TobyFlynn / OPS

OPS is an API with associated libraries and preprocessors to generate parallel executables for applications on mulit-block structured meshes.

##OPS

OPS is an API with associated libraries and pre-processors to generate parallel executables for applications on multi-block structured grids.

This repository contains the implementation of the run-time library and the pre-processor, and is structured as follows:

• ops: Implementation of the user and run-time OPS C/C++ APIs

• apps: Application examples in C. These are examples of user application code and also include the target code an OPS pre-processor should produce to correctly use the OPS run-time library. Currently the main application developed with OPS is a single block structured mesh application - Cloverleaf originally developed at https://github.com/Warwick-PCAV/CloverLeaf

• translator: Python OPS pre-processor for C/C++ API

• doc: Documentation

####Installation

1. Set up environmental variables:

• CUDA_PATH - Installation directory of CUDA, usually /usr/local/cuda (to build CUDA libs and applications, only needed if CUDA cannot be found in standard locations, or to enable OpenCL)
• MPI_HOME - Installation directory of MPI (to build MPI based distributed memory libs and applications) only needed if MPI not installed in standard locations
• HDF5_ROOT - Installation directory of HDF5 (to support HDF5 based File I/O) if HDF5 not installed in standard location

2. Build OPS back-end libraries.

Create a build directory, and run CMake (version 3.9 or newer)

mkdir build
cd build
cmake ${PATH_TO_OPS}
make

Options of interest to specify to cmake include:

• -DCMAKE_BUILD_TYPE=Release - enable optimizations
• -DBUILD_OPS_FROTRAN=ON - enable building OPS Fortran libraries.
• -DBUILD_OPS_APPS=ON - build example applications
• -DHDF5_PREFER_PARALLEL=ON - build using parallel HDF5, rather than serial HDF5 libraries