enable cuda

I want to learning deep learning, so config Cuda is a essential step. Luckily it's very easy in UbuntuInstall Theano+cuda in Ubuntu1. Install TheanoA) sudo apt-get install python-numpy python-scipy python-dev python-pip python-nose g++ libopenblas-dev gitb) sudo pip install Theano2. Install CudaA) sudo apt install nvidia-331If It is a successful, we can test it with$dkms statusIf you see the response like n

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

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

Nvidia cuda Driver For Linux local information leakage Vulnerability Release date:Updated on: Affected Systems:Nvidia cuda DriverDescription:--------------------------------------------------------------------------------Bugtraq id: 45717 NVidia is the world's leading manufacturer of graphics processing chips and graphics cards. Nvidia cuda Driver for linux h

1. Update DriverTo download the system graphics driver, first view your graphics card model in Device Manager, mine is GeForce GTX 960, then download the corresponding driver and install it on the official website.Official website: NVIDIA driver download2. Installing CudaDownload the corresponding Cuda Toolkit on the website, here I choose the Underground download, and then directly installed.Website: CUDA

9. Cuda shared memory use ------ GPU revolutionPreface: I will graduate next year and plan for my future life in the second half of the year. In the past six months, it may be a decision and a decision. Maybe I have a strong sense of crisis and have always felt that I have not done well enough. I still need to accumulate and learn. Maybe it's awesome to know that you can go to Hong Kong from the Hill Valley. Step by step, you are satisfied, but you ha

Today we will talk about several cuda-related concepts in the GPU hardware structure: thread block grid warp SP Sm SP: the most basic processing unit. The specific commands and tasks of streaming processor are processed on the SP. GPU for parallel computing, that is, multiple SPs simultaneously Process SM: multiple SPs and other resources form an SM, streaming multiprocessor. Other resources are storage resources, shared memory, and storage devices. W

Finally, the content of the thread is parsed: In SIMD terms, each of the 32 threads is called a line Cheng, which executes the same instruction, and each thread uses a private register to make this operation request.Suddenly feel, do Cuda program like to go to Beijing to work: write MPI, but also to see Pthread, and then switch to English class to write a pile of homework, and also see jquery sometimes write a page unavoidably use, and go to Beijing,

Cuda InstallationCuda is installed in Windows 7,1. First, download and install the relevant driver, toolki, and SDK from the cuda official website (these three software packages can be downloaded directly on the official website as prompted );2. After the preceding three environment variables are installed, three environment variables, CUDA_INC_PATH, CUDA_LIB_PATH, and CUDA_BIN_PATH, are automatically set.

Recently, I am working on a Cuda project, where the texture memory is used to accelerate the Data Reading and interpolation processes. because some details are not fully noticed. the progress of this project is slow. data accuracy is very high. there is no way. We can only conduct step-by-step troubleshooting and solve this problem completely today. the reason is that the texture index is not noticed. OK. If you want to talk less, pay attention direct

Because our CudaProgramIs put on the server to run, so I want to connect to the host using SSH, and then compile and run the program in the host. Because it was installed by the Administrator and I am not an administrator user, Cuda is not configured in the environment variable and needs to be configured manually. Method: VI ~ /. Bashrc After entering VI, press I to enter the insert and modify mode, and add the following to the end of the file:

Caffe is a concise and efficient deep learning framework, the specific introduction can be seen here, Caffe environment configuration process can refer to here, I built the environment when the collection of a lot of information, here to organize a bit, introduce caffe in the environment without cuda how to configure.1. Installing Build-essentialsinstall some basic packages needed for development sudo apt-get Install build-essentialIf the essential pa

The most common C + + compiler under Windows is the compiler that comes with Visual Studio Cl.exeThis is usually the directory where:C:\Program Files (x86) \microsoft Visual Studio 10.0\vc\binIf you are not prompted to find Mspdb100.dll, you can usually find this file hereD:\Program Files (x86) \microsoft Visual Studio 10.0\Common7\IDEand add it into the system path.Set path=%path%;D: \program Files (x86) \microsoft Visual Studio 10.0\Common7\IDEIf you are programming Nvidia graphics, you need t

About cuda Register arraysin order to improve the speed of the algorithm in the parallel optimization of some algorithms based on Cuda, sometimes we would like to use Register array to make the algorithm fly generally fast, however, the effect is always passable. Used to be faster than useless, this is why? Haha, to say the point, we define the array of registers in the following two ways:1 Inta[8]; At this

Thank your friends for supporting this blog, welcome to discuss the exchange, because of limited capacity and time, mistakes are unavoidable. Please correct me!If reproduced, please retain the author's information.Blog Address: http://blog.csdn.net/qq_21398167Original post address: http://blog.csdn.net/qq_21398167/article/details/46413683Login system with usernamecluster1. Check if the GPUis installed: Lspci | Grep-i nvidia 2. Install gcc,g++ compiler sudo yum install gcc

This program is to add two vectorsAddTid=blockidx.x;//blockidx is a built-in variable, blockidx.x represents this is a 2-D indexCode:/*============================================================================Name:vectorsum-cuda.cuAuthor:canVersion:Copyright:your Copyright NoticeDescription:cuda Compute reciprocals============================================================================*/#include using namespace Std;#define N 10__global__ void Add (int *a,int *b,int *c);static void Checkcud

In the written template, the error is as follows when copying the image data using OpenCV:Unhandled exception at 0x74dec42d in Xxxx_cuda.exe:Microsoft C + + exception:cv::exception at memory location 0x0017f878.Navigate to Error in:Cvreleaseimage (copy_y), that is, the release of image data is the time, the occurrence of illegal memory read and write;TemplateAfter reviewing the literature, many people encounter similar problems, the conclusion is OPENCV itself bug;Strangely, I willIplimage *copy

char) (128.0f+127.0f*cos (d/10.0f-ticks/7.0f)/(d/10.0f+1.0f));Ptr[offset*4+0]=grey;Ptr[offset*4+1]=grey;Ptr[offset*4+2]=grey;ptr[offset*4+3]=255;}int main (){DataBlock data;Cpuanimbitmap bitmap (Dim,dim,data);Data.bitmap = bitmap;Cuda_check_return (Cudamalloc (void * *) data.dev_bitmap,bitmap.image_size ()));Bitmap.anim_and_exit ((Void (*) (Void*,int)) Generate_frame, (Void (*) (void*)) cleanup);}void Generate_frame (DataBlock *d,int ticks){A total of dimxdim pixels, each pixel corresponding to

The simple vector Plus/** * Vector addition:c = a + B. * * This sample was A very basic sample that implements element by element * Vector Addit Ion. It is the same as the sample illustrating Chapter 2 * of the Programming Guide with some additions like error checking. */#include Copyright NOTICE: This article for Bo Master original article, without Bo Master permission not reproduced. Cuda Learning Note Two

CUDA Computational ModelCuda is calculated in two parts, the serial part executes on the host, namely the CPU, while the parallel part executes on the device, namely the GPU.Cuda has added some extensions, including libraries and keywords, compared to the traditional C language.Cuda code is submitted to the NVCC compiler, which divides the code into both the host code and the device code.The host code is the original C language, referred to GCC,ICC or