tinyML Asia 2023 – Roger Levinson: All Analog Compute for Ultra-Low Power Neural Network Processing

All Analog Compute for Ultra-Low Power Neural Network Processing
Roger LEVINSON
CEO
Blumind

Blumind has developed an all-analog neural network processor capable of realizing nW consumption on real world problems. Leveraging standard CMOS with no special masking steps, Blumind has combined the best attributes from neuromorphic compute, precision analog processing, device physics for in memory compute and data science to create the AMPLTM solution. In this presentation we will cover the fundamentals of the Blumind architecture, including the unique approach to leveraging standard CMOS devices for coefficient storage and synaptic computation. We will provide an example audio solution in which the RNN achieves multiple KWD in less than 100nW leveraging an all analog feature extraction implementation. We will present a CNN vision solution based upon the AMPLTM architecture for always on object detection, such as human presence detection which consumes less than 1uJ per inference. The technical and market benefits of direct connection to analog sensors and direct processing of analog signals will be outlined and the significant 20X power advantage of such a solution in the audio application will be described. Blumind has demonstrated the solution in silicon and is currently building its first commercial product and open to custom collaboration and partnership.

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