Gosar's Ubuntu Installation Procedure

Gosar's Ubuntu Installation Procedure
- Contents
Before installing Ubuntu
- Download Ubuntu
- Make a bootable USB
Installing Ubuntu
- Follow Tutorial
After installing Ubuntu
Clayton's Ubuntu Installation Procedure

Before installing Ubuntu

Download Ubuntu

Make a bootable USB

For windows,
- Download Rufus
- Use Rufus to burn
For Linux,
- Follow this Tutorial

Installing Ubuntu

After installing Ubuntu

Installing CUDA 10

Steps

Cuda

Use deb (network) to Download.

Or run thefollowing commands,






wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo add-apt-repository "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
sudo apt-get update
sudo apt-get -y install cuda

Reboot and then check nvidia-smi

Setting Cuda path on .bashrc

Open .bashrc
```
nano ~/.bashrc
```

Add these lines to .bashrc file

export CUDAHOME=/usr/local/cuda-11.1
export PATH=${CUDAHOME}/bin:${CUDAHOME}/NsightCompute-2019.3${PATH:+:${PATH}}
export LD_LIBRARY_PATH=${CUDAHOME}/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

Change 11.1 to the latest version
```
sudo sh ~/.bashrc
```

Installing CuDNN

CuDNN

Reference Document
Download cudNN
- cuDNN Runtime Library for Ubuntu18.04 (Deb)
- cuDNN Developer Library for Ubuntu18.04 (Deb)
- cuDNN Code Samples and User Guide for Ubuntu18.04 (Deb)
Installing from a Debian File
- Navigate to your <cudnnpath> directory containing cuDNN Debian file.
- Install the runtime library, for example:
  sudo dpkg -i libcudnn8_8.0.4.30-1+cuda11.1_amd64.deb
- Install the developer library, for example:
  sudo dpkg -i libcudnn8-dev_8.0.4.30-1+cuda11.1_amd64.deb
- Install the code samples and the cuDNN Library User Guide, for example:
  sudo dpkg -i libcudnn8-samples_8.0.4.30-1+cuda11.1_amd64.deb
Verifying The cuDNN Install On Linux
- To verify that cuDNN is installed and is running properly, compile the mnistCUDNN sample located in the /usr/src/cudnn_samples_v8 directory in the debian file.
```
cp -r /usr/src/cudnn_samples_v8/ $HOME
cd  $HOME/cudnn_samples_v8/mnistCUDNN
make clean && make
./mnistCUDNN
```
- If cuDNN is properly installed and running on your Linux system, you will see a message similar to the following: Test passed!
- Run sudo apt install nvidia-cuda-toolkit -y
- Check nvcc --version

Setup

Install Pyenv Procedure

sudo apt-get install -y make build-essential libssl-dev zlib1g-dev libbz2-dev \
libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev libncursesw5-dev \
xz-utils tk-dev libffi-dev liblzma-dev python-openssl git

git clone https://github.com/pyenv/pyenv.git ~/.pyenv
echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc
echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc
echo -e 'if command -v pyenv 1>/dev/null 2>&1; then\n  eval "$(pyenv init -)"\nfi' >> ~/.bashrc
exec "$SHELL"
pyenv install 3.7.3
pyenv global 3.7.3
python --version

Virtual Environment Setup

Install virtualenv

pip install virtualenv

Create a new virtual environment

In this example, the name of virtual environment is set as "venv" using the below command, you can use any other name.

virtualenv venv

Activate your virtual environment

source venv/bin/activate

Install packages as usual

pip install <dependencies go here>

Export your dependencies

pip freeze > requirements.txt

Import your dependencies

pip install -r requirements.txt

Check Cuda using torch

pip install torch torchvision





import torch
torch.cuda.is_available()
print(torch.cuda.get_device_name(0))
print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB')
print('Cached:   ', round(torch.cuda.memory_cached(0)/1024**3,1), 'GB')

Pip install (My usual packages)

pip install torch torchvision Cython opencv-python

Important Sofwares

Creating Simulation environment - Unreal Engine and NDDS

VLC

sudo snap install vlc

Pycharm

sudo snap install pycharm-community --classic

VS Code

sudo snap install code --classic

Increase (max_user_watches) limit for VS Code
(ref)
- Check current limit
  cat /proc/sys/fs/inotify/max_user_watches
- Edit
  sudo nano /etc/sysctl.conf
  In the end, add this line
```
fs.inotify.max_user_watches=524288
```
- Save changes
  sudo sysctl -p
FiraCode

Better Ubuntu

Minimize on Click

Enable ‘Minimize on Click’ for the Ubuntu Dock
gsettings set org.gnome.shell.extensions.dash-to-dock click-action 'minimize'

gnome-tweaks

sudo apt-get install gnome-tweaks

Terminator

Add Terminator Repository:

sudo add-apt-repository ppa:gnome-terminator

Open Software & Updates, Other Software tab.
find the PPA definition that contains "gnome-terminator"
select it and click Edit
For ubuntu 18.xx: change the Distribution field from bionic to xenial
For ubuntu 20.xx: change the Distribution field from bionic to focal

Update sources.list

sudo apt-get update

Install Terminator

sudo apt-get install terminator

Keyboard Language

(ref)

Run the following command in the terminal and then reboot

sudo apt install -y ibus-mozc

Open Region & Language
Click on Manage Installed Languages
Click on Install
Close
Click on + sign
Click on Japanese
Click on Japanese (Mozc) then add
Customise key bindings

Detectron2

pytorch

pip install opencv-python
pip install torch==1.7.1 torchvision==0.8.2
pip install detectron2-0.5

Bash

How to update bash commands

Open .bashrc
```
nano ~/.bashrc
```

Add this lines to .bashrc file

export dataset=/home/jitesh/detectron_tutorial/dataset
export dl=/home/jitesh/Downloads

Update bashrc
```
sudo sh ~/.bashrc
```

bashrc

bash_aliases

Not Important

Installing drivers

Method 0 (uninstall)

yes| sudo apt-get purge nvidia*
sudo apt-get autoremove

sudo apt-get remove --purge '^nvidia-.*'
sudo apt-get install ubuntu-desktop

purge nvidia

Method 1

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
ubuntu-drivers devices

Using the above command, check the recommended Nvidia-driver (in my case, it was nvidia-driver-440)
Open softare & updates program from you application menu. Click the additional drivers tab.
Select nvidia-driver that you want to install.

Then click on Apply Changes and then close.
Install from the popup window.
If you couldn't install from the popup window, then run the command, sudo apt install nvidia-440

If a window asking for bios password popsup, then create an 8 character password and use it after reboot when a blue screen comes. Choose the second option on the blue screen and enable the key. (I don' remeber exactly that what options are there.)

Method 2 (without GUI)

Method 3

Download Nvidia Driver

To install all dependencies

sudo apt-get install build-essential gcc-multilib dkms

Creat Blacklist for Nouveau Driver
Create a file at /etc/modprobe.d/blacklist-nouveau.conf with the following contents:
```
blacklist nouveau
options nouveau modeset=0
```
- for Ubuntu 14.04 LTS, reboot the computer;
- for Ubuntu 16.04 LTS, excute sudo update-initramfs -u and reboot the computer

For Ubuntu / Fedora / CentOS, after computer restarts, excute

sudo systemctl stop lightdm

(or use gdm or kdm instead of lightdm)

cd ~/Downloads
chmod +x NVIDIA-Linux-x86_64-440.64.run
sudo ./NVIDIA-Linux-x86_64-440.64.run --dkms -s

Check the installation by command, nvidia-smi

Links

https://medium.com/@antonioszeto/how-to-install-nvidia-driver-on-ubuntu-18-04-7b464bab43e6

xserver

It's apparently a better solution to run X11 as root. The one-line fix is to add this line to /etc/X11/Xwrapper.config:

needs_root_rights = yes

You can install xserver-xorg-core appropriate for your system by just typing

sudo apt-get install xserver-xorg-legacy
sudo apt-get install xserver-xorg-core

If you are still having the problem please add the output of :

apt-cache madison xserver-common

grub2

sudo gedit /etc/default/grub

Add nouveau.modeset=0 to the end of the linux line - press F10 to boot.

sudo update-grub2

Clayton's Ubuntu Installation Procedure