opencl | 易学教程

Best approach for GPGPU/CUDA/OpenCL in Java?

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问题 General-purpose computing on graphics processing units (GPGPU) is a very attractive concept to harness the power of the GPU for any kind of computing. I'd love to use GPGPU for image processing, particles, and fast geometric operations. Right now, it seems the two contenders in this space are CUDA and OpenCL. I'd like to know: Is OpenCL usable yet from Java on Windows/Mac? What are the libraries ways to interface to OpenCL/CUDA? Is using JNA directly an option? Am I forgetting something? Any

What is the algorithm to determine optimal work group size and number of workgroup

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问题 OpenCL standard defines the following options to get info about device and compiled kernel: CL_DEVICE_MAX_COMPUTE_UNITS CL_DEVICE_MAX_WORK_GROUP_SIZE CL_KERNEL_WORK_GROUP_SIZE CL_KERNEL_PREFERRED_WORK_GROUP_SIZE_MULTIPLE Given this values, how can I calculate the optimal size of work group and number of work groups? 回答1: You discover these values experimentally for your algorithm. Use a profiler to get hard numbers. I like to use CL_DEVICE_MAX_COMPUTE_UNITS as the number of work groups,

library is linked but reference is undefined

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问题 I'm trying to compile an openCL program on Ubuntu with an NVIDIA card that worked once before, #include <CL/cl.h> #include <iostream> #include <vector> using namespace std; int main() { cl_platform_id platform; cl_device_id device; cl_context context; cl_command_queue command_queue; cl_int error; if(clGetPlatformIDs(1, &platform, NULL) != CL_SUCCESS) { cout << "platform error" << endl; } if(clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 1, &device, NULL) != CL_SUCCESS) { cout << "device error"

How to compile OpenCL on Ubuntu?

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问题 Question: What is needed headers and drivers are needed and where would I get them for compiling open CL on ubuntu using gcc/g++? Info: for a while now I've been stumbling around trying to figure out how to install open CL on my desktop and if possible my netbook. There are a couple tutorials out there that I've tried but none seem to work. Also, they all just give a step by step with out really explaining why for the what, or even worse they are specific to a particular IDE so you have to

What is a bank conflict? (Doing Cuda/OpenCL programming)

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问题 I have been reading the programming guide for CUDA and OpenCL, and I cannot figure out what a bank conflict is. They just sort of dive into how to solve the problem without elaborating on the subject itself. Can anybody help me understand it? I have no preference if the help is in the context of CUDA/OpenCL or just bank conflicts in general in computer science. 回答1: For nvidia (and amd for that matter) gpus the local memory is divided into memorybanks. Each bank can only address one dataset

mali GPU 官网指南

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https://blog.csdn.net/heliangbin87/article/details/79650654 1、简介 GPU（图形处理单元），是一种专门在个人电脑、工作站、游戏机和移动设备上图形运算工作的微处理器。以前GPU主要用于图形处理，现在GPU的通用计算技术也得到了飞速发展，事实证明在浮点运算、并行计算等部分计算方面，GPU可以提供数十倍乃至上百倍于CPU的性能。通用计算方面的标准有：OpenCl、CUDA、ATISTREAM。其中，OpenCL(全称Open Computing Language，开放运算语言)是第一个面向异构系统通用目的并行编程的开放式、免费标准，也是一个统一的编程环境，便于软件开发人员为高性能计算服务器、桌面计算系统、手持设备编写高效轻便的代码，而且广泛适用于多核心处理器(CPU)、图形处理器(GPU)、Cell类型架构以及数字信号处理器(DSP)等其他并行处理器，在游戏、娱乐、科研、医疗等各种领域都有广阔的发展前景，AMD-ATI、NVIDIA时下的产品都支持Open CL。 GPU的生产厂商非常多，最大的三家是英特尔、NVIDIA、AMD，他们主要应用于PC领域。相比ARM CPU占据了移动端90%市场，ARM的mali GPU只是移动市场众多GPU的一小众，它主要应用基于ARM 体系结构的移动设备上，得益于CPU占有率发展迅猛