Changes in doc/guide/gpu_setup.rst [63602b1:8b31efa] in sasmodels


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  • doc/guide/gpu_setup.rst

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    9494Device Selection 
    9595================ 
     96**OpenCL drivers** 
     97 
    9698If you have multiple GPU devices you can tell the program which device to use. 
    9799By default, the program looks for one GPU and one CPU device from available 
     
    104106was used to run the model. 
    105107 
    106 **If you don't want to use OpenCL, you can set** *SAS_OPENCL=None* 
    107 **in your environment settings, and it will only use normal programs.** 
    108  
    109 If you want to use one of the other devices, you can run the following 
     108If you want to use a specific driver and devices, you can run the following 
    110109from the python console:: 
    111110 
     
    115114This will provide a menu of different OpenCL drivers available. 
    116115When one is selected, it will say "set PYOPENCL_CTX=..." 
    117 Use that value as the value of *SAS_OPENCL*. 
     116Use that value as the value of *SAS_OPENCL=driver:device*. 
     117 
     118To use the default OpenCL device (rather than CUDA or None), 
     119set *SAS_OPENCL=opencl*. 
     120 
     121In batch queues, you may need to set *XDG_CACHE_HOME=~/.cache*  
     122(Linux only) to a different directory, depending on how the filesystem  
     123is configured.  You should also set *SAS_DLL_PATH* for CPU-only modules. 
     124 
     125    -DSAS_MODELPATH=path sets directory containing custom models 
     126    -DSAS_OPENCL=vendor:device|cuda:device|none sets the target GPU device 
     127    -DXDG_CACHE_HOME=~/.cache sets the pyopencl cache root (linux only) 
     128    -DSAS_COMPILER=tinycc|msvc|mingw|unix sets the DLL compiler 
     129    -DSAS_OPENMP=1 turns on OpenMP for the DLLs 
     130    -DSAS_DLL_PATH=path sets the path to the compiled modules 
     131 
     132 
     133**CUDA drivers** 
     134 
     135If OpenCL drivers are not available on your system, but NVidia CUDA 
     136drivers are available, then set *SAS_OPENCL=cuda* or 
     137*SAS_OPENCL=cuda:n* for a particular device number *n*.  If no device 
     138number is specified, then the CUDA drivers looks for look for 
     139*CUDA_DEVICE=n* or a file ~/.cuda-device containing n for the device number. 
     140 
     141In batch queues, the SLURM command *sbatch --gres=gpu:1 ...* will set 
     142*CUDA_VISIBLE_DEVICES=n*, which ought to set the correct device 
     143number for *SAS_OPENCL=cuda*.  If not, then set 
     144*CUDA_DEVICE=$CUDA_VISIBLE_DEVICES* within the batch script.  You may 
     145need to set the CUDA cache directory to a folder accessible across the 
     146cluster with *PYCUDA_CACHE_DIR* (or *PYCUDA_DISABLE_CACHE* to disable 
     147caching), and you may need to set environment specific compiler flags 
     148with *PYCUDA_DEFAULT_NVCC_FLAGS*.  You should also set *SAS_DLL_PATH*  
     149for CPU-only modules. 
     150 
     151**No GPU support** 
     152 
     153If you don't want to use OpenCL or CUDA, you can set *SAS_OPENCL=None* 
     154in your environment settings, and it will only use normal programs. 
     155 
     156In batch queues, you may need to set *SAS_DLL_PATH* to a directory 
     157accessible on the compute node. 
     158 
    118159 
    119160Device Testing 
     
    154195*Document History* 
    155196 
    156 | 2017-09-27 Paul Kienzle 
     197| 2018-10-15 Paul Kienzle 
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