CUDA7.0 Drivers Installation Guide

Pre-installation Actions

Verify You Have a CUDA-Capable GPU

If you have CUDA capable GPU you should see something like,

01:00.0 VGA compatible controller: NVIDIA Corporation GK107M [GeForce GT 730M]

Verify You Have a Supported Version of Linux

Supported distributions can be found here.

Verify the System Has gcc Installed

should give something like,

gcc (Ubuntu 4.9.1-16ubuntu6) 4.9.1

Download the NVIDIA CUDA Toolkit

Choose suitable version for your system from here.

Download Verification

Downloaded file can be verified by comparing the MD5 checksum posted at with that of the downloaded file. If either of the checksums differ, the downloaded file is corrupt and needs to be downloaded again.

To calculate the MD5 checksum of the downloaded file, run the following:

Handle Conflicting Installation Methods

Before installing CUDA, any previously installations that could conflict should be uninstalled. This will not affect systems which have not had CUDA installed previously,

Use the following command to uninstall a Toolkit runfile installation:

Use the following command to uninstall a Driver runfile installation:

Use the following commands to uninstall a RPM/Deb installation:

Package Manager Installation

  • Install repository meta-data

Depending on your downloaded version you should execute something like

sudo dpkg -i cuda-repo-ubuntu1410-7-0-local7.0-28amd64.deb

  • Update the Apt repository cache
  • Install CUDA

Post-installation Actions

Environment Setup

The PATH variable needs to include /usr/local/cuda-7.0/bin. These paths must be added into .bashrc file under home directory.

For 64-bit system

For 32-bit system

Then execute .bashrc file with following command

Install Writable Samples

In order to modify, compile, and run the samples, the samples must be installed with write permissions with following command.

Samples will come to specified directory.

Verify the Driver Version

When the driver is loaded, the driver version can be found by executing the command.

This command will not work on an iGPU/dGPU system. Instead you may try the following.

Compiling the Examples

The version of the CUDA Toolkit can be checked by running.

The NVIDIA CUDA Toolkit includes sample programs in source form. You should compile them by wherever you installed “NVIDIACUDA-7.0Samples” directory and type

The resulting binaries will be placed under “NVIDIACUDA-7.0Samples/bin”.

Running the Binaries

At this point, rebooting is recommended, otherwise this step might be failed.

After compilation, find and run “NVIDIACUDA-7.0Samples/1_Utilities/deviceQuery/deviceQuery”. If the CUDA software is installed and configured correctly you should see something like


NVIDIA cuDNN – GPU Accelerated Deep Learning

Get cuDNN library from attachment.

Then apply the following commands upon the downladed file.

Adding cuDNN libraries into cuda libraries


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