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Iterative linear solvers Conjugate Gradient

In CED, a number of different iterative solvers for linear algebraic systems have been applied. Two of the most successful and most widely used methods are conjugate gradient and multigrid methods. The basic idea of the conjugate gradient method is to transform the linear equation system Eq. (38) into a minimization problem... [Pg.166]

M-Shake This is Newton-iteration-based implementation of SHAKE, using (4.18)-(4.19) to solve Eqs. (4.27)-(4.29). Methods like this were first proposed by Ciccotti and Ryckaert [84] in the context of rigid body molecular dynamics. An extended discussion of such methods with reference to their convergence, implementation, in particular linear system solvers, and variants such as SHAKE-SOR (which uses the successive over-relaxation method) can be found in [25]. A conjugate gradient method can also be used [392]. [Pg.164]


See other pages where Iterative linear solvers Conjugate Gradient is mentioned: [Pg.101]    [Pg.166]    [Pg.260]    [Pg.381]    [Pg.411]    [Pg.95]    [Pg.1092]    [Pg.395]    [Pg.142]   
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