SRAM

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An Approximate Digital CIM Macro With Low-Power Multiply-Add Units and Dynamic Sparse-Adaptive Configuring for Edge AI Inference

An Approximate Digital CIM Macro With Low-Power Multiply-Add Units and Dynamic Sparse-Adaptive Configuring for Edge AI Inference 150 150
Author(s): Xiaofeng Li, Yi Zhan, Purui Zhu, Rui Zhou, Jiayin Song, Heng You, Yumei Zhou, Shushan Qiao

Abstract:

This paper presents an approximate digital compute-in-memory (CIM) macro for low-power edge AI inference. It introduces three hierarchical innovations: 1) novel fused approximate multiply-add units (FAMUs) that reduces power and area consumption; 2) a bit-critical weight allocation architecture that optimally balances accuracy and hardware cost; and 3) a dynamic sparsity-adaptive configuration method to …

Published in: IEEE Solid-State Circuits Letters
Page(s): 1 – 1
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3652570
Publisher: IEEE

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A 3-nm FinFET 563-kbit 35.5-Mbit/mm2 Dual-Rail SRAM With 3.89-pJ/Access High Energy Efficient and 27.5-μW/Mbit One-Cycle Latency Low-Leakage Mode

A 3-nm FinFET 563-kbit 35.5-Mbit/mm2 Dual-Rail SRAM With 3.89-pJ/Access High Energy Efficient and 27.5-μW/Mbit One-Cycle Latency Low-Leakage Mode 150 150
Author(s): Yumito Aoyagi, Koji Nii, Makoto Yabuuchi, Tomotaka Tanaka, Kazuto Mizutani, Masaya Hamada, Yuichiro Ishii, Yen Chi Chou, Jun Cheng Liu, Chien-Yu Huang, Kang-Hui Peng, Yu-Hao Hsu, Isabel Wang, Hong-Chen Cheng, Hung-Jen Liao, Tsung-Yung Jonathan Chang

Abstract:

This article presents a high-density (HD) 6T SRAM macro designed in 3-nm FinFET technology with an extended dual-rail (XDR) architecture, addressing active energy and leakage for mobile applications. Two key innovations are introduced: the delayed-wordline in write operation (DEWL) technique and a one-cycle latency low-leakage access mode (1-CLM). The XDR …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3639747
Publisher: IEEE

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A 28-nm Digital Compute-in-Memory Ising Annealer With Asynchronous Random Number Generator for Traveling Salesman Problem

A 28-nm Digital Compute-in-Memory Ising Annealer With Asynchronous Random Number Generator for Traveling Salesman Problem 150 150
Author(s): Yuyao Kong, Haomei Liu, Vaidehi Garg, Shimeng Yu

Abstract:

This work presents a compact digital compute-in-memory (DCIM) Ising annealer targeting large-scale combinatorial optimization. A centroid-based weight mapping method combined with hierarchical clustering reduces the memory capacity required for traveling salesman problem (TSP) weights, enabling efficient mapping with limited on-chip storage. An asynchronous random number generator (ARNG) based on dual …

Published in: IEEE Solid-State Circuits Letters
Page(s): 1 – 4
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3639178
Publisher: IEEE

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A 37.8 Mb/mm² SRAM in Intel 18A Technology Featuring a Resistive Supply-Line Write Scheme and Write-Assist With Parallel Boost Injection

A 37.8 Mb/mm² SRAM in Intel 18A Technology Featuring a Resistive Supply-Line Write Scheme and Write-Assist With Parallel Boost Injection 150 150
Author(s): Harold Pilo, Manish Arora, Chien-An Lai, Mike Lee, Zack Lo, Mayur Randeria

Abstract:

A high-density (HD), SRAM-based register file (RF) has been demonstrated in Intel 18A Technology (Wang et al., 2025 and Pilo et al., 2025) featuring RibbonFET GAA transistors and a back side power delivery network (BSDPN). The RF is optimized for HD and array efficiency and achieves a density of 37.8 Mb/mm2, the …

Published in: IEEE Solid-State Circuits Letters
Page(s): 357 – 360
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3628176
Publisher: IEEE

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Impact of Aging, Self-Heating, and Parasitics Effects on NSFET and CFET

Impact of Aging, Self-Heating, and Parasitics Effects on NSFET and CFET 150 150
Author(s): Swati Deshwal, Sufia Shahin, Anirban Kar, Yogesh S. Chauhan, Hussam Amrouch

Abstract:

This work presents a comparative analysis of complementary field-effect transistor (CFET) and nanosheet FET (NSFET) architectures, with a focus on self-heating effects (SHEs), negative bias temperature instability (NBTI), hot carrier degradation (HCD), and the impact of back-end-of-line (BEOL) parasitics on standard cell performance. NBTI degradation is modeled using a framework …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 188 – 196
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3624653
Publisher: IEEE

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MIX-ACIM: A 28-nm Mixed-Precision Analog Compute-in-Memory With Digital Feature Restoration for Vector-Matrix Multiplication

MIX-ACIM: A 28-nm Mixed-Precision Analog Compute-in-Memory With Digital Feature Restoration for Vector-Matrix Multiplication 150 150
Author(s): Wei-Chun Wang, Shida Zhang, Laith Shamieh, Narasimha Vasishta Kidambi, Isha Chakraborty, Saibal Mukhopadhyay

Abstract:

A mixed-precision analog compute-in-memory (Mix-ACIM) is presented for mixed-precision vector-matrix multiplication (VMM). The design features an all-analog current-domain fixed-point (FxP) VMM with floating-point conversion and feature restoration. A 28 nm CMOS test chip shows 41 TOPS/W and 24 TOPS/mm2 for FxP (8-bit input/weight and 12-bit output) and 24.18 TFLOPS/W and 3.3 …

Published in: IEEE Solid-State Circuits Letters
Page(s): 213 – 216
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3590757
Publisher: IEEE

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CFET Beyond 3 nm: SRAM Reliability Under Design-Time and Run-Time Variability

CFET Beyond 3 nm: SRAM Reliability Under Design-Time and Run-Time Variability 150 150
Author(s): Sufia Shahin, Swati Deshwal, Anirban Kar, Mahdi Benkhelifa, Yogesh S. Chauhan, Hussam Amrouch

Abstract:

This work investigates the reliability of complementary field-effect transistors (CFETs) by addressing both design-time variability arising from process variations and run-time variability due to temperature and aging effects. A rigorously calibrated TCAD model, validated against experimental CFET data, is employed to quantify the impact of metal gate granularity (MGG)-induced …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 51 – 59
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3568622
Publisher: IEEE

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An Investigation of Minimum Supply Voltage of 5-nm SRAM From 300 K Down to 10 K

An Investigation of Minimum Supply Voltage of 5-nm SRAM From 300 K Down to 10 K 150 150
Author(s): Hafeez Raza, Shivendra Singh Parihar, Yogesh Singh Chauhan, Hussam Amrouch, Avinash Lahgere

Abstract:

In this article, we present a comprehensive study of the impact of cryogenic temperatures on the minimum operating voltage ( $V_{\min }$ ) of 5-nm Fin Field-Effect Transistors (FinFETs)-based Static Random Access Memory (SRAM) cells. To perform the SRAM $V_{\min }$ evaluation, we have measured the FinFETs fabricated using a commercial 5…

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 42 – 50
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3560215
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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