Installation of CUDA Toolkit 7.5 On Ubuntu 14.04

CONSIDER USING CUDA???
FROM THIS: https://en.wikipedia.org/wiki/CUDA, MY GPU Nvidia GeForce GT 520M IS SUPPORTED!!! Micro Architecture Fermi (https://en.wikipedia.org/wiki/Fermi_(microarchitecture)) version 2.1
CHECK CUDA FROM TERMINAL:
ref:http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/#axzz44a7lZNcT

INSTALLING CUDA TOOLKIT 7.5 ON UBUNTU 14.04
ref:http://www.r-tutor.com/gpu-computing/cuda-installation/cuda7.5-ubuntu
https://www.quantstart.com/articles/Installing-Nvidia-cuda-on-Ubuntu-14-04-for-Linux-GPU-Computing
https://developer.nvidia.com/cuda-downloads -> Linux -> x86_64 -> Ubuntu -> 14.04 -> deb(local)
http://developer.download.nvidia.com/compute/cuda/7.5/Prod/local_installers/cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb
(1.9 GB)
1. The first task is to make sure that you have the GNU compiler collection (GCC) tools installed. This is carried out by installing the build-essential package:

2. Download the latest Cuda toolkit:
Manually FROM:
http://developer.download.nvidia.com/compute/cuda/7.5/Prod/local_installers/cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb
OR:

3. PREPARE THE PACKAGE:

OK

4. Update

5. INSTALL CUDA:

SOLUTION:
ref:http://askubuntu.com/questions/672047/anyone-has-successfully-installed-cuda-7-5-on-ubuntu-14-04-3-lts-x86-64

RUN AGAIN:

6. REBOOT

7. MODIFY ENVIRONMENT VARIABLES:
As part of the CUDA environment, you should add the following in the .bashrc file of your home folder.

ADD THESE LINES AT THE BOTTOM:

THEN SAVE AND CLOSE!

8. Remember to make sure that the terminal has access to these variables:

9. Before proceeding to test the GPU cards we will ensure that the drivers are correctly installed. The following line will provide us with the driver version:

10. Check the version of the Nvidia CUDA compiler:

TRY THE CUDA 7.5 SAMPLES:
1. Copy the samples into /home/teddy/Documents/

2. GO to the samples directory:

3. Go to the deviceQuery directory THEN make:

4. run the deviceQuery script to test if we can communicate with the GPU:

 

5. Go to the bandwidthTest directory THEN make:

 

6. run bandwidthTest:

 

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