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include
src
CMakeLists.txt
README.md

README.md

coursera-heterogeneous

Provides the wb.h header file for the Heterogenous Parallel Programming course from Coursera. This file can be used to work offline on the course assignments, provided you have access to CUDA hardware.

Running on Windows with Visual Studio

  • Update NVIDIA driver for your CUDA hardware
  • Download and install Visual Studio or Visual C++ Express Edition.
  • Download and install CUDA toolkit
  • Create CUDA project in Visual Studio
  • Place this wb.h in same directory as your CUDA source file (mp1.cu for example)
  • Compile and run!

Running on OSX via Xcode

Make sure you have XCode & Cmake. You can get cmake from macports via: sudo port install cmake or homebrew via: brew install cmake

  • Download & Install NVIDIA CUDA: http://developer.download.nvidia.com/compute/cuda/5_0/rel-update-1/installers/cuda_5.0.36_macos.pkg
  • Clone repo and run: cmake CMakeLists.txt -G Xcode
  • Open the resulting Project.xcodeproj
  • Change Loading flags:
    • Highlight Project
    • Select mp0 under targets
    • Under Build Settings, select Linking: Other Linker flags
    • Double click to expand the flags
    • Click the (+) at the bottom of the flags window
    • Add the following: -F/Library/Frameworks -framework CUDA
  • Now you can run & add debug points