Jetson Orin Nano Dev Kit
by NVIDIA
NVIDIA Jetson Orin™ Nano Developer Kit is a compact edge AI board built with Jetson Orin™ Nano 8GB module which delivers up to 40TOPS AI performance and has a rich set of IOs including USB 3.2 Gen 2 ports, 2x M.2 Key M for SSD, pre-installed Wi-Fi module, and more.
The NVIDIA Jetson Orin™ Nano Developer Kit sets a new standard for creating entry-level AI-powered robots, smart drones, and intelligent cameras. It also simplifies the process of starting with Jetson Orin Nano series modules. Compact design, lots of connectors, and up to 40 TOPS of AI performance make this the perfect developer kit to bring your AI concepts to life. With up to 80X the performance of Jetson Nano, it can run all modern AI models, including transformer and advanced robotics models.
The developer kit comprises a Jetson Orin™ Nano 8GB module and a reference carrier board that can accommodate all Orin Nano and Orin NX modules. This provides the ideal platform for prototyping your next-gen edge-AI product. The Jetson Orin™ Nano 8GB module features an Ampere architecture GPU and a 6-core ARM CPU, enabling multiple concurrent AI application pipelines and high-performance inference. The carrier board boasts a wide array of connectors, including two camera connectors that can handle 2-lane and 4-lane cameras.
Features
- Excellent AI Performance for production: on-device processing with up to 40 TOPS AI performance with low power and low latency
- Hand-size edge AI device: compact size at 100mm x79mm x 21mm, includes Jetson Orin™ Nano 8GB module, a heatsink with a fan and a power adapter.
- Expandable with rich I/Os: USB 3.2 Gen 2 ports(4x), DP 1.2, M.2 key E with pre-installed Wi-Fi module, 2x M.2 Key M for SSD, microSD slot, 2x MIPI CSI-2 connectors, Gigabit Ethernet, 40-pin GPIO
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Adafruit Blinka Installation
We use a special library called adafruit_blinka (named after Blinka, the CircuitPython mascot) to provide the layer that translates the CircuitPython hardware API to whatever library the Linux board provides.
For example, on Raspberry Pi we use the python RPi.GPIO library. For any I2C interfacing we'll use ioctl messages to the /dev/i2c device. For SPI we'll use the spidev python library, etc. These details don't matter so much because they all happen underneath the adafruit_blinka layer.