cs344 [Introduction to Parallel Programming] (https://www.udacity.com/course/intro-to-parallel-programming--cs344)

Instructions for setting up an X64 Windows 10 system to build CUDA code on Visual Studio 2015

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1. Install Visual Studio:

   • download here.

   I installed Visual Studio 2015.

2. Install Cuda Toolkit:

   • Nvidia Instructions for Windows.

   • Download here.

   I installed version 8.0.

3. Install CMake:

   • Download here.

   I installed version 3.7.2.

4. Install OpenCV:

   • Instructions for Installing on Windows.

   • Download here.

   • Run the EXE to extract the files. This EXE does not have an installer. Instead, you put your files where you want, and then add environment variables for the installation location and path to DLLs.

   • for an installation in c:\OpenCV3.2 the following commands need to be run in a command window.

   setx -m OPENCV_DIR C:\OpenCV_3.2\build
   setx -m PATH=%PATH%;%OPENCV_DIR%\x64\vc14\bin
   

   note: that you may have a different path based on architecture x86 vs x64.

   I installed 3.2.12.

Test the nVidia compiler Version

Run the following in a command window to check that the CUDA compiler is set properly.

	C:\ProgramData\NVIDIA Corporation\CUDA Samples\v8.0>nvcc -V
	nvcc: NVIDIA (R) Cuda compiler driver
	Copyright (c) 2005-2016 NVIDIA Corporation
	Built on Sat_Sep__3_19:05:48_CDT_2016
	Cuda compilation tools, release 8.0, V8.0.44

Download and build cs344 Problem Sets in Visual Studio

git clone https://github.com/teeekay/cs344.git
cd cs344
mkdir build
cd build
cmake .. -G "Visual Studio 14 2015 Win64"

The Visual Studio Solution file cs344.sln should then be found in the build subdirectory and can be used to load them into Visual studio where they can be built.

• Note: I had problems building the cs344 code due to issues with X86 and X64 in the target machine type during the linking stage. these were resolved by setting the generator type in cmake

Building from a command window

General instructions on how to use cl in command window - nvcc should work from there too. I have not yet attempted this for these problem sets.

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Thanks to https://github.com/wykvictor who had a set of instructions for older versions of CUDA and Visual Studio and has solutions set up for the problem sets.