cuda book

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

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

according to the range of input and output values set by LUT. In this process, the CPU that has been highly optimized (mainly OpenMP and SIMD)CodeThe execution speed exceeds the GPU because the CPU clock speed is high. Unlike GPU, it is divided into two parts: core frequency and SP frequency. The existing openexr fp16 is inefficient due to lack of native support from hardware and compiler. Then the 3D LUT value is generated. Because the volume of 3D LUT is relatively large compared with 1D Lut,

Yesterday I saw that the official version of Cuda 4.0 was finally released, so I rushed to download it and ran to my computer to install it after work. After the installation, the devicequery routine of the new SDK is always unable to run successfully, but the devicequerydrv is no problem. I thought that the configuration was wrong, and I couldn't access the internet at home. So I had to try again and again. After one night, I still couldn't solve the

Main categories and features of GPU device-side memory: Size: Global and texture memory: The size is limited by the ram size. Local Memory: Each thread is limited to 16 KB Shared Memory: up to 16 KB Constant memory: 64 kB in total Each SM has 8192 or 16384 32-bit registers. Speed: Global, local, texture Data Alignment: The device can read 4-byte, 8-byte, or 16-byte content from the global memory in one operation to the Register, an error may be returned when an alignment of 8-byte or 16-byte