dandanmylady · December 23, 2021 08:32 · Aug 26, 2021 · Jun 30, 2021 · Mar 29, 2021 · Mar 29, 2021
diff --git a/cuda-11.2_installation_on_Ubuntu-18.04 b/cuda-11.2_installation_on_Ubuntu-18.04
@@ -60,7 +60,7 @@ tar -xzvf ${CUDNN_TAR_FILE}
 
 
 # copy the following files into the cuda toolkit directory.
-sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.2/include
+sudo cp -P cuda/include/cudnn*.h /usr/local/cuda-11.2/include
 sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-11.2/lib64/
 sudo chmod a+r /usr/local/cuda-11.2/lib64/libcudnn*
 

diff --git a/cuda-11.2_installation_on_Ubuntu-18.04 b/cuda-11.2_installation_on_Ubuntu-18.04
@@ -52,12 +52,10 @@ echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH' >> ~/.
 source ~/.bashrc
 sudo ldconfig
 
-# install cuDNN v8.1
-# in order to download cuDNN you have to be regeistered here https://developer.nvidia.com/developer-program/signup
-# then download cuDNN v8.1 form https://developer.nvidia.com/cudnn
+# install cuDNN v8.2
 
-CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.1.1.33.tgz"
-wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.1.1.33/11.2_20210301/cudnn-11.2-linux-x64-v8.1.1.33.tgz
+CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.2.0.53.tgz"
+wget http://people.cs.uchicago.edu/~kauffman/nvidia/cudnn/cudnn-11.2-linux-x64-v8.2.0.53.tgz
 tar -xzvf ${CUDNN_TAR_FILE}
 
 

diff --git a/cuda-11.2_installation_on_Ubuntu-18.04 b/cuda-11.2_installation_on_Ubuntu-18.04
@@ -1,6 +1,11 @@
 #!/bin/bash
 ## This gist contains instructions about cuda v11.2 and cudnn 8.1 installation in Ubuntu 18.04 for PyTorch
 
+#############################################################################################
+##### forked by : https://gist.github.com/Mahedi-61/2a2f1579d4271717d421065168ce6a73 ########
+#############################################################################################
+
+
 ### steps ####
 # verify the system has a cuda-capable gpu
 # download and install the nvidia cuda toolkit and cudnn

diff --git a/cuda-11.2_installation_on_Ubuntu-18.04 b/cuda-11.2_installation_on_Ubuntu-18.04
@@ -51,8 +51,8 @@ sudo ldconfig
 # in order to download cuDNN you have to be regeistered here https://developer.nvidia.com/developer-program/signup
 # then download cuDNN v8.1 form https://developer.nvidia.com/cudnn
 
-CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.1.0.77.tgz"
-wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.1.0.77/11.2_20210127/cudnn-11.2-linux-x64-v8.1.0.77.tgz
+CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.1.1.33.tgz"
+wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.1.1.33/11.2_20210301/cudnn-11.2-linux-x64-v8.1.1.33.tgz
 tar -xzvf ${CUDNN_TAR_FILE}
 
 

diff --git a/cuda-11.2_installation_on_Ubuntu-18.04 b/cuda-11.2_installation_on_Ubuntu-18.04
@@ -67,4 +67,4 @@ nvcc -V
 
 # install PyTorch (an open source machine learning framework)
 
-sudo pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
+pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
diff --git a/cuda-11.2_installation_on_Ubuntu-18.04 b/cuda-11.2_installation_on_Ubuntu-18.04
@@ -0,0 +1,70 @@
+#!/bin/bash
+## This gist contains instructions about cuda v11.2 and cudnn 8.1 installation in Ubuntu 18.04 for PyTorch
+
+### steps ####
+# verify the system has a cuda-capable gpu
+# download and install the nvidia cuda toolkit and cudnn
+# setup environmental variables
+# verify the installation
+###
+
+### If you have previous installation remove it first. 
+sudo apt-get purge nvidia*
+sudo apt remove nvidia-*
+sudo rm /etc/apt/sources.list.d/cuda*
+sudo apt-get autoremove && sudo apt-get autoclean
+sudo rm -rf /usr/local/cuda*
+
+
+### to verify your gpu is cuda enable check
+lspci | grep -i nvidia
+
+### gcc compiler is required for development using the cuda toolkit. to verify the version of gcc install enter
+gcc --version
+
+# system update
+sudo apt-get update
+sudo apt-get upgrade
+
+
+# install other import packages
+sudo apt-get install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev
+
+
+# first get the PPA repository driver
+sudo add-apt-repository ppa:graphics-drivers/ppa
+sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
+echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda.list
+sudo apt-get update
+
+ # installing CUDA-11.2
+sudo apt-get -o Dpkg::Options::="--force-overwrite" install cuda-11-2 cuda-drivers
+
+
+# setup your paths
+echo 'export PATH=/usr/local/cuda-11.2/bin:$PATH' >> ~/.bashrc
+echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
+source ~/.bashrc
+sudo ldconfig
+
+# install cuDNN v8.1
+# in order to download cuDNN you have to be regeistered here https://developer.nvidia.com/developer-program/signup
+# then download cuDNN v8.1 form https://developer.nvidia.com/cudnn
+
+CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.1.0.77.tgz"
+wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.1.0.77/11.2_20210127/cudnn-11.2-linux-x64-v8.1.0.77.tgz
+tar -xzvf ${CUDNN_TAR_FILE}
+
+
+# copy the following files into the cuda toolkit directory.
+sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.2/include
+sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-11.2/lib64/
+sudo chmod a+r /usr/local/cuda-11.2/lib64/libcudnn*
+
+# Finally, to verify the installation, check
+nvidia-smi
+nvcc -V
+
+# install PyTorch (an open source machine learning framework)
+
+sudo pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
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