PCCP#

a “column-projection” preconditioner This is a terrible preconditioner and is not recommended, ever!

Loops over the entries of x computing dx_i (e_i is the unit vector in the ith direction) to


        min || b - A(x + dx_i e_i ||_2
        dx_i

    That is, it changes a single entry of x to minimize the new residual norm.
   Let A_i represent the ith column of A, then the minimization can be written as

       min || r - (dx_i) A e_i ||_2
       dx_i
   or   min || r - (dx_i) A_i ||_2
        dx_i

    take the derivative with respect to dx_i to obtain
        dx_i = (A_i^T A_i)^(-1) A_i^T r

    This algorithm can be thought of as Gauss-Seidel on the normal equations

Notes#

This procedure can also be done with block columns or any groups of columns but this is not coded.

These “projections” can be done simultaneously for all columns (similar to Jacobi) or sequentially (similar to Gauss-Seidel/SOR). This is only coded for SOR type.

This is related to, but not the same as “row projection” methods.

This is currently coded only for MATSEQAIJ matrices

See Also#

KSP: Linear System Solvers, PCCreate(), PCSetType(), PCType, PCJACOBI, PCSOR

Level#

intermediate

Location#

src/ksp/pc/impls/cp/cp.c


Index of all PC routines
Table of Contents for all manual pages
Index of all manual pages