Energy efficiency

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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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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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ROZK: An Energy-Efficient DNN Accelerator Based on Reconfigurable NoC and Local Zero-Skipping

ROZK: An Energy-Efficient DNN Accelerator Based on Reconfigurable NoC and Local Zero-Skipping 150 150
Author(s): Heetak Kim, Yunpyo Hong, Byungsoo Kim, Jongsun Park

Abstract:

Zero-skipping is a famous technique to improve the energy efficiency of deep neural network (DNN) accelerators. When the zero-skipping is realized with encoded data using lossless compression, irregular and unpredictable size of data due to inconsistent compression rate incurs several design issues including: 1) load imbalance from irregularity of data stored …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 12
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3604814
Publisher: IEEE

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24.86 Gb/s Full-Digital Chaos Random Number 1.53 GSamples/s Noise Generator in 40nm CMOS

24.86 Gb/s Full-Digital Chaos Random Number 1.53 GSamples/s Noise Generator in 40nm CMOS 150 150
Author(s): Cheng-Bin Chen, Tsung Chen, Yuan-Hao Huang

Abstract:

This letter presents a fully digital true random number generator (TRNG) and noise generator (NG) based on a chaos system. We design the chaos random number generator (CRNG) using the proposed Euler-based modified Lorenz system with periodic perturbation and modified modulo unit. The chaos NG (CNG) processor integrates the CRNG …

Published in: IEEE Solid-State Circuits Letters
Page(s): 253 – 256
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3605369
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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