Multiphysics modeling of Ge2Sb2Te5 based synaptic devices for brain inspired computing
Author
Demirağ, Yiğit
Advisor
Özbay, Ekmel
Date
2018-07Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Modeling nanoscale devices that emulate the functionality of synapses of the
biological brain is a fundamental operation for developing brain-inspired computational
systems. Phase-change material based synaptic devices offer promising
performance in speed, spatial and power efficiency metrics, up to human brain
level, when connected in a massively parallel crossbar array architecture. In
this work, we modeled electrothermal characteristics of a single synaptic device
consisting of phase-change material based memory and its selector. First, we
proposed a finite element method based simulation framework for modeling electrical,
thermal and probabilistic crystallization dynamics of the memory unit.
Gradual phase transitions that form device memory between amorphous and
crystalline states are studied under nanosecond voltage pulses. Second, we implemented
time and temperature dependent resistance drift saturation model for
phase-change material based selector device. Our model is in close agreement
with the ultrafast saturation phenomena which is observed for the first time in
fabricated devices with 8 nm node technology.
Keywords
Phase Change MemoryDevice Modeling
Synaptic Device
Neuromorphic Computing
GST
Multiphysics