactive.sub
opps dum mistake.
Request_gpus = 1
Request_cpus = 30
requirements = (CUDADeviceName != "Tesla K40m")
# requirements = (CUDADeviceName == "Quadro RTX 6000")
Queue