Latest version of Cuda development Pack download: Click to open link
This article is based on vs2012,pc win7 x64,opencv2.4.9
compiling OPENCV source code
Refer to "How to Build OpenCV 2.2 with GPU" on Windows 7, which is a bit cumbersome, you can see the following
1, installation Cuda Toolkit, official instructions: Click to open the link
Installation process is like ordinary software, the last hint that s
original version was 8.0.1.After an afternoon of trying, and thought is the problem of network cable, changed the network cable, useless.The final method: sudo pip install.Python path for each installation package:/usr/local/lib/python2.7/dist-packagesError encountered:1. Some dependencies are not installed, such as Glog,lmdb. HDF5 because the installation is Hdf5-serial-dev, the Makefile.config header file library path needs to be added to the/usr/include/hdf5/serial.2.NVCC fatal:unsupported G
Http://heresy.spaces.live.com/blog/cns! E0070fb8ecf9015f! 3114. Entry
Sort Test Materials:
Cuda ZoneNVIDIA Cuda Official Website
Programming Guide
Cuda programming guide 1.0
Cuda programming guide 1.1
NVIDIA forums Cuda GPU computingCuda offi
://bugs.launchpad.net/ubuntu"
We can see that the machine version is ubuntu14.04.
Then, use gcc -- version to check whether the gcc version meets the requirements in connection 1:
~ $ Gcc -- versionGcc (Ubuntu 4.8.2-19ubuntu1) 4.8.2Copyright (C) 2013 Free Software Foundation, Inc.This is free software; see the source for copying conditions. There is NOWarranty; not even for MERCHANTABILITY or fitness for a particle PURPOSE.
After checking, go to the nvidia website (refer to link 3) to download t
Since the launch of NVIDIA's Cuda (compute United device architecture), it has been sought after by countless NVIDIA fans, and many technical staff in the non-graphic image field have started to play with Cuda. I am a bit lazy. Technically, apart from the theoretical and architectural aspects, other things, such as language details, are learned only when the actual work is needed, it took me some time to se
CUDA Installation Guide on Linux systems
Applicable operating system
Fedora 7,8,9,10
Redhat Enterprise 3.x,4.x,5.x
SUSE Linux Enterprise Desktop 10-sp1,10.2,11.0
OpenSUSE 10.1,10.2,10.3,11.0,11.1
Ubuntu 7.04, 7.10.,8.04,8.10,9.04
--------------------------------------------------------------------------------
Download and operating system matching
Driver, SDK, Tookit
Address: http://www.nvidia.com/object/cuda_get.html
---------------------------------
Yesterday hand cheap, put cuda and OPENCV environment variable changed, restart login interface input password prompts error, password must be correct, is not into, is very silent. Various solutions have been tried on the web, such as deleting/tmp and./xauthor in command line mode, or changing the environment variables previously changed, and so on.
Finally reinstall the CUDA again, reboot incredibly good.
In the past, the use of Cuda in the Linux environment, write Cuda program, because a paper source requirements with win system +vs, first in VS Open, compile Cuda project, encountered some obstruction, hereby record.My computer environment is win10,cuda7.5,vs2010. The first loaded vs2015, can not find NVCC, by Google, it seems vs2015 does not support
A while ago, I completed both the ant colony algorithm and the improved K-means algorithm, and then watched Cuda programming. I read the introduction of Cuda and thought that Cuda would be easy to use after C, in fact, you still need to know some GPU architecture-related knowledge to write a good program. After reading this book "
Discover this problem by chance ----
Who knows the performance and advantages and disadvantages of the program designed with OpenMP, Cuda, Mpi, and TBB. Please kindly advise me ~
I hope you can have a better understanding of this after learning it!
This problem is too big. It may not be clear to say three or two sentences.
Let's take a look at the parallel programming mode. There are shared memory and distributed, pure Data Parallel and task parall
Del. icio. us tags: cuda, shared library
Several dynamic connection libraries of Cuda:
Cutil: Cuda utility library, in the Cuda SDK
Cublas: Cuda Blas library, basic Linear Algebra
Cublasemu: cublas library in simulated state
Cudafft:
can't carry a hoe or a bamboo pole to conquer the conquering. The reason why Qin can unify the Six Nations and unify the weapons provide the same model of weaponry (see Qin's history, you can find all the weapons are the same model of production, crossbow devices can be interchangeable, from the Terracotta Warriors found in the pit, the size of the error is very small, can be interchangeable), It is also a good basis for him to conquer the other six countries.
Body:
Zi Yue: 工欲善其事, its prerequ
-Section 1.2: -Updated figure
The illustration graph is added to better explain that Cuda is not just a language, but a platform and a platform. It can be used to build other language platforms or programming environments on Cuda. Cuda has its own ISA architecture and PTx code. Therefore, do not simply think of Cuda as
Cuda was introduced a few months ago. At that time, I only learned about how to use it. Now I have read the large-scale parallel processor programming practice book again, the book talks about the first generation of Cuda architecture. Now the GPU has gone through Fermi and is already in the Kepler architecture. I still use the g80 card. It seems that I have to keep up with the times.
Today, when we use
The installation process is a bit tortuous, but finally can be successfully installed, because did not look at the official installation documents, resulting in a lot of time to install, I hope this article can let the students want to pack cuda little detour1.NVIDIA driver whether to installJust started to install Cuda, thought to install the video card driver, search how to install the driver, causing the
What? You learn the Cuda series (a), (b) It's all over. Still don't know why to use GPU to speed up? Oh, yes.. Feedback on Weibo I silently feel that the small number of partners to raise such a problem, but more small partners should be seen (a) feel away from their own too far so hurriedly remove powder ran away ... I didn't write Cuda series study (0) ... Well, this chapter on this piece, through a bunch
1. precautions
to compile the method see:
http://blog.csdn.net/wangyaninglm/article/details/39997113
The following is the program code, online search examples:
Note: 32-bit projects add 64-bit support (mainly depending on the version you compiled), and the project path of the CUDA is configured to include
2. Code
//SWAP.CU # Include "Cuda_runtime.h" #include "device_launch_parameters.h" #include
Swap.cpp
#include
Main.cpp
#include
3. Ac
From this part began to combine the bug's demo program to analyze the Cuda performance and feasibility.
One. The implementation process is outlined first.
Cuda is executed by letting one of the host's kernel perform on the graphics hardware (GPU) according to the concept of thread grid (GRID). Each thread grid can also contain multiple line Cheng (block), each of which can contain multiple threads (thread
I. Concept.
1. Related keywords.
CUDA (Compute Unified Device Architecture).
GPU English full name graphic processing unit, Chinese translation as "graphics processor."
2. Cuda is a general-purpose parallel computing architecture introduced by NVIDIA, which enables the GPU to solve complex computational problems. It contains the CUDA instruction set architect
Deb file installation, the advantage is not to exit the graphical interface.
1) Download the Deb file from the Cuda website
2) According to the process of the official website.
$ sudo dpkg-i cuda-repo-$ sudo apt-get update$ sudo apt-get install Cuda
3) Configure the environment, add the following command to/etc/profile or. BASHRC, save and make it effective with
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