Ms. Siri Narla Profile

Siri Narla

at Georgia Institute of Technology

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Proceedings Article | 3 October 2022 Presentation + Paper

Crosslayer modeling and design for spin-orbit-torque and magnetoelectric memory arrays and compute-in-memory

Piyush Kumar, Siri Narla, Yu-Ching Liao, Azad Naeemi

Proceedings Volume 12205, 1220504 (2022) https://doi.org/10.1117/12.2633519

KEYWORDS: Switching, Transistors, Instrument modeling, Magnetism, Spintronics, Polarization, Ferroelectric materials, Device simulation, Resistance, Content addressable memory

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A diverse set of novel materials, physical phenomena, logic/memory devices, and circuit/system options/concepts are being pursued globally to design and develop the next generations of information storage and processing platforms. Many of these potential options are vastly different compared to their conventional counterparts and cannot be used as drop-in replacements. This research should therefore include several levels of abstraction, and must take a holistic approach to truly leverage the benefits offered by the promising options. Among the emerging materials and devices, magnetic and multiferroic devices are of particular interest thanks to their non-volatility, density, energy efficiency and durability. This paper presents a co-design framework for magnetic materials, devices, and memory arrays based on a hierarchy of physical models. Two major categories of devices are considered: spin-orbit-torque (SOT) and magnetoelectric (ME) random access memories. Circuit compatible experimentally validated/calibrated physical models for such devices is presented and used to optimize material and device parameters to minimize energy/delay for read and write operations for various target error rates. Finally, novel SOT and ME based cell designs for ternary content-addressable memories (TCAM) are presented and their potential performance is quantified against their SRAM and FeFET based designs using a comprehensive modeling and benchmarking framework.

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