ubuntu cuda

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

Caffegit clone git://github.com/bvlc/caffe.git7. Installing CaffeCP Makefile.config.example Makefile.configBecause there is no GPU here, you need to set cpu_only:= 1 in the Makefile.config file to remove the comment.and then compile Make All Make Test make RuntestAfter installation we can try to run a lenet on the mnist.1. Get Mnist Data firstCD Caffe. /data/mnist/get_mnist. SH2. Then create the lenet, be sure to run the following command at the root of the Caffe, otherwise the "Build/exampl

In some applications we need to implement functions such as linear solvers, nonlinear optimizations, matrix analysis, and linear algebra in the GPU. The Cuda library provides a Blas linear algebra library, Cublas. BLAS specifies a series of low-level lines that run common linear algebra operations, such as vector addition, constant multiplication, inner product, linear transformation, matrix multiplication, and so on. Blas has prepared a standard low-

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

1. When using shared memory, if stated__shared__ myshared;You do not need to indicate the size of shared when using the kernel functionIf you useextern __shared__ myshared;When you need to use kernel again 2. No space is requested for the asserted device variableWhen you run the Cuda code again, if you do not use the error-checking function for memory that is not used in the GPUCudamalloc allocates storage space, the code can be compiled through, and

In the process of image processing, we often use the gradient iteration to solve large-scale present equations; today, when the singular matrix is solved, there is a lack of DLL;Errors such as:Missing Cusparse32_60.dllMissing Cublas32_60.dllSolution:(1) Copy the Cusparse32_60.dll and Cublas32_60.dll directly to the C:\Windows directory, but the same error will occur at all times, in order to avoid trouble, it is best to use the method (2)(2) Copy Cusparse32_60.dll and Cublas32_60.dll to the file

. However, the actual scheduler in terms of instruction execution are half-warp Based,not warp based. Therefore we can arrange the divergence to fall on a half warp (16-thread) Boundary,then It can execute both sides of the Branch condition.if ((thread_idx%) ) { do something;} Else { do something;}However,it just happens when the data across memory is continuous. Sometimes we can supplement with zeros behind the Array,just as the previous blog mentioned,to a standard length of the Integ

Cudaprintfinit and Cudaprintfend only need to be called once in your entire project's use. The display results are not automatically displayed on the screen, but are stored in the cache and are cleared and displayed when Cudaprintfdisplay is called. The size of this cache can be specified by the optional parameters of the function cudaprintfinit (size_t bufferlen). Cudaprintfend simply frees up the storage space requested by Cudaprintfinit. When Cudaprintfdisplay is called, it is stored in cac

Reprinted: http://blog.csdn.net/jdhanhua/article/details/4843653 An unknown error is reported when time_t and a series of functions are used for compiling the. Cu file with nvcc. There are three methods to calculate the computing time in Cuda: Unsigned int timer = 0;// Create a timerCutcreatetimer ( timer );// Start timingCutstarttimer (timer );{// Code segment for Statistics............}// Stop timingCutstoptimer (timer );// Obtain the time from sta

Today, I tried to implement FFT using cuda, and encountered a problem. If you call the cufft library directly, the memory copy-to-data processing time is about. However, it is said that cufft is not the most efficient, so I want to exercise it myself. My idea is to map each row of two-dimensional data to a block, and each vertex is a thread. First, copy the data to the global memory of the video card, and then copy the data to the shared memory of ea

Opencv + cuda Memory leakage error, opencvcuda Memory leakage When using opencv to copy image data in a template, the following error is reported: Unhandled exception at 0x74dec42d in XXXX_CUDA.exe: Microsoft C ++ exception: cv: Exception at memory location 0x0017f878. Locate the error: CvReleaseImage ( copy_y); that is to say, when the image data is released, illegal memory read/write occurs; Template After reading the literature, many people

Cudaarray * dst,3 size_t woffset,4 size_t hoffset,5 const void * src,6 size_t count,7 enum cudamemcpykind kind 8) Cases:1 void initcudatexture (float *h_volume, float2 *velocity) 2 {3 cudachannelformatdesc desc = Cudacreatechanneldesc (32 , 0, 0, 0, cudachannelformatkindfloat); 4 5 cudamallocarray (d_volumearray, desc, 6 7 cudamemcpytoarray (D_volumearray, 0, 0, h_volume, sizeof (float) *128*128, cudamemcpydevicetodevice); 8 9

coalesce accessExample: The following code assigns a two-dimensional floating-point array of size width*height, and demonstrates how to iterate over the elements of the arrays in device code1//Host code 2 int width =, height = 3 float* devptr; 4 int pitch; 5 Cudamallocpitch ((void**) ;d evptr, pitch, Width * sizeof (float), height); 6 mykernel }15} 3, 3D linear memory1 cudaerror_t cudamalloc3d ( 2 struct cudapitchedptr * pitcheddevptr,3 struct cudaextent

Recently, some netizens in the group asked the Cuda 2D gmem copy question. Yesterday, the Forum also asked the same question: copy a sub slice of source gmem to another gmem, the following describes in detail how to implement a kernel that is no longer needed: Test (copy a sub-area with a size of 50x50 to the target gmem starting from the gmem area of 100x100 and the starting index is (25, 25): Note:CodeTested

First, install opencv correctly and pass the test.I understand that the GPU environment configuration consists of three main steps.1. Generate the associated file, that is, makefile or project file.2. compile and generate library files related to hardware usage, including dynamic and static library files.3. Add the generated library file to the program. The addition process is similar to that of the opencv library.For more information, see:Http://wenku.baidu.com/link? Url = GGDJLZFwhj26F50GqW-q1