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This article mainly introduces "how to build Linux GPU server in CentOS7". In daily operation, I believe many people have doubts about how to build Linux GPU server in CentOS7. The editor consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful to answer the doubts about "how to build Linux GPU server in CentOS7". Next, please follow the editor to study!

1. Installation of cuda toolkit

To query the supported cuda versions of gpu:

According to the choice of the operating system, download the corresponding cuda toolkit version, download a .run file, and run the file installation directly with the root user after the download is completed.

After the installation is complete. Run:

The copy code is as follows:

Nvidia-smi

If the gpu status information is listed, the installation is successful:

2. Installation of cudnn

Tensorflow accelerates the neural network through the cudnn library, so first go to https://developer.nvidia.com/rdp/cudnn-archive, download the corresponding version of cudnn according to the version of cuda, which is also a .run file, and run it directly after download.

3. Installation of tensorflow

In order to avoid problems such as version conflicts during installation, it is recommended that you install anoconda first. After downloading to https://www.anaconda.com/download/#linux, run the .sh file to install.

Then install tensorflow using the following command:

Conda create-n tensorflow python=2.7source activate tensorflowexport tf_binary_url= https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whlpip install-- ignore-installed-- upgrade $tf_binary_url

Enter in turn:

Source activate tensorflowpythonimport tensorflow as tfimport pandas as pdtf.__version__

If no error is reported, the installation is successful:

At this point, the study on "how to build a Linux GPU server by CentOS7" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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