enable cuda

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

parallel acceleration when cmake based on the number of CPU cores you haveThe error that occurred:Error: ' Nppigraphcutstate ' have not been declaredBy modifying:Vim ~/envoriment/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cppSolve.6.sudo make Install7.Gedit/etc/profileAdd the following two lines to saveExport pkg_config_path=$PKG _config_path:/usr/local/lib/pkgconfig Export ld_library_path=$LD _library_path:/usr/local/lib Source/etc/profileGedit/etc/bash.bashrcAdd the following two lines t

(stderr,"MEMCPYHTD:%s\n", cudageterrorstring (status)); - } in -Cudamemcpy3dparms Devtohost = {0 }; toDevtohost.srcptr =devpitchedptr; +Devtohost.dstptr = Make_cudapitchedptr ((void*) BMP2, Width *sizeof(int), Width, Height); -Devtohost.extent =extent; theDevtohost.kind =Cudamemcpydevicetohost; *Status = Cudamemcpy3d (devtohost); $ if(Status! =cudasuccess) {Panax Notoginsengfprintf (stderr,"MEMCPYHTD:%s\n", cudageterrorstring (status)); - } theCudafree (devpitchedptr); + A int

that the GPU does the work we requested the BOOLSuccess =true; - for(inti =0; i) { in if((A[i] + b[i])! =C[i]) { theprintf"Error:%d +%d! =%d\n", A[i], b[i], c[i]); theSuccess =false; About } the } the if(success) printf ("We did it!\n"); the + //The memory we allocated on the GPU - Handle_error (Cudafree (dev_a)); the Handle_error (Cudafree (Dev_b));Bayi Handle_error (Cudafree (Dev_c)); the the //Free the memory we allocated on the CPU - Free (a); - Fr

1. Install NVIDIA graphics driver; then install Opencl/cuda http://blog.csdn.net/canhui_wang/article/details/72540004 2. Configure the local environment for Ethereum Mining sudo apt-gethttps://github.com/genoil/cpp-ethereum/blob/master/readme.md-y install Software-properties-common sudo add-apt-repository-y ppa:ethereum/ethereum sudo apt-get update sudo apt-get install git sudo apt-get install CMake sudo apt-get install Libcryptopp-dev sudo apt-

My first Ubuntu under the C program. C language 1. First confirm that you have the GCC compiler in the terminal input GCC--version view your GCC version. As shown, if there is no error occurs, it is installed 2. Create a new file of. C with a terminal Type vim hello.cin the terminal (file name is optional, but you need to use. C as the extension).3. After the creation press I enter the edit mode to enter the following code, then ESC exit screenwriter mode, in English state input: Wq (don'

First, the preface This paper mainly explains a small example of cuda parallel acceleration, and accelerates the nearest neighbor interpolation algorithm for image scaling. second, code implementation Because each new pixel is calculated in the same way as it is scaled, parallel computations can be used, as do the resize in OpenCV. main.cu////#include "cuda_runtime.h" #include iii. Results of the experiment In this paper, the experimental environ