Search Results - Parallel Thomas algorithm

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  1. 1

    swPTS: an efficient parallel Thomas split algorithm for tridiagonal systems on Sunway manycore processors by Tian, Min, Liu, Qi, Pan, Jingshan, Gou, Ying, Zhang, Zanjun

    ISSN: 0920-8542, 1573-0484
    Published: New York Springer US 01.03.2024
    Published in The Journal of supercomputing (01.03.2024)
    “… Based on the performance analysis of the classic Thomas algorithm and matrix splitting method, we propose a parallel Thomas split (PTS) algorithm…”
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  2. 2

    Parallel implementation of Thomas algorithm for the 2D heat equation by Kenzhebek, Yerzhan, Imankulov, Timur, Matkerim, Bazargul, Akhmed-Zaki, Darkhan

    ISSN: 1563-0277, 2617-4871
    Published: Al-Farabi Kazakh National University 28.10.2019
    “…In this paper was considered a parallel implementation of the Thomas algorithm for the 2D heat equation…”
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  3. 3
  4. 4

    Parallel tridiagonal matrix inversion with a hybrid multigrid-Thomas algorithm method by Parker, J.T., Hill, P.A., Dickinson, D., Dudson, B.D.

    ISSN: 0377-0427, 1879-1778
    Published: Elsevier B.V 01.01.2022
    “… In this paper, we derive a hybrid multigrid-Thomas algorithm designed to efficiently invert tridiagonal matrix equations in a highly-scalable fashion in the context of time evolving partial…”
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  5. 5

    High-performance modeling acoustic and elastic waves using the parallel Dichotomy Algorithm by Fatyanov, Alexey G., Terekhov, Andrew V.

    ISSN: 0021-9991, 1090-2716
    Published: United States Elsevier Inc 01.03.2011
    Published in Journal of computational physics (01.03.2011)
    “…A high-performance parallel algorithm is proposed for modeling the propagation of acoustic and elastic waves in inhomogeneous media…”
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  6. 6

    GPUSCAN: GPU-Based Parallel Structural Clustering Algorithm for Networks by Stovall, Thomas Ryan, Kockara, Sinan, Avci, Recep

    ISSN: 1045-9219, 1558-2183
    Published: New York IEEE 01.12.2015
    “…This paper presents a massively parallel implementation of a prominent network clustering algorithm, the structural clustering algorithm for networks (SCAN…”
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  7. 7

    A scalable, parallel algorithm for maximal clique enumeration by Schmidt, Matthew C., Samatova, Nagiza F., Thomas, Kevin, Park, Byung-Hoon

    ISSN: 0743-7315, 1096-0848
    Published: Amsterdam Elsevier Inc 01.04.2009
    “… Even the most efficient serial MCE algorithms require large amounts of time to enumerate the maximal cliques in networks arising from these problems that contain hundreds, thousands, or larger numbers of vertices…”
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  8. 8

    GBEES-GPU: An efficient parallel GPU algorithm for high-dimensional nonlinear uncertainty propagation by Hanson, Benjamin L., Rubio, Carlos, García-Gutiérrez, Adrián, Bewley, Thomas

    ISSN: 0010-4655
    Published: Elsevier B.V 01.12.2025
    Published in Computer physics communications (01.12.2025)
    “… A recent approach to this class of algorithm, Grid-based Bayesian Estimation Exploiting Sparsity, addresses the first challenge by dynamically allocating a discretized grid in regions of phase space…”
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  9. 9

    Parallel Thomas approach development for solving tridiagonal systems in GPU programming − steady and unsteady flow simulation by Souri, Milad, Akbarzadeh, Pooria, Darian, Hossein Mahmoodi

    ISSN: 2257-7777, 2257-7750
    Published: Villeurbanne EDP Sciences 2020
    “…The solution of tridiagonal system of equations using graphic processing units (GPU) is assessed. The parallel-Thomas-algorithm…”
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  10. 10

    Round-Competitive Algorithms for Uncertainty Problems with Parallel Queries by Erlebach, Thomas, Hoffmann, Michael, de Lima, Murilo Santos

    ISSN: 0178-4617, 1432-0541
    Published: New York Springer US 01.02.2023
    Published in Algorithmica (01.02.2023)
    “…). We introduce a new model where  k queries can be made in parallel in each round, and the goal is to minimize the number of query rounds…”
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  11. 11

    A Higher-Order Compact Method in Space and Time Based on Parallel Implementation of the Thomas Algorithm by Povitsky, Alex, Morris, Philip J.

    ISSN: 0021-9991, 1090-2716
    Published: Elsevier Inc 10.06.2000
    Published in Journal of computational physics (10.06.2000)
    “…–Kutta temporal update. The most efficient direct method to compute spatial derivatives on a serial computer is a version of Gaussian elimination for narrow linear banded systems known as the Thomas algorithm…”
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  12. 12

    Adaptive Collision Culling for Massive Simulations by a Parallel and Context-Aware Sweep and Prune Algorithm by Capannini, Gabriele, Larsson, Thomas

    ISSN: 1077-2626, 1941-0506, 1941-0506
    Published: United States IEEE 01.07.2018
    “…We present an improved parallel Sweep and Prune algorithm that solves the dynamic box intersection problem in three dimensions…”
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  13. 13

    Discriminating flash crowds from DDoS attacks using efficient thresholding algorithm by David, Jisa, Thomas, Ciza

    ISSN: 0743-7315, 1096-0848
    Published: Elsevier Inc 01.06.2021
    “…Distributed Denial-of-Service attacks have been a challenge to cyberspace, as the attackers send a large number of attack packets similar to the normal…”
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  14. 14

    A parallel algorithm for Bayesian network structure learning from large data sets by Madsen, Anders L., Jensen, Frank, Salmerón, Antonio, Langseth, Helge, Nielsen, Thomas D.

    ISSN: 0950-7051, 1872-7409
    Published: Elsevier B.V 01.02.2017
    Published in Knowledge-based systems (01.02.2017)
    “…This paper considers a parallel algorithm for Bayesian network structure learning from large data sets…”
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  15. 15

    Optimal polynomial smoothers for parallel AMG by D’Ambra, Pasqua, Durastante, Fabio, Filippone, Salvatore, Massei, Stefano, Thomas, Stephen

    ISSN: 1017-1398, 1572-9265
    Published: New York Springer US 01.12.2025
    Published in Numerical algorithms (01.12.2025)
    “…In this paper, we explore polynomial accelerators that are well-suited for parallel computations, specifically as smoothers in Algebraic MultiGrid (AMG…”
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  16. 16

    Parallel Implementation of Curvilinear High-order Formulas by Ladeinde, F., Cai, X., Visbal, M.R., Gaitonde, D.

    ISSN: 1061-8562
    Published: 01.12.2003
    “… Three procedures were selected: the one-sided method, the parallel diagonal dominant (PDD) method, and the parallel Thomas algorithm…”
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  17. 17

    The Largest-Z-ratio-First algorithm is 0.8531-approximate for scheduling unreliable jobs on m parallel machines by Agnetis, Alessandro, Lidbetter, Thomas

    ISSN: 0167-6377, 1872-7468
    Published: Elsevier B.V 01.07.2020
    Published in Operations research letters (01.07.2020)
    “…In this paper we analyze the worst-case performance of a greedy algorithm called Largest-Z-ratio-First for the problem of scheduling unreliable jobs on m parallel machines…”
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  18. 18

    Efficient parallel resolution of the simplified transport equations in mixed-dual formulation by Barrault, M., Lathuilière, B., Ramet, P., Roman, J.

    ISSN: 0021-9991, 1090-2716
    Published: Kidlington Elsevier Inc 01.03.2011
    Published in Journal of computational physics (01.03.2011)
    “…]. In order to obtain a high parallel efficiency, we improve the parallelization scheme by changing the location of the loop over the subdomains in the overall algorithm and by benefiting…”
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  19. 19

    Parallel Direct and Iterative Methods for Solving the Time-Fractional Diffusion Equation on Multicore Processors by Sultanov, Murat A., Akimova, Elena N., Misilov, Vladimir E., Nurlanuly, Yerkebulan

    ISSN: 2227-7390, 2227-7390
    Published: Basel MDPI AG 01.02.2022
    Published in Mathematics (Basel) (01.02.2022)
    “… The developed parallel algorithms are based on the Thomas algorithm, parallel sweep algorithm, and accelerated over-relaxation method for solving this system…”
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  20. 20

    Detecting global hyperparaboloid correlated clusters: a Hough-transform based multicore algorithm by Kazempour, Daniyal, Mauder, Markus, Kröger, Peer, Seidl, Thomas

    ISSN: 0926-8782, 1573-7578
    Published: New York Springer US 15.03.2019
    “…Correlation clustering detects complex and intricate relationships in high-dimensional data by identifying groups of data points, each characterized by…”
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