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Dynamic simulation of multibody systems using a new state-time methodology

MULTIBODY SYSTEM DYNAMICS 2005年第1期14卷 61-80页

作者： Anderson, KS Oghbaei, M Rensselaer Polytech Inst Dept Mech Aerosp & Nucl Engn Troy NY 12180 USA

This paper presents a new methodology demonstrating the feasibility and advantages of a state-time formulation for dynamic simulation of complex multibody systems which shows potential advantages for exploiting massively parallel computing resources. This formulation allows time to be discretized and parameterized so that it can be treated as a variable in a manner similar to the system state variables. As a consequence of such a state-time discretization scheme, the system of governing equations yields to a set of loosely coupled linear-quadratic algebraic equations that is well-suited in structure for some families of nonlinear algebraic equations solvers. The goal of this work is to develop efficient multibody dynamics algorithm that is extremely scalable and better able to fully exploit anticipated immensely parallel computing machines (tera flop, peta flop and beyond) made available to it.

关键词： multibody dynamics state-time formulation scalable algorithm parallel computing

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Flexible and scalable Particle-in-Cell Methods With Adaptive Mesh Refinement for Geodynamic Computations

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GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS 2018年第9期19卷 3596-3604页

作者： Gassmoller, Rene Lokavarapu, Harsha Heien, Eric Puckett, Elbridge Gerry Bangerth, Wolfgang Univ Calif Davis Dept Earth & Phys Sci Davis CA 95616 USA Univ Calif Davis Computat Infrastruct Geodynam Davis CA 95616 USA Univ Calif Davis Dept Math Davis CA 95616 USA Colorado State Univ Dept Math Ft Collins CO 80523 USA

Particle-in-cell (PIC) methods couple mesh-based methods for the solution of continuum mechanics problems with the ability to advect and evolve properties on particles. PIC methods have a long history and numerous applications in geodynamic modeling. However, they are historically either implemented in sequential codes or in parallel codes with structured, statically partitioned meshes. Yet today's codes increasingly use adaptive mesh refinement (AMR) of unstructured coarse meshes, dynamic repartitioning, and scale to thousands of processors. Optimally balancing the work per processor for a PIC method in these environments is a difficult problem, and many existing implementations are not sufficient for this task. Thus, there is a need to revisit these algorithms for future applications. Here we describe challenges and solutions to implement PIC methods in the context of large-scale parallel geodynamic modeling codes that use dynamically changing meshes. We also provide guidance for how to address bottlenecks that impede the efficient implementation of these algorithms and demonstrate with numerical tests that our algorithms can be implemented with optimal complexity and that they are suitable for large-scale, practical applications. We provide a reference implementation in the Advanced Solver for Problems in Earth's ConvecTion (ASPECT), an open source code for geodynamic modeling built on the *** finite element library.

关键词： Particle in cell method Adaptive mesh refinement Geodynamic software Numerical modeling High performance computing scalable algorithm

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Run-length chain coding and scalable computation,of a shape's moments using reconfigurable optical buses

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 2004年第2期34卷 845-855页

作者： Wu, CH Horng, SJ Chinease Naval Acad Dept Informat Management Kaohsiung Taiwan Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei Taiwan

The main contribution of this paper is the design of several efficient algorithms for modified run-length chain coding and for computing a shape's moments on arrays with reconfigurable optical buses. The proposed algorithms, are based on the boundary representation of an object. Instead of using chain code, the boundary can be represented by a modified run-length chain code, where each entity represents a line segment (two adjacent. corner pixels). The sequential nature of the chain code makes it difficult to be parallelized. We first propose two constant time algorithms for boundary extraction and run-length chain coding. To the authors' knowledge, these are the most time efficient algorithms yet published. Based on the modified run-length chain coding, and the advantages of both optical transmission And electronic computation, a constant time parallel algorithm for computing a shape's moments using N x N processors is proposed. Additionally, instead of using N x N processors, a scalable moment algorithm using r x r processors is also derived, where r < N. Based on the product of time and the number of processors used, both proposed parallel algorithms are time and cost optimal.

关键词： parallel algorithm reconfigurable optical bus system run-length chain code scalable algorithm shape's moments

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A scalable Approach for Variational Data Assimilation

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JOURNAL OF SCIENTIFIC COMPUTING 2014年第2期61卷 239-257页

作者： D'Amore, Luisa Arcucci, Rossella Carracciuolo, Luisa Murli, Almerico Univ Naples Federico II Dept Math & Applicat Naples Italy CNR Ist Chim & Tecnol Polimeri I-80125 Naples Italy Univ Naples Federico II Dept Math & Applicat SPACI Naples Italy

Data assimilation (DA) is a methodology for combining mathematical models simulating complex systems (the background knowledge) and measurements (the reality or observational data) in order to improve the estimate of the system state (the forecast). The DA is an inverse and ill posed problem usually used to handle a huge amount of data, so, it is a large and computationally expensive problem. Here we focus on scalable methods that makes DA applications feasible for a huge number of background data and observations. We present a scalable algorithm for solving variational DA which is highly parallel. We provide a mathematical formalization of this approach and we also study the performance of the resulted algorithm.

关键词： Data assimilation Inverse problem Parallel computing scalable algorithm

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A case study in scalability: An ADI method for the two-dimensional time-dependent Dirac equation

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PARALLEL COMPUTING 1999年第5期25卷 525-533页

作者： Rathe, UW Sanders, P Knight, PL Max Planck Inst Informat D-66123 Saarbrucken Germany Univ London Imperial Coll Sci Technol & Med Blackett Lab Opt Sect London SW7 2BZ England

The dynamics of relativistic atomic wave functions evolving under the influence of intense laser pulses is used as an example of a general class of applications employing the alternating direction implicit method. The method requires the solution of many tridiagonal systems of linear equations. A range of parallel algorithms for this setting are analyzed with respect to their scalability on large parallel machines. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： parallel linear algebra tridiagonal systems alternating direction implicit method scalable algorithm Dirac equation

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A scalable APPROACH TO COMPUTE DELAY MARGIN OF A CLASS OF NEUTRAL-TYPE TIME DELAY SYSTEMS

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 2021年第2期59卷 805-824页

作者： Ramirez, Adrian Breda, Dimitri Sipahi, Rifat IPICYT Catedras CONACYT Div Control & Dynam Syst San Luis Potosi 78216 San Luis Potosi Mexico Univ Udine Dept Math Comp Sci & Phys CDLab Computat Dynam Lab I-33100 Udine Italy Northeastern Univ Dept Mech & Ind Engn Boston MA 02115 USA

An approach is presented to approximate the delay margin of a class of linear time-invariant neutral-type time delay systems. The approach is based on frequency sweeping tools and factorization of the corresponding characteristic function of the system, without any assumptions on the structure of system matrices. Different from published work, it enables the approximation of the delay margin on a scalable framework by means of a suitable numerical search of roots crossing the imaginary axis, hence it allows to substantially reduce computation times through parallel processing. Effectiveness of the approach is demonstrated on various problems.

关键词： time-delay systems neutral systems delay margin scalable algorithm

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Fast and scalable computations of 2D image moments

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IMAGE AND VISION COMPUTING 2008年第6期26卷 799-811页

作者： Wu, Chin-Hsiung Horng, Shi-Jinn Wen, Ching-Feng Wang, Yuh-Rau Shih Chien Univ Dept Informat Technol & Commun Kaohsiung Taiwan Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei Taiwan Kaohsiung Med Univ Gen Educ Ctr Kaohsiung Taiwan St Johns Univ Dept Comp Sci & Informat Engn Taipei Taiwan

Image moments are used in image analysis for object modelling and matching. The moment computation of a two-dimensional (213) image involves a significant amount of multiplication and addition in a direct method. In this paper, we use the suffix sum functions to compute the gray-level image moments instead of using a direct method. This new method can reduce drastically the number of multiplications required. We first derive the mathematical relationships between moment computations and suffix sums. Based on the derived mathematical relationships, four new parallel algorithms for computing image moments are derived on various computational models. By integrating the advantages of both optical transmission and electronic computation, the 2D image moments can be computed in constant time on a 2D array with reconfigurable optical buses. The performance comparison shows that the proposed method is fast and efficient. In addition, three scalable and cost optimal algorithms are derived on the AROB, the hypercube computer and the EREW PRAM model. (c) 2007 Elsevier B.V. All rights reserved.

关键词： image moments moment invariants suffix sums scalable algorithm pattern recognition reconfigurable optical buses

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Fast parallel algorithm for distance transform

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 2003年第4期33卷 429-434页

作者： Datta, A Soundaralakshmi, S Univ Western Australia Sch Comp Sci & Software Engn Perth WA 6009 Australia

We present an O((log log N)(2)) -time algorithm for computing the distance transform of an N x N binary image. Our algorithm is designed for the common concurrent read concurrent write parallel random access machine (CRCW PRAM) and requires O(N2+epsilon / log log N) processors, for any epsilon such that 0 < E < 1. Our algorithm is based on a novel deterministic sampling scheme and can be used for computing distance transforms for a very general class of distance functions. We also present a scalable version of our algorithm when the number of processors is available p(2+epsilon) / log log p for some p < N. In this case, our algorithm runs in O((N-2/p(2)) + (N/p) log log p + (log log p)(2)) time. This scalable algorithm is more practical since usually the number of available processors is much less than the size of the image.

关键词： binary image CRCW PRAM deterministic sampling distance transform parallel algorithm pattern recognition scalable algorithm

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Parallel simulation by multi-instruction, longest-path algorithms

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QUEUEING SYSTEMS 1997年第1-2期27卷 37-54页

作者： Chen, L Lucent Technol Inc Whippany NJ 07981 USA

This paper presents several basic algorithms for the parallel simulation of G/G/1 queueing systems and certain networks of such systems. The coverage includes systems subject to manufacturing or communication blocking, or to loss of customer due to capacity constraints. The key idea is that the customer departure times are represented by longest-path distance in directed graphs instead of by the usual recursive equations. This representation leads to scalable algorithms with a high degree of parallelism that can be implemented on either MIMD or SIMD parallel computers.

关键词： massive parallel processing simulation MIMD and SIMD parallel computers scalable algorithm G/G/1 queue longest path queueing networks

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Accurate and scalable social recommendation using mixed-membership stochastic block models

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2016年第50期113卷 14207-14212页

作者： Godoy-Lorite, Antonia Guimera, Roger Moore, Cristopher Sales-Pardo, Marta Univ Rovira & Virgili Dept Engn Quim E-43007 Tarragona Catalonia Spain Inst Catalana Recerca & Estudis Avancats Barcelona 08010 Catalonia Spain Santa Fe Inst Santa Fe NM 87501 USA

With increasing amounts of information available, modeling and predicting user preferences-for books or articles, for example-are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users' ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user's and item's groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets.

关键词： recommender systems stochastic block model collaborative filtering social recommendation scalable algorithm

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