No language package, dependent and environmental management: Python, R, Ruby, Lua, Scala, Java, JavaScript, C / C ++, Fortran, Conda is an open source package management system and environmental management system for installation multiple versions. The package and its dependencies and it is easy to switch between them. It applies to Linux, OS X, and Windows, which is created for Python programs, but can package and distribute any software.
I am a discrete graphics card that supports CUDA installation. The calculation is 6.1

Select the CUDA version for installation, then the installation process, double-click to open the display temporary decompressed directory, do not need to change, default.
Because there is no screenshot at the time of installation, the screenshot of 10.0 version is found online, thank youOriginal author。


Enter the NVIDIA installation process, I choose a custom installation method and give the VS to remove it, you can install it.
After the installation is complete, it is configured environment variables.

After completing, you can enter the NVCC -V test through the CMD.

https://developer.nvidia.com/cudnn
Select Download Download Cudnn, but here you need to register an account, and then you can download the page.
Because my CUDA version is 10.0, and the version of CUDNN is consistent with the CUDA version.
Download cuDNN v7.6.2[July22,2019],for CUDA 10.0
After download, decompress, copy the bin, clude, lib files in the CUDNN compressed package to the CUDA installation directory, overwrite the installation directly

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