Difference between revisions of "NVidia CUDA Worksation installation instructions"

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(Install SiftGPU library and its dependancies =)
(From Distribution repository (Debian / Ubuntu, quite old versions))
 
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== Install cuda toolkit  ==
 
== Install cuda toolkit  ==
  
From debian non-free repository, install the following packages  
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=== From Distribution repository (Debian / Ubuntu, quite old versions) ===
 
+
* DEBIAN : from debian ''non-free'' repository, install the following packages  
 +
  nvidia-cuda-toolkit nvidia-cuda-dev
 +
* UBUNTU : from ''multiverse'' repository, install the following packages
 
   nvidia-cuda-toolkit nvidia-cuda-dev
 
   nvidia-cuda-toolkit nvidia-cuda-dev
  
== Install SiftGPU library and its dependancies  ===
+
=== From the nVidia Developer website (Ubuntu, always the latest version) ===
 +
Install the package for your distribuition and architecture from : https://developer.nvidia.com/cuda-downloads
  
 +
== Install SiftGPU library and its dependancies  ==
 
*get SiftGPU from [http://cs.unc.edu/~ccwu/siftgpu/ | SiftGPU website]  
 
*get SiftGPU from [http://cs.unc.edu/~ccwu/siftgpu/ | SiftGPU website]  
 
*extract SiftGPU in /usr/loca/src/robot  
 
*extract SiftGPU in /usr/loca/src/robot  

Latest revision as of 17:02, 2 October 2015

This page contains guidelines to install the iCub nVidia CUDA Workstation.

We assume you have installed a working Debian or Ubuntu on the laptop. You can freely decide to install 32 bit or 64 bit, the code compiles on both architectures. Be aware that if you plan to share the repository with other machines, all machines need to have the same architecture (32 versus 64 bits, same versions of the libraries). A possibility would be to share the same code directory and different builds.

Prerequisite : basic system setup for a iCub machine

Please follow the instructions on page Generic iCub machine installation instructions, in order to prepare a generic machine for the iCub network. Then, follow the below steps to customize it as the iCub Laptop

NOTE

In the following instructions, we assume that the installed OS is a Debian GNU/Linux Wheezy. if you are usign a different distribution os release, please modify the instructions accordingly.

Install cuda toolkit

From Distribution repository (Debian / Ubuntu, quite old versions)

  • DEBIAN : from debian non-free repository, install the following packages
 nvidia-cuda-toolkit nvidia-cuda-dev
  • UBUNTU : from multiverse repository, install the following packages
 nvidia-cuda-toolkit nvidia-cuda-dev

From the nVidia Developer website (Ubuntu, always the latest version)

Install the package for your distribuition and architecture from : https://developer.nvidia.com/cuda-downloads

Install SiftGPU library and its dependancies

  • get SiftGPU from | SiftGPU website
  • extract SiftGPU in /usr/loca/src/robot
  • install dependancies (DevIL and GLEW), by installing the following packages
libdevil-dev libglew-dev
  • compile SiftGPU