RSACIM: Resistance Summation Analog Computing in Memory With Accuracy Optimization Scheme Based on MRAM

Wang, Jinkai; Gu, Zhengkun; Zhang, Bojun; Chen, Youxiang; Wang, Zekun; Zhang, Kun; Zhang, Youguang; Zhang, Yue

doi:10.1109/tcsi.2023.3334950

IEEE Trans. Circuits Syst. I

2024

DOI: 10.1109/tcsi.2023.3334950

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RSACIM: Resistance Summation Analog Computing in Memory With Accuracy Optimization Scheme Based on MRAM

Jinkai Wang,

Zhengkun Gu,

Bojun Zhang

et al.

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Cited by 4 publications

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Capacitance and Conductance Compensation Methods for Efficient Computing‐In‐Memory Designs

Luo,

Qiao,

Sun

2024

Adv Elect Materials

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Compensation has been a common while unacknowledged strategy in the design of computing‐in‐memory (CIM) schemes. It enables efficient CIM designs by intentionally letting the sum of capacitances or conductances of two or more rows or columns in the memory array equal, thus resulting in a concise mathematical formula regarding the memory cell data and the input data, which constitute computing primitives. Here, the capacitance and conductance compensation methods are reviewed that have been used for CIM designs based on static random‐access memory (SRAM) in combination with capacitors and nonvolatile resistive memory, respectively, and uncover the underlying principles and their application to CIM. It is hoped this effort will help recognize the compensation methods as a building block for CIM designs, and will be an inspiration to developing more CIM schemes that are more compact in area, more efficient in energy consumption, and capable of solving more complicated problems.

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Capacitance and Conductance Compensation Methods for Efficient Computing‐In‐Memory Designs

Luo,

Qiao,

Sun

2024

Adv Elect Materials

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Dual in-memory computing of matrix-vector multiplication for accelerating neural networks

Wang,

Sun

2024

Device

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Utilizing MRAMs With Low Resistance and Limited Dynamic Range for Efficient MAC Accelerator

Sateesh,

Chakarwar,

Sahay

2024

IEEE Open J. Nanotechnol.

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RSACIM: Resistance Summation Analog Computing in Memory With Accuracy Optimization Scheme Based on MRAM

Cited by 4 publications

References 43 publications

Capacitance and Conductance Compensation Methods for Efficient Computing‐In‐Memory Designs

Capacitance and Conductance Compensation Methods for Efficient Computing‐In‐Memory Designs

Dual in-memory computing of matrix-vector multiplication for accelerating neural networks

Utilizing MRAMs With Low Resistance and Limited Dynamic Range for Efficient MAC Accelerator

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