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arXiv 2020年

作者： Barbosa, Carlos H.S. Kunstmann, Liliane N.O. Silva, Rômulo M. Alves, Charlan D.S. Silva, Bruno S. Filho, Djalma M.S. Mattoso, Marta Rochinha, Fernando A. Coutinho, Alvaro L.G.A. High-Performance Computing Center COPPE Federal University of Rio de Janeiro Brazil Department of Civil Engineering COPPE Federal University of Rio de Janeiro Brazil Department of Mechanical Engineering COPPE Federal University of Rio de Janeiro Brazil Department of Computer Science COPPE Federal University of Rio de Janeiro Brazil CENPES Petrobras

The interpretation of seismic images faces challenges due to the presence of several uncertainty sources. Uncertainties exist in data measurements, source positioning, and subsurface geophysical properties. Understanding uncertainties' role and how they influence the outcome is an essential part of the decision-making process in the oil and gas industry. Geophysical imaging is time-consuming. When we add uncertainty quantification, it becomes both time and data-intensive. In this work, we propose a workflow for seismic imaging with quantified uncertainty. We build the workflow upon Bayesian tomography, reverse time migration, and image interpretation based on statistical information. The workflow explores an efficient hybrid parallel computational strategy to decrease the reverse time migration execution time. high levels of data compression are applied to reduce data transfer among workflow activities and data storage. We capture and analyze provenance data at runtime to improve workflow execution, monitoring, and debugging with negligible overhead. Numerical experiments on the Marmousi2 Velocity Model Benchmark demonstrate the workflow capabilities. We observe excellent weak and strong scalability, and results suggest that the use of lossy data compression does not hamper the seismic imaging uncertainty quantification. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Improving unsupervised domain adaptation by reducing bi-level feature redundancy

arXiv

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arXiv 2020年

作者： Wang, Mengzhu Zhang, Xiang Lan, Long Wang, Wei Tan, Huibin Luo, Zhigang Science and Technology on Parallel and Distributed Laboratory College of Computer National University of Defense Technology Changsha China Institute for Quantum State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China DUT-RU International School of Information Science & Engineering Dalian University of Technology DalianLiaoning116000 China Department of Science and Technology on Parallel and Distributed Processing National University of Defense Technology Changsha China

Reducing feature redundancy has shown beneficial effects for improving the accuracy of deep learning models, thus it is also indispensable for the models of unsupervised domain adaptation (UDA). Nevertheless, most recent efforts in the field of UDA ignore this point. Moreover, main schemes realizing this in general independent of UDA purely involve a single domain, thus might not be effective for cross-domain tasks. In this paper, we emphasize the significance of reducing feature redundancy for improving UDA in a bi-level way. For the first level, we try to ensure compact domain-specific features with a transferable decorrelated normalization module, which preserves specific domain information whilst easing the side effect of feature redundancy on the sequel domain-invariance. In the second level, domain-invariant feature redundancy caused by domain-shared representation is further mitigated via an alternative brand orthogonality for better generalization. These two novel aspects can be easily plugged into any BN-based backbone neural networks. Specifically, simply applying them to ResNet50 has achieved competitive performance to the state-of-the-arts on five popular benchmarks. Our code will be available at https://***/dreamkily/gUDA. © 2020, CC BY.

关键词： Deep learning

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SEBF: A single-chain based extension model of blockchain for fintech 29

SEBF: A single-chain based extension model of blockchain for...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Ji, Yimu Gu, Weiheng Chen, Fei Xiao, Xiaoying Sun, Jing Liu, Shangdong He, Jing Li, Yunyao Zhang, Kaixiang Mei, Fen Wu, Fei School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Institue of High Performance Computing and Bigdata Nanjing University of Posts and Telecommunications Nanjing China Nanjing Center of HPC China Nanjing China Jiangsu HPC and Intelligent Processing Engineer Research Center Nanjing China Institute of Information Technology Nanjing University of Finance and Economics Nanjing China School of Software and Electrical Engineering Swinburne University of Technology Hawthorn Australia WeBank Co. Ltd. Shenzhen China College of Automation Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9780999241165

The traditional blockchain has the shortcoming that a single-chain can only deal with one or a few specific data types. The research question of how to make blockchain be able to deal with various data types has not been well studied. In this paper, we propose a single-chain based extension model of blockchain for fintech (SEBF). In the financial environment, we design a four-layer architecture for this model. By employing the external trusted oracle group and a financial regulator agency, a variety types of data can be effectively stored in the blockchain, such that the data type extension based on a single-chain is realized. The experimental results indicate that the proposed model can improve the efficiency of simplified payment verification. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Blockchain

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Sulfurized Composite Interphase Enables a highly Reversible Zn Anode

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Angewandte Chemie 2024年第7期137卷

作者： Lu Wu Dr. Hao Yuan Yongkang An Dr. Jianguo Sun Yu Liu Dr. Han Tang Wei Yang Lianmeng Cui Jinghao Li Prof. Qinyou An Prof. Yong-Wei Zhang Prof. Lin Xu Prof. Liqiang Mai State Key Laboratory of Advanced Technology for Materials Synthesis and Processing School of Materials Science and Engineering Wuhan University of Technology Wuhan 430070 China Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Department of Materials Science and Engineering National University of Singapore Singapore 117574 Singapore Hubei Provincial Key Laboratory of Green Materials for Light Industry School of Materials and Chemical Engineering Hubei University of Technology Wuhan 430068 China Hubei Longzhong Laboratory Wuhan University of Technology (Xiangyang Demonstration Zone) Xiangyang 441000 China Zhongyu Feima New Material Technology Innovation Center (Zhengzhou) Co. Ltd. Zhengzhou 450001 China

The stability and reversibility of Zn anode can be greatly improved by in situ construction of solid electrolyte interphase (SEI) on Zn surface via a low-cost design strategy of ZnSO 4 electrolyte. However, the role of hydrogen bond acceptor -SO 3 accompanying ZnS formation during SEI reconstruction is overlooked. In this work, we have explored and revealed the new role of -SO 3 and ZnS in the in situ formed sulfide composite SEI (SCSEI) on Zn anode electrochemistry in ZnSO 4 aqueous electrolytes. Structure characterization and DFT demonstrate that the introduction of -SO 3 can not only reduce the dehydration energy of [Zn(H 2 O) 6 ] 2+ , but also enhance the stability of the ZnS/Zn interface and homogenize the ZnS/Zn interface electric field, thereby significantly improving the dynamic kinetics and uniform deposition of Zn 2+ . Owing to the synergistic effect of ZnS and -SO 3 , a high cycling stability of 1500 h with a cumulative-plated capacity of 7.5 Ah cm −2 at 10 mA cm −2 has been achieved within the symmetrical cell. Furthermore, the full cell with NH 4 V 4 O 10 cathode exhibits outstanding cyclic stability, exceeding 2000 cycles at 5 A g −1 and maintaining a Coulombic efficiency of 100 %. These new insights into anionic synergistic strategy could significantly enhance the practical application of zinc-ion batteries.

关键词： electrolyte in situ sulfurized SEI anionic synergistic zinc ion batteries

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Recent Progress in Metasurfaces: An Introductory Note from Fundamentals and Design Methods to Applications

World Scientific Annual Review of Functional Materials

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World Scientific Annual Review of Functional Materials 2024年第2期wsarfm卷

作者： Wei Chen Jiaqing Shen Yujie Ke Yuwei Hu Lin Wu Jinfeng Zhu Zhaogang Dong Institute of Electromagnetics and Acoustics and Key Laboratory of Electromagnetic Wave Science and Detection Technology Xiamen University Xiamen Fujian 361005 P. R. China Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A*STAR) 2 Fusionopolis Way Innovis #08-03 Singapore 138634 Singapore Science Mathematics and Technology (SMT) Singapore University of Technology and Design (SUTD) 8 Somapah Road Singapore 487372 Singapore Institute of High Performance Computing A*STAR (Agency for Science Technology and Research) 1 Fusionopolis Way No. 16-16 Connexis Singapore 138632 Singapore Department of Materials Science and Engineering National University of Singapore 9 Engineering Drive 1 Singapore 117575 Singapore

Metasurfaces refer to the sub-wavelength nanostructures that are capable of manipulating the amplitude, phase, polarization, and other characteristics of light, to enable diverse applications across the ultraviolet, visible, infrared, and terahertz spectra. In this review paper, we aim to provide an introductory note on metasurfaces, from fundamentals and design methods to applications, such as biosensing, environmental monitoring, metalenses, optical cloaking, electromagnetic scattering, structural color, miniaturized devices, and others. Moreover, we also identify the key challenges and limitations of metasurfaces, such as fabrication, integration, optimization, tuning, signal processing, and analysis, and suggest possible directions and solutions for future research. At last, we envision several emerging and promising trends for metasurfaces, such as new materials and structures, new phenomena and mechanisms, machine learning, and artificial intelligence techniques. The review is expected to inspire future development in this exciting and rapidly evolving field of metasurface devices.

关键词： Metamaterial metasurface deep learning nanophotonics

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Gate-tunable cross-plane heat dissipation in single-layer transition metal dichalcogenides

arXiv

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arXiv 2020年

作者： Ong, Zhun-Yong Zhang, Gang Zhang, Yong-Wei Cao, Linyou Institute of High Performance Computing A*STAR Singapore138632 Singapore Department of Materials Science and Engineering North Carolina State University RaleighNC27695 United States Department of Physics North Carolina State University RaleighNC27695 United States Department of Electrical and Computer Engineering North Carolina State University RaleighNC27695 United States

Efficient heat dissipation to the substrate is crucial for optimal device performance in nanoelectronics. We develop a theory of electronic thermal boundary conductance (TBC) mediated by remote phonon scattering for the single-layer transition metal dichalcogenide (TMD) semiconductors MoS2 and WS2, and model their electronic TBC with different dielectric substrates (SiO2, HfO2 and Al2O3). Our results indicate that the electronic TBC is strongly dependent on the electron density, suggesting that it can be modulated by the gate electrode in field-effect transistors, and this effect is most pronounced with Al2O3. Our work paves the way for the design of novel thermal devices with gate-tunable cross-plane heat-dissipative properties. Copyright © 2020, The Authors. All rights reserved.

关键词： Aluminum oxide

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Charge state-dependent symmetry breaking of atomic defects in transition metal dichalcogenides

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Nature communications 2024年第1期15卷 2738页

作者： Feifei Xiang Lysander Huberich Preston A Vargas Riccardo Torsi Jonas Allerbeck Anne Marie Z Tan Chengye Dong Pascal Ruffieux Roman Fasel Oliver Gröning Yu-Chuan Lin Richard G Hennig Joshua A Robinson Bruno Schuler nanotech@surfaces Laboratory Empa - Swiss Federal Laboratories for Materials Science and Technology Dübendorf 8600 Switzerland. Department of Materials Science and Engineering University of Florida Gainesville FL 32611 USA. Department of Materials Science and Engineering The Pennsylvania State University University Park PA 16082 USA. Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) Singapore 138632 Republic of Singapore. Two-Dimensional Crystal Consortium The Pennsylvania State University University Park PA 16802 USA. Department of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu City 300 Taiwan ROC. Department of Chemistry and Department of Physics The Pennsylvania State University University Park PA 16802 USA. nanotech@surfaces Laboratory Empa - Swiss Federal Laboratories for Materials Science and Technology Dübendorf 8600 Switzerland. bruno.schuler@empa.ch.

The functionality of atomic quantum emitters is intrinsically linked to their host lattice coordination. Structural distortions that spontaneously break the lattice symmetry strongly impact their optical emission properties and spin-photon interface. Here we report on the direct imaging of charge state-dependent symmetry breaking of two prototypical atomic quantum emitters in mono- and bilayer MoS by scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM). By changing the built-in substrate chemical potential, different charge states of sulfur vacancies (Vac) and substitutional rhenium dopants (Re) can be stabilized. Vac as well as Re and Re exhibit local lattice distortions and symmetry-broken defect orbitals attributed to a Jahn-Teller effect (JTE) and pseudo-JTE, respectively. By mapping the electronic and geometric structure of single point defects, we disentangle the effects of spatial averaging, charge multistability, configurational dynamics, and external perturbations that often mask the presence of local symmetry breaking.

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The Power Of Triply Complementary Priors For Image Compressive Sensing

The Power Of Triply Complementary Priors For Image Compressi...

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IEEE International Conference on Image Processing

作者： Zhiyuan Zha Xin Yuan Joey Tianyi Zhou Jiantao Zhou Bihan Wen Ce Zhu School of Electrical & Electronic Engineering Nanyang Technological University Singapore Nokia Bell Labs 600 Mountain Avenue Murray Hill NJ USA Institute of High Performance Computing A&STAR Singapore Department of Computer and Information Science University of Macau Macau China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Recent works that utilized deep models have achieved superior results in various image restoration applications. Such approach is typically supervised which requires a corpus of training images with distribution similar to the images to be recovered. On the other hand, the shallow methods which are usually unsupervised remain promising performance in many inverse problems, e.g., image compressive sensing (CS), as they can effectively leverage non-local self-similarity priors of natural images. However, most of such methods are patch-based leading to the restored images with various ringing artifacts due to naive patch aggregation. Using either approach alone usually limits performance and generalizability in image restoration tasks. In this paper, we propose a joint low-rank and deep (LRD) image model, which contains a pair of triply complementary priors, namely external and internal, deep and shallow, and local and nonlocal priors. We then propose a novel hybrid plug-and-play (H-PnP) framework based on the LRD model for image CS. To make the optimization tractable, a simple yet effective algorithm is proposed to solve the proposed H-PnP based image CS problem. Extensive experimental results demonstrate that the proposed H-PnP algorithm significantly outperforms the state-of-the-art techniques for image CS recovery such as SCSNet and WNNM.

关键词： Image restoration Optimization Inverse problems Standards Noise reduction Compressed sensing Sensors

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CDNET: A Content Delivery Network Emulator

CDNET: A Content Delivery Network Emulator

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International Symposium on Networks, computers and Communications (ISNCC)

作者： Hoang-Loc La Anh-Tu Ngoc Tran Masato Yoshimi Takuma Nakajima Nam Thoai High Performance Computing Laboratory Advanced Institute of Interdisciplinary Science and Technology Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh City Vietnam Strategic Technology Center TIS Inc. Shinjuku-ku Tokyo Japan Service Strategy Sector TIS Inc. Shinjuku-ku Tokyo Japan

Analyzing Content Delivery Network (CDN) systems’ performance can help the CDNs’ owners increase their benefits, improve the systems’ service quality, and reduce investment costs. To analyze caching systems, besides mathematical models, there are simulation-based methods, which are based on virtual environments to mimic the system behaviors, typically, such as CDN simulators and testbeds. But these simulators and testbeds have their limitations. In particular, simulators cannot guarantee the functional realism of service applications. Meanwhile, testbeds are cumbersome and inflexible to adapt to new topologies or caching strategies. In this work, we develop a CDN emulator, which is adaptive, flexible, high-fidelity, and reliable. To evaluate the reproducibility of experimental results, we also run our tools multiple configuration parameter sets and compare the results with a discrete event simulation. Our experiments show that our emulator is stable and works properly. The tool’s resource consumption is also evaluated.

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Resolving the GPU responsiveness dilemma through program transformations

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Frontiers of computer science 2018年第3期12卷 545-559页

作者： Qi ZHU Bo WU Xipeng SHEN Kai SHEN Li SHEN Zhiying WANG National Key Laboratory of High Performance Computing National University of Defense Technology Changsha 410073 China Jiangnan Institute of Computing Technology Wuxi 214083 China Department of Computer Science North Carolina State University Raleigh NC 27695 USA EECS Colorado School of Mines Golden CO 80401 USA Department of Computer Science University of Rochester Rochester NY 14627 USA

The emerging integrated CPU-GPU architectures facilitate short computational kernels to utilize GPU acceleration. Evidence has shown that, on such systems, the GPU control responsiveness （how soon the host program finds out about the completion of a GPU kernel） is essential for the overall performance. This study identifies the GPU responsiveness dilemma： host busy polling responds quickly, but at the expense of high energy consumption and interference with co-running CPU programs; interrupt-based notification minimizes energy and CPU interference costs, but suffers from substantial response delay. We present a programlevel solution that wakes up the host program in anticipation of GPU kernel completion. We systematically explore the design space of an anticipatory wakeup scheme through a timerdelayed wakeup or kernel splitting-based pre-completion notification. Experiments show that our proposed technique can achieve the best of both worlds, high responsiveness with low power and CPU costs, for a wide range of GPU workloads.

关键词： program transformation GPU integrated architecture responsiveness

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