cuda book

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

Talking about memory access, in fact, is also a few API function calls, feel nothing good to say, know Cudamalloc, know cudamemcpy, and cudafree, you should be able to allocate device memory, then you can use memory on the device. But just like when we watch the sports meeting, just look at the 100 meters of less than 10 seconds, perhaps you will only say that he runs really fast. How many people can understand the temper of the process? To really understand the device of memory scheduling acces

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

Oracle VM VirtualBox Downloadubuntu14.04Install the VirtualBox first and then mount the ubuntu14.04 on top. Note To install the enhancements (after starting the virtual machine, select the "Devices" menu, select the "Insert Guest additions CD Images" option.) If you do not see devices, press the right crtl+c), otherwise the screen is not displayed completely.Caffe installation (temporarily not well, encountered problems: After the installation of Cuda

Blacklist nouveau Blacklist rivafb Blacklist nvidiafb Blacklist rivatv After completing the preceding steps, download the cuda software (using the latest version 6.5) The https://developer.nvidia.com/cuda-downloads downloads from the appropriate System Selection After the download, you can run the installation. Chmod + x cuda_6.5.14_linux_64.run ./Cuda_6.5.14_linux_64.run The process went smoothly and ther

Looking at Cuda information for some time, there are also a lot of information on the Cuda environment configuration online, such: visual Studio 2008 + visual assist X's cuda2.3 compiling environment sets up yongge's Cuda vs2005 wizard and so on, mainly for the configuration of vs integrated development environment, but there are few command line methods. I think

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

1, first need to uninstall the system comes with the NVIDIA-related driver: $ sudo apt-get –purge remove nvidia-GLX Nvidia-GLX-New$ sudo apt - Get –purge remove nvidia-settings nvidia-kernel -Common 2, after the original drive deleted, also need to add Ubuntu integrated open source driver blacklist, that is, modify the/etc/modprobe.d/blacklist.conf file: sudo gedit /etc/modprobe. D / blacklist . confAdd the following two lines to the file:Blacklist nouveauOptions Nouveau modeset=03, in

The content of further learning after getting started is how to optimize your code. Our previous example did not consider any performance optimizations in order to better learn the basic points of knowledge, rather than other detail issues. Starting with this section, we want to think about performance and constantly optimize the code, making execution faster is the only purpose of parallel processing. There are many ways to run the code, and the C language provides an API similar to SYSTEMTIME

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

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 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