Orin

This tutorial was written for the NVIDIA Jetson Orin Nano Developer Kit (8 GB). The tutorial was written on 2024-2-13:19-42-5. Details of the board are:

Key	Value
P-Number	p3767-0005
Module	NVIDIA Jetson Orin Nano (Developer kit)
SoC	tegra234
CUDA Arch BIN	8.7
L4T	36.2.0
Jetpack	6.0 DP
Machine	aarch64
System	Linux
Distribution	Ubuntu 22.04 Jammy Jellyfish
Release	5.15.122-tegra
Python	3.11.5
CUDA	12.2.140
OpenCV	4.8.0
OpenCV-Cuda	False
cuDNN	8.9.4.25
TensorRT	8.6.2.3
VPI	3.0.10
Vulkan	1.3.204

IMPORTANT WARNING: The host must be running on __Ubuntu 20.04__to flash the board.

Flashing the Board

The board can be flashed using the SDK Manager. The SDK Manager can be downloaded from the NVIDIA website. To flash the board, force the board into recovery mode by following the steps in JetsonHacks Tutorial. Then, select the following options:

• Host Machine: Ubuntu 20.04
• Target Hardware: Jetson Orin Nano Developer Kit 8 GB
• Target OS: Jetpack 6.0 DP
• DeepStream: 6.0

In my case, I had already mounted an NVME SSD as a storage component. Most tutorials do SD cards, but I went with a mainstream 1 TB NVME SSD for performance reasons. Select the pre-config option to set the board and initialize it with a username and a password. For simplicity, the username and password are set to nvidia. The board will be flashed, and it will be ready to use.

Setting up the Board

First, update the system:

sudo apt-get update
sudo apt-get upgrade
sudo reboot

Then, install the following packages:

sudo apt-get upgrade
sudo apt install ssh firefox zlib1g 
sudo apt-get install python3 python3-dev python3-distutils python3-venv python3-pip
sudo apt-get install ninja-build
sudo apt install software-properties-common lsb-release
sudo apt install cmake
sudo apt install build-essential libtool autoconf unzip wget
sudo apt-get install terminator

These packages will prepare the board for development. If you are working extensively with Python, install conda package manager. The following commands will install miniconda:

cd Downloads/
sudo apt upgrade
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-aarch64.sh
chmod +x Miniconda3-latest-Linux-aarch64.sh
./Miniconda3-latest-Linux-aarch64.sh

Checking CUDA and cuDNN

Before we advance on checking CUDA and cuDNN, we need to verify gcc and nvidia-smi:

gcc --version
nvidia-smi

We will begin with checking CUDA:

git clone https://github.com/NVIDIA/cuda-samples.git
cd cuda-samples/Samples/1_Utilities/deviceQuery/
make
./deviceQuery

After checking CUDA, we will check cuDNN:

cp -r /usr/src/cudnn_samples_v8/ ~/Documents/workspace/
cd cudnn_samples_v8/mnistCUDNN/
sudo apt install libfreeimage3 libfreeimage-dev
sudo apt-get update
sudo apt-get upgrade
make clean && make
./mnistCUDNN

Monitoring the Board

To monitor the board, we will install jetson-stats:

sudo pip3 install -U jetson-stats

Notes

It is important to note that the NVIDIA SDK Manager must be installed on an Ubuntu 20.04 engine. I tried two different machines running Ubuntu 22.04 and attempted to flash the board, but it would yield errors. I also tried Ubuntu 18.04, but the latest supported Jetpack was 5.x.y, and at the moment of writing, the latest Jetpack is 6.z. Therefore, the host machine must be running Ubuntu 20.04.