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CUDA Nsight Debugging Lab - Code

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CIS 565 Debugging Lab

This is the first in series of 2 labs for CUDA. In this lab, we will discuss how NVIDIA's Nsight for Visual Studio can aid in debugging CUDA programs.

The debugging lab will be held in class. Please bring your Windows CUDA-Capable laptop with the code downloaded and built. If you do not have a Windows CUDA-Capable laptop, please find a partner to work with.

Clone, Build and Run

The source code consists of a CMake build structure similar to Project 0. Clone this repository from Github and then run the instructions below.

  1. In Git Bash, navigate to your cloned project directory.
  2. Create a build directory: mkdir build
    • (This "out-of-source" build makes it easy to delete the build directory and try again if something goes wrong with the configuration.)
  3. Navigate into that directory: cd build
  4. Open the CMake GUI to configure the project:
    • cmake-gui .. or "C:\Program Files (x86)\cmake\bin\cmake-gui.exe" ..
      • Don't forget the .. part!
    • Click Configure. Select your version of Visual Studio, Win64. (NOTE: you must use Win64, as we don't provide libraries for Win32.)
    • If you see an error like CUDA_SDK_ROOT_DIR-NOTFOUND, set CUDA_SDK_ROOT_DIR to your CUDA install path. This will be something like: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v8.0
    • Click Generate.
  5. If generation was successful, there should now be a Visual Studio solution (.sln) file in the build directory that you just created. Open this. (from the command line: explorer *.sln)
  6. Build. (Note that there are Debug and Release configuration options.)
  7. Run. Make sure you run the transpose target (not ALL_BUILD) by right-clicking it and selecting "Set as StartUp Project".
    • If you have switchable graphics (NVIDIA Optimus), you may need to force your program to run with only the NVIDIA card. In NVIDIA Control Panel, under "Manage 3D Settings," set "Multi-display/Mixed GPU acceleration" to "Single display performance mode".

Please ask me or the TAs ahead of time if you have trouble compiling the code. We want to be ready to go at the start of the lab.

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CUDA Nsight Debugging Lab - Code


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Language:Cuda 55.6%Language:CMake 34.4%Language:C++ 10.0%