Installing CUDA on Ubuntu 12.04

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If you’re looking for a quick and easy way to get started with GPGPU computing, you really can’t go wrong with nVidia’s CUDA. It is a parallel computing architecture that harnesses the power of GPUs in order to achieve significant speedups in problems that would have otherwise taken a significantly longer time while executing on the CPU. It is the most mature architecture for GPGPU computing, with a wide number of libraries based around it. This guide is going to cover the installation of the CUDA toolkit and SDK on Ubuntu, along with the necessary development drivers.

NOTE – For CUDA to work, you must have an nVidia GPU which is CUDA capable. If you have an ATI GPU, this guide is not for you. You can, however, look into OpenCL.

If your GPU meets the requirements, head over to the CUDA Downloads page and download the toolkit, drivers and SDK from under the Linux section, taking care to choose the 32 or 64-bit version depending on your system. If you’re not sure, run
uname -m
in a terminal. i686 denotes a 32-bit system, and x86_64 denotes a 64-bit one. For the toolkit, I chose the one titled Ubuntu 11.04, although either of the Ubuntu toolkits should work just fine.

Save all three files in an easy to access location, like your Home folder. Do not proceed with this guide until you’ve either memorized the following steps or printed them for easy reference!

STEP I – Driver installation

Make sure the requisite tools are installed using the following command -

sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev

Next, blacklist the required modules (so that they don’t interfere with the driver installation) -

gksu gedit /etc/modprobe.d/blacklist.conf

Add the following lines to the end of the file, one per line -

blacklist amd76x_edac
blacklist vga16fb
blacklist nouveau
blacklist rivafb
blacklist nvidiafb
blacklist rivatv

Save the file and exit gedit.

Update – WARNING – Reader Bart points out in the comments that the purge nvidia* command resulted in a prompt to remove ubuntu-desktop (for him). If this occurs, do not proceed or it will wreck your GUI. You could reinstall ubuntu-desktop after the entire process but I’m not sure if that’ll affect your data (configs for each app).

In order to get rid of any nVidia residuals, run the following command in a terminal -

sudo apt-get remove --purge nvidia*

This may take a while, so be patient. Once it’s done, reboot your machine. At the login screen, don’t login just yet. Press Ctrl+Alt+F1 to switch to a text-based login. Login and switch to the directory which contains the downloaded drivers, toolkit and SDK. Run the following commands -

sudo service lightdm stop
chmod +x devdriver*.run

where devdriver*.run is the full name of your driver. Next, start the installation with -

sudo ./devdriver*.run

Follow the onscreen instructions. If the installer throws up an error about nouveau still running, allow it to create a blacklist for nouveau, quit the installation and reboot. In that case, run the following commands again -

sudo service lightdm stop
sudo ./devdriver*.run

The installation should now proceed smoothly. When it asks you if you want the 32-bit libraries and if you want it to edit xorg.conf to use these drivers by default, allow both.

Reboot once the installation completes.

STEP II – CUDA toolkit installation

Next, enter the following in a terminal window (in the directory where the files are stored) -

chmod +x cudatoolkit*.run
sudo ./cudatoolkit*.run

where cudatoolkit*.run is the full name of the toolkit installer. I recommend leaving the installation path to its default setting (/usr/local/cuda) unless you have a specific reason for not doing so.

STEP III – CUDA SDK installation

Update – I’ve just found out that the SDK must be installed as a regular user (and not as root) according to the “nVidia CUDA C Getting Started Guide for Linux” (refer pg 11). Apparently, this is to prevent access issues with the SDK files.
Also, readers Fernest Hall and Adub have mentioned tips in the comments that might be useful for some readers, although they haven’t worked for me. Thanks guys!

Update 2 – Reader Alan has mentioned a link in the comment section. Although I haven’t checked it out yet, it might work for you.

Once the toolkit is installed, enter the following in a terminal -

chmod +x gpucomputingsdk*.run
./gpucomputingsdk*.run

where gpucomputingsdk*.run is the full name of the SDK installer. Again, follow the instructions onscreen to complete the installation.

You’re now ready to journey into the world of CUDA and GPGPU computing. If you’re looking for books on the same, check out this page.

Credit for the driver installation goes to this awesome video.

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79 thoughts on “Installing CUDA on Ubuntu 12.04

      • I tried to install cuda 5 on ubunto 12.04 but i receive the following error :
        E: Impossible de trouver le paquet libxll-dev
        E: Impossible de trouver le paquet libgll-mesa-glx
        E: Impossible de trouver le paquet libglul-mesa
        E: Impossible de trouver le paquet libglul-mesa-dev

      • The correct package names are libx11-dev, libgl1-mesa-glx, libglu1-mesa and libglu1-mesa-dev. You seem to have substituted the digits for the letter ‘l’. Please copy-paste the command as listed in the guide.

  1. Tried your installation method of Ubuntu 12.04 installation since the one in the nVidia documentation did not work for me. Specifically, even though CUDA gets installed and apps like VMD work fine but I can’t compile any of the gpucomputing examples – lot’s of compiler errors. Strangely, OpenCL examples work just fine.
    Unfortunately using your instructions did not remedy that. I gues we will have to wait for nVidia to update.

    • I’m getting errors in the gpucomputing examples too. I thought they were on my part since I’m new to CUDA! Btw, I just found out that gpucomputing must be installed as a regular user (and not as root). Although that didn’t help in my case, it might be of some use to you.

      • I tried both, installation of gpucomputing examples as root and regular user – no difference.

  2. Indeed, thanks very much! I’m running through this on my Ubuntu setup and everything is going swimingly. I even had the nouveau driver running and everything. Thanks again!

  3. I had to do a bit more stuff to compile the CUDA SDK.

    If you want the SDK to compile, but get errors:
    In the Terminal:

    1.) sudo gedit /etc/ld.so.conf
    and add this lines at the end:
    /usr/local/cuda/lib64
    /usr/local/cuda/lib

    2.) ldconfig

    Assuming you installed to /usr/local/cuda:
    3.) export LD_LIBRARY_PATH=/usr/local/cuda/lib:$LD_LIBRARY_PATH
    4.) export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

    If the SDK still does not compile, but aborts during the compiling of nbody, do following:
    gedit ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk
    find all the lines which begin with “LIB += ” and contain ${OPENGLLIB} as well as $(RENDERCHECKGLLIB)
    (In my version there were 3 of them.)
    Switch in those lines the position of ${OPENGLLIB} and $(RENDERCHECKGLLIB)

    (For me this did the trick. If you find this helpfull, feel free to add it to your post)
    Cheers.

    • Thank you, I’ll check it out :)

      UPDATE – It managed to get farther, but the SDK still won’t compile entirely. Thanks anyway, I’ve mentioned your comment in the article :)

    • Hi Fernest,
      I had to do what you said to remove compile errors. I do get some warnings though like ‘-Wimplicit does not work’. Is that fine? Do you use gcc 4.6.3? But thanks you saved my day. I am using GTX 690 so got nervous about it.
      Regards
      Vivek

  4. Will this work if I have hybrid graphics (Intel integrated and NVIDIA discrete)? I recently tried installing the NVIDIA driver for a 560M card and I guess Ubuntu always uses the Intel card by default. I also had a problem where the resolution changed to the lowest setting, so I reinstalled Ubuntu. From everything else I’ve seen online I might need bumblebee instead of the NVIDIA driver. You have a pretty solid guide here either way.

    TL;DR What assumptions are you making in this tutorial, are you using hybrid graphics or just NVIDIA?

    • Thanks for your kind words Will :) I don’t own a machine with hybrid graphics, so I’ve tested it on ones with just nVidia graphics – a laptop with an 8600M GT, and a desktop with a GTX 260. Sorry but I’m not really sure about your case.

      • I actually figured out my situation, so I’ll post here for others to see: basically if you have hybrid graphics, do not install the NVIDIA driver from the website. Download the 4.2 Toolkit and the SDK, and install the bumblebee package (can easily be found via Google). If this is working then you may run the command “optirun glxspheres” or “optirun glxgears” (from the package mesa-apps) to test out a program running on the NVIDIA card.

        Then of course, make sure your PATH and LD_LIBRARY_PATH variables are updated in .bashrc for the CUDA bin and lib respectively (don’t forget lib64 for x64!). Reboot or logout to save changes.

        Now install the Toolkit and SDK as usual.

        The last thing that might cause issues is the version of gcc and g++. Long story short, make sure the pointers gcc and g++ in /usr/bin (and subsequently /usr/local/cuda/bin) are pointing to gcc-4.5 and g++-4.5 (can get these with apt-get) since they are the most recent versions supported by nvcc. Use the soft-link command to achieve this.

        The easiest program to make and run in the SDK is vectorAdd since it has one .cu file and no other .cpp or .h files. Make it and go to the bottom of the /C/bin folder and run it via “optirun ./vectoradd”. It should run perfectly. Now the next step would be to run matrixMul, since this uses .cpp files and will test your gcc/g++ dependencies. If you have the correct version (and both versions match) and all soft-links are done correctly, it should compile and run via “optirun ./matrixMul”. Then you can move on and address the other examples in the SDK, but this is at least enough to compile and run your own programs if you know how to write a makefile.

        This should address most common issues users will find and sums up what seemed like dozens of other posts I read. Best of luck!

      • A couple of extra comments. The SDK would not compile until I followed ALL of the steps at

        http://fcns.eu/2012/05/24/cuda-4-2-9-sdk-compile-on-ubuntu-12-04-lts-fails-with-undefined-reference-to-gluerrorstring/

        and ran the command “source .profile” after adding the line

        export LIBRARY_PATH=”$LIBRARY_PATH:/usr/lib/nvidia-current”

        to .profile in my home directory (which is really where the other exports that Will mentions should go.) I would also reiterate that ANY cuda file (or anything else you want to run on the graphics card) has to be run with the “optirun” prefix if you’re using Bumblebee on an optimus-enabled machine.

  5. Pingback: 如何在Ubuntu 12.04上配置CUDA 4.2 | bfcat-计算机视觉博客

  6. Thank you for the article. it was helpful and it was presented very professionally.

    I do have a few questions regarding errors that appeared at the end of compiling the SDK file.

    collect2: ld returned 1 exit status
    make[2]: *** [../../bin/linux/release/randomFog] Error 1
    make[2]: Leaving directory `/root/NVIDIA_GPU_Computing_SDK/CUDALibraries/src/randomFog’
    make[1]: *** [src/randomFog/Makefile.ph_build] Error 2
    make[1]: Leaving directory `/root/NVIDIA_GPU_Computing_SDK/CUDALibraries’
    make: *** [all] Error 2

    Do you know why these error messages are here? could they cause future problems?
    we are using cuda for important research so we want to make sure everything is working without errors.

    One important detail is that we accidentally installed SDK from root. What problems will this cause?

    ———–My System Information————
    -Ubuntu 12.04
    -Nvidia driver and the toolbar has been fully installed
    -driver version 295.41
    -gcc 4.6.3
    -I have already made the suggested changes to common.mk, common_cudalib.mk along with the changes to boxFilterNPP, imageSegmentationNPP, freeImageInteropNPP, histEqualizationNPP, and randomFog Makefiles. these changes were suggested at http://forums.nvidia.com/index.php?showtopic=231150
    -everything we installed was from cuda 4.2

    • Hey Nick,

      Thanks for your kind words :) The SDK merely includes examples and is as such not necessary for CUDA development. As far as I know, these errors seem to be pretty common (I still have them) and should not cause any issues in the future. They have something to do with the SDK referencing a different gcc version than the one you have installed, if I recall correctly. I’m not exactly sure how to fix these linking errors and I haven’t had the time to work them all out, so I’m afraid you’ll have to look elsewhere. If you do find a solution, please let me know so I can add it to the guide!

      And I’d accidentally installed the SDK as root too, all you have to do is delete the folder NVIDIA_GPU_Computing_SDK and reinstall it as a regular user. The CUDA getting started guide recommends this to avoid access issues, although this seems to be a moot point since the SDK won’t compile anyway.

      • thank you very much for the quick responce. luckily i did successfully compile sdk earlier this morning. without any errors. everything is running smothly now. thank you for the tutorial tho.

  7. Hi
    First of all thank you for the post, it was very useful. i am having a compilation error which is the following:
    navish@navish-MacBookPro:~/cuda/test$ nvcc helloworld1.cu
    helloworld1.cu:2:28: fatal error: ../common/book.h: No such file or directory
    compilation terminated.
    trying to find out what the problem is and would really appreciate any help of yours.
    Regards

    • Hi, thanks for your feedback :) First off, your compile command is correct. I’m guessing you’re using the hello world example from the “CUDA By Example” book. Unless you have specified the correct path to the book.h header, the nvcc compiler will output an error. If you’ve not received any source files with the book, you will not have the book.h header since it is a custom header developed by the authors of the book, and is not a part of the standard CUDA library. You can replace it with , and use the corresponding C headers for and C library functions your program may use.

      • thanks again.yes i am starting off with the book and did not receive any source files. i will replace it and shall let you know about the output.
        Regards

  8. Getting stuck while rebooting, after purging for any nVidia residuals. Can’t i simply install the drivers making the run file executable and then following the other steps of Installing CUDA n SDK? what difference will it make? Pls help. Need Cuda for blender cycles.

      • The machine is not able to show show the login screen. Btw i’m using Ubuntu Studio 12.04, the start up screen is where the machine gets stuck after the initial animation of the curved streaks going in circles stops.
        Sys config: i5 2nd generation, 16 gb Ram, nVidia 550 Ti

  9. What happen if I have a second GPU from AMD and I wan to use it for my diplay. I should not allow the Nvidia driver change my xorg.conf?

  10. Hi! When I run the programs from NVIDIA, I get a no CUDA-capable device is detected

    Have you run ino this please?

  11. Pingback: Update: CUDA computing « Entertaining Research

  12. This is really good, but to complete the task you must follow the instructions on this website http://fcns.eu/2012/05/24/cuda-4-2-9-sdk-compile-on-ubuntu-12-04-lts-fails-with-undefined-reference-to-gluerrorstring/ and then go to NVIDIA_GPU_Computing_SDK and type “make” to build the test programs. Finally go to NVIDIA_GPU_Computing_SDK/C/bin/linux and type “deviceQuery” to see if your CUDA card is operating properly. There are lots of cool demos in the same directory. I like smokeParticles.

  13. Pingback: Installing CUDA on Ubuntu 12.04 |

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  15. When I run the command sudo apt-get remove –purge nvidia*, it tells me:
    The following packages will be REMOVED:
    nvidia-common* nvidia-current* nvidia-settings* ubuntu-desktop*
    I’m especially concerned about the last package (although it only seems to be a meta package), is it really safe to remove this?
    Thanks!

    • From this link, removing ubuntu-desktop seems to be inviting trouble. I’m not sure about it, but I’d advise you to hold off for now. Can you post the details of lsmod on pastebin and link to it here? And try asking on the Ubuntu forums as well, a lot of knowledgeable folk out there :) let’s see if we can get to the bottom of this!

      • Thanks for your fast response. I was in a brave (but stupid) mood yesterday and went ahead, and it is indeed not healthy to remove ubuntu-desktop :) But since I was already having some problems with Ubuntu (mainly on memory usage when running code parallel with MPI), I’m migrating back to good old OpenSUSE. I’ve been working with that for years, and it suits me better than Ubuntu…
        So sorry, can’t help you (or myself) get to the bottom of this, but you might want to warn about this in your post. I was using a relatively clean and up-to-date Ubuntu (12.04) installation, so others might run into the same problem.
        Cheers, Bart

  16. Pingback: Installing CUDA on Ubuntu 12.04 | Peter Luk's Blog

  17. Hi all,
    Thanks for this post. I am also having problems when trying to compile the SDK examples. When I go:
    make
    in the ~/NVIDIA_GPU_Computing_SDK/ I get:
    make[2]: Entering directory `/home/edgar/NVIDIA_GPU_Computing_SDK/C/src/SobolQRNG’
    /usr/local/cuda/bin/nvcc: 1: /usr/local/cuda/bin/nvcc: Syntax error: “)” unexpected
    make[2]: *** [obj/i386/release/sobol_gpu.cu.o] Error 2
    make[2]: Leaving directory `/home/edgar/NVIDIA_GPU_Computing_SDK/C/src/SobolQRNG’
    make[1]: *** [src/SobolQRNG/Makefile.ph_build] Error 2
    make[1]: Leaving directory `/home/edgar/NVIDIA_GPU_Computing_SDK/C’
    make: *** [all] Error 2

    so it seems that something is wrong with nvcc. I get the same error when I try to compile any cuda file: /usr/local/cuda/bin/nvcc: 1: /usr/local/cuda/bin/nvcc: Syntax error: “)” unexpected. Do you guys have any idea about how to go about it?

    Cheers,
    Edgar

  18. Hi again,
    Just wanted to say thanks for posting this and your help. Finally it worked for me! :)
    What I did was to change my kernel from 32 bits to 64 bits and followed the steps here again and BUM!

    I still have compilation errors for when building the SDK examples but I am reading
    http://fcns.eu/2012/05/24/cuda-4-2-9-sdk-compile-on-ubuntu-12-04-lts-fails-with-undefined-reference-to-gluerrorstring/ and it seems like it is an already documented fix.

    Cheers!
    Edgar

  19. Hi there,
    Could you please help me with my problem? I’ve got stuck in it in two weeks already :(

    nvcc warning : option ‘host-compilation’ has been deprecated and is ignored
    nvcc fatal : A single input file is required for a non-link phase when an outputfile is specified
    CMake Error at cuda_stuff_library_generated_get_feature_value_tex2d.cu.o.cmake:198 (message):
    Error generating
    /home/nana/Desktop/rodrigo/src/applications/objects_detection/CMakeFiles/cuda_stuff_library.dir/__/__/__/src/objects_detection/gpu/./cuda_stuff_library_generated_get_feature_value_tex2d.cu.o

    make[2]: *** [CMakeFiles/cuda_stuff_library.dir/__/__/__/src/objects_detection/gpu/./cuda_stuff_library_generated_get_feature_value_tex2d.cu.o] Error 1
    make[1]: *** [CMakeFiles/cuda_stuff_library.dir/all] Error 2
    make: *** [all] Error 2
    ———————

    And it seems I couldn’t use “nvcc -v”, it happend that “nvcc: command not found”
    I am new in Ubuntu and Cuda and Cmake. I’ve just worked with them since last week :(

    Thanks a lot :)

    • Hey, I’d love to help out but I’m sorry I don’t have access to a CUDA enabled machine right now – it was just a summer intern. I’m not experienced enough to help offsite, and this guide was just a documentary of my findings as I managed to get CUDA working on Ubuntu 12.04. I’m afraid you’ll have to look elsewhere. Hope you manage to solve it soon :)

  20. Pingback: How to install CUDA on hybrid graphics notebooks with Ubuntu 12.04 | Jaideep @ CES

  21. Is there no way of installing the drivers without removing the ubuntu-desktop package? Or rather, is removing just bumblebee-nvidia*, nvidia-common*, nvidia-current* and nvidia-settings* sufficient to install the drivers?

    • Ideally, the removal of bumblebee-nvidia*, nvidia-common*, nvidia-current* and nvidia-settings* ought to be sufficient to install the drivers. I do not remember getting a prompt to remove ubuntu-desktop while installing the development drivers. Do consult the Ubuntu forums and back your system up before proceeding though.

  22. Pingback: installing GTX 560 on Windows 7 and Ubuntu 12.04 « Heru Suhartanto

  23. hi! im new in ubuntu and im stuck with the devdriver*.run command. the thing is, i dont know the name of my driver. can you help me with this?.. thank you very much!

  24. Pingback: Installing CUDA 5 on Ubuntu 12.04 | sn0v

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  28. Hi, is there some one who can hlep me , i started following the instruction above to install cuda but i get this error messages.
    shams@ubuntu:~$ sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
    Reading package lists… Done
    Building dependency tree
    Reading state information… Done
    libglu1-mesa is already the newest version.
    libglu1-mesa set to manually installed.
    Some packages could not be installed. This may mean that you have
    requested an impossible situation or if you are using the unstable
    distribution that some required packages have not yet been created
    or been moved out of Incoming.
    The following information may help to resolve the situation:

    The following packages have unmet dependencies:
    freeglut3-dev : Depends: libgl1-mesa-dev but it is not going to be installed or
    libgl-dev
    Depends: libxt-dev but it is not going to be installed
    Depends: libxext-dev but it is not going to be installed
    libgl1-mesa-glx : Depends: libglapi-mesa (= 8.0.2-0ubuntu3)
    Recommends: libgl1-mesa-dri (>= 7.2)
    libglu1-mesa-dev : Depends: libglu1-mesa (= 8.0.2-0ubuntu3) but 8.0.4-0ubuntu0.6 is to be installed
    Depends: libgl1-mesa-dev but it is not going to be installed or
    libgl-dev
    libx11-dev : Depends: libx11-6 (= 2:1.4.99.1-0ubuntu2) but 2:1.4.99.1-0ubuntu2.1 is to be installed
    Depends: libxcb1-dev but it is not going to be installed
    Recommends: libx11-doc but it is not going to be installed
    libxi-dev : Depends: libxi6 (= 2:1.6.0-0ubuntu2) but 2:1.6.0-0ubuntu2.1 is to be installed
    Depends: libxext-dev but it is not going to be installed
    libxmu-dev : Depends: libxext-dev but it is not going to be installed
    Depends: libxt-dev but it is not going to be installed
    E: Unable to correct problems, you have held broken packages.
    THANKS

      • Thank you Utkarsh, i will try it now, this whole week i had been trying to install CUDA, did so many fresh install of Ubuntu and follow the instruction on forum. I hop you could help me out with this,
        you have mentioned about three files but i found only two on CUDA download page DEB** RUN , is that right ?
        here is my system config.
        i7 processor with Nvidia Geforce 640
        I am trying to run blender under Ubuntu and i want to use GPU option which needs CUDA as far as i guess. Blender runs fine but without GPU option.

  29. after running given command this is what i got
    shams@ubuntu:~$ sudo apt-get -f install
    [sudo] password for shams:
    Reading package lists… Done
    Building dependency tree
    Reading state information… Done
    0 upgraded, 0 newly installed, 0 to remove and 154 not upgraded.
    BTW ITS A FRESH INSTALL.

  30. Pingback: Cuda4Ubuntu | bittnt's Research Blog

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