cuda driver

First of all, my computer is Win7 64-bit operating system, installed is 32 for the Vs2008, to compile the OpenCv2.4.3 and TBB4.2; The process of compiling is a lot of people have said the blog of one of the most detailed, also most comprehensive: http://blog.csdn.net/shuxiao9058/article/details/7529684 The following content I just paste this article, easy to see ( where the green part is different from the original text, but also we need to pay attention to): Earlier, we talked about how to u

Tags: roc port nim Uda cal. Text exec iOS libFile directory:Cudatest|--utils.cu|--utils.h|--squaresum.cu|--squaresum.h|--test.cpp|--cmakelists.txtCompile command:$CD/root/cudatest$mkdir Build$CD Build$cmake:$makeThe relationship between the helpers:Utils: Provide common tools, here to provide query equipment information function;Squaresum: Calculates the square sum function, realizes the core function of Cuda runningTest: Call the square sum functionC

CUDA, cudagpuDynamic Parallelism So far, all the kernel is called on the host, and the GPU works completely under the control of the CPU. CUDA Dynamic Parallelism allows the GPU kernel to create a call on the device. Dynamic Parallelism makes recursion easier to implement and understand, because the startup configuration can be determined by the thread on the device at runtime, which also reduces data trans

Today, using the thread in Cuda block to modify the hexahedral of two for loops has been wrong.// For (int i= 0;i// { int j= threadidx.x; int i= threadidx.y; // For (int j = 0; j {Is that the incorrect sequence of I and J affects the coordinate position when calculating vertex coordinates: Boxverticescuda[gridindexnumstop]. Pos,-boxlength/2+widthblock*j, Boxtopy, (Boxlength/2-lengthblock*i));The Thread.x Thread.y

Create a Cuda project on vs2008, create the test. Cu file, copy the following code, compile and execute the code, and clearly see the difference between GPU running matrix multiplication and CPU efficiency. The following result is displayed on my PC. The GPU efficiency of matrix multiplication is improved by about an order of magnitude (relative to the CPU). The development environment is vs2008 + cuda5.x Development Kit + gt520m graphics card. Progr

Vs2010 error: the imported project XXX is not found. Make sure that the path in the E: \ igsnrr \ Dev \ phdthesiscode_cuda \ gtcg. vcxproj: error: the imported project "C: \ Program Files (x86) \ msbuild \ Microsoft. CPP \ v4.0 \ buildcustomizations \ Cuda 5.5.props ". Make sure that the path in the Solution: Find the vcxproj file of the project and find all "Cuda 5.5" content, as shown below:Modify the ver

Writing is not necessarily right. Wrong, please. Preface This article is made of c++11 thread.Compiling is probably g++ Sort.cpp-o3-pthread-std=c++14-o Sort Actually, I haven't learned c++14. Recently began to learn Cuda, feel thread specific how to use and hardware is directly related to different architectures AH different precision AH the way to use threads should be different. This blog is an experiment, using CPU to achieve parity sorting for fu

the GPU, parallel computing, all of a sudden, we have a lot closer to the parallel computation. Now in school to learn the computer is from the serial algorithm began, formed a lot of fixed serial thinking. When the problem is divided in parallel, there is a serial of ideas, it is not good: Text: We have talked about some concepts of threads before, but these concepts are soft links. We often hear so-and-so units say how good their hardware and software configuration is. The software is good,

MemoryThe performance of kernel can not be explained simply from the execution of Warp. For example, the previous post involved that setting the block dimension to half of the warp size would cause the load efficiency to be lowered, which could not be explained by warp scheduling or parallelism. The root cause is that the way to get global memory is poor.It is well known that the operation of memory occupies a very important position in the language that emphasizes efficiency. Low-latency and Hi

CUDA 8.0 in the function of the call is easy to move people. The following is the VC + + from the online learning of the. cpp file calls the Cuda. cu file in the function method, and the general VC + + function call method basically no difference.The Cuda version used is Cuda 8.0, which is installed by default.1.vs2013

Problem Description: Error while loading shared Libraries:libcudart.so.8.0:cannot open Shared object file:no such file or directory Workaround: First verify that the path in/etc/profile contains the installation path of the cuda8.0 and the corresponding library file Export path= $PATH:/usr/local/cuda-8.0/binExport Ld_library_path= $LD _library_path:/usr/local/cuda-8.0/lib64Export Library_path= $LIBRARY _p

For the purposes of performance and multi-GPU training, CNN has been studying cuda-convnet2 for a while.Search, online incredibly a decent research Cuda-convnet2 code articles are not found, it seems that the holiday has been busy.Caffe author Jiayanqing also expressed his admiration for Convnet2 author Alex in a number of occasions, showing the gap between the two CNN implementations.Caffe more in line wit

./configuresudo make sudo make install6. Lib Path(1) Open/build mkl.conf fileCommand: sudo gedit/etc/ld.so.conf.d/mkl.confInput content/opt/intel/lib/intel64/opt/intel/mkl/lib/intel64(2) Open/build cuda.conf fileCommand: sudo gedit/etc/ld.so.conf.d/cuda.confInput content:/usr/local/cuda/lib64/usr/local/cuda/lib(3) Immediate effectCommand: sudo ldconfig7. Installing protoc-cCommand: sudo apt-get install Pro

Ref: 22718173NVIDIA cuda:http://www.nvidia.cn/object/cuda-cn.htmlCuda Test Execution Time: http://www.cnblogs.com/lopezycj/archive/2011/08/09/cuda_time.htmlLearn makefile:http://www.cnblogs.com/freeaquar/archive/2012/04/03/2430860.html with Cuda SDKLinux command-line gdb debug command: http://blog.csdn.net/dadalan/article/details/3758025---------------------This article from Sandiwang csdn blog, full-text a

Cuda stream Test 1/* 2 * copyright 1993-2010 NVIDIA Corporation. all rights reserved. 3*4 * NVIDIA Corporation and its Licensors retain all intellectual property and 5 * proprietary rights in and to this software and related documentation. 6 * any use, reproduction, disclosure, or distribution of this software 7 * and related documentation without an express license agreement from 8 * NVIDIA Corporation is stric Tly prohibited. 9*10 * Please refer to

Cuda vs wizard 2.9 update Supports the latest Cuda version 5.0 First install Cuda 5.0, and then install this wizard You can easily create a project. You can easily create Lib. DLL. EXE. Static Link Library, dynamic link library, and execution program. Currently, only VS 2005 and vs2008 are supported. Vs2010 and vs2012 will be launched later. Below is MD5：dda87a94

During this time, I became familiar with Cuda and added the triangle mesh model for my experiment Renderer, We initially transplanted the original KD-tree to the GPU, but the structure of the KD-tree is still in the CPU. From simple smallpt (all of which are sphere) to the present,ProgramThe structure has been modified several times. Currently We still haven't found a good model. Cuda needs to inline all

Preface: from the previous article "Cuda Programming Interface (ii) ------ 18 weapons" to the present, it has been almost three months, and I don't know how everyone is doing in the "Summer vacation, what have you experienced? I spent two weeks before I went to bed. After reading the fifth book of "those things of the Ming Dynasty", I looked at the weapons of the Ming Dynasty, and thought about the Major of aircraft design I learned. The weapons of th

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

Link addr One: Run the programAccording to the previous article, after installing the Cuda software, you can use the "nvcc-v" command to view the compiler version used, I use the version information from: "Cuda compilation tools, Release 3.2, V0.2.1221." Create a directory yourself, in which the new CU file, write code, save, you can use the terminal to switch to the corresponding directory to compile, comp