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Both sides previous revision Previous revision 2024/10/02 15:21 popel 2022/09/20 09:39 rosa [GPU at ÚFAL] todo slurm2022/09/07 14:38 vodrazka 2022/08/23 13:15 vodrazka 2022/08/23 13:14 vodrazka 2022/08/23 11:57 fucik [Servers with GPU units] 2022/08/23 11:56 fucik [Servers with GPU units] 2021/12/15 17:57 kasner [Set-up CUDA and CUDNN] 2021/12/15 17:57 kasner [Pytorch Environment] 2021/12/15 17:53 kasner Update CUDA version2021/12/03 17:28 vodrazka 2021/12/03 17:27 vodrazka 2021/12/03 17:27 vodrazka 2021/08/31 12:25 vodrazka [Servers with GPU units] 2021/07/02 16:50 ptacek 2021/07/02 16:49 ptacek 2021/07/02 13:25 vodrazka 2021/07/02 13:19 vodrazka [Servers with GPU units] 2021/02/15 13:21 vodrazka [Servers with GPU units] 2021/02/15 13:20 vodrazka [Servers with GPU units] 2021/02/15 12:51 vodrazka [Servers with GPU units] 2021/02/15 12:41 vodrazka [Servers with GPU units] 2021/02/15 12:36 vodrazka [Servers with GPU units] 2021/02/15 12:35 vodrazka [Servers with GPU units] 2021/02/04 16:39 krubinski [Basic commands] 2020/09/14 15:29 fucik [Rules] 2020/09/14 15:28 fucik [Rules] 2020/07/27 13:12 dusek [Servers with GPU units] 2020/03/14 15:49 popel [Servers with GPU units] 2020/03/14 12:16 popel [Rules] 2020/03/06 15:14 popel one bad GPU removed from dll62020/03/06 09:14 vodrazka [Servers with GPU units] 2019/11/12 16:03 popel [Set-up CUDA and CUDNN] 2019/11/08 09:57 vodrazka [Servers with GPU units] 2019/10/31 09:23 vodrazka 2019/10/18 09:57 vodrazka [Servers with GPU units] 2019/10/02 14:34 vodrazka [Servers with GPU units] 2019/10/02 14:33 vodrazka [Servers with GPU units] 2019/08/27 19:12 popel [Rules] 2019/08/27 19:10 popel [Rules] 2019/07/15 11:21 vodrazka [Servers with GPU units] 2019/07/02 15:18 vodrazka [Servers with GPU units] 2019/04/17 15:13 ufal [Servers with GPU units] 2019/04/17 14:11 ufal [Servers with GPU units] 2019/03/05 13:15 vodrazka [Servers with GPU units] 2019/02/11 13:03 popel [Rules] at se pouziva i gpu-troja Go Next revision		Previous revision 2024/10/02 15:21 popel 2022/09/20 09:39 rosa [GPU at ÚFAL] todo slurm2022/09/07 14:38 vodrazka 2022/08/23 13:15 vodrazka 2022/08/23 13:14 vodrazka 2022/08/23 11:57 fucik [Servers with GPU units] 2022/08/23 11:56 fucik [Servers with GPU units] 2021/12/15 17:57 kasner [Set-up CUDA and CUDNN] 2021/12/15 17:57 kasner [Pytorch Environment] 2021/12/15 17:53 kasner Update CUDA version2021/12/03 17:28 vodrazka 2021/12/03 17:27 vodrazka 2021/12/03 17:27 vodrazka 2021/08/31 12:25 vodrazka [Servers with GPU units] 2021/07/02 16:50 ptacek 2021/07/02 16:49 ptacek 2021/07/02 13:25 vodrazka 2021/07/02 13:19 vodrazka [Servers with GPU units] 2021/02/15 13:21 vodrazka [Servers with GPU units] 2021/02/15 13:20 vodrazka [Servers with GPU units] 2021/02/15 12:51 vodrazka [Servers with GPU units] 2021/02/15 12:41 vodrazka [Servers with GPU units] 2021/02/15 12:36 vodrazka [Servers with GPU units] 2021/02/15 12:35 vodrazka [Servers with GPU units] 2021/02/04 16:39 krubinski [Basic commands] 2020/09/14 15:29 fucik [Rules] 2020/09/14 15:28 fucik [Rules] 2020/07/27 13:12 dusek [Servers with GPU units] 2020/03/14 15:49 popel [Servers with GPU units] 2020/03/14 12:16 popel [Rules] 2020/03/06 15:14 popel one bad GPU removed from dll62020/03/06 09:14 vodrazka [Servers with GPU units] 2019/11/12 16:03 popel [Set-up CUDA and CUDNN] 2019/11/08 09:57 vodrazka [Servers with GPU units] 2019/10/31 09:23 vodrazka 2019/10/18 09:57 vodrazka [Servers with GPU units] 2019/10/02 14:34 vodrazka [Servers with GPU units] 2019/10/02 14:33 vodrazka [Servers with GPU units] 2019/08/27 19:12 popel [Rules] 2019/08/27 19:10 popel [Rules] 2019/07/15 11:21 vodrazka [Servers with GPU units] 2019/07/02 15:18 vodrazka [Servers with GPU units] 2019/04/17 15:13 ufal [Servers with GPU units] 2019/04/17 14:11 ufal [Servers with GPU units] 2019/03/05 13:15 vodrazka [Servers with GPU units] 2019/02/11 13:03 popel [Rules] at se pouziva i gpu-troja2019/02/11 10:50 naplava [Servers with GPU units] 2019/02/07 10:44 vodrazka GPU troja machines added2019/01/08 09:36 vodrazka [Servers with GPU units] 2018/12/19 12:21 vodrazka GPU machine table update2018/12/16 16:26 straka [Rules] Go
gpu [2021/02/15 12:51] vodrazka [Servers with GPU units]		gpu [2024/10/02 15:21] (current) popel
Line 2:		Line 2:
	This page summarizes which UFAL servers have some GPU card, and suggests basic diagnostic commands, paths to installed tools, etc., simply everything necessary at the very beginning of using GPUs for experiments.		This page summarizes which UFAL servers have some GPU card, and suggests basic diagnostic commands, paths to installed tools, etc., simply everything necessary at the very beginning of using GPUs for experiments.
		+
		+	**TODO: IN 2022 MOVING FROM SGE TO SLURM** (see [[slurm|slurm guidelines]]) -- **commands like ''qsub'' and ''qstat'' will stop working!**
		+
		+	**IN 2024: Newly, all the documentation is at a dedicated wiki https://ufal.mff.cuni.cz/lrc (you need to use ufal and [[internal:welcome-at-ufal#small-linguistic-password|small-linguistic password]] to access the wiki from outside of the UFAL network).***
	===== Servers with GPU units =====		===== Servers with GPU units =====
Line 7:		Line 11:
	| machine | GPU type | GPU driver version | [[https://en.wikipedia.org/wiki/CUDA#GPUs_supported|cc]] | GPU cnt | GPU RAM (GB) | machine RAM (GB)|		| machine | GPU type | GPU driver version | [[https://en.wikipedia.org/wiki/CUDA#GPUs_supported|cc]] | GPU cnt | GPU RAM (GB) | machine RAM (GB)|
-	| dll1 |  Quadro RTX 5000 |  440.33.01 |  7.5 |  8 |  16 |  367 |	+	| dll1 |  Quadro RTX 5000 |   455.23.05 |  7.5 |  8 |  16 |  366.2 |
-	| dll3 |  GeForce GTX 1080 Ti |  440.33.01 |  6.1 |  10 |  11 |  249 |	+	| dll3 |  NVIDIA RTX A4000 |   510.73.08 |  8.6 |  10 |  16 |  248.8 |
-	| dll4 |  GeForce GTX 1080 Ti |  440.33.01 |  6.1 |  10 |  11 |  249 |	+	| dll4 |  GeForce GTX 1080 Ti |   455.23.05 |  6.1 |  10 |  11 |  248.8 |
-	| dll5 |  GeForce GTX 1080 Ti |  440.33.01 |  6.1 |  10 |  11 |  249 |	+	| dll5 |  GeForce GTX 1080 Ti |   455.23.05 |  6.1 |  10 |  11 |  248.8 |
-	| dll6 |  GeForce GTX 1080 Ti |  440.33.01 |  6.1 |  8 |  11 |  249 |	+	| dll6 |  NVIDIA RTX A4000 |   510.73.08 |  8.6 |  8 |  16 |  248.8 |
-	| dll7 |  GeForce RTX 2080 Ti |  440.33.01 |  7.5 |  8 |  11 |  249 |	+	| dll7 |  NVIDIA RTX A4000 |   510.73.08 |  8.6 |  8 |  16 |  248.8 |
-	| dll8 |  Quadro RTX 5000 |  440.33.01 |  7.5 |  8 |  16 |  367 |	+	| dll8 |  Quadro RTX 5000 |   455.23.05 |  7.5 |  8 |  16 |  366.2 |
-	| dll9 |  GeForce RTX 3090 |  455.23.05 |  8.6 |  4 |  24 |  183 |	+	| dll9 |  GeForce RTX 3090 |   455.23.05 |  8.6 |  4 |  25 |  183.0 |
-	| dll10 |  GeForce RTX 3090 |  455.23.05 |  8.6 |  4 |  24 |  183 |	+	| dll10 |  GeForce RTX 3090 |   455.23.05 |  8.6 |  4 |  25 |  183.0 |
	GPU cluster ''gpu-troja.q'' at Troja:		GPU cluster ''gpu-troja.q'' at Troja:
	| machine | GPU type | GPU driver version | [[https://en.wikipedia.org/wiki/CUDA#GPUs_supported|cc]] | GPU cnt | GPU RAM (GB) | machine RAM (GB)|		| machine | GPU type | GPU driver version | [[https://en.wikipedia.org/wiki/CUDA#GPUs_supported|cc]] | GPU cnt | GPU RAM (GB) | machine RAM (GB)|
-	| tdll1 |  Quadro P5000 |  440.33.01 |  6.1 |  8 |  16 |  245 |	+	| tdll1 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 |
-	| tdll2 |  Quadro P5000 |  440.33.01 |  6.1 |  8 |  16 |  245 |	+	| tdll2 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 |
-	| tdll3 |  Quadro P5000 |  440.33.01 |  6.1 |  8 |  16 |  245 |	+	| tdll3 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 |
-	| tdll4 |  Quadro P5000 |  440.33.01 |  6.1 |  8 |  16 |  245 |	+	| tdll4 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 |
-	| tdll5 |  Quadro P5000 |  440.33.01 |  6.1 |  8 |  16 |  245 |	+	| tdll5 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 |
	Desktop machines:		Desktop machines:
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	You need to set library path from your ''~/.bashrc'':		You need to set library path from your ''~/.bashrc'':
-	CUDA_version=10.1	+	CUDA_version=11.1
-	CUDNN_version=7.6	+	CUDNN_version=8.0
	CUDA_DIR_OPT=/opt/cuda/$CUDA_version		CUDA_DIR_OPT=/opt/cuda/$CUDA_version
	if [ -d "$CUDA_DIR_OPT" ] ; then		if [ -d "$CUDA_DIR_OPT" ] ; then
Line 67:		Line 71:
	fi		fi
-	* When not using Theano, just Tensorflow this can be simplified to ''export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/cuda/10.1/lib64:/opt/cuda/10.1/cudnn/7.6/lib64''.	+	* When not using Theano, just Tensorflow this can be simplified to ''export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/cuda/10.1/lib64:/opt/cuda/11.1/cudnn/8.0/lib64''.
	* Note that the ''cudnn'' library is compiled for specific version of ''cuda''. If you need specific version of ''cudnn'', you can look in ''/opt/cuda/$CUDA_version/cudnn/'' whether it is available for a given ''$CUDA_version''.		* Note that the ''cudnn'' library is compiled for specific version of ''cuda''. If you need specific version of ''cudnn'', you can look in ''/opt/cuda/$CUDA_version/cudnn/'' whether it is available for a given ''$CUDA_version''.
Line 89:		Line 93:
	This environment have TensorFlow 1.8.0 and all necessary requirements for NeuralMonkey.		This environment have TensorFlow 1.8.0 and all necessary requirements for NeuralMonkey.
-	==== Pytorch Environment ====	+	==== PyTorch Environment ====
-	If you want to use pytorch, there is a ready-made environment in	+	Install PyTorch following the instructions on https://pytorch.org.
-	/home/hajicj/anaconda3/envs/pytorch/bin	+	At the time of writing, the recommended setup for CUDA 11.1 (supported by all GPU nodes) is:
-		+
-	It does rely on the CUDA and CuDNN setup above.	+
		+	pip3 install torch==1.10.0+cu111 torchvision==0.11.1+cu111 torchaudio==0.10.0+cu111 -f https://download.pytorch.org/whl/cu111/torch_stable.html
	==== Using cluster ====		==== Using cluster ====

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