The Preconditioned Conjugate Gradient Method
See also: PreconditionerIn most cases, preconditioning is necessary to ensure fast convergence of the conjugate gradient method. The preconditioned conjugate gradient method takes the following form:
- repeat
- if rk+1 is sufficiently small then exit loop end if
- end repeat
- The result is xk+1
The above formulation is equivalent to applying the conjugate gradient method without preconditioning to the system
where and .
The preconditioner matrix M has to be symmetric positive-definite and fixed, i.e., cannot change from iteration to iteration. If any of these assumptions on the preconditioner is violated, the behavior of the preconditioned conjugate gradient method may become unpredictable.
An example of a commonly used preconditioner is the incomplete Cholesky factorization.
Read more about this topic: Conjugate Gradient Method
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