Jetson Nano

NVIDIA Jetson Nano is an embedded system-on-module (SoM) and developer kit from the NVIDIA Jetson family, including an integrated 128-core Maxwell GPU, quad-core ARM A57 64-bit CPU, 4GB LPDDR4 memory, along with support for MIPI CSI-2 and PCIe Gen2 high-speed I/O.

Useful for deploying computer vision and deep learning, Jetson Nano runs Linux and provides 472 GFLOPS of FP16 compute performance with 5-10W of power consumption.

Jetson Nano is currently available as the Jetson Nano Developer Kit for $99, with the production compute module coming in June 2019. See the wiki of the other Jetson's here.



= Jetson Nano Developer Kit =

The Jetson Nano Developer Kit is an easy way to get started using Jetson Nano, including the module, carrier board, and software. It costs $99 and is available from distributors worldwide.



What's Included
(the complete devkit with module and heatsink weighs 138 grams)
 * 80x100mm Reference Carrier Board
 * Jetson Nano Module with passive heatsink
 * Pop-Up Stand
 * Getting Started Guide

What You Will Need

 * Power Supply
 * 5V⎓2A Micro-USB adapter (see Adafruit GEO151UB)
 * 5V⎓4A DC barrel jack adapter, 5.5mm OD x 2.1mm ID x 9.5mm length, center-positive (see Adafruit 1446)
 * See Power Supply Considerations for more information.
 * MicroSD card (16GB UHS-1 recommended minimum)

Ports & Interfaces

 * 4x USB 3.0 A (Host)
 * USB 2.0 Micro B (Device)
 * MIPI CSI-2 x2 (15-position Camera Flex Connector)
 * HDMI 2.0
 * DisplayPort
 * Gigabit Ethernet (RJ45)
 * M.2 Key-E with PCIe x1
 * MicroSD card slot
 * (3x) I2C, (2x) SPI, UART, I2S, GPIOs

Getting Started

 * Follow the Getting Started with Jetson Nano Guide to setup your devkit and format the MicroSD card.


 * Plug in an HDMI display into Jetson, attach a USB keyboard & mouse, and apply power to boot it up.


 * Visit the Embedded Developer Zone and Jetson Nano Developer Forum to access the latest documentation & downloads.

Availability
The devkit is available for $99 from the NVIDIA webstore and global distributors, including:


 * Amazon
 * Arrow
 * Newegg
 * Seeed Studio
 * Silicon Highway
 * SparkFun

For the full list, refer to the Region Selector.

= Software Support =
 * JetPack 4.2
 * Linux4Tegra R32.1 (L4T)
 * Linux kernel 4.9
 * Ubuntu 18.04 LTS aarch64
 * CUDA Toolkit 10.0
 * cuDNN 7.3.1
 * TensorRT 5.0.6
 * TensorFlow 1.31.1
 * VisionWorks 1.6
 * OpenCV 3.3.1
 * OpenGL 4.6
 * OpenGL ES 3.2
 * EGL 1.5
 * Vulkan 1.1
 * GStreamer 1.14.1
 * V4L2 media controller support

= Guides and Tutorials =

This section contains recipes for following along on Jetson Nano.

System Tools

 * L4T Kernel Development Guide
 * Power Supply Considerations
 * Upstream Development Guide
 * CUDA and VisionWorks Samples
 * Preliminary 3D CAD Model
 * Mounting a SWAP File
 * GPIO Header Pin-out
 * Reading Serial Number
 * jetson_easy - automatic setup/scripting
 * jetson_stats - jtop, service and other tools

Multimedia

 * RidgeRun's GstInterpipe (GStreamer plug-in for communication between two or more independent pipelines)
 * RidgeRun's GstRRWebRTC (GStreamer plug-in that turns pipelines into WebRTC compliant endpoints)
 * RidgeRun's GstRTSPSink (GStreamer element for high performance streaming to multiple computers using the RTSP/RTP protocols)
 * RidgeRun's Gstreamer Daemon - GstD (GStreamer framework for controlling audio and video streaming using TCP connection messages)
 * RidgeRun's GstCUDA (RidgeRun CUDA ZeroCopy for GStreamer)
 * RidgerRun's GstPTZR (GStreamer Pan Tilt Zoom and Rotate Element)
 * RidgeRun's GstColorTransfer (GStreamer plug-in that transfers the color scheme from a reference to a target image)

Deep Learning

 * Hello AI World (jetson-inference)
 * TensorFlow 1.13.1 Installer (pip wheel)
 * PyTorch 1.1 Installer (pip wheel)
 * MXNet 1.4 Installer (pip wheel)
 * Deep Learning Inference Benchmarking Instructions
 * TensorFlow Object Detection With TensorRT (TF-TRT)
 * RidgeRun's GstInference
 * RidgeRun's R2Inference

See the NVIDIA AI-IoT GitHub for other coding resources on deploying AI and deep learning.

Robotics

 * NVIDIA JetBot (AI-powered robotics kit)
 * jetbot_ros (ROS nodes for JetBot)
 * ROS Melodic (ROS install guide)
 * ros_deep_learning (jetson-inference nodes)

V4L2 drivers for cameras

 * RidgeRun has a list of drivers already supported in Jetson, please check if the driver that you need is already there. Otherwise, RidgeRun offers services to create the driver for you

= Ecosystem Products and Sensors =

The following are 3rd-party accessories, peripherals, and cameras available for Jetson Nano.

Cameras

 * e-con Systems e-CAM30_CUNANO (3.4 MP MIPI Camera)
 * Logitech C920 (USB webcam)
 * Leopard Imaging LI-IMX219-MIPI-FF-NANO (IMX219 sensor)
 * Raspberry Pi Camera v2 (IMX219 sensor)
 * Stereolabs ZED (stereo camera)

Carriers

 * Antmicro Jetson Nano Baseboard (module carrier)
 * Auvidea JN30 (module carrier)
 * Auvidea JN30-LC (module carrier)

Enclosures

 * ConnectTech Nano-Pac (3D-printable enclosure)
 * Jetson Nano Case (3D-printable enclosure)
 * Jetson NanoMesh (3D-printable enclosure)
 * Jetson NanoMesh Mini (3D-printable enclosure)
 * jetson_nano_enc (3D-printable enclosure)
 * Geekworm Jetson Nano Case (metal enclosure)

Power Supplies
See the Power Supply section for more information about selecting proper power adapters.


 * Adafruit GEO151UB (5V⎓2.5A Micro-USB adapter)
 * Adafruit 1446 (5V⎓4A DC barrel jack adapter)

Battery Packs

 * INUI 10000mAh (dual 5V⎓3A Micro-USB)
 * Krisdonia 25000mAh (5V⎓3A Micro-USB / DC barrel jack)

Wireless

 * Edimax EW-7811Un (USB Wi-Fi wireless dongle)
 * Intel 8265NGW (M.2 Key-E Wi-Fi/BT wireless card)

Other

 * M.2 Key-E to Mini-PCIe (PCIe adapter)
 * M.2 Key-E to Key-M (PCIe adapter)
 * Noctua NF-A4x20 5V PWM (optional fan)

See the Jetson Nano Supported Components List for devices that have been qualified by NVIDIA to work with Jetson Nano.

= Getting Help = If you have a technical question or bug report, please visit the Jetson Nano Developer Forum and search or start a new topic.

See the official Support page on Embedded Developer Zone for warranty and RMA information.

For NVIDIA webstore Customer Service, please see the My Account page or contact 1-800-797-6530.