New AI technology delivers unprecedented on-device intelligence for IoT : Page 4 of 5

April 06, 2020 //By Thomas Ensergueix – Senior Director, Low Power IoT Business
Endpoint AI is accessible to many more with simplified software development on Arm
Arm has expanded its AI platform to bring the benefits of AI to billions enabling more distributed compute from the cloud and edge to endpoint devices, and providing new opportunities, such as more natural human interaction on smaller devices.

The Cortex-M55 and the Ethos-U55 (optional) can be incorporated into an SoC design with the lowest risk and development cost with the Corstone-300 reference design. It integrates the processor, security components (e.g. the SIE-300 AXI5 TrustZone controllers) and system IP (e.g. the Power Control Kit PCK-600). Since trust is key for IoT devices to deliver real value, the Corstone-300 also simplifies security implementation with an optimized AXI5 system for TrustZone, accelerating the route to PSA Certified silicon and devices. Developers can speed time to market with open-source software, such as Trusted Firmware-M, and familiar development tools.

Cortex-M55 and Ethos-U55 extend Arm's AI portfolio of CPUs, GPUs and NPUs into a new class, and ultimately provide more options for device makers to balance performance, cost and energy efficiency for endpoint AI. It is certainly possible to build silicon today with a combination of a CPU, a DSP and an NPU to get the same raw hardware horsepower as the Cortex-M55 and Ethos-U55 combination. However, once the hardware is built, how do hundreds of programmers write, debug and tune code for chips with two three separate tool chains, three compilers, three debuggers, three probes? This introduces complexity and slows time to market; however, Arm ensures these hardware capabilities are all integrated into a single, high productivity toolchain, supported by optimized software libraries and a broad knowledge base. Most importantly and as mentioned, they work with existing ML frameworks, such as TensorFlow Lite Micro, and enable developers to draw on support from an existing, broad software and tools ecosystem. This makes it vastly easier and quicker to design, develop and maintain AI-based IoT applications with the lowest risk and cost possible.



Endpoint AI is accessible to many more with simplified software development on Arm.

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