Computer architecture

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A Simultaneous Dual-Carrier Transformer-Coupled Passive Mixer-First Receiver Front-End Supporting Blocker Suppression

A Simultaneous Dual-Carrier Transformer-Coupled Passive Mixer-First Receiver Front-End Supporting Blocker Suppression 150 150
Author(s): Jamie C. Ye, Alain H. Antón, Sanaz Sadeghi, Russ H. Huang, Alyosha C. Molnar

Abstract:

A high dynamic range N-path passive mixer-first receiver architecture capable of simultaneously down-converting two arbitrary bands through a single RF port is presented. The architecture consists of two passive mixers arranged in a series configuration with a transformer front-end to minimize cross-loading between mixers while still providing impedance transparency and …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1541 – 1553
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3546082
Publisher: IEEE

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Device Nonideality-Aware Compute-in-Memory Array Architecting: Direct Voltage Sensing, I–V Symmetric Bitcell, and Padding Array

Device Nonideality-Aware Compute-in-Memory Array Architecting: Direct Voltage Sensing, I–V Symmetric Bitcell, and Padding Array 150 150
Author(s): Jianzi Jin, Shifan Gao, Cimang Lu, Xiang Qiu, Yi Zhao

Abstract:

A voltage sensing compute-in-memory (CIM) architecture has been designed to improve the analog computing accuracy, and a chip on 90-nm flash platform has been successfully fabricated, with the bidirectional operation enabled by the symmetric bitcell structure. By padding the weight sum to a global value for all bit lines (BLs), …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 19 – 24
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3539470
Publisher: IEEE

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Binarized Neural-Network Parallel-Processing Accelerator Macro Designed for an Energy Efficiency Higher Than 100 TOPS/W

Binarized Neural-Network Parallel-Processing Accelerator Macro Designed for an Energy Efficiency Higher Than 100 TOPS/W 150 150
Author(s): Yusaku Shiotsu, Satoshi Sugahara

Abstract:

A binarized neural-network (BNN) accelerator macro is developed based on a processing-in-memory (PIM) architecture having the ability of eight-parallel multiply-accumulate (MAC) processing. The parallel-processing PIM macro, referred to as a PPIM macro, is designed to perform the parallel processing with no use of multiport SRAM cells and to achieve the …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 25 – 33
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3538702
Publisher: IEEE

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