ArrayFire package includes simple ArrayFire benchmarks and demos.
ArrayFire is a library for fast GPU computing, supporting both Nvidia CUDA and OpenCL devices, and it is open source (BSD 3-clause).
It includes matrix algebra, algorithms, image processing, etc. classes and functions.
Benchmarks and demos are:
Pi Pi number benchmark
Matrix NxN matrix product benchmark
Vectorize Different strategies to do operations between vectors
Demo Basic matrix algebra demos
You can download ArrayFire sources from GitHub or the binaries from the ArrayFire page.
In the last case you will have to register (no cost, no personal data required) and after installing you will get a "include" and "lib" folder, that also includes the required dll.
the "include" folder in your Setup/Build methods/Include directories
the "lib" folder in your Setup/Build methods/Lib directories
the "lib" folder in your Setup/Build methods/Path - executable directories
and in the "Main package configuration" set AF_CPU (ArrayFire libraries use your CPU cores), AF_OPEN_CL (ArrayFire libraries use your GPU through OpenCL) or AF_CUDA (ArrayFire libraries use your GPU through Nvidia CUDA).
Finally install the GPU drivers:
If you have a Nvidia graphic card, you can install CUDA
For the rest of graphic cards as AMD/ATI or Intel, you can install OpenCL from their vendor download web
ArrayFire does not yet compile with MinGW on Windows platform. In this case it is advised to use an updated Visual Studio compiler.