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README.txt | 2014-08-09 | 2.1 kB | |
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Getting started: Windows: To build and run on windows you must install at least Visual Studio Express 2013 C++ edition. http://www.visualstudio.com/downloads/download-visual-studio-vs#d-express-windows-desktop Download git for windows (or some other variant) avoid GUI-based git clients. Get the latest revision: git clone git://git.code.sf.net/p/octetframework/code octet Xcode: Get the latest revision: git clone git://git.code.sf.net/p/octetframework/code octet You will need to make some xcode projects for the examples. Only add "src/main.cpp" do not add *all* the source files. You will need to add the OpenAL, OpenGL and OpenCL frameworks. All libraries come as standard with Xcode, but you must use the "Product -> Edit Scheme -> Options" dialogue to set the working directory to a folder under the "xcode" folder in your project. By default, the framework travels up two directories before looking for files. Make (on any system): The simplet way of building is to use "make". But you have to have installed some unix utilities (such as unxutils on sourceforge) if you are using Windows. Just typing $ make will build all the examples in bin/ Example projects are in src\examples Click on the sln files (if working with Visual studio) Each sln file has one project and one .cpp file (main.cpp) If you are brave, you can also build from the command line using "cl" (windows) or "clang" (mac) and rarely these days "gcc" (linux, mac, android). You can make a new project by using the python script in "packaging". cd into packaging and run: make_example.py project_name This will put the solution, vcproj, main.cpp and header into src\examples Later, it might be worth downloading your Vendor's OpenCL implementation AMD http://developer.amd.com/tools-and-sdks/heterogeneous-computing/amd-accelerated-parallel-processing-app-sdk/downloads/ NVidia https://developer.nvidia.com/opencl Intel http://software.intel.com/en-us/vcsource/tools/opencl-sdk-2013