This is a simple and practical C++ sample showing how to use OpenCL v1.2 on Windows/Linux/OSX with no 3rd party SDK installs required under Windows/OSX.
Unlike every other OpenCL example I've seen, this example demonstrates a bunch of things you would need to do in practice to build an app using OpenCL:
- Importantly, no 3rd party SDK dependencies are required to compile/link under Windows. All required OpenCL headers and the 2 import .LIB's are in the "OpenCL" directory.
- How to safely use OpenCL from multiple threads (by using a local context, and creating your command queue/kernels on that context).
- How to work around AMD driver serialization issues if you use OpenCL from multiple threads
- How to load your program kernel source code from either a file, or from an array in a C-style header
Windows has strong support for OpenCL v1.2 on NVidia, AMD, and Intel drivers. In my testing, even brand new Windows AMD machines right out of the box with no updates have working OpenCL drivers. Some of OpenCL v1.2's strengths are its maturity, driver support, ease of use, and no large 3rd party SDK's or libraries are required to use it.
Here's a good introductory book on OpenCL. (This is the book I used to learn it.)
Use "cmake .". Then under OSX/Linux, use "make".
Under Windows load the generated .SLN with Visual Studio 2019/2022. All included headers/import libs are in the project, so no 3rd party SDK's are required. Be sure to right click on "simple_ocl" and select "Set as Startup Project" before running.
Under Linux, you will need a driver with OpenCL support, and the OpenCL headers/libraries. The easiest thing to do is to use the NVidia proprietary driver, then use "
sudo apt-get install nvidia-cuda-toolkit". This page may help. You may need to also install "opencl-headers". Install and run the "clinfo" app to validate that your driver supports OpenCL. CMake will automatically find the OpenCL headers/libraries.
Under OSX (High Sierra), it just works for me. CMake handles finding the libs/headers.
The "bin" directory contains the sample executable, "simple_ocl". Running it will generate a buffer of random values. The GPU kernel will modify this buffer, and the CPU will read it back and validate its contents.
You should see something like this (note the random numbers will likely be different for you):
OpenCL platform version: "OpenCL 3.0 CUDA 11.4.94" Serializing OpenCL calls across threads: 0 OpenCL device initialized successfully Using kernel source code from array in header src/ocl_kernels.h OpenCL context initialized successfully Running "process_buffer" kernel Validation succeeded Input/output buffer contents (first 16 bytes): 41 41 35 34 190 188 132 135 225 229 108 105 214 208 174 169 82 90 144 153 73 67 241 250 241 253 187 182 233 231 235 228
This sample was derived from how we're using OpenCL in Basis Universal, our GPU texture interchange library/tool. OpenCL support is optional, so we placed all the OpenCL code in one .cpp file and exposed a simple C-style API to its functionality. When OpenCL is not being compiled in we use dummy functions for this API which always return false. We have one large kernel source file which exposes multiple kernels. We pass in C-style structs, OpenCL buffers, and floats/ints/etc. to/from our kernels.
simple_ocl_wrapper.h contains a basic C++ wrapper on top of the C OpenCL API. OpenCL does have its own standard C++ wrapper, but by writing your own you can control exactly how OpenCL is called, which features are exposed, and what C++ features are utilized by the wrapper. (Also, the entire point of this sample is how to directly use OpenCL with as few bloated libs/wrappers/SDK's/frameworks/etc. in between you and the API as possible.)
ocl_device.cpp/h uses this wrapper to create the OpenCL device. It exposes a simple C-style API that callers can use to initialize/deinitalize the device, and create/destroy per-thread contexts and kernels. Out of the box it supports a single kernel source code file (which can contain multiple kernels) which can be either loaded from disk or from a C-style array in a header file. On (only) AMD drivers, this code automatically serializes all calls made into the driver, to avoid race conditions in AMD's driver when OpenCL is called from multiple threads.
simple_ocl.cpp utilizes the C-style API exposed by ocl_device.h. It creates a byte buffer of random numbers, then calls
opencl_process_buffer() in ocl_device.cpp to process this buffer to an output buffer.
Modifying the kernel source code
By default, this sample compiles the OpenCL program from an array of text in src/ocl_kernels.h. This header file was created using the xxd tool with the -i option from the kernel source code file located under bin/ocl_kernels.cl. If you want the sample to always load the kernel source code from the "bin" directory instead, set
OCL_USE_KERNELS_HEADER to 0 in src/ocl_device.cpp.