void AZ_matvec_mult(double *val, int *indx, int *bindx, int *rpntr, int *cpntr,
int *bpntr, double *b, register double *c,
int exchange_flag, int *data_org)
/******************************************************************************
c = Ab:
Sparse (square) overlapped matrix-vector multiply, using the distributed
variable block row (DVBR) data structure (A = val).
Author: Scott A. Hutchinson, SNL, 1421
=======
Return code: void
============
Parameter list:
===============
m: Number of (block) rows in A.
val: Array containing the entries of the matrix. The matrix is
stored block-row-by-block-row. Each block entry is dense and
stored by columns (VBR).
indx: The ith element of indx points to the location in val of the
(0,0) entry of the ith block entry. The last element is the
number of nonzero entries of matrix A plus one.
bindx: Contains the block column indices of the non-zero block
entries.
rpntr: The ith element of rpntr indicates the first point row in
the i'th block row. The last element is the number of block
rows plus one.
cpntr: The jth element of cpntr indicates the first point column in
the jth block column. The last element is the number of
bpntr: The ith element of bpntr points to the first block entry of
the ith row in bindx. The last element is the number of
nonzero blocks of matrix A plus one.
b: Contains the vector b.
c: Contains the result vector c.
exchange_flag: Flag which controls call to exchange_bdry.
data_org: Array containing information on the distribution of the
matrix to this processor as well as communication parameters
(see Aztec User's Guide).
******************************************************************************/
{
/* local variables */
AZ_MATRIX Amat;
int proc_config[AZ_PROC_SIZE];
static int first_time = 1;
if (exchange_flag != 1) {
printf("Warning: exchange_flag is no longer used in AZ_matvec_mult().\n");
printf(" Set to '1' to avoid this message.\n");
}
Amat.rpntr = rpntr; Amat.cpntr = cpntr;
Amat.bpntr = bpntr; Amat.bindx = bindx;
Amat.indx = indx; Amat.val = val;
Amat.data_org = data_org;
Amat.aux_ival = NULL;
Amat.aux_dval = NULL;
Amat.aux_matrix = NULL;
Amat.matrix_type = data_org[AZ_matrix_type];
#ifdef AZTEC_MPI
AZ_set_comm(proc_config, MPI_COMM_WORLD);
if (first_time == 1) {
AZ_set_proc_config(proc_config, MPI_COMM_WORLD);
#else
if (first_time == 1) {
AZ_set_proc_config(proc_config, AZ_NOT_MPI);
#endif
if (proc_config[AZ_node] == 0) {
printf("Warning: AZ_matvec_mult() should be replaced with either\n");
printf(" AZ_MSR_matvec_mult or AZ_VBR_matvec_mult()\n");
}
}
first_time = 0;
if (Amat.matrix_type == AZ_MSR_MATRIX) Amat.matvec = AZ_MSR_matvec_mult;
else if (Amat.matrix_type == AZ_VBR_MATRIX) Amat.matvec = AZ_VBR_matvec_mult;
Amat.matvec(b, c, &Amat, proc_config);
}
void init_guess_and_rhs(int update_index[], int update[], double *x[],double
*ax[],int data_org[], double val[], int indx[], int
bindx[], int rpntr[], int cpntr[], int bpntr[], int
proc_config[])
/*
* Set the initial guess and the right hand side where the right hand side
* is obtained by doing a matrix-vector multiplication.
*
* Author: Ray Tuminaro, Div 1422, SNL
* Date : 3/15/95
*
* Parameters
*
* update_index == On input, ordering of update and external
* locally on this processor. For example
* 'update_index[i]' gives the index location
* of the block which has the global index
* 'update[i]'.
* update == On input, list of pts to be updated on this node
* data_org == On input, indicates how data is set on this node.
* For example, data_org[] contains information on
* how many unknowns are internal, external and
* border unknowns as well as which points need
* to be communicated. See User's Guide for more
* details.
* val, indx, == On input, holds matrix nonzeros. See User's Guide
* bindx, rpntr, for more details.
* cpntr, bpntr
* x == On output, 'x' is allocated and set to all zeros.
* ax == On output, 'ax' is allocated and is set to the
* result of a matrix-vector product.
*/
{
int i,j;
int temp,num;
double sum = 0.0;
AZ_MATRIX *Amat;
temp = data_org[AZ_N_int_blk] + data_org[AZ_N_bord_blk];
num = data_org[AZ_N_internal] + data_org[AZ_N_border];
/* allocate vectors */
i = num + data_org[AZ_N_external];
*x = (double *) AZ_allocate((i+1)*sizeof(double));
*ax = (double *) AZ_allocate((i+1)*sizeof(double));
if (*ax == NULL) {
(void) fprintf(stderr, "Not enough space in init_guess_and_rhs() for ax\n");
exit(1);
}
for (j = 0 ; j < i ; j++ ) (*x)[j] = 0.0;
for (j = 0 ; j < i ; j++ ) (*ax)[j] = 0.0;
/* initialize 'x' to a function which will be used in matrix-vector product */
if (data_org[AZ_matrix_type] == AZ_VBR_MATRIX) {
for (i = 0; i < temp; i++) {
for (j = rpntr[i]; j < rpntr[i+1]; j++) {
(*x)[j] = (double) (update[i]) + (double)(j-rpntr[i]) /
(double)(num_PDE_eqns);
}
}
}
else {
for (i = 0; i < temp; i++) {
(*x)[i] = (double) (update[i]) / (double) (num_PDE_eqns);
}
}
/* Reorder 'x' so that it conforms to the transformed matrix */
AZ_reorder_vec(*x,data_org,update_index,rpntr);
if (application == 2) {
/* take out the constant vector. Used for the */
/* finite element problem because it is singular */
sum = AZ_gsum_double(sum, proc_config);
i = AZ_gsum_int(num, proc_config);
if (i != 0) sum = sum / ((double) i);
for (i = 0; i < num; i++) (*x)[i] -= sum;
}
Amat = AZ_matrix_create(num);
if (data_org[AZ_matrix_type] == AZ_MSR_MATRIX)
AZ_set_MSR(Amat, bindx, val, data_org, 0, NULL, AZ_LOCAL);
else if (data_org[AZ_matrix_type] == AZ_VBR_MATRIX)
AZ_set_VBR(Amat, rpntr,cpntr, bpntr, indx,bindx, val, data_org, 0, NULL,AZ_LOCAL);
Amat->matvec(*x, *ax, Amat, proc_config);
AZ_matrix_destroy( &Amat );
for (i = 0; i < num; i++) (*x)[i] = 0.0;
} /* init_guess_and_rhs */
int main(int argc, char *argv[])
{
int num_PDE_eqns=1, N_levels=3, nsmooth=2;
int leng, level, N_grid_pts, coarsest_level;
int leng1,leng2;
/* See Aztec User's Guide for more information on the */
/* variables that follow. */
int proc_config[AZ_PROC_SIZE], options[AZ_OPTIONS_SIZE];
double params[AZ_PARAMS_SIZE], status[AZ_STATUS_SIZE];
/* data structure for matrix corresponding to the fine grid */
double *val = NULL, *xxx, *rhs, solve_time, setup_time, start_time;
AZ_MATRIX *Amat;
AZ_PRECOND *Pmat = NULL;
ML *ml;
FILE *fp;
int i, j, Nrigid, *garbage, nblocks=0, *blocks = NULL, *block_pde=NULL;
struct AZ_SCALING *scaling;
ML_Aggregate *ag;
double *mode, *rigid=NULL, alpha;
char filename[80];
int one = 1;
int proc,nprocs;
char pathfilename[100];
#ifdef ML_MPI
MPI_Init(&argc,&argv);
/* get number of processors and the name of this processor */
AZ_set_proc_config(proc_config, MPI_COMM_WORLD);
proc = proc_config[AZ_node];
nprocs = proc_config[AZ_N_procs];
#else
AZ_set_proc_config(proc_config, AZ_NOT_MPI);
proc = 0;
nprocs = 1;
#endif
if (proc_config[AZ_node] == 0) {
sprintf(pathfilename,"%s/inputfile",argv[1]);
ML_Reader_ReadInput(pathfilename, &context);
}
else context = (struct reader_context *) ML_allocate(sizeof(struct reader_context));
AZ_broadcast((char *) context, sizeof(struct reader_context), proc_config,
AZ_PACK);
AZ_broadcast((char *) NULL , 0 , proc_config, AZ_SEND);
N_levels = context->N_levels;
printf("N_levels %d\n",N_levels);
nsmooth = context->nsmooth;
num_PDE_eqns = context->N_dofPerNode;
printf("num_PDE_eqns %d\n",num_PDE_eqns);
ML_Set_PrintLevel(context->output_level);
/* read in the number of matrix equations */
leng = 0;
if (proc_config[AZ_node] == 0) {
sprintf(pathfilename,"%s/data_matrix.txt",argv[1]);
fp=fopen(pathfilename,"r");
if (fp==NULL) {
printf("**ERR** couldn't open file data_matrix.txt\n");
exit(1);
}
fscanf(fp,"%d",&leng);
fclose(fp);
}
leng = AZ_gsum_int(leng, proc_config);
N_grid_pts=leng/num_PDE_eqns;
/* initialize the list of global indices. NOTE: the list of global */
/* indices must be in ascending order so that subsequent calls to */
/* AZ_find_index() will function properly. */
#if 0
if (proc_config[AZ_N_procs] == 1) i = AZ_linear;
else i = AZ_file;
#endif
i = AZ_linear;
/* cannot use AZ_input_update for variable blocks (forgot why, but debugged through it)*/
/* make a linear distribution of the matrix */
/* if the linear distribution does not align with the blocks, */
/* this is corrected in ML_AZ_Reader_ReadVariableBlocks */
leng1 = leng/nprocs;
leng2 = leng-leng1*nprocs;
if (proc >= leng2)
{
leng2 += (proc*leng1);
}
else
{
leng1++;
leng2 = proc*leng1;
}
N_update = leng1;
update = (int*)AZ_allocate((N_update+1)*sizeof(int));
if (update==NULL)
{
(void) fprintf (stderr, "Not enough space to allocate 'update'\n");
fflush(stderr); exit(EXIT_FAILURE);
}
for (i=0; i<N_update; i++) update[i] = i+leng2;
#if 0 /* debug */
printf("proc %d N_update %d\n",proc_config[AZ_node],N_update);
fflush(stdout);
#endif
sprintf(pathfilename,"%s/data_vblocks.txt",argv[1]);
ML_AZ_Reader_ReadVariableBlocks(pathfilename,&nblocks,&blocks,&block_pde,
&N_update,&update,proc_config);
#if 0 /* debug */
printf("proc %d N_update %d\n",proc_config[AZ_node],N_update);
fflush(stdout);
#endif
sprintf(pathfilename,"%s/data_matrix.txt",argv[1]);
AZ_input_msr_matrix(pathfilename,update, &val, &bindx, N_update, proc_config);
/* This code is to fix things up so that we are sure we have */
/* all blocks (including the ghost nodes) the same size. */
/* not sure, whether this is a good idea with variable blocks */
/* the examples inpufiles (see top of this file) don't need it */
/* anyway */
/*
AZ_block_MSR(&bindx, &val, N_update, num_PDE_eqns, update);
*/
AZ_transform_norowreordering(proc_config, &external, bindx, val, update, &update_index,
&extern_index, &data_org, N_update, 0, 0, 0, &cpntr,
AZ_MSR_MATRIX);
Amat = AZ_matrix_create( leng );
AZ_set_MSR(Amat, bindx, val, data_org, 0, NULL, AZ_LOCAL);
Amat->matrix_type = data_org[AZ_matrix_type];
data_org[AZ_N_rows] = data_org[AZ_N_internal] + data_org[AZ_N_border];
start_time = AZ_second();
options[AZ_scaling] = AZ_none;
ML_Create(&ml, N_levels);
/* set up discretization matrix and matrix vector function */
AZ_ML_Set_Amat(ml, 0, N_update, N_update, Amat, proc_config);
ML_Set_ResidualOutputFrequency(ml, context->output);
ML_Set_Tolerance(ml, context->tol);
ML_Aggregate_Create( &ag );
if (ML_strcmp(context->agg_coarsen_scheme,"Mis") == 0) {
ML_Aggregate_Set_CoarsenScheme_MIS(ag);
}
else if (ML_strcmp(context->agg_coarsen_scheme,"Uncoupled") == 0) {
ML_Aggregate_Set_CoarsenScheme_Uncoupled(ag);
}
else if (ML_strcmp(context->agg_coarsen_scheme,"Coupled") == 0) {
ML_Aggregate_Set_CoarsenScheme_Coupled(ag);
}
else if (ML_strcmp(context->agg_coarsen_scheme,"Metis") == 0) {
ML_Aggregate_Set_CoarsenScheme_METIS(ag);
for (i=0; i<N_levels; i++)
ML_Aggregate_Set_NodesPerAggr(ml,ag,i,9);
}
else if (ML_strcmp(context->agg_coarsen_scheme,"VBMetis") == 0) {
/* when no blocks read, use standard metis assuming constant block sizes */
if (!blocks)
ML_Aggregate_Set_CoarsenScheme_METIS(ag);
else {
ML_Aggregate_Set_CoarsenScheme_VBMETIS(ag);
ML_Aggregate_Set_Vblocks_CoarsenScheme_VBMETIS(ag,0,N_levels,nblocks,
blocks,block_pde,N_update);
}
for (i=0; i<N_levels; i++)
ML_Aggregate_Set_NodesPerAggr(ml,ag,i,9);
}
else {
printf("**ERR** ML: Unknown aggregation scheme %s\n",context->agg_coarsen_scheme);
exit(-1);
}
ML_Aggregate_Set_DampingFactor(ag, context->agg_damping);
ML_Aggregate_Set_MaxCoarseSize( ag, context->maxcoarsesize);
ML_Aggregate_Set_Threshold(ag, context->agg_thresh);
if (ML_strcmp(context->agg_spectral_norm,"Calc") == 0) {
ML_Set_SpectralNormScheme_Calc(ml);
}
else if (ML_strcmp(context->agg_spectral_norm,"Anorm") == 0) {
ML_Set_SpectralNormScheme_Anorm(ml);
}
else {
printf("**WRN** ML: Unknown spectral norm scheme %s\n",context->agg_spectral_norm);
}
/* read in the rigid body modes */
Nrigid = 0;
if (proc_config[AZ_node] == 0) {
sprintf(filename,"data_nullsp%d.txt",Nrigid);
sprintf(pathfilename,"%s/%s",argv[1],filename);
while( (fp = fopen(pathfilename,"r")) != NULL) {
fclose(fp);
Nrigid++;
sprintf(filename,"data_nullsp%d.txt",Nrigid);
sprintf(pathfilename,"%s/%s",argv[1],filename);
}
}
Nrigid = AZ_gsum_int(Nrigid,proc_config);
if (Nrigid != 0) {
rigid = (double *) ML_allocate( sizeof(double)*Nrigid*(N_update+1) );
if (rigid == NULL) {
printf("Error: Not enough space for rigid body modes\n");
}
}
/* Set rhs */
sprintf(pathfilename,"%s/data_rhs.txt",argv[1]);
fp = fopen(pathfilename,"r");
if (fp == NULL) {
rhs=(double *)ML_allocate(leng*sizeof(double));
if (proc_config[AZ_node] == 0) printf("taking linear vector for rhs\n");
for (i = 0; i < N_update; i++) rhs[i] = (double) update[i];
}
else {
fclose(fp);
if (proc_config[AZ_node] == 0) printf("reading rhs from a file\n");
AZ_input_msr_matrix(pathfilename, update, &rhs, &garbage, N_update,
proc_config);
}
AZ_reorder_vec(rhs, data_org, update_index, NULL);
for (i = 0; i < Nrigid; i++) {
sprintf(filename,"data_nullsp%d.txt",i);
sprintf(pathfilename,"%s/%s",argv[1],filename);
AZ_input_msr_matrix(pathfilename, update, &mode, &garbage, N_update,
proc_config);
AZ_reorder_vec(mode, data_org, update_index, NULL);
#if 0 /* test the given rigid body mode, output-vector should be ~0 */
Amat->matvec(mode, rigid, Amat, proc_config);
for (j = 0; j < N_update; j++) printf("this is %d %e\n",j,rigid[j]);
#endif
for (j = 0; j < i; j++) {
alpha = -AZ_gdot(N_update, mode, &(rigid[j*N_update]), proc_config)/
AZ_gdot(N_update, &(rigid[j*N_update]), &(rigid[j*N_update]),
proc_config);
DAXPY_F77(&N_update, &alpha, &(rigid[j*N_update]), &one, mode, &one);
}
/* rhs orthogonalization */
alpha = -AZ_gdot(N_update, mode, rhs, proc_config)/
AZ_gdot(N_update, mode, mode, proc_config);
DAXPY_F77(&N_update, &alpha, mode, &one, rhs, &one);
for (j = 0; j < N_update; j++) rigid[i*N_update+j] = mode[j];
free(mode);
free(garbage);
}
for (j = 0; j < Nrigid; j++) {
alpha = -AZ_gdot(N_update, rhs, &(rigid[j*N_update]), proc_config)/
AZ_gdot(N_update, &(rigid[j*N_update]), &(rigid[j*N_update]),
proc_config);
DAXPY_F77(&N_update, &alpha, &(rigid[j*N_update]), &one, rhs, &one);
}
#if 0 /* for testing the default nullsp */
ML_Aggregate_Set_NullSpace(ag, num_PDE_eqns, 6, NULL, N_update);
#else
if (Nrigid != 0) {
ML_Aggregate_Set_NullSpace(ag, num_PDE_eqns, Nrigid, rigid, N_update);
}
#endif
if (rigid) ML_free(rigid);
ag->keep_agg_information = 1;
coarsest_level = ML_Gen_MGHierarchy_UsingAggregation(ml, 0,
ML_INCREASING, ag);
coarsest_level--;
if ( proc_config[AZ_node] == 0 )
printf("Coarse level = %d \n", coarsest_level);
#if 0
/* set up smoothers */
if (!blocks)
blocks = (int *) ML_allocate(sizeof(int)*N_update);
#endif
for (level = 0; level < coarsest_level; level++) {
num_PDE_eqns = ml->Amat[level].num_PDEs;
/* Sparse approximate inverse smoother that acutally does both */
/* pre and post smoothing. */
if (ML_strcmp(context->smoother,"Parasails") == 0) {
ML_Gen_Smoother_ParaSails(ml , level, ML_PRESMOOTHER, nsmooth,
parasails_sym, parasails_thresh,
parasails_nlevels, parasails_filter,
(int) parasails_loadbal, parasails_factorized);
}
/* This is the symmetric Gauss-Seidel smoothing that we usually use. */
/* In parallel, it is not a true Gauss-Seidel in that each processor */
/* does a Gauss-Seidel on its local submatrix independent of the */
/* other processors. */
else if (ML_strcmp(context->smoother,"GaussSeidel") == 0) {
ML_Gen_Smoother_GaussSeidel(ml , level, ML_BOTH, nsmooth,1.);
}
else if (ML_strcmp(context->smoother,"SymGaussSeidel") == 0) {
ML_Gen_Smoother_SymGaussSeidel(ml , level, ML_BOTH, nsmooth,1.);
}
else if (ML_strcmp(context->smoother,"Poly") == 0) {
ML_Gen_Smoother_Cheby(ml, level, ML_BOTH, 30., nsmooth);
}
else if (ML_strcmp(context->smoother,"BlockGaussSeidel") == 0) {
ML_Gen_Smoother_BlockGaussSeidel(ml , level, ML_BOTH, nsmooth,1.,
num_PDE_eqns);
}
else if (ML_strcmp(context->smoother,"VBSymGaussSeidel") == 0) {
if (blocks) ML_free(blocks);
if (block_pde) ML_free(block_pde);
blocks = NULL;
block_pde = NULL;
nblocks = 0;
ML_Aggregate_Get_Vblocks_CoarsenScheme_VBMETIS(ag,level,N_levels,&nblocks,
&blocks,&block_pde);
if (blocks==NULL) ML_Gen_Blocks_Aggregates(ag, level, &nblocks, &blocks);
ML_Gen_Smoother_VBlockSymGaussSeidel(ml , level, ML_BOTH, nsmooth,1.,
nblocks, blocks);
}
/* This is a true Gauss Seidel in parallel. This seems to work for */
/* elasticity problems. However, I don't believe that this is very */
/* efficient in parallel. */
/*
nblocks = ml->Amat[level].invec_leng;
for (i =0; i < nblocks; i++) blocks[i] = i;
ML_Gen_Smoother_VBlockSymGaussSeidelSequential(ml , level, ML_PRESMOOTHER,
nsmooth, 1., nblocks, blocks);
ML_Gen_Smoother_VBlockSymGaussSeidelSequential(ml, level, ML_POSTSMOOTHER,
nsmooth, 1., nblocks, blocks);
*/
/* Jacobi Smoothing */
else if (ML_strcmp(context->smoother,"Jacobi") == 0) {
ML_Gen_Smoother_Jacobi(ml , level, ML_PRESMOOTHER, nsmooth,.4);
ML_Gen_Smoother_Jacobi(ml , level, ML_POSTSMOOTHER, nsmooth,.4);
}
/* This does a block Gauss-Seidel (not true GS in parallel) */
/* where each processor has 'nblocks' blocks. */
/* */
else if (ML_strcmp(context->smoother,"Metis") == 0) {
if (blocks) ML_free(blocks);
if (block_pde) ML_free(block_pde);
nblocks = 250;
ML_Gen_Blocks_Metis(ml, level, &nblocks, &blocks);
ML_Gen_Smoother_VBlockSymGaussSeidel(ml , level, ML_BOTH, nsmooth,1.,
nblocks, blocks);
}
else {
printf("unknown smoother %s\n",context->smoother);
exit(1);
}
}
/* set coarse level solver */
nsmooth = context->coarse_its;
/* Sparse approximate inverse smoother that acutally does both */
/* pre and post smoothing. */
if (ML_strcmp(context->coarse_solve,"Parasails") == 0) {
ML_Gen_Smoother_ParaSails(ml , coarsest_level, ML_PRESMOOTHER, nsmooth,
parasails_sym, parasails_thresh,
parasails_nlevels, parasails_filter,
(int) parasails_loadbal, parasails_factorized);
}
else if (ML_strcmp(context->coarse_solve,"GaussSeidel") == 0) {
ML_Gen_Smoother_GaussSeidel(ml , coarsest_level, ML_BOTH, nsmooth,1.);
}
else if (ML_strcmp(context->coarse_solve,"Poly") == 0) {
ML_Gen_Smoother_Cheby(ml, coarsest_level, ML_BOTH, 30., nsmooth);
}
else if (ML_strcmp(context->coarse_solve,"SymGaussSeidel") == 0) {
ML_Gen_Smoother_SymGaussSeidel(ml , coarsest_level, ML_BOTH, nsmooth,1.);
}
else if (ML_strcmp(context->coarse_solve,"BlockGaussSeidel") == 0) {
ML_Gen_Smoother_BlockGaussSeidel(ml, coarsest_level, ML_BOTH, nsmooth,1.,
num_PDE_eqns);
}
else if (ML_strcmp(context->coarse_solve,"Aggregate") == 0) {
if (blocks) ML_free(blocks);
if (block_pde) ML_free(block_pde);
ML_Gen_Blocks_Aggregates(ag, coarsest_level, &nblocks, &blocks);
ML_Gen_Smoother_VBlockSymGaussSeidel(ml , coarsest_level, ML_BOTH,
nsmooth,1., nblocks, blocks);
}
else if (ML_strcmp(context->coarse_solve,"Jacobi") == 0) {
ML_Gen_Smoother_Jacobi(ml , coarsest_level, ML_BOTH, nsmooth,.5);
}
else if (ML_strcmp(context->coarse_solve,"Metis") == 0) {
if (blocks) ML_free(blocks);
if (block_pde) ML_free(block_pde);
nblocks = 250;
ML_Gen_Blocks_Metis(ml, coarsest_level, &nblocks, &blocks);
ML_Gen_Smoother_VBlockSymGaussSeidel(ml , coarsest_level, ML_BOTH,
nsmooth,1., nblocks, blocks);
}
else if (ML_strcmp(context->coarse_solve,"SuperLU") == 0) {
ML_Gen_CoarseSolverSuperLU( ml, coarsest_level);
}
else if (ML_strcmp(context->coarse_solve,"Amesos") == 0) {
ML_Gen_Smoother_Amesos(ml,coarsest_level,ML_AMESOS_KLU,-1, 0.0);
}
else {
printf("unknown coarse grid solver %s\n",context->coarse_solve);
exit(1);
}
ML_Gen_Solver(ml, ML_MGV, 0, coarsest_level);
AZ_defaults(options, params);
if (ML_strcmp(context->krylov,"Cg") == 0) {
options[AZ_solver] = AZ_cg;
}
else if (ML_strcmp(context->krylov,"Bicgstab") == 0) {
options[AZ_solver] = AZ_bicgstab;
}
else if (ML_strcmp(context->krylov,"Tfqmr") == 0) {
options[AZ_solver] = AZ_tfqmr;
}
else if (ML_strcmp(context->krylov,"Gmres") == 0) {
options[AZ_solver] = AZ_gmres;
}
else {
printf("unknown krylov method %s\n",context->krylov);
}
if (blocks) ML_free(blocks);
if (block_pde) ML_free(block_pde);
options[AZ_scaling] = AZ_none;
options[AZ_precond] = AZ_user_precond;
options[AZ_conv] = AZ_r0;
options[AZ_output] = 1;
options[AZ_max_iter] = context->max_outer_its;
options[AZ_poly_ord] = 5;
options[AZ_kspace] = 130;
params[AZ_tol] = context->tol;
options[AZ_output] = context->output;
ML_free(context);
AZ_set_ML_preconditioner(&Pmat, Amat, ml, options);
setup_time = AZ_second() - start_time;
xxx = (double *) malloc( leng*sizeof(double));
for (iii = 0; iii < leng; iii++) xxx[iii] = 0.0;
/* Set x */
/*
there is no initguess supplied with these examples for the moment....
*/
fp = fopen("initguessfile","r");
if (fp != NULL) {
fclose(fp);
if (proc_config[AZ_node]== 0) printf("reading initial guess from file\n");
AZ_input_msr_matrix("data_initguess.txt", update, &xxx, &garbage, N_update,
proc_config);
options[AZ_conv] = AZ_expected_values;
}
else if (proc_config[AZ_node]== 0) printf("taking 0 initial guess \n");
AZ_reorder_vec(xxx, data_org, update_index, NULL);
/* if Dirichlet BC ... put the answer in */
for (i = 0; i < data_org[AZ_N_internal]+data_org[AZ_N_border]; i++) {
if ( (val[i] > .99999999) && (val[i] < 1.0000001))
xxx[i] = rhs[i];
}
fp = fopen("AZ_no_multilevel.dat","r");
scaling = AZ_scaling_create();
start_time = AZ_second();
if (fp != NULL) {
fclose(fp);
options[AZ_precond] = AZ_none;
options[AZ_scaling] = AZ_sym_diag;
options[AZ_ignore_scaling] = AZ_TRUE;
options[AZ_keep_info] = 1;
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, NULL, scaling);
/*
options[AZ_pre_calc] = AZ_reuse;
options[AZ_conv] = AZ_expected_values;
if (proc_config[AZ_node] == 0)
printf("\n-------- Second solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, NULL, scaling);
if (proc_config[AZ_node] == 0)
printf("\n-------- Third solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, NULL, scaling);
*/
}
else {
options[AZ_keep_info] = 1;
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, Pmat, scaling);
options[AZ_pre_calc] = AZ_reuse;
options[AZ_conv] = AZ_expected_values;
/*
if (proc_config[AZ_node] == 0)
printf("\n-------- Second solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, Pmat, scaling);
if (proc_config[AZ_node] == 0)
printf("\n-------- Third solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, Pmat, scaling);
*/
}
solve_time = AZ_second() - start_time;
if (proc_config[AZ_node] == 0)
printf("Solve time = %e, MG Setup time = %e\n", solve_time, setup_time);
if (proc_config[AZ_node] == 0)
printf("Printing out a few entries of the solution ...\n");
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 7) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 23) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 47) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 101) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 171) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
ML_Aggregate_Destroy(&ag);
ML_Destroy(&ml);
AZ_free((void *) Amat->data_org);
AZ_free((void *) Amat->val);
AZ_free((void *) Amat->bindx);
AZ_free((void *) update);
AZ_free((void *) external);
AZ_free((void *) extern_index);
AZ_free((void *) update_index);
AZ_scaling_destroy(&scaling);
if (Amat != NULL) AZ_matrix_destroy(&Amat);
if (Pmat != NULL) AZ_precond_destroy(&Pmat);
free(xxx);
free(rhs);
#ifdef ML_MPI
MPI_Finalize();
#endif
return 0;
}
int main(int argc, char *argv[])
{
char global[]="global";
char local[]="local";
int proc_config[AZ_PROC_SIZE];/* Processor information. */
int options[AZ_OPTIONS_SIZE]; /* Array used to select solver options. */
double params[AZ_PARAMS_SIZE]; /* User selected solver paramters. */
int *data_org;
/* Array to specify data layout */
double status[AZ_STATUS_SIZE]; /* Information returned from AZ_solve(). */
int *update; /* vector elements updated on this node. */
int *external;
/* vector elements needed by this node. */
int *update_index;
/* ordering of update[] and external[] */
int *extern_index;
/* locally on this processor. */
int *indx; /* MSR format of real and imag parts */
int *bindx;
int *bpntr;
int *rpntr;
int *cpntr;
AZ_MATRIX *Amat;
AZ_PRECOND *Prec;
double *val;
double *x, *b, *xexact, *xsolve;
int n_nonzeros, n_blk_nonzeros;
int N_update; /* # of block unknowns updated on this node */
int N_local;
/* Number scalar equations on this node */
int N_global, N_blk_global; /* Total number of equations */
int N_external, N_blk_eqns;
double *val_msr;
int *bindx_msr;
double norm, d ;
int matrix_type;
int has_global_indices, option;
int i, j, m, mp ;
int ione = 1;
#ifdef TEST_SINGULAR
double * xnull; /* will contain difference of given exact solution and computed solution*/
double * Axnull; /* Product of A time xnull */
double norm_Axnull;
#endif
#ifdef AZTEC_MPI
double MPI_Wtime(void) ;
#endif
double time ;
#ifdef AZTEC_MPI
MPI_Init(&argc,&argv);
#endif
/* get number of processors and the name of this processor */
#ifdef AZTEC_MPI
AZ_set_proc_config(proc_config,MPI_COMM_WORLD);
#else
AZ_set_proc_config(proc_config,0);
#endif
printf("proc %d of %d is alive\n",
proc_config[AZ_node],proc_config[AZ_N_procs]) ;
#ifdef AZTEC_MPI
MPI_Barrier(MPI_COMM_WORLD) ;
#endif
#ifdef VBRMATRIX
if(argc != 3)
perror("error: enter name of data and partition file on command line") ;
#else
if(argc != 2) perror("error: enter name of data file on command line") ;
#endif
/* Set exact solution to NULL */
xexact = NULL;
/* Read matrix file and distribute among processors.
Returns with this processor's set of rows */
#ifdef VBRMATRIX
read_hb(argv[1], proc_config, &N_global, &n_nonzeros,
&val_msr, &bindx_msr, &x, &b, &xexact);
create_vbr(argv[2], proc_config, &N_global, &N_blk_global,
&n_nonzeros, &n_blk_nonzeros, &N_update, &update,
bindx_msr, val_msr, &val, &indx,
&rpntr, &cpntr, &bpntr, &bindx);
if(proc_config[AZ_node] == 0)
{
free ((void *) val_msr);
free ((void *) bindx_msr);
free ((void *) cpntr);
}
matrix_type = AZ_VBR_MATRIX;
#ifdef AZTEC_MPI
MPI_Barrier(MPI_COMM_WORLD) ;
#endif
distrib_vbr_matrix( proc_config, N_global, N_blk_global,
&n_nonzeros, &n_blk_nonzeros,
&N_update, &update,
&val, &indx, &rpntr, &cpntr, &bpntr, &bindx,
&x, &b, &xexact);
#else
read_hb(argv[1], proc_config, &N_global, &n_nonzeros,
&val, &bindx, &x, &b, &xexact);
#ifdef AZTEC_MPI
MPI_Barrier(MPI_COMM_WORLD) ;
#endif
distrib_msr_matrix(proc_config, N_global, &n_nonzeros, &N_update,
&update, &val, &bindx, &x, &b, &xexact);
#ifdef DEBUG
for (i = 0; i<N_update; i++)
if (val[i] == 0.0 ) printf("Zero diagonal at row %d\n",i);
#endif
matrix_type = AZ_MSR_MATRIX;
#endif
/* convert matrix to a local distributed matrix */
cpntr = NULL;
AZ_transform(proc_config, &external, bindx, val, update,
&update_index, &extern_index, &data_org,
N_update, indx, bpntr, rpntr, &cpntr,
matrix_type);
printf("Processor %d: Completed AZ_transform\n",proc_config[AZ_node]) ;
has_global_indices = 0;
option = AZ_LOCAL;
#ifdef VBRMATRIX
N_local = rpntr[N_update];
#else
N_local = N_update;
#endif
Amat = AZ_matrix_create(N_local);
#ifdef VBRMATRIX
AZ_set_VBR(Amat, rpntr, cpntr, bpntr, indx, bindx, val, data_org,
N_update, update, option);
#else
AZ_set_MSR(Amat, bindx, val, data_org, N_update, update, option);
#endif
printf("proc %d Completed AZ_create_matrix\n",proc_config[AZ_node]) ;
#ifdef AZTEC_MPI
MPI_Barrier(MPI_COMM_WORLD) ;
#endif
/* initialize AZTEC options */
AZ_defaults(options, params);
options[AZ_solver] = AZ_gmres;
options[AZ_precond] = AZ_sym_GS;
options[AZ_poly_ord] = 1;
options[AZ_graph_fill] = 1;
params[AZ_rthresh] = 0.0E-7;
params[AZ_athresh] = 0.0E-7;
options[AZ_overlap] = 1;
/*
params[AZ_ilut_fill] = 2.0;
params[AZ_drop] = 0.01;
options[AZ_overlap] = 0;
options[AZ_reorder] = 0;
params[AZ_rthresh] = 1.0E-1;
params[AZ_athresh] = 1.0E-1;
options[AZ_precond] = AZ_dom_decomp ;
options[AZ_subdomain_solve] = AZ_bilu_ifp;
options[AZ_reorder] = 0;
options[AZ_graph_fill] = 0;
params[AZ_rthresh] = 1.0E-7;
params[AZ_athresh] = 1.0E-7;
options[AZ_poly_ord] = 1;
options[AZ_precond] = AZ_Jacobi;
params[AZ_omega] = 1.0;
options[AZ_precond] = AZ_none ;
options[AZ_poly_ord] = 1;
options[AZ_precond] = AZ_Jacobi ;
options[AZ_scaling] = AZ_sym_row_sum ;
options[AZ_scaling] = AZ_sym_diag;
options[AZ_conv] = AZ_noscaled;
options[AZ_scaling] = AZ_Jacobi ;
options[AZ_precond] = AZ_dom_decomp ;
options[AZ_subdomain_solve] = AZ_icc ;
options[AZ_subdomain_solve] = AZ_ilut ;
params[AZ_omega] = 1.2;
params[AZ_ilut_fill] = 2.0;
params[AZ_drop] = 0.01;
options[AZ_reorder] = 0;
options[AZ_overlap] = 0;
options[AZ_type_overlap] = AZ_symmetric;
options[AZ_precond] = AZ_dom_decomp ;
options[AZ_subdomain_solve] = AZ_bilu ;
options[AZ_graph_fill] = 0;
options[AZ_overlap] = 0;
options[AZ_precond] = AZ_dom_decomp ;
options[AZ_subdomain_solve] = AZ_bilu_ifp ;
options[AZ_graph_fill] = 0;
options[AZ_overlap] = 0;
params[AZ_rthresh] = 1.0E-3;
params[AZ_athresh] = 1.0E-3;
options[AZ_poly_ord] = 1;
options[AZ_precond] = AZ_Jacobi ; */
options[AZ_kspace] = 600 ;
options[AZ_max_iter] = 600 ;
params[AZ_tol] = 1.0e-14;
#ifdef BGMRES
options[AZ_gmres_blocksize] = 3;
options[AZ_gmres_num_rhs] = 1;
#endif
#ifdef DEBUG
if (proc_config[AZ_N_procs]==1)
write_vec("rhs.dat", N_local, b);
#endif
/* xsolve is a little longer vector needed to account for external
entries. Make it and copy x (initial guess) into it.
*/
if (has_global_indices)
{
N_external = 0;
}
else
{
N_external = data_org[AZ_N_external];
}
xsolve = (double *) calloc(N_local + N_external,
sizeof(double)) ;
for (i=0; i<N_local; i++) xsolve[i] = x[i];
/* Reorder rhs and xsolve to match matrix ordering from AZ_transform */
if (!has_global_indices)
{
AZ_reorder_vec(b, data_org, update_index, rpntr) ;
AZ_reorder_vec(xsolve, data_org, update_index, rpntr) ;
}
#ifdef VBRMATRIX
AZ_check_vbr(N_update, data_org[AZ_N_ext_blk], AZ_LOCAL,
bindx, bpntr, cpntr, rpntr, proc_config);
#else
AZ_check_msr(bindx, N_update, N_external, AZ_LOCAL, proc_config);
#endif
printf("Processor %d of %d N_local = %d N_external = %d NNZ = %d\n",
proc_config[AZ_node],proc_config[AZ_N_procs],N_local,N_external,
n_nonzeros);
/* solve the system of equations using b as the right hand side */
Prec = AZ_precond_create(Amat,AZ_precondition, NULL);
AZ_iterate(xsolve, b, options, params, status, proc_config,
Amat, Prec, NULL);
/*AZ_ifpack_iterate(xsolve, b, options, params, status, proc_config,
Amat);*/
if (proc_config[AZ_node]==0)
{
printf("True residual norm = %22.16g\n",status[AZ_r]);
printf("True scaled res = %22.16g\n",status[AZ_scaled_r]);
printf("Computed res norm = %22.16g\n",status[AZ_rec_r]);
}
#ifdef TEST_SINGULAR
xnull = (double *) calloc(N_local + N_external, sizeof(double)) ;
Axnull = (double *) calloc(N_local + N_external, sizeof(double)) ;
for (i=0; i<N_local; i++) xnull[i] = xexact[i];
if (!has_global_indices) AZ_reorder_vec(xnull, data_org, update_index, rpntr);
for (i=0; i<N_local; i++) xnull[i] -= xsolve[i]; /* fill with nullerence */
Amat->matvec(xnull, Axnull, Amat, proc_config);
norm_Axnull = AZ_gvector_norm(N_local, 2, Axnull, proc_config);
if (proc_config[AZ_node]==0) printf("Norm of A(xexact-xsolve) = %12.4g\n",norm_Axnull);
free((void *) xnull);
free((void *) Axnull);
#endif
/* Get solution back into original ordering */
if (!has_global_indices) {
AZ_invorder_vec(xsolve, data_org, update_index, rpntr, x);
free((void *) xsolve);
}
else {
free((void *) x);
x = xsolve;
}
#ifdef DEBUG
if (proc_config[AZ_N_procs]==1)
write_vec("solution.dat", N_local, x);
#endif
if (xexact != NULL)
{
double sum = 0.0;
double largest = 0.0;
for (i=0; i<N_local; i++) sum += fabs(x[i]-xexact[i]);
printf("Processor %d: Difference between exact and computed solution = %12.4g\n",
proc_config[AZ_node],sum);
for (i=0; i<N_local; i++) largest = AZ_MAX(largest,fabs(xexact[i]));
printf("Processor %d: Difference divided by max abs value of exact = %12.4g\n",
proc_config[AZ_node],sum/largest);
}
free((void *) val);
free((void *) bindx);
#ifdef VBRMATRIX
free((void *) rpntr);
free((void *) bpntr);
free((void *) indx);
#endif
free((void *) b);
free((void *) x);
if (xexact!=NULL) free((void *) xexact);
AZ_free((void *) update);
AZ_free((void *) update_index);
AZ_free((void *) external);
AZ_free((void *) extern_index);
AZ_free((void *) data_org);
if (cpntr!=NULL) AZ_free((void *) cpntr);
AZ_precond_destroy(&Prec);
AZ_matrix_destroy(&Amat);
#ifdef AZTEC_MPI
MPI_Finalize() ;
#endif
/* end main
*/
return 0 ;
}
int main(int argc, char *argv[])
{
int num_PDE_eqns=6, N_levels=4, nsmooth=2;
int leng, level, N_grid_pts, coarsest_level;
/* See Aztec User's Guide for more information on the */
/* variables that follow. */
int proc_config[AZ_PROC_SIZE], options[AZ_OPTIONS_SIZE];
double params[AZ_PARAMS_SIZE], status[AZ_STATUS_SIZE];
/* data structure for matrix corresponding to the fine grid */
double *val = NULL, *xxx, *rhs, solve_time, setup_time, start_time;
AZ_MATRIX *Amat;
AZ_PRECOND *Pmat = NULL;
ML *ml;
FILE *fp;
int i, j, Nrigid, *garbage = NULL;
#ifdef ML_partition
int nblocks;
int *block_list = NULL;
int k;
#endif
struct AZ_SCALING *scaling;
ML_Aggregate *ag;
double *mode, *rigid;
char filename[80];
double alpha;
int allocated = 0;
int old_prec, old_sol;
double old_tol;
/*
double *Amode, beta, biggest;
int big_ind = -1, ii;
*/
ML_Operator *Amatrix;
int *rowi_col = NULL, rowi_N, count2, ccc;
double *rowi_val = NULL;
double max_diag, min_diag, max_sum, sum;
int nBlocks, *blockIndices, Ndof;
#ifdef ML_partition
FILE *fp2;
int count;
if (argc != 2) {
printf("Usage: ml_read_elas num_processors\n");
exit(1);
}
else sscanf(argv[1],"%d",&nblocks);
#endif
#ifdef HAVE_MPI
MPI_Init(&argc,&argv);
/* get number of processors and the name of this processor */
AZ_set_proc_config(proc_config, MPI_COMM_WORLD);
#else
AZ_set_proc_config(proc_config, AZ_NOT_MPI);
#endif
/* read in the number of matrix equations */
leng = 0;
if (proc_config[AZ_node] == 0) {
# ifdef binary
fp=fopen(".data","rb");
# else
fp=fopen(".data","r");
# endif
if (fp==NULL) {
printf("couldn't open file .data\n");
exit(1);
}
# ifdef binary
fread(&leng, sizeof(int), 1, fp);
# else
fscanf(fp,"%d",&leng);
# endif
fclose(fp);
}
leng = AZ_gsum_int(leng, proc_config);
N_grid_pts=leng/num_PDE_eqns;
/* initialize the list of global indices. NOTE: the list of global */
/* indices must be in ascending order so that subsequent calls to */
/* AZ_find_index() will function properly. */
if (proc_config[AZ_N_procs] == 1) i = AZ_linear;
else i = AZ_file;
AZ_read_update(&N_update, &update, proc_config, N_grid_pts, num_PDE_eqns,i);
AZ_read_msr_matrix(update, &val, &bindx, N_update, proc_config);
/* This code is to fix things up so that we are sure we have */
/* all block (including the ghost nodes the same size. */
AZ_block_MSR(&bindx, &val, N_update, num_PDE_eqns, update);
AZ_transform_norowreordering(proc_config, &external, bindx, val, update, &update_index,
&extern_index, &data_org, N_update, 0, 0, 0, &cpntr,
AZ_MSR_MATRIX);
Amat = AZ_matrix_create( leng );
AZ_set_MSR(Amat, bindx, val, data_org, 0, NULL, AZ_LOCAL);
Amat->matrix_type = data_org[AZ_matrix_type];
data_org[AZ_N_rows] = data_org[AZ_N_internal] + data_org[AZ_N_border];
#ifdef SCALE_ME
ML_MSR_sym_diagonal_scaling(Amat, proc_config, &scaling_vect);
#endif
start_time = AZ_second();
options[AZ_scaling] = AZ_none;
ML_Create(&ml, N_levels);
ML_Set_PrintLevel(10);
/* set up discretization matrix and matrix vector function */
AZ_ML_Set_Amat(ml, N_levels-1, N_update, N_update, Amat, proc_config);
#ifdef ML_partition
/* this code is meant to partition the matrices so that things can be */
/* run in parallel later. */
/* It is meant to be run on only one processor. */
#ifdef MB_MODIF
fp2 = fopen(".update","w");
#else
fp2 = fopen("partition_file","w");
#endif
ML_Operator_AmalgamateAndDropWeak(&(ml->Amat[N_levels-1]), num_PDE_eqns, 0.0);
ML_Gen_Blocks_Metis(ml, N_levels-1, &nblocks, &block_list);
for (i = 0; i < nblocks; i++) {
count = 0;
for (j = 0; j < ml->Amat[N_levels-1].outvec_leng; j++) {
if (block_list[j] == i) count++;
}
fprintf(fp2," %d\n",count*num_PDE_eqns);
for (j = 0; j < ml->Amat[N_levels-1].outvec_leng; j++) {
if (block_list[j] == i) {
for (k = 0; k < num_PDE_eqns; k++) fprintf(fp2,"%d\n",j*num_PDE_eqns+k);
}
}
}
fclose(fp2);
ML_Operator_UnAmalgamateAndDropWeak(&(ml->Amat[N_levels-1]),num_PDE_eqns,0.0);
#ifdef MB_MODIF
printf(" partition file dumped in .update\n");
#endif
exit(1);
#endif
ML_Aggregate_Create( &ag );
/*
ML_Aggregate_Set_CoarsenScheme_MIS(ag);
*/
#ifdef MB_MODIF
ML_Aggregate_Set_DampingFactor(ag,1.50);
#else
ML_Aggregate_Set_DampingFactor(ag,1.5);
#endif
ML_Aggregate_Set_CoarsenScheme_METIS(ag);
ML_Aggregate_Set_NodesPerAggr( ml, ag, -1, 35);
/*
ML_Aggregate_Set_Phase3AggregateCreationAggressiveness(ag, 10.001);
*/
ML_Aggregate_Set_Threshold(ag, 0.0);
ML_Aggregate_Set_MaxCoarseSize( ag, 300);
/* read in the rigid body modes */
Nrigid = 0;
/* to ensure compatibility with RBM dumping software */
if (proc_config[AZ_node] == 0) {
sprintf(filename,"rigid_body_mode%02d",Nrigid+1);
while( (fp = fopen(filename,"r")) != NULL) {
which_filename = 1;
fclose(fp);
Nrigid++;
sprintf(filename,"rigid_body_mode%02d",Nrigid+1);
}
sprintf(filename,"rigid_body_mode%d",Nrigid+1);
while( (fp = fopen(filename,"r")) != NULL) {
fclose(fp);
Nrigid++;
sprintf(filename,"rigid_body_mode%d",Nrigid+1);
}
}
Nrigid = AZ_gsum_int(Nrigid,proc_config);
if (Nrigid != 0) {
rigid = (double *) ML_allocate( sizeof(double)*Nrigid*(N_update+1) );
if (rigid == NULL) {
printf("Error: Not enough space for rigid body modes\n");
}
}
rhs = (double *) malloc(leng*sizeof(double));
xxx = (double *) malloc(leng*sizeof(double));
for (iii = 0; iii < leng; iii++) xxx[iii] = 0.0;
for (i = 0; i < Nrigid; i++) {
if (which_filename == 1) sprintf(filename,"rigid_body_mode%02d",i+1);
else sprintf(filename,"rigid_body_mode%d",i+1);
AZ_input_msr_matrix(filename,update,&mode,&garbage,N_update,proc_config);
AZ_reorder_vec(mode, data_org, update_index, NULL);
/* here is something to stick a rigid body mode as the initial */
/* The idea is to solve A x = 0 without smoothing with a two */
/* level method. If everything is done properly, we should */
/* converge in 2 iterations. */
/* Note: we must also zero out components of the rigid body */
/* mode that correspond to Dirichlet bcs. */
if (i == -4) {
for (iii = 0; iii < leng; iii++) xxx[iii] = mode[iii];
ccc = 0;
Amatrix = &(ml->Amat[N_levels-1]);
for (iii = 0; iii < Amatrix->outvec_leng; iii++) {
ML_get_matrix_row(Amatrix,1,&iii,&allocated,&rowi_col,&rowi_val,
&rowi_N, 0);
count2 = 0;
for (j = 0; j < rowi_N; j++) if (rowi_val[j] != 0.) count2++;
if (count2 <= 1) { xxx[iii] = 0.; ccc++; }
}
free(rowi_col); free(rowi_val);
allocated = 0; rowi_col = NULL; rowi_val = NULL;
}
/*
* Rescale matrix/rigid body modes and checking
*
AZ_sym_rescale_sl(mode, Amat->data_org, options, proc_config, scaling);
Amat->matvec(mode, rigid, Amat, proc_config);
for (j = 0; j < N_update; j++) printf("this is %d %e\n",j,rigid[j]);
*/
/* Here is some code to check that the rigid body modes are */
/* really rigid body modes. The idea is to multiply by A and */
/* then to zero out things that we "think" are boundaries. */
/* In this hardwired example, things near boundaries */
/* correspond to matrix rows that do not have 81 nonzeros. */
/*
Amode = (double *) malloc(leng*sizeof(double));
Amat->matvec(mode, Amode, Amat, proc_config);
j = 0;
biggest = 0.0;
for (ii = 0; ii < N_update; ii++) {
if ( Amat->bindx[ii+1] - Amat->bindx[ii] != 80) {
Amode[ii] = 0.; j++;
}
else {
if ( fabs(Amode[ii]) > biggest) {
biggest=fabs(Amode[ii]); big_ind = ii;
}
}
}
printf("%d entries zeroed out of %d elements\n",j,N_update);
alpha = AZ_gdot(N_update, Amode, Amode, proc_config);
beta = AZ_gdot(N_update, mode, mode, proc_config);
printf("||A r||^2 =%e, ||r||^2 = %e, ratio = %e\n",
alpha,beta,alpha/beta);
printf("the biggest is %e at row %d\n",biggest,big_ind);
free(Amode);
*/
/* orthogonalize mode with respect to previous modes. */
for (j = 0; j < i; j++) {
alpha = -AZ_gdot(N_update, mode, &(rigid[j*N_update]), proc_config)/
AZ_gdot(N_update, &(rigid[j*N_update]),
&(rigid[j*N_update]), proc_config);
/* daxpy_(&N_update,&alpha,&(rigid[j*N_update]), &one, mode, &one); */
}
#ifndef MB_MODIF
printf(" after mb %e %e %e\n",mode[0],mode[1],mode[2]);
#endif
for (j = 0; j < N_update; j++) rigid[i*N_update+j] = mode[j];
free(mode);
free(garbage); garbage = NULL;
}
if (Nrigid != 0) {
ML_Aggregate_Set_BlockDiagScaling(ag);
ML_Aggregate_Set_NullSpace(ag, num_PDE_eqns, Nrigid, rigid, N_update);
free(rigid);
}
#ifdef SCALE_ME
ML_Aggregate_Scale_NullSpace(ag, scaling_vect, N_update);
#endif
coarsest_level = ML_Gen_MGHierarchy_UsingAggregation(ml, N_levels-1,
ML_DECREASING, ag);
AZ_defaults(options, params);
coarsest_level = N_levels - coarsest_level;
if ( proc_config[AZ_node] == 0 )
printf("Coarse level = %d \n", coarsest_level);
/* set up smoothers */
for (level = N_levels-1; level > coarsest_level; level--) {
/*
ML_Gen_Smoother_BlockGaussSeidel(ml, level,ML_BOTH, 1, 1., num_PDE_eqns);
*/
/* Sparse approximate inverse smoother that acutally does both */
/* pre and post smoothing. */
/*
ML_Gen_Smoother_ParaSails(ml , level, ML_PRESMOOTHER, nsmooth,
parasails_sym, parasails_thresh,
parasails_nlevels, parasails_filter,
parasails_loadbal, parasails_factorized);
*/
/* This is the symmetric Gauss-Seidel smoothing that we usually use. */
/* In parallel, it is not a true Gauss-Seidel in that each processor */
/* does a Gauss-Seidel on its local submatrix independent of the */
/* other processors. */
/* ML_Gen_Smoother_Cheby(ml, level, ML_BOTH, 30., nsmooth); */
Ndof = ml->Amat[level].invec_leng;
ML_Gen_Blocks_Aggregates(ag, level, &nBlocks, &blockIndices);
ML_Gen_Smoother_BlockDiagScaledCheby(ml, level, ML_BOTH, 30.,nsmooth,
nBlocks, blockIndices);
/*
ML_Gen_Smoother_SymGaussSeidel(ml , level, ML_BOTH, nsmooth,1.);
*/
/* This is a true Gauss Seidel in parallel. This seems to work for */
/* elasticity problems. However, I don't believe that this is very */
/* efficient in parallel. */
/*
nblocks = ml->Amat[level].invec_leng/num_PDE_eqns;
blocks = (int *) ML_allocate(sizeof(int)*N_update);
for (i =0; i < ml->Amat[level].invec_leng; i++)
blocks[i] = i/num_PDE_eqns;
ML_Gen_Smoother_VBlockSymGaussSeidelSequential(ml , level, ML_PRESMOOTHER,
nsmooth, 1., nblocks, blocks);
ML_Gen_Smoother_VBlockSymGaussSeidelSequential(ml, level, ML_POSTSMOOTHER,
nsmooth, 1., nblocks, blocks);
free(blocks);
*/
/* Block Jacobi Smoothing */
/*
nblocks = ml->Amat[level].invec_leng/num_PDE_eqns;
blocks = (int *) ML_allocate(sizeof(int)*N_update);
for (i =0; i < ml->Amat[level].invec_leng; i++)
blocks[i] = i/num_PDE_eqns;
ML_Gen_Smoother_VBlockJacobi(ml , level, ML_BOTH, nsmooth,
ML_ONE_STEP_CG, nblocks, blocks);
free(blocks);
*/
/* Jacobi Smoothing */
/*
ML_Gen_Smoother_Jacobi(ml , level, ML_PRESMOOTHER, nsmooth, ML_ONE_STEP_CG);
ML_Gen_Smoother_Jacobi(ml , level, ML_POSTSMOOTHER, nsmooth,ML_ONE_STEP_CG);
*/
/* This does a block Gauss-Seidel (not true GS in parallel) */
/* where each processor has 'nblocks' blocks. */
/*
nblocks = 250;
ML_Gen_Blocks_Metis(ml, level, &nblocks, &blocks);
ML_Gen_Smoother_VBlockJacobi(ml , level, ML_BOTH, nsmooth,ML_ONE_STEP_CG,
nblocks, blocks);
free(blocks);
*/
num_PDE_eqns = 6;
}
/* Choose coarse grid solver: mls, superlu, symGS, or Aztec */
/*
ML_Gen_Smoother_Cheby(ml, coarsest_level, ML_BOTH, 30., nsmooth);
ML_Gen_CoarseSolverSuperLU( ml, coarsest_level);
*/
/*
ML_Gen_Smoother_SymGaussSeidel(ml , coarsest_level, ML_BOTH, nsmooth,1.);
*/
old_prec = options[AZ_precond];
old_sol = options[AZ_solver];
old_tol = params[AZ_tol];
params[AZ_tol] = 1.0e-9;
params[AZ_tol] = 1.0e-5;
options[AZ_precond] = AZ_Jacobi;
options[AZ_solver] = AZ_cg;
options[AZ_poly_ord] = 1;
options[AZ_conv] = AZ_r0;
options[AZ_orth_kvecs] = AZ_TRUE;
j = AZ_gsum_int(ml->Amat[coarsest_level].outvec_leng, proc_config);
options[AZ_keep_kvecs] = j - 6;
options[AZ_max_iter] = options[AZ_keep_kvecs];
ML_Gen_SmootherAztec(ml, coarsest_level, options, params,
proc_config, status, options[AZ_keep_kvecs], ML_PRESMOOTHER, NULL);
options[AZ_conv] = AZ_noscaled;
options[AZ_keep_kvecs] = 0;
options[AZ_orth_kvecs] = 0;
options[AZ_precond] = old_prec;
options[AZ_solver] = old_sol;
params[AZ_tol] = old_tol;
/* */
#ifdef RST_MODIF
ML_Gen_Solver(ml, ML_MGV, N_levels-1, coarsest_level);
#else
#ifdef MB_MODIF
ML_Gen_Solver(ml, ML_SAAMG, N_levels-1, coarsest_level);
#else
ML_Gen_Solver(ml, ML_MGFULLV, N_levels-1, coarsest_level);
#endif
#endif
options[AZ_solver] = AZ_GMRESR;
options[AZ_solver] = AZ_cg;
options[AZ_scaling] = AZ_none;
options[AZ_precond] = AZ_user_precond;
options[AZ_conv] = AZ_r0;
options[AZ_conv] = AZ_noscaled;
options[AZ_output] = 1;
options[AZ_max_iter] = 500;
options[AZ_poly_ord] = 5;
options[AZ_kspace] = 40;
params[AZ_tol] = 4.8e-6;
AZ_set_ML_preconditioner(&Pmat, Amat, ml, options);
setup_time = AZ_second() - start_time;
/* Set rhs */
fp = fopen("AZ_capture_rhs.dat","r");
if (fp == NULL) {
AZ_random_vector(rhs, data_org, proc_config);
if (proc_config[AZ_node] == 0) printf("taking random vector for rhs\n");
for (i = 0; i < -N_update; i++) {
rhs[i] = (double) update[i]; rhs[i] = 7.;
}
}
else {
if (proc_config[AZ_node]== 0) printf("reading rhs guess from file\n");
AZ_input_msr_matrix("AZ_capture_rhs.dat", update, &rhs, &garbage,
N_update, proc_config);
free(garbage);
}
AZ_reorder_vec(rhs, data_org, update_index, NULL);
printf("changing rhs by multiplying with A\n");
Amat->matvec(rhs, xxx, Amat, proc_config);
for (i = 0; i < N_update; i++) rhs[i] = xxx[i];
fp = fopen("AZ_capture_init_guess.dat","r");
if (fp != NULL) {
fclose(fp);
if (proc_config[AZ_node]== 0) printf("reading initial guess from file\n");
AZ_input_msr_matrix("AZ_capture_init_guess.dat", update, &xxx, &garbage,
N_update, proc_config);
free(garbage);
xxx = (double *) realloc(xxx, sizeof(double)*(
Amat->data_org[AZ_N_internal]+
Amat->data_org[AZ_N_border] +
Amat->data_org[AZ_N_external]));
}
AZ_reorder_vec(xxx, data_org, update_index, NULL);
/* if Dirichlet BC ... put the answer in */
/*
for (i = 0; i < data_org[AZ_N_internal]+data_org[AZ_N_border]; i++) {
if ( (val[i] > .99999999) && (val[i] < 1.0000001))
xxx[i] = rhs[i];
}
*/
fp = fopen("AZ_no_multilevel.dat","r");
scaling = AZ_scaling_create();
start_time = AZ_second();
if (fp != NULL) {
fclose(fp);
options[AZ_precond] = AZ_none;
options[AZ_scaling] = AZ_sym_diag;
options[AZ_ignore_scaling] = AZ_TRUE;
options[AZ_keep_info] = 1;
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, NULL, scaling);
/*
options[AZ_pre_calc] = AZ_reuse;
options[AZ_conv] = AZ_expected_values;
if (proc_config[AZ_node] == 0)
printf("\n-------- Second solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, NULL, scaling);
if (proc_config[AZ_node] == 0)
printf("\n-------- Third solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, NULL, scaling);
*/
}
else {
options[AZ_keep_info] = 1;
options[AZ_conv] = AZ_noscaled;
options[AZ_conv] = AZ_r0;
params[AZ_tol] = 1.0e-7;
/* ML_Iterate(ml, xxx, rhs); */
alpha = sqrt(AZ_gdot(N_update, xxx, xxx, proc_config));
printf("init guess = %e\n",alpha);
alpha = sqrt(AZ_gdot(N_update, rhs, rhs, proc_config));
printf("rhs = %e\n",alpha);
#ifdef SCALE_ME
ML_MSR_scalerhs(rhs, scaling_vect, data_org[AZ_N_internal] +
data_org[AZ_N_border]);
ML_MSR_scalesol(xxx, scaling_vect, data_org[AZ_N_internal] +
data_org[AZ_N_border]);
#endif
max_diag = 0.;
min_diag = 1.e30;
max_sum = 0.;
for (i = 0; i < N_update; i++) {
if (Amat->val[i] < 0.) printf("woops negative diagonal A(%d,%d) = %e\n",
i,i,Amat->val[i]);
if (Amat->val[i] > max_diag) max_diag = Amat->val[i];
if (Amat->val[i] < min_diag) min_diag = Amat->val[i];
sum = fabs(Amat->val[i]);
for (j = Amat->bindx[i]; j < Amat->bindx[i+1]; j++) {
sum += fabs(Amat->val[j]);
}
if (sum > max_sum) max_sum = sum;
}
printf("Largest diagonal = %e, min diag = %e large abs row sum = %e\n",
max_diag, min_diag, max_sum);
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, Pmat, scaling);
options[AZ_pre_calc] = AZ_reuse;
options[AZ_conv] = AZ_expected_values;
/*
if (proc_config[AZ_node] == 0)
printf("\n-------- Second solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, Pmat, scaling);
if (proc_config[AZ_node] == 0)
printf("\n-------- Third solve with improved convergence test -----\n");
AZ_iterate(xxx, rhs, options, params, status, proc_config, Amat, Pmat, scaling);
*/
}
solve_time = AZ_second() - start_time;
if (proc_config[AZ_node] == 0)
printf("Solve time = %e, MG Setup time = %e\n", solve_time, setup_time);
if (proc_config[AZ_node] == 0)
printf("Printing out a few entries of the solution ...\n");
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 7) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 23) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 47) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 101) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
j = AZ_gsum_int(7, proc_config); /* sync processors */
for (j=0;j<Amat->data_org[AZ_N_internal]+ Amat->data_org[AZ_N_border];j++)
if (update[j] == 171) {printf("solution(gid = %d) = %10.4e\n",
update[j],xxx[update_index[j]]); fflush(stdout);}
ML_Aggregate_Destroy(&ag);
ML_Destroy(&ml);
AZ_free((void *) Amat->data_org);
AZ_free((void *) Amat->val);
AZ_free((void *) Amat->bindx);
AZ_free((void *) update);
AZ_free((void *) external);
AZ_free((void *) extern_index);
AZ_free((void *) update_index);
AZ_scaling_destroy(&scaling);
if (Amat != NULL) AZ_matrix_destroy(&Amat);
if (Pmat != NULL) AZ_precond_destroy(&Pmat);
free(xxx);
free(rhs);
#ifdef HAVE_MPI
MPI_Finalize();
#endif
return 0;
}
int test_azoo_conv_with_scaling(int conv_option, int scaling_option,
const Epetra_Comm& comm, bool verbose)
{
int localN = 20;
int numprocs = comm.NumProc();
int globalN = numprocs*localN;
Epetra_Map emap(globalN, 0, comm);
Epetra_CrsMatrix* Acrs = create_and_fill_crs_matrix(emap);
Epetra_Vector x_crs(emap), b_crs(emap);
x_crs.PutScalar(1.0);
Acrs->Multiply(false, x_crs, b_crs);
x_crs.PutScalar(0.0);
AztecOO azoo(Acrs, &x_crs, &b_crs);
azoo.SetAztecOption(AZ_conv, conv_option);
azoo.SetAztecOption(AZ_solver, AZ_cg);
azoo.SetAztecOption(AZ_scaling, scaling_option);
azoo.Iterate(100, 1.e-9);
//now, do the same thing with 'old-fashioned Aztec', and compare
//the solutions.
int* proc_config = new int[AZ_PROC_SIZE];
#ifdef EPETRA_MPI
AZ_set_proc_config(proc_config, MPI_COMM_WORLD);
AZ_set_comm(proc_config, MPI_COMM_WORLD);
#else
AZ_set_proc_config(proc_config, 0);
#endif
int *external, *update_index, *external_index;
int *external2, *update_index2, *external_index2;
AZ_MATRIX* Amsr = NULL;
AZ_MATRIX* Avbr = NULL;
int err = create_and_transform_simple_matrix(AZ_MSR_MATRIX, localN, 4.0,
proc_config, Amsr,
external, update_index,
external_index);
int N_update = localN+Amsr->data_org[AZ_N_border];
double* x_msr = new double[N_update];
double* b_msr = new double[N_update*2];
double* b_msr_u = b_msr+N_update;
double* x_vbr = new double[N_update];
double* b_vbr = new double[N_update*2];
double* b_vbr_u = b_vbr+N_update;
err = create_and_transform_simple_matrix(AZ_VBR_MATRIX, localN, 4.0,
proc_config, Avbr,
external2, update_index2,
external_index2);
for(int i=0; i<N_update; ++i) {
x_msr[i] = 1.0;
b_msr[i] = 0.0;
b_msr_u[i] = 0.0;
x_vbr[i] = 1.0;
b_vbr[i] = 0.0;
b_vbr_u[i] = 0.0;
}
Amsr->matvec(x_msr, b_msr, Amsr, proc_config);
Avbr->matvec(x_vbr, b_vbr, Avbr, proc_config);
for(int i=0; i<N_update; ++i) {
x_msr[i] = 0.0;
x_vbr[i] = 0.0;
}
//check that the rhs's are the same.
double max_rhs_diff1 = 0.0;
double max_rhs_diff2 = 0.0;
double* bptr_crs = b_crs.Values();
AZ_invorder_vec(b_msr, Amsr->data_org, update_index, NULL, b_msr_u);
AZ_invorder_vec(b_vbr, Avbr->data_org, update_index2, Avbr->rpntr, b_vbr_u);
for(int i=0; i<localN; ++i) {
if (std::abs(bptr_crs[i] - b_msr_u[i]) > max_rhs_diff1) {
max_rhs_diff1 = std::abs(bptr_crs[i] - b_msr_u[i]);
}
if (std::abs(bptr_crs[i] - b_vbr_u[i]) > max_rhs_diff2) {
max_rhs_diff2 = std::abs(bptr_crs[i] - b_vbr_u[i]);
}
}
if (max_rhs_diff1> 1.e-12) {
cout << "AztecOO rhs not equal to Aztec msr rhs "<<max_rhs_diff1<<endl;
return(-1);
}
if (max_rhs_diff2> 1.e-12) {
cout << "AztecOO rhs not equal to Aztec vbr rhs "<<max_rhs_diff2<<endl;
return(-1);
}
int* az_options = new int[AZ_OPTIONS_SIZE];
double* params = new double[AZ_PARAMS_SIZE];
double* status = new double[AZ_STATUS_SIZE];
AZ_defaults(az_options, params);
az_options[AZ_solver] = AZ_cg;
az_options[AZ_conv] = conv_option;
az_options[AZ_scaling] = scaling_option;
az_options[AZ_max_iter] = 100;
params[AZ_tol] = 1.e-9;
AZ_iterate(x_msr, b_msr, az_options, params, status, proc_config,
Amsr, NULL, NULL);
AZ_iterate(x_vbr, b_vbr, az_options, params, status, proc_config,
Avbr, NULL, NULL);
AZ_invorder_vec(x_msr, Amsr->data_org, update_index, NULL, b_msr_u);
AZ_invorder_vec(x_vbr, Avbr->data_org, update_index2, Avbr->rpntr, b_vbr_u);
double max_diff1 = 0.0;
double max_diff2 = 0.0;
double* xptr_crs = x_crs.Values();
for(int i=0; i<localN; ++i) {
if (std::abs(xptr_crs[i] - b_msr_u[i]) > max_diff1) {
max_diff1 = std::abs(xptr_crs[i] - b_msr_u[i]);
}
if (std::abs(xptr_crs[i] - b_vbr_u[i]) > max_diff2) {
max_diff2 = std::abs(xptr_crs[i] - b_vbr_u[i]);
}
}
if (max_diff1 > 1.e-7) {
cout << "AztecOO failed to match Aztec msr with scaling and Anorm conv."
<< endl;
return(-1);
}
if (max_diff2 > 1.e-7) {
cout << "AztecOO failed to match Aztec vbr with scaling and Anorm conv."
<< endl;
return(-1);
}
delete Acrs;
delete [] x_msr;
delete [] b_msr;
delete [] x_vbr;
delete [] b_vbr;
destroy_matrix(Amsr);
destroy_matrix(Avbr);
delete [] proc_config;
free(update_index);
free(external);
free(external_index);
free(update_index2);
free(external2);
free(external_index2);
delete [] az_options;
delete [] params;
delete [] status;
return(0);
}
double AZK_residual_norm_no_copy(double *xr, double *xi, double *br, double *bi,
int *options, double *params,
int *proc_config,
AZ_MATRIX *Amat_real, AZ_MATRIX *Amat_imag)
/*******************************************************************************
Author: Mike Heroux, SNL, 9222
=======
Return code: double
============
Parameter list:
===============
xr,xi: On input, contains the initial guess, real part in xr and
imaginary part in xi.
br,bi: Right hand side of linear system.
options: Determines specific solution method and other parameters.
params: Drop tolerance and convergence tolerance info.
proc_config: Machine configuration. proc_config[AZ_node] is the node
number. proc_config[AZ_N_procs] is the number of processors.
Amat_real,
Amat_imag: The real and imaginary parts of the complex operator, each
stored separately as AZ_MATRIX structures.
Overview
========
AZK_residual_norm_no_copy computes the two norm of the residual ||r|| where
r = b - A*x. Specifically, writing in terms of real and imaginary parts,
we have
(rr + i*ri) = (br + i*bi) - (Ar + i*Ai)*(xr + i*xi).
The two-norm of the complex vector r is identical to the two-norm of the
twice-length real vector formed by concatenating rr = real(r) and
ri = imag(r).
*******************************************************************************/
{
AZ_MATRIX *Amat; /* Structure representing matrix to be solved. */
double *x, *b; /* Solution and right-hand side to linear system. */
int N_equations, i;
double *y_tmp, result;
/* Transform complex system into komplex system */
AZK_create_linsys_no_copy (xr, xi, br, bi, options, params,
proc_config, Amat_real, Amat_imag, &x, &b, &Amat);
/* Allocate temp vector y */
N_equations = Amat->data_org[AZ_N_internal] + Amat->data_org[AZ_N_border];
y_tmp = (double *) AZ_allocate(N_equations*sizeof(double));
if (y_tmp == NULL)
AZ_perror("AZK_residual_norm_no_copy: Out of memory.");
/* Compute y = A*x. */
Amat->matvec(x, y_tmp, Amat, proc_config);
/* Compute r = b - A*x (put in y_tmp) */
/*daxpy_(&N_equations, &neg_one, b, &ione, y_tmp, &ione);*/
for (i=0; i<N_equations; i++) y_tmp[i] = y_tmp[i] - b[i];
/* Use Aztec function to compute norm */
result = AZ_gvector_norm(N_equations, 2, y_tmp, proc_config);
/* Free memory space */
AZK_destroy_linsys (options, params, proc_config, &x, &b, &Amat);
AZ_free((void *) y_tmp);
result = sqrt(result);
return(result);
/* AZK_residual_norm */
}
