Simple matrix-vector multiplication example showing increasingly optimized implementations. Element by element addition of two 1-dimensional arrays. Efficient matrix solvers for large number of small independent tridiagonal linear systems. password?
Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU.
Gravitational Simulation of a large # of bodies.
Since the opencl-headers package in the main repository is for OpenCL 1.2, you can get the OpenCL 1.1 header files from here. The browser version you are using is not recommended for this site.Please consider upgrading to the latest version of your browser by clicking one of the following links. OpenCL support is included in the latest NVIDIA GPU drivers, available at www.nvidia.com/drivers. Dot Product (scalar product) of set of input vector pairs.
Demonstrates that one array can be modified several times without having to re-read and re-write data to and from the GPU. Measures the duration of adding two vectors.
Implemented in OpenCL for CUDA GPU's. We use essential cookies to perform essential website functions, e.g. Simple example that demonstrates use of 3D textures in OpenCL. C# implementation of OpenCL 1.2: number of platforms for an AMD system in 64-bit windows # OpenCL is low level api so it must be implemented in "C space" first. download the GitHub extension for Visual Studio, official C++ bindings from the OpenCL registr, clFFT is required; installation instructions can be found inside example04/README.md, FFTW is required; installation is as simple as extracting FFTW's tar file, then running. This sample implements a Hidden Markov Model in OpenCL for the GPU.
The program creates a number of D3D10 textures (2D, 3D, and CubeMap) which are written to from OpenCL kernels. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. The program creates a number of D3D9 textures (2D, 3D, and CubeMap) which are written to from OpenCL kernels.
A simple test application that demonstrates a new CUDA 4.0 driver ability to embed PTX in a OpenCL kernel. You can always update your selection by clicking Cookie Preferences at the bottom of the page.
GPU-Quicksort: The Generic Address Space in OpenCL™ 2.0: SPIR in OpenCL 2.0: Using SPIR for fun and profit with Intel® OpenCL™ Code Builder: Getting Started with OpenCL™ on Android* OS: OpenCL™ and OpenGL* Interoperability Tutorial: OpenCL™ and OpenGL* Interoperability Sample: Sharing Surfaces between OpenCL™ and OpenGL* 4.3 on Intel® Processor Graphics using implicit synchronization: Sharing Surfaces between OpenCL™ and DirectX* 11 on Intel® Processor Graphics: Using Basic Capabilities of Multi-Device Systems with OpenCL™: Intel® VTune™ Amplifier XE: Getting started with OpenCL* performance analysis on Intel® HD Graphics: Performance Tuning of OpenCL™ Applications on Intel® Xeon Phi™ Coprocessor using Intel® VTune™ Amplifier XE 2013/2015: https://software.intel.com/en-us/intel-opencl.
Forgot your Intel
here is my feeble attempt at learning OpenCL, please don't make fun of me too much .
Implemented in OpenCL for CUDA GPU's. Demonstrates overlapped copy/compute in 2 command queues. By signing in, you agree to our Terms of Service.
High Quality DXT Compression using OpenCL.
Simple program which demonstrates Direct3D9 texture interoperability with OpenCL.
for a basic account. I have no idea why. Multi-GPU enabled, 2-dimensional 3x3 Median Filter of RGBA image. This is collection of WebGL Samples.
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. In this example, 10 threads are spawned but two 100-element vectors are used, and it is shown how to split up a specific number of elements per thread. In the blogspot example, two 10-element vectors are created and a thread is used for each pair of elements. Simple program which demonstrates Direct3D10 texture interoperability with OpenCL. This sample implements bitonic sort algorithm for batches of short arrays. This sample implements convolution filter of a 2D image with arbitrary separable kernel. Feel free to add more. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.
Robert M Ioffe, Published:06/08/2015 From the guide on programming OpenCL for NVIDIA: We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products.
Another CLFFT example where an in-place real transform and an out-of-place real transform are performed. One example use of this is for a real-time computer vision applications where we want to run a feature detector over an image in OpenCL but render the final output to the screen in real time with the detectors clearly marked.
This repository uses sub-modules for the OpenCL Headers, OpenCL C++ bindings, and OpenCL ICD Loader. Each of the R, G, B and A channels are treated independently with results computed concurrently for each.
For example, if a single thread of cpu can build a 32x32 verticed sphere in 10000 cycles, then a gpu with opencl can build 20 spheres in 1000 cycles. Each of the R, G, B and A channels are treated independently with results computed concurrently for each. they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. For example 04, run (inside the directory): where PATH/TO/CLFFT is the path to the clFFT library. This sample demonstrates how Discrete Cosine Transform (DCT) for 8x8 blocks can be implemented in OpenCL. A simple example using the cl_khr_fp64 extension which allows for usage of doubles instead of floats. Linear 2-dimensional variable-width Box Filter of RGBA image. 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. 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. Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. Given an array of numbers, scan computes a new array in which each element is the sum of all the elements before it in the input array.
The GPU Computing SDK provides examples with source code, utilities, and white papers to help you get started writing GPU Computing software.
Learn more. If nothing happens, download GitHub Desktop and try again. Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation.
This sample extracts a geometric isosurface from a volume dataset using the marching cubes algorithm. This is a simple test program to measure the memcopy bandwidth of the GPU. Work fast with our official CLI.
Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. This sample implements Niederreiter quasirandom number generator and Moro's Inverse Cumulative Normal Distribution generator. For more information, see our Privacy Statement. 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. In this example, 10 threads are spawned but two 100-element vectors are used, and it is shown how to split up a specific number of elements per thread.
or Direct3D then renders the results on the screen. This code uses OpenCL 1.1 on a NVIDIA GPU.
The full SDK includes dozens of code samples covering a wide range of applications.
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Element by element hypotenuse for two 1-dimensional arrays. The program modifies vertex positions with OpenCL and uses OpenGL to render the geometry. This sample enumerates the properties of the OpenCL devices present in the system. Use Git or checkout with SVN using the web URL. CUBLAS provides high-performance matrix multiplication. Runtime Generated FFT for Intel® Processor Graphics. Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation.
OpenCL is a trademark of Apple Inc., used under license by Khronos. This sample shows how to post-process an image rendered in OpenGL using OpenCL. Simulation of elastic collisions of a large # of bodies.
This sample shows the implementation of multi-threaded heterogeneous computing workloads with tight cooperation between CPU and GPU.
Get the official C++ bindings from the OpenCL registr and copy it to the OpenCL framework directory, or do the following: For some reason, the makefile didn't want to work for Windows. This sample demonstrates efficient implementation of 64-bin and 256-bin histograms.
OpenCL Post-Process OpenGL-Rendered Image. Using the OpenCL API, developers can launch compute kernels written using a limited subset of the C programming language on a GPU. OpenCL Headers (include/api) OpenCL C++ bindings (include/cpp) OpenCL Loader; OpenCL utility library (include/utils) It also contains resources useful to OpenCL developers: Code samples (samples/) Documentation (docs/) Setting Up the SDK. This application demonstrates how to make use of multiple GPUs in OpenCL.
(Only tested on Ubuntu).
If nothing happens, download the GitHub extension for Visual Studio and try again. Initially, stenciling is not used so if you look (by holding down the left mouse button and moving) at the dinosaur from "below" the floor, you'll see a bogus dinosaur and appreciate how the basic technique works. For OpenCL 1.2, use the "Alternative Way" to run the kernel given in the complete code example of the original tutorial: cl::Kernel kernel_add=cl::Kernel(program,"simple_add"); kernel_add.setArg(0,buffer_A); kernel_add.setArg(1,buffer_B); kernel_add.setArg(2,buffer_C); queue.enqueueNDRangeKernel(kernel_add,cl::NullRange,cl::NDRange(10),cl::NullRange); If nothing happens, download Xcode and try again. 2-dimensional 3x3 Sobel Magnitude Filter of RGBA image.
Last Updated:06/08/2015. Each of the R, G & B channels are treated independently with results computed concurrently for each. A parallel sum reduction that computes the sum of large arrays of values. NVIDIA IndeX Now Available on Google Cloud, Facebook Rolls out a GPU-Accelerated AI Shopping Tool for Marketplace, Microsoft and NVIDIA Announce June Preview for GPU-Acceleration Support for WSL, NVIDIA and Oracle Team up to Support AI Startups, NVIDIA Omniverse Available for Early Access Customers.
This sample evaluates fair call and put prices for a given set of European options by Black-Scholes formula.
Don’t have an Intel account? This example shows how to implement an existing computationally-intensive CPU compression algorithm in parallel on the GPU, and obtain an order of magnitude performance improvement. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Use the OpenCL technology to perform post processing on the surface before rendering to the screen with DXVA. These tutorials work with the supplied sample code to demonstrate important features in this release and can be found on Intel Software Documentation Library repository.. Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors.
See the README in the folder for more details. OpenCL is installed on OS X by default, but since this code uses the C++ bindings, you'll need to get that too. 2-dimensional Gaussian Blur Filter of RGBA image using IRF method. Learn more.
Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation. this example is based off of this example(example-ception), but it goes a bit further. OpenCL™ (Open Computing Language) is a low-level API for heterogeneous computing that runs on CUDA-powered GPUs.
Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. It uses the scan (prefix sum) function from the oclScan SDK sample to perform stream compaction.
For NVIDIA GPUs, I've installed the following packages: nvidia-346 nvidia-346-dev nvidia-346-uvm nvidia-libopencl1-346 nvidia-modprobe nvidia-opencl-icd-346 nvidia-settings. Try these quick links to visit popular site sections.
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