Ovonic Switches Enable Energy-Efficient Dendrite-like Computing

Over the past decade, dendrites of neurons, which were previously thought to perform only information pooling and networking, have now been shown to express complex temporal dynamics, Boolean-like logic, arithmetic, signal discrimination, and edge detection. Mimicking this rich functionality could offer a powerful primitive for neuromorphic computing. Here, using Ovonic threshold switching in Sb-Te-doped GeSe, we demonstrate a single two-terminal component capable of self-sustained dynamics and universal Boolean logic in addition to XOR operations (which is traditionally thought to require a network of active components). We then employed logic-driven dynamics to detect and estimate the gradients of edges in images. The Ovonic switch exhibits properties of a half adder and a full adder in addition to discriminative logic accommodating inhibitory and excitatory signals. We show that this simple computational primitive offers a highly improved energy efficiency. As such, this work paves the path for potentially emulating dendrites for efficient postdigital neuromorphic computing.