gpu sandbox

Sandbox to test various GPU algorithms, image filters, etc. implemented using OpenCL or Cuda.

Image filters (Naive CPU / OpenCL)

Flip X	Flip Y

Blur 3/5/7	Motion 9

Sobel	Grayscale

Building from sources

Prerequisites

• Common:
  • Git (to get source code)
  • CMake (the latest version)
  • Ninja (as build files generator)
  • Python 3.7+
• Windows 10:
  • Microsoft Visual C++ Compiler (MSVC) with C++ 17 support
  • x64 Native Tools Command Prompt for VS
• Ubuntu 20.04:
  • GNU C++ Compiler with C++ 17 support
• MaсOS Catalina 10.15:
  • Clang Compiler with C++ 17 support

Get source code

The following code snippet downloads project source code repository, and enters project root folder. Must be executed from the folder where you want to locate project.

$ git clone https://github.com/EgorOrachyov/gpu-sandbox.git
$ cd gpu-sandbox

Configure and run build

Attention! On Windows platform building commands must be executed in x64 Native Tools Command Prompt for VS.

The following code snippet runs build.py script, which allows configuring cmake and running of actual build with selected options. You can specify build directory, build type, number of system threads for build. Must be executed from project root folder.

$ python ./build.py --build-dir=build --build-type=Release --nt=4

On macOS, you can optionally specify target binaries architecture to build. Pass option --arch with x86_64 or arm64 respectively. By default, build falls back to CMAKE_SYSTEM_PROCESSOR specified architecture. See example bellow, replace <arch> with desired architecture for your build. Must be executed from project root folder.

$ python ./build.py --build-dir=build --build-type=Release --nt=4 --arch=<arch>

Run executable

The following code snippet allows to run executable application of the project to test different algorithms. Must be executed from the directory used for a build in the previous step.

Print help message to get all possible options.

$ ./gpusandbox -h

List all available filters.

$ ./gpusandbox -l

Apply filter to an image and save result.

$ ./gpusandbox --filter=<filter name> --input=<image_src>.png --output=<image_dst>.bmp

Contributors

• Egor Orachyov (Github: @EgorOrachyov)

Citation

@online{spla,
  author = {Orachyov, Egor},
  title = {Gpu Sandbox: Sandbox to test various GPU algorithms, image filters, etc. implemented using OpenCL or Cuda},
  year = 2023,
  url = {https://github.com/EgorOrachyov/gpu-sandbox},
  note = {Version 1.0.0}
}

Project structure

Entry	Description
📁 .github	CI/CD scripts and GitHub related files
📁 deps	Third-party project dependencies, stored as submodules
📁 resource	Example resource images for testing and playing with
📁 src	Private compiled source directory
📄 CMakeLists.txt	CMake configuration, add as sub directory to your project
📄 build.py	Script to build project sources to executable

License

This project licensed under MIT License. License text can be found in the license file.