tinyML Asia 2021 Mahesh Mehendale: ML@ExtremeEdge of Always-on Intelligent Sensor Networks
Mahesh MEHENDALE, Adjunct Professor & TI Fellow and leads the Nano-power Foundational Technology at Kilby Labs, Texas Instruments & IISc Bangalore
In Always-on intelligent IoT sensor nodes, detecting the event of interest at the End Node (Extreme Edge) as against on the Gateway or Cloud provides significant advantages including low latency, privacy, reduced communication bandwidth, and operation with no or unreliable connectivity. Deep Neural Networks (DNNs) have emerged as the promising machine learning technology for a number of such sensing applications including voice activity detection, voice command recognition, acoustic signature detection, object detection, face recognition, anomaly detection, etc. working with different sensing modalities – including acoustic, image, vibration, current, voltage and others. DNNs are computed and data-intensive, so implementing them on highly resource-constrained (both in terms of cost and power) End Nodes while meeting latency/real-time constraints presents a huge challenge. In this talk, we present system, algorithm, architecture, circuit, and process technology level optimization techniques and highlight how co-optimization across all these levels is key to achieving the target two to three orders of magnitude reduction in area-power FoM.