#Opengl nvidia cuda toolkit 9 windows 10 how to#

On Windows, to build and run MPI-CUDA applications one can install MS-MPI SDK. It is also available on some online resources, such as Open MPI. A MPI compiler can be installed using your Linux distribution's package manager system. MPI (Message Passing Interface) is an API for communicating data between distributed processes. dll file to root level bin/win64/Debug and bin/win64/Release folder. /./Common/FreeImage/Dist/圆4 such that it contains the. To set up FreeImage on a Windows system, extract the FreeImage DLL distribution into the folder. FreeImage can also be downloaded from the FreeImage website. FreeImage can usually be installed on Linux using your distribution's package manager system. FreeImageįreeImage is an open source imaging library. If available, these dependencies are either installed on your system automatically, or are installable via your system's package manager (Linux) or a third-party website.

These third-party dependencies are required by some CUDA samples. If a sample has a third-party dependency that is available on the system, but is not installed, the sample will waive itself at build time.Įach sample's dependencies are listed in its README's Dependencies section. Some CUDA Samples rely on third-party applications and/or libraries, or features provided by the CUDA Toolkit and Driver, to either build or execute. Samples that demonstrate performance optimization. Samples that are specific to domain (Graphics, Finance, Image Processing).

#Opengl nvidia cuda toolkit 9 windows 10 how to#

Samples that demonstrate how to use CUDA platform libraries (NPP, NVJPEG, NVGRAPH cuBLAS, cuFFT, cuSPARSE, cuSOLVER and cuRAND). Samples that demonstrate CUDA Features (Cooperative Groups, CUDA Dynamic Parallelism, CUDA Graphs etc). Samples that demonstrate CUDA related concepts and common problem solving techniques. Utility samples that demonstrate how to query device capabilities and measure GPU/CPU bandwidth.

Basic CUDA samples for beginners that illustrate key concepts with using CUDA and CUDA runtime APIs.