CUDA - Revision history

Mbaney at 20:39, 26 February 2024

2024-02-26T20:39:15Z

← Older revision		Revision as of 20:39, 26 February 2024
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	#: <pre> module load cuda</pre>		#: <pre> module load cuda</pre>
	# Obtain a copy of the cuda samples:		# Obtain a copy of the cuda samples:
	#: <pre>rsync -a /opt/common/cuda/$CUDA Version/samples/ ~/cuda_samples</pre>		#: <pre>rsync -a /opt/common/cuda/<CUDA Version>/samples/ ~/cuda_samples</pre>
	# Build and run the device query		# Build and run the device query
	#: <pre> cd ~/cuda_samples/1_Utilities/deviceQuery/ && make && ./deviceQuery</pre>		#: <pre> cd ~/cuda_samples/1_Utilities/deviceQuery/ && make && ./deviceQuery</pre>

	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'		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'

Mbaney at 18:14, 2 March 2022

2022-03-02T18:14:47Z

← Older revision		Revision as of 18:14, 2 March 2022
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	* NVIDIA Driver		* NVIDIA Driver

	{{Note \| If you are unsure if your device is CUDA capable, please [[HelpDesk \| contact staff]].}}		{{Note \| If you are unsure if your device is CUDA capable, please [[HelpDesk \|contact staff]].}}

	==Getting Started==		==Getting Started==

Mbaney at 18:14, 2 March 2022

2022-03-02T18:14:40Z

← Older revision		Revision as of 18:14, 2 March 2022
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	* NVIDIA Driver		* NVIDIA Driver

	{{Note \| If you are unsure if your device is CUDA capable, ~~feel free to~~ contact staff~~@umiacs~~.~~umd.edu~~}}		{{Note \| If you are unsure if your device is CUDA capable, please [[HelpDesk \| contact staff]].}}

	==Getting Started==		==Getting Started==

Sabobbin at 17:00, 1 February 2016

2016-02-01T17:00:23Z

@@ Line 1: / Line 1: @@
-[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).
-=CUDA Software on Linux=
+==Prerequisites==
-==RHEL==
+{{Note | If you are unsure if your device is CUDA capable, feel free to contact staff@umiacs.umd.edu}}
-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'''
+==Getting Started==
-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 '''319.30''' or greater for Cuda 5.5.22.
+# Load the CUDA Environmental variables via [[Modules | GNU Modules]]
-<pre>
+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'

Derek: /* Cuda 6.0 Beta */

2014-04-24T02:06:28Z

Cuda 6.0 Beta

← Older revision		Revision as of 02:06, 24 April 2014
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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.		'''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.

	===Cuda 6.0 ~~Beta~~===		===Cuda 6.0===

	You need to have driver 331.62 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.		You need to have driver 331.62 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.

Derek: /* Cuda 6.0 Beta */

2014-04-24T02:06:18Z

Cuda 6.0 Beta

← Older revision		Revision as of 02:06, 24 April 2014
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	===Cuda 6.0 Beta===		===Cuda 6.0 Beta===

	You need to have driver 331.44 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.		You need to have driver 331.62 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.

	module load cuda/6.0.~~26rc1~~		module load cuda/6.0.37

	You can then make a copy of the samples to test with. All the same caveats as with the 5.5 samples above.		You can then make a copy of the samples to test with. All the same caveats as with the 5.5 samples above.

	* RHEL6 - <tt>rsync -a /opt/common/cuda/cuda-6.0.~~26rc1~~/samples ~/cuda6_samples</tt>		* RHEL6 - <tt>rsync -a /opt/common/cuda/cuda-6.0.37/samples ~/cuda6_samples</tt>


	==Ubuntu 12.04==		==Ubuntu 12.04==

Derek at 16:55, 24 February 2014

2014-02-24T16:55:42Z

← Older revision		Revision as of 16:55, 24 February 2014
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	===Cuda 6.0 Beta===		===Cuda 6.0 Beta===

	You need to have driver 331.44 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.		You need to have driver 331.44 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.

Derek at 16:54, 24 February 2014

2014-02-24T16:54:24Z

← Older revision		Revision as of 16:54, 24 February 2014
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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.		'''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.

			===Cuda 6.0 Beta===
			You need to have driver 331.44 or later installed to use this (see above for finding out what driver version you are running) and you will need to ask staff to upgrade if not. This is only available currently on RHEL6 x86_64.

			module load cuda/6.0.26rc1

			You can then make a copy of the samples to test with. All the same caveats as with the 5.5 samples above.

			* RHEL6 - <tt>rsync -a /opt/common/cuda/cuda-6.0.26rc1/samples ~/cuda6_samples</tt>


	==Ubuntu 12.04==		==Ubuntu 12.04==

Derek: /* RHEL */

2013-11-25T20:23:51Z

RHEL

← Older revision		Revision as of 20:23, 25 November 2013
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	<pre>		<pre>
	$ cat /proc/driver/nvidia/version		# cat /proc/driver/nvidia/version
	NVRM version: NVIDIA UNIX x86_64 Kernel Module ~~304~~.64 ~~Tue~~ Oct 30 10:58:20 PDT ~~2012~~		NVRM version: NVIDIA UNIX x86_64 Kernel Module 331.20 Wed Oct 30 17:43:35 PDT 2013
	GCC version: gcc version 4.4.~~6 20120305~~ (Red Hat 4.4.6-4) (GCC)		GCC version: gcc version 4.4.7 20120313 (Red Hat 4.4.7-3) (GCC)
	</pre>		</pre>

Derek: /* RHEL */

2013-11-25T20:21:00Z

RHEL

← Older revision		Revision as of 20:21, 25 November 2013
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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'''		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'''

	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.		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 '''319.30''' or greater for Cuda 5.5.22.

	<pre>		<pre>