https://github.com/Gladdy/EasyOpenCL
The easiest way to get started with OpenCL!
https://github.com/Gladdy/EasyOpenCL
Last synced: 3 months ago
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The easiest way to get started with OpenCL!
- Host: GitHub
- URL: https://github.com/Gladdy/EasyOpenCL
- Owner: Gladdy
- License: gpl-3.0
- Created: 2015-06-01T23:28:00.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2015-09-06T10:22:42.000Z (over 9 years ago)
- Last Synced: 2024-07-31T22:44:04.724Z (10 months ago)
- Language: C++
- Homepage:
- Size: 2.84 MB
- Stars: 307
- Watchers: 16
- Forks: 15
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## EasyOpenCL
#### No exposed low-level C, just the C++ standard library
### Features
* Focus on programming the GPU instead of messing about with long C-style OpenCL function calls and manual memory management.
* CMake support for Linux and Mac - No more linking problems when you have installed the correct driver.
* Support for scalar values: pass additional structs to your kernel, eg. transformation matrices or custom constants.
* Chain kernels together in order to create a true pipeline on your GPU in which kernels can depend on multiple others. (`example/main.cpp`)
* Human readable OpenCL errors for easy debugging and teaching of the OpenCL basics.
### Overview: it's this easy!
```cpp
// example/simple.cpp
try {
EasyOpenCL framework (SHOW_DEBUG);
//Register the kernel with the framework
auto& square = framework.load("squarefloat");
//Bind the input buffer (initial values from a std::vector) and the output buffer
square.bindInput(0, std::vector { 1.1, 2.2, 3.3, 4.4, 5.5, 11.0 });
square.bindOutput(1);
//Evaluate the kernel and display the output
square.evaluate();
square.showBuffer(1); // [ 1.21, 4.84, 10.89, 19.36, 30.25, 121 ]
} catch (std::exception& e) { std::cerr << "Error: " << e.what() << std::endl; }
```
```c
// kernels/squarefloat.cl
__kernel void squarefloat(__global float* input, __global float* output)
{
int i = get_global_id(0);
output[i] = input[i] * input[i];
}
```
### Getting started
All platforms:
* Update your graphics drivers
* Install the drivers with OpenCL support (NVIDIA CUDA Toolkit, AMD APP SDK or Intel OpenCL™ Code Builder)
```
git clone https://github.com/Gladdy/EasyOpenCL.git
cd EasyOpenCL
mkdir build && cd build
cmake ..
make
./simple
```
### TODO:
* High priority
* More examples - image processing, deep learning (matrix operations) and a renderer/raytracer
* Asynchronous kernel calls + benchmarks of asynchronous vs synchronous kernel calls
* Cleaning up the framework, getting public/private right + the different constructors
* Low priority:
* Automatic generation of local and global work group sizes
* Detect circular dependencies of kernels
* Mehh whenever I have the time:
* .dot output of your current kernel dependency graph
* Automatic generation of stub kernel (.cl) files based on the kernel links specified.
### Thanks to:
* Dhruba Bandopadhyay: [OpenCL Cookbook: Listing all devices and their critical attributes](http://dhruba.name/2012/08/14/opencl-cookbook-listing-all-devices-and-their-critical-attributes/)
* elhigu: [cmake-findopencl](https://github.com/elhigu/cmake-findopencl)
* Tom Scogland: [OpenCL error checking](http://tom.scogland.com/blog/2013/03/29/opencl-errors/)