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  • Numerical analysis  (2)
  • Numerical time integration  (1)
  • 1
    ISSN: 1436-5057
    Keywords: 65L05 ; G.1.7 ; G.1.8 ; Numerical analysis ; ordinary differential equations ; Runge-Kutta methods ; predictorcorrector methods ; periodic solutions
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Description / Table of Contents: Zusammenfassung Für die numerische Behandlung von Differentialgleichungen zweiter Ordnung, bei dennen die Lösung im wesentlichen durch die von einer äußeren periodischen Kraft erzwungenen Schwingung bestimmt wird, werden Diskretisierungsmethoden vom Runge-Kutta-Nyström Typ und spezielle Prädiktor-Korrektor Methoden konstruiert. Für eine Klasse expliziter und linear-impliziter Runge-Kutta-Nyström Methoden der Ordung zwei zeigen wir, daß die erzwungene Schwingung keinen Phasenfehler aufweist. Für eine Klasse von Prädiktor-Korrektor Methoden vierter Ordnung wird nachgewiesen, daß die Phasen- und Dissipationsfehlerordnung beliebig groß gemacht werden kann. Numerische Beispiele bestätigen die Wirksamkeit unserer Methoden mit reduziertem Phasenfehler.
    Notes: Abstract Runge-Kutta-Nyström type methods and special predictor-corrector methods are constructed for the accurate solution of second-order differential equations of which the solution is dominated by the forced oscillation originating from an external, periodic forcing term. For a family of second-order explicit and linearly implicit Runge-Kutta-Nyström methods it is shown that the forced oscillation is represented with zero phase lag. For a family of predictor-corrector methods of fourth-order, it is shown that both the phase lag order and the dissipation of the forced oscillation can be made arbitrarily high. Numerical examples illustrate the effectiveness of our reduced phase lag methods.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Numerical algorithms 8 (1994), S. 293-312 
    ISSN: 1572-9265
    Keywords: Numerical analysis ; Runge-Kutta methods ; parallelism ; G.1.7.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract For the parallel integration of stiff initial value problems (IVPs) three main approaches can be distinguished: approaches based on “parallelism across the problem”, on “parallelism across the method” and on “parallelism across the steps”. The first type of parallelism does not require special integration methods can be exploited within any available IVP solver. The methodparallel approach received some attention in the case of Runge-Kutta based methods. For these methods, the required number of processors is roughly half the order of the generating Runge-Kutta method and the speed-up with respect to a good sequential IVP solver is about a factor 2. The third type of parallelism (step-parallelism) can be achieved in any IVP solver based on predictor-corrector iteration. Most step-parallel methods proposed so far employ a large number of processors, but lack the property of robustness, due to a poor convergence behaviour in the iteration process. Hence, the effective speed-up is rather poor. The step-parallel iteraction process proposed in the present paper is less massively parallel, but turns out to be sufficiently robust to solve the four-stage Radau IIA corrector used in our experiments within a few effective iterations per step and to achieve speed-up factors up to 10 with respect to the best sequential codes.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Chichester : Wiley-Blackwell
    International Journal for Numerical Methods in Fluids 20 (1995), S. 213-231 
    ISSN: 0271-2091
    Keywords: Transport models ; 3D advection-diffusion equations ; Numerical time integration ; Vectorization ; Parallel processing ; Engineering ; Engineering General
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: The total solution of a three-dimensional model for computing the transport of salinity, pollutants, suspended material (such as sediment or mud), etc. in shallow seas involves many aspects, each of which has to be treated in an optimal way in order to cope with the tremendous computational task involved. In this paper we focus on one of these aspects, i.e. on the time integration, and discuss two numerical solution methods. The emphasis in this paper is on the performance of the methods when implemented on a vector/parallel, shared memory computer such as a Cray-type machine. The first method is an explicit time integrator and can straightforwardly be vectorized and parallelized. Although a stabilizing technique has been applied to this method, it still suffers from a severe time step restriction. The second method is partly implicit, resulting in much better stability characteristics; however, as a consequence of the implicitness, it requires in each step the solution of a large number of tridiagonal systems. When implemented in a standard way, the recursive nature would prevent vectorization, resulting in a very long solution time. Following a suggestion of Golub and Van Loan, this part of the algorithm has been tuned for use on the Cray C98/4256. On the basis of a large-scale test problem, performance results will be presented for various implementations.
    Additional Material: 2 Ill.
    Type of Medium: Electronic Resource
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