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gpu [2018/12/01 21:09]
popel [Rules] -pe smp now works with gpu
gpu [2019/02/11 10:50]
naplava [Servers with GPU units]
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 ===== Servers with GPU units ===== ===== Servers with GPU units =====
 GPU cluster ''gpu-ms.q'' at Malá Strana: GPU cluster ''gpu-ms.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)| AVX + 
-| dll1 |  GeForce GTX 1080 |  396.24 |  6.1 |  8 |  8 |  249 | yes +| machine | GPU type | GPU driver version | [[https://en.wikipedia.org/wiki/CUDA#GPUs_supported|cc]] | GPU cnt | GPU RAM (GB) | machine RAM (GB)| 
-| dll2 (out of order) |  GeForce GTX 1080 |  396.24 |  6.1 |  8 |  8 |  249 | yes +| dll1 |  GeForce GTX 1080 |  396.24 |  6.1 |  8 |  8 |  249 | 
-| dll3 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  249 | yes +| dll2 |  GeForce GTX 1080 |  396.24 |  6.1 |  8 |  8 |  249 | 
-| dll4 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  249 | yes +| dll3 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  249 | 
-| dll5 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  249 | yes | +| dll4 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  249 | 
-| dll6 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  123 | yes +| dll5 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  249 |                                                                     
-| kronos |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  1 |  11 |  123 | yes | +| dll6 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  10 |  11 |  123 |                                                                     
-| titan1 |  GeForce GTX 1080 |  396.24 |  6.1 |  1 |  8 |  30 | yes | +| dll7 |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  1 |  11 |  123                                                                      
-| titan2 |  Tesla K40c |  396.24 |  3.5 |  1 |  11 |  30 | yes +| kronos |  GeForce GTX 1080 Ti |  396.24 |  6.1 |  1 |  11 |  123 |                                                                    
-twister1 |  Tesla K40c |  396.24 |  3.|  1 |  11 |  45 no +| titan1 |  GeForce GTX 1080 |  396.24 |  6.1 |  1 |  8 |  30 |                                                                         
-twister2 |  Tesla K40c |  396.24 |  3.|  1 |  11 |  45 no |+| titan2 |  Tesla K40c |  396.24 |  3.5 |  1 |  11 |  30 | 
 + 
 +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)
 +tdll1 |  Quadro P5000 |  410.48 |  6.|  8 |  16 |  245 |                                                                            
 +| tdll2 |  Quadro P5000 |  410.48 |  6.1 |  |  16  245                                                                            
 +tdll3 |  Quadro P5000 |  410.48 |  6.|  8 |  16 |  245 |                                                                            
 +| tdll4 |  Quadro P5000 |  410.48 |  6.1 |  |  16  245 |                                                                            
 +| tdll5 |  Quadro P5000 |  410.48 |  6.1 |  8 |  16 |  245                                                                           
  
 Desktop machines: Desktop machines:
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 | 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 |
  
-Not used at the moment: GeForce GTX 570 (from twister2) 
 Multiple versions of CUDA library are accessible on each machine together with cudnn. Theano and TensorFlow is supported. Multiple versions of CUDA library are accessible on each machine together with cudnn. Theano and TensorFlow is supported.
  
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 ===== Rules ===== ===== Rules =====
   * First, read [[internal:Linux network]] and [[:Grid]].   * First, read [[internal:Linux network]] and [[:Grid]].
-  * All the rules from [[:Grid]] apply, even more strictly than for CPU because there are too many GPU users and not as many GPUs available. So as a reminder: always use GPUs via ''qsub'' (or ''qrsh''), never via ''ssh''. You can ssh to any machine e.g. to run ''nvidia-smi'' or ''htop'', but not to start computing on GPU. Don't forget to specify you RAM requirements with e.g. ''-l mem_free=8G,act_mem_free=8G,h_vmem=12G''.+  * All the rules from [[:Grid]] apply, even more strictly than for CPU because there are too many GPU users and not as many GPUs available. So as a reminder: always use GPUs via ''qsub'' (or ''qrsh''), never via ''ssh''. You can ssh to any machine e.g. to run ''nvidia-smi'' or ''htop'', but not to start computing on GPU. Don't forget to specify you RAM requirements with e.g. ''-l mem_free=8G,act_mem_free=8G,h_data=12G''
 +    * **Note that you need to use ''h_data'' instead of ''h_vmem'' for GPU jobs.** CUDA driver allocates a lot of "unused" virtual memory (tens of GB per card), which is counted in ''h_vmem'', but not in ''h_data''. All usual allocations (''malloc'', ''new'', Python allocations) seem to be included in ''h_data''.
   * Always specify the number of GPU cards (e.g. ''gpu=1''), the minimal Cuda capability you need (e.g. ''gpu_cc_min3.5=1'') and your GPU memory requirements (e.g. ''gpu_ram=2G''). Thus e.g. <code>qsub -q gpu-ms.q -l gpu=1,gpu_cc_min3.5=1,gpu_ram=2G</code>   * Always specify the number of GPU cards (e.g. ''gpu=1''), the minimal Cuda capability you need (e.g. ''gpu_cc_min3.5=1'') and your GPU memory requirements (e.g. ''gpu_ram=2G''). Thus e.g. <code>qsub -q gpu-ms.q -l gpu=1,gpu_cc_min3.5=1,gpu_ram=2G</code>
   * If you need more than one GPU card (on a single machine), always require as many CPU cores (''-pe smp X'') as many GPU cards you need. E.g. <code>qsub -q gpu-ms.q -l gpu=4,gpu_cc_min3.5=1,gpu_ram=7G -pe smp 4</code>   * If you need more than one GPU card (on a single machine), always require as many CPU cores (''-pe smp X'') as many GPU cards you need. E.g. <code>qsub -q gpu-ms.q -l gpu=4,gpu_cc_min3.5=1,gpu_ram=7G -pe smp 4</code>

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