Titlebook: Large-Scale Scientific Computing; 4th International Co Ivan Lirkov,Svetozar Margenov,Plamen Yalamov Conference proceedings 2004 Springer-Ve

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賞心悅目

Solution of Robust Linear Regression Problems by Krylov Subspace Methodsly transforming the sequence of linear systems to be solved. Appropriate sequences of linear systems for sparse and dense matrices are given. By employing efficient sparse . factorization methods, we show that it is possible to solve efficiently large sparse linear systems with an unpreconditioned Krylov subspace method.

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鞠躬

Decimate

A Parallel Monte Carlo Method for Electron Quantum Kinetic EquationnMP codes..Numerical results for the parallel efficiency of the algorithm are obtained. The dependence of the electron energy distribution on applied electric field is investigated for long evolution times. The distribution function is computed for GaAs material parameters.

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Parallel Solution of Very Large Sparse Systems of Linear Algebraic Equationsven to demonstrate the ability of the algorithm to handle very large systems of linear algebraic equations..The algorithm can be applied in the treatment of some large-scale air pollution models without using splitting procedures.

手榴彈

Modeling of Narrow-Width SOI Devices: The Role of Quantum Mechanical Narrow Channel Effects on Devicmulations. Quantum mechanical space-quantization effects have been accounted for via an effective potential scheme that has been quite successful in describing bandgap widening effect and charge set back from the interface in conventional MOSFET devices.