tinyML Asia 2022 Yuya Ling: Xylo: A sub-mW, low-dimensional Signal Neuromorphic Processor скачать в хорошем качестве

tinyML Asia 2022 Yuya Ling: Xylo: A sub-mW, low-dimensional Signal Neuromorphic Processor

Xylo: A sub-mW, low-dimensional Signal Neuromorphic Processor Yuya LING, Algorithm Application Engineer, SynSense The neuromorphic industry is growing rapidly, with significant contributions from large players such as Intel and IBM. SynSense is developing approaches for machine vision, bio- and industrial-signal processing, based on binary event-based neuronal architectures and communication emulated on low-power neuromorphic hardware. Our advantages are our long experience in designing low-power neuromorphic circuits, and our expertise in theory of neuromorphic computation. Xylo is a new family of ultra-low-power (1mW) neuromorphic ML inference processors designed by SynSense. Xylo is a fully programmable, ultra-low power neuromorphic architecture supporting feed forward, recurrent, reservior and other complex spiking neural networks. Xylo-A2 also integrates a dedicated analog Audio-Front-End supporting low-power real-time processing of single-channel audio signals. Xylo provides efficient simulation of spiking leaky integrate-and-fire neurons with exponential input synapses. Xylo is highly configurable, and supports individual synaptic and membrane time-constants, thresholds and biases for each neuron. Xylo supports arbitrary network architectures, including recurrent networks, for up to 1000 neurons. With the adaption of SynSense’s novel spiking neural network algorithms, Xylo is able to power TinyML applications continuously at a few hundred uW.