# KSPTSIRM#

Implements the two-stage iteration with least-squares residual minimization method [CKG16]

## Options Database Keys#

the type of the inner solver (GMRES or any of its variants for instance)**-ksp_ksp_type**- the type of the preconditioner applied to the inner solver**-ksp_pc_type**- the maximum number of inner iterations (iterations of the inner solver)**-ksp_ksp_max_it**- sets the relative convergence tolerance of the inner solver**-ksp_ksp_rtol**- if 1 use CGLS solver in the minimization step, otherwise use LSQR solver**-ksp_tsirm_cgls**- the maximum number of iterations for the least-squares minimization solver**-ksp_tsirm_max_it_ls**- sets the convergence tolerance of the least-squares minimization solver**-ksp_tsirm_tol_ls**- the number of residuals for the least-squares minimization step**-ksp_tsirm_size_ls**-

## Notes#

`KSPTSIRM`

is a two-stage iteration method for solving large sparse linear systems of the form \(Ax=b\). The main idea behind this new
method is the use a least-squares residual minimization to improve the convergence of Krylov based iterative methods, typically those of GMRES variants.
The principle of TSIRM algorithm is to build an outer iteration over a Krylov method, called the inner solver, and to frequently store the current residual
computed by the given Krylov method in a matrix of residuals S. After a few outer iterations, a least-squares minimization step is applied on the matrix
composed by the saved residuals, in order to compute a better solution and to make new iterations if required.
The minimization step consists in solving the least-squares problem \(\min||b-ASa||\) to find ‘a’ which minimizes the
residuals \((b-AS)\). The minimization step is performed using two solvers of linear least-squares problems: `KSPCGLS`

or `KSPLSQR`

. A new solution x with
a minimal residual is computed with \(x=Sa\).

## Contributed by#

Lilia Ziane Khodja

## References#

- CKG16
Raphaël Couturier, Lilia Ziane Khodja, and Christophe Guyeux. TSIRM: a two-stage iteration with least-squares residual minimization algorithm to solve large sparse linear and nonlinear systems.

*Journal of Computational Science*, 17:535–546, 2016.

## See Also#

KSP: Linear System Solvers, `KSPCreate()`

, `KSPSetType()`

, `KSPType`

, `KSP`

, `KSPFGMRES`

, `KSPLGMRES`

,
`KSPGMRESSetRestart()`

, `KSPGMRESSetHapTol()`

, `KSPGMRESSetPreAllocateVectors()`

, `KSPGMRESSetOrthogonalization()`

, `KSPGMRESGetOrthogonalization()`

,
`KSPGMRESClassicalGramSchmidtOrthogonalization()`

, `KSPGMRESModifiedGramSchmidtOrthogonalization()`

,
`KSPGMRESCGSRefinementType`

, `KSPGMRESSetCGSRefinementType()`

, `KSPGMRESGetCGSRefinementType()`

, `KSPGMRESMonitorKrylov()`

, `KSPSetPCSide()`

## Level#

advanced

## Location#

src/ksp/ksp/impls/tsirm/tsirm.c

Index of all KSP routines

Table of Contents for all manual pages

Index of all manual pages