Installing NVIDIA Optix on Windows

Download the latest version of the NVIDIA Optix SDK. As of April 2021, the latest version is 7.2.0. Check the driver requirements. Version 7.2.0 requires NVIDIA R456.71 driver or newer for Windows. The download requires setting up an NVIDIA developer account.

Windows installation

Execute the NVIDIA-OptiX-SDK-7.2.0-win64.exe file. It will create the C:\ProgramData\NVIDIA Corporation\OptiX SDK 7.2.0\SDK directory. As of April 2021, the latest Cmake version is 3.20.0.

From the binary distributions at https://cmake.org/download/, download the .msi file and install Cmake.

After having installed Cmake, run cmake-gui.

Create a build directory for Optix, C:\ProgramData\NVIDIA Corporation\OptiX SDK 7.2.0\SDK\build for example. If you don’t have write permissions, pick a different directory where you do have write permissions.

Where is the source code: C:/ProgramData/NVIDIA Corporation/OptiX SDK 7.2.0/SDK

Where to build the binaries: C:\ProgramData\NVIDIA Corporation\OptiX SDK 7.2.0\SDK\build

Important. If you are working with the Maxwell architecture, please, change sm_60 and compute_60 to sm_50 and compute_50, respectively, in the CMakeLists of the SDK directory before generating the build.

Press Configure and select the version of Visual Studio you wish to use. Make sure that, for the selected compiler, the Optional platform for generator is either selected to x64 or defaults to x64.

The result will be the following:

Press Configure again, then Generate.

This will populate the build directory and, in particular, generate the OptiX-Samples.sln. Open the solution. Right click on one of the projects (for example, optixHello) and select “Set as start up project”.

Alt+F5 and the project will be executed. Enjoy.

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We are teaching, researching and consulting parallel programming on Graphics Processing Units (GPUs) since the delivery of CUDA. We also play Matlab and Python.

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We are teaching, researching and consulting parallel programming on Graphics Processing Units (GPUs) since the delivery of CUDA. We also play Matlab and Python.

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