Area-Efficient Multibit-per-Cell Architecture for Spin-Orbit-Torque Magnetic Random-Access Memory With Dedicated Diodes

Ahmed, Karim Ali; Li, Fēi; Lua, S. Y. H.; Heng, Chun-Huat

doi:10.1109/lmag.2018.2829111

Cited by 11 publications

(8 citation statements)

References 17 publications

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“…Such different vacancies distributions naturally lead to various metastable GST structures, and the most thermodynamically favorable GST phase was reported to have a highly ordered distribution of the vacancies in {111} planes, defined as GST phase 2 that comprises GST building blocks periodically separated by the vacancy layers between adjacent Te-Te planes [50], as illustrated in Figure 3(b). The Ge and Sb atoms are still off-center within Te(GeSb) 6 , as similar to phase 1, and the degree of vacancy ordering strongly pertains to the Te-Te distance. The distribution of Ge and Sb atomic species is random within individual cation layers, while the ordering of Sb and Ge atoms are preferable to be found in the cation layers next to the vacancy layers and in the middle of GST building units, respectively.…”

Section: Phase-change Materialsmentioning

confidence: 95%

“…As Moore's law approaches its limits, further boosting the integration density of conventional volatile memories becomes extremely difficult [1]. In view of this, the concept of properly scalable non-volatile memory has become a topic of intensive study over the past decade, resulting in the emergence of several non-volatile memory devices such as ferroelectric RAM (FeRAM) [2][3][4], magnetic RAM (MRAM) [5][6][7], phase-change RAM (PCRAM) [8][9][10], and resistive RAM (RRAM) [11][12][13]. Out of these competing possibillities, PCRAM offers the widest range of advantages including superb scalability [14], fast write/read speeds [15], low energy consumption [16], and a long data retention time [17].…”

Section: Introductionmentioning

confidence: 99%

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Overview of Phase-Change Materials Based Photonic Devices

Wang

2020

IEEE Access

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Non-volatile storage memory is widely considered to be one of the most promising candidates to replace dynamic random access memory and even static random access memory. It has recently received particular attention because of its great potential for brain-like neuromorphic applications. Phase-change materials, also known as Chalcogenide alloys, exhibit several especially advantageous traits for non-volatile applications. These include scalability, fast switching speeds, low switching energy and outstanding thermal stability. As a result, most research to date has sought to identify electrical applications for phase-change materials in relation to phase-change random access memory, phase-change memristors and phase-change neuro networks, while overlooking their potential for non-volatile photonic applications. To address this issue, we provide a comprehensive review that examines the remarkable physical properties of phase-change materials for photonic applications, together with emerging phase-change photonic devices. The review begins by presenting the atomic structure and physical properties of phase-change materials, followed by an elaboration of the issues that phase-change materials are currently facing and the strategies being developed to overcome them. The current state-of-the-art and technical challenges confronting phasechange materials in relation to non-volatile photonic applications, such as phase-change photonic memory, phase-change photonic neuro-networks, phase-change metasurfaces and phase-change color displays are then considered. The review concludes by discussing the outlook for successfully implementing phasechange materials in emerging photonic domains.

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Section: Phase-change Materialsmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Overview of Phase-Change Materials Based Photonic Devices

Wang

2020

IEEE Access

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“…Ali et al [18] extended the SLC diode-based SOT-MRAM proposal to be a multibit per cell (MBC). Their proposed design, shown in Figure 4, relies on a metaloxide-metal (MOM) diode (or also known as selector) stacked over an MTJ (forming a D-MTJ) to replace the task of the read Tx in controlling the read current flow.…”

Section: Multi-bit Per Cell Dedicated Diode (Mbc-dd) Sot-mrammentioning

confidence: 99%

“…3D structure of the proposed dedicated diode multi-bit per cell (MBC) DD SOT-MRAM with (a) uniform HM electrode and MTJs with different t fl[18], (b) different HM width and MTJs with similar t fl[18].…”

mentioning

confidence: 99%

Area-Efficient Spin-Orbit Torque Magnetic Random-Access Memory

Ali¹

2020

Integrated Circuits/Microchips

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Spin-orbit torque magnetic random-access memory (SOT-MRAM) has shown promising potential to realize reliable, high-speed and energy-efficient on-chip memory. However, conventional SOT-MRAM requires two access transistors per cell. This limits the use of conventional SOT-MRAM in high-density memories. Thus, various architectures in the literature have been proposed to improve the area efficiency of the SOT-MRAM. In this chapter, these proposals are divided into two categories: non-diode-based SOT-MRAM and diode-based SOT-MRAM cells. The non-diode-based proposals may result in a 1-bit effective area saving up to 50% compared to the conventional SOT-MRAM, whereas the diode-based designs may result in 1-bit effective area-saving of up to 75%. However, the area saving may be accompanied by higher energy and reliability issue penalties. Therefore, here, the various proposals in the literature are presented, highlighting the pros and cons of each design. Moreover, the technology requirements to realize these proposals are discussed. Finally, the various designs are evaluated from both cell and system level perspectives.

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“…Recent progress in the development of non-volatile nanoscale random access memories (RAMs) has led to them offering a viable solution to the von Neumann bottleneck. These devices come mainly in the form of ferroelectric RAM (FeRAM) [9][10][11][12][13], magnetic RAM (MRAM) [14][15][16][17][18], phase-change RAM (PCRAM) [19][20][21][22][23], and resistive RAM (RRAM) [24][25][26][27][28] (see Figure 2). They usually have two distinct physical states relating to when they are either immune to or subject to external excitations.…”

Section: Introductionmentioning

confidence: 99%

In-Memory Logic Operations and Neuromorphic Computing in Non-Volatile Random Access Memory

Xiong

et al. 2020

Materials

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Recent progress in the development of artificial intelligence technologies, aided by deep learning algorithms, has led to an unprecedented revolution in neuromorphic circuits, bringing us ever closer to brain-like computers. However, the vast majority of advanced algorithms still have to run on conventional computers. Thus, their capacities are limited by what is known as the von-Neumann bottleneck, where the central processing unit for data computation and the main memory for data storage are separated. Emerging forms of non-volatile random access memory, such as ferroelectric random access memory, phase-change random access memory, magnetic random access memory, and resistive random access memory, are widely considered to offer the best prospect of circumventing the von-Neumann bottleneck. This is due to their ability to merge storage and computational operations, such as Boolean logic. This paper reviews the most common kinds of non-volatile random access memory and their physical principles, together with their relative pros and cons when compared with conventional CMOS-based circuits (Complementary Metal Oxide Semiconductor). Their potential application to Boolean logic computation is then considered in terms of their working mechanism, circuit design and performance metrics. The paper concludes by envisaging the prospects offered by non-volatile devices for future brain-inspired and neuromorphic computation.

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Area-Efficient Multibit-per-Cell Architecture for Spin-Orbit-Torque Magnetic Random-Access Memory With Dedicated Diodes

Cited by 11 publications

References 17 publications

Overview of Phase-Change Materials Based Photonic Devices

Overview of Phase-Change Materials Based Photonic Devices

Area-Efficient Spin-Orbit Torque Magnetic Random-Access Memory

In-Memory Logic Operations and Neuromorphic Computing in Non-Volatile Random Access Memory

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