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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Hu, Qiqi Chen, Jianxi Feng, Dan Yang, Qing Liu, Bo Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Huazhong University of Science and Technology Wuhan China Hikstor Technology Co. LTD. Zhejiang China

ISBN: (纸本)9781728120584

Since the number of NAND flash write cycles reaches the upper limit, data cannot be reliably stored. Therefore, the lifespan of Solid State Disks (SSDs) is limited, making it impossible to become a reliable storage device in a write-intensive data center. Deduplication can effectively reduce write traffic and increase the lifespan of SSDs. However, the fingerprint calculation overhead in the traditional data deduplication scheme is too large, which will reduce the write performance of the SSDs. In this paper, we propose a new deduplication scheme D-pblk based on Open-Channel SSDs(OCSSDs), which can reduce fingerprint computing overhead with modern high performance CPUs. In D-pblk, we use the light-weight hash CRC32 to filter most of the non-duplicated data, and When CRC32 is first hit, we read the data from Open-Channel SSDs and calculate the heavy-weight hash SHA-1 for accurate comparison, which reducing fingerprint computing overhead and hardly affects the deduplication rate of workloads. And we use multi-thread to calculate fingerprints in parallel, further reducing fingerprint computing overhead. In addition, we use double ring buffers to solve the problem that the data size after deduplication may not match the size of a flash page. We use FEMU to simulate Open-Channel SSDs for evaluation. The experimental results show that D-pblk can achieve the deduplication rate ranging from 4.61% to 31.63% and the write latency is improved by a factor of up to 29%. © 2019 IEEE.

关键词： Program processors

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PDRM: A Probability Distribution Based Resource Management for Batch Workloads in Heterogeneous Cluster 16th

PDRM: A Probability Distribution Based Resource Management f...

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16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019

作者： Zhou, Jun Feng, Dan Wang, Fang School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Wuhan National Laboratory for Optoelectronics Wuhan430074 China Key Laboratory of Information Storage System Engineering Research Center of data storage systems and Technology Ministry of Education of China Wuhan China

ISBN: (纸本)9783030307080

Resource consumption prediction and dynamic resource provision based on historical consumption are common methods to improve cluster resource utilization, however they have to face the challenge of fluctuation in resource consumption for accurate prediction. We propose PDRM, an efficient resource management scheme based on resource consumption probability distribution for batch workloads to deal with this dilemma. Based on the common sense that the same type of tasks have similar resource consumption on the same node, we get the resource consumption probability distribution of each type of task to describe the fluctuations in its resource consumption. Based on the resource consumption distribution function, we can allocate resources precisely for tasks. Experimental results demonstrate that PDRM achieves good performance for various application in the heterogeneous cluster. PDRM can effectively improve resource utilization and reduce job completion time. © 2019, IFIP International Federation for Information Processing.

关键词： Big data

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Conditional Generative Modeling for Amorphous Multi-Element Materials

arXiv

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arXiv 2025年

作者： Li, Honglin Liu, Chuhao Guo, Yongfeng Luo, Xiaoshan Chen, Yijie Liu, Guangsheng Li, Yu Wang, Ruoyu Wang, Zhenyu Wu, Jianzhuo Ma, Cheng Xie, Zhuohang Lv, Jian Ding, Yufei Zhang, Huabin Luo, Jian Zhong, Zhicheng Li, Mufan Wang, Yanchao Li, Wan-Lu Key Laboratory of Material Simulation Methods and Software Ministry of Education College of Physics Jilin University Changchun China Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California La Jolla San DiegoCA United States Institute of Molecular Engineering Plus College of Chemistry Fuzhou University Fuzhou China College of Chemistry and Molecular Engineering Peking University Beijing China School of Physics Nankai University Tianjin China Institute of Modern Physics Fudan University Shanghai China Program in Materials Science and Engineering University of California La Jolla San DiegoCA United States School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China International Center of Future Science Jilin University Changchun China Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Center for Renewable Energy and Storage Technologies Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Suzhou Lab Suzhou215123 China

Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Amorphization

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NGenE 2021: Electrochemistry Is Everywhere

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ACS ENERGY LETTERS 2022年第1期7卷 368-374页

作者： Cabana, Jordi Alaan, Thomas Crabtree, George W. Hatzell, Marta C. Manthiram, Karthish Steingart, Daniel A. Zenyuk, Iryna Jiao, Feng Vojvodic, Aleksandra Yang, Jenny Y. Balsara, Nitash P. Persson, Kristin A. Siegel, Donald J. Haynes, Christy L. Mauzeroll, Janine Shen, Mei Venton, B. Jill Balke, Nina Rodriguez-Lopez, Joaquin Rolison, Debra R. Shahbazian-Yassar, Reza Srinivasan, Venkat Chaudhuri, Santanu Couet, Adrien Hattrick-Simpers, Jason Department of Chemistry University of Illinois at Chicago Chicago Illinois 60607 United States Department of Physics University of Illinois at Chicago Chicago Illinois 60607 United States Joint Center for Energy Storage Research Argonne National Laboratory Lemont Illinois 60439 United States George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia 30332 United States Division of Chemistry and Chemical Engineering California Institute of Technology Pasadena California 91125 United States Department of Chemical Engineering Columbia University New York New York 10027 United States Columbia Electrochemical Energy Center Columbia University New York New York 10027 United States Department of Earth and Environmental Engineering Columbia University New York New York 10027 United States Department of Chemical and Biomolecular Engineering University of California Irvine California 92697 United States Center for Catalytic Science and Technology Department of Chemical and Biomolecular Engineering University of Delaware Newark Delaware 19716 United States Department of Chemical and Biomolecular Engineering University of Pennsylvania Philadelphia Pennsylvania 19104 United States Department of Chemistry University of California Irvine California 92697 United States Department of Chemical and Biomolecular Engineering University of California Berkeley California 94720 United States Materials Science Division Lawrence Berkeley National Laboratory Berkeley California 94720 United States Molecular Foundry Lawrence Berkeley National Laboratory Berkeley California 94720 United States Department of Materials Science and Engineering University of California Berkeley California 94720 United States Walker Department of Mechanical Engineering University of Texas at Austin Austin Texas 78712 United States Department of Chemistry University of Minnesota Minneapolis Minnesota 55455 United States Department of Chemistry McGill

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Exploiting dynamic nonlinearity in upconversion nanoparticles for super-resolution imaging

arXiv

引用

arXiv 2022年

作者： Chen, Chaohao Ding, Lei Liu, Baolei Du, Ziqin Liu, Yongtao Di, Xiangjun Shan, Xuchen Lin, Chenxiao Zhang, Min Xu, Xiaoxue Zhong, Xiaolan Wang, Jianfeng Chang, Lingqian Halkon, Ben J. Chen, Xin Cheng, Faliang Wang, Fan Guangdong Engineering and Technology Research Center for Advanced Nanomaterials School of Environment and Civil Engineering Dongguan University of Technology Dongguan523808 China Department of Chemical Engineering Shaanxi Key Laboratory of Energy Chemical Process Intensification Institute of Polymer Science in Chemical Engineering School of Chemical Engineering and Technology Xi'an Jiaotong University Xi'An710049 China School of Mathematical and Physical Sciences Faculty of Science University of Technology SydneyNSW2007 Australia School of Physics Beihang University Beijing100191 China Smart Computational Imaging Laboratory Nanjing University of Science and Technology Jiangsu Province Nanjing210094 China Department for Electrochemical Energy Storage Helmholtz-Zentrum Berlin für Materialien und Energie Hahn-Meitner-Platz Berlin14109 Germany School of Biomedical Engineering Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing100191 China Centre for Audio Acoustics & Vibration Faculty of Engineering & IT University of Technology Sydney UltimoNSW2007 Australia School of Electrical and Data Engineering Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

Single-beam super-resolution microscopy, also known as superlinear microscopy, exploits the nonlinear response of fluorescent probes in confocal microscopy. The technique requires no complex purpose-built system, light field modulation, or beam shaping. Here, we present a strategy to enhance this technique's spatial resolution by modulating excitation intensity during image acquisition. This modulation induces dynamic optical nonlinearity in upconversion nanoparticles (UCNPs), resulting in variations of higher spatial-frequency information in the obtained images. The high-order information can be extracted with a proposed weighted finite difference imaging algorithm from raw fluorescence images, to generate an image with a higher resolution than superlinear microscopy images. We apply this approach to resolve two adjacent nanoparticles within a diffraction-limited area, improving the resolution to 130 nm. This work suggests a new scope for developing dynamic nonlinear fluorescent probes in super-resolution nanoscopy. © 2022, CC BY.

关键词： Nanoparticles

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SRSC: Improving Restore Performance for Deduplication-Based storage Systems

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ZTE Communications 2019年第2期17卷 59-66页

作者： ZUO Chunxue WANG Fang TANG Xiaolan ZHANG Yucheng FENG Dan Key Laboratory of Information Storage Systems Engineering Research Center of Data Storage Systems and TechnologyHuazhong University of Science and TechnologyWuhanHubei 430074China 5G Application Product Line ZTE CorporationShenzhenGuangdong 518057China

Modern backup systems exploit data deduplication technology to save stor-age space whereas suffering from the fragmentation problem caused by *** degrades the restore performance because of restoring the chunks thatare scattered all over different containers. To improve the restore performance, thestate-of-the-art History Aware Rewriting Algorithm(HAR) is proposed to collect frag-mented chunks in the last backup and rewrite them in the next backup. However, dueto rewriting fragmented chunks in the next backup, HAR fails to eliminate internalfragmentation caused by self-referenced chunks(that exist more than two times in abackup) in the current backup, thus degrading the restore performance. In this paper,we propose Selectively Rewriting Self-Referenced Chunks(SRSC), a scheme that de-signs a buffer to simulate a restore cache, identify internal fragmentation in the cacheand selectively rewrite them. Our experimental results based on two real-world datas-ets show that SRSC improves the restore performance by 45% with an acceptable sac-rifice of the deduplication ratio.

关键词： data deduplication fragmentation restore performance

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ReRAM Crossbar-Based Analog Computing Architecture for Naive Bayesian Engine

ReRAM Crossbar-Based Analog Computing Architecture for Naive...

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IEEE International Conference on Computer Design: VLSI in Computers and Processors, (ICCD)

作者： Bing Wu Dan Feng Wei Tong Jingning Liu Chengning Wang Wei Zhao Mengye Peng Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology (School of Computer Science and Technology Huazhong University of Science and Technology) Ministry of Education of China

Recent advances in Resistive RAM (ReRAM) have explored the in-situ Matrix-Vector Multiplication (MVM) ability of crossbar arrays to achieve high energy-efficiency Process-In-Memory (PIM) architectures for Convolutional Neural Network (CNN), image processing, and so on. However, the existing ReRAM-based PIM architectures suffer from considerable additional auxiliary logic and device variations. In this work, we propose a novel analog computing architecture NB Engine for classification by implementing Naive Bayesian (NB) algorithm on ReRAM crossbar arrays. The two key steps of the NB algorithm, that is, probability calculation and electing the class that has the highest probability, are elaborately accomplished in our architecture. The ReRAM arrays are both used as storage and computation components. We store the pre-calculated prior probabilities and conditional probabilities of every class in crossbar arrays. Then the probability calculation step is completed in parallel through the MVM operation of the array. In general, the election step is a multiple-comparison procedure and is normally implemented by a comparison tree. Here, we reuse the max pooling module in a conventional CNN PIM architecture to realize a compatible comparison logic. However, neither of the two designs can avoid the overhead of costly high bit-precision Analog-to-Digital Converters (ADCs). So we introduce a novel analog parallel comparison design which does not need any ADCs or other computing logic with better energy-saving and area-efficiency. Our proposed NB Engine is tested by 11 various datasets. The influence of several non-ideal device properties is discussed and the NB Engine exhibits great tolerance to these variations. The experiment results show that our design offers a runtime speedup up to 2289.6x compared with the software-implemented NB classifier with negligible accuracy loss. In addition, the NB Engine saves 96.2% energy consumption and 45.2% array area compared with the CNN P

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A Hypothesis on the Function of High-Valent Fe in NiFe (Hydr)oxide in the Oxygen-Evolution Reaction

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Angewandte Chemie 2024年第6期137卷

作者： Nader Akbari Jafar Hussain Shah Cejun Hu Subhajit Nandy Pavlo Aleshkevych Rile Ge Sumbal Farid Changchang Dong Liang Zhang Keun Hwa Chae Wei Xie Taifeng Liu Junhu Wang Mohammad Mahdi Najafpour Department of Chemistry Institute for Advanced Studies in Basic Sciences (IASBS) Zanjan 45137-66731 Iran CAS Key Laboratory of Science and Technology on Applied Catalysis Mössbauer Effect Data Center Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian 116023 China Key Lab of Advanced Energy Materials Chemistry (Ministry of Education) Renewable Energy Conversion and Storage Center College of Chemistry Nankai University Tianjin 300071 China Advanced Analysis Center Korea Institute of Science and Technology Seoul 02792 Republic of Korea Institute of Physics Polish Academy of Sciences Warsaw 02-668 Poland School of Environmental and Chemical Engineering Jiangsu University of Science and Technology Zhenjiang 212100 China National and Local Joint Engineering Research Center for Applied Technology of Hybrid Nanomaterials Henan University Kaifeng 475004 China Department of Chemistry Sharif University of Technology Tehran 11155-9516 Iran

This study investigated the dynamic changes in NiFe (hydr)oxide and identified the role of high-valent Fe in the oxygen-evolution reaction (OER) within alkaline media via in situ techniques. Several high-valent Fe ions were found to remain considerably stable in the absence of potential in NiFe (hydr)oxide, even 96 hours after the OER. For Ni 2+ hydroxide treated with 57 Fe ions, where Fe sites are introduced onto the surface of Ni 2+ hydroxide, no Fe 4+ species were detected at the rate-determining step (RDS). The findings of this study suggested that the oxidation of bulk Fe ions, similar to Ni ions, to high valent forms, is charge accumulation without a direct role in OER; these results offered a novel perspective on manipulating Fe states to optimize OER efficacy. The prevailing hypothesis suggested that trace amounts of high-valent Fe ions, notably those on the surface, directly participate in OER.

关键词： NiFe (hydr)oxide oxygen evolution reaction high-valent Fe4+ in situ techniques electrocatalysts alkaline conditions mechanism active sites

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Analyses of geographical observations in the Heihe River Basin: Perspectives from complexity theory

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Journal of Geographical Sciences 2019年第9期29卷 1441-1461页

作者： Gao Jianbo FANG Peng YUAN Lihua State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Institute of Complexity Science and Big Data Technology Guangxi UniversityNanning 530004China Wuhan National Laboratory for Optoelectronics Key Laboratory of In formation Storage SystemEngineering Research Center of Data Storage Systems and TechnologyMinistry of Education of ChinaSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Center for GeoData and Analysis Faculty of Geographical ScieneeBeijing Normal UniversityBeijing 100875China

Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been *** adequately analyze these available data and data to be further collected in future,we present a perspective from complexity *** concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process *** adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal *** SDLE is illustrated to determine intermittent chaos from river flow data.

关键词： Heihe River basin geographical observation complexity theory adaptive multiscale filter fractal analysis scale-dependent Lyapunov exponent

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Reconstruction of Solid Electrolyte Interphase with SrI2Reactivates Dead Li for Durable Anode-Free Li-Metal Batteries

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Angewandte Chemie 2023年第23期135卷

作者： Dr. Liwei Dong Dr. Shijie Zhong Dr. Botao Yuan Dr. Yaqiang Li Dr. Jipeng Liu Dr. Yuanpeng Ji Dr. Dongjiang Chen Dr. Yuanpeng Liu Prof. Chunhui Yang Prof. Jiecai Han Prof. Weidong He National Key Laboratory of Science and Technology on Advanced Composites in Special Environments and Center for Composite Materials and Structures Harbin Institute of Technology Harbin 150080 China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150080 China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of Technology Harbin 150080 China Contribution: Conceptualization (lead) Data curation (lead) Writing - original draft (lead) Contribution: Conceptualization (equal) Data curation (equal) Contribution: Data curation (equal) Investigation (equal) Contribution: Data curation (supporting) Writing - original draft (supporting) Contribution: Conceptualization (supporting) Data curation (supporting) Chongqing Research Institute Harbin Institute of Technology Chongqing 401151 China Contribution: Investigation (supporting) Writing - review & editing (supporting) Contribution: Data curation (supporting) Investigation (supporting) Contribution: Project administration (supporting) Resources (supporting) Contribution: Conceptualization (supporting) Project administration (supporting) Resources (supporting) School of Mechanical Engineering Chengdu University Chengdu 610106 China Contribution: Conceptualization (equal) Project administration (equal) Writing - original draft (equal)

Without excess Li, anode-free Li-metal batteries (AFLMBs) have been proposed as the most likely solution to realizing highly-safe and cost-effective Li-metal batteries. Nevertheless, short cyclic life puzzles conventional AFLMBs due to anodic dead Li accumulation with a local current concentration induced by irreversible electrolyte depletion, insufficient active Li reservoir and slow Li + transfer at the solid electrolyte interphase (SEI). Herein, SrI 2 is introduced into carbon paper (CP) current collector to effectively suppress dead Li through synergistic mechanisms including reversible I − /I 3 − redox reaction to reactivate dead Li, dielectric SEI surface with SrF 2 and LiF to prevent electrolyte decomposition and highly ionic conductive (3.488 mS cm −1 ) inner layer of SEI with abundant LiI to enable efficient Li + transfer inside. With the SrI 2 -modified current collector, the NCM532/CP cell delivers unprecedented cyclic performances with a capacity of 129.2 mAh g −1 after 200 cycles.

关键词： Anode-Free Li-Metal Batteries Current Collector Dead Li SrF2 SrI2

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