ubuntu cuda

Login system with username cluster1. Check if the GPUis installed: Lspci | Grep-i nvidia 2. Install gcc,g++ compiler sudo yum install gcc sudo yum install gcc-c++ 3. Installing kernel-devel sudo yum install Kernel-devel 4. installation of Driver,Toolkit and Samples sudo sh cuda_5.5.22_linux_64.run--kernel-source-path= '/usr/src/kernels/2.6.32-358.23.2.el6.x86_64 ' Here we have installed a matching driver, so the first Driver out of the t

Recently need to use matconvnet under Ubuntu16.04. Because TensorFlow 1.6 supports Cuda 9.0, the new machine is loaded directly 9.0 but there are some problems when compiling matconvnet.1. Error using MEX NVCC fatal:unsupported GPU architecture ' compute_20 'Solution: This is because Cuda 8 does not support COMPUTE_20, the lowest is compute_30. So you need to modify the following code in the VL_COMPILENN.MO

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

Now it is necessary to get the sum of all the elements of an array, which seems unlikely before, because each thread only processes one element and cannot relate all the elements, but has recently learned a piece of code that can be implemented, and also has a further understanding of shared memory.First, C + + serial implementationThe method of serial implementation is very simple, as long as all elements are added sequentially to get the corresponding results, in fact, we focus on not the resu

1. Install Blas:$ sudo apt-get install Libatlas-base-dev2. Install the dependencies:$ sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev Libhdf5-serial-dev Protobuf-compiler Liblmdb-dev3. Install additional dependencies:$ sudo apt-get install Libgflags-dev libgoogle-glog-dev Liblmdb-dev4. Download Caffe:$ git clone git://github.com/bvlc/caffe.gitBecause of the slow download speed, this step can be directly used by others to download the Caffe package

CUDA cannot recognize texture Just began to learn cuda texture memory, from the Internet to find learning materials, but the test, the program is prompted error: Texture Output[y*width + x] = tex2d (Texref, TU, TV); Texture,tex2d not recognized The first thought was to find the definition of the function, which was defined in the Cuda_texture_types.h file, defined as Template , so the hea

GPGPU is a nuclear equipment, including a large number of computing units, to achieve ultra-high speed parallelism. When you use Cuda to program on the NVIDIA graphics card, you can use the event provided by Cuda to do the timer. Of course, each programming language basically provides a function to get the system time, such as the C/c++/java program timer function An event can be used to count the exact

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;//

There are two versions that developers need to care about when developing Cuda applications: computing capability-describe product specifications and computing device features and Cuda driver API version-Describe the features supported by the driver API and runtime.You can obtain the driver API version from the macro cuda_version in the driver header file. Developers can check whether their applications req

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

I have long heard of many advantages of Cuda nexus: Support for GPU thread debugging and analysis... It took me one afternoon to build the Cuda nexus environment. The following are the points to pay attention to when building: I. Hardware: During remote debugging, the target machine's video card must be a Cuda Device of G92 or gt200, and the host can be any vi

This is a wonderful idea ... We don't talk about whether it means anything. This wonderful idea appears based on the following 2 points: 1, OPENCV code once compiled into a library file, it is difficult to modify the internal code, although most of the need to modify the part has been referred to the interface above. 2, OpenCV in the use of Cuda accelerated code written or very efficient, however, the corresponding large, complex C + + interface conv

cudaevent_t Start,stop;Cudaeventcreate (start);//Create EventCudaeventcreate (stop);Cudaeventrecord (start,0);//Record Current timeThings to keep track of time/workCudaeventrecord (stop,0);//Record Current timeCudaeventsynchronize ();//Syncfloat ElapsedTime;Cudaeventelapsedtime (elapsedtime,start,stop);//calculation of the time difference, that is, the execution times of the eventCudaeventdestroy (start);//Destroy EventCudaeventdestroy (stop);The Cuda