NVIDIA Jetson Orin Nano 8GB Developer Kit

The NVIDIA Jetson Orin Nano Developer Kit has revolutionized the development of AI-powered robotics, quadcopters, and computer vision solutions, as demonstrated at NVIDIA GTC 2023. This kit simplifies programming with the Jetson Orin Nano series, and its small form factor, assortment of interfaces, and 40TOPS of AI acceleration grant the power for revolutionary projects.

The developer kit consists of an 8 GB Jetson Orin Nano module and a reference carrier board that supports all Jetson Orin Nano and Jetson Orin NX modules, creating the ideal platform for prototyping edge AI products of the future.. This powerful and flexible developer kit provides the platform to create innovative, advanced edge AI products for any application. Ready to take your project to the next level? This one’s a game changer.

NVIDIA’s Jetson Orin Nano 8GB dev kit offers a GPU with 1024 CUDA cores, 32 Tensor Cores, and 6-core Arm CPU, enabling simultaneous AI tasks and improved inference. Furthermore, the board provides two MIPI CSI ports (4 lanes per camera) for higher resolution and frame rate.

The previous Jetson Nano Developer Kit allowed developers to easily deploy AI applications. The new Jetson Orin Nano Developer Kit pushes the boundaries of entry-level AI development, with 80x the performance of its predecessor. Thus, developers can run intricate AI models such as transformers and advanced robotics applications. Furthermore, Jetson Orin Nano boasts 5.4x CUDA compute capacity, 6.6x CPU horsepower, and 50x the performance per watt than the prior-generation Jetson Nano.

Figure 1. Performance and efficiency comparison between NVIDIA Jetson Orin Nano and NVIDIA Jetson Nano

 

NVIDIA Jetson Orin Nano Developer Kit features

The NVIDIA Jetson Orin Nano Developer Kit includes a special NVIDIA Orin Nano 8 GB module with an SD-card slot, a reference carrier board, preassembled heatsink/fan, a 19 V DC power supply, and an M.2-Key E based wireless networking module. In addition to the bootable microSD card slot, two M.2 Key-M NVMe sockets are provided on the underside of the carrier for high-speed storage.

Figure 2. The Jetson Orin Nano Developer Kit

 

Jetson Orin Nano runs all modern AI models

The Jetson Orin Nano Developer Kit, with up to 40 TOPS of AI performance, can run all modern AI models. This major leap in compute makes the most demanding AI applications possible, including running transformer models right at the edge, which was not possible before with Jetson Nano.

Transformer models are the basis of recent generative AI applications like ChatGPT and DALL-E, which are taking the world by storm. A transformer model learns context and meaning by tracking the relationship between elements in sequential data, eliminating the need for a large labeled dataset.

Get started today with support for:

City Segmentation for segmenting urban cityscapes into different classes

PeopleNet Transformer based on the Deformable Detection Transformer

BERT for NLP

Jetson software accelerates AI and TTM

Jetson Orin Nano Developer Kit runs the NVIDIA AI software stack, with available use-case-specific application frameworks. These include NVIDIA Isaac for robotics, NVIDIA DeepStream for vision AI, and NVIDIA Riva for conversational AI. You can save significant time with NVIDIA Omniverse Replicator for synthetic data generation (SDG), and with NVIDIA TAO Toolkit for fine-tuning pretrained AI models from the NGC catalog.

Figure 3 shows results from running some computer vision benchmarks with Jetson Orin Nano using the upcoming NVIDIA JetPack 5.1.1. These results show that the developer kit raises the bar for entry-level computer vision. Testing included some dense INT8 and FP16 pretrained models from NGC, and an Industry Resnet-50 Benchmark. The benchmark testing included the following:

NVIDIA PeopleNet v2.5 for the highest accuracy people detection

NVIDIA ActionRecognitionNet 2D and 3D models

NVIDIA LPRNet for license plate recognition

NVIDIA DashCamNet, BodyPoseNet for multiperson human pose estimation

ResNet-50 (224×224) model for object detectio

Figure 3. Results from benchmark testing with pretrained models comparing the Jetson Nano to the Jetson Orin Nano 8 GB

 

The Jetson Orin Nano Developer Kit is a versatile platform that supports models trained with NVIDIA TAO Toolkit 4.0, and will soon support newly announced models in TAO Toolkit 5.0. With TAO Toolkit 5.0, developers can take advantage of several state-of-the-art vision transformer models for image classification, object detection, and segmentation use cases. To learn more, see Access the Latest in Vision AI Model Development Workflows with NVIDIA TAO Toolkit 5.0.

NVIDIA Jetson Orin Nano and NVIDIA DeepStream make an ideal combination for edge applications, such as smart retail, smart city intersections, and industrial automation. With the upcoming version of DeepStream, and the introduction of the GXF runtime, Jetson Orin Nano is an ideal platform for running AI graphs that require tight integration with deterministic systems, common in factory automation use cases.

Additionally, you can quickly familiarize yourself with DeepStream by building applications using the latest version of DeepStream Graph Composer, and deploy them to a Jetson Orin Nano with the click of a button.

Figure 4. Build applications in DeepStream Graph Composer and deploy them to Jetson Orin Nano

 

Accelerate robotics applications with NVIDIA Isaac on NVIDIA Jetson Orin

NVIDIA Isaac robotics platform is a powerful, end-to-end platform for the development, simulation, and deployment of AI-enabled robots. Specifically NVIDIA Isaac ROS, a collection of hardware-accelerated packages, makes it easier for ROS 2 developers to build high-performance solutions on the Jetson Orin Nano Developer Kit. The new NVIDIA Isaac ROS DP release optimizes ROS 2 nodes processing pipelines, which can be executed on the Jetson Orin Platform. It also provides new DNN-based GEMS designed to increase throughput.

Figure 4 shows the results of running these robotics packages on the Jetson Orin Nano using the upcoming NVIDIA Isaac ROS DP3 release. The performance is measured under load including message transport costs in RCL for practical benchmarking indicative of real-world performance. Testing included the algorithms seen in the chart (Figure 4), including:

Visual SLAM that enables a robot to compute its location and movement from images by tracking visual features around its environment

April Tags for AprilTag detection and pose estimation

Image Detection 

Image Segmentation

Proximity Segmentation to determine whether an obstacle is within a proximity field and to avoid collisions with obstacles during navigation

Stereo Disparity for taking stereo input images and generating a disparity map of the input image for robot navigation

Figure 5. Performance, latency, and resolution of NVIDIA Isaac ROS GEMs on NVIDIA Jetson Orin Nano 8 GB

Applications:

AI-powered robots

Smart drones

Intelligent vision system

Specification:

GPU: NVIDIA Ampere architecture with 1024 NVIDIA CUDA Cores and 32 Tensor Cores

CPU: 6-core Arm Cortex-A78AE v8.2 64-bit CPU 1.5 MB L2 + 4 MB L3

Memory: 8 GB 128-bit LPDDR5 68 GB/s

Storage: External through microSD slot, External NVMe through M.2 Key M

Power: 7 W to 15 W

Camera: 2x MIPI CSI-2 22-pin Camera Connectors

M.2 Key M: x4 PCIe Gen3

M.2 Key M: x2 PCIe Gen3

M.2 Key E: PCIe (x1), USB 2.0, UART, I2S, and I2C

USBType A: 4x USB 3.2 Gen2 Type C: 1x for Debug and Device Mode

Networking: 1x GbE Connector

Display: DisplayPort 1.2 (+MST)

microSD slot: UHS-1 cards up to SDR104 mode

Others: 40-pin Expansion Header (UART, SPI, I2S, I2C, GPIO)12-pin button header4-pin fan header DC power jack

Dimensions: 100 mm x 79 mm x 21 mm(Height includes feet, carrier board, module, and thermal solution)

Documents:

Getting Started Guide

User Guide

JetPack SDK

FAQ

Product Includes:

NVIDIA Jetson Orin nano 8GB Developer Kit x1