cuda tools

First verify that you have an NVIDIA graphics card (Http://developer.nvidia.com/cuda-gpus this site to see if you have a graphics card that supports GPU): $ LSPCI | Grep-i nvidia See your Linux distributions (mostly 64-bit or 32-bit): $ uname-m cat/etc/*release Look at the version of GCC: $ gcc--versionFirst download the NVIDIA Cuda Warehouse installation package (my Ubuntu 14.04 64 bit, so the down

Based on years of Cuda development experience, we will briefly introduce the general development steps of the Cuda program, and follow the principle of first modifying the CPU serial program and then porting it to the GPU platform, modify the work that needs to be done on the GPU as much as possible on the CPU platform, reducing the difficulty of Program Development and debugging with bugs. By implementing

Install some dependencies first$sudo apt-get Install Freeglut3-dev build-essential libx11-dev libxmu-dev libgl1-mesa-dev Libglu1-mesa Libglu1-mesa-dev Libxi-devThere are two options for offline Installation: Debian installation package; Run Installation methodDeb Installation MethodThis is the case with Cuda 7.5 for 14.04, preferably MD5 validation of cuda installation files prior to this$ md5sum

Part of the content is transferred fromHttps://chenrudan.github.io/blog/2015/07/22/cudastream.htmlHttp://stackoverflow.com/questions/10415204/how-to-create-a-cuda-contextEarly on, it was discovered that the first function that was run on Cuda would take a long time to explain because Cuda initialization.So what's the main problem with

Summary of accelerated installation of Amber11 + AmberTools1.5 + CUDA The following installation method is based on some of the previous posts on the Forum simulated by the numerator. The installation and testing can be successful as long as the operation is correct. Considering that Amber11 is generally installed on clusters, the intel compiler and Openmpi parallel tool are used for installation. You need to purchase the Amber11 software to obtain th

For the first time, I officially wrote a technical blog. First, I exercised my ability to write summaries. Second, I felt ashamed to have read many technical posts but never contributed myself. 1. preparation 1. first, the runtime environment is ubuntu14.04. Therefore, this document assumes that ubuntu14.04 has been installed. In addition, nvidia designed its gpu programming architecture for cuda. For the first time, I officially wrote a technical blo

Since this book contains a lot of content, a lot of content is repeated with other books that explain cuda, so I only translate some key points. Time is money. Let's learn Cuda together. If any errors occur, please correct them. Since Chapter 1 and Chapter 2 do not have time to take a closer look, we will start from Chapter 3. I don't like being subject to people, so I don't need its header file. I will re

First install Cuda:Download from the NVIDIA official website: Cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb, there are two types of run and Deb, heavily recommended Deb format, easy to installCD to the directory where Cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb is located, such as mine:CD ~/software/cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.debPerform:sud

This article is originally contained in my homepage:planckscale.info, reproduced here. Copyright Notice: Original works, welcome reprint, but reproduced please indicate the source of the article (Planckscale.info), author information and this statement in the form of hyperlinks, otherwise the legal liability will be investigated.In the previous article, two points to Cuda's computational power are very significant: data parallelism, and the use of multithreading to mask the delay. Next we'll go

Bo Master due to the needs of the work, began to learn the GPU above the programming, mainly related to the GPU based on the depth of knowledge, in view of the previous did not contact GPU programming, so here specifically to learn the GPU above programming. Have like-minded small partners, welcome to exchange and study, my email: caijinping220@gmail.com. Using the Geforce 103m graphics card on his old notebook, although the graphics card is already very weak relative to the current mainstream s

Install Torch in Ubuntu and configure CUDA and cuDNNGeneral description Ubuntu is 14.04, and cuda is 7.5 cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64. Cudnn is 7.5, cudnn-7.5-linux-x64-v5.0-ga.tgz.Reference: Link: https://github.com/jcjohnson/neural-style/blob/master/INSTALL.mdNeural-styleIn fact, this article has clearly explained how to install it, but it still

1. Installing Build-essentialsInstall some basic packages needed for developmentInstall Build-essential2. Install the Nvidia driver (3.4.0) 2.1 Preparation work (2014-12-03 Update)In the case of shutting down the desktop management LIGHTDM, installing the driver seems to implement Intel HD graphics to display + NVIDIA graphics card to calculate. The steps are as follows:1. First select the Intel graphics card to display or use as the primary display device in the BIOS setup.2. Enter Ubuntu, pres

The author took a long time to install, mainly Cuda installation and OpenCV installation more laborious, Cuda find 32-bit installation package had to reinstall 64-bit Ubuntu system, OpenCV is also trying to solve, it is recommended to use 2.4.9 version. In fact, if the GPU does not need to install CUDA, but for subsequent compatibility considerations, the system

The same machine can be compatible with multiple versions of the CUDA, these two days will be so back and forth, slightly trouble. 1. View the current Cuda version; NVCC--versionFrom this we can see that the current is Cuda 8.0. 2. Modify the. bashrc file. Export path= $PATH:/usr/local/cuda-8.0/bin export ld_library

Software Version Window10 X64 Python 3.6.4 (64-bit) CUDA CUDA Toolkit 9.0 (Sept 2017) CuDNN CuDNN v7.0.5 (Dec 5), for CUDA 9.0 The above version of the test passed.Installation steps:1. to install python, remember to tick pip. 2. detects if

Because of the project needs, our deep learning algorithm must be accelerated, so the group gave me two gpu:gtx-750 Ti GRID-K2 GTX-750 Ti was I installed in the local, GRID-K2 installed on the server, need to SSH login to use, followed by a variety of pits ......... ..... First, let's talk about Grid-k2, server-side installation: 1. First, if you have only this card, sorry, you can not click here to see Cuda supported GPU here to find the information

This article is originally contained in my homepage:planckscale.info, reproduced here. Copyright Notice: Original works, welcome reprint, but reproduced please indicate the source of the article (Planckscale.info), author information and this statement in the form of hyperlinks, otherwise the legal liability will be investigated.The previous article discussed how concepts such as blocks in the programming model map to hardware execution, and how Cuda

In the past two days, I took some time to study the problem of calling the Cuda program using Matlab. I found that there was less information on the Internet and the White Paper provided by NVIDIA was not detailed enough. Therefore, I would like to summarize the development process, hope you can use it. In general, there are two methods to call the Cuda program in MATLAB. The first is to create the DLL of t

Solution to installation failure of cuda-8.0 driver on centos7 Once upon a time, the NVIDIA Titan X card is inserted on the centos7 machine, according to the official website tutorial (https://developer.nvidia.com/cuda-downloads) one-click installation of cuda-8.0 everything went smoothly Installation Instructions: 'Sudo rpm-icuda-repo-rhel7-8-0-local-8.0.44-1.

Caffe + Ubuntu 15.04 + CUDA 7.5 Novice Installation Configuration GuideSpecial:0. Caffe website address: http://caffe.berkeleyvision.org/1. This article is for the author to complete the experiment, but only for the use of academic exchange, the use of this guide any adverse consequences of the user's own responsibility, not related to the author of this article, thank you! In order to ensure timely updates, reproduced please indicate the source, than