Energy efficiency

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A 29-Gb/mm2 1-Tb 3-b/Cell 3-D Flash Memory With CMOS Direct Bonded Array (CBA) Technology

A 29-Gb/mm2 1-Tb 3-b/Cell 3-D Flash Memory With CMOS Direct Bonded Array (CBA) Technology 150 150
Author(s): Kosuke Yanagidaira, Mario Sako, Yasuhiro Hirashima, Yumi Higashi, Yutaka Shimizu, Takeshi Nakano, Yusuke Ochi, Hiroaki Yamada, Nobushi Matsuura, Akihiro Imamoto, Kazuaki Kawaguchi, Koji Tabata, Hiroaki Hoshino, Takeshi Hioka, Shigehito Saigusa, Hiroki Date, Masaki Unno, Jumpei Sato, You Kamata, Takahiro Shimizu, Akio Sugahara, Taira Shibuya, Atsushi Okuyama, Junji Yamada, Takatoshi Minamoto, Hardwell Chibvongodze, Naoki Ojima, Hiroshi Sugawara, Masahiro Kano, Jang-Woo Lee, Hiroyuki Mizukoshi, Ryuji Yamashita, Kensaku Abe, Naohito Morozumi, In-Soo Yoon, Takuya Ariki, Jong Hak Yuh, Khin Htoo, Yosuke Kato, Yoshihiro Oyama, Yen-Lung Jason Li, Yoshihisa Watanabe, Toshiyuki Kouchi, Koji Hosono

Abstract:

This article reports a 1-Tb 3-b/cell 3-D flash memory fabricated with CMOS direct bonded array (CBA) technology. Compaction of circuits and wires achieves the highest bit density in the world over 29 Gb/mm2 with 332-word line (WL) layers. The bit density is improved by 71% from a previous generation despite …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 237 – 249
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3617579
Publisher: IEEE

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A 14-b Energy-Efficient BW/Power Scalable CTDSM With a Frequency-Controlled Current Source

A 14-b Energy-Efficient BW/Power Scalable CTDSM With a Frequency-Controlled Current Source 150 150
Author(s): Xinjie Wu, Xiaopeng Yu, Nick Nianxiong Tan, Zhong Tang

Abstract:

This work presents a 14-bit energy-efficient bandwidth (BW)/power scalable continuous-time delta–sigma modulator (CTDSM) for sensor interfaces in IoT applications. To ensure low noise for small input signals and achieve BW/power scalability, it is built around Gm-C integrators biased via a linear frequency-controlled current source (FCCS). The FCCS …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 10
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3621527
Publisher: IEEE

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AACIM: A 2785-TOPS/W, 161-TOP/mm2, <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm

AACIM: A 2785-TOPS/W, 161-TOP/mm2, <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm 150 150
Author(s): Rentao Wan, Chuan-Tung Lin, Bo Zhang, Yannis Tsividis, Mingoo Seok

Abstract:

This article presents an analog-in analog-out CIM macro (AACIM) for use in analog deep neural network (DNN) processors. Our macro receives analog inputs, performs a 64-by-32 vector–matrix multiplication (VMM) with a current-discharging computation mechanism, and produces analog outputs. It stores a 4-bit weight as an analog voltage in the …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3622309
Publisher: IEEE

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A Machine Learning-Inspired PAM-4 Transceiver for Medium-Reach Wireline Links

A Machine Learning-Inspired PAM-4 Transceiver for Medium-Reach Wireline Links 150 150
Author(s): Ramin Javadi, Tejasvi Anand

Abstract:

This article presents an energy-efficient machine learning-inspired PAM-4 wireline transceiver that leverages data encoding at the transmitter (Tx) and feature extraction with classification at the receiver (Rx) to compensate for channel loss ranging from 13 to 26 dB, while maintaining the bit error rate (BER)<10-11. A new consecutive symbol-to-center (CSC) encoding …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3616072
Publisher: IEEE

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A RISC-V SoC With Reconfigurable Custom Instructions on a Synthesized eFPGA Fabric in 22nm FinFET

A RISC-V SoC With Reconfigurable Custom Instructions on a Synthesized eFPGA Fabric in 22nm FinFET 150 150
Author(s): Prashanth Mohan, Siddharth Das, Ken Mai

Abstract:

This letter presents a flexible and energy-efficient RISC-V system-on-chip (SoC) in 22nm FinFET technology, achieving state-of-the-art performance by tightly integrating the CPU with a synthesized embedded FPGA (embedded field programmable gate array (eFPGA)), enabling the implementation of reconfigurable custom instructions. The tight integration of the eFPGA with SoC scratchpad memory …

Published in: IEEE Solid-State Circuits Letters
Page(s): 321 – 324
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3618942
Publisher: IEEE

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Ultra-Low-Power Dynamic-Bias Comparators With Self-Clocked Latch in 65-nm CMOS

Ultra-Low-Power Dynamic-Bias Comparators With Self-Clocked Latch in 65-nm CMOS 150 150
Author(s): Anojh Kumaran Rajendra, Harijot Singh Bindra, Bram Nauta

Abstract:

This article introduces two comparators featuring a dynamic-bias preamplifier and self-clocked latches, tailored for ultra-low-power and medium-speed applications with <500- $\mu $ V input-referred noise (IRN). The proposed self-clocked latches are activated by the preamplifier outputs and therefore operate with a lower common-mode current, which in turn minimizes the crowbar current …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3612157
Publisher: IEEE

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A 28-nm Computing-in-Memory Processor With Zig-Zag Backbone-Systolic CIM and Block-/Self-Gating CAM for NN/Recommendation Applications

A 28-nm Computing-in-Memory Processor With Zig-Zag Backbone-Systolic CIM and Block-/Self-Gating CAM for NN/Recommendation Applications 150 150
Author(s): Shengzhe Yan, Zhuoyu Dai, Zhaori Cong, Zeyu Guo, Yifan He, Wenyu Sun, Chunmeng Dou, Feng Zhang, Jinshan Yue, Yongpan Liu, Ming Liu

Abstract:

Computing-in-memory (CIM) chips have demonstrated promising energy efficiency for artificial intelligence (AI) applications such as neural networks (NNs), Transformer, and recommendation system (RecSys). However, several challenges still exist. First, a large gap between the macro and system-level CIM energy efficiency is observed. Second, several memory-dominate operations, such as embedding in …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 15
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3610539
Publisher: IEEE

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A Fully-Dynamic Capacitive Touch Sensor With Tri-level Energy Recycling and Compressive Sensing Technique

A Fully-Dynamic Capacitive Touch Sensor With Tri-level Energy Recycling and Compressive Sensing Technique 150 150
Author(s): Xiangdong Feng, Zhiyu Wang, Haoyang Li, Jiaqing Li, Wei-Chin Lin, Xin Hu, Zhong Tang, Yuyan Liu, Qinwen Fan, Yuxuan Luo, Bo Zhao

Abstract:

Capacitive touch screens have become the dominant user interface over the past decade. Achieving high framerates with low power consumption remains a critical design goal for touch systems. The conventional charge-recycling technique reduces driving power by 64%, but it relies on off-chip capacitors. To address this issue, we propose a tri-level …

Published in: IEEE Solid-State Circuits Letters
Page(s): 1 – 1
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3612093
Publisher: IEEE

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Energy-Efficient Reconfigurable XGBoost Inference Accelerator With Modular Unit Trees via Selective Node Execution and Data Movement

Energy-Efficient Reconfigurable XGBoost Inference Accelerator With Modular Unit Trees via Selective Node Execution and Data Movement 150 150
Author(s): Chang Eun Song, Yidong Li, Amardeep Ramnani, Pulkit Agrawal, Purvi Agrawal, Sung-Joon Jang, Sang-Seol Lee, Tajana Rosing, Mingu Kang

Abstract:

The extreme gradient boosting (XGBoost) has emerged as a powerful AI algorithm, achieving high accuracy and winning multiple Kaggle competitions in various tasks including medical diagnosis, recommendation systems, and autonomous driving. It has great potential for running on edge devices due to its binary tree-based simple computing kernel, offering unique …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3607896
Publisher: IEEE

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