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gpu [2017/03/16 17:10]
kocmanek [Basic commands] 		gpu [2017/05/16 10:40]
kocmanek [Servers with GPU units]
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 ===== Servers with GPU units ===== ===== Servers with GPU units =====
  
-| machine | GPU; [[https://en.wikipedia.org/wiki/CUDA#Supported_GPUs|Capability]] [cc]  | cores | GPU RAM | Comment | +| machine    | GPU; [[https://en.wikipedia.org/wiki/CUDA#Supported_GPUs|Capability]] [cc]  | cores | GPU RAM | Comment | 
-| titan-gpu  | GeForce GTX Titan Z; cc3.5 | 2 | 6 GB each core |        |+| titan-gpu  | GeForce GTX 1080 Ti; cc6.1 | 1 | 12 GB |        | 
 +| titan      | GeForce GTX Titan Z; cc3.5 | 2 | 6 GB each core |        |
 | twister1   | Tesla K40c; cc3.5          | 1 | 12 GB          |        | | twister1   | Tesla K40c; cc3.5          | 1 | 12 GB          |        |
 | twister2   | Tesla K40c; cc3.5          | 1 | 12 GB          |        | | twister2   | Tesla K40c; cc3.5          | 1 | 12 GB          |        |
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 | iridium    | Quadro K2000; cc3.0        | 1 | 2 GB           |        | | iridium    | Quadro K2000; cc3.0        | 1 | 2 GB           |        |
 | victoria   | GeForce GT 630; cc3.0      | 1 | 2 GB           | Ondrej Bojar's desktop machine | | victoria   | GeForce GT 630; cc3.0      | 1 | 2 GB           | Ondrej Bojar's desktop machine |
-| arc        | GeForce GT 630; cc3.0      | 1 | 2 GB           | Ales's desktop machine |+| arc        | GeForce GT 630; cc3.0      | 1 | 2 GB           | Lucka's desktop machine |
 | athena     | GeForce GTX 1080; cc6.1    | 1 | 8 GB           | Tom's desktop machine | | athena     | GeForce GTX 1080; cc6.1    | 1 | 8 GB           | Tom's desktop machine |
-| dll1     | GeForce GTX 1080; cc6.1    | 8 | 8 GB each core |  | +| dll1       | GeForce GTX 1080; cc6.1    | 8 | 8 GB each core |  | 
-| dll2     | GeForce GTX 1080; cc6.1    | 8 | 8 GB each core |  |+| dll2       | GeForce GTX 1080; cc6.1    | 8 | 8 GB each core |  |
  
 not used at the moment: GeForce GTX 570 (from twister2) not used at the moment: GeForce GTX 570 (from twister2)
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   qsubmit --gpumem=2G --queue="gpu.q" WHAT_SHOULD_BE_RUN   qsubmit --gpumem=2G --queue="gpu.q" WHAT_SHOULD_BE_RUN
      
 +It is recommended to use priority -100 if you are not rushing for the results and don't need to leap over your colleagues jobs.
 ==== Basic commands ==== ==== Basic commands ====
  
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   /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery   /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery
     # shows CUDA capability etc.     # shows CUDA capability etc.
 +    
 +=== Select GPU device ===
 +
 +Use variable CUDA_VISIBLE_DEVICES to constrain tensorflow to compute only on the selected one. For the use of first GPU use (GPU queue do this for you):
 +  export CUDA_VISIBLE_DEVICES=0
 +
 +To list available devices, use:
 +  /opt/cuda/samples/1_Utilities/deviceQuery/deviceQuery | grep ^Device
 +
 ===== Performance tests ===== ===== Performance tests =====
  
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-===== Installed toolkits ===== 
- 
-//This should mention where each interesting toolkit lives (on a particular machine).// 
- 
-==== TensorFlow ==== 
- 
-[[https://redmine.ms.mff.cuni.cz/projects/mmmt/repository/revisions/6a064187fc6959db9b77cf2d5350c5f4918a8067/entry/prepare_env.sh|This script]] installs TensorFlow 0.7.1 (and all other dependencies we need for Multimodal Translation) into `tf' and `tf-gpu' virtual environments. The GPU environment can be loaded by calling <code>source tf-gpu/bin/activate-gpu</code> 
- 
-OP: I created [[https://gist.github.com/oplatek/323b63b8f116cd3d78c0f492f78cc289|script]] which install Tensorflow 0.8 and test it if it uses GPU. TF is installed into `user` or `global` installation either for `python3.4` or `python2.7` 
- 
-=== Select GPU device === 
- 
-Use variable CUDA_VISIBLE_DEVICES to constrain tensorflow to compute only on the selected one. For the use of first GPU use: 
-<code>export CUDA_VISIBLE_DEVICES=0</code> 
- 
-To list available devices, use: 
-<code>/opt/cuda/samples/1_Utilities/deviceQuery/deviceQuery | grep ^Device</code> 
- 
-===== Basic commands ===== 
- 
-  lspci 
-    # is any such hardware there? 
-  nvidia-smi 
-    # more details, incl. running processes on the GPU 
-    # nvidia-* are typically located in /usr/bin 
-  watch nvidia-smi 
-    # For monitoring GPU activity in a separate terminal (thanks to Jindrich Libovicky for this!) 
-  nvcc --version 
-    # this should tell CUDA version 
-    # nvcc is typically installed in /usr/local/cuda/bin/ 
-  theano-test 
-    # dela to vubec neco uzitecneho? :-) 
-    # theano-* are typically located in /usr/local/bin/ 
-  /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery 
-    # shows CUDA capability etc. 
  
 ===== Links ===== ===== Links =====

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