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Both sides previous revision Previous revision 2018/08/10 13:49 rosa [Set-up CUDA and CUDNN] 2018/06/21 10:04 vodrazka [Servers with GPU units] 2018/06/21 10:04 vodrazka [Servers with GPU units] 2018/06/12 14:17 popel 2018/06/12 13:50 machacek.dominik [Servers with GPU units] 2018/06/12 12:42 vodrazka [Servers with GPU units] 2018/06/12 12:42 vodrazka [Servers with GPU units] 2018/06/12 12:08 ufal [TensorFlow Environment] 2018/05/31 10:30 popel [Set-up CUDA and CUDNN] 2018/05/30 09:57 vodrazka [Set-up CUDA and CUDNN] 2018/05/30 09:54 vodrazka [Set-up CUDA and CUDNN] 2018/04/27 18:22 popel [Servers with GPU units] 2018/04/24 10:01 vodrazka [Set-up CUDA and CUDNN] 2018/04/23 12:53 vodrazka [Set-up CUDA and CUDNN] 2018/04/16 11:35 kocmanek [Performance tests] 2018/04/16 11:29 kocmanek [Performance tests] 2018/04/16 11:18 kocmanek [Performance tests] 2018/04/13 12:50 kocmanek [Performance tests] 2018/04/12 17:11 kocmanek [Performance tests] 2018/04/12 16:02 kocmanek [Performance tests] 2018/04/12 15:17 kocmanek [Performance tests] 2018/04/09 12:45 vodrazka documenting default settings for cuda and cudnn libraries2018/04/05 14:41 vodrazka table update - Quadro P5000 for testing in twister22018/03/22 11:14 vodrazka Updated cluster GPU table2018/03/21 15:29 ufal [Servers with GPU units] 2018/02/20 17:54 kruza [Rules] typo2018/02/09 15:15 popel [Set-up CUDA and CUDNN] 2018/02/08 15:26 popel [Rules] 2018/02/08 15:21 kocmanek [Servers with GPU units] 2018/02/08 15:20 kocmanek [Rules] 2018/02/08 15:16 kocmanek [Servers with GPU units] 2018/02/08 15:10 kocmanek [Servers with GPU units] 2018/02/08 14:56 kocmanek [Servers with GPU units] 2018/01/25 17:27 popel [Using cluster] 2018/01/23 23:16 popel [Servers with GPU units] 2018/01/15 21:51 popel [Rules] 2018/01/15 10:39 popel [Set-up CUDA and CUDNN] 2018/01/08 13:25 popel dll6 now has 9 cards, so it is the same config as dll32018/01/06 21:17 popel [Rules] 2017/12/05 18:02 popel [Rules] 2017/11/23 14:15 bojar link to munin graphs2017/11/13 09:43 bojar [Rules] 2017/10/17 16:51 popel [Rules] 2017/10/17 16:43 popel [Rules] 2017/10/17 16:39 popel [Using cluster] 2017/10/17 16:38 popel [Rules] 2017/10/17 16:37 popel 2017/10/12 13:42 ufal [How to use cluster] 2017/10/11 13:07 bojar people should not set CUDA_VISIBLE_DEVICES2017/10/11 11:46 popel [Basic commands] 2017/09/11 11:26 fucik Go Next revision		Previous revision 2018/12/19 12:21 vodrazka GPU machine table update2018/12/16 16:26 straka [Rules] 2018/12/01 21:09 popel [Rules] -pe smp now works with gpu2018/11/28 11:21 laitoch [Rules] 2018/11/28 11:11 laitoch [Rules] 2018/11/14 13:46 kocmi [Using cluster] 2018/11/12 10:36 vodrazka [Servers with GPU units] 2018/11/01 14:41 vodrazka [Servers with GPU units] 2018/10/22 16:02 vodrazka [Servers with GPU units] 2018/10/10 16:48 fucik 2018/10/02 16:41 kocmi [Set-up CUDA and CUDNN] 2018/10/01 10:07 vodrazka [Servers with GPU units] 2018/09/05 10:17 vodrazka [Servers with GPU units] 2018/08/10 13:49 rosa [Set-up CUDA and CUDNN] 2018/06/21 10:04 vodrazka [Servers with GPU units] 2018/06/21 10:04 vodrazka [Servers with GPU units] 2018/06/12 14:17 popel 2018/06/12 13:50 machacek.dominik [Servers with GPU units] 2018/06/12 12:42 vodrazka [Servers with GPU units] 2018/06/12 12:42 vodrazka [Servers with GPU units] 2018/06/12 12:08 ufal [TensorFlow Environment] 2018/05/31 10:30 popel [Set-up CUDA and CUDNN] 2018/05/30 09:57 vodrazka [Set-up CUDA and CUDNN] 2018/05/30 09:54 vodrazka [Set-up CUDA and CUDNN] 2018/04/27 18:22 popel [Servers with GPU units] 2018/04/24 10:01 vodrazka [Set-up CUDA and CUDNN] 2018/04/23 12:53 vodrazka [Set-up CUDA and CUDNN] 2018/04/16 11:35 kocmanek [Performance tests] 2018/04/16 11:29 kocmanek [Performance tests] 2018/04/16 11:18 kocmanek [Performance tests] 2018/04/13 12:50 kocmanek [Performance tests] 2018/04/12 17:11 kocmanek [Performance tests] 2018/04/12 16:02 kocmanek [Performance tests] 2018/04/12 15:17 kocmanek [Performance tests] 2018/04/09 12:45 vodrazka documenting default settings for cuda and cudnn libraries2018/04/05 14:41 vodrazka table update - Quadro P5000 for testing in twister22018/03/22 11:14 vodrazka Updated cluster GPU table2018/03/21 15:29 ufal [Servers with GPU units] 2018/02/20 17:54 kruza [Rules] typo2018/02/09 15:15 popel [Set-up CUDA and CUDNN] 2018/02/08 15:26 popel [Rules] 2018/02/08 15:21 kocmanek [Servers with GPU units] 2018/02/08 15:20 kocmanek [Rules] 2018/02/08 15:16 kocmanek [Servers with GPU units] 2018/02/08 15:10 kocmanek [Servers with GPU units] 2018/02/08 14:56 kocmanek [Servers with GPU units] 2018/01/25 17:27 popel [Using cluster] 2018/01/23 23:16 popel [Servers with GPU units] 2018/01/15 21:51 popel [Rules] 2018/01/15 10:39 popel [Set-up CUDA and CUDNN] 2018/01/08 13:25 popel dll6 now has 9 cards, so it is the same config as dll3 Go Next revision Both sides next revision
gpu [2018/02/20 17:54] kruza [Rules] typo		gpu [2018/04/24 10:01] vodrazka [Set-up CUDA and CUDNN]
Line 5:		Line 5:
	===== Servers with GPU units =====		===== Servers with GPU units =====
	GPU cluster ''gpu.q'' at Malá Strana:		GPU cluster ''gpu.q'' at Malá Strana:
-		+	| 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 | [[https://en.wikipedia.org/wiki/CUDA#GPUs_supported|cc]] | GPUs | GPU RAM | RAM | Comment |	+	| dll1 |  GeForce GTX 1080 |  384.69 |  6.1 |  8 |  8 |  250 |
-	| iridium                    | Quadro K2000        |  cc3.0 |   1|   2 GB | 52 GB | driver(iridium)=367.48 |	+	| dll2 |  GeForce GTX 1080 |  387.34 |  6.1 |  8 |  8 |  250 |
-	| titan-gpu                  | GeForce GTX Titan Z |  cc3.5 |   2|   6 GB | 32 GB | driver(titan-gpu)=381.22 |	+	| dll3 |  GeForce GTX 1080 Ti |  375.66 |  6.1 |  9 |  11 |  250 |
-	| twister1; twister2; kronos | Tesla K40c          |  cc3.5 |   1|  12 GB | 48 GB; 48GB; 128 GB | driver(twister*)=367.48, driver(kronos)=384.81 |	+	| dll4 |  GeForce GTX 1080 Ti |  375.66 |  6.1 |  10 |  11 |  250 |
-	| titan                      | GeForce GTX 1080    |  cc6.1 |   1|   8 GB | 32 GB  | driver(titan)=381.22|	+	| dll5 |  GeForce GTX 1080 Ti |  384.69 |  6.1 |  10 |  11 |  250 |
-	| dll1; dll2                 | GeForce GTX 1080    |  cc6.1 |   8|   8 GB | 250 GB | driver(dll1)=375.66, driver(dll2)=387.26 |	+	| dll6 |  GeForce GTX 1080 Ti |  384.69 |  6.1 |  9 |  11 |  122 |
-	| dll4; dll5                 | GeForce GTX 1080 Ti |  cc6.1 |  10|  11 GB | 250 GB | driver(dll4)=375.66, driver(dll5)=384.69 |	+	| gpu |  GeForce GTX TITAN Z |  381.22 |  3.5 |  2 |  6 |  31 |
-	| dll3                       | GeForce GTX 1080 Ti |  cc6.1 |   9|  11 GB | 250 GB | driver(dll3)=375.66 |	+	| iridium |  Quadro K2000 |  367.48 |  3.0 |  1 |  2 |  504 |
-	| dll6                       | GeForce GTX 1080 Ti |  cc6.1 |   9|  11 GB | 126 GB | driver(dll6)=384.69 |	+	| kronos |  GeForce GTX 1080 Ti |  384.81 |  6.1 |  1 |  11 |  125 |
		+	| titan |  GeForce GTX 1080 |  381.22 |  6.1 |  1 |  8 |  31 |
		+	| twister1 |  Tesla K40c |  367.48 |  3.5 |  1 |  11 |  47 |
		+	| twister2 |  Quadro P5000 |  367.48 |  6.1 |  1 |  17 |  47 |
	Desktop machines:		Desktop machines:
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	You also need to use ''qsub -q gpu.q@dll[256]'' because only those machines have drivers which support CUDA 9.		You also need to use ''qsub -q gpu.q@dll[256]'' because only those machines have drivers which support CUDA 9.
		+
		+	**Testing configuration (so far on twister1 & 2, titan and titan-gpu only)**
		+
		+	Multiple versions of ''cuda'' can be accessed in ''/opt''.
		+	System default version for cuda library is configured in ''/etc/ld.so.conf.d/cuda.conf'' as:
		+
		+	/opt/cuda/lib64
		+	/opt/cuda/extras/CUPTI/lib64
		+
		+	Actual version used depends on the link in ''/opt''. For example:
		+
		+	ls -l /opt
		+	...
		+	lrwxrwxrwx 1 root root  8 dub  9 12:30 cuda -> cuda-9.0
		+	...
		+
		+	This means that the system is using ''cuda 9.0'' by default.
		+
		+	If system default version does not work for you, you can set library path from your ''~/.bashrc''. Your LD_LIBRARY_PATH should contain:
		+
		+	/opt/cuda-$CUDA_version/lib64
		+
		+	In order to link specific version of ''cudnn'' your LD_LIBRARY_PATH should contain:
		+
		+	/opt/cuda-$CUDA_version/cudnn/$CUDNN_version/lib64
		+
		+	Please check if required CUDNN_version is available for given CUDA_version.
		+
		+
		+
		+
		+
	==== TensorFlow Environment ====		==== TensorFlow Environment ====
Line 132:		Line 167:
	| titan      | GeForce GTX 1080 Ti                |   10:45:11 | (new result with correct CUDA version) |		| titan      | GeForce GTX 1080 Ti                |   10:45:11 | (new result with correct CUDA version) |
	| dll1       | (2 GPU) GeForce GTX 1080; cc6.1    |   12:34:34 | Probably only one GPU was used |		| dll1       | (2 GPU) GeForce GTX 1080; cc6.1    |   12:34:34 | Probably only one GPU was used |
		+	| twister2   | Quadro P5000                       |   13:19:00 |  |
	| dll2       | GeForce GTX 1080; cc6.1            |   13:01:05 | Only one GPU was used |		| dll2       | GeForce GTX 1080; cc6.1            |   13:01:05 | Only one GPU was used |
	| titan-gpu  | (2 GPU) GeForce GTX Titan Z; cc3.5 |   16:05:24 | Probably only one GPU was used |		| titan-gpu  | (2 GPU) GeForce GTX Titan Z; cc3.5 |   16:05:24 | Probably only one GPU was used |
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	The previous benchmark only compares the speed of processing units within the GPUs and do not take into account the size of memory. Therefore I have conducted another benchmark, this time for each graphic card I have increased the batch size as much as possible so the model still could fit into the GPU (the previous benchmark model had batch size 20). This way the results should be more representative of the power for each GPU.		The previous benchmark only compares the speed of processing units within the GPUs and do not take into account the size of memory. Therefore I have conducted another benchmark, this time for each graphic card I have increased the batch size as much as possible so the model still could fit into the GPU (the previous benchmark model had batch size 20). This way the results should be more representative of the power for each GPU.
-	| GPU; Cuda capability       | GPU RAM |  Walltime | Batch size | Machine |	+	| GPU; Cuda capability       | GPU RAM |  Walltime | Batch size | Machine   |
-	| Tesla K40c; cc3.5          |   12 GB |           |        |  |	+	| GeForce GTX 1080 Ti; cc6.1 |   11 GB |  00:55:56 |       2300 | dll5      |
-	| GeForce GTX 1080 Ti; cc6.1 |   11 GB |  00:55:56 |       2300 | dll5 |	+	| GeForce GTX 1080; cc6.1    |    8 GB |  01:10:57 |       1700 | dll1      |
-	| GeForce GTX 1080; cc6.1    |    8 GB |  01:10:57 |       1700 | dll1 |	+	| Quadro P5000               |   16 GB |  01:17:00 |       3400 | twister2  |
	| GeForce GTX Titan Z; cc3.5 |    6 GB |  02:20:47 |       1100 | titan-gpu |		| GeForce GTX Titan Z; cc3.5 |    6 GB |  02:20:47 |       1100 | titan-gpu |
-	| Quadro K2000; cc3.0        |    2 GB |  28:15:26 |         50 | iridium |	+	| Quadro K2000; cc3.0        |    2 GB |  28:15:26 |         50 | iridium   |
	===== Links =====		===== Links =====

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