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gpu [2018/04/27 18:22]
popel [Servers with GPU units] 		gpu [2018/06/12 12:08]
ufal [TensorFlow Environment]
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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)**+**THE NEW CLUSTER (SGE 8.1.9)**
  
-Multiple versions of ''cuda'' can be accessed in ''/opt''. +Multiple versions of ''cuda'' can be accessed in ''/opt/cuda''. **Compared to the old cluster there is a difference in setting the CUDA_DIR_OPT variable!!**
-System default version for cuda library is configured in ''/etc/ld.so.conf.d/cuda.conf'' as:+
  
-  /opt/cuda/lib64 +You need to set library path from your ''~/.bashrc'':
-  /opt/cuda/extras/CUPTI/lib64+
  
-Actual version used depends on the link in ''/opt''. For example:+  CUDNN_version=7.0 
 +  CUDA_version=9.0 
 +  CUDA_DIR_OPT=/opt/cuda/$CUDA_version 
 +  if [ -d "$CUDA_DIR_OPT" ] ; then 
 +    CUDA_DIR=$CUDA_DIR_OPT 
 +    export CUDA_HOME=$CUDA_DIR 
 +    export THEANO_FLAGS="cuda.root=$CUDA_HOME,device=gpu,floatX=float32" 
 +    export PATH=$PATH:$CUDA_DIR/bin 
 +    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_DIR/cudnn/$CUDNN_version/lib64:$CUDA_DIR/lib64 
 +    export CPATH=$CUDA_DIR/cudnn/$CUDNN_version/include:$CPATH 
 +  fi
  
-  ls -l /opt +  * When not using Theano, just Tensorflow this can be simplified to ''export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/cuda/9.0/lib64:/opt/cuda/9.0/cudnn/7.0/lib64''.
-  ... +
-  lrwxrwxrwx 1 root root  8 dub  9 12:30 cuda -> cuda-9.0 +
-  ... +
-   +
-This means that the system is using ''cuda 9.0'' by default. +
- +
-If system default version does not work for you, you can set library path from your ''~/.bashrc''. Your LD_LIBRARY_PATH should contain: +
- +
-  /opt/cuda-$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.+  * There is no default and you always need to set ''LD_LIBRARY_PATH'' explicitly.
  
 +  * Note that ''cudnn'' library is compiled for specific version of ''cuda''. If you need specific version of ''cudnn'', you can look in ''/opt/cuda/$CUDA_version/cudnn/'' whether it is available for given ''$CUDA_version''.
  
  
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 And then you can activate your environment: And then you can activate your environment:
  
-  source activate tf1 +  source activate tf18 
-  source activate tf1cpu+  source activate tf18cpu
  
-This environment have TensorFlow 1.0 and all necessary requirements for NeuralMonkey.+This environment have TensorFlow 1.8.0 and all necessary requirements for NeuralMonkey.
  
 ==== Pytorch Environment ==== ==== Pytorch Environment ====

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