agp gpu

functionChangeshader ():void88 {_shader.data.exposure.value = [0.5-math.random ()];90 91graphics.clear (); Graphics.beginshaderfill (_shader); Graphics.drawrect (0,0,300,300); } } }Pixel Bender Code (OPENGLTEST.PBK):kernel Exposurefilternamespace:"TB"; Vendor:"Common"; Version:1; Description:"Picture Exposure";>{parameterfloatExposureMinValue:float(-0.5); MaxValue:float(0.5); DefaultValue:float(0.0); Description:"Exposure"; >; Input image4 src;

Install theano and configure GPU in Win10, win10theano I. Software and Environment (1) installation date; (2) Raw Materials VS2013, cuda-8.0 (it is best to download cuda7.5, the current theano-0.8.2 for cuda-8 support is not very good), Anaconda3-4.2.0 (64-bit ); (3) The environment is win10. Ii. Installation Steps (1) install VS2013. There is nothing to say. After downloading the 64-bit version, you just need to take the next step. Remember to insta

Recently started a GTX 1070 notebook, preface want to Win10 on the GPU run model, so there is the next installation GPU version of the bumpy course of mxnet, after multiple experiments finally fixed python and R installation Mxnet, the main points are recorded as follows:I mainly refer to these 2 blog posts:https://my.oschina.net/qinhui99/blog/845249http://blog.csdn.net/u010414386/article/details/533041771.

Installing Theano Configuring the GPU "Original" Liu_longpoReprint Please specify the source "CSDN" http://blog.csdn.net/llp1992Installing TheanoThis post is an experience and I hope to help those who have struggled with me.Already said, non-root users, so can not use sudo, only this series of trouble.To install Theano, you need some dependencies, and you can refer to the blog for details:Deeplearning (i) Best en

Respect for the wisdom of others, welcome reprint, please indicate the author's heart if Transparent address http://www.cnblogs.com/ubanck/p/4110618.htmlIn the previous blog, roughly explained the principle of 3D rendering, that is, from a simple model to the process of rendering to the screen! It mentions the important coordinate transformation way, said not clear! Today to talk about the implementation of the shader languageHardware, the GPU has a v

Tags: blog from the This COM update inter for pass ALS1. Show current GPU usageNvidia-smi2. Usage of the periodic input GPUUse the watch command to periodically output GPU usage$ Whatis WatchWatch (1)-Execute a program periodically, showing output fullscreen$watchUsage:Watch [Options] CommandOptions:-B,--beep beep if command has a Non-zero exit-C,--color interpret ANSI color sequences-D,--differences[=Highl

Statement This document is only for learning and exchange, please do not use for other commercial purposesAuthor: Chaoyang _tonyE-mail:linzhaolover@163.comCreate date:2018 Year April 8 20:29:38Last change:2018 year April 8 20:29:50Reprint please indicate the source: Http://blog.csdn.net/linzhaolover Summary A recent need to build an environment requires the physical machine's GPU card to be mapped to the KVM for use. That is, passthrough on the Inter

1. Display current GPU usage Nvidia has a Nvidia-smi command-line tool that displays video memory usage: $ nvidia-smi1 1 Output:2. Periodic output GPU usage But sometimes we want to not only know the GPU usage at that fixed moment, we want to keep it going, we want to output periodically, like updating the display every 10s. At this point, you need to use the Wa

Change at a glance: Last month, the 9-year long stay in the beta version of the graphics card first identification tool Gpu-z released the first official version of v1.9.0, during a total of 89 versions of the evolution. Today, the v1.10.0 release adds support for new cards such as AMD RX470460, Nvidia TITAN X, and so on, in the near period. Functional changes: -Increase support for Radeon Rx 470, RX 460 -Increased support for Nvidia GTX TITAN X

It is best to apply thermal grease between the heatsink and the CPU when installing the cooling fan. The role of silicone grease is not only the heat produced by the CPU quickly and evenly passed to the heat sink, in many cases, silicone grease can also increase the heat sink not too flat under the surface of the heat contact with the CPU. and silicone grease has a certain viscosity, in the fixed heat sink metal shrapnel slightly aging loose, you can to a certain extent so that the heatsink wil

. As long as there is this concept, the purpose of my article is achieved. Front of the "Cuda Hardware Implementation Analysis (i)------Camp-----GPU Revolution" has explained the thread in the cuda of the concrete running process. Let's look at some of the provisions in the CUDA hardware implementation. This is more reasonable, army camp, it should be promulgated rules system, only understand the rules of CUDA system, can really put the various thread

has been in Linux under the Theano,gpu with a good match. Need to work under Windows last week, so toss for a week, just inexplicably to match the GPU.First on a Theano successful use of the GPU screenshot Here is my experience in configuring Theano:It's basically two steps away:1. Installation Theano2. Installation CudaNote that under Win7 64, Python and Cuda should be unified, either with 32-bit or 64-

Before the beginning of the article, I would like to take this garden to sincerely apologize to my dearest Mi bao, I remember my serious mistakes, as a training, all my friends testify, I will be self-restraint, repent. I'm fully aware of the GPU's massive throughput and strong floating-point computing capabilities, will be very high to improve the program performance, but also to give full play to the value of the graphics card, GPU as a computer 2 p

The author runs TensorFlow program on Ubuntu, midway using the Win+c key to end the program, but the GPU's video memory is not released, has been in the occupied state.Using commandsWatch-n 1 Nvidia-smiShows the followingTwo GPU programs are in execution, in fact, gpu:0 has been stopped by the author, but the GPU is not released, the process continues, so only th

With the assessment in the previous section, I am sure you have been impressed by the use of GPU hardware acceleration in Silverlight to improve performance. Silverlight game development, we need to use a variety of forms of animation and related graphics processing skills, at this time if the full and reasonable use of GPU hardware acceleration function, with the most cost-effective function implementation

Nowadays, AI is getting more and more attention, and this is largely attributed to the rapid development of deep learning. The successful cross-border between AI and different industries has a profound impact on traditional industries.Recently, I also began to keep in touch with deep learning, before I read a lot of articles, the history of deep learning and related theoretical knowledge also have a general understanding.But as the saying goes: The end of the paper is shallow, it is known that t

The method of referring to the great God: http://www.th7.cn/system/win/201603/155182.shtmlFirst step: Need to install CUDA, vs2013;cuda default path, note Cuda version and GPU to matchThe second step:. Download CUDNN, build a local folder under the Matconvnet folder, and put the CUDNN in (I changed the filename called CUDNN)Step three: Open vl_compilenn.m, Run, wait for compilation to finishThe fourth step is to copy the Cudnn64_4.dll under the bin to

D3d9 GPU HacksI ' ve been trying to catch up what hacks GPU vendors has exposed in Direct3D9, and turns out there's a lot of them!If you know more hacks or more details, please let me know in the comments!Most hacks is exposed as custom ("FOURCC") formats. So-check for the CheckDeviceFormat . Here's the list (Usage column codes:ds=depthstencil, Rt=rendertarget; Resource column codes:tex=texture, Surf=surfac

The most important Optimization of body rendering is to reduce GPU sampling. Testing the filling rate of the GPU material can guide our work. Do you want to know why the GPU can only reach 12 FPS in 800*600 environments? This depends on the number of GPU samples per second. I wrote a simple OSGProgramTo test the numb

of dll ). 2. next, the application delegates the NiD3DShader initialization work to NiShaderLibrary for processing. NiShaderLibrary first loads all shader text files through nid3dxjavastloader, and uses nid3dxjavastparser to parse the text to generate the nid3dxjavastfile object, at the same time, NiD3DXEffectLoader is responsible for compiling shader code into a binary form GPU program. 3. NiD3DXEffectTechnique is responsible for generating the NiD3