in-memory computing (IMC)

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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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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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AACIM: A 2785-TOPS/W, 161-TOP/mm2, <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm

AACIM: A 2785-TOPS/W, 161-TOP/mm2, <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm 150 150
Author(s): Rentao Wan, Chuan-Tung Lin, Bo Zhang, Yannis Tsividis, Mingoo Seok

Abstract:

This article presents an analog-in analog-out CIM macro (AACIM) for use in analog deep neural network (DNN) processors. Our macro receives analog inputs, performs a 64-by-32 vector–matrix multiplication (VMM) with a current-discharging computation mechanism, and produces analog outputs. It stores a 4-bit weight as an analog voltage in the …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3622309
Publisher: IEEE

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Cryogenic Hyperdimensional In-Memory Computing Using Ferroelectric TCAM

Cryogenic Hyperdimensional In-Memory Computing Using Ferroelectric TCAM 150 150
Author(s): Shivendra Singh Parihar, Shubham Kumar, Swetaki Chatterjee, Girish Pahwa, Yogesh Singh Chauhan, Hussam Amrouch

Abstract:

Cryogenic operations of electronics present a significant step forward to achieve huge demand of in-memory computing (IMC) for high-performance computing, quantum computing, and military applications. Ferroelectric (FE) is a promising candidate to develop the complementary metal oxide semiconductor (CMOS)-compatible nonvolatile memories. Hence, in this work, we investigate the effectiveness …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 34 – 41
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3547797
Publisher: IEEE

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