cuda in python

Just like a freshman C ++ or a sophomore compilation, I also wrote Cuda for a few months. Then, think about it, and I should start to explain it, I learned something at the lower layer of Cuda and may know more about heterogeneous programming. 1 OverviewFull name of opencl: Development Computing language, parallelProgramThe development standard, used in combination with any heterogeneous platform-includin

exchange of ideas. In fact, when learning engineering, there is a little trick, that is to find the rules. There are established rules, and that is the theorem and the definition. If you can find a new rule, it is a new discovery that can be written paper. When we meet new things, we'd better find the shadow in our own thinking and find the same rules. So that you can learn new things very well. However, often learn engineering thinking more regular, in addition to the usual reading of the engi

The head hurts with the pit.Process:1. Browse Web download OpenCV source Opencv3.1.0 zip2.unzip Decompression3. Install a stack of pre-requisite environments:sudo apt-get install xx xx xxsudo apt-get install build-essentialsudo apt-get install CMake git libgtk2. 0-dev pkg-config libavcodec-dev libavformat-dev libswscale-devsudo apt-get Install Python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-de

The Cuda 4.0 version is very different from the previous Cuda 2.3 version. At least, the Cubin format is changed to the ELF File and is no longer the decuda input file. I tested my graphics card with a GPU-Z, gt218 supports opencl, Cuda, directcompute4.1. All right, everything is installed, including vs2008. Below is a simple

Installation Process of CUDA (including GPU driver) in Ubuntu OS: Ubuntu 12.04 (amd64) Basic tool set Aptitude install binutils ia32-libs gcc make automake autoconf libtool g ++-4.6 gawk gfortran freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev-y If it is a server system without a graphical interface, the lightdm GUI manager step is not stopped... This stuff shouldn't be available on the serve

Original link1. OverviewThe data in the texture memory is stored in memory in the form of one-, two-, or three-dimensional arrays, which can be accessed through the cache and can be declared larger than the constant memory.The operation to access the texture memory in kernel is called texture pickup (texture fetching). The operation of associating data in memory with a texture reference frame is called binding the data to the texture (texture binding).There are two types of data that can be boun

Today, I thought about the Cuda zero-memory copy problem. I felt that it would be useful in the program to be designed, so I checked the relevant information. The following are some helpful links: Zero copy usage in Cuda -- for two-dimensional pointers Zero-copy usage in Cuda -- for one-dimensional pointers Cuda zero

Tags: code stat leave Tor dia pool ack drivers what to doBy TensorFlow 1.8, Ubuntu 16.04, Cuda 9.0, nvidia-390 tortured for 5 days, finally on the pit, leaving a guide for the benefit of posterity.1. Find out the dependencies first:TensorFlow 1.8 relies on Cuda 9.0,cuda 9.0 dependent nvidia-390.2. Pit:Only nvidia-384,nvidia-390 newness is not supported in Ubuntu

Http://www.cnblogs.com/gaowengang/p/6068788.htmlThis 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 b

In recent days want to c,cuda,mpi mixed compiled Linux to rewrite the dynamic link library libtest.so, after two or three days of the first large variety of search information, turn over a variety of makefile files, all kinds of reading blog, finally. Finally, I'm crying for joy. 1. First understand how the CPU side to encapsulate code into a dynamic link library Reprint Address: http://www.cnblogs.com/huangxinzhen/p/4047051.html Of course, a lot of r

1. For more information, see Https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#runfile-nouveau2. Remote SSH access to the Ubuntu host needs to set a static IP address.3. Install the official guide to determine that the installed Cuda version is compatible with the Ubuntu system version and is compatible with the GCC version4. Turn off the grap

CUDA, cudagpuMemory The level of kernel performance cannot be simply explained from the execution of warp. As mentioned in the previous blog post, setting the block dimension to half the warp Size will reduce the load efficiency, which cannot be explained by the scheduling or parallelism of warp. The root cause is the poor way to get global memory. As we all know, memory operations play a very important role in efficiency-oriented languages. Low-laten

I just read something about Cuda and planned to write a program. As a result, I encountered a bunch of problems. The first problem is the array transfer problem on the host and device, which is a bit dizzy. After reading some information, I will summarize it as follows. 1: How did the problem come about? One-dimensional array, two-dimensional array, and three-dimensional array are used on device. For one-dimensional arrays, cudamalloc and cudamemcpy a

This section describes the main concepts of the Cuda programming model. 2.1.kernels (kernel function) Cuda C extends the C language and allows programmers to define C functions, called kernels ). Execute n times in N Cuda threads in parallel. Use the _ global _ specifier to declare a core function, call and use For example, add two vectors, add a and B, and stor

Http://blog.csdn.net/yutianzuijin/article/details/8147912category: Programming Language 2521 people read comments (0) Add to favorites report cudagpu Recently, I first tried Cuda programming. As a newbie, I encountered various problems and spent a lot of time solving these incredible problems. In order to avoid people from repeating the same mistakes, we will summarize the problems we have encountered as follows. (1). cudamalloc The first time I used

Cuda Basic Concept Cuda grid limits 1.2CPU and GPU design differences 2.1cuda-thread2.2cuda-memory (storage) and Bank-conflict2.3cuda matrix multiplication 3.1 Global storage bandwidth and consolidated access Memory (DRAM) bandwidth and memory coalesce3.2 convolution 3.3 analysis of the multiplexed 4.1Reduction model of convolution multiplication optimization 4.2 CUDA