opencl

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: While "googl'ing" and doing some research I were not able to find any serious/popular framework/sdk for scientific GPGPU-Computing and OpenCL on AMD hardware. Is there any literature and/or software I missed? Especially I am interested in deep learning . For all I know deeplearning.net recommends NVIDIA hardware and CUDA frameworks. Additionally all big deep learning frameworks I know, such as Caffe , Theano , Torch , DL4J , ... are focussed on CUDA and do not plan to support OpenCL/AMD . Furthermore one can find plenty of scientific papers

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I am currently using Intel's OpenCL SDK platform for heterogeneous parallel programming (OpenCL). I am using Visual Studio 2010 Ultimate for this. My system doesn't have any GPU in it. I have worked on CUDA SDK platform for opencl programming. This the first time I am using Intel's OpenCL SDK for opencl programming. I have tried some basic platform, device, context identifying/creating/defining codes from 'OpenCL in Action' book. They all worked fine. So we can consider that visual studio is properly configured. Now, I am trying to build a

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: After finally managing to get my code to compile with OpenCL, I cannot seem to get the output binary to run! This is on my linux laptop running Kubuntu 13.10 x64 The error I get is (Printed from cl::Error): ERROR: clGetPlatformIDs -1001 I found this post but there does not seem to be a clear solution. I added myself to the video group but this does not seem to work. With regards to the ICD profile... I am not sure what I need to do - shouldn't this be included with the cuda toolkit? If not, where could I download one? EDIT : It seems I have

Is it possible to compile OpenCL using Mingw and Nvidia SDK? I'm aware that its not officially supported but that just doesn't make sense. Aren't the libraries provided as a statically linked libraries? I mean once compiled with whatever compiler that may be, and linked successfully, whats should be the problem? I managed to compile and successfully link my code to OpenCL libraries provided with Nvidia's SDK, however the executable throws Segmentation Fault at clGetPlatformIDs which is the first OpenCL call in my code. Here is my compilation command x86_64-w64-mingw32-g++ -std=c++11 File.cpp \

1.配置OpenCL 1.下载 https://software.intel.com/en-us/intel-opencl 2.安装过程中会自动检查缺少的库。 2.CMakelists include_directories (/opt/intel/opencl-sdk/ include /CL) target_link_libraries (untitled1 /opt/intel/opencl-sdk/lib64/libOpenCL.so) 3.获取平台和设备信息 #include <iostream> #include <opencl.h> #include <time.h> using namespace std ; void show_platfor_device() { cl_platform_id *platform; cl_uint num_platform; cl_int error; error = clGetPlatformIDs( 0 , NULL, &num_platform); platform = (cl_platform_id *) malloc ( sizeof (cl_platform_id) * num_platform); error = clGetPlatformIDs(num_platform, platform, NULL); for

本篇结构： 背景 OpenCL是什么 框架组成 基本概念 编写OpenCL程序的基本步骤 参考博文 在过去利用GPU对图像渲染进行加速的技术非常成熟，因为GPU是典型的单指令多数据（SIMD）的体系结构，擅长大规模的并行计算；而CPU是多指令单数据流（MISD）的体系结构，更擅长逻辑控制。 在当今数据量计算越发庞大的情况下，为了提升计算效率，人们希望将GPU大规模的并行计算的能力扩展到更多领域，而不只局限与图像渲染。这样，CPU只负责逻辑控制，GPU更多负责计算，这种一个CPU（控制单元）+几个GPU（有时可能再加几个CPU）（计算单元）的架构就是所谓的异构编程。 OpenCL就是这种情况下出现的，它是一种 异构计算 的标准，可以用来针对GPU编程。其实在OpenCL出来之前，NVIDIA就推出了GPGPU计算CUDA架构。 只不过CUDA只能使用自家的N卡 ，对其他显卡不支持，而 OpenCL则是一个通用的标准，对A卡，N卡等都支持，还支持CPU计算 。 关于GPU和CPU的区别，可以参考我之前的博文 。 OpenCL(全称为Open Computing Langugae，开放运算语言)是第一个 面向异构系统 (此系统中可由CPU，GPU或其它类型的处理器架构组成)的 并行编程的开放式标准 。它是 跨平台 的。 OpenCL由两部分组成， 一是用于编写kernels

I'm trying to use Python with Theano to accelerate some code with OpenCL. I installed libgpuarray and pygpu as instructed (I think), and got no errors. The installation detected the OpenCL runtime installed. I just cannot run the Theano example for OpenCL, mainly because I don't know how to specify my GPU. My GPU is a Radeon HD 5340/5450/5470 , according to inxi . All code in the Theano documentation uses device=cuda0 and the only place where OpenCL is mentioned, it says device=openclN where N is a number. I tried device=opencl0 and got a pygpu error saying that the correct format is opencl

I am totally a beginner on opencl, I searched around the internet and found some "helloworld" demos for opencl project. Usually in such sort of minimal project, there is a *.cl file contains some sort of opencl kernels and a *.c file contains the main function. Then the question is how do I compile this kind of project use a command line. I know I should use some sort of -lOpenCL flag on linux and -framework OpenCL on mac. But I have no idea to link the *.cl kernel to my main source file. Thank you for any comments or useful links. Farzad In OpenCL, the .cl files that contain device kernel

I know the question is only partially programming-related because the answer I would like to get is originally from these two questions: Why are CPU cores number so low (vs GPU)? and Why aren't we using GPUs instead of CPUs, GPUs only or CPUs only? (I know that GPUs are specialized while CPUs are more for multi-task, etc.). I also know that there are memory (Host vs GPU) limitations along with precision and caches capability. But, In term of hardware comparison, high-end to high-end CPU/GPU comparison GPUs are much much more performant. So my question is: Could we use GPUs instead of CPUs for