Very large scale integration

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An 800MS/s 13b 2x TI Pipelined-SAR ADC with Rapid Digital Amplification

An 800MS/s 13b 2x TI Pipelined-SAR ADC with Rapid Digital Amplification 150 150
Author(s): Peizhe Li, Danfeng Zhai, Qi Liu, Chixiao Chen

Abstract:

This work proposes a rapid digital amplification (RDA) with residue-aware reference, offering an equivalent open-loop (OL) gain enhancement of 25 dB and reducing the inter-stage gain error (ISGE)-induced SNR degradation by 20 dB, with an extra amplification latency of only 200 ps. It is implemented in an 800MS/s 13b two-way time-interleaved (…

Published in: IEEE Solid-State Circuits Letters
Page(s): 1 – 1
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3684735
Publisher: IEEE

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Self-Enabled Write Assist Cells for High-Density SRAM in Resistance-Dominated Technology Node

Self-Enabled Write Assist Cells for High-Density SRAM in Resistance-Dominated Technology Node 150 150
Author(s): Minjune Yeo, Seungjae Yei, Keonhee Cho, Giseok Kim, Mingu Kang, Seong-Ook Jung

Abstract:

As technology scaling increases interconnect resistance, writeability degradation in static random access memory (SRAM) becomes critical. This article presents a self-enabled write assist cell (SEWAC) that mitigates writeability degradation caused by increased bitline resistance (R ${}_{\mathrm {BL}}$ ) without requiring timing control. The SEWAC has a cell-compatible layout with the standard 6…

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3681916
Publisher: IEEE

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A 3nm Fin-FET 19.87-Mbit/mm2 2RW Pseudo Dual-Port 6T SRAM With Metal Wire-R Tracking and Sequential Access-Aware Dynamic Power Reduction

A 3nm Fin-FET 19.87-Mbit/mm2 2RW Pseudo Dual-Port 6T SRAM With Metal Wire-R Tracking and Sequential Access-Aware Dynamic Power Reduction 150 150
Author(s): Tomotaka Tanaka, Koji Nii, Yuichiro Ishii, Makoto Yabuuchi, Yumito Aoyagi, Masaya Hamada, Kazuto Mizutani, Hidehiro Fujiwara, Isabel Wang, Hong-Chen Cheng, Hung-Jen Liao, Tsung-Yung Jonathan Chang

Abstract:

This article presents a 2-read/write (2RW) pseudo dual-port (PDP) static random access memory (SRAM) macro implemented in advanced 3nm Fin-FET technology, achieving a competitive bit density of 19.87Mbit/mm2 for advanced nodes. To address challenges in process scaling, reliability under process voltage temperature variations, and dynamic power consumption, two …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3682256
Publisher: IEEE

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A Continuous-Time Zoom Sensor Readout Frontend With Fast Tracking and Floating-Gm-CCO Integrator

A Continuous-Time Zoom Sensor Readout Frontend With Fast Tracking and Floating-Gm-CCO Integrator 150 150
Author(s): Haoyang Luo, Zongnan Wang, Jiarui Wang, Bingrui Li, Zilong Shen, Yang Liu, Xiaojie Duan, Yuan Wang, Xiyuan Tang

Abstract:

Emerging edge applications processing weak signals in noisy environments demand sensor readout frontends with low noise, low power, high dynamic range (DR), and high input impedance. This article presents a zoom sensor readout frontend design that can track signals with rapid changes over a wide DR with high energy efficiency. …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 12
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3677053
Publisher: IEEE

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A 28-nm Digital Transpose SRAM Compute-in-Memory Macro With Accurate/Approximate Dual Mode for Floating-Point Edge Training and Inference

A 28-nm Digital Transpose SRAM Compute-in-Memory Macro With Accurate/Approximate Dual Mode for Floating-Point Edge Training and Inference 150 150
Author(s): Yiyang Yuan, Bingxin Zhang, Yiming Yang, Yishan Luo, Qirui Chen, Haitao Wang, Qihao Liu, Zhiming Chen, Hao Wu, Jinshan Yue, Shidong Lv, Xinghua Wang, Pui-In Mak, Xiaoran Li, Feng Zhang

Abstract:

Static random-access memory (SRAM)-based computing-in-memory (CIM) macros have been widely studied to improve the energy efficiency of edge artificial intelligence (AI) inference tasks. However, less attention has been given to AI training, which requires CIM macros to not only perform matrix multiply-accumulate (MAC) operations but also support matrix transposition. …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3679560
Publisher: IEEE

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A Wide-Dynamic-Range Photovoltaic Energy Harvester With Adaptive Power-Scalable MPPT Control and Direct Power-to-Digital Converter

A Wide-Dynamic-Range Photovoltaic Energy Harvester With Adaptive Power-Scalable MPPT Control and Direct Power-to-Digital Converter 150 150
Author(s): Yuyan Liu, Huajun Zhang, Mustafa Becermis, Jieyu Liao, Mohit Dandekar, Kofi A. A. Makinwa, Qinwen Fan

Abstract:

This article presents a photovoltaic energy harvester (PVEH) that achieves high maximum power point tracking (MPPT) efficiency and power conversion efficiency across a $100~000{\times }$ input power dynamic range (DR) (from $10~{\mu }$ W to 1W). Wide-dynamic-range operation is challenging due to the inherent tradeoff between MPPT accuracy and controller power consumption. …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 12
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3675521
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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