As an Arm partner, we had early access to the new extensions and we can reveal that our already lean sound recognition software (ai3) will be at least 50% faster when running on chips based on the new Armv8.1-M architecture. As a result, we believe that the performance enhancements made possible by these new vector extensions will offer a major step change in tinyML.
Commenting on the launch, Dr Chris Mitchell, Audio Analytic’s CEO and Founder, said: “There is considerable demand to run advanced AI, like sound recognition, at the edge. Principally because cloud infrastructure is expensive and edge-based processing offers privacy benefits for end users. Now, thanks to Arm, consumer and IoT devices can deliver supercharged AI at even lower-power and lower-cost. The net result is being able to fit more features onto a device or being able to offer AI on an AA battery.”
Audio Analytic’s VP of Technology, Dominic Binks added: “With Helium, next generation Cortex-M processors gain the vectorising capabilities of NEON-class processors, along with other new capabilities, which together deliver tangible improvements in performance, and cost, in the microcontroller space.”