Abstract: "In this paper, we construct block predictor-corrector methods using Runge-Kutta correctors. Our approach consists of applying the predictor-corrector method not only at step points, but also at off- step points (block points), so that, in each step, a whole block of approximations to...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Houwen, Pieter J. van der (VerfasserIn), Nguyen, Huu Cong (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Amsterdam 1992
Schriftenreihe:	Centrum voor Wiskunde en Informatica <Amsterdam> / Afdeling Numerieke Wiskunde: Report NM 1992,20
Schlagworte:	Runge-Kutta formulas
Zusammenfassung:	Abstract: "In this paper, we construct block predictor-corrector methods using Runge-Kutta correctors. Our approach consists of applying the predictor-corrector method not only at step points, but also at off- step points (block points), so that, in each step, a whole block of approximations to the exact solution is computed. In the next step, these approximations are used for obtaining a high-order predictor formula by Lagrange or Hermite interpolation. By choosing the abscissas of the off- step points narrowly spaced, a much more accurately predicted value is obtained than by predictor formulas based on preceding step point values Since the approximations at the off-step points to be computed in each step can be obtained in parallel, the sequential costs of these block predictor-corrector methods are comparable with those of a conventional predictor-corrector method. Futhermore, by using Runge-Kutta correctors, the predictor-corrector iteration scheme itself is also highly parallel. Application of these block predictor-corrector methods based on Langrange- Gauss pairs to a few widely-used test problems reveals that the sequential costs are reduced by a factor ranging from 2 until 11 when compared with the best sequential methods.
Beschreibung:	10 S.