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SPH-EXA: Enhancing the Scalability of SPH codes Via an Exascale-Ready SPH Mini-App

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arXiv 2019年

作者： Guerrera, Danilo Cavelan, Aurélien Cabezón, Rubén M. Imbert, David Piccinali, Jean-Guillaume Mohammed, Ali Mayer, Lucio Reed, Darren Ciorba, Florina M. Department of Mathematics and Computer Science University of Basel Switzerland University of Basel Switzerland Xxx Software YYY ZZZ Swiss National Supercomputing Centre Scientific Computing Support Lugano Switzerland Center for Theoretical Astrophysics and Cosmology Institute for Computational Science University of Zürich Switzerland

Numerical simulations of fluids in astrophysics and computational fluid dynamics (CFD) are among the most computationallydemanding calculations, in terms of sustained floating-point operations per second, or FLOP/s. It is expected that these numerical simulations will significantly benefit from the future Exascale computing infrastructures, that will perform 1018FLOP/s. The performance of the SPH codes is, in general, adversely impacted by several factors, such as multiple time-stepping, long-range interactions, and/or boundary conditions. In this work an extensive study of three SPH implementations SPHYNX [1], ChaNGa [2], and XXX [?] is performed, to gain insights and to expose any limitations and characteristics of the codes. These codes are the starting point of an interdisciplinary co-design project, SPH-EXA, for the development of an Exascale-ready SPH mini-app. We implemented a rotating square patch [4] as a joint test simulation for the three SPH codes and analyzed their performance on a modern HPC system, Piz Daint. The performance profiling and scalability analysis conducted on the three parent codes allowed to expose their performance issues [5], such as load imbalance, both in MPI and OpenMP. Two-level load balancing has been successfully applied to SPHYNX to overcome its load imbalance. The performance analysis shapes and drives the design of the SPH-EXA mini-app towards the use of efficient parallelization methods, fault-tolerance mechanisms, and load balancing approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Fault tolerance

Incentivizing wi-fi network crowdsourcing: A contract theoretic approach

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arXiv 2018年

作者： Ma, Qian Gao, Lin Liu, Ya-Feng Huang, Jianwei Department of Information Engineering Chinese University of Hong Kong Hong Kong School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China 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 China

Crowdsourced wireless community network enables individual users to share their private Wi-Fi access points (APs) with each other, hence can achieve a large Wi-Fi coverage with a small deployment cost via crowdsourcing. This paper presents a novel contract-based incentive framework to incentivize such a Wi-Fi network crowdsourcing under incomplete information (where each user has certain private information such as mobility pattern and Wi-Fi access quality). In the proposed framework, the network operator designs and offers a set of contract items to users, each consisting of a Wi-Fi access price (that a user can charge others for accessing his AP) and a subscription fee (that a user needs to pay the operator for joining the community). Different from the existing contracts in the literature, in our contract model each user's best choice depends not only on his private information but also on other users' choices. This greatly complicates the contract design, as the operator needs to analyze the equilibrium choices of all users, rather than the best choice of each single user. We first derive the feasible contract that guarantees the users' truthful information disclosure based on the equilibrium analysis of user choice, and then derive the optimal (and feasible) contract that yields the maximal profit for the operator. Our analysis shows that a user who provides a higher Wi-Fi access quality is more likely to choose a higher Wi-Fi access price and subscription fee, regardless of the user mobility pattern. Simulation results further show that when increasing the average Wi-Fi access quality of users, the operator can gain more profit, but (counter-intuitively) offer lower Wi-Fi access prices and subscription fees for users. Copyright © 2018, The Authors. All rights reserved.

关键词： Crowdsourcing

The 2025 Roadmap to Ultrafast Dynamics: Frontiers of Theoretical and computational Modelling

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arXiv 2025年

作者： Caruso, Fabio Sentef, Michael A. Attaccalite, Claudio Bonitz, Michael Draxl, Claudia De Giovannini, Umberto Eckstein, Martin Ernstorfer, Ralph Fechner, Michael Grüning, Myrta Hübener, Hannes Joost, Jan-Philip Juraschek, Dominik M. Karrasch, Christoph Kennes, Dante Marvin Latini, Simone Lu, I-Te Neufeld, Ofer Perfetto, Enrico Rettig, Laurenz Pela, Ronaldo Rodrigues Rubio, Angel Rudzinski, Joseph F. Ruggenthaler, Michael Sangalli, Davide Schüler, Michael Shallcross, Samuel Sharma, Sangeeta Stefanucci, Gianluca Werner, Philipp Institute of Theoretical Physics and Astrophysics University of Kiel Leibnizstrasse 15 Kiel24116 Germany Institute for Theoretical Physics Bremen Center for Computational Materials Science University of Bremen Bremen28359 Germany Luruper Chaussee 149 Hamburg22761 Germany CNRS Aix-Marseille Université Centre Interdisciplinaire de Nanoscience de Marseille UMR 7325 Campus de Luminy Marseille13288 cedex 9 France Physics Department CSMB Adlershof Humboldt-Universität zu Berlin Berlin12489 Germany Università degli Studi di Palermo Dipartimento di Fisica e Chimica—Emilio Segrè PalermoI-90123 Italy Institute for Theoretical Physics University of Hamburg Notkestraße 9-11 Hamburg22607 Germany The Hamburg Centre for Ultrafast Imaging Hamburg Germany Fritz Haber Institute Max Planck Society Faradayweg 4-6 Berlin14195 Germany Institut für Optik und Atomare Physik Technische Universität Berlin Straße des 17 Juni 135 Berlin10623 Germany Max Planck Institute for the Structure and Dynamics of Matter Hamburg Germany School of Mathematics and Physics Queen’s University Belfast University Road BelfastBT7 1NN United Kingdom Max Planck Institute for the Structure and Dynamics of Matter Center for Free Electron Laser Science Hamburg22761 Germany Department of Applied Physics and Science Education Eindhoven University of Technology Eindhoven Netherlands Technische Universität Braunschweig Institut für Mathematische Physik Mendelssohnstr. 3 Braunschweig38106 Germany Institut für Theorie der Statistischen Physik RWTH Aachen University JARA – Fundamentals of Future Information Technology Aachen52056 Germany Max Planck Institute for the Structure and Dynamics of Matter Center for Free Electron Laser Science Hamburg22761 Germany Department of Physics Technical University of Denmark Kgs Lyngby2800 Denmark Max Planck Institute for the Structure and Dynamics of Matter Center for Free-Electron Laser Science Luruper Chaussee 149 Hamburg22761 Germany Schulich Fac

The exploration of ultrafast phenomena is a frontier of condensed matter research, where the interplay of theory, computation, and experiment is unveiling new opportunities for understanding and engineering quantum materials. With the advent of advanced experimental techniques and computational tools, it has become possible to probe and manipulate nonequilibrium processes at unprecedented temporal and spatial resolutions, providing insights into the dynamical behavior of matter under extreme conditions. These capabilities have the potential to revolutionize fields ranging from optoelectronics and quantum information to catalysis and energy storage. This Roadmap captures the collective progress and vision of leading researchers, addressing challenges and opportunities across key areas of ultrafast science. Contributions in this Roadmap span the development of ab initio methods for time-resolved spectroscopy, the dynamics of driven correlated systems, the engineering of materials in optical cavities, and the adoption of FAIR principles for data sharing and analysis. Together, these efforts highlight the interdisciplinary nature of ultrafast research and its reliance on cutting-edge methodologies, including quantum electrodynamical density-functional theory, correlated electronic structure methods, nonequilibrium Green’s function approaches, quantum and ab initio simulations. Copyright © 2025, The Authors. All rights reserved.

关键词： Time-resolved spectroscopy

Understanding metric-related pitfalls in image analysis validation

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arXiv 2023年

作者： Reinke, Annika Tizabi, Minu D. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Kavur, A. Emre Rädsch, Tim Sudre, Carole H. Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Buettner, Florian Cardoso, M. Jorge Cheplygina, Veronika Chen, Jianxu Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kleesiek, Jens Kofler, Florian Kooi, Thijs Kopp-Schneider, Annette Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Riegler, Michael A. Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. van Calster, Ben Varoquaux, Gaël Yaniv, Ziv R. Jäger, Paul F. Maier-Hein, Lena Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg A Partnership Between DKFZ University Medical Center Heidelberg Germany Heidelberg Division of Medical Image Computing Germany Heidelberg Division of Intelligent Medical Systems Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montreal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Leuven Belgium partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany and Frankfurt Cancer Insititute Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for Statistics in Medicine University of Oxford Oxford United Kingdom Center for Biomedical In

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately. While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. While focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. © 2023, CC BY.

关键词： Computer vision

Stability selection enables robust learning of partial differential equations from limited noisy data

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arXiv 2019年

作者： Maddu, Suryanarayana Cheeseman, Bevan L. Sbalzarini, Ivo F. Müller, Christian L. Chair of Scientific Computing for Systems Biology Faculty of Computer Science TU Dresden Dresden01069 Germany Center for Systems Biology Dresden Max Planck Institute of Molecular Cluster of Excellence Physics of Life TU Dresden Dresden01062 Germany Center for Computational Mathematics Flatiron Institute New York United States

We present a statistical learning framework for robust identification of partial differential equations (PDEs) from noisy spatiotemporal data. Extending previous sparse regression approaches for inferring PDE models from simulated data, we address key issues that have thus far limited the application of these methods to noisy experimental data, namely their robustness against noise and the need for manual parameter tuning. We address both points by proposing a stability-based model selection scheme to determine the level of regularization required for reproducible recovery of the underlying PDE. This avoids manual parameter tuning and provides a principled way to improve the method's robustness against noise in the data. Our stability selection approach, termed PDE-STRIDE, can be combined with any sparsity-promoting penalized regression model and provides an interpretable criterion for model component importance. We show that in particular the combination of stability selection with the iterative hard-thresholding algorithm from compressed sensing provides a fast, parameter-free, and robust computational framework for PDE inference that outperforms previous algorithmic approaches with respect to recovery accuracy, amount of data required, and robustness to noise. We illustrate the performance of our approach on a wide range of noise-corrupted simulated benchmark problems, including 1D Burgers, 2D vorticity-transport, and 3D reaction-diffusion problems. We demonstrate the practical applicability of our method on real-world data by considering a purely data-driven re-evaluation of the advective triggering hypothesis for an embryonic polarization system in C. elegans. Using fluorescence microscopy images of C. elegans zygotes as input data, our framework is able to recover the PDE model for the regulatory reaction-diffusion-flow network of the associated proteins. Copyright © 2019, The Authors. All rights reserved.

关键词： Stability

Author Correction: The influence of natural variability on extreme monsoons in Pakistan

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npj Climate and Atmospheric Science 2023年第1期6卷 1页

作者： Moetasim Ashfaq Matthew F. Horan Salil Mahajan Katherine J. Evans Nathaniel Johnson Fred Kucharski Muhammad Adnan Abid Noah S. Diffenbaugh Deepti Singh Subimal Ghosh Auroop R. Ganguly Shafiqul Islam Computational Sciences and Engineering Division (CSED) Oak Ridge National Laboratory Oak Ridge TN USA Bredesen Center University of Tennessee Knoxville TN USA National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory Princeton NJ USA Earth System Physics Abdus Salam International Centre for Theoretical Physics Trieste Italy Doerr School of Sustainability Stanford University Stanford CA USA School of the Environment Washington State University Vancouver WA USA Department of Civil Engineering Indian Institute of Technology Bombay Mumbai India Sustainability and Data Sciences Laboratory Civil and Environmental Engineering Northeastern University Boston MA USA Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory Richland WA USA Indian Institute of Technology Gandhinagar Gandhinagar GJ India Department of Civil and Environmental Engineering The Fletcher School of Law and Diplomacy Tufts University Medford MA USA

Thermal Stress and Reliability Analysis of TSV-Based 3-D ICs With a Novel Adaptive Strategy Finite Element Method

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Thermal Stress and Reliability Analysis of TSV-Based 3-D ICs...

作者： Zhou, Hao Zhu, Hengliang Cui, Tao Pan, David Z. Zhou, Dian Zeng, Xuan State Key Laboratory of ASIC and Systems Department of Microelectronics Fudan University Shanghai200433 China State Key Laboratory of Scientific and Engineering Computing National Center for Mathematics and Interdisciplinary Sciences Institute of Computational Mathematics Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Department of Electrical Engineering University of Texas at Dallas RichardsonTX75080 United States

Thermomechanical stress is one of the most important issues in performance and reliability analysis of through silicon via-based 3-D integrated circuits (3-D ICs), where an accurate numerical approach is generally needed to produce stress models and identify weak points in the structure. In this paper, we propose a knowledge-oriented nonuniform (KONU) refinement strategy for 3-D IC stress simulation under the framework of a parallel adaptive finite element method (FEM), and apply it in 3-D IC stress and reliability analysis. Parallel adaptive FEM is promising for solving large-scale problems due to its high accuracy and parallel efficiency. It produces refined meshes based on the a posteriori error analysis, which has the quasi-optimal convergence rate for solving the problem. It has high parallel efficiency, which makes it suitable for handling large and complex structures in 3-D ICs. The KONU refinement strategy developed in this paper can efficiently reduce the number of refinement iterations in parallel adaptive FEM for 3-D IC thermomechanical stress simulation and improves the computational efficiency. It is demonstrated in this paper through several examples that parallel adaptive FEM for thermomechanical stress evaluation can be widely applied in 3-D IC reliability analysis, where accurate stress simulation and modeling is exceptionally important to produce accurate results. © 2018 IEEE.

关键词： Reliability analysis

An adaptive multi-fidelity pc-based ensemble kalman inversion for inverse problems

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arXiv 2018年

作者： Yan, Liang Zhou, Tao Department of Mathematics Southeast University Nanjing210096 China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

The ensemble Kalman inversion (EKI), as a derivative-free methodology, has been widely used in the parameter estimation of inverse problems. Unfortunately, its cost may become moderately large for systems described by high dimensional nonlinear PDEs, as EKI requires a relatively large ensemble size to guarantee its performance. In this paper, we propose an adaptive multi-fidelity polynomial chaos (PC) based EKI technique to address this challenge. Our new strategy combines a large number of low-order PC surrogate model evaluations and a small number of high-fidelity forward model evaluations, yielding a multi-fidelity approach. Especially, we present a new approach that adaptively constructs and refines a multi-fidelity PC surrogate during the EKI simulation. Since the forward model evaluations are only required for updating the low-order multifidelity PC model, whose number can be much smaller than the total ensemble size of the classic EKI, the entire computational costs are thus significantly reduced. The new algorithm was tested through the two-dimensional time fractional inverse diffusion problems and demonstrated great effectiveness in comparison with PC based EKI and classic EKI. Copyright © 2018, The Authors. All rights reserved.

关键词： Differential equations

Anisotropic spectral manifold wavelet descriptor for deformable shape analysis and matching 26

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Anisotropic spectral manifold wavelet descriptor for deforma...

26th Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2018

作者： Li, Qinsong Liu, Shengjun Hu, Ling Liu, Xinru Institute of Engineering Modeling and Scientific Computing Central South University Hunan Changsha410083 China School of Mathematics and Computational Science Hunan First Normal University Hunan Changsha410205 China State Key Laboratory of High Performance Manufacturing Complex Central South University Hunan Changsha410083 China

ISBN: (纸本)9783038680734

In this paper, we present a novel framework termed Anisotropic Spectral Manifold Wavelet Transform (ASMWT) for shape analysis. ASMWT comprehensively analyzes the signals from multiple directions on local manifold regions of the shape with a series of low-pass and band-pass frequency filters in each direction. Using the ASMWT coefficients of a very simple function, we efficiently construct a localizable and discriminative multiscale point descriptor, named as the Anisotropic Spectral Manifold Wavelet Descriptor (ASMWD). Since the filters used in our descriptor are direction-sensitive and able to robustly reconstruct the signals with a finite number of scales, it makes our descriptor be intrinsic-symmetry unambiguous, compact as well as efficient. The extensive experimental results demonstrate that our method achieves significant performance than several state-of-the-art methods when applied in vertex-wise shape matching. © 2018 The Author(s).

关键词： Wavelet transforms