cuda driver

A very simple Cuda program, suitable for people who have just reached Cuda to understand how Cuda works, and the basic usage of combining with OPENCV. #include http://blog.csdn.net/mmjwung/article/details/6273653

To create a new simple console application, the project name is Test00301, as shown in the following illustration: Then create a new file named Test01.cu in your project, as shown in the following illustration: Then select the item in Solution Explorer and right-click and select "Generate Custom ..." From the pop-up menu, as shown in the following figure: Check CUDA4.2 (or other versions) on the pop-up Visual C + + Build Customization files form, as shown in the following illustration: The

We all say that GPU Cuda is very Nb-hard, so the next step is to run the program through GPU acceleration. This week, we have been configuring the Cuda environment of opencv. Today we finally ended up failing because the graphics card of the lab machine does not support Cuda... Sorry, a week !!! Cuda-supported GPU: h

Transferred from: http://www.cnblogs.com/yeahgis/p/3853420.htmlVS2010 Error: The imported project XXX was not found, make sure that the path in the E:\igsnrr\dev\phdthesiscode_cuda\gtcg\gtcg.vcxproj:error: Imported items not found "C:\Program Files (x86) \msbuild\microsoft.cpp\ V4.0\buildcustomizations\cuda 5.5.props ". Make sure that the path in the Workaround: Locate the project Engineering Vcxproj file and find all "

Flow: The Cuda stream is much like a CPU thread, and the operations in a cuda stream are sequential and coarse-grained to manage the concurrent execution of multiple processing units.In layman's terms, the flow is used for parallel operations, such as processing the same image, you use a stream to process the left half of the picture, and then the second stream to process the right half of the picture, the

Cuda is very handy for parallel computing, but the interaction between the GPU and the CPU, such as passing parameters, is relatively cumbersome. When writing the Cuda kernel function, there will often be many parameters, to reach 10-20, if the data can be organized in advance of the CPU, such as the use of two-dimensional arrays, which can save a lot of arguments, in the kernel function can use a two-dimen

First build your own project, ordinary C + + project Write the C + + program you want to run Check a cuda option, because I installed two, casually select one can Select Properties Of course, if the new time is based on cudac++ then there is no need to choose this step. Then open the properties of the project and add Cudart.lib to the attachment dependencies in the configuration Properties-linker-Input And then you can write your own code. The code

Compare trial Platform Introduction After experiencing the outstanding performance of the core I5 2300 in 3D games and multitasking, HD playback and more, today I used my free time to compare my old platform against the core I5 2300 in HD transcoding, and the results were shocking. Good gossip not much to say, first to give their own new and old PC to do an introduction: Overview of the new platform (The NVIDIA GeForce 9800 GT is intentionally configured in the legacy system to compensate for

In the fifth lecture, we studied the GPU three important basic parallel algorithms: Reduce, Scan and histogram, and analyzed its function and serial parallel implementation method. In the sixth lecture, this paper takes the Bubble sort, merge sort, and sort in the sorting network, and Bitonic sort as an example, explains how to convert the serial parallel sorting method from the data structure class to the parallel sort, and attach the GPU implementation code.In the parallel method, we will cons

Original article link Today, we will introduce the relevant properties of Cuda devices. We can write code that is more suitable for hardware work only when we are familiar with the hardware and how it works. The cudadeviceprop struct records the properties of the device. 1 struct cudadeviceprop 2 {3 char name [256];/** Use cudagetdeviceproperties () to obtain the device attribute. Use cudagetdevicecount () to obtain the number of devices. Use cudacho

Source code and running result Cuda: https://github.com/zhxfl/cuCNN-I C language version reference from: http://eric-yuan.me/ The accuracy of the mnist library for famous handwritten numbers recognition is 99.7%. In a few minutes, CNN training can reach 99.60% accuracy. Parameter configuration The network configuration uses config.txt for configuration # comments between them, and the code will be filtered out automatically. For other formats, refer

Syntax highlighting in addition to the look comfortable, you can use F11 to find functions, variable definitions, hitting the function will also have a corresponding hint.The following is a set of code highlighting.In the Helloworldcuda.cu file above, the Cuda C + + keyword __global__ and so on are not highlighted, and there is a stroke curve. The following syntax highlighting of Cuda C + + keywords and fun

1. when compile /home/wangxiao/NVIDIA-CUDA-7.5 SAMPLES, it warning: gcc version larger than 4.9 not supported, so:old verson of gcc and g++ are needed: sudo apt-get install gcc-4.7 sudo apt-get install g++-4.7 Then, a link needed:sudo ln-S/Usr/Bin/gcc-4.7 / usr/local/cuda/bin/gccsudo ln - s /usr/bin /g++-4.7/usr/local/ cuda/bin/g ++ When c

What is CUDA Toolkit?For developers using C and C + + to develop GPU- accelerated applications, NVIDIA CUDA Toolkit provides a comprehensive development environment. CUDA Toolkit includes a compiler for Nvidia GPUs, many math libraries, and a variety of tools that you can use to debug and optimize application performance. You'll also find programming guides, use

0. IntroductionThis paper records the learning process of cuda-just beginning to touch the GPU-related things, including graphics, computing, parallel processing mode, first from the concept of things to start, and then combined with practice began to learn. Cuda feel no authoritative books, development tools change is faster, so the total feeling is not very practical. So this article is from the perspecti

(texref1d));//Unbind -Cutilsafecall (Cudafree (dev1d));//Free memory Space $ Cutilsafecall (Cudafree (DEVRET1D)); theFree (HOST1D);//free up memory space the Free (HOSTRET1D); the the ///2D Texture Memory -cout "2D Texture"Endl; in intwidth =5, height =3; the float*HOST2D = (float*) Calloc (width*height,sizeof(float));//Memory Raw Data the float*HOSTRET2D = (float*) Calloc (width*height,sizeof(float));//Memory return Data About theCudaarray *cuarray;//

Cuda file organization Original article address:Cuda Study Notes 2 Author:Ye Isaac Cuda file organization: 1. Cuda projects can contain. Cu AND. cpp. 2. In the. Cu file, you can use # include "cuda_x.cuh" to call the functions in. Cu or # include "cpp_x.h ". For example, declare Class A in test1.h; Define the related member functions of Class A in t

Compiling the environmentVMWare Workstation PlayerUbuntu-15.10-desktop-amd64CPU 4700MQ, allocating 6 cores +4GB memory +80GB HDD to VMCompile stepThe main reference is Caffe official websiteHttp://caffe.berkeleyvision.org/install_apt.html1. Install the Basic Package sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev Protobuf-compilersudo apt-get install--no-install-recommends Libboost-all-dev Cuda