The NVIDIA Jetson Nano Developer Kit is a $99 Jetson built for Maker and AI projects. Looky here:
There have been several models of the Jetson over the last 5 years, starting with the Jetson TK1 and most recently the Jetson AGX Xavier. Each model is much more powerful than its predecessor in computing power, with increases in memory, number of CPU cores, storage and so on. And with each new model, the price increased.
Now we have an entry level version! The Jetson Nano uses a variant of the chip in the Jetson TX1.
Hardware and Stuffs
Earlier we covered the hardware specifications of the Nano. You can also get the details straight from the Tech Sheet at NVIDIA.
As is usual Jetson system architecture, the Jetson Nano Module connects to a carrier board which contains physical access to all of the different I/O connectors. The connector between the module and the carrier board is a little different than the other Jetsons, this one being a 260 pin SO-DIMM connector.
One of the nice features of the Jetson Nano Dev Kit is that there are 4 USB 3 connectors. These 4 USB connectors go internally through one USB hub to the Nano.
There are two ways to power the developer kit. The first is to provide 2A @ 5V to the micro-USB connector. Many common phone chargers can supply this amount of power. For more power hungry applications, you can provide 4A @ 5V to the barrel jack after putting a jumper on the power selection pins. The jumper determines which power jack to use.
The extra juice can add power to the USB ports. Think of the USB ports as two stacks of two, with each stack able to provide 1A. The GPIO pins can supply up to 2A. You can mix and match to meet your application requirements, but remember that you only have 4A available.
Note that at full throttle, the Jetson Nano by itself can use more than 2A. You can use the supplied nvpmodel utility to set the power envelope to use 5W, or 10W.
Speaking of GPIO, there is a new software library to bit-bang the GPIO pins. The default device tree for the GPIO pins now mimics the Raspberry Pi, which means that many Raspberry Pi projects can work with little to no modifications.
In addition, Adafruit has ported their Blinka library to the Jetson, which allows access to the entire Adafruit project ecosystem. Good stuff!
Installation is straightforward. The Jetson Nano uses a Micro-SD card to hold the operating system. NVIDIA supplies a ISO image of the file system to flash the card.
You will need at least a 16GB MicroSD card. In the video, we use a Samsung 64GB MicroSD card. You know we love our GBs! I also grabbed a 5V Power Supply off of Amazon and jumpered the power input selector.
It is straightforward to flash the SD card using the instructions on the NVIDIA website: Getting Started With Jetson Nano Developer Kit. In the video, we flash from a Windows machine, but you can use a Macintosh or a Linux machine instead.
For you diehards out there, you can also command line it, but you probably don’t need help with that. NVIDIA helpfully provides the secret commands in their Linux documentation section on the above web page.
One of the nice things about using a disk image on the Nano is that all of the Jetson libraries are already installed. The Nano runs an Ubuntu 18.04 variant named L4T. The CUDA libraries are already installed, along with OpenCV with GStreamer support, cuDNN, TensorRT, VisionWorks and other libraries.
There are additional packages available for later installation, most notably deep learning support. This includes TensorFlow, PyTorch, Caffe, Keras and MXNet. ROS is also available.
Some folks like benchmarks. Here’s a great article benchmarking the Nano against the usual suspects, like Raspberry Pi 3 Model B+, ODROID-XU4, ASUS TinkerBoard and the rest of the Jetson family. The article is here: NVIDIA Jetson Nano: A Feature-Packed Arm Developer Kit For $99 USD.
If you’re into Deep Learning and more Nitty Grittys, here’s a great article from Dustin Franklin at NVIDIA: Jetson Nano Brings AI Computing to Everyone.
Setting up the Jetson Nano Developer Kit is now straightforward, and can now be done from your platform of choice. We’ll soon start looking at how to use this little pup in some of our projects. Stay tuned!
You will see many references to ‘Tegra’ in the Jetson world, this is in reference to the chip family. The Jetson is based on a a Tegra chip.