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作者： Harrison, Robert J. Beylkin, Gregory Bischoff, Florian A. Calvin, Justus A. Fann, George I. Fosso-Tande, Jacob Galindo, Diego Hammond, Jeff R. Hartman-Baker, Rebecca Hill, Judith C. Jia, Jun Kottmann, Jakob S. Ou, M-J. Yvonne Pei, Junchen Ratcliff, Laura E. Reuter, Matthew G. Richie-Halford, Adam C. Romero, Nichols A. Sekino, Hideo Shelton, William A. Sundahl, Bryan E. Thornton, W. Scott Valeev, Edward F. Vázquez-Mayagoitia, Álvaro Vence, Nicholas Yanai, Takeshi Yokoi, Yukina Stony Brook University Stony BrookNY11794 United States University of Colorado at Boulder BoulderCO80309 United States Institut für Chemie Humboldt-Universität Zu Berlin Unter den Linden 6 Berlin10099 Germany Department of Chemistry Virginia Tech. BlacksburgVA24061 United States Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Chemistry and Biochemistry Florida State University TallahasseeFL32306 United States Parallel Computing Lab Intel Corporation PortlandOR97219 United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA94720 United States LinkedIn Mountain ViewCA94043 United States Department of Mathematical Sciences University of Delaware NewarkDE19716 United States State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Beijing100871 China Argonne Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Department of Physics University of Washington SeattleWA98195 United States Computer Science and Engineering Toyohashi University of Technology ToyohashiAichi441-8580 Japan Louisiana State University Baton RougeLA70803 United States Department of Physics LaSierra University RiversideCA92505 United States Theoretical and Computational Molecular Science Institute for Molecular Science OkazakiAichi444-8585 Japan

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics. © 2016 Society for Industrial and Applied mathematics.

关键词： Multiresolution analysis

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Two-component dissipative particle dynamics model of red blood cell membranes 30

Two-component dissipative particle dynamics model of red blo...

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30th Annual Technical Conference of the American Society for Composites, ASC 2015

作者： Peng, Z. Li, X. Pivkin, I. Karniadakis, G. Dao, Ming Department of Aerospace and Mechanical Engineering University of Notre Dame 369 Fitzpatrick Hall Notre DameIN46556 United States Department of Applied Mathematics Brown University ProvidenceRI77204 United States Institute of Computational Science Faculty of Informatics University of Lugano Lugano6904 Switzerland Department of Materials Science and Engineering Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States

ISBN: (纸本)9781605952253

By modeling the lipid bilayer and the cytoskeleton as two distinct layers, we developed a two-layer whole cell dissipative particle dynamics (DPD) model of erythrocyte membranes to investigate quasi-static, thermal and dynamic problems. First, we validated our two-layer DPD model by simulating the membrane thermal fluctuations of healthy and malaria-infected erythrocytes. We found that the bilayer-skeletal interaction plays a significant role and the two-layer DPD model matches the experiment better than the one-layer DPD model. In addition, by simulating the bilayer-skeletal detachment in a flow channel experiment, we predicted the interaction strength at the molecular level. Copyright © 2015 by DEStech Publications, Inc. and American Society for Composites. All rights reserved.

关键词： Lipid bilayers

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KM3NeT front-end and readout electronics system: Hardware, firmware and software

arXiv

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arXiv 2019年

作者： Aiello, S. Ameli, F. Andre, M. Androulakis, G. Anghinolfi, M. Anton, G. Ardid, M. Aublin, J. Bagatelas, C. Barbarino, G. Baret, B. Basegmez Du Pree, S. Belias, A. Bendahman, M. Berbee, E. Van Den Berg, A.M. Bertin, V. Van Beveren, V. Biagi, S. Biagioni, A. Bissinger, M. Bos, P. Boumaaza, J. Bourret, S. Bouta, M. Bouvet, G. Bouwhuis, M. Bozza, C. Brânzaş, H. Briel, M.M. Bruchner, M. Bruijn, R. Brunner, J. Buis, E. Buompane, R. Busto, J. Calvo, D. Capone, A. Celli, S. Chabab, M. Chau, N. Cherubini, S. Chiarella, V. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Colomer Molla, M. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. D'Amico, A. D'Onofrio, A. Dallier, R. De Palma, M. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donà, R. Donzaud, C. Dornic, D. Dörr, M. Durocher, M. Eberl, T. Van Eeden, T. El Bojaddaini, I. Eljarrari, H. Elsaesser, D. Enzenhöfer, A. Fermani, P. Ferrara, G. Filipović, M.D. Fusco, L.A. Gajanana, D. Gal, T. Garcia Soto, A. Garufi, F. Gialanella, L. Giorgio, E. Gozzini, S.R. Gracia, R. Graf, K. Grasso, D. Grégoire, T. Grella, G. Guderian, D. Guidi, C. Hallmann, S. Hamdaoui, H. Van Haren, H. Heijboer, A. Hekalo, A. Hernández-Rey, J.J. Hofestädt, J. Huang, F. Huesca Santiago, E. Illuminati, G. James, C.W. Jansweijer, P. Jongen, M. De Jong, M. De Jong, P. Kadler, M. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Van Der Knaap, F. Koffeman, E.N. Kooijman, P. Kouchner, A. Kreter, M. Kulikovskiy, V. Lahmann, R. Larosa, G. Le Breton, R. Leone, F. Leonora, E. Levi, G. Lincetto, M. Lonardo, A. Longhitano, F. Lopez-Coto, D. Maggi, G. Mańczak, J. Mannheim, K. Margiotta, A. Marinelli, A. Markou, C. Martignac, G. Martin, L. Martínez-Mora, J.A. Martini, A. Marzaioli, F. Mazzou, S. Mele, R. Melis, K.W. Migliozzi, P. Migneco, E. Mijakowski, P. Miranda, L.S. Mollo, C.M. Morganti, M. Moser, M. Moussa, A. Muller, R. Musico, P. Musumeci, M. Nauta, L. Navas, S. INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Centre for Astroparticle Physics Erwin-Rommel-Straße 1 Erlangen91058 Germany Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain APC Université Paris Diderot CNRS/IN2P3 CEA/IRFU Observatoire de Paris Sorbonne Paris Cité Paris75205 France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 R.P Rabat10000 Morocco KVI-CART University of Groningen Groningen Netherlands Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France INFN Laboratori Nazionali del Sud Via S. Sofia 62 Catania95123 Italy University Mohammed I Faculty of Sciences BV Mohammed VI B.P. 717 R.P Oujda60000 Morocco Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie NantesBP20722 44307 France Università di Salerno INFN Gruppo Collegato di Salerno Dipartimento di Fisica Via Giovanni Paolo II 132 Fisciano84084 Italy ISS Atomistilor 409 MagureleRO-077125 Romania University of Amsterdam Institute of Physics/IHEF PO Box 94216 Amsterdam1090 GE Netherlands TNO T

The KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host water-Cherenkov telescopes for the detection of cosmic neutrinos. The neutrino telescopes will consist of large volume three-dimensional grids of optical modules to detect the Cherenkov light from charged particles produced by neutrino-induced interactions. Each optical module houses 31 3-inch photomultiplier tubes, instrumentation for calibration of the photomultiplier signal and positioning of the optical module and all associated electronics boards. By design, the total electrical power consumption of an optical module has been capped at seven watts. This paper presents an overview of the front-end and readout electronics system inside the optical module, which has been designed for a 1 ns synchronization between the clocks of all optical modules in the grid during a life time of at least 20 years. Copyright © 2019, The Authors. All rights reserved.

关键词： Charged particles

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Simulation of Electrohydrodynamic Phenomenon using computational Intelligence Methods

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Procedia Computer science 2015年 60卷 188-196页

作者： Jolanta Wojtowicz Hubert Wojtowicz Wieslaw Wajs University of Rzeszow Faculty of Mathematics and Nature Chair of Computer Science Rzeszow Poland University of Rzeszow Faculty of Mathematics and Nature Interdisciplinary Centre for Computational Modelling Rzeszow Poland AGH University of Science and Technology Faculty of Electrical Engineering Institute of Automatics Cracow Poland

The electrohydrodynamic effect occurring during an underwater electrical explosion of a copper wire and method of its simulation using computational intelligence algorithms are presented in the paper. Principles of operation of the seismic wave EHD generator are explained. Differential equations describing a mathematical model of changes in a release circuit of the EHD generator are provided. The results of computations of differential equations, using Runge -Kutta algorithm, are provided. The simulation is based on current intensity and pressure data sets recorded during field experiments and data obtained by solving differential equations of the theoretical model. The relationships between electrical parameters of the electrohydrodynamic discharge circuit, material parameters of the exploded wire and result- ing pressure values of the shock wave are discussed. A regression model is created using computational intelligence algorithms for prediction of pressure values of a seismic wave resulting from the explosion of the wire. The results of the prediction of the pressure wave using neural networks are presented in the paper and verified by comparing the measured and calculated values of the pressure wave.

关键词： electrohydrodynamic effect computer simulation prediction using regression model computational intelligence algorithms

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Investigation on the influence of atomic potentials on the above threshold ionization

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Chinese Physics B 2014年第5期23卷 238-243页

作者：田原野李苏宇魏珊珊郭福明曾思良陈基根杨玉军 Institute of Atomic and Molecular Physics Jilin University Data Center for High Energy Density Physics Institute of Applied Physics and Computational Mathematics Science and Technology Computation Physics Laboratory Institute of Applied Physics and Computational Mathematics Department of Physics and Materials Engineering Taizhou University

We systematically investigate the influence of atomic potentials on the above-threshold ionization （ATI） spectra in one-dimensional （1D） cases and compare them with the three-dimensional （3D） case by numerically solving the time-dependent Schrrdinger equation. It is found that the direct ionization plateau and the rescattering plateau of the ATI spectrum in the 3D case can be well reproduced by the 1D ATI spectra calculated from the supersolid-core potential and the soft-core potential, respectively. By analyzing the factors that affect the yield of the ATI spectrum, we propose a modified-potential with which we can reproduce the overall 3D ATI spectrum. In addition, the influence of the incident laser intensities and frequencies on the ATI spectra calculated from the proposed modified potential is studied.

关键词： above threshold ionization model potential angular distribution of photoelectron

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Scalable Bayesian optimization using deep neural networks 32

Scalable Bayesian optimization using deep neural networks

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32nd International Conference on Machine Learning, ICML 2015

作者： Snoek, Jasper Ripped, Oren Swersky, Kevin Kiros, Ryan Satish, Nadathur Sundaram, Narayanan Patwary, Md. Mostofa Ali Prabhat Adams, Ryan P. Harvard University School of Engineering and Applied Sciences United States Massachusetts Institute of Technology Department of Mathematics United States University of Toronto Department of Computer Science Canada Intel Labs Parallel Computing Lab Switzerland NERSC Lawrence Berkeley National Laboratory United States

ISBN: (纸本)9781510810587

Bayesian optimization is an effective methodology for the global optimization of functions with expensive evaluations. It relies on querying a distribution over functions defined by a relatively cheap surrogate model. An accurate model for this distribution over functions is critical to the effectiveness of the approach, and is typically fit using Gaussian processes (GPs). However, since GPs scale cubically with the number of observations, it has been challenging to handle objectives whose optimization requires many evaluations, and as such, massively parallelizing the optimization. In this work, we explore the use of neural networks as an alternative to GPs to model distributions over functions. We show that performing adaptive basis function regression with a neural network as the parametric form performs competitively with state-of-the-art GP-based approaches, but scales linearly with the number of data rather than cubically. This allows us to achieve a previously intractable degree of parallelism, which we apply to large scale hyperparameter optimization, rapidly finding competitive models on benchmark object recognition tasks using convolutional networks, and image caption generation using neural language models. © Copyright 2015 by International Machine Learning Society (IMLS). All rights reserved.

关键词： Global optimization

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FlashGraph: Processing billion-node graphs on an array of commodity SSDs 13

FlashGraph: Processing billion-node graphs on an array of co...

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13th USENIX Conference on File and Storage Technologies, FAST 2015

作者： Zheng, Da Mhembere, Disa Burns, Randal Vogelstein, Joshua Priebe, Carey E. Szalay, Alexander S. Department of Computer Science Johns Hopkins University United States Institute for Computational Medicine Department of Biomedical Engineering Johns Hopkins University United States Department of Applied Mathematics and Statistics Johns Hopkins University United States Department of Physics and Astronomy Johns Hopkins University United States

ISBN: (纸本)9781931971201

Graph analysis performs many random reads and writes, thus, these workloads are typically performed in memory. Traditionally, analyzing large graphs requires a cluster of machines so the aggregate memory exceeds the graph size. We demonstrate that a multicore server can process graphs with billions of vertices and hundreds of billions of edges, utilizing commodity SSDs with minimal performance loss. We do so by implementing a graph-processing engine on top of a user-space SSD file system designed for high IOPS and extreme parallelism. Our semi-external memory graph engine called FlashGraph stores vertex state in memory and edge lists on SSDs. It hides latency by overlapping computation with I/O. To save I/O bandwidth, FlashGraph only accesses edge lists requested by applications from SSDs;to increase I/O throughput and reduce CPU overhead for I/O, it conservatively merges I/O requests. These designs maximize performance for applications with different I/O characteristics. FlashGraph exposes a general and flexible vertex-centric programming interface that can express a wide variety of graph algorithms and their optimizations. We demonstrate that FlashGraph in semi-external memory performs many algorithms with performance up to 80% of its in-memory implementation and significantly outperforms PowerGraph, a popular distributed in-memory graph engine.

关键词： Engines

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Telescopic Hybrid Fast Solver for 3D Elliptic Problems with Point Singularities

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Procedia Computer science 2015年 51卷 2744-2748页

作者： Anna Paszyńska Konrad Jopek Krzysztof Banaś Maciej Paszyński Piotr Gurgul Andrew Lenerth Donald Nguyen Keshav Pingali Lisandro Dalcin Victor Calo Jagiellonian University Krakow Poland AGH University of Science and Technology Krakow Poland Institute for Computational and Engineering Sciences (ICES) TX USA Center for Numerical Porous Media King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Earth Science & Engineering and Center for Numerical Porous Media (KAUST) Applied Mathematics & Computational Science (KAUST)

This paper describes a telescopic solver for two dimensional h adaptive grids with point singularities. The input for the telescopic solver is an h refined two dimensional computational mesh with rectangular finite elements. The candidates for point singularities are first localized over the mesh by using a greedy algorithm. Having the candidates for point singularities, we execute either a direct solver, that performs multiple refinements towards selected point singularities and executes a parallel direct solver algorithm which has logarithmic cost with respect to refinement level. The direct solvers executed over each candidate for point singularity return local Schur complement matrices that can be merged together and submitted to iterative solver. In this paper we utilize a parallel multi-thread GALOIS solver as a direct solver. We use Incomplete LU Preconditioned Conjugated Gradients (ILUPCG) as an iterative solver. We also show that elimination of point singularities from the refined mesh reduces significantly the number of iterations to be performed by the ILUPCG iterative solver.

关键词： hybrid solver multi-frontal solver h adaptive finite element method ILUPCG GALO

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Historical typewritten document recognition using minimal user interaction 15

Historical typewritten document recognition using minimal us...

引用

3rd International Workshop on Historical Document Imaging and Processing, HIP 2015

作者： Retsinas, George Gatos, Basilis Antonacopoulos, Apostolos Louloudis, Georgios Stamatopoulos, Nikolaos Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research Demokritos AthensGR-15310 Greece School of Electrical and Computer Engineering National Technical University of Athens AthensGR-15773 Greece Research Lab School of Computing Science and Engineering University of Salford Greater ManchesterM5 4WT United Kingdom

ISBN: (纸本)9781450336024

Recognition of low-quality historical typewritten documents can still be considered as a challenging and difficult task due to several issues i.e. the existence of faint and degraded characters, stains, tears, punch holes etc. In this paper, we exploit the unique characteristics of historical typewritten documents in order to propose an efficient recognition methodology that requires minimum user interaction. It is based on a pre-processing stage in order to enhance the quality and extract connected components, on a semi-supervised clustering for detecting the most representative character samples and on a segmentation-free recognition stage based on a template matching and cross-correlation technique. Experimental results prove that even with minimum user interaction, the proposed method can lead to promising accuracy results. © 2015 ACM.

关键词： Template matching

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