WLINUX/Install_new_linux.md at master · datlt4/WLINUX

Install

sudo apt-get update && sudo apt-get --assume-yes upgrade
sudo apt --assume-yes install cmake htop tree tmux build-essential gcc g++ make binutils software-properties-common git openssh-server openssh-client

Install the latest version of `cmake`

sudo apt remove --purge --auto-remove cmake

Download .sh file from this link

$ wget https://github.com/Kitware/CMake/releases/download/v3.18.3/cmake-3.18.3-Linux-x86_64.sh
$ sudo sh cmake-3.18.3-Linux-x86_64.sh --prefix=/opt/cmake

Add to the end of file .bashrc

$ export PATH=/opt/cmake/cmake-3.18.3-Linux-x86_64/bin:${PATH:+:${PATH}}

$ cmake --version

Install TeamVier

$ sudo apt update -y && sudo apt upgrade -y
$ wget https://download.teamviewer.com/download/linux/teamviewer_amd64.deb
$ sudo apt install ./teamviewer_amd64.deb

Start Teamviewer

$ /usr/bin/teamviewer

Get ID

$ sudo teamviewer --info print version, status, id

Install `Skype`

$ wget https://go.skype.com/skypeforlinux-64.deb
$ sudo apt install ./skypeforlinux-64.deb

Install `Visual Code`

[Access](https://code.visualstudio.com/download)

Install `Sublime Text`

sudo apt update
sudo apt install apt-transport-https ca-certificates curl software-properties-common -y
curl -fsSL https://download.sublimetext.com/sublimehq-pub.gpg | sudo apt-key add -
sudo add-apt-repository "deb https://download.sublimetext.com/ apt/stable/"
sudo apt update
sudo apt install sublime-text -y

Install `ibus-unikey`

$ sudo apt install ibus-unikey -y
$ sudo add-apt-repository -r ppa:ubuntu-vn/ppa
$ sudo apt update -q
$ ibus restart

[ERROR] Can't connect ibus

$ ibus-daemon &

Install Bluetooth 5 USB Dongle Orico BTA-608/ Ugreen CM390 Driver

Download .7z file and unzip (Google Drive).
After unzip:

cd 20201202_LINUX_BT_DRIVER/
sudo make install INTERFACE=usb
cd rtkbt-firmware/lib/firmware/
sudo cp rtl8761bu_fw /lib/firmware/rtl_bt/rtl8761b_fw.bin
sudo cp rtl8761bu_config /lib/firmware/rtl_bt/rtl8761b_config.bin
sudo reboot 0

Install Gnome Shell Extensions

$ sudo apt install gnome-shell-extensions

Install Firefox Add-on

Open up your Firefox Browser and visit firefox addons page for Gnome Shell Integration. Once ready, click + Add to Firefox.
Install Host Connector
```
 $ sudo apt install chrome-gnome-shell
```
Install Gnome Extensions

Nagativate your Firefox brower to Gnome Extention website

Install KDE-Plasma

$ sudo apt install tasksel
$ sudo tasksel install kubuntu-desktop
    - select <OK>
    - select sddm
$ sudo apt install sddm
$ sudo dpkg-reconfigure sddm

Customize:

$sudo apt install g++ cmake libx11-dev libxext-dev qtbase5-dev libqt5svg5-dev libqt5x11extras5-dev libqt4-dev qttools5-dev-tools libkf5windowsystem-dev git
$ sudo add-apt-repository ppa:papirus/papirus
$ sudo apt-get update
$ sudo apt-get install --install-recommends adapta-kde

Install Kvantum

$ sudo add-apt-repository ppa:papirus/papirus
$ sudo apt install qt5-style-kvantum

Customize KDE-Plasma - Dark Material Blur

Install GPU Driver - Support higher graphic resolutions or how GPU talk to python interface.

Download

$ chmod +x NVIDIA-Linux-x86_64–440.44.run
$ sudo sh NVIDIA-Linux-x86_64–440.44.run

[ERROR] disable Nouveau nvidia driver on Ubuntu 18.04 Bionic Beaver Linux

$ sudo bash -c "echo blacklist nouveau > /etc/modprobe.d/blacklist-nvidia-nouveau.conf"
$ sudo bash -c "echo options nouveau modeset=0 >> /etc/modprobe.d/blacklist-nvidia-nouveau.conf"
$ cat /etc/modprobe.d/blacklist-nvidia-nouveau.conf
$ sudo update-initramfs -u
$ sudo reboot

[ERROR] ERROR: An NVIDIA kernel module 'nvidia-drm' appears to already be loaded in your kernel. This may be because it is in use (for example, by an X server, a CUDA program, or the NVIDIA Persistence Daemon)

$ sudo systemctl set-default multi-user.target
$ sudo reboot 0

$ sudo ./NVIDIA-Linux-x86_64-440.44.run

$ sudo systemctl set-default graphical.target
$ sudo reboot 0

[ERROR] Possible missing firmware /lib/firmware/rtl_nic/rtl8105e-1.fw for module r8169 with 2.6.39 kernel

$ git clone git://git.kernel.org/pub/scm/linux/kernel/git/firmware/linux-firmware.git
$ sudo cp -r linux-firmware/rtl_nic/ /lib/firmware/
$ sudo update-initramfs -u

[ERROR] Restore nouveau driver and get desktop working.

$ sudo apt-get purge nvidia*
$ sudo apt-get install xserver-xorg-video-nouveau
$ sudo reboot now

[ERROR] PCIe BUS error severity=Corrected

$ cp /etc/default/grub ~/grub.backup
$ sudo nano /etc/default/grub
GRUB_CMDLINE_LINUX_DEFAULT="quite splash pci=noaer"

Install CUDA - allows us a way to write code for GPUs (Install cuda 10.0 - 10.1)

$ 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 && sudo apt-get -o Dpkg::Options::="--force-overwrite" install cuda-10-1 cuda-drivers
$ echo 'export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}' >> ~/.bashrc && echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}' >> ~/.bashrc
$ source ~/.bashrc && sudo ldconfig
$ nvcc --version
$ nvidia-smi

Install CuDNN - Primitives for Deep Learning Network

[Access]

https://developer.nvidia.com/rdp/cudnn-download

Download cuDNN Runtime Library for Ubuntu18.04 (Deb)

sudo dpkg -i libcudnn7_7.6.5.32-1+cuda10.1_amd64.deb

Download cuDNN Developer Library for Ubuntu18.04 (Deb)

sudo dpkg -i libcudnn7-dev_7.6.5.32-1+cuda10.1_amd64.deb

Download cuDNN Code Samples and User Guide for Ubuntu18.04 (Deb)

sudo dpkg -i libcudnn7-doc_7.6.5.32-1+cuda10.1_amd64.deb

Install cuDNN with Tar file installation

tar -xzvf cudnn-x.x-linux-x64-v8.x.x.x.tgz
sudo cp cuda/include/cudnn*.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*

Install multiple versions of CUDA on one machine

Install all necessary CUDA versions

Reference

Point symlink /usr/local/cuda to default version

$ cd /usr/local
$ sudo rm cuda
$ sudo ln -s cuda-10.0 cuda

Install suitable cuDNN versions for each CUDA using the Library for Linux tar files

Reference

Add each CUDA lib directory to LD_LIBRARY_PATH in order

$ sudo sh -c ‘echo export LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda-10.0/lib64:/usr/local/cuda-8.0/lib64:\$LD_LIBRARY_PATH > /etc/profile.d/cuda.sh’

Install TensorRT

ACCESS to download the version of TensorRT that you are interested in.

$ os="ubuntu1804"
$ tag="cuda10.0-trt7.0.0.11-ga-20191216"
$ sudo dpkg -i nv-tensorrt-repo-${os}-${tag}_1-1_amd64.deb
$ sudo apt-key add /var/nv-tensorrt-repo-${tag}/7fa2af80.pub
$ sudo apt update
$ sudo apt upgrade -y
$ sudo apt install tensorrt
$ sudo apt-get install python3-libnvinfer-dev
$ sudo apt-get install uff-converter-tf

Install Onnx

$ git clone https://github.com/NVIDIA/TensorRT.git
$ cd TensorRT/tools/onnx-graphsurgeon/
$ make build
$ python -m pip install onnx_graphsurgeon-X.Y.Z-py2.py3-none-any.whl --user

where X, Y, Z if the vertion number.

Verify the installation.

$ dpkg -l | grep TensorRT

Install TensorRT python

$ pip install nvidia-pyindex
$ pip install nvidia-tensorrt

Install Pycuda

$ conda activate M
$ arch=$(uname -m)
$ folder=${HOME}/src
$ mkdir -p $folder
$ sudo apt-get install -y build-essential python3-dev
$ sudo apt-get install -y libboost-python-dev libboost-thread-dev
$ sudo /home/m/.conda/envs/M/bin/pip install setuptools==41.0.0
$ boost_pylib=$(basename /usr/lib/${arch}-linux-gnu/libboost_python*-py3?.so)
$ boost_pylibname=${boost_pylib%.so}
$ boost_pyname=${boost_pylibname/lib/}
$ pushd $folder
$ wget https://files.pythonhosted.org/packages/5e/3f/5658c38579b41866ba21ee1b5020b8225cec86fe717e4b1c5c972de0a33c/pycuda-2019.1.2.tar.gz
$ CPU_CORES=$(nproc)
$ tar xzvf pycuda-2019.1.2.tar.gz
$ cd pycuda-2019.1.2
$ sudo /home/m/.conda/envs/M/bin/python ./configure.py --python-exe=/home/m/.conda/envs/M/bin/python --cuda-root=/usr/local/cuda --cudadrv-lib-dir=/usr/lib/${arch}-linux-gnu --boost-inc-dir=/usr/include --boost-lib-dir=/usr/lib/${arch}-linux-gnu --boost-python-libname=${boost_pyname} --boost-thread-libname=boost_thread
$ make -j$CPU_CORES
$ sudo /home/m/.conda/envs/M/bin/python setup.py build
$ sudo /home/m/.conda/envs/M/bin/python setup.py install
$ popd
$ sudo /home/m/.conda/envs/M/bin/python -c "import pycuda; print('pycuda version:', pycuda.VERSION)"

Install FFmpeg with Nvidia Accelator

Install necessary packages.

sudo apt --assume-yes install libfdk-aac-dev libass-dev libopus-dev libtheora-dev libvorbis-dev libvpx-dev libssl-dev build-essential yasm cmake libtool libc6 libc6-dev unzip wget libnuma1 libnuma-dev libmp3lame-dev nasm

Install ffnvcodec

git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers.git
cd nv-codec-headers && sudo make install && cd -

Clone FFmpeg's public GIT repository.

git clone https://git.ffmpeg.org/ffmpeg.git ffmpeg/ && cd ffmpeg/
./configure --enable-nonfree --enable-cuda-nvcc --enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64
make -j$(nproc)
sudo make install
ffmpeg -version
cd -

Testing

[ERROR] Ffmpeg: error while loading shared libraries: libavdevice.so.52: cannot open shared object file

Install Boost C++

Download

tar -xvf boost_1_76_0.tar.gz
cd boost_1_76_0

sudo apt-get install build-essential g++ python-dev autotools-dev libicu-dev build-essential libbz2-dev libboost-all-dev -y
./bootstrap.sh --prefix=/usr/ --with-libraries=python
sudo ./b2 --with=all -j16 install

// main.cpp
#include <boost/python/numpy.hpp>
#include <iostream>

namespace py = boost::python;
namespace np = boost::python::numpy;

int main(int argc, char ** argv) {
    Py_Initialize();
    np::initialize();
    py::tuple shape = py::make_tuple(3, 3);
    np::dtype dtype = np::dtype::get_builtin<float>();
    np::ndarray a = np::zeros(shape, dtype);
    np::ndarray b = np::empty(shape, dtype);

    std::cout << "Original array:\n" << py::extract<char const *> (py::str(a)) << std::endl;
    // Reshape the array into a 1D array
    a = a.reshape(py::make_tuple(9));
    // Print it again.
    std::cout << "Reshaped array:\n" << py::extract <char const *> (py::str(a)) << std::endl;
}

# CMakeLists.txt
project(EMoi)
cmake_minimum_required(VERSION 3.10)

set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")

FIND_PACKAGE(PythonInterp 3)
if (PYTHONINTERP_FOUND)
  if (UNIX AND NOT APPLE)
    if (PYTHON_VERSION_MAJOR EQUAL 3)
        FIND_PACKAGE(Boost COMPONENTS python${PYTHON_VERSION_MAJOR} numpy)
        FIND_PACKAGE(PythonInterp 3)
        FIND_PACKAGE(PythonLibs 3 REQUIRED)
    else()
        FIND_PACKAGE(Boost COMPONENTS python numpy)
        FIND_PACKAGE(PythonInterp)
        FIND_PACKAGE(PythonLibs REQUIRED)
    endif()
  else()	
    if (PYTHON_VERSION_MAJOR EQUAL 3)
        FIND_PACKAGE(Boost COMPONENTS python${PYTHON_VERSION_MAJOR}${PYTHON_VERSION_MINOR} numpy)
        FIND_PACKAGE(PythonInterp 3)
        FIND_PACKAGE(PythonLibs 3 REQUIRED)
    else()
        FIND_PACKAGE(Boost COMPONENTS python${PYTHON_VERSION_MAJOR}${PYTHON_VERSION_MINOR} numpy)
        FIND_PACKAGE(PythonInterp)
        FIND_PACKAGE(PythonLibs REQUIRED)
    endif()
  endif()
else()
    message("Python not found")
endif()

message(STATUS "PYTHON_LIBRARIES = ${PYTHON_LIBRARIES}")
message(STATUS "PYTHON_EXECUTABLE = ${PYTHON_EXECUTABLE}")
message(STATUS "PYTHON_INCLUDE_DIRS = ${PYTHON_INCLUDE_DIRS}")
message(STATUS "Boost_LIBRARIES = ${Boost_LIBRARIES}")

INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS} ${PYTHON_INCLUDE_DIRS})

add_executable(app main.cpp)
target_link_libraries(app ${Boost_LIBRARIES} ${PYTHON_LIBRARIES})

Install Docker

Install

sudo apt remove docker docker-engine docker.io containerd runc -y
sudo apt autoremove -y
sudo apt update
sudo apt install apt-transport-https ca-certificates curl gnupg lsb-release
curl -fsSL https://download.docker.com/linux/debian/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/debian $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt update
sudo apt install docker-ce docker-ce-cli containerd.io -y
sudo docker run hello-world

Got Permission

sudo groupadd docker
sudo chmod 666 /var/run/docker.sock
sudo usermod -aG docker ${USER}

Install Anaconda

[Access]

https://www.anaconda.com/products/individual

[Install]

sudo sh Anaconda3-2019.10-Linux-x86_64.sh
sudo chown -R 1000:1000 ~/.conda
sudo chmod 666 ~/.conda/environments.txt
cat >> ~/.bashrc << 'EOF' export PATH=$HOME/anaconda3/bin:${PATH} 'EOF'
source ~/.bashrc
conda upgrade -y --all

Install Pip

sudo apt install python3-pip -y

GPU check AI framework

Pytorch

import torch
torch.cuda.current_device()
torch.cuda.device(0)
torch.cuda.device_count()
torch.cuda.get_device_name(0)
torch.cuda.is_available()

Mxnet

import mxnet as mx
mx.runtime.feature_list()
_ = mx.nd.array([1, 2, 3], ctx=mx.gpu(0))

Tensorflow

import tensorflow as tf
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
with tf.Session() as sess:
    devices = sess.list_devices()

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Install

Install the latest version of `cmake`

Install TeamVier

Install `Skype`

Install `Visual Code`

Install `Sublime Text`

Install `ibus-unikey`

Install Bluetooth 5 USB Dongle Orico BTA-608/ Ugreen CM390 Driver

Install Gnome Shell Extensions

Install KDE-Plasma

Install GPU Driver - Support higher graphic resolutions or how GPU talk to python interface.

Install CUDA - allows us a way to write code for GPUs (Install cuda 10.0 - 10.1)

Install CuDNN - Primitives for Deep Learning Network

Install multiple versions of CUDA on one machine

Install TensorRT

Install FFmpeg with Nvidia Accelator

Install Boost C++

Install Docker

Install Anaconda

Install Pip

GPU check AI framework

FilesExpand file tree

Install_new_linux.md

Latest commit

History

Install_new_linux.md

File metadata and controls

Install

Install the latest version of cmake

Install TeamVier

Install Skype

Install Visual Code

Install Sublime Text

Install ibus-unikey

Install Bluetooth 5 USB Dongle Orico BTA-608/ Ugreen CM390 Driver

Install Gnome Shell Extensions

Install KDE-Plasma

Install GPU Driver - Support higher graphic resolutions or how GPU talk to python interface.

Install CUDA - allows us a way to write code for GPUs (Install cuda 10.0 - 10.1)

Install CuDNN - Primitives for Deep Learning Network

Install multiple versions of CUDA on one machine

Install TensorRT

Install FFmpeg with Nvidia Accelator

Install Boost C++

Install Docker

Install Anaconda

Install Pip

GPU check AI framework

Install the latest version of `cmake`

Install `Skype`

Install `Visual Code`

Install `Sublime Text`

Install `ibus-unikey`