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OpenCL size_t Error

There is a problem with the programming test:1, increase kernel when the OpenCL compile error, AMD platform Error said that the source kernel cannot generate the corresponding executable program object;2, but the same set of code on the Intel E3 can operate normally;Obviously, it is also a implementation-dependent problem;This problem is in the implementation of size_t, has been experimental validation, here (LINK) has a simple description, the use of

Comparison of the use of the Altera OpenCL SDK with Xilinx SDAccel

For job requirements, the two high-level language synthesis tools were applied, and the typical algorithms were implemented and evaluated (data is temporarily kept secret).Briefly talk about the experience of using.1. Altera OpenCL SDKFirst, you need to install Quartus (more than 13.1 version) and the supporting Soc EDS, respectively, apply for two license, one for the OpenCL SDK, one for soceds, indispensa

NVIDIA Titan X graphics card performance evaluation NVIDIA Titan X

/s.Thanks to the new technology, new architecture, and new design, the power consumption of the whole-card thermal design remains at 250 W, with 8 + 6-pin auxiliary power supply.Another increase was the price of $1200, equivalent to nearly $8000, compared with $1000.However, you don't have the money to buy it, because the new Titan X is only available in Europe and America through the NVIDIA official website for the moment, and AIC vendors are not

Using OpenCL in Go, "crushing the GPU with a rainy day"

Original title: The OpenCL language binding package that can be used in the go GPU operationFirst page Access https://github.com/pseudomind/go-opencl/Find out and then download it C \Go\src\src>go get github.com/pseudomind/go-opencl/cl Search your OpenCL.dll file again and copy it to the Lib directory of the GCC compilerLike

Learning opencl development from scratch (4) shader

Here we will introduce how to write the program function in opencl. The program function is usually in the text format and load it in using interfaces such as clcreateprogramwithsource. This type of code is often used in shader programming to write the code running on the GPU. So for clarity and understanding, let's call the source code text of these program functions as the shader of opencl. The following

Opencl learning step by step (7) grayscale image histogram computing (1)

CPUVoid cpu_histgo (){Int I, J;For (I = 0; I {For (j = 0; j {// Printf ("data: % d \ n", data [I * width + J]);Hostbin [DATA [I * width + J] ++;// Printf ("hostbin % d = % d \ n", data [I * width + J], hostbin [DATA [I * width + J]);}}} How to Use opencl to calculate grayscale images is not that easy. We know that the advantage of GPU is parallel computing. How to partition images to calculate histograms in parallel is the focus of our discussion. Th

OpenCL Learning Resources

1.AMD Opencl-optimization-guidehttp://developer.amd.com/tools-and-sdks/opencl-zone/amd-accelerated-parallel-processing-app-sdk/ opencl-optimization-guide/#50401315_pgfId-5208002.apple of Opencl_macprogguidehttps://developer.apple.com/library/mac/documentation/Performance/Conceptual/OpenCL_MacProgGuide/ Tuningperformanceonthegpu/tuningperformanceonthegpu.html#//ap

AMD opencl university course (4)

Kernel Object: Kernel is a function in the program code, which can be executed on the opencl device. A kernel object is the kernel function and its related input parameters. The kernel object is created through the program object and the specified function name. Note: A function must exist in the source code of the program. Compile at runtime: During runtime, compiling programs and creating kernel objects have time overhead, but this is flexible an

Opencl Memory Object-global memory (1)

This log is a summary of the amd opencl document. Opencl uses memory object to transmit data between host and device. Memory Object is managed by Runtime (part of the Runtime Library and driver. The memory objects in opencl include buffer and image. buffer is a collection of One-dimensional data elements. Image is mainly used to store one-dimensional, two-dimensi

Accelerating computer vision algorithms using opencl on the mobile GPU

Accelerating computer vision algorithms using opencl on the mobile GPU March 12th, 2013 Abstract: Recently, general-purpose computing on graphics processing units (gpgpu) has been enabled on mobile devices thanks to the emerging heterogeneous programming models such as opencl. the capability of gpgpu on mobile devices opens a new era for mobile computing and can enable computationally demaning computer vi

Android Arm Mali OpenCL example-grayscale conversion

At hand a RK3288 board, on the board tested a 1080p color graph gray Conversion of OpenCL example. OpenCL does not have any optimizations. For example, please visit here. This example is an executable program compiled under the cheer Android platform.Go to the Jni folder and do the following:For my environment, the executable files, kernel.cl, and pictures are push to the//mnt/sdcard/

Improvement of image integration graph algorithm based on OpenCL

Complex algorithms are not necessarily inefficient, and simple algorithms often pay a price, which can be costly. Programming in the OPENCL environment has some differences with our traditional programming ideas on the CPU, which seem trivial, but often the details determine success, and these seemingly insignificant differences are infinitely magnified on multicore GPUs, resulting in a huge difference in the performance of the same algorithm on the G

OPENCL+OPENCV implementation of Sobel algorithm

These days, looking at the OpenCL Programming Guide, follow the example in the book to implement the Sobel algorithm:1. Combine OpenCV to read the image and save to the buffer;2. Write and compile the kernel and save the results after display processing.Kernel:Const sampler_t Sampler = Clk_address_clamp_to_edge | Clk_filter_nearest;kernel void Sobel_rgb (read_only image2d_t src,write_only image2d_t DST) {int x = (int) get_global_id (0 int y = (int) ge

OPENCL error code

Cl_invalid_work_item_size -55#define Cl_invalid_global_offset -56#define Cl_invalid_event_wait_list -57#define Cl_invalid_event -58#define Cl_invalid_operation -59#define Cl_invalid_gl_object -60#define Cl_invalid_buffer_size -61#define Cl_invalid_mip_level -62#define Cl_invalid_global_work_size -63#define Cl_i

Opencl kernel functions support double and struct

In opencl development, the double type must be supported to ensure accuracy. However, the double type is not mandatory in opencl standards. Some devices support it, and some do not, if your device supports this function, you need to declare the following statement at the beginning of all the values that appear in double: # Pragma opencl extension cl_khr_fp64: Ena

10 major considerations for GPGPU Opencl/cuda High performance programming

1. Expand the Cycle If you know the number of cycles in advance, you can do cyclic expansion, which eliminates the number of times the cycle conditions are compared. But it also doesn't make kernel code too big. Looping through code examples: #include 2. Avoid dealing with non-standardized figures OpenCL numbers are normal values that are less than the minimum exponent. Because of the limited number of digits in the computer, the range and prec

Use opencl to calculate the natural logarithm

The main reason is that the teacher used different methods to calculate the natural logarithm and understand the characteristics of different parallel languages. So I used multithreading. After OpenMP, I want to use opencl to implement the following. First I will introduce the algorithm. Method 1. Code host /* Project: multiply the matrix of opencl by: Liu Rong time: 2012.11.20 */# include Kernel Functio

Opencl learning step by step (9) grayscale image histogram computing (3)

In opencl programming, especially GPU-based opencl programming, the most important way to improve program performance is to improve memory utilization. One is to improve the overall memory read/write efficiency, the other is to reduce the bank conflit of local memory. Next, let's analyze the code in tutorial 7. What is the memory utilization rate? First, we use AMD's o

Opencl learning step by step (6) Rotating Images

In this tutorial, we will learn how to use opencl for simple image processing and rotating an image. Image reading, saving and other work, we use open source freeimage,: http://freeimage.sourceforge.net/ First, we create a gfreeimage class to load images. This class mainly calls the freeimage function, first initializes the freeimage library, and then guesses the image file format based on the file name, load the image file to the variable fibitmap *

Opencl learning step by step (8) grayscale image histogram computing (2)

Now we use the method in the previous tutorial to count the number of pixels in a pair of rgba images (This pixel satisfies the arbitrary components of R, G, B, And a> = 5 )? The method I want to consider is to create a histogram of 256 bin. For a pixel, calculate max (R, G, B, A) and use this value to determine the pixel to enter the bin, after obtaining the histogram, the width * Height-hostbin [0]-hostbin [1]-hostbin [2]-hostbin [3]-hostbin [4], that is, the result we want. The code in this t

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