cpptensorrtz

Index

• Getting Started
• Resources

1. Getting Started

Using docker (Preferred)

Note: This method is tested using Ubuntu Distros. This method doesn't work for Windows/MacOS as nvidia-docker isn't supported.

1. Install docker. (Skip this step if docker is already installed)

 $ sudo apt-get update
 $ sudo apt-get install docker-ce docker-ce-cli containerd.io

2. Install nvidia-container-toolkit to use gpus with docker. Reference - nvidia-docker

 $ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
 $ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
 $ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
 $ sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
 $ sudo systemctl restart docker

3. Pull TensorRT image from NVIDIA GPU cloud.

 $ docker pull nvcr.io/nvidia/tensorrt:20.12-py3

2. Resources

1. Docker quick-start
2. TensorRT Developer Guide
3. TensorRT NVIDIA GPU Cloud
4. wang-xinyu/tensorrtx. Thanks to this repo for all the resources and inspiration.