Cmake Gui For Mac Install3/31/2021
These are enviroment variables (and not command line arguments) and are used as e.g.BlueGene Cmake Compiling QMMM Cygwin GROMACS-OpenMM Intel(R) Cluster Rea.One of the biggest selling points is its ability to manage native builds on MS Windows.Starting with the 4.5 release, it is possible to configure and compile the source code with it.
With the 4.6 release CMake is the deafult and only build system, while autoconfautomake is deprecated. The information below pertains to the way GROMACS 4.5.x used CMake. For 4.6, consult the Installation Instructions. Most of the Linux distributions come with packages available through the corresponding package manager. Make sure the installed version is 2.8 or later, while for building GROMACS-GPU version 2.6.4 or later is required. On LinuxMac, the following commands will configure a build with the default settings. OpenMP will work out of the box with any modern compiler (e.g. The native GPU acceleration requires the NVIDIA CUDA toolkit and to run a comatible graphics card ( Fermi or Kepler series, compute capability 2.0 ) has to be present in the system. Note that compiling with GPU acceleration does not produce a GPU-only mdrun, CPU or GPU acceleration for non-bonded calculation can be selected at run-time. Therefore, compiling without GPU acceleration is advised only in case if no compatible GPU is (planned to be) present in the system. Note that the source path should be the last argument (otherwise dont put the spaces between -D and OPTION ). Note, that the NVIDIA GPU compiler (nvcc) requires a C compiler to compile host-code -- the part of the code.cu files contain which runs on the CPU. Whenever considered safe, the build system will automatically pass the used C compiler for nvcc to be used as host-compiler. Cmake Gui Full Path ToTo manually set the nvcc compiler wrapper configure with passing the full path to a C compiler using CUDANVCCHOSTCOMPILER. When configuring with both MPI and GPU support, the default CMake-based MPI detections should be preferred. This is becauise when the MPI compiler-wrapper approach is used, as nvcc can not reliably use compiler wrappers, the nvcc host compiler needs to be set manually. When using a C compiler which is not officially supported by CUDA (e.g. In this case nvcc will use the platform-default assumed to be in the path (e.g. Linux). Although mixing compilers is not advised, this will most probably work, but if sich a setup fails, a CPU compiler supported by nvcc should be used. The compilers officially compatible with nvcc are gcc and Intel on Linux, gcc on Mac OS X, and msvc on Windows; for more detailed information on version compatibilities consult the NVIDIA documentation (or just try). The file can be edited using a text editor, but after that cmake should be run again. Note that the build has to be reconfigured to commit any changes. The respective include, lib, or bin is appended to the path.
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