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| [http://en.wikipedia.org/wiki/CUDA CUDA] is a programming architecture developed by NVIDIA to allow General Purpose Computing on GPUs or '''"GPGPU"'''. It requires a specific card and driver to work correctly, UMIACS has a number of facilities and labs that have Cuda hardware available. | | [http://en.wikipedia.org/wiki/CUDA CUDA] is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). |
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| ==CUDA Software on Linux== | | ==Prerequisites== |
| | * NVIDIA GPU device |
| | * NVIDIA Driver |
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| ===RHEL5===
| | {{Note | If you are unsure if your device is CUDA capable, please [[HelpDesk |contact staff]].}} |
| The RHEL5 CUDA infrastructure comes in two parts.
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| First is the driver which installs libraries in /usr/lib.
| | ==Getting Started== |
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| Second is the CUDA toolkit. The currently supported CUDA toolkit is stored under /usr/local. Please change the "common.mk" settings in your CUDA SDK to set the CUDA root directory to "/usr/local"
| | # Load the CUDA Environmental variables via [[Modules | GNU Modules]] |
| | #*Multiple versions are available. See the modules documentation and <code>module list cuda</code> for more information. |
| | #: <pre> module load cuda</pre> |
| | # Obtain a copy of the cuda samples: |
| | #: <pre>rsync -a /opt/common/cuda/<CUDA Version>/samples/ ~/cuda_samples</pre> |
| | # Build and run the device query |
| | #: <pre> cd ~/cuda_samples/1_Utilities/deviceQuery/ && make && ./deviceQuery</pre> |
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| You will also need to put the CUDA libraries in your LD_LIBRARY_PATH.
| | Assuming the deviceQuery complication completed without error, you should now see output listing the details of the GPUs in your system. If desired you can compile additional samples by switching to their respective directory and running 'make' |
| *If you are using a 64-bit machine this will be /usr/local/lib64.
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| *If you are using a 32-bit machine this will be /usr/local/lib.
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| Older versions of the CUDA toolkit are stored in /usr/local/stow/cudatoolkit_X.Y where X.Y is the version number. So, CUDA 2.2 is stored in /usr/local/stow/cudatoolkit2.2
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| ===RHEL6===
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| '''Updated for Cuda 5'''
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| The first component you will need if you are not using a resource that you know is running CUDA is to check to see if you have the Nvidia driver running. You can run '''cat /proc/driver/nvidia/version'''
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| If something like the following example does not show you will need to contact staff to see if your hardware is capable and if so we will need to add the driver to the machine. You must have version '''304.64''' or greater for Cuda 5.0.35.
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| <pre>
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| $ cat /proc/driver/nvidia/version
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| NVRM version: NVIDIA UNIX x86_64 Kernel Module 304.64 Tue Oct 30 10:58:20 PDT 2012
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| GCC version: gcc version 4.4.6 20120305 (Red Hat 4.4.6-4) (GCC)
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| </pre>
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| The other component is the toolkit and in RHEL6 we have relocated non-locally compiled software into /opt/common. This includes the CUDA toolkit. You can find all the versions available in '''/opt/common/cuda'''.
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| <pre>
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| $ ls /opt/common/cuda
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| cuda-5.0.35 cudatoolkit-4.0.17 cudatoolkit-4.2.9
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| cudatoolkit-3.2.16 cudatoolkit-4.1.28 UMIACS-CUDA-SDK.diff
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| </pre>
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| You will need to setup a number of environmental variables to get started.
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| * bash/sh
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| ** export PATH=/opt/common/cuda/cuda-5.0.35/bin:${PATH}
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| ** export LD_RUN_PATH=/opt/common/cuda/cuda-5.0.35/lib64:/opt/common/cuda/cuda-5.0.35/lib:${LD_RUN_PATH}
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| ** export LIBRARY_PATH=/usr/lib64/nvidia:/usr/lib/nvidia
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| * tcsh/csh
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| ** setenv PATH /opt/common/cuda/cuda-5.0.35/bin:${PATH}
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| ** setenv LD_RUN_PATH /opt/common/cuda/cuda-5.0.35/lib64:/opt/common/cuda/cuda-5.0.35/lib:${LD_RUN_PATH}
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| ** setenv LIBRARY_PATH /usr/lib64/nvidia:/usr/lib/nvidia
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| To get started you might want to build and test with the Cuda GPU Computing SDK. In Cuda 5 the SDK is no longer separate and you need to make a copy of the examples directory inside the cuda toolkit directory. You can do this by running the following command.
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| rsync -a /opt/common/cuda/cuda-5.0.35/samples ~/cuda_samples
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| You should now be able to run <tt>make</tt> command in the <tt>~/cuda_samples</tt> directory and compile all the examples. Please note that you will need to activate a MPI module if you wish to be able to compile all the examples correctly, for example you can run <tt>module load openmpi-x86_64</tt>. You can alternatively compile the specific sample codes by going into the respective directories and typing <tt>make</tt>
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| '''Note''': Compiling requires the <tt>LIBRARY_PATH</tt> environmental variable above to tell GCC where to find the nvidia shared libraries. If using an alternate compiler please consult it as to how to modify the compile time linker path.
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| ===Ubuntu 12.04===
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| First you will need to ensure you have the updated x-updates repository added to your workstation. Please contact staff@umiacs.umd.edu and we will help get this in place for your workstation.
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| The other component is the toolkit and in Ubuntu non-locally compiled software is available in /opt/common. This includes the CUDA toolkit. You can find all the versions available in '''/opt/common/cuda'''.
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| Ubuntu and Cuda are tested in 4.2.9 and higher.
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| <pre>
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| $ ls /opt/common/cuda
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| cudatoolkit-3.2.16 cudatoolkit-4.0.17 cudatoolkit-4.1.28 cudatoolkit-4.2.9
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| </pre>
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| * bash/sh
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| ** export PATH=/opt/common/cuda/cudatoolkit-4.2.9/bin:${PATH}
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| ** export LD_LIBRARY_PATH=/opt/common/cuda/cudatoolkit-4.2.9/lib64:/opt/common/cuda/cudatoolkit-4.2.9/lib:${LD_LIBRARY_PATH}
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| * tcsh/csh
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| ** setenv PATH /opt/common/cuda/cudatoolkit-4.2.9/bin:${PATH}
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| ** setenv LD_LIBRARY_PATH /opt/common/cuda/cudatoolkit-4.2.9/lib64:/opt/common/cuda/cudatoolkit-4.2.9/lib:${LD_LIBRARY_PATH}
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| To get started you might want to build and test with the GPU Computing SDK. You can do this by running '''/opt/common/cuda/cudatoolkit-4.2.9/gpucomputingsdk_4.2.9_linux.run'''. It will prompt you to where you want to install the SDK.
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| Once it is installed please apply this patch from the directory you installed the SDK into.
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| <pre>
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| patch -p1 < /opt/common/cuda/cudatoolkit-4.2.9/UMIACS-CUDA-SDK-Ubuntu-12.04.diff
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| </pre>
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| You should now be able to run '''make''' and compile all the examples.
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