OpenCL™ (Open Computing Language) is a low-level API for heterogeneous computing that runs on CUDA-powered GPUs. Using the OpenCL API, developers can launch compute kernels written using a limited subset of the C programming language on a GPU.
OpenCL support is included in the latest NVIDIA GPU drivers, available at www.nvidia.com/drivers
In addition to OpenCL, NVIDIA supports a variety of GPU-accelerated libraries and high-level programming solutions that enable developers to get started quickly with GPU Computing.
OpenCL is a trademark of Apple Inc., used under license by Khronos.
NVIDIA OpenCL SDK Code Samples
OpenCL Tridiagonal
Efficient matrix solvers for large number of small independent tridiagonal linear systems. OpenCL implementation of 3 different solvers: Parallel Cyclic Reduction, Cyclic Reduction, Sweep (Gauss elimination + reordering optimization for full coalescing).
OpenCL Bandwidth Test
This is a simple test program to measure the memcopy bandwidth of the GPU. It currently is capable of measuring device to device copy bandwidth, host to device and host to device copy bandwidth for pageable and page-locked memory, memory mapped and direct access.
Simple OpenCL D3D10 Texture
Simple program which demonstrates Direct3D10 texture interoperability with OpenCL. The program creates a number of D3D10 textures (2D, 3D, and CubeMap) which are written to from OpenCL kernels. Direct3D then renders the results on the screen.
Simple OpenCL D3D9 Texture
Simple program which demonstrates Direct3D9 texture interoperability with OpenCL. The program creates a number of D3D9 textures (2D, 3D, and CubeMap) which are written to from OpenCL kernels. Direct3D then renders the results on the screen.
OpenCL Matrix Multiplication
This sample implements matrix multiplication and is exactly the same as Chapter 6 of the programming guide. It has been written for clarity of exposition to illustrate various OpenCL programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. CUBLAS provides high-performance matrix multiplication.
OpenCL Box Filter
Linear 2-dimensional variable-width Box Filter of RGBA image. Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. Each of the R, G, B and A channels are treated independently with results computed concurrently for each.
OpenCL Sobel Filter
2-dimensional 3x3 Sobel Magnitude Filter of RGBA image. Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. Gradient magnitude for each of the R, G & B channels is computed concurrently and independently, then combined into a single gradient intensity with linear weighting factors.
OpenCL Median Filter
Multi-GPU enabled, 2-dimensional 3x3 Median Filter of RGBA image. Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. Each of the R, G & B channels are treated independently with results computed concurrently for each.
OpenCL Recursive Gaussian Filter
2-dimensional Gaussian Blur Filter of RGBA image using IRF method. Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. Each of the R, G, B and A channels are treated independently with results computed concurrently for each.
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