Resistive switching in ferroelectric synaptic weights
Elisabetta Morabito
Resistive switching in ferroelectric synaptic weights.
Rel. Carlo Ricciardi. Politecnico di Torino, Master of science program in Nanotechnologies For Icts, 2023
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Abstract
ResistiveThe Von Neumann architecture has determined the characteristics and working principles of classical computing paradigms since 1945. CMOS technology had a major role in the improvement of modern computers thanks to advancements in device scaling. However, recent years saw the advancement in deep learning algorithms built on brain-inspired networks of artificial neurons, also referred to as artificial neural networks (ANNs), con- currently with an exponential increase of processed data, representing a big challenge for conventional computer hardware. The "bottleneck" of the Von Neumann architecture is due to the unavoidable movement of data between the central processing unit (CPU) and memory, causing latency and high energy consumption.
Neuromorphic computing allows the hardware implementation of the "in-memory" computing paradigm taking ad- vantage of cross-point technologies where the data can be processed and stored within the same site
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