The processor is capable of performing sensor processing at under 100 microwatts and can operate as a standalone SoC solution or as the always-on component of a larger system. With a package size of 1.71 mm x 2.51 mm, the NDP102 can be used in a variety of edge AI applications, such as event detection, pressure sensing, gesture recognition, sensor fusion and other condition-based monitoring use cases.
“Our new NDP102 compliments our family of Neural Decision Processors by providing an easily deployed machine learning solution for always-on sensor processing in even the smallest of devices,” said Kurt Busch, CEO of Syntiant. “Whether used in wearables such as personal fitness trackers or with condition-based monitoring systems in the home or factory, the NDP102 serves as a powerful AI interface for sensor processing in a tiny package with near-zero power consumption.”
Syntiant’s architecture has been designed to enable machine learning workloads that are typically run on cloud servers to be performed on-device in the always-on domain.
The company says that the NDP102 allows critical and time-sensitive decisions to be made faster, more reliably and with greater security, such as remote patient monitoring in next-generation medical devices, or event detection in smart homes. It can also continuously monitor vibrations or temperature to detect and act on any anomaly before costly downtime failures occur.
Leveraging the Syntiant Core 1 architecture, the NDP102’s native neural network processing capabilities eliminate the need for intermediate compilers and works seamlessly with machine learning frameworks such as TensorFlow, greatly reducing time to market and helping to assure expected performance.
