This is the base Nerves System configuration for the Jetson Nano 2Gb Developer kit.
| Feature | Description |
|---|---|
| CPU | Quad-core ARM A57 @ 1.43 GHz |
| GPU | 128-core NVIDIA Maxwell™ |
| Memory | 2 GB 64-bit LPDDR4 25.6 GB/s |
| Storage | MicroSD |
| Linux kernel | 4.9.140 w/ OE4T patches |
| IEx terminal | UART ttyS0 |
| GPIO, I2C, SPI | Yes - Elixir Circuits |
| UART | ttyS0 + more via device tree overlay |
| Camera | MIPI CSI-2 x2 (15-position Flex Connector) |
| Ethernet | Gigabit Ethernet |
| WiFi | M.2 Key-E with PCIe x1 |
| USB | 1x USB 3.0 Type A, 2x USB 2.0 Type A, 1x USB 2.0 Micro-B |
This system is under development. Components of the system may change without upgrade paths until the partition structure and included helper libraries are added. It is also unclear what will be required in the system to support cross compiling for CUDA and the inclusions are subject to change. Other quirks and known issues are:
- Reboot sometimes hangs when rebooting too soon after boot.
It seems to be associated with
sdhci-tegra. When the reboot hangs, eventually the messagesdhci-tegra sdhci-tegra.0: Tuning donewill be seen and the system will reboot. - Booting with a display attached results in a white screen and a kernel panic.
It is highly recommended to power the board using a USB-C power adapter that can provide up to 3A of power. Powering from your laptop may be unreliable.
The most common way of using this Nerves System is create a project with mix nerves.new, add :jetson_nano_2g to the @all_targets list at the top of the
mix.exs file, and add the system to the deps:
{:nerves_system_jetson_nano_2g, "~> 0.1", runtime: false, targets: :jetson_nano_2g}Finally, you can export the Mix target and MIX_TARGET=jetson_nano_2g.
The most common way of using this Nerves System is create a project with mix nerves.new and to export MIX_TARGET=jetson_nano_2g. See the Getting started
guide
for more information.
If you need custom modifications to this system for your device, clone this repository and update as described in Making custom systems
The console is configured to output to the pins on header J12 located under the Jetson Nano module on the carrier board. A 3.3V FTDI cable is needed to access the output.
This system supports storing provisioning information in a small key-value store outside of any filesystem. Provisioning is an optional step and reasonable defaults are provided if this is missing.
Provisioning information can be queried using the Nerves.Runtime KV store's
Nerves.Runtime.KV.get/1
function.
Keys used by this system are:
| Key | Example Value | Description |
|---|---|---|
nerves_serial_number |
"12345678" |
By default, this string is used to create unique hostnames and Erlang node names. If unset, it defaults to part of the BBB's serial number. |
The normal procedure would be to set these keys once in manufacturing or before deployment and then leave them alone.
For example, to provision a serial number on a running device, run the following and reboot:
iex> cmd("fw_setenv nerves_serial_number 12345678")This system supports setting the serial number offline. To do this, set the
NERVES_SERIAL_NUMBER environment variable when burning the firmware. If you're
programming MicroSD cards using fwup, the commandline is:
sudo NERVES_SERIAL_NUMBER=12345678 fwup path_to_firmware.fwSerial numbers are stored on the MicroSD card so if the MicroSD card is replaced, the serial number will need to be reprogrammed. The numbers are stored in a U-boot environment block. This is a special region that is separate from the application partition so reformatting the application partition will not lose the serial number or any other data stored in this block.
Additional key value pairs can be provisioned by overriding the default provisioning.conf
file location by setting the environment variable
NERVES_PROVISIONING=/path/to/provisioning.conf. The default provisioning.conf
will set the nerves_serial_number, if you override the location to this file,
you will be responsible for setting this yourself.
The Jetson nano Linux kernel originates from the NVIDIA Linux4Tegra (L4T)
repository at nv-tegra.nvidia.com/linux-4.9.git. The kernel expects a
number of other repositories to be located at paths relative to the kernel.
OpenEmbedded4Linux (OE4L) has created a copy of the NVIDIA Tegra upstream kernel
with these files pulled into the kernel tree and the relative paths
have been updated to reference the in tree locations. OE4L has also added
a number of patches required to compile the kernel using GCC 9 / 10.
U-Boot originates from nv-tegra.nvidia.com/3rdparty/u-boot.git with
patches originally coming from OE4T. The OE4T U-Boot patches have been updated
to work with U-Boot 2021.01.
Image credit: This image is from Nvidia.