- Timestamp:
- Oct 30, 2018 10:43:35 AM (6 years ago)
- Branches:
- master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
- Children:
- 765d025, 23df833
- Parents:
- 153f8f6 (diff), c6084f1 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent. - Location:
- doc/guide
- Files:
-
- 2 edited
Legend:
- Unmodified
- Added
- Removed
-
doc/guide/plugin.rst
r81751c2 raa8c6e0 744 744 erf, erfc, tgamma, lgamma: **do not use** 745 745 Special functions that should be part of the standard, but are missing 746 or inaccurate on some platforms. Use sas_erf, sas_erfc andsas_gamma747 instead (see below). Note: lgamma(x) has not yet been tested.746 or inaccurate on some platforms. Use sas_erf, sas_erfc, sas_gamma 747 and sas_lgamma instead (see below). 748 748 749 749 Some non-standard constants and functions are also provided: … … 812 812 Gamma function sas_gamma\ $(x) = \Gamma(x)$. 813 813 814 The standard math function, tgamma(x) is unstable for $x < 1$814 The standard math function, tgamma(x), is unstable for $x < 1$ 815 815 on some platforms. 816 816 817 817 :code:`source = ["lib/sas_gamma.c", ...]` 818 818 (`sas_gamma.c <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_gamma.c>`_) 819 820 sas_gammaln(x): 821 log gamma function sas_gammaln\ $(x) = \log \Gamma(|x|)$. 822 823 The standard math function, lgamma(x), is incorrect for single 824 precision on some platforms. 825 826 :code:`source = ["lib/sas_gammainc.c", ...]` 827 (`sas_gammainc.c <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_gammainc.c>`_) 828 829 sas_gammainc(a, x), sas_gammaincc(a, x): 830 Incomplete gamma function 831 sas_gammainc\ $(a, x) = \int_0^x t^{a-1}e^{-t}\,dt / \Gamma(a)$ 832 and complementary incomplete gamma function 833 sas_gammaincc\ $(a, x) = \int_x^\infty t^{a-1}e^{-t}\,dt / \Gamma(a)$ 834 835 :code:`source = ["lib/sas_gammainc.c", ...]` 836 (`sas_gammainc.c <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_gammainc.c>`_) 819 837 820 838 sas_erf(x), sas_erfc(x): … … 854 872 If $n$ = 0 or 1, it uses sas_J0($x$) or sas_J1($x$), respectively. 855 873 874 Warning: JN(n,x) can be very inaccurate (0.1%) for x not in [0.1, 100]. 875 856 876 The standard math function jn(n, x) is not available on all platforms. 857 877 … … 862 882 Sine integral Si\ $(x) = \int_0^x \tfrac{\sin t}{t}\,dt$. 863 883 884 Warning: Si(x) can be very inaccurate (0.1%) for x in [0.1, 100]. 885 864 886 This function uses Taylor series for small and large arguments: 865 887 866 For large arguments ,888 For large arguments use the following Taylor series, 867 889 868 890 .. math:: … … 872 894 - \frac{\sin(x)}{x}\left(\frac{1}{x} - \frac{3!}{x^3} + \frac{5!}{x^5} - \frac{7!}{x^7}\right) 873 895 874 For small arguments ,896 For small arguments , 875 897 876 898 .. math:: -
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
Note: See TracChangeset
for help on using the changeset viewer.