Changes in doc/guide/gpu_setup.rst [63602b1:8b31efa] in sasmodels
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doc/guide/gpu_setup.rst
r63602b1 r8b31efa 94 94 Device Selection 95 95 ================ 96 **OpenCL drivers** 97 96 98 If you have multiple GPU devices you can tell the program which device to use. 97 99 By default, the program looks for one GPU and one CPU device from available … … 104 106 was used to run the model. 105 107 106 **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 108 If you want to use a specific driver and devices, you can run the following 110 109 from the python console:: 111 110 … … 115 114 This will provide a menu of different OpenCL drivers available. 116 115 When one is selected, it will say "set PYOPENCL_CTX=..." 117 Use that value as the value of *SAS_OPENCL*. 116 Use that value as the value of *SAS_OPENCL=driver:device*. 117 118 To use the default OpenCL device (rather than CUDA or None), 119 set *SAS_OPENCL=opencl*. 120 121 In batch queues, you may need to set *XDG_CACHE_HOME=~/.cache* 122 (Linux only) to a different directory, depending on how the filesystem 123 is 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** 134 135 If OpenCL drivers are not available on your system, but NVidia CUDA 136 drivers are available, then set *SAS_OPENCL=cuda* or 137 *SAS_OPENCL=cuda:n* for a particular device number *n*. If no device 138 number 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. 140 141 In batch queues, the SLURM command *sbatch --gres=gpu:1 ...* will set 142 *CUDA_VISIBLE_DEVICES=n*, which ought to set the correct device 143 number for *SAS_OPENCL=cuda*. If not, then set 144 *CUDA_DEVICE=$CUDA_VISIBLE_DEVICES* within the batch script. You may 145 need to set the CUDA cache directory to a folder accessible across the 146 cluster with *PYCUDA_CACHE_DIR* (or *PYCUDA_DISABLE_CACHE* to disable 147 caching), and you may need to set environment specific compiler flags 148 with *PYCUDA_DEFAULT_NVCC_FLAGS*. You should also set *SAS_DLL_PATH* 149 for CPU-only modules. 150 151 **No GPU support** 152 153 If you don't want to use OpenCL or CUDA, you can set *SAS_OPENCL=None* 154 in your environment settings, and it will only use normal programs. 155 156 In batch queues, you may need to set *SAS_DLL_PATH* to a directory 157 accessible on the compute node. 158 118 159 119 160 Device Testing … … 154 195 *Document History* 155 196 156 | 201 7-09-27Paul Kienzle197 | 2018-10-15 Paul Kienzle
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