NVIDIA

Intel® Core™ i5-12600K
msi 主板 PRO Z790-P WIFI
GeForce RTX 2080 Ti
32G 2T

# 安装驱动
sudo ubuntu-drivers autoinstall

wget https://developer.download.nvidia.com/compute/cuda/12.0.0/local_installers/cuda_12.0.0_525.60.13_linux.run
sudo sh cuda_12.0.0_525.60.13_linux.run

Please make sure that
 -   PATH includes /usr/local/cuda-12.0/bin
 -   LD_LIBRARY_PATH includes /usr/local/cuda-12.0/lib64, or, add /usr/local/cuda-12.0/lib64 to /etc/ld.so.conf and run ldconfig as root

# 在 ~/.bashrc 添加以下内容
export PATH=$PATH:/usr/local/cuda/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64
# 执行 source ~/.bashrc 或者重启一个终端，就可以检查是否安装成功了。

# Unzip the cuDNN package.
tar -xvf cudnn-linux-x86_64-8.x.x.x_cudaX.Y-archive.tar.xz
# Copy the following files into the CUDA toolkit directory.
sudo cp cudnn-*-archive/include/cudnn*.h /usr/local/cuda/include
sudo cp -P cudnn-*-archive/lib/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
# 验证
cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

# Unzip the TensorRT package.
tar -xzvf TensorRT-${version}.Linux.${arch}-gnu.${cuda}.tar.gz
# 在 ~/.bashrc 添加以下内容
export PATH=/home/admin1/work/TensorRT-8.6.1.6/bin:$PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/admin1/work/TensorRT-8.6.1.6/lib
export LIBRARY_PATH=/home/admin1/work/TensorRT-8.6.1.6/lib:$LIBRARY_PATH
# 执行 source ~/.bashrc 或者重启一个终端，就可以检查是否安装成功了。

# 验证
trtexec
# 验证
cd work/TensorRT-8.6.1.6/samples/sampleOnnxMNIST/
make
# 输出 Linking: ../../bin/sample_onnx_mnist 就成功了。