GreenWaves Introduces Ultra-Low Power IoT Application Processor for Next Generation Devices

French fabless semiconductor startup GreenWaves announced its latest IoT application...

Image: GreenWaves Technologies

French fabless semiconductor startup GreenWaves announced its latest IoT application processor GAP9 – an ultra-low power embedded solution for AI processing in IoT devices. GAP9 combines architectural enhancements and an industry-leading Global Foundries 22nm FDX semiconductor process to deliver a peak cluster memory bandwidth of 41.6 GB/sec and up to 50 GOPS combined compute power at an overall power consumption of 50mW.

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Using GAP9, consumers can embed machine learning and signal processing capabilities into battery operated or energy harvesting devices such as IoT sensors in smart building, consumer and industrial markets and consumer and medical wearable devices. Compared to the company’s similar products, GAP9 reduces energy consumption by 5 times while enabling inference on neural networks 10 times larger, reports Business Wire.

“GAP9 enables a new level of capabilities for embedding combinations of sophisticated machine learning and signal processing capabilities into consumer, medical and industrial product applications,” said Loic Lietar, CEO of GreenWaves Technologies. “The GAP family provides product designers with a powerful, flexible solution for bringing the next generation of intelligent devices to market.”

Image: GreenWaves Technologies

Built on the same GAP architectural attributes as its predecessor GAP8, GAP9 adds support for floating-point arithmetic across all cores based on an innovative transprecision floating-point unit capable of handling floating-point numbers in 8, 16, and 32-bit precision with support for vectorization. GAP9 also extends GAP8’s support for fixed-point arithmetic with support for vectorized 4-bit and 2-bit operations.

Incorporating bi-directional multichannel, synchronized digital audio interfaces GAP9 is a perfect fit for sophisticated wearable audio products. It also incorporates both CSI2 and parallel camera interfaces allowing the use of low resolution, low power camera for scene analysis and then extract a region of interest from high-resolution, higher power camera for analysis of scene details.

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The new processor also handles sophisticated neural networks such as MobileNet V1 with ease processing a 160 x 160 image with a channel scaling of 0.25 in just 12ms with a power consumption of 806μW/frame/second.

Additional security features in GAP9 protects device makers’ firmware and models while also protecting devices from tampering and a Physically Unclonable Function (PUF) unit that allows devices to be uniquely and securely identified.

Sam Draper
December 16, 2019

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