Skewed Straintronic Magnetotunneling-Junction-Based Ternary Content-Addressable Memory—Part II

Manasi, Susmita Dey; Al-Rashid, Md Mamun; Atulasimha, Jayasimha; Bandyopadhyay, Supriyo; Trivedi, Amit Ranjan

doi:10.1109/ted.2017.2706744

Cited by 11 publications

(9 citation statements)

References 30 publications

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“…In contrast, if we left the nanomagnet with its magnetization oriented, say, to the left, then it will persist in that state for centuries or decades after all power is turned off. This feature can not only be exploited to build non-volatile memory (which is obvious), but it can also be utilized for non-von-Neumann data processing architectures and several other nontraditional circuitry that may eclipse their more conventional counterparts in many applications such as Bayesian inference engines for computing in the presence of uncertainty [15,16], content addressable memory [17,18], machine learning [19], belief networks [20], etc. In a von-Neumann architecture, the processor and memory are two physically separate units and there is a partition between them.…”

Section: Magnetic Switchesmentioning

confidence: 99%

“…We will try to conclude this section by trying to estimate what is the minimum energy that a FINFET type device could dissipate while still being operational. The FINFET of circa 2015 dissipates 130 aJ while working with a voltage supply of 1.2 V. Hence, from Equation 2, the amount of charge that is moved in the channel of the FINFET to switch it on and off is roughly 18 16…”

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confidence: 99%

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Straintronics: Digital and Analog Electronics With Strain-Switched Nanomagnets

Bandyopadhyay

2020

IEEE Open J. Nanotechnol.

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The search for a binary switch that is more energy-efficient than a transistor has led to many ideas, notable among which is the notion of using a nanomagnet with two stable magnetization orientations. The nanomagnet is switched between them with electrically generated mechanical strain. A tiny amount of voltage is required for switching, with energy dissipation on the order of a few to few tens of aJ. Logic gates and memory, predicated on this technology, have been demonstrated in our group. While they indeed dissipate very little energy, they are unfortunately plagued by unacceptably high switching error probability that hinders their application in most types of Boolean logic. Fortunately, they can still be used in applications that are more forgiving of switching errors, e.g. probabilistic computing, analog arithmetic circuits, belief networks, artificial neurons, restricted Boltzmann machines, image processing, and others where the collective activity of many devices acting cooperatively elicit the computing or signal processing function and the failure of a single or few devices does not matter critically. These ultra-energy-efficient strain-switched nanomagnets can also be used for non-computing devices such as microwave oscillators that perform better than spin-torque-nano-oscillators. This short review provides an introduction to this exciting burgeoning field.

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Section: Magnetic Switchesmentioning

confidence: 99%

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confidence: 99%

Straintronics: Digital and Analog Electronics With Strain-Switched Nanomagnets

Bandyopadhyay

2020

IEEE Open J. Nanotechnol.

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“…Instruction sets for running a program do not have to be fetched from a remote memory into a processor since they are stored in situ, cutting down on the time and improving reliability of the computation. This can lead to computers with zero boot delay as well as certain other types of computer architectures that can operate more efficiently than their traditional counterparts built with transistors [18][19][20].…”

Section: Non-volatilitymentioning

confidence: 99%

“…Since t is a function of I, there is some optimization involved in choosing the right amount of current to minimize the energy dissipation. 20 The use of heat assisted switching to lower the critical current has been investigated theoretically [47] while thermally assisted switching of the soft layer of a magnetic tunnel junction that is exchange biased has been experimentally demonstrated [48]. It was shown that a current pulse can raise the temperature of the soft layer above its blocking temperature without significantly affecting the hard layer and that makes it easier to rotate the former's magnetization with a lower current.…”

Section: 2mentioning

confidence: 99%

Energy-efficient switching of nanomagnets for computing: straintronics and other methodologies

et al. 2018

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The need for increasingly powerful computing hardware has spawned many ideas stipulating, primarily, the replacement of traditional transistors with alternate 'switches' that dissipate miniscule amounts of energy when they switch and provide additional functionality that are beneficial for information processing. An interesting idea that has emerged recently is the notion of using two-phase (piezoelectric/magnetostrictive) multiferroic nanomagnets with bistable (or multi-stable) magnetization states to encode digital information (bits), and switching the magnetization between these states with small voltages (that strain the nanomagnets) to carry out digital information processing. The switching delay is ∼1 ns and the energy dissipated in the switching operation can be few to tens of aJ, which is comparable to, or smaller than, the energy dissipated in switching a modern-day transistor. Unlike a transistor, a nanomagnet is 'non-volatile', so a nanomagnetic processing unit can store the result of a computation locally without refresh cycles, thereby allowing it to double as both logic and memory. These dual-role elements promise new, robust, energy-efficient, high-speed computing and signal processing architectures (usually non-Boolean and often non-von-Neumann) that can be more powerful, architecturally superior (fewer circuit elements needed to implement a given function) and sometimes faster than their traditional transistor-based counterparts. This topical review covers the important advances in computing and information processing with nanomagnets, with emphasis on strain-switched multiferroic nanomagnets acting as non-volatile and energy-efficient switches-a field known as 'straintronics'. It also outlines key challenges in straintronics.

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“…Bayesian inference engines [22,23], image processing [24,25], ternary content addressable memory [26], restricted Boltzmann machines [27]) and sub-wavelength antennas [28][29][30] to name a few. There, the high error rate may be tolerable and the excellent energy efficiency is a welcome boon.…”

Section: Introductionmentioning

confidence: 99%

Reliability of Magnetoelastic Switching of Nonideal Nanomagnets with Defects: A Case Study for the Viability of Straintronic Logic and Memory

et al. 2019

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Magneto-elastic (straintronic) switching of bistable magnetostrictive nanomagnets is an extremely energyefficient switching methodology for (magnetic) binary switches that has recently attracted widespread attention because of its potential application in ultra-low-power digital computing hardware. Unfortunately, this modality of switching is also error very prone at room temperature. Theoretical studies of switching error probability of magneto-elastic switches have predicted probabilities ranging from 10 -8 -10 -3 at room temperature for ideal, defect-free nanomagnets, but experiments with real nanomagnets show a much higher probability that exceeds 0.1 in some cases. To understand what causes this large difference, we have theoretically studied the effect of common defects (that occur during fabrication) on magneto-elastic switching probability in the presence of room-temperature thermal noise. Surprisingly, we found that even small defects increase the switching error probabilities by orders of magnitude. This could limit or preclude the application of magneto-elastic (straintronic) binary switches in either Boolean logic or memory, despite their excellent energy-efficiency, and restrict them to non-Boolean (e.g. neuromorphic, stochastic) computing applications. We also studied the difference between magneto-elastic switching with a stress pulse of constant amplitude and sinusoidal time-varying amplitude (e.g. due to a surface acoustic wave) and found that the latter method is more reliable and generates lower switching error probabilities in most cases, provided the time variation is reasonably slow.

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Skewed Straintronic Magnetotunneling-Junction-Based Ternary Content-Addressable Memory—Part II

Cited by 11 publications

References 30 publications

Straintronics: Digital and Analog Electronics With Strain-Switched Nanomagnets

Straintronics: Digital and Analog Electronics With Strain-Switched Nanomagnets

Energy-efficient switching of nanomagnets for computing: straintronics and other methodologies

Reliability of Magnetoelastic Switching of Nonideal Nanomagnets with Defects: A Case Study for the Viability of Straintronic Logic and Memory

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