1 Nvidia Driver

The RTX30-series has the Ampere architecture, therefore it will only work with Driver 450+ versions only.

图片.png
source: https://docs.nvidia.com/deploy/cuda-compatibility/index.html

2. Nvidia CUDA

Since we are now restricted by the driver version, we can only go for CUDA 11.0+.

图片.png
source: https://docs.nvidia.com/deploy/cuda-compatibility/index.html

3. Nvidia cuDnn

With CUDA 11.0+, we can only use cuDnn 8.0+.

图片.png
source: https://docs.nvidia.com/deeplearning/cudnn/support-matrix/index.html

4 Pytorch

Pytorch actually released a new stable version 1.7.0 one day before I started writing this article, and it is now officially supporting CUDA 11