在WSL+Ubuntu22.04下安装CUDA11.8+CUDNN8.9+tensorrt8.6，接近Jetson的环境-优快云博客

#在WSL+Ubuntu22.04下安装CUDA11.8+CUDNN8.9+tensorrt8.6，接近Jetson的环境


# 更新apt仓库
sudo apt-get update

# 安装开发环境
sudo apt install -y \
    build-essential \
    software-properties-common \
    wget \
    curl \
    git \
    vim \
    cmake \
    pkg-config \
    libtool \
    autoconf \
    automake \
    lsb-core \
    ubuntu-drivers-common

# 安装 Python 开发环境
sudo apt install -y \
    python3 \
    python3-dev \
    python3-pip \
    python3-venv \
    python3-wheel

#安装cmake
sudo apt install -y cmake

# 安装opencv
sudo apt install -y libopencv-dev libopencv-dnn-dev

# 添加 NVIDIA 仓库密钥
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600


# 下载cuda 11.8 
# 到nvidia官网下载 cuda-repo-wsl-ubuntu-11-8-local_11.8.0-1_amd64.deb

# 下载并安装 CUDA 11.8 仓库
sudo dpkg -i cuda-repo-wsl-ubuntu-11-8-local_11.8.0-1_amd64.deb

# 添加 NVIDIA 公钥，注意文件名
sudo cp /var/cuda-repo-wsl-ubuntu-11-8-local/cuda-9EA88183-keyring.gpg /usr/share/keyrings/

#更新 APT 并安装 CUDA
sudo apt update
sudo apt install -y cuda-toolkit-11-8

# 验证 CUDA 安装
/usr/local/cuda-11.8/bin/nvcc --version

# 添加到 ~/.bashrc
echo '# CUDA 11.8' >> ~/.bashrc
echo 'export CUDA_HOME=/usr/local/cuda-11.8' >> ~/.bashrc
echo 'export PATH=$CUDA_HOME/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
echo 'export CUDADIR=/usr/local/cuda-11.8' >> ~/.bashrc

# 重新加载配置
source ~/.bashrc


# 下载cudnn
# cudnn-local-repo-ubuntu2204-8.9.7.29_1.0-1_amd64.deb

# 安装 cuDNN 本地仓库包
sudo dpkg -i cudnn-local-repo-ubuntu2204-8.9.7.29_1.0-1_amd64.deb

# 导入 NVIDIA 公钥，注意文件名
sudo cp /var/cudnn-local-repo-ubuntu2204-8.9.7.29/cudnn-local-8AE81B24-keyring.gpg /usr/share/keyrings/

# 更新 apt 仓库
sudo apt update

# 查看可用的 cuDNN 包
apt search libcudnn8 | grep 8.6

# 安装dev
sudo apt install -y libcudnn8-dev

# 或者安装所有相关包
sudo apt install -y \
    libcudnn8 \
    libcudnn8-dev \
    libcudnn8-samples

# 验证库版本
cat /usr/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

# 运行 cuDNN 示例
cd /usr/src/cudnn_samples_v8
sudo make -C mnistCUDNN
sudo sudo make -C conv_sample/

# 运行示例
./mnistCUDNN
# 应该看到输出：Test passed!



# 下载tensorrt-8.6
# nv-tensorrt-local-repo-ubuntu2204-8.6.1-cuda-11.8_1.0-1_amd64.deb

# 安装 TensorRT 仓库包
sudo dpkg -i nv-tensorrt-local-repo-ubuntu2204-8.6.1-cuda-11.8_1.0-1_amd64.deb

# 导入 NVIDIA 公钥，注意文件名
sudo cp /var/nv-tensorrt-repo-ubuntu2204-cuda11.8-trt8.6.1.6-ga-20231016/*-keyring.gpg /usr/share/keyrings/

# 更新 apt 仓库
sudo apt update

# 查看可用的 TensorRT 包
apt search tensorrt | grep 8.6

sudo apt install -y tensorrt-dev tensorrt

# 验证库版本
dpkg -l | grep nvinfer

# 测试 trtexec 工具
trtexec --help | head -20
#或者 
cd /usr/src/tensorrt/samples/trtexec
sudo make
../../bin/trtexec