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OpenCL-examples

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Simple OpenCL examples for exploiting GPU computing

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최종 버전 다운로드 (.zip)

- add_numbers.c
- add_numbers.cl
- CMakeLists.txt
- Makefile
- README.md
- clbuild.c
- CMakeLists.txt
- cr.cl
- defs.h
- exposure.clh
- main.c
- Makefile
- README.md
- make.sh
- mysum.c
- mysum.cl
- README.md
- cl_compat.h
- FindclRNG.cmake
- clbuild.c
- CMakeLists.txt
- defs.h
- - add-numbers.md
  - auger.md
  - cf4cl.md
  - hello-world.md
  - julia-set.md
  - mandelbrot.md
  - n-body.md
  - rng.md
  - square-array.md
  - sum-array.md
  - waste.md
- architecture.md
- building.md
- index.md
- - project.pbxproj
- CMakeLists.txt
- hello.c
- Makefile
- README.md
- clbuild.c
- CMakeLists.txt
- defs.h
- Makefile
- mandelbrot.c
- mandelbrot.cl
- mandelbrot_serial.c
- README.md
- - project.pbxproj
- GalaxyIcon.icns
- LICENSE.txt
- README.md
- - project.pbxproj
- CMakeLists.txt
- Makefile
- qjulia.c
- qjulia_kernel.cl
- README.md
- CMakeLists.txt
- device.c
- host.c
- kernel.cl
- Makefile
- README.md
- clbuild.c
- CMakeLists.txt
- defs.h
- Makefile
- README.md
- square.c
- square.cl
- square_serial.c
- CMakeLists.txt
- Makefile
- README.md
- vecAdd.c
- vecAdd.cl
- clbuild.c
- CMakeLists.txt
- defs.h
- Makefile
- waste.c
- waste.cl
- waste_serial.c
CLAUDE.md
CMakeLists.txt
mkdocs.yml
README.md

// repository documentation

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# Simple examples of OpenCL code

Simple examples of OpenCL code used to learn heterogeneous and GPU computing with OpenCL.

**Documentation:** https://rsnemmen.github.io/OpenCL-examples/

## Examples included

`*` -- reproduced to work in 2025 on AMD GPU

- *`add_numbers`: add a list of numbers together. Includes detailed error handling which makes the code harder to read and understand
- *`square_array`: computes *array*^2 (I am playing mostly with this one)
- *`sum_array`: sums two arrays
- `cf4cl`: testing OpenCL C wrapper
- *`Hello_World`: OpenCL "Hello World" by Apple
- *`mandelbrot`: my attempt at a simple Mandelbrot set calculation
- `N-BodySimulation`: Apple's N-body simulator which clearly illustrates the speedup gained by using the GPU. Requires Xcode
- `RayTraced_Quaternion_Julia-Set_Example`: Apple's ray-traced quaternion Julia set renderer. Requires Xcode
- `rng`: Illustrates how to generate random numbers in the host and in the GPU using the library [`clRNG`](http://clmathlibraries.github.io/clRNG/htmldocs/index.html)
- `auger`: generates random cosmic rays on an isotropic sky
- *`waste`: compute cycle waster

The examples that clearly demonstrate the computational advantage of using a GPU for processing are `N-BodySimulation`, `RayTraced_Quaternion_Julia-Set_Example` (both developed by Apple programmers) and `auger`. For `auger`, I got impressive speedups of >200x compared to a serial code on the CPU.

## How to build

### CMake (recommended — works on macOS and Linux)

```bash
mkdir build && cd build
cmake ..
make
```

Each target is placed in its corresponding subdirectory under `build/`.  Run
executables from that subdirectory so the `.cl` kernel files are found:

```bash
cd build/square_array && ./square
```

Examples requiring [clRNG](http://clmathlibraries.github.io/clRNG/htmldocs/index.html)
(`auger`, `rng`) are built automatically when clRNG is detected; they are
silently skipped otherwise.

### Makefiles

Each example also has its own `Makefile`. Build from within the project directory:

```bash
cd <example> && make        # build OpenCL version
cd <example> && make run    # build and run
```

Exceptions: `N-BodySimulation` uses an Xcode project. `RayTraced_Quaternion_Julia-Set_Example` has a Makefile and CMakeLists.txt. `cf4cl` uses `make.sh`.

## Info about OpenCL devices

To learn about your OpenCL devices, try:

clinfo

To install `clinfo` on MacOS:

brew install clinfo

## TODO

- [ ] similar repo with CUDA examples

[![Buy Me a Coffee](https://img.buymeacoffee.com/button-api/?text=Buy%20me%20a%20coffee&emoji=&slug=nemmen&button_colour=FFDD00&font_colour=000000&font_family=Cookie&outline_colour=000000&coffee_colour=ffffff)](https://www.buymeacoffee.com/nemmen)

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