Docker 运行cuda11.8 + TensorRT8.5.3

宿主机系统 CUDA Toolkit=12.8不用改动； NVIDIA 驱动是向下兼容的（高驱动可以跑容器内 CUDA11.8 程序）。

1、安装 nvidia-container-toolkit

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list sudo apt update sudo apt install -y nvidia-container-toolkit sudo nvidia-ctk runtime configure --runtime=docker sudo systemctl restart docker

2、直接使用 NGC 官方预构建镜像

# 启动容器 docker run -it --gpus all \ --name trt85_infer \ -v /home/server/code:/workspace/code \ -v /home/server/data:/workspace/data \ nvcr.io/nvidia/tensorrt:22.12-py3