Every day the number of sensors and connected devices at the edge continues to grow at an exponential rate. Analog electronic sensors connected to digital compute devices allow systems to gain situational awareness and optimize performance to achieve high productivity and efficiency. There are multiple approaches to tackling the processing challenges from the explosion of sensor data that is being produced at the edge:
- Send all the collected data to the cloud for processing
- This approach adds latency and high data transmission costs
- Process all the collected data at the edge (near the analog-digital boundary)
- This approach demands higher processing locally
- Distribute the data across the cloud and the edge
- This hybrid approach brings a balance between latency, compute, data transmission costs, and power.
A hybrid approach of distributed computing can be achieved by using an adaptive compute platform that is scalable, efficient, and low power at the edge, which can seamlessly connect to the cloud to transfer bi-directional data. To give users a jump-start on this journey, the entire AMD Kria™ Starter Kit portfolio, including its Kria SOMs, is certified to run the most popular IoT management systems available - AWS IoT Greengrass and the Azure IoT Edge.
The AMD Kria Starter Kit portfolio includes out-of-the-box ready developer platforms for designing vision AI, robotics and industrial, and motor control and DSP applications. AMD Kria Starter Kits allow embedded software developers without FPGA expertise to easily get started developing unique edge applications and solutions for production volume deployment with the Kria K26 SOM. Kria SOM-equipped heterogeneous computing can address edge compute requirements with low latency, low power, and determinism while taking on sensor fusion and AI distributed between cloud and edge. By being certified for AWS IoT Greengrass and Azure IoT Edge, getting started with AMD has never been easier.
What are IoT management systems and why do they matter?
In a typical deployment, there will be multiple edge devices connected with sensors that are talking to the cloud. An IoT management system allows users to register these edge devices to establish communication to the cloud, create groups, collect data, push updates, and communicate locally with other edge devices, all while keeping security at the forefront!
AWS IoT Greengrass is an open-source IoT edge runtime and cloud service that helps you build, deploy, and manage IoT applications on your devices. AWS IoT Greengrass enables your devices to collect and analyze data closer to where the data is generated, react autonomously to local events, and communicate securely with other devices on the local network. Greengrass devices can also privately communicate with AWS IoT Core and export IoT data to the AWS Cloud.
Azure offers IoT Edge which is a device-focused runtime that enables you to deploy, run, and monitor containerized Linux workloads. Azure IoT Edge is a feature of Azure IoT Hub and enables you to scale out and manage an IoT solution from the cloud. Azure IoT Edge helps you bring the analytical power of the cloud closer to your devices to drive better business insights and enable offline decision-making.
Getting started with AMD Kria Starter Kits:
Kria SOMs were designed with software engineers in mind, providing familiar design environments without requiring FPGA programming experience. They are enabled by the Kria Starter Kits which are low-cost out-of-the-box ready development platforms certified to work with AWS IoT Greengrass and Azure IoT Edge. Getting started with AMD and achieving the benefits of distributed computing across cloud and edge has never been easier.
AWS IoT Greengrass
Kria KV260 Vision AI Starter Kit
Kria KR260 Robotics Starter Kit
Azure IoT Edge
Kria KV260 Vision AI Starter Kit