Get Started With Jetson Nano Developer Kit

Welcome to our guide on getting started with the Jetson Nano 4GB Developer Kit! This powerful AI computer is perfect for makers, learners, and developers looking to build practical AI applications, cool AI robots, and more.

1. Components

You can find a comprehensive guide on the Get Started With Jetson Nano Developer Kit | NVIDIA Developer. This guide covers everything from preparing your microSD card to connecting peripherals and powering up the device. It's a great resource to help you get started with your Jetson Nano Developer Kit.

• MicroSD Card: 64GB.
• USB Keyboard and Mouse.
• Computer Display: HDMI.
• DC Barrel jack for 5V, 4mA power input.
• Internet Connection: For downloading software and updates.

2. Specification

3. Setup Guide

1. Download Etcher: Go to https://etcher.balena.io/ and download the appropriate version of Etcher for your operating system (Windows, macOS, or Linux). In my case is Windows 10 as shows on the figure below.

2. Download the JetPack 4.6.1 SDK Image: Obtain the correct JetPack 4.6.1 SDK image file from the NVIDIA Developer website. The appropriate JetPack version depends on your specific Jetson Nano model, so verify compatibility before downloading. You can find JetPack 4.6.1 here: https://developer.nvidia.com/embedded/jetpack-sdk-461.

3. Prepare your MicroSD Card:

Ensure your microSD card is compatible with the Jetson Nano (size and speed). Insert the microSD card into a card reader and plug it into your PC and Launch Etcher application.

4.Select the Target:

Choose your microSD card from the list of available drives. Be absolutely certain you select the correct drive! Etcher will erase the entire drive you select.

5. Select the Image:

In the Etcher interface, click "Flash from file."· Browse to the location where you saved the JetPack 4.6.1 SDK image file and select it as shows on the figure below.

6. Flash the Image:

Click "Flash!" Etcher will now begin flashing the JetPack image onto the microSD card. This process may take some time, depending on the size of the image and the speed of your card reader and microSD card.

7. Connect Peripherals:

• Attach the display, keyboard, and mouse to the Jetson Nano.
• Connect the Ethernet cable or a Wi-Fi adapter for internet access.
• Insert the microSD card into the Jetson Nano slot, as shown in the figure below.

4. Power Up

• Connect the Micro-USB power supply to the Jetson Nano.
• The device will boot up, and you should see the initial setup screen on your display.

5. Initial Setup

• Follow the on-screen instructions to complete the initial setup.
• Create a user account and connect to the internet.

6. Update and Install Software

Open a terminal and run the following commands to update the system:

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

7. Memory Swapping

Swapping memory on the Jetson Nano 4GB is a technique used to extend the available memory beyond its physical 4GB limit. Here's why it's beneficial and how to do it:

• Limited Physical Memory: The Jetson Nano has only 4GB of LPDDR4 memory, which can be insufficient for running large deep-learning models or compiling extensive programs.
• Improved Performance: Swapping allows the system to handle memory-intensive tasks by temporarily moving less-used data to disk, freeing up physical RAM for active processes.
• Prevent Out-of-Memory Errors: Swapping helps avoid system crashes or program terminations due to memory exhaustion.

1.Check memory usage

$free -h

2.Creating Swapfile

Use fallocate to create a swapfile and set appropriate permissions.

$df -h

$ls -lh /swapfile

3. Enabling the Swap Partition

$do chmod 600 /swapfile
$sudo mkswap/swapfile
$sudo swapon /swapfile

4.Check Swap Memory

$free -h

8. Verify CUDA Installation

To check if CUDA is running properly on your Jetson Nano, follow these steps:

• Open a terminal window.
• Run the following command to check the CUDA version:

$nvcc --version

Conclusion

With the Jetson Nano 4GB Developer Kit, you are now ready to explore the world of AI and machine learning. From building AI-powered robots to developing smart applications, the possibilities are endless.