安裝ubuntu 18.04要記得選取"安裝第三方驅動"
1.重灌完後，在grub界面按e進入修改參數，quite splash 後面空一格後加入nomodeset後進入系統
2.利用ubuntu自帶的"軟體與更新"，選擇欲用的"顯卡驅動"
3.之後也不需要永久修改grub參數了，重啟後仍然會使用"專用顯卡驅動"
1.bluez從5.48更新到5.50
dpkg --status bluez | grep '^Version:'` #查看bluez版本
sudo add-apt-repository ppa:bluetooth/bluez #添加套件源
sudo apt-get update
sudo apt upgrade
#進入藍芽界面scan on、pair和trust mac地址
bluetoothctl
scan on
pair mac地址
trust mac 地址
2.聲音控制界面(開啟界面後將"線路輸入"改成"耳機"就可以讓後方面板音源線有聲音)
sudo apt install pavucontrol
pavucontrol #開啟聲音控制界面（因為gnome內建的再後方面板音源線預設設定有Bug）
1.pip 3
sudo apt install python3-pip
pip3 install setuptools
bash Anaconda3-2020.07-Linux-x86_64.sh
1.安裝前硬體資訊檢查 [參考源]
2.進行Runfile Installation [參考源]
lsmod | grep nouveau #確保沒有任何文字被輸出（詳細請見參考源）
這邊不繼續下去～因為比較喜歡用套件管理軟體安裝
3.進行package Manager Installation [參考源]
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
wget http://developer.download.nvidia.com/compute/cuda/11.0.2/local_installers/cuda-repo-ubuntu1804-11-0-local_11.0.2-450.51.05-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-11-0-local_11.0.2-450.51.05-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu1804-11-0-local/7fa2af80.pub
sudo apt-get update
sudo apt-get install --no-install-recommends cuda
4.新增環境變數至檔案最後面 [參考源]
vim ~/.bashrc
- export PATH=/usr/local/cuda-11.0/bin${PATH:+:${PATH}}
export LDLIBRARYPATH="/usr/local/cuda-11.0/lib64:${LDLIBRARYPATH}"
source ~/.bashrc #載入新的bash設定檔
5.驗證安裝是否成功 Verify the Driver Version
cat /proc/driver/nvidia/version #出現kernel version表成功
5.1 查看NVIDIA-SMI和Driver Version的版本號是否一致
nvidia-smi #順便看CUDA Version是不是你裝好的！
應該會顯示error，因為cuda11自動裝了相容的顯卡驅動450，須重新開機讓系統應用。
5.2 重開機再確認一次版本號
reboot
nvidia-smi #看看NVIDIA-SMI和Driver Version是否一致
應該一致了，如果不一致，那肯定沒做好之前的步驟。
6.（選擇性安裝套件 #我有裝，但好像沒必要）
sudo apt-get install g++ freeglut3-dev build-essential libx11-dev \
libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev
7.(當你想要移除cuda)
sudo apt-get --purge remove "*cublas*" "*cufft*" "*curand*" \
"*cusolver*" "*cusparse*" "*npp*" "*nvjpeg*" "cuda*" "nsight*"
8.(當你想要移除NVIDIA driver)
sudo apt-get --purge remove "*nvidia*"
0.安裝前硬體資訊檢查 [參考源]
0.下載cuDNN v8.0.2 (July 24th, 2020)forCUDA 11.0 註冊後下載
|cuDNN Runtime Library for Ubuntu18.04 x86_64 (Deb)
|cuDNN Developer Library for Ubuntu18.04 x86_64 (Deb)
|cuDNN Code Samples and User Guide for Ubuntu18.04 x86_64 (Deb)
1.安裝cudnn庫
sudo dpkg -i libcudnn8_8.0.2.39-1+cuda11.0_amd64.deb
2.安裝開發者cudnn庫
sudo dpkg -i libcudnn8-dev_8.0.2.39-1+cuda11.0_amd64.deb
3.驗證cudnn和cuda成功運行
sudo dpkg -i libcudnn8-doc_8.0.2.39-1+cuda11.0_amd64.deb
cp -r /usr/src/cudnn_samples_v8/ $HOME
cd $HOME/cudnn_samples_v8/mnistCUDNN
make clean && make #會出現很多warning沒差拉！
./mnistCUDNN # "Test passed!" 出現表示成功
0.下載TensorRT 7.1 GA 註冊後下載
|TensorRT 7.1.3.4 for Ubuntu 1804 and CUDA 11.0 DEB local repo packages
1.確認RT支援的推理精度和特殊硬體的支援功能參考源
2.先安裝PyCUDA參考源
nvcc --version #確認nvcc能被bash找到
顯示以下資訊表示成功
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Thu_Jun_11_22:26:38_PDT_2020
Cuda compilation tools, release 11.0, V11.0.194
Build cuda_11.0_bu.TC445_37.28540450_0 pip3 install 'pycuda>=2019.1.1'
3.開始TensorRT(.deb)安裝 參考源
cd 至"nv-tensorrt-repo-ubuntu1804-cuda11.0-trt7.1.3.4-ga-20200617_1-1_amd64.deb" 檔案資料夾位置
sudo dpkg -i nv-tensorrt-repo-ubuntu1804-cuda11.0-trt7.1.3.4-ga-20200617_1-1_amd64.deb
sudo apt-key add /var/nv-tensorrt-repo-cuda11.0-trt7.1.3.4-ga-20200617/7fa2af80.pub
sudo apt-get update
sudo apt-get install tensorrt cuda-nvrtc-11-0
sudo apt-get install python3-libnvinfer-dev
sudo apt-get install uff-converter-tf
4.驗證TensorRT安裝
dpkg -l | grep TensorRT
顯示以下資訊表示成功
ii graphsurgeon-tf 7.1.3-1+cuda11.0 amd64 GraphSurgeon for TensorRT package
ii libnvinfer-bin 7.1.3-1+cuda11.0 amd64 TensorRT binaries
ii libnvinfer-dev 7.1.3-1+cuda11.0 amd64 TensorRT development libraries and headers
ii libnvinfer-doc 7.1.3-1+cuda11.0 all TensorRT documentation
ii libnvinfer-plugin-dev 7.1.3-1+cuda11.0 amd64 TensorRT plugin libraries
ii libnvinfer-plugin7 7.1.3-1+cuda11.0 amd64 TensorRT plugin libraries
ii libnvinfer-samples 7.1.3-1+cuda11.0 all TensorRT samples
ii libnvinfer7 7.1.3-1+cuda11.0 amd64 TensorRT runtime libraries
ii libnvonnxparsers-dev 7.1.3-1+cuda11.0 amd64 TensorRT ONNX libraries
ii libnvonnxparsers7 7.1.3-1+cuda11.0 amd64 TensorRT ONNX libraries
ii libnvparsers-dev 7.1.3-1+cuda11.0 amd64 TensorRT parsers libraries
ii libnvparsers7 7.1.3-1+cuda11.0 amd64 TensorRT parsers libraries
ii python3-libnvinfer 7.1.3-1+cuda11.0 amd64 Python 3 bindings for TensorRT
ii python3-libnvinfer-dev 7.1.3-1+cuda11.0 amd64 Python 3 development package for TensorRT
ii tensorrt 7.1.3.4-1+cuda11.0 amd64 Meta package of TensorRT
ii uff-converter-tf 7.1.3-1+cuda11.0 amd64 UFF converter for TensorRT package5.如果你要當App Server用來推理
sudo apt-get update
sudo apt-get install libnvinfer7 cuda-nvrtc-11-0
sudo apt-get install python3-libnvinfer
安裝前重啟一次電腦 參考源
sudo apt update
sudo apt install python3-dev python3-pip
sudo pip3 install -U virtualenv # system-wide install
#建立虛擬環境
virtualenv --system-site-packages -p python3 ./venv
source ./venv/bin/activate # sh, bash, ksh, or zsh
pip install --upgrade pip
pip install --upgrade tensorflow
#驗證tensorflow安裝
python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
#要關掉虛擬環境（注意tensorflow不能在運行的情況下關閉）
deactivate # don't exit until you're done using TensorFlow
1.安裝
sudo apt update
sudo apt install openssh-server
2.驗證
sudo systemctl status ssh
顯示包含以下資訊表示成功
Active: active (running)按下"q"離開 3.打開ssh port
sudo ufw allow ssh
4.如果想關閉ssh
sudo systemctl stop ssh
sudo systemctl disable ssh