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46th AIAA Fluid Dynamics Conference, 2016

作者： Sprague, Michael A. Boldyrev, Stanislav Chang, Choong-Seock Fischer, Paul Grout, Ray Gustafson, William I. Hittinger, Jeffrey A. F. Merzari, Elia Moser, Robert National Renewable Energy Laboratory 15013 DenverWest Parkway GoldenCO80401 United States University of Wisconsin-Madison MadisonWI53706 United States Princeton University PrincetonNJ08543 United States University of Illinois at Urbana-Champaign UrbanaIL61801 United States National Renewable Energy Laboratory GoldenCO80401 United States Pacific Northwest National Laboratory RichlandWA99352 United States Lawrence Livermore National Laboratory LivermoreCA94551 United States Argonne National Laboratory ArgonneIL60439 United States University of Texas at Austin AustinTX78712 United States Computational Science Center 15013 DenverWest Parkway United States Physics Department 1150 University Avenue United States Princeton Plasma Physics Laboratory P.O. Box 451 United States Department of Computer Science 201 North Goodwin Avenue United States Computational Science Center 5013 Denver West Parkway United States Atmospheric Sciences and Global Change Division P.O. Box 999 K9-30 United States Scientific Computing Group Center for Applied Scientific Computing PO Box 808 L-561 United States Mathematics and Computer Science 9700 S. Cass Avenue United States Institute for Computational Engineering and Sciences and Department of Mechanical Engineering 201 East 24th United States

ISBN: (数字)9781624104367

ISBN: (纸本)9781624104367

This paper summarizes the outcomes from the Turbulent Flow Simulation at the Exascale: Opportunities and Challenges Workshop, which was held 4-5 August 2015, and was sponsored by the U.S. Department of Energy (DOE) Office of Advanced scientific computing Research (ASCR). The workshop objectives were to define and describe the challenges and opportunities that computing at the exascale will bring to turbulent-flow simulations in applied science and technology. The need for accurate simulation of turbulent flows is evident across the DOE applied-science and engineering portfolios, including combustion, plasma physics, nuclear-reactor physics, wind energy, and atmospheric science. The work-shop brought together experts in turbulent-flow simulation, computational mathematics, and high-performance computing. Building upon previous ASCR workshops on exascale computing, participants defined a research agenda and path forward that will enable scientists and engineers to continually leverage, engage, and direct advances in computational systems on the path to exascale computing. © 2016, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Turbulent flow

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A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

A Scalable Real-Time Data Assimilation Framework for Predict...

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High Performance computing, Networking, Storage and Analysis, SC-W: Workshops of the International Conference for

作者： Junqi Yin Siming Liang Siyan Liu Feng Bao Hristo G. Chipilski Dan Lu Guannan Zhang National Center for Computational Science Oak Ridge National Laboratory Oak Ridge TN USA Department of Mathematics Florida State University Tallahassee FL USA Computational Science and Engineering Division Oak Ridge National Laboratory Oak Ridge TN USA Department of Scientific Computing Florida State University Tallahassee FL USA Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

AI-based foundation models like FourCastNet, GraphCast, ClimaX, and Pangu-Weather are revolutionizing weather and climate predictions but are not yet ready for operational use. Their limitation lies in the absence of a data assimilation system to incorporate real-time Earth system observations, crucial for accurately forecasting events like tropical cyclones and atmospheric rivers. To overcome these obstacles, we introduce a generic real-time data assimilation framework and demonstrate its end-to-end performance on the Frontier supercomputer. This framework comprises two primary modules: an ensemble score filter (EnSF), which significantly outperforms the state-of-the-art data assimilation method, e.g., the Local Ensemble Transform Kalman Filter (LETKF); and a vision transformer-based surrogate capable of real-time adaptation through the integration of observational data. We demonstrate both the strong and weak scaling of our framework up to 1024 GPUs on the Exascale supercomputer, Frontier. Our results not only illustrate the framework’s exceptional scalability on high-performance computing systems, but also demonstrate the importance of supercomputers in real-time data assimilation for weather and climate predictions. Even though the proposed framework is tested only on a benchmark surface quasi-geostrophic (SQG) turbulence system, it has the potential to be combined with existing AI-based foundation models, making it suitable for future operational implementations.

关键词： Earth Foundation models Computational modeling High performance computing Scalability Atmospheric modeling Supercomputers Real-time systems Numerical models Data assimilation

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scientific Data Management: An Orphan in the Database Community?

Scientific Data Management: An Orphan in the Database Commun...

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International Conference on Data Engineering

作者： Randal Burns Susan B. Davidson Yannis Ioannidis Miron Livny Jignesh M. Patel Moderator Assistant Professor Department of Computer Science Johns Hopkins University. Department Chair Weiss Professor of Computer and Information Science ACM Fellow a Fulbright scholar founding co-Director of the Center for Bioinformatics at UPenn (PCBI) Professor Department of Informatics & Telecommunications University of Athens ACM Fellow ACM SIGMOD Vice-Chair member of the Scientific Advisory Board Max Planck Institute for Informatics. Professor of Computer Sciences director of the Center for High Throughput Computing Associate Professor faculty member EECS department University of Michigan

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A Fast Rankability Method Based on Fuzzy Entropy

SSRN

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SSRN 2024年

作者： Kong, Lingping Velasquez, Juan D. Pant, Millie Pan, Jeng-Shyang Snášel, Václav Department of Computer Science VSB-Technical University of Ostrava Listpodu 17 Czech Republic Department of Industrial Engineering University of Chile O’Higgins 1058 Santiago Chile Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Uttarakhand Roorkee247667 India College of Computer Science and Engineering Shandong University of Science and Technology China School of Artificial Intelligence Nanjing University of Information Science and Technology 219 Ningliu Road China Instituto Sistemas Complejos de Ingeniería Santiago Chile Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Uttarakhand Roorkee247667 India

Rankability is a fundamental concept that evaluates a dataset's inherent capacity to establish a meaningful ranking of its elements, with widespread applications in web search, data mining, cybersecurity, and machine *** its significance, relatively little focus has been on evaluating datasets for ranking suitability. Several rankability measures have emerged, such as comparing graphs representing datasets with complete dominance graphs using combinatorial and linear algebraic techniques. However, these approaches typically involve solving eigenvalue problems for large matrices or training regression models on extensive datasets. In this paper, we propose to adopt efficient and straightforward statistical metrics, entropy, and variance to develop a novel rankability method. Our method is designed to be fast and efficient, addressing the challenges posed by existing techniques. We conducted experiments using three football tournament datasets, and the results demonstrate a strong correlation scores (correlation coefficients) in terms of Spearman and Kendall's tau evaluations with Elo rating, a system developed by Arpad Elo in the 1950s and applied in many competitions. Specifically, the Spearman correlation between the proposed method and the Elo rating reached 0.9205 on Atlantic Coast data with a p-value of 0.0004, which is higher than the compared algorithm by 0.2424 in correlation score. © 2024, The Authors. All rights reserved.

关键词： Entropy

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A hybrid FEM-PINN method for time-dependent partial differential equations

arXiv

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arXiv 2024年

作者： Feng, Xiaodong Shangguan, Haojiong Tang, Tao Wan, Xiaoliang Zhou, Tao Division of Science and Technology BNU-HKBU United International College Zhuhai519087 China School of Electrical and Computer Engineering Guangzhou Nanfang College Guangzhou510970 China Department of Mathematics Center for Computation and Technology Louisiana State University Baton Rouge70803 United States Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In this work, we present a hybrid numerical method for solving evolution partial differential equations (PDEs) by merging the time finite element method with deep neural networks. In contrast to the conventional deep learning-based formulation where the neural network is defined on a spatiotemporal domain, our methodology utilizes finite element basis functions in the time direction where the space-dependent coefficients are defined as the output of a neural network. We then apply the Galerkin or collocation projection in the time direction to obtain a system of PDEs for the space-dependent coefficients which is approximated in the framework of PINN. The advantages of such a hybrid formulation are twofold: statistical errors are avoided for the integral in the time direction, and the neural network’s output can be regarded as a set of reduced spatial basis functions. To further alleviate the difficulties from high dimensionality and low regularity, we have developed an adaptive sampling strategy that refines the training set. More specifically, we use an explicit density model to approximate the distribution induced by the PDE residual and then augment the training set with new time-dependent random samples given by the learned density model. The effectiveness and efficiency of our proposed method have been demonstrated through a series of numerical experiments. © 2024, CC BY.

关键词： Partial differential equations

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Learning Interface Conditions in Domain Decomposition Solvers

arXiv

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arXiv 2022年

作者： Taghibakhshi, Ali Nytko, Nicolas Zaman, Tareq MacLachlan, Scott Olson, Luke West, Matthew Mechanical Science and Engineering University of Illinois Urbana-Champaign UrbanaIL61801 United States Computer Science University of Illinois Urbana-Champaign UrbanaIL61801 United States Scientific Computing Program Memorial University of Newfoundland and Labrador St. John'sNL Canada Mathematics and Statistics Memorial University of Newfoundland and Labrador St. John'sNL Canada

Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations. Yet the optimal construction of these methods requires tedious analysis and is often available only in simplified, structured-grid settings, limiting their use for more complex problems. In this work, we generalize optimized Schwarz domain decomposition methods to unstructured-grid problems, using Graph Convolutional Neural Networks (GCNNs) and unsupervised learning to learn optimal modifications at subdomain interfaces. A key ingredient in our approach is an improved loss function, enabling effective training on relatively small problems, but robust performance on arbitrarily large problems, with computational cost linear in problem size. The performance of the learned linear solvers is compared with both classical and optimized domain decomposition algorithms, for both structured- and unstructured-grid problems. © 2022, CC BY.

关键词： Domain decomposition methods

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Covariance-Based Activity Detection in Cooperative Multi-Cell Massive MIMO: Scaling Law and Efficient Algorithms

arXiv

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arXiv 2023年

作者： Wang, Ziyue Liu, Ya-Feng Wang, Zhaorui Yu, Wei The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Shenzhen518172 China The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

This paper focuses on the covariance-based activity detection problem in a multi-cell massive multiple-input multiple-output (MIMO) system. In this system, active devices transmit their signature sequences to multiple base stations (BSs), and the BSs cooperatively detect the active devices based on the received signals. While the scaling law for the covariance-based activity detection in the single-cell scenario has been extensively analyzed in the literature, this paper aims to analyze the scaling law for the covariance-based activity detection in the multi-cell massive MIMO system. Specifically, this paper demonstrates a quadratic scaling law in the multi-cell system, under the assumption that the path-loss exponent of the fading channel γ > 2. This finding shows that, in the multi-cell massive MIMO system, the maximum number of active devices that can be correctly detected in each cell increases quadratically with the length of the signature sequence and decreases logarithmically with the number of cells (as the number of antennas tends to infinity). Moreover, in addition to analyzing the scaling law for the signature sequences randomly and uniformly distributed on a sphere, the paper also establishes the scaling law for signature sequences based on a finite alphabet, which are easier to generate and store. Finally, this paper proposes two efficient accelerated coordinate descent (CD) algorithms with a convergence guarantee for solving the device activity detection problem. The first algorithm reduces the complexity of CD by using an inexact coordinate update strategy. The second algorithm avoids unnecessary computations of CD by using an active set selection strategy. Simulation results show that the proposed algorithms exhibit excellent performance in terms of computational efficiency and detection error probability. Copyright © 2023, The Authors. All rights reserved.

关键词： Fading channels

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Distributed XML processing over multicore servers

WEBIST 2014 - Proceedings of the 10th International Conferen...

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WEBIST 2014 - Proceedings of the 10th International Conference on Web Information Systems and Technologies 2014年 1卷 200-207页

作者： Uratani, Yoshiyuki Koide, Hiroshi Cavendish, Dirceu Global Scientific Information and Computing Center Tokyo Institute of Technology O-okayama 2-12-1 Meguroku Tokyo 152-8550 Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Kawazu 680-4 Iizuka Fukuoka 820-8502 Japan Network Design Research Center Kyushu Institute of Technology Kawazu 680-4 Iizuka Fukuoka 820-8502 Japan

ISBN: (纸本)9789897580239

Nowadays, multicore CPU become popular technology to enhance services quality in Web services. This paper characterizes parallel distributed XML processing which can off-load the amount of processing at their servers to networking nodes with varying number of CPU cores. Our implemented distributed XML processing system sends XML documents from a sender node to a server node through relay nodes, which process the documents before arriving at the server. When the relay nodes are connected in tandem, the XML documents are processed in a pipelining manner. When the relay nodes are connected in parallel, the XML documents are processed in a parallel fashion. For well-formedness and grammar validation tasks, the parallel processing reveals inherent advantages compared with pipeline processing regardless of document type, number of CPU cores and processing environment. Moreover, the number of CPU cores impacts efficiency of distributed XML processing via buffer access contention. Copyright © 2014 SCITEPRESS.

关键词： XML

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Template-based quadrilateral mesh generation from imaging data

Template-based quadrilateral mesh generation from imaging da...

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作者： Liziér, Mario A. S. Siqueira, Marcelo F. Daniels II, Joel Silva, Claudio T. Nonato, L. Gustavo Departamento de Computação Universidade Federal de São Carlos São Carlos Brazil Departamento de Informática e Matemática Aplicada Universidade Federal Do Rio Grande Do Norte Natal Brazil Scientific Computing and Imaging Institute University of Utah Salt Lake City United States Computer Science and Engineering Polytechnic Institute New York University New York United States Instituto de Ciências Matemáticas e de Computaçã o Universidade de São Paulo São Paulo Brazil

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples. © 2011 Springer-Verlag.

关键词： Mesh generation

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Vaccine efficacy and SARS-CoV-2 control in California and *** the session 2020e2026:A modeling study

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Infectious Disease Modelling 2022年第1期7卷 62-81页

作者： Md Shahriar Mahmud Md Kamrujjaman Md Mashih Ibn Yasin Adan Md Alamgir Hossain Md Mizanur Rahman Md Shahidul Islam Muhammad Mohebujjaman Md Mamun Molla Department of Computer Science and Engineering State University of BangladeshDhaka1205Bangladesh Department of Mathematics University of DhakaDhaka1000Bangladesh Department of Mathematics and Statistics University of CalgaryCalgaryABCanada Computational Biology Research Lab(CBRL) Department of PharmacyJagannath UniversityDhaka1100Bangladesh Hitotsubashi Institute for Advanced Study Hitotsubashi UniversityNaka KunitachiTokyo186-8601Japan Department of Mathematics and Physics Texas A&M International UniversityLaredoTX78041USA Department of Mathematics&Physics North South UniversityDhaka1229Bangladesh Center for Applied Scientific Computing(CASC) North South UniversityDhaka1229Bangladesh

Background:Besides maintaining health precautions,vaccination has been the only prevention from SARS-CoV-2,though no clinically proved 100%effective vaccine has been developed till *** this stage,to withhold the debris of this pandemic-experts need to know the impact of the vaccine efficacy rates,the threshold level of vaccine effectiveness and how long this pandemic may extent with vaccines that have different efficacy *** this article,a mathematical model study has been done on the importance of vaccination and vaccine efficiency rate during an ongoing ***:We simulated a five compartment mathematical model to analyze the pandemic scenario in both California,and whole *** considered four vaccines,Pfizer(95%),Moderna(94%),AstraZeneca(79%),and Johnson&Johnson(72%),which are being used rigorously to control the SARS-CoV-2 pandemic,in addition with two special cases:a vaccine with 100%efficacy rate and no vaccine under ***-CoV-2 related data of California,and *** used in this ***:Both the infection and death rates are very high in *** model suggests that the pandemic situation in California will be under control in the last quartile of the year 2023 if vaccination program is continued with the Pfizer *** this time,six waves may happen from the beginning of the immunization where the case fatality and recovery rates will be 1.697%and 98.30%,***,according to the considered model,this period might be extended to the mid of 2024 when vaccines with lower efficacy rates are *** the other hand,the daily cases and deaths in the *** be under control at the end of 2026 with multiple *** the number of susceptible people will fall down to none in the beginning of 2027,there is less chance to stop the vaccination program if vaccinated with a vaccine other than a 100%effective vaccine or Pfizer,and at that case vaccination program must run till the mid of *** to this s

关键词： Vaccine Model California Control measurement SARS-CoV-2

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