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doku:vsc3_gpu [2018/01/16 12:57] shdoku:vsc3_gpu [2018/04/10 09:47] markus
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-^  Tesla k20m (kepler)  ^^+^  Enterprise-grade Tesla k20m (kepler)  ^^
 |  Total amount of global memory|4742 MBytes | |  Total amount of global memory|4742 MBytes |
 |  (13) Multiprocessors, (192) CUDA Cores/MP|2496 CUDA Cores | |  (13) Multiprocessors, (192) CUDA Cores/MP|2496 CUDA Cores |
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-^  Tesla m60 (maxwell)  ^^+^  Enterprise-grade Tesla m60 (maxwell)  ^^
 |  Total amount of global memory|8114 MBytes | |  Total amount of global memory|8114 MBytes |
 |  (16) Multiprocessors, (128) CUDA Cores/MP|2048 CUDA Cores | |  (16) Multiprocessors, (128) CUDA Cores/MP|2048 CUDA Cores |
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-^  Consumer grade GeForce GTX 1080 (pascal)  ^^+^  Consumer-grade GeForce GTX 1080 (pascal)  ^^
 |  Total amount of global memory|8113 MBytes | |  Total amount of global memory|8113 MBytes |
 |  (20) Multiprocessors, (128) CUDA Cores/MP|2560 CUDA Cores | |  (20) Multiprocessors, (128) CUDA Cores/MP|2560 CUDA Cores |
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 GPU nodes are selected via the **generic resource (--gres=)** and **constraints (-C,--constraint=)** options: GPU nodes are selected via the **generic resource (--gres=)** and **constraints (-C,--constraint=)** options:
-  * c2050 (fermi) GPU node: <code>#SBATCH -C c2050 
-#SBATCH --gres=gpu:2 
-</code> 
   * k20m (kepler) GPU nodes: <code>#SBATCH -C k20m   * k20m (kepler) GPU nodes: <code>#SBATCH -C k20m
 #SBATCH --gres=gpu:2 #SBATCH --gres=gpu:2
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 -------------------------------------------------- --------------------------------------------------
  
-===== Visualization ======+===== Visualization (!!currently not supported!!) ======
  
 To make use of a gpu node for visualization you need to perform the following steps. To make use of a gpu node for visualization you need to perform the following steps.
  • doku/vsc3_gpu.txt
  • Last modified: 2018/04/10 09:52
  • by markus