Jetson Nano

Welcome to RidgeRun's guide to NVIDIA®Jetson Nano™	NVIDIA®Jetson Nano™ Introduction Overview Developer Kit Getting Started Development Getting into the Board Building Kernel from Source GStreamer Accelerated Elements Example Pipelines Capture and Display Encoding Decoding Streaming Transforming Contact Us
NVIDIA®Jetson Nano™
NVIDIA®Jetson Nano™ is an embedded system-on-module (SoM) from the NVIDIA Jetson family. It is a small, and powerful computer for embedded AI systems and IoT that delivers the power of modern AI in a low-power and low-cost platform. This is the smallest, cheapest, and less power consumption device of the Jetson Family, but still maintains a high computing capability that delivers the performance and power efficiency needed for the latest visual computing applications, making it a very good option for embedded deep learning, computer vision, IoT, graphics, and GPU computing projects. Jetson Nano supports high-resolution sensors, can process many sensors in parallel and can run multiple modern neural networks on each sensor stream. It also supports many popular AI frameworks, making it easy for developers to integrate their preferred models and frameworks into the product. The Jetson Nano comes with 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. It provides 472 GFLOPS of FP16 compute performance with 5-10W of power consumption. Jetson Nano runs Linux and it's compatible with all the Jetson family software stack (Jetpack, L4T, CUDA, DeepStream, TensorRT, CuDNN, AI Frameworks ...). As it is common with all the NVIDIA Jetson Family devices, this platform has huge support from NVIDIA, Jetson Ecosystem Partners, and the community. Jetson Nano comes in two versions — the $99 devkit for developers, makers, and enthusiasts and the $129 production-ready module for companies looking to create mass-market edge systems. The Jetson Nano Developer Kit is an easy to use, low power consumption (5-10W), small and powerful computer/platform that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing out of the box. This kit makes more accessible the power of modern AI to makers, learners, and embedded developers. See also Xavier Getting Started Guide for Jetson TX1 Compiling Jetson TX1/TX2 source code Installing JetPack 4.2 - Nvidia SDK Manager
RidgeRun support
RidgeRun is an official NVIDIA Partner and we have created this extensive set of documentation to support our joint customers. If you have any questions on the content, please contact us through our Contact Us page. RidgeRun provides support for embedded Linux development for NVIDIA's platforms, specializing in the use of hardware accelerators in multimedia applications. RidgeRun's products take full advantage of the accelerators that NVIDIA exposes to perform transformations on the video streams achieving great performance on complex processes. This page contains detailed guides and information on how to get started with the NVIDIA Jetson Nano and start using its full capabilities. To get up-to-speed with your NVIDIA Jetson Nano board, start by clicking below: Error creating thumbnail: Unable to save thumbnail to destination RidgeRun Resources Quick Start Client Engagement Process RidgeRun Blog Homepage Technical and Sales Support RidgeRun Online Store RidgeRun Videos Contact Us Contact Us Visit our Main Website for the RidgeRun Products and Online Store. RidgeRun Engineering informations are available in RidgeRun Professional Services, RidgeRun Subscription Model and Client Engagement Process wiki pages. Please email to support@ridgerun.com for technical questions and contactus@ridgerun.com for other queries. Contact details for sponsoring the RidgeRun GStreamer projects are available in Sponsor Projects page.