Ubuntu EnvironmentNew Ubuntu 18.04 install on x86_64 workstationInstall Ubuntu 18.04 Alongside With Windows 10 in Dual BootNew Ubuntu 18.04 install on x86_64 MSI GS65 laptopInstall Ubuntu 18.04 Alongside With Windows 10 in Dual BootInstalling system libraries and toolsUpdate UbuntuInstall the NVIDIA 440 driverCheck CPU temp with Psensor GUI toolDevelopment ToolsNvidia LibrariesCUDACuDNNVideo CodecOptiX - Ray Tracing EngineInstall Third Party LibrariesQt 5.15.0Install DatasetsInstall Neural Network modelsCLion buildCheckout the sourceCreate the CLion project
$ sudo apt-get update
$ sudo apt-get full-upgrade
$ sudo ubuntu-drivers autoinstall
# Disable auto resize of windows at top
$ gsettings set org.gnome.mutter edge-tiling false
Get the latest supported drivers from the Ubuntu
repository
$ sudo add-apt-repository ppa:graphics-drivers/ppa
$ sudo apt update
Open Softare & Updates
program from the application menu. Click the Additional Drivers
tab. You can see what driver is being used for NVIDIA and a list of proprietary drivers.
As you can see nvidia-driver-440
is available for the GeForce GTX 1080 Ti
card. Select nvidia-driver-440
and click Apply Changes
button to install the driver. Reboot the system to apply the changes.
After reboot, use the follow command to check the driver version
$ nvidia-smi
Install the needed tools
$ sudo apt install lm-sensors hddtemp
Start the detection of your hardware sensors:
$ sudo sensors-detect
Check the operations
$ sensors
Install Psensor
$ sudo apt install psensor
CLion IDE - ubuntu software app
Google Chrome Web Browser
Go to https://www.google.com/chrome. Click the Download Chrome
button. Select the first option (64 bit .deb for Debian/Ubuntu), click Accept and Install
to download the installer google-chrome-stable_current_amd64.deb
. Double click on the install file to install.
CMake - ubuntu software app
KDiff3 (File And Directory Comparison And Merge Tool) - ubuntu software app
Doxygen
$ sudo apt-get install doxygen
$ sudo apt-get install doxygen-gui
$ sudo $HOME/Projects/pdp/scripts/add-doxygenMenuItem.sh
Typora
$ sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys BA300B7755AFCFAE
$ sudo add-apt-repository 'deb https://typora.io/linux ./'
$ sudo apt-get update
$ sudo apt-get install typora
Subversion - command line (svn)
$ sudo apt-get install subversion
SmartSVN
smartsvn-linux-11_0_0.tar.gz
from https://www.smartsvn.com/downloads/smartsvn/smartsvn-linux-11_0_0.tar.gz$HOME/Developer/smartsvn
$ cd $HOME/Developer/smartsvn/bin
$ sudo ./add-menuitem.sh
7Zip
$ sudo apt install p7zip-full p7zip-rar
Build essential tools
$ sudo apt-get install build-essential g++
libjpeg
$ sudo apt-get install libjpeg-dev
libturbojpeg
$ sudo apt-get install libturbojpeg-dev
libz
$ sudo apt-get install libz-dev
liblzma
$ sudo apt-get install liblzma-dev
EGL
$ sudo apt-get install libegl1-mesa
$ sudo apt-get install libegl1-mesa-dev
GLES
$ sudo apt-get install libgles2-mesa
$ sudo apt-get install libgles2-mesa-dev
$ sudo apt-get install freeglut3-dev
X11 development
sudo apt-get install xorg-dev
Cleanup
$ sudo apt-get update
$ sudo apt autoremove
Download the CUDA 10.2
Ubuntu
installer
$ cd ~/Developer/Projects
$ mkdir installers
$ cd installers
$ wget http://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda_10.2.89_440.33.01_linux.run
Install CUDA 10.2
using the installer
x$ sudo sh cuda_10.2.89_440.33.01_linux.run
Choose "Continue" when prompted about the existing package manager
Type "accept" when prompted for acceptance of the EULA
Turn off the Driver install on the following options screen (440 driver installed above)
CUDA Installer
- [ ] Driver
[ ] 440.33.01
+ [X] CUDA Toolkit 10.2
[X] CUDA Samples 10.2
[X] CUDA Demo 10.2
[X] CUDA Documentation 10.2
Then choose "Install"
Add CUDA 10
to the development search path by adding the following lines to .bashrc
$ nano .bashrc
# NVIDIA CUDA Toolkit
if [ -d "/usr/local/cuda-10.2/bin/" ]; then
export PATH=/usr/local/cuda-10.2/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
fi
$ source ~/.bashrc
Check NVIDIA CUDA
Compiler
$ nvcc --version
Download the cuDNN
pre-built libraries for Linux, CUDA version 10.2
cudnn-10.2-linux-x64-v7.6.5.32.tgz
from https://developer.nvidia.com/rdp/cudnn-download using the cuDNN Library for Linux link. Move cudnn-10.2-linux-x64-v7.6.5.32.tgz
to $HOME/Developer/Projects/installers
Add the header files and pre-built libraries to the CUDA
install
$ cd $HOME/Developer/Projects/installers
$ tar -xvf cudnn-10.2-linux-x64-v7.6.5.32.tgz
$ cd cuda
$ sudo cp -P include/* /usr/local/cuda/include/
$ sudo cp -P lib64/* /usr/local/cuda/lib64/
$ cd ..
$ sudo rm -rf cuda
Download the Video Codec SDK 9.1
pre-built libraries for Linux, Video_Codec_SDK_9.1.23.zip
from https://developer.nvidia.com/nvidia-video-codec-sdk/download to $HOME/Developer/Projects/installers
and unzip to Video_Codec_SDK_9.1.23
Add the header files and pre-built libraries to the CUDA
install
$ cd $HOME/Developer/Projects/installers
$ sudo cp include/* /usr/local/cuda/include/
$ sudo cp Lib/linux/stubs/x86_64/* /usr/local/cuda/lib64/
Download the OptiX SDK 7.0
pre-built libraries for Linux, NVIDIA-OptiX-SDK-7.0.0-linux64.sh
from https://developer.nvidia.com/designworks/optix/download to $HOME/Developer/Projects
Install OptiX SDK 7.0
using the installer
$ cd $HOME/Developer/Projects
$ sh NVIDIA-OptiX-SDK-7.0.0-linux64.sh
$ mv NVIDIA-OptiX-SDK-7.0.0-linux64.sh installers/.
$ mv NVIDIA-OptiX-SDK-7.0.0-linux64 NVIDIA-OptiX-7.0.0
Download the following third party libraries for Ubuntu 18.04
from the BAP
development website at Third party libraries downloads (Will need your username
and password
to access the site)
xboost 1.73.0
glfw 3.3.2
libpng 1.6.37
itk 5.1.0
pdp 2.6.4
rnifti 1.1.0
sqlite 3.32.1
Move the downloaded files to $HOME/Developer/Projects
directory and and extract with the 7-Zip
Extract Here
command from the file browser.
Download the latest Qt unified windows installer from https://www.qt.io/download-qt-installer
Run the unified installer using open source user login. You will need to register as a QT Open Source user at the Qt website.
Select $HOME/Developer/Projects/QT
as the install directory
Select Qt 5.15.0
packages Desktop gcc 64-bit
and QtCharts
and run install
Create symbolic link for install directory
$ cd ~/Developer/Projects
$ ln -s ~/Developer/Projects/QT/5.15.0/gcc_64 qt-5.15.0
Download the following Datasets for the BAP
development website at Data sets (Will need your username
and password
to access the site)
BRATS PBT voxel classification
MNIST hand written numbers
Move the downloaded files to $HOME/data/ImageData
directory and and extract with the 7-Zip
Extract Here
command from the file browser.
Download the following models for the BAP
development website at Models (Will need your username
and password
to access the site)
BRATS PBT voxel classification
MNIST hand written numbers
Move the downloaded files to $HOME/networks
directory and and extract with the 7-Zip
Extract Here
command from the file browser.
Use either the SmartSVN
or TortoiseSVN
svn
clients to checkout the BAP
source code from svn://3.14.90.147/bap/trunk
to `$HOME/Projects/bap
(Will need your username
and password
to access this repository).
`$HOME/Projects/bap-clion