cu file, you’ll have to do something slightly annoying, because I haven’t found a way to automate it. * Project -> Project tree -> Edit file types & categories. Before we get into the really fun stuff (as described in my original blog post), we’ll do a couple of easy things to make life more convenient. * Add /your_location/NVIDIA_CUDA_SDK2/common/lib/linux (modify for your OS) to the Linker box. * Add /your_location/NVIDIA_CUDA_SDK2/lib to the Linker box. * Under the Search directories tab, add /your_location/NVIDIA_CUDA_SDK2/common/inc to the Compiler box (so that headers like cutil.h will be found). * Debugger: cuda-gdb? (I haven't actually tried it yet) * Enter nvcc's installation directory (e.g., /opt/local/cuda). * Do exactly what you're told, and go to the Toolchain executables tab. Something like 'NVIDIA NVCC CUDA Compiler', but perhaps with less shouting. * At the top under Selected compiler, make sure 'GNU GCC Compiler' is selected, and click the Copy button. Here I’ll outline the procedure for setting up the nvcc compiler in Code::Blocks from scratch.įirst we create a new compiler within Code::Blocks. While my first post highlighted the key sticking-points I faced when I first tried to use the nvcc compiler within the Code::Blocks IDE, it was probably jumping the gun a bit. 'CUDA in Code::Blocks - First things second Lastly, Code Blocks colors the source-code syntax, includes a 'code folding' function for C++ and XML languages, has a tabbed interface, comes with a class browser, and a feature for completing the source-code.Hi, just wanted to share this while i was on google i found it very useful. Another noteworthy feature are the custom memory dumps. You can also create defined inspections by user. It has a fast, customized construction system that doesn't require makefiles, and allows you to perform parallel constructions on systems with a multi-core CPU.Ĭode Block's debugger supports the application of breakpoints on the source code, or on the data that the program handles, as well as the establishment of conditions and counters for said breakpoints. The default compiler that this Code Blocks packet comes with is MinGW.Ĭode Blocks' functionality can be expanded by using plugins. It is an open-source, integrated, cross-platform development environment that supports the use of multiple compilers, such as: GCC (MingW/GNU GCC), MSVC, Digital Mars, Borland C++ 5.5, and Open Watcom. Code Blocks is an excellent option for programming in C++.

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