or This sample implements Mersenne Twister random number generator and Cartesian Box-Muller transformation on the GPU. Try these quick links to visit popular site sections. 2-dimensional Gaussian Blur Filter of RGBA image using IRF method. 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.
This sample implements bitonic sort algorithm for batches of short arrays. Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation. Another CLFFT example where an in-place real transform and an out-of-place real transform are performed.
WebGL Fundamentals (start here to learn WebGL) 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 Niederreiter quasirandom number generator and Moro's Inverse Cumulative Normal Distribution generator.
High Quality DXT Compression using OpenCL. For example 04, run (inside the directory): where PATH/TO/CLFFT is the path to the clFFT library. 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. This sample implements matrix multiplication and is exactly the same as Chapter 6 of the programming guide.
Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. password? Optimizing Simple OpenCL Kernels: Modulate Kernel Optimization: Optimizing Simple OpenCL Kernels: Sobel Kernel Optimization: OpenCL™ - Introduction for HPC Programmers: Video Motion Estimation Using OpenCL™ Technology: Advanced Video Motion Estimation Tutorial: OpenCL 2.0 Shared Virtual Memory Code Sample: Device Self-enqueue in OpenCL 2.0: Recursive Algorithm Example. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors.
We use essential cookies to perform essential website functions, e.g. Learn more. Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation. 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. Ok let's go; More info; WebGL Resources. they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. There's also FFTW code and Python code for checking the answer. Dot Product (scalar product) of set of input vector pairs. A simple example using the cl_khr_fp64 extension which allows for usage of doubles instead of floats. Efficient matrix solvers for large number of small independent tridiagonal linear systems.
Learn more. 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. Using the OpenCL API, developers can launch compute kernels written using a limited subset of the C programming language on a GPU. You can always update your selection by clicking Cookie Preferences at the bottom of the page. The GPU Computing SDK provides examples with source code, utilities, and white papers to help you get started writing GPU Computing software. Forgot your Intel Simple matrix-vector multiplication example showing increasingly optimized implementations. Demonstrates that one array can be modified several times without having to re-read and re-write data to and from the GPU. Implemented in OpenCL for CUDA GPU's. basic examples of OpenCL with the C++ API. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. You signed in with another tab or window.
Robert M Ioffe, Published:06/08/2015 The program creates a number of D3D10 textures (2D, 3D, and CubeMap) which are written to from OpenCL kernels. Implemented in OpenCL for CUDA GPU's, with performance comparison against simple C++ on host CPU. 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. Don’t have an Intel account? Measures the duration of adding two vectors. If nothing happens, download the GitHub extension for Visual Studio and try again. Each of the R, G, B and A channels are treated independently with results computed concurrently for each. CUBLAS provides high-performance matrix multiplication. OpenCL Post-Process OpenGL-Rendered Image. Simple program which demonstrates interoperability between OpenCL and OpenGL. Use Git or checkout with SVN using the web URL.
By signing in, you agree to our Terms of Service. This code uses OpenCL 1.1 on a NVIDIA GPU. This sample demonstrates a very fast and efficient parallel radix sort implemented in OpenCL for CUDA GPUs. Feel free to add more.
This sample demonstrates basic volume rendering using 3D textures. An example of the CLFFT library for an in-place complex-planar transform. OpenCL is installed on OS X by default, but since this code uses the C++ bindings, you'll need to get that too. Demonstrates overlapped copy/compute in 2 command queues. This sample demonstrates how Discrete Cosine Transform (DCT) for 8x8 blocks can be implemented in OpenCL. This sample demonstrates several important optimization strategies for parallel algorithms like reduction.
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