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  Subjects -> ELECTRONICS (Total: 207 journals)
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IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Online) 2329-9231
Published by IEEE Homepage  [228 journals]
  • Valley-Spin Hall Effect-Based Nonvolatile Memory With
           Exchange-Coupling-Enabled Electrical Isolation of Read and Write Paths

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      Authors: Karam Cho;Sumeet Kumar Gupta;
      Pages: 157 - 165
      Abstract: Valley-spin hall (VSH) effect in monolayer WSe2 has been shown to exhibit highly beneficial features for nonvolatile memory (NVM) design. Key advantages of VSH-based magnetic random access memory (VSH-MRAM) over spin orbit torque (SOT)-MRAM include access transistor-less compact bit-cell and low-power switching of perpendicular magnetic anisotropy (PMA) magnets. Nevertheless, large device resistance in the read path ( $R_{S}$ ) due to low mobility of WSe2 and Schottky contacts deteriorates sense margin (SM), offsetting the benefits of VSH-MRAM. To address this limitation, we propose another flavor of VSH-MRAM that (while inheriting most of the benefits of VSH-MRAM) achieves lower $R_{S}$ in the read path by electrically isolating the read and write terminals. This is enabled by coupling VSH with electrically isolated but magnetically coupled PMA magnets via interlayer exchange coupling. Designing the proposed devices using object-oriented micromagnetic framework (OOMMF) simulation, we ensure the robustness of the exchange-coupled PMA system under process variations. To maintain a compact memory footprint, we share the read access transistor across multiple bit-cells. Compared with the existing VSH-MRAMs, our design achieves 39%–42% and 36%–46% reduction in read time and energy, respectively, along with $1.1times - 1.3times $ larger SM at a comparable area. This comes at the cost of $1.7times $ and $2.0times $ increase in write time and energy, respectively. Thus, the proposed design is suitabl- for applications in which reads are more dominant than writes.
      PubDate: Dec. 2022
      Issue No: Vol. 8, No. 2 (2022)
       
  • Self-Reset Schemes for Magnetic Domain Wall-Based Neuron

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      Authors: Debasis Das;Xuanyao Fong;
      Pages: 166 - 172
      Abstract: Spintronic artificial spiking neurons are promising due to their ability to closely mimic the leaky integrate-and-fire (LIF) dynamics of the biological LIF spiking neuron. However, the neuron needs to be reset after firing. Few of the spintronic neurons that have been proposed in the literature discuss the reset process in detail. In this article, we discuss the various schemes to achieve this reset in a magnetic domain wall (DW)-based spintronic neuron in which the position of the DW represents the membrane potential. In all the spintronic neurons studied, the neuron enters a refractory period and is reset when the DW reaches a particular position. We show that the self-reset operation in the neuron devices consumes energy that can vary from several pJ to a few fJ, which highlights the importance of the reset strategy in improving the energy efficiency of spintronic artificial spiking neurons.
      PubDate: Dec. 2022
      Issue No: Vol. 8, No. 2 (2022)
       
  • Review of Magnetic Tunnel Junctions for Stochastic Computing

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      Authors: Brandon R. Zink;Yang Lv;Jian-Ping Wang;
      Pages: 173 - 184
      Abstract: Modern computing schemes require large circuit areas and large energy consumption for neuromorphic computing applications, such as recognition, classification, and prediction. This is because these tasks require parallel processing on large datasets. Stochastic computing (SC) is a promising alternative to conventional binary computing schemes due to its low area cost, low processing power, and robustness to noise. However, the large area and energy costs for random number generation with CMOS-based circuits make SC impractical for most hardware implementations. For this reason, beyond-CMOS approaches to random number generation have been investigated in recent years. Spintronics is one of the most promising approaches due to the intrinsic stochasticity of the magnetic tunnel junction (MTJ). In this review article, we provide an overview of the literature published in recent years investigating the tunable, intrinsic stochasticity of MTJs and proposing practical methods for random number generation using spintronic hardware.
      PubDate: Dec. 2022
      Issue No: Vol. 8, No. 2 (2022)
       
  • High-Density Spin–Orbit Torque Magnetic Random Access Memory With
           Voltage-Controlled Magnetic Anisotropy/Spin-Transfer Torque Assist

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      Authors: Piyush Kumar;Azad Naeemi;
      Pages: 185 - 193
      Abstract: This article explores an area saving scheme for spin–orbit torque (SOT) magnetic random access memory (MRAM) by sharing the SOT channel and write transistor among multiple magnetic tunnel junctions (MTJs). We use two write mechanisms to selectively write the MTJs, i.e., voltage-controlled magnetic anisotropy (VCMA)-assisted write in the presence of an external magnetic field and field-free spin-transfer torque (STT)-assisted write. Using micromagnetic simulations that are augmented by the rare-event enhancement, we study various trade-offs among write current, time, and energy, write error rate (WER), and the number of MTJs on an SOT channel. We quantify the issue of IR drop on the SOT channel as a function of the SOT layer thickness and number of MTJs. Our results show having more than four MTJs on an SOT channel poses major challenges in terms of IR drop and WER. In addition, we evaluate the impact of the proposed scheme on read performance.
      PubDate: Dec. 2022
      Issue No: Vol. 8, No. 2 (2022)
       
  • Random Bitstream Generation Using Voltage-Controlled Magnetic Anisotropy
           and Spin Orbit Torque Magnetic Tunnel Junctions

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      Authors: Samuel Liu;Jaesuk Kwon;Paul W. Bessler;Suma G. Cardwell;Catherine Schuman;J. Darby Smith;James B. Aimone;Shashank Misra;Jean Anne C. Incorvia;
      Pages: 194 - 202
      Abstract: Probabilistic computing using random number generators (RNGs) can leverage the inherent stochasticity of nanodevices for system-level benefits. Device candidates for this application need to produce highly random “coinflips” while also having tunable biasing of the coin. The magnetic tunnel junction (MTJ) has been studied as an RNG due to its thermally-driven magnetization dynamics, often using spin transfer torque (STT) current amplitude to control the random switching of the MTJ free layer (FL) magnetization, here called the stochastic write method. There are additional knobs to control the MTJ-RNG, including voltage-controlled magnetic anisotropy (VCMA) and spin orbit torque (SOT), and there is a need to systematically study and compare these methods. We build an analytical model of the MTJ to characterize using VCMA and SOT to generate random bit streams. The results show that both methods produce high-quality, uniformly distributed bitstreams. Biasing the bitstreams using either STT current or an applied magnetic field shows a sigmoidal distribution versus bias amplitude for both VCMA and SOT, compared to less sigmoidal for stochastic write. The energy consumption per sample is calculated to be 0.1 pJ (SOT), 1 pJ (stochastic write), and 20 pJ (VCMA), revealing the potential energy benefit of using SOT and showing using VCMA may require higher damping materials. The generated bitstreams are then applied to two tasks: generating an arbitrary probability distribution and using the MTJ-RNGs as stochastic neurons to perform simulated annealing, where both VCMA and SOT methods show the ability to effectively minimize the system energy with a small delay and low energy. These results show the flexibility of the MTJ as a true RNG and elucidate design parameters for optimizing the device operation for applications.
      PubDate: Dec. 2022
      Issue No: Vol. 8, No. 2 (2022)
       
 
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