Tunable synaptic working memory with volatile memristive devices
Year: 2023
Type: article
Abstract: Different real-world cognitive tasks evolve on different relevant timescales. Processing these tasks requires memory mechanisms able to match their specific time constants. In particular, the working memory (WM) utilizes mechanisms that span orders of magnitudes of timescales, from milliseconds to seconds or even minutes. This plentitude of timescales is an essential ingredient of WM tasks like visual or language processing. This degree of flexibility is challenging in analog computing hardware because it requires the integration of several reconfigurable capacitors of different size. Emerging volatile memristive devices present a compact and appealing solution to reproduce reconfigurable temporal dynamics in a neuromorphic network. We present a demonstration of WM using a silver-based memristive device whose key parameters, retention time and switching probability, can be electrically tuned and adapted to the task at hand. First, we demonstrate the principles of WM in a small scale hardware to execute an associative memory task. Then, we use the experimental data in two larger scale simulations, the first featuring WM in a biological environment, the second demonstrating associative symbolic WM.
Authors: Saverio Ricci, David Kappel, Christian Tetzlaff, Daniele Ielmini, Erika Covi
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,700
OpenAlex ID: W4387483879