TensorFlow is unable to detect GPU

Accelerated Computing CUDA CUDA Programming and Performance
1

TensorFlow is unable to detect GPU.

How canb I resolve this?

F:\git\hec_v2>python cnn_search_hec.py
2023-11-10 16:44:55.126779: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusolver64_11.dll'; dlerror: cusolver64_11.dll not found
2023-11-10 16:44:55.131357: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2023-11-10 16:44:55.131462: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1850] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...

F:\git\hec_v2>pip show tensorflow
Name: tensorflow
Version: 2.8.0
Summary: TensorFlow is an open source machine learning framework for everyone.
Home-page: https://www.tensorflow.org/
Author: Google Inc.
Author-email: packages@tensorflow.org
License: Apache 2.0
Location: c:\users\pc\appdata\local\programs\python\python37\lib\site-packages
Requires: absl-py, astunparse, flatbuffers, gast, google-pasta, grpcio, h5py, keras, keras-preprocessing, libclang, numpy, opt-einsum, protobuf, setuptools, six, tensorboard, tensorflow-io-gcs-filesystem, termcolor, tf-estimator-nightly, typing-extensions, wrapt
Required-by: autokeras

F:\git\hec_v2>python --version
Python 3.7.0

F:\git\hec_v2>

F:\git\hec_v2>nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Wed_Jul_22_19:09:35_Pacific_Daylight_Time_2020
Cuda compilation tools, release 11.0, V11.0.221
Build cuda_11.0_bu.relgpu_drvr445TC445_37.28845127_0


F:\git\hec_v2>nvidia-smi
Fri Nov 10 16:48:26 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 391.35                 Driver Version: 391.35                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 480    WDDM  | 00000000:03:00.0 N/A |                  N/A |
| 44%   51C   P12    N/A /  N/A |    302MiB /  1536MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

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

F:\git\hec_v2>
2

Have you done what is suggested to you?

Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at Install TensorFlow with pip for how to download and setup the required libraries for your platform.

3

I have installed CUDA 11.0 using an installer.

The question is: why are these files missing?

4

afaik, cudnn is not part of the cuda toolkit.
I would also check that all paths are correctly set in the PATH environment variable.

5

Also, your GTX480 is too old for tensorflow. It’s a Compute Capability 2.0 (Cuda Architecture), and tensorflow requires CC 3.5 or greater.

6

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