Once you have [Anaconda](https://www.anaconda.com/distribution/#download-section) installed, here are the instructions.
If you want to compile with CUDA support, install
-- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 9.2 or above
+- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 10.2 or above
- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v7 or above
- [Compiler](https://gist.github.com/ax3l/9489132) compatible with CUDA
Note: You could refer to the [cuDNN Support Matrix](https://docs.nvidia.com/deeplearning/cudnn/pdf/cuDNN-Support-Matrix.pdf) for cuDNN versions with the various supported CUDA, CUDA driver and NVIDIA hardwares
# nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04
# nvidia/cuda:10.2-cudnn8-devel-ubuntu18.04
# nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
-# nvidia/cuda:9.2-cudnn7-devel-ubuntu18.04
#
# Available MAGMA_CUDA_VERSION options (for GPU/CUDA builds):
# magma-cuda112
# magma-cuda111
# magma-cuda102
# magma-cuda101
-# magma-cuda92
#
# Available TORCH_CUDA_ARCH_LIST_VAR options (for GPU/CUDA builds):
# "3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0;8.6" for CUDA 11.2/11.1
# "3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0" for CUDA 11.0
# "3.7+PTX;5.0;6.0;6.1;7.0;7.5" for CUDA 10.2/10.1
-# "3.7+PTX;5.0;6.0;6.1;7.0" for CUDA 9.2
#
# Build image with CPU or GPU support with the following command:
# nvidia-docker build -t ${CONTAINER_TAG}
REM 2.5.3 (CUDA 10.1 10.2 11.0) x (Debug Release)
REM 2.5.2 (CUDA 9.2 10.0 10.1 10.2) x (Debug Release)
REM 2.5.1 (CUDA 9.2 10.0 10.1 10.2) x (Debug Release)
- REM 2.5.0 (CUDA 9.0 9.2 10.0 10.1) x (Debug Release)
- REM 2.4.0 (CUDA 8.0 9.2) x (Release)
- set CUDA_PREFIX=cuda101
+ set CUDA_PREFIX=cuda102
set CONFIG=release
curl -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_PREFIX%_%CONFIG%.7z -o magma.7z
7z x -aoa magma.7z -omagma