static random access memory (SRAM)

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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 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 3 nm FinFET 125 TOPS/W-29 TFLOPS/W, 90 TOPS/mm2-17 TFLOPS/mm2 SRAM-Based INT8, and FP16 Digital-CIM Compiler With Support for Multi-Weight Update/Cycle

A 3 nm FinFET 125 TOPS/W-29 TFLOPS/W, 90 TOPS/mm2-17 TFLOPS/mm2 SRAM-Based INT8, and FP16 Digital-CIM Compiler With Support for Multi-Weight Update/Cycle 150 150
Author(s): Haruki Mori, Je-Min Hung, Wei-Chang Zhao, Kinshuk Khare, Brian Crafton, Hiroaki Ishii, Cheng-En Lee, Xiaochen Peng, Xiaoyu Sun, Yorinobu Fujino, Chia-Jung Tsen, Vineet Joshi, Chao-Kai Chuang, Takeshi Hashizume, Chia-Fu Lee, Tan-Li Chou, Kerem Akarvardar, Saman Adham, Yih Wang, Hidehiro Fujiwara, Yu-Der Chih, Yen-Huei Chen, Hung-Jen Liao, Tsung-Yung Jonathan Chang

Abstract:

This article presents an static random-access memory (SRAM)-based digital compute-in-memory (CIM) compiler implemented with 3 nm high- $\kappa $ metal gate (HKMG) FinFET technology, supporting flexible INT8 and FP16 formats for weight and activation multiply-accumulate (MAC) operations, offering configuration flexibility, high accuracy, and improved area and power efficiency. The FP16 digital …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3646072
Publisher: IEEE

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A High-Density Low-Leakage and Low-Power Fully Voltage-Stacked SRAM for IoT Application

A High-Density Low-Leakage and Low-Power Fully Voltage-Stacked SRAM for IoT Application 150 150
Author(s): Sekeon Kim, Giseok Kim, Kyeongrim Baek, Keonhee Cho, Hyunjun Kim, Yeonho Jung, Dongwook Seo, Sangyeop Baeck, Sungjae Lee, Seong-Ook Jung

Abstract:

The general approach to suppress leakage in static random access memory (SRAM) is to use a low voltage ( $V_{text {L}}$ ), generated by a low-dropout regulator (LDO), as the cell supply voltage (CVDD) of SRAM array in the standby mode. However, the effectiveness of lowering CVDD is constrained by the …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 12
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3582974
Publisher: IEEE

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