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Adding triangle mesh support for my Cuda Renderer!

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

Introduction to Cuda C Programming-Programming Interface (3.4) Computing Model

Tesla solutions running on Windows Server 2008 and later versions or Linux can be used through the NVIDIA System Management Interface (NVIDIA-SMI, as a tool for release drivers) set any device in the system to run in one of the following three computing modes: Default computing mode: Multiple Threads can use devices at the same time (use the Runtime API to call cudasetdevice () on this device, or use the driver API to associate the current context with the device ). Computing mode exclu

Linux (CentOS7) installation Cuda

Login system with username cluster1. Check if the GPUis installed: Lspci | Grep-i nvidia 2. Install gcc,g++ compiler sudo yum install gcc sudo yum install gcc-c++ 3. Installing kernel-devel sudo yum install Kernel-devel 4. installation of Driver,Toolkit and Samples sudo sh cuda_5.5.22_linux_64.run--kernel-source-path= '/usr/src/kernels/2.6.32-358.23.2.el6.x86_64 ' Here we have installed a matching driver, so the first Driver out of the t

"Record" compilation Matconvnet on ubuntu16.04 with Cuda 9.0

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

The basic process of CUDA programming under Ubuntu

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

Gamma transform of the image implemented by Cuda and OPENCV

A very simple Cuda program, suitable for people who have just reached Cuda to understand how Cuda works, and the basic usage of combining with OPENCV. #include http://blog.csdn.net/mmjwung/article/details/6273653

Learning opencv -- configuring the Cuda Environment

We all say that GPU Cuda is very Nb-hard, so the next step is to run the program through GPU acceleration. This week, we have been configuring the Cuda environment of opencv. Today we finally ended up failing because the graphics card of the lab machine does not support Cuda... Sorry, a week !!! Cuda-supported GPU: h

Upgrade Cuda version causes VS2010 error: The imported item xxx is not found, verify that the path in the <Import> declaration is correct, and that the file exists on the disk

Transferred from: http://www.cnblogs.com/yeahgis/p/3853420.htmlVS2010 Error: The imported project XXX was not found, make sure that the path in the E:\igsnrr\dev\phdthesiscode_cuda\gtcg\gtcg.vcxproj:error: Imported items not found "C:\Program Files (x86) \msbuild\microsoft.cpp\ V4.0\buildcustomizations\cuda 5.5.props ". Make sure that the path in the Workaround: Locate the project Engineering Vcxproj file and find all "

Flow and events in Cuda

Flow: The Cuda stream is much like a CPU thread, and the operations in a cuda stream are sequential and coarse-grained to manage the concurrent execution of multiple processing units.In layman's terms, the flow is used for parallel operations, such as processing the same image, you use a stream to process the left half of the picture, and then the second stream to process the right half of the picture, the

Win10 Cuda 9.0 Uninstall

1. First For cuda8.0, cuda7.5 Uninstall can be compatible After installing cuda9.0, the original NVIDIA graphics driver for the computer will be updated and the Nvidia PhysX system software will be updated (installing the low cuda may not be updated). Please pay attention when unloading, do not move these 2. 2. Uninstall:1. Preface: Anti-virus software to uninstall this, not easy to find. Open the computer's control pane

Ubuntu 14.04 Installation CUDA problem and solution

This article installs the environment:-Dual Graphics: Intel set + NVIDIA single display-Ubuntu 14.04.4-CUDA 8.0.441. The Deb installation package is a pit ( don't use this method!) )With the DEB installation package Cuda-repo-ubuntu1404-8-0-local_8.0.44-1_amd64.deb, after the installation is complete, the reboot appears with a black screen,-resolution after a black screen appears:(1) Ctrl + Alt + F1 into co

OpenCV the use of two-dimensional mat arrays (level two pointers) in Cuda

Cuda is very handy for parallel computing, but the interaction between the GPU and the CPU, such as passing parameters, is relatively cumbersome. When writing the Cuda kernel function, there will often be many parameters, to reach 10-20, if the data can be organized in advance of the CPU, such as the use of two-dimensional arrays, which can save a lot of arguments, in the kernel function can use a two-dimen

C + + mixed implementation of C + + GPU program in VS Cuda

First build your own project, ordinary C + + project Write the C + + program you want to run Check a cuda option, because I installed two, casually select one can Select Properties Of course, if the new time is based on cudac++ then there is no need to choose this step. Then open the properties of the project and add Cudart.lib to the attachment dependencies in the configuration Properties-linker-Input And then you can write your own code. The code

Intel hardware Acceleration VS cuda outright video transcoding experience

Compare trial Platform Introduction After experiencing the outstanding performance of the core I5 2300 in 3D games and multitasking, HD playback and more, today I used my free time to compare my old platform against the core I5 2300 in HD transcoding, and the results were shocking. Good gossip not much to say, first to give their own new and old PC to do an introduction: Overview of the new platform (The NVIDIA GeForce 9800 GT is intentionally configured in the legacy system to compensate for

Parity ordering (without Cuda) based on c++11 CPU threads __c++

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

ubuntu14.04+cuda8.0 re-installing CUDA

The problem occurs when you re-make the Caffe:sudo make runtest after reinstalling the video driver: Check Failed:error = = cudasuccess (30vs.0) unkown error ... 1. Uninstall the original Cuda sudo/usr/local/cuda-8.0/bin/uninstall-cuda-8.0.pl 2. Re-install Cuda 3. Problems occurred: /USR/BIN/LD:-lglut collect2 not foun

IOS Address Book programming, listening for system address book changes, and ios address book

IOS Address Book programming, listening for system address book changes, and ios address book Listen for address book changes The client code must be implemented as follows: /* Remove the registration function */-(void) dealloc {ABAddressBookUnregisterExternalChangeCallback (_ addressBook, ContactsChangeCallback, nil)

CUDA (vi). Understanding parallel thinking from the parallel sort method--the GPU implementation of bubbling, merging and double-tuning sort

In the fifth lecture, we studied the GPU three important basic parallel algorithms: Reduce, Scan and histogram, and analyzed its function and serial parallel implementation method. In the sixth lecture, this paper takes the Bubble sort, merge sort, and sort in the sorting network, and Bitonic sort as an example, explains how to convert the serial parallel sorting method from the data structure class to the parallel sort, and attach the GPU implementation code.In the parallel method, we will cons

Cuda development: Understanding device Properties

Original article link Today, we will introduce the relevant properties of Cuda devices. We can write code that is more suitable for hardware work only when we are familiar with the hardware and how it works. The cudadeviceprop struct records the properties of the device. 1 struct cudadeviceprop 2 {3 char name [256];/** Use cudagetdeviceproperties () to obtain the device attribute. Use cudagetdevicecount () to obtain the number of devices. Use cudacho

Use Cuda to accelerate convolutional Neural Networks-Handwritten digits recognition accuracy of 99.7%

Source code and running result Cuda: https://github.com/zhxfl/cuCNN-I C language version reference from: http://eric-yuan.me/ The accuracy of the mnist library for famous handwritten numbers recognition is 99.7%. In a few minutes, CNN training can reach 99.60% accuracy. Parameter configuration The network configuration uses config.txt for configuration # comments between them, and the code will be filtered out automatically. For other formats, refer

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