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Preface to the Special Issue on Beyond Moore: Resistive Switching Devices for Emerging Memory and Neuromorphic Computing

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Journal of Semiconductors 2021年第1期42卷 31-32页

Traditional charge-based memories,such as dynamic random-access memory(DRAM)and flash,are approaching their scaling limits.A variety of resistance-based memories,such as phase-change memory(PCM),magnetic random-access memory(MRAM)and resistive random-access memory(RRAM),have been long considered for emerging memory applications thanks to their non-volatility,fast speed,low power,and compact size for potentially high-density integration.

关键词： flash approaching random

Cryogenic quasi-static embedded DRAM for energy-efficient compute-in-memory applications

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arXiv 2023年

作者： Shu, Yuhao Zhang, Hongtu Sun, Hao Zhang, Mengru Zhao, Wenfeng Deng, Qi Tang, Zhidong Yuan, Yumeng Hu, Yongqi Gu, Yu Kou, Xufeng Ha, Yajun School of Information Science and Technology ShanghaiTech University Shanghai China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China State Key Laboratory of Integrated Chip and System Frontier Institute of Chip and System Fudan University Shanghai China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Department of Electrical and Computer Engineering Binghamton University SUNY BinghamtonNY United States Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China Shanghai Engineering Research Center of Energy Efficient and Custom AI IC Shanghai China

Compute-in-memory (CIM) presents an attractive approach for energy-efficient computing in data-intensive applications. However, the development of suitable memory designs to achieve high-performance CIM remains a challenging task. Here, we propose a cryogenic quasi-static embedded DRAM to address the logic-memory mismatch of CIM. Guided by the re-calibrated cryogenic device model, the designed four-transistor bit-cell achieves full-swing data storage, low power consumption, and extended retention time at cryogenic temperatures. Combined with the adoption of cryogenic write bitline biasing technique and readout circuitry optimization, our 4Kb cryogenic eDRAM chip demonstrates a 1.37×106 times improvement in retention time, while achieving a 75 times improvement in retention variability, compared to room-temperature operation. Moreover, it also achieves outstanding power performance with a retention power of 112 fW and a dynamic power of 108 µW at 4.2 K, which can be further decreased by 7.1% and 13.6% using the dynamic voltage scaling technique. This work reveals the great potential of cryogenic CMOS for high-density data storage and lays a solid foundation for energy-efficient CIM implementations. Copyright © 2023, The Authors. All rights reserved.

关键词： Computation theory

Disjoint-Path and Golden-Pin Based Irregular PCB Routing with Complex Constraints

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Disjoint-Path and Golden-Pin Based Irregular PCB Routing wit...

Design Automation Conference

作者： Qinghai Liu Qinfei Tang Jiarui Chen Chuandong Chen Ziran Zhu Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China College of Computer and Date Science Fuzhou University Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Department of Microelectronics Southeast University Nanjing China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

PCB routing becomes time-consuming as the complexity of PCB design increases. Unlike traditional schemes that treat the two essential PCB routing processes separately, namely, escape and bus routing, we consider the continuity between them and present a golden-pin-based routing scheme to find the desired solution with angle and topology constraints. Further, conventional rip-up and reroute methods are often ineffective and inefficient for congestion alleviation and routability optimization. We construct a component graph by modeling components as vertices and applying the minimum weight vertex covering method to improve the routability. A self-adaptable ordering method is presented for escape routing to arrange the pin order on the component boundary, guaranteeing successful bus routing. In addition, escape routing is performed based on a disjoint path method. We construct a dynamic Hanan grid in bus routing and utilize a novel congestion adjustment technique to improve solution quality. Compared with FreeRouting and Allegro, the experiment results show that our algorithm achieves high routability and a significant 90% runtime reduction.

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Hierarchical Nb2o5@Zno Hetero-Branched Nanorods for Enhanced H2s Gas Sensing

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SSRN

SSRN 2022年

作者： Wu, Tao Tao Zhu, Liyuan Wu, Xue-Yan Miao, Xiao-Yong Mao, Li-Wen Jin, Xuan-Hong Lu, Hong-Liang State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai 200433 China School of Optical-Electrical & Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China Yiwu Research Institute of Fudan University Chengbei Road Zhejiang Yiwu City322000 China

Hierarchical Nb 2 O 5 @ZnO hetero-branched nanorods used for highly responsive, selective, and stable hydrogen sulfide (H 2 S) sensors were synthesized through a sequential process combining a hydrothermal method, atomic-layer-deposition processing, and modified hydrothermal processing for branching ZnO nanowires. The Nb 2 O 5 @ZnO hetero-branched nanorod sensors exhibited a great response (R a /R g ) of 6.10 towards 20 ppm H 2 S at an optimal working temperature of 400 o C, whose resistance changing rate (~5.10) was 39.2- and 1.9-fold those of Nb 2 O 5 (~0.13) and Nb 2 O 5 @ZnO core-shell nanorod (~2.74) sensors, respectively. The heterojunction formed at the Nb 2 O 5 @ZnO interface and the characteristic reaction between ZnO and H 2 S effectively improved H 2 S sensing performance. Moreover, the branching of ZnO nanowires introduced abundant homojunctions and prominently enlarged the specific surface area, further increasing the response of hetero-branched sensors. Meanwhile, the Nb 2 O 5 @ZnO hetero-branched sensors maintained steady performance over a month, indicating good stability and repeatability. In a word, such hierarchical Nb 2 O 5 @ZnO hetero-branched nanorod gas sensors are promising for the development of sensitive and selective H 2 S detection. © 2022, The Authors. All rights reserved.

关键词： Zinc oxide

Pruning random resistive memory for optimizing analogue AI

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arXiv 2023年

作者： Li, Yi Wang, Songqi Zhao, Yaping Wang, Shaocong Zhang, Woyu He, Yangu Lin, Ning Cui, Binbin Chen, Xi Zhang, Shiming Jiang, Hao Lin, Peng Zhang, Xumeng Qi, Xiaojuan Wang, Zhongrui Xu, Xiaoxin Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong State Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Frontier Institute of Chip and System Fudan University Shanghai200433 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong University of Chinese Academy of Sciences Beijing100049 China Institute of Mind The University of Hong Kong Hong Kong

The rapid advancement of artificial intelligence (AI) has been marked by the large language models exhibiting human-like intelligence. However, these models also present unprecedented challenges to energy consumption and environmental sustainability, which are exacerbated by the increasing number of users and the development of even larger models. One promising solution is to revisit analogue computing, a technique that predates digital computing and exploits emerging analogue electronic devices, such as resistive memory, which features in-memory computing, high scalability, and nonvolatility that addresses the von Neumann bottleneck, slowdown of Moore’s law, and volatile DRAM of conventional digital hardware. However, analogue computing still faces the same challenges as before: programming nonidealities and expensive programming due to the underlying devices physics. Therefore, leveraging the efficiency advantage while mitigating the programming disadvantage of analogue computing with resistive memory is a major open problem in AI hardware and electronics communities. Here, we report a universal solution, software-hardware co-design using structural plasticity-inspired edge pruning to optimize the topology of a randomly weighted analogue resistive memory neural network. Software-wise, the topology of a randomly weighted neural network is optimized by pruning connections rather than precisely tuning resistive memory weights. Hardware-wise, we reveal the physical origin of the programming stochasticity using transmission electron microscopy, which is leveraged for large-scale and low-cost implementation of an overparameterized random neural network containing high-performance sub-networks. We implemented the co-design on a 40nm 256K resistive memory macro, observing 17.3% and 19.9% accuracy improvements in image and audio classification on FashionMNIST and Spoken digits datasets, as well as 9.8% (2%) improvement in PR (ROC) in image segmentation on DRIVE datasets, r

关键词： Energy utilization

Investigation of the long-term adhesion and barrier properties of a PDMS-Parylene stack with PECVD ceramic interlayers for the conformal encapsulation of neural implants 23

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Investigation of the long-term adhesion and barrier properti...

23rd European microelectronics and Packaging Conference and Exhibition, EMPC 2021

作者： Babaroud, Nasim Bakhshaee Dekker, Ronald Holk, Ole Tiringer, Ursa Taheri, Peyman Horvath, Domonkos Nanasi, Tibor Ulbert, Istvan Serdijn, Wouter Giagka, Vasiliki Department of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Technologies for Bioelectronics Group Department of System Integration and Interconnection Technologies Fraunhofer Institute for Reliability and Micro-Integration IZM Berlin Germany Delft University of Technology Delft Netherlands Institute of Cognitive Neuroscience and Psychology Research Center for Natural Science Budapest Hungary Philips Research Eindhoven Netherlands Rotterdam Netherlands

ISBN: (纸本)9780956808677

In this paper, we investigate the long-term adhesion strength and barrier property of our recently proposed encapsulation stack that includes PDMS-Parylene C and PECVD interlayers (SiO2 and SiC) for adhesion improvement. To evaluate the adhesion strength of our proposed stack, the sample preparation consisted in depositing approximately 25 nm of SiC and 25 nm of SiO2 on half wafers, previously coated with Parylene C. Next, 50 µm PDMS was spin-coated on top. Finally, the samples were detached from the Si wafer and soaked in a PBS solution at 67 °C to accelerate the aging process. Two samples were also implanted, subcutaneously, on the left and right subscapular regions of a rat. The optical inspection and peel tests performed after two months confirmed our preliminary findings and showed a significant improvement of the adhesion in our proposed encapsulation stack compared to the case of PDMS on Parylene C alone. In addition, the X-ray photoelectron spectroscopy (XPS) analysis at the interface between SiC and Parylene C showed different peaks for the interface compared to the reference spectra, which could be an indication of a chemical bond. Finally, water vapor transmission rate (WVTR) tests were performed to investigate the barrier property of our proposed encapsulation stack against water vapor transmission. The results demonstrated that the proposed stack acts as a significantly (two orders of magnitude) higher barrier against moisture compared to only Parylene C and PDMS encapsulation layers. The proposed method yields a fully transparent encapsulation stack over a broad wavelength spectrum that can be used for the conformal encapsulation of flexible devices and thus, making them compatible with techniques such as optical imaging and optogenetics. © 2021 2021 23rd European microelectronics and Packaging Conference and Exhibition, EMPC 2021. All rights reserved.

关键词： Adhesion

Analysis of Age of Information in Dual Updating systems

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arXiv 2022年

作者： Chen, Zhengchuan Deng, Dapeng Yang, Howard H. Pappas, Nikolaos Hu, Limei Jia, Yunjian Wang, Min Quek, Tony Q.S. The School of Microelectronics and Communication Engineering Chongqing University China The Zhejiang University/UIUC Institute Zhejiang University China The Department of Computer and Information Science Linköping University Linköping581 83 Sweden The School of Optoelectronics Engineering Chongqing University of Posts and Telecommunications China The Information System Technology and Design Pillar Sutd Singapore487372 Singapore

We study the average Age of Information (AoI) and peak AoI (PAoI) of a dual-queue status update system that monitors a common stochastic process. Although the double queue parallel transmission is instrumental in reducing AoI, the out of order of data arrivals also imposes a significant challenge to the performance analysis. We consider two settings: the M-M system where the service time of two servers is exponentially distributed;the M-D system in which the service time of one server is exponentially distributed and that of the other is deterministic. For the two dual-queue systems, closed-form expressions of average AoI and PAoI are derived by resorting to the graphic method and state flow graph analysis method. Our analysis reveals that compared with the single-queue system with an exponentially distributed service time, the average PAoI and the average AoI of the M-M system can be reduced by 33.3% and 37.5%, respectively. For the M-D system, the reduction in average PAoI and the average AoI are 27.7% and 39.7%, respectively. Numerical results show that the two dual-queue systems also outperform the M/M/2 single queue dual-server system with optimized arrival rate in terms of average AoI and PAoI. Copyright © 2022, The Authors. All rights reserved.

关键词： Graphic methods

Efficient and accurate neural field reconstruction using resistive memory

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arXiv 2024年

作者： Yu, Yifei Wang, Shaocong Zhang, Woyu Zhang, Xinyuan Wu, Xiuzhe He, Yangu Yang, Jichang Zhang, Yue Lin, Ning Wang, Bo Chen, Xi Wang, Songqi Zhang, Xumeng Qi, Xiaojuan Wang, Zhongrui Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Hong Kong ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Hong Kong Institute of Mind The University of Hong Kong Hong Kong Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China Frontier Institute of Chip and System Fudan University Shanghai200433 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Hong Kong

Human beings construct perception of space by integrating sparse observations into massively interconnected synapses and neurons, offering a superior parallelism and efficiency. Replicating this capability in AI finds wide applications in medical imaging, AR/VR, and embodied AI, where input data is often sparse and computing resources are limited. However, traditional signal reconstruction methods on digital computers face both software and hardware challenges. On the software front, difficulties arise from storage inefficiencies in conventional explicit signal representation. Hardware obstacles include the von Neumann bottleneck, which limits data transfer between the CPU and memory, and the limitations of CMOS circuits in supporting parallel processing. We propose a systematic approach with software-hardware co-optimizations for signal reconstruction from sparse inputs. Software-wise, we employ neural field to implicitly represent signals via neural networks, which is further compressed using low-rank decomposition and structured pruning. Hardware-wise, we design a resistive memory-based computing-in-memory (CIM) platform, featuring a Gaussian Encoder (GE) and an MLP Processing Engine (PE). The GE harnesses the intrinsic stochasticity of resistive memory for efficient input encoding, while the PE achieves precise weight mapping through a Hardware-Aware Quantization (HAQ) circuit. We demonstrate the system’s efficacy on a 40nm 256Kb resistive memory-based in-memory computing macro, achieving 31.5×, 35.5×, and 47.2× energy efficiency improvements and 10.8×, 38.8×, and 6.2× parallelism improvements without compromising reconstruction quality in tasks like 3D CT sparse reconstruction, novel view synthesis, and novel view synthesis for dynamic scenes. This work advances the AI-driven signal restoration technology and paves the way for future efficient and robust medical AI and 3D vision applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Signal reconstruction

High Performance Computing Framework for Variable Selection on Genome-wide Association Studies

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High Performance Computing Framework for Variable Selection ...

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiang Liu Xueling Liu Jing Diao Mengyao Zheng Jihe Li Dehui Wei Qipeng Xie Xia Li Linshan Jiang School of Computing National University of Singapore Group Technology Office National University Health System Department of Preventive Dentistry Peking University School and Hospital of Stomatology National Center for Stomatology & National Clinical Research Center for Oral Diseases Harvard T.H. Chan School of Public Health Harvard University School of Software and Microelectronics Peking University IoT Thrust Information Hub Hong Kong University of Science and Technology Guangzhou Department of Computer Science ETH Zurich Institute of Data Science National University of Singapore

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Variable selection for genome-wide association studies (GWAS) has been a major research focus for decades. With the exponential growth of biological and biomedical data in the era of big data, scientists are confronted with the challenge of extracting meaningful information from vast datasets while managing the inherent heterogeneity in bioinformatics. To date, there are no highly effective tools that support high-dimensional datasets and achieve robust variable selection performance, all while accounting for the non-i.i.d. features and structured relatedness among explanatory and response *** address these challenges, we introduce the first high-performance computing framework for variable selection in GWAS. Our framework integrates various state-of-the-art methods, allowing researchers to easily combine different techniques and fully explore their potential. Additionally, our approach employs novel optimization strategies to solve the problem efficiently, even for high-dimensional data with sparse characteristics. By processing the data holistically, the framework delivers comprehensive analysis and accurate linkage mapping associations. Designed for ease of use, the framework is implemented in Python and offers seamless deployment, making it accessible to a wide range of researchers.

关键词： Accuracy High dimensional data Input variables High performance computing Instruments Noise Genomics Feature extraction Bioinformatics Optimization