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Grenoble, France, Feb. 26, 2018: GreenWaves Technologies, a fabless semiconductor startup designing disruptive ultra-low power embedded solutions for image, sound and vibration AI processing in sensing devices, today announced its GAP8 Internet of Things (IoT) application processor, along with the availability of the GAP8 Software Development Kit.
GAP8 evaluation boards can be pre-ordered at www.greenwaves-technologies.com/gap8.
The company said GAP8 IoT application processor enabled the cost-effective development, deployment and autonomous operation of intelligent sensing devices that captured, analysed, classified and acted on the fusion of rich data sources such as images, sounds or vibrations.
It added that GAP8 was “uniquely optimised” to execute a large spectrum of image and audio algorithms including convolutional neural network (CNN) inference, with extreme energy efficiency, thanks to an integrated 8-core computational cluster combined with a convolution hardware accelerator. A separate core, within an independent voltage and frequency domain, took care of communication, control and information pre-analysis.
The advantage of these features were they allowed industrial and consumer product manufacturers to integrate artificial intelligence and advanced classification into new classes of wireless sensing devices for IoT applications including image recognition, counting people and objects, machine health monitoring, home security, speech recognition, consumer robotics, wearables and smart toys.
“GAP8 differs radically from the flurry of other AI focused processors, which target either far more complex applications that can’t be battery powered, or much narrower application spaces. Instead, GAP8 is precisely positioned at the crossroads of the AI, IoT and MCU worlds. The autonomous operation enabled by GAP8 dramatically reduces the deployment and operating costs of image, sound and vibration sensing devices, enabling an unprecedented scale of adoption,” said Loïc Liétar, Co-founder and CEO of GreenWaves Technologies. “Furthermore, building on the RISC-V and PULP open source projects has allowed us to bring to market radical innovation with an outstanding capital efficiency at a speed that allows us to promptly serve customer demand.”
For most developers, GAP8 was programmed just like any MCU. When compute-intense tasks needed to be launched they are off-loaded to the cluster through the APIs of a rich compute library included in the GAP8 SDK. A well guided, tool-driven methodology also allows trained CNNs described with an AI framework to be optimized for and ported onto GAP8.
Image Credit: Greenwaves Tech