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Ubuntu View installed Cuda Toolkit with its own tools and other installation files

Original works, reproduced please specify the source: Viewing toolsThe default directory is: local, enter local:cd/usr/localInput command: LS, view the files in this directory, you can see the installation of Cuda hereEnter Cuda file: CD cuda-7.5 (mine is 7.5), here for the installation of somethingLocate the ins

The cuda--translation of the Deep learning CUDA installation Guide for Linux (1) __linux

distribution, or enter from the command line:$ LSPCI | Grep-i nvidia If you don't have a settings, update the PCI hardware database that Linux maintains by entering Update-pciids (generally Found In/sbin) at the command line and rerun the previous LSPCI command.If you do not see any settings, please update-pciids (commonly seen/sbin) at the command line and re-run the previous LSPCI command by entering the update Linux maintenance PCI hardware database.If your graphics card are from NVIDIA and

CUDA Learning notes One: CUDA+OPENCV image transpose, using shared memory for CUDA program optimization

original articles, reproduced please indicate the source ... I. Background of the problem Recently to do a learning sharing report on Cuda, I would like to make an example of using Cuda for image processing in the report, and use shared memory to avoid the global memory not merging, improve image processing performance. But for the CUDA program how to read the

Windows-based Cuda installation (Setup Cuda on Windows)

location; this allows you to conveniently find the files in it. 4. syntax highlighting 4.1 set the usertype of the syntax file compiled by NVIDIA under % nvidia gpu computing SDK %/C/doc/syntax_highlighting/visual_studio_8. copy dat to % PAIA studio %/common7/ide. 4.2 start Visual Studio and choose tools> Options> text editor> file extension ", set the extension to Cu, select Microsoft Visual C ++ in the editor, and click "OK". 4.3 restart Visual Stu

windows-based CUDA Installation (Setup CUDA on Windows)

SDK location, so that it is easy to find the files inside. 4. Syntax highlighting 4.1 copies the%nvidia GPU Computing sdk%/c/doc/syntax_highlighting/visual_studio_8 under NVIDIA's written grammar file Usertype.dat to% Visua studio%/common7/ide 4.2 Start Visual Studio, select Tools > Options > Text editor > File extensions, set to CU with the editor select Microsoft Visual C + +, click "OK" and 4.3 reboot visual Studio. 5.IDE environment variable sett

Cuda Programming (ii) CUDA initialization and kernel functions

Cuda Programming (ii) CUDA initialization and kernel functionsCuda InitializationAs has been said in the last time, Cuda installation success, a new project is very simple, directly in the new project when the Nvidia Cuda project can be selected, we first create a new Mycudatest project, Delete the sample, an

Go Cuda in Windows under the Software development environment to build

Citation: this paper, we use Visual Studio 2005 as an example to demonstrate CUDA installation and software development environment, as well as CUDA and MFC to the implementation of the joint. 1. CUDA installation PackageCuda is free to use, the CUDA

[CUDA] some CUDA configurations

We have installed winxp64 + nvidia driver19 *. * + VS2008 (sp1), and we feel very stuck, so we have been using cuda2.2. I installed win7 recently and found that the driver compatibility for Versions later than 190 is very good. I installed cuda2.3. I wanted to try VS2010 beta2, However, I learned from Microsoft's staff that MSBuild still has some bugs, so I cannot use cuda normally and cannot patch me for the moment. Switch back to VS2008. When using

Ubuntu 16.04 Uninstall Cuda 6.5 and install Cuda 8.0

One, Introduction Since the system was upgraded from Ubuntu 14.04 to 16.04, the original Cuda 6.5 could not continue to be used, so Cuda 8.0 was reinstalled. Two, uninstall Cuda 6.5 and drive The following actions are operated at the command-line interface, such as pressing CTRL+ALT+F1 into the command lineFirst stop LIGHTDM:sudo service LIGHTDM stop Uninstall n

Cuda: supercomputing for the masses (Super computing for large amounts of data)-Section 1

homepage (find "Get Cuda "). Then, follow your specific operating system installation instructions. You don't even need a graphics processor, because you can use a software simulator to run on your laptop or workstation and start working. Of course, you can achieve better performance by running the Cuda GPU. Maybe your computer should have such a GPU. View cuda-

Cuda Software System

of threads in warp. 5. The 6. introduced some function sensitivity: Memory fence function, synchronous function, mathematical function, texture function, test time function, atomic function, warp vote function. The above extensions have some restrictions. If these restrictions are violated, nvcc will give an error or warning message, but sometimes it will not report an error and the program cannot run. Ii. nvcc Compiler The nvcc compiler compiles the Cuda

Cuda Advanced Third: Cuda timing mode

write in front The content is divided into two parts, the first part is translation "Professional CUDA C Programming" section 2. The timing YOUR KERNEL in CUDA programming model, and the second part is his own experience. Experience is not enough, you are welcome to add greatly. Cuda, the pursuit of speed ratio, want to get accurate time, the timing function is


CUDA 2, CUDACUDA Introduction CUDA is a platform for parallel computing and a class C programming model. We can easily implement parallel algorithms, just like writing C code. With NVIDIA GPUs, you can run your parallel programs on many devices, including desktops, laptops, and tablets. Familiarity with the C language helps you master CUDA as soon as possible.CUD

NVIDIA Cuda C Getting Started Guide for Microsoft Windows

Download the Cuda Software The Cuda software is available athttp: // the platform you are using and download the following: The Cuda driver The Cuda driver is integrated into the NVIDIA forceware graphics driver, which can be downloaded fromhttp: //

Install cuda, pyrit-cuda, And optimus on Kali Linux

I won't talk about the installation of cuda and optimus on the theme. I found that some foreigners did not succeed or there were few articles about Kali. After more than one day of repeated installation and testing, this article is the final one, the English version is also released.InstallCudaAndNvidiaDriverThis step is relatively simple. Before installation, we recommend that you edit the/etc/apt/source. list file, comment out the foreign source and

Nvidia DIGITS Learning Notes (nvidia DIGITS-2.0 + Ubuntu 14.04 + CUDA 7.0 + CuDNN 7.0 + Caffe 0.13.0)

Nvidia DIGITS Learning Notes (nvidia DIGITS-2.0 + Ubuntu 14.04 + CUDA 7.0 + CuDNN 7.0 + Caffe 0.13.0)Enjoyyl 2015-09-02 machine learning original linkNVIDIA DIGITS-2.0 + Ubuntu 14.04 + CUDA 7.0 + CuDNN 7.0 + Caffe 0.13.0 Environment configuration Introduction Digits Introduction Digits characteristics Resource information Description Digits installation

Ubuntu14.04 configure cuda-convnet and cuda-convnet

Ubuntu14.04 configure cuda-convnet and cuda-convnet Reprinted Please note: In the previous Link, I configured cuda and had a powerful GPU. Naturally, the resources could not be completely idle, So I configured a convolutional neural network to run the program. As for the principle of the convolutional neura

ubuntu14.04 Installation CUDA 7.5/cuda 8.0

Translated from: installation of CUDA7.5 and CUDA8.0 is a hair-like process. So if you install CUDA8.0, just replace all of the 7.5 below with 8.0.Toss a lot of days, before and after re-installed probably 六、七次 Ubuntu, finally on the Cuda installed, was the pit several times, also took a lot of detours.The first post, also please more advice.EnvironmentNotebook: ThinkPad T450 x86_64Video card:

Install cuda, pyrit-cuda, And Optimus on Kali Linux

I won't talk about the installation of Cuda and Optimus on the theme. I found that some foreigners did not succeed or there were few articles about Kali. After more than one day of repeated installation and testing, this article is the final one, the English version is also released. Install Cuda and NVIDIA driversThis step is relatively simple. Before installation, we recommend that you edit the/etc/APT/so

Cuda Learning: First CUDA code: Array summation

Today we have a few gains, successfully running the array summation code: Just add the number of n sumEnvironment: cuda5.0,vs2010#include "cuda_runtime.h"#include "Device_launch_parameters.h"#include cudaerror_t Addwithcuda (int *c, int *a);#define TOTALN 72120#define Blocks_pergrid 32#define THREADS_PERBLOCK 64//2^8__global__ void Sumarray (int *c, int *a)//, int *b){__shared__ unsigned int mycache[threads_perblock];//sets the shared memory within each block threadsperblock==blockdim.xint i = t

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