Prepare for an Explosion in AI Edge Computing Use Cases
The AI revolution is expanding beyond the cloud and large servers, and into billions of smaller devices at the dynamic edge. Thanks to increasingly performant hardware, we can process data where it is collected or at the network edge, informing the fast and efficient insights required for tomorrow's tailored and autonomous services everywhere.
As many aspects of our lives become software-defined, developers require a radically new, holistic approach to software development to address the major requirements outlined below.
These are triggered by the profusion of data processed outside the datacenter and across connected devices. Governments are building new regulations for security and data privacy, protecting the consumer but increasing software support requirements.
This is essential to allow software developers to leverage performance diversity while optimizing for individual use cases, but without paying heavier software development costs.
Today, this requires more complex and connected software solutions across multivendor stacks. Instead, we need a new approach based on open standards and hardware-agnostic development, enabling greater efficiency and software re-use.
The Important Advantages of Edge Computing
Improve market scalability, reducing the overhead of migrating onto newer generations of SOC for the entire value chain, streamlining legacy support and reducing TCO.
Create more opportunities for differentiation and volume. Minimize vendor lock-in to reduce the high legacy support costs and fragmentation that can impede an ODM’s ability to scale.
Access to a more diverse supply chain. Fast availability of trusted software components for compliance.
Monetize software features sooner with the easiest route to market across platforms. Scale with minimal effort thanks to consistencies across hardware ecosystems.
Arm is at the Heart of Next-Gen Edge Collaboration
Arm is working across hundreds of silicon, software, and manufacturing solution providers to help everyone achieve their full potential within a fully connected and AI-charged edge computing future. Together with Arm software ecosystem partner, Linaro, we are orchestrating new common standards for maximizing insights, efficiencies, opportunities, and compliance. Read our new white paper, which explores the case and evidence for heightening industry collaboration.
Projects Supporting Edge Computing on Arm
The key projects to unleash a new age of opportunity as edge computing evolves on Arm.
ONELab
A web platform facilitating rapid software and firmware testing for interoperability and security compliance. The lab checks for alignment with standards for IoT security from PSA Certified and operating system support from Arm SystemReady.
PARSEC
This Arm ecosystem project sits in the sandbox stage with the Cloud Native Computing Foundation (CNFC). The open-source initiative provides a common API to hardware security and cryptographic services via a platform-agnostic web service. PARSEC decouples workloads from device-specific details, enabling cloud-native development flows for edge developers.
SOAFEE
SOAFEE is an industry-led collaboration between companies to support the development of software-defined vehicles. The group’s goal is to radically simplify vehicle software solutions by creating a shared platform for vehicles using a hardware agnostic, cloud-native architecture.
Arm SystemReady
A set of hardware and firmware standards uniting the Arm ecosystem around a common approach to supporting rich operating systems. Standards center around Base System Architecture (BSA) and Base Boot Requirements (BBR) and include a growing list of supplementary areas for ecosystem collaboration to ensure a framework of interoperability and efficiency for developers.
PSA Certified
PSA Certified is a third-party, independent IoT security evaluation and certification framework. It provides product compliance for hardware, software, and firmware that developers can trust, as well as standardized resources to resolve security and compliance challenges most efficiently across fragmented requirements in IoT and edge computing.