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gpu [2021/02/04 16:39]
krubinski [Basic commands] 		gpu [2022/09/07 14:38]
vodrazka
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 | 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 |  7.5 |   8 |  16.0 |  366.0 |  +| dll1 |  Quadro RTX 5000 |   455.23.05 |  7.5 |  8 |  16 |  366.2 | 
-| dll3 |  GeForce GTX 1080 Ti |  440.33 |  6.1 |  10 |  11.0 |  248.0 | +| dll3 |  NVIDIA RTX A4000 |   510.73.08 |  8.6 |  10 |  16 |  248.8 | 
-| dll4 |  GeForce GTX 1080 Ti |  440.33 |  6.1 |  10 |  11.0 |  248.0 | +| dll4 |  GeForce GTX 1080 Ti |   455.23.05 |  6.1 |  10 |  11 |  248.8 | 
-| dll5 |  GeForce GTX 1080 Ti |  440.33 |  6.1 |  10 |  11.0 |  248.0 | +| dll5 |  GeForce GTX 1080 Ti |   455.23.05 |  6.1 |  10 |  11 |  248.8 | 
-| dll6 |  GeForce GTX 1080 Ti |  440.33 |  6.1 |   9 |  11.0 |  248.0 | +| dll6 |  NVIDIA RTX A4000 |   510.73.08 |  8.6 |  8 |  16 |  248.8 | 
-| dll7 |  GeForce RTX 2080 Ti |  418.39 |  7.5 |   8 |  11.0 |  248.0 |                                                                  +| dll7 |  NVIDIA RTX A4000 |   510.73.08 |  8.6 |  8 |  16 |  248.8 | 
-| dll8 | Quadro RTX 5000      |  440.33 |  7.5 |   8 |  16.0 |  366.0 |  +| dll8 |  Quadro RTX 5000 |   455.23.05 |  7.5 |  8 |  16 |  366.2 | 
-| kronos |  Tesla K40c        |  418.39 |  3.5 |   1 |  11.0 |  122.0 |                                                                                                                                               +| dll9 |  GeForce RTX 3090 |   455.23.05 |  8.6 |  4 |  25 |  183.0 | 
 +| 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 |  410.48 |  6.1 |  8 |  16.0 |  245.0 |                                                                        +| tdll1 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 | 
-| tdll2 |  Quadro P5000 |  410.48 |  6.1 |  8 |  16.0 |  245.0 |                                                                        +| tdll2 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 | 
-| tdll3 |  Quadro P5000 |  410.48 |  6.1 |  8 |  16.0 |  245.0 |                                                                        +| tdll3 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 | 
-| tdll4 |  Quadro P5000 |  410.48 |  6.1 |  8 |  16.0 |  245.0 |                                                                        +| tdll4 |  Quadro P5000 |   455.23.05 |  6.1 |  8 |  16 |  245.0 | 
-| tdll5 |  Quadro P5000 |  410.48 |  6.1 |  8 |  16.0 |  245.0 | +| 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
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   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''.
  
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 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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