could not fine compatible graphic hardware: visual studio integration failed

问题:Cuda安装中提示could not fine compatible graphic hardware(截图如下),并最终安装失败,查看失败项是:visual studio integration failed。

解决方案:清理cuda环境,安装基础网卡驱动再安装cuda。

I had the same problem and finally I could find a solution. Visual Studio integration failed every time. I tried all possible combinations and nothing worked (Visualstudio 2010, VisualStudio 2017, Cuda 9.1.85, 9.0, 8.0, 7.5). I also tried reinstall windows 10 in all possible ways. Fortunately the method sugested by @oregonduckman and orangesherbet0 worked for me (https://devtalk.nvidia.com/default/topic/1033111/cuda-setup-and-installation/cuda-9-1-cannot-install-due-to-failed-visual-studio-integration/):

Step 1: Install the standard VGA driver:
1. Bring up the Windows Device Manager. You can do that my right-clicking on the Start button and then select Device Manager.
2. Expand the "Display Adapter" list, right-click on the GeForce card and then select "Update Driver Software".
3. Click "Browse my computer for driver software".
4. Then click the "Let me pick from a list of device drivers on my computer".
5. Uncheck the "Show compatible hardware" option.
6. Under the "Manufacture" scroll to the top and select the "(Standard display type)" and then click "Next". If you are running multiple GPUs then repeat steps #2 - #6 for each GPU.
7. Restart Windows. This will basically load the standard VGA driver.

Step 2: Delete all Cuda reference:
1. In Windows Services, stop all nvidia services
2. Delete all nvidia files from C:\ProgramData, C:\Program Files, C:\Program Files(x86). 
3. Proceed with cuda installation.

Step 3: Install correct version Nvidia graphic dirver, if not, tensorflow will not find cuda capatible graphic device and lead to an error "ImportError: Could not find 'nvcuda.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable".

eg. I must install GF 1060 MaxQ dirver.

could not fine compatible graphic hardware其它可能导致的原因是cuda中驱动的版本低于机器已安装版本,此时解决方案是安装cuda时自定义不安装驱动。还有一些歪招是禁用非Nvidia显卡。

 

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