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gpu [2017/03/16 17:09]
kocmanek [Using cluster] 		gpu [2017/03/16 17:11]
kocmanek [Installed toolkits]
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 ===== How to use cluster ===== ===== How to use cluster =====
  
-In this section will be explained how to use cluster properly. Rule number one, always use the GPU queue (never log in machine by ssh). +In this section will be explained how to use cluster properly. 
 ==== TensorFlow Environment ==== ==== TensorFlow Environment ====
  
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 ==== Basic commands ==== ==== 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.
 +    
 +=== 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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