J
John W. Ruge
Researcher at University of Colorado Boulder
Publications - 43
Citations - 1122
John W. Ruge is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Multigrid method & Linear system. The author has an hindex of 15, co-authored 43 publications receiving 1010 citations.
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Journal ArticleDOI
Robustness and Scalability of Algebraic Multigrid
A. Cleary,Robert D. Falgout,Van Emden Henson,Jim E. Jones,Thomas A. Manteuffel,Stephen F. McCormick,Gerald N. Miranda,John W. Ruge +7 more
TL;DR: Some of the situations in which standard AMG does not work well are shown and the current directions taken by AMG researchers to alleviate these difficulties are indicated.
Journal ArticleDOI
Adaptive Algebraic Multigrid
Marian Brezina,Robert D. Falgout,S. MacLachlanT. Manteuffel,Stephen F. McCormick,John W. Ruge +4 more
TL;DR: This paper introduces an extension to algebraic multigrid methods that removes the need to make unsatisfied assumptions made on the near null spaces of these matrices by utilizing an adaptive process.
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Adaptive Smoothed Aggregation ($\alpha$SA) Multigrid
M. Brezina,Robert D. Falgout,Scott MacLachlan,Thomas A. Manteuffel,Stephen F. McCormick,John W. Ruge +5 more
TL;DR: An extension of the SA method in which good convergence properties are achieved in situations where explicit knowledge of the near-kernel components is unavailable is introduced in an adaptive process that uses the method itself to determine near- kernel components and adjusts the coarsening processes accordingly.
Journal ArticleDOI
Multilevel Adaptive Aggregation for Markov Chains, with Application to Web Ranking
TL;DR: Numerical tests serve to illustrate for which types of stochastic matrices the multilevel adaptive method may provide significant speedup compared to standard iterative methods.
Journal ArticleDOI
Smoothed Aggregation Multigrid for Markov Chains
H. De Sterck,Thomas A. Manteuffel,Stephen F. McCormick,K. L. Miller,J. Pearson,John W. Ruge,Geoffrey Sanders +6 more
TL;DR: It is shown how smoothing the interpolation and restriction operators can dramatically increase the efficiency of aggregation multigrid methods for Markov chains that have been proposed in the literature.