IEEE Journal on Exploratory Solid-State Computational Devices and Circuits – Journals

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Antiferromagnetic Programmable Neuron: Structure, Training, and Pattern Recognition Applications

Antiferromagnetic Programmable Neuron: Structure, Training, and Pattern Recognition Applications 150 150
Author(s): I. Sotnyk, O. Prokopenko

Abstract:

Artificial neurons based on antiferromagnetic (AFM) spin Hall oscillators (SHOs) are promising elements for creating ultrafast, energy-efficient neuromorphic computing systems. These structures can generate picosecond spikes in response to dc and ac electric currents, thereby mimicking the reaction of biological neurons to an external stimulus. However, conventional AFM neurons have …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 9 – 17
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3633490
Publisher: IEEE

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PERCEL: A Rewritable NVM CIM Incorporating a CTT-Based Per-Cell DAC

PERCEL: A Rewritable NVM CIM Incorporating a CTT-Based Per-Cell DAC 150 150
Author(s): Samyak Chakrabarty, Vinod Jacob, Mohammadreza Zeinali, Georgios Karfakis, Siyun Qiao, Ziyi Guo, Puneet Gupta, Subramanian Iyer, Sudhakar Pamarti

Abstract:

Compute-in-memory (CiM) accelerators perform matrix vector multiplications (MVMs) directly inside memory arrays, reducing data movement and improving both energy efficiency and throughput for artificial intelligence (AI) workloads. To reduce the number of conversions, recent designs use multibit compute cells. Nevertheless, practical multibit CiM still faces a tension among accuracy, efficiency, …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 70 – 77
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3680497
Publisher: IEEE

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OISMA: On-the-Fly In-Memory Stochastic Multiplication Architecture for Approximate Matrix Multiplication

OISMA: On-the-Fly In-Memory Stochastic Multiplication Architecture for Approximate Matrix Multiplication 150 150
Author(s): Shady Agwa, Yihan Pan, Georgios Papandroulidakis, Themis Prodromakis

Abstract:

Artificial intelligence (AI) models are currently driven by a significant upscaling of their complexity, with massive matrix-multiplication workloads representing the major computational bottleneck. In-memory computing (IMC) architectures are proposed to avoid the von Neumann bottleneck. However, both digital/binary-based and analog IMC architectures suffer from various limitations, which significantly degrade …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 56 – 64
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3680281
Publisher: IEEE

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A Novel VGSOT-pMTJ Write Circuit for Hybrid CMOS/MTJ CIM Architecture

A Novel VGSOT-pMTJ Write Circuit for Hybrid CMOS/MTJ CIM Architecture 150 150
Author(s): Prashanth Barla, Ramya Moodakare

Abstract:

Hybrid computation-in-memory (CIM) architecture has emerged as the most promising alternative to overcome the drawbacks of the conventional CMOS-only devices used in the conventional von-Neumann architecture. In the hybrid CIM architecture, a pair of perpendicular magnetic tunnel junctions (pMTJs) is used to store one bit of information. Though there are …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 65 – 69
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3679830
Publisher: IEEE

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LUT-Based Convolutional Tsetlin Machine Accelerator With Dynamic Clause Scaling for Resources-Constrained FPGAs

LUT-Based Convolutional Tsetlin Machine Accelerator With Dynamic Clause Scaling for Resources-Constrained FPGAs 150 150
Author(s): Rashed Al Amin, Roman Obermaisser

Abstract:

The rapid growth of machine learning (ML) workloads, particularly in computer vision applications, has significantly increased computational and energy demands in modern electronic systems, motivating the use of hardware accelerators to offload processing from general-purpose processors. Despite advances in computationally efficient ML models, achieving energy-efficient inference on resource-constrained edge devices …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 45 – 55
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3676833
Publisher: IEEE

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Design and Analysis of a Three-Stream STT-MTJ TRNG With XOR and Majority Voter Logic as Postprocessing Architectures

Design and Analysis of a Three-Stream STT-MTJ TRNG With XOR and Majority Voter Logic as Postprocessing Architectures 150 150
Author(s): M. Satwik Rai, Akshaja Kanugovi, Vinod Kumar Joshi

Abstract:

True random number generators (TRNGs) are critical for hardware security, providing unpredictable entropy for cryptographic applications. Spin-transfer torque magnetic tunnel junction (STT-MTJ) devices offer a promising entropy source due to their low-power consumption, nonvolatility, and stochastic switching behavior. This work presents an MTJ-based TRNG that produces three independent bit streams. …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 36 – 44
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3671608
Publisher: IEEE

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Characterization and Modeling of Multilevel Analog ReRAM Synapses in the Sky130 Process

Characterization and Modeling of Multilevel Analog ReRAM Synapses in the Sky130 Process 150 150
Author(s): Irem Didin, Carl Brando, Ching-Yi Lin, Sahil Shah

Abstract:

Nonvolatile memory devices play a key role in enabling energy-efficient computing. Among them, analog nonvolatile memories such as resistive random access memory (ReRAM) offer high density and low power compared to conventional digital memories. However, their analog nature introduces device-level variability that impacts computational accuracy. This work presents the characterization …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 27 – 35
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3670667
Publisher: IEEE

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Special Topic on Modeling and Simulation of Emerging Materials, Devices, and Circuits for Energy-Efficient Computing

Special Topic on Modeling and Simulation of Emerging Materials, Devices, and Circuits for Energy-Efficient Computing 150 150
Author(s): Sumeet Gupta

Abstract:

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Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): iv – vi
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3662448
Publisher: IEEE

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Coupled Simulation Methodology for In-Memory Computing Systems

Coupled Simulation Methodology for In-Memory Computing Systems 150 150
Author(s): Daniel Schön, Christian Owusu-Afriyie, Quang Huy Nguyen, Rainer Leupers, Stephan Menzel, Melvin Galicia

Abstract:

Simulations for the development and optimization of future in-memory computing (IMC) systems often face the problem that the modeling of the large system is desired, but at the same time, the effects at the device level should also be taken into account. Such effects could be due to the material …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 18 – 26
Year of Publication: 2026
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2026.3652426
Publisher: IEEE

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