8.1
general documentation
Data Fields
cs_iter_algo_aac_t Struct Reference

Context structure for the algorithm called Anderson acceleration. More...

#include <cs_iter_algo.h>

+ Collaboration diagram for cs_iter_algo_aac_t:

Data Fields

cs_iter_algo_param_aac_t param
 
cs_sles_convergence_state_t cvg_status
 
double normalization
 
double tol
 
double prev_res
 
double res
 
double res0
 
int n_algo_iter
 
int n_inner_iter
 
int last_inner_iter
 
cs_lnum_t n_elts
 
Work quantities (temporary)
int n_dir
 
cs_real_t * fold
 
cs_real_t * df
 
cs_real_t * gold
 
cs_real_t * dg
 
cs_real_t * Q
 
cs_sdm_t * R
 
cs_real_t * gamma
 

Detailed Description

Context structure for the algorithm called Anderson acceleration.

Set of parameters and arrays to manage the Anderson acceleration

Field Documentation

◆ cvg_status

cvg_status

Converged, iterating or diverged status

◆ df

df

Difference between the current and previous values of f

◆ dg

dg

Difference between the current and previous values of g

◆ fold

fold

Previous values for f

◆ gamma

gamma

Coefficients used to define the linear combination

◆ gold

gold

Previous values for g

◆ last_inner_iter

last_inner_iter

Last number of iterations for the inner solver

◆ n_algo_iter

n_algo_iter

Current number of iterations for the algorithm (outer iterations)

◆ n_dir

n_dir

Number of directions currently at stake

◆ n_elts

cs_lnum_t n_elts

◆ n_inner_iter

n_inner_iter

Curent cumulated number of inner iterations (sum over the outer iterations)

◆ normalization

normalization

Value of the normalization for the relative tolerance.

The stopping criterion is such that res < rtol * normalization. By default, the normalization is set to 1.

◆ param

param

Set of parameters driving the behavior of the Anderson acceleration

◆ prev_res

prev_res

Value of the previous residual achieved during the iterative process

◆ Q

Q

Matrix Q in the Q.R factorization (seen as a bundle of vectors)

◆ R

R

Matrix R in the Q.R factorization (small dense matrix)

◆ res

res

Value of the residual for the iterative algorithm

◆ res0

res0

Value of the first residual of the iterative process. This is used for detecting the divergence of the algorithm.

◆ tol

tol

Tolerance computed as tol = max(atol, normalization*rtol) where atol and rtol are respectively the absolute and relative tolerance associated to the algorithm

The documentation for this struct was generated from the following file: