void AZK_create_vector_c2k(int *options, double *params, int *proc_config, AZ_MATRIX *Amat_komplex, double *vc, double **vk) { AZ_KOMPLEX *linsys_pass_data; int i; int N_equations, N_external; int *data_org, *rpntr, *update_index; /* First executable statement */ linsys_pass_data = (AZ_KOMPLEX *) Amat_komplex->aux_ptr; data_org = Amat_komplex->data_org; update_index = linsys_pass_data->update_index; rpntr = Amat_komplex->rpntr; N_equations = data_org[AZ_N_internal] + data_org[AZ_N_border]; N_external = data_org[AZ_N_external]; (*vk) = (double *) AZ_allocate((N_equations+N_external)*sizeof(double)); if ((*vk) == NULL) AZ_perror("AZK_create_vector_c2k: Out of memory"); for (i=0; i <N_equations; i++) (*vk)[i] = vc[i]; /* Check if we need to reorder vector */ if (linsys_pass_data->From_Global_Indices) AZ_reorder_vec((*vk), data_org, update_index, rpntr); return; }
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[]) { /* See Aztec User's Guide for the variables that follow: */ int proc_config[AZ_PROC_SIZE];/* Processor information. */ int N_update; /* # of unknowns updated on this node */ int *update; /* vector elements updated on this node */ int *data_orgA; /* Array to specify data layout */ int *externalA; /* vector elements needed by this node. */ int *update_indexA; /* ordering of update[] and external[] */ int *extern_indexA; /* locally on this processor. */ int *bindxA; /* Sparse matrix to be solved is stored */ double *valA; /* in these MSR arrays. */ AZ_MATRIX *mat_curl_edge; /* curl operator matrix */ int *data_orgB; /* Array to specify data layout */ int *externalB; /* vector elements needed by this node. */ int *update_indexB; /* ordering of update[] and external[] */ int *extern_indexB; /* locally on this processor. */ int *bindxB; /* Sparse matrix to be solved is stored */ double *valB; /* in these MSR arrays. */ AZ_MATRIX *mat_curl_face; /* curl operator matrix */ int *bc_indx; int n_bc; double *efield; double *bfield; double *epsilon; double *tmp_vec; double *tmp_vec2; int i, nrow, x, y, z; int k, t; long startTime, endTime; int myrank; int vec_len; /* get number of processors and the name of this processor */ #ifdef AZ_MPI MPI_Init(&argc,&argv); AZ_set_proc_config(proc_config, MPI_COMM_WORLD); MPI_Comm_rank(MPI_COMM_WORLD, &myrank); #else myrank = 0; AZ_set_proc_config(proc_config, AZ_NOT_MPI); #endif nrow = ncomp * nx * ny * nz; /* overll number of matrix rows */ // Define partitioning: matrix rows (ascending order) owned by this node // Here it is done automatically, but it can also be specified by hand AZ_read_update(&N_update, &update, proc_config, nrow, 1, AZ_linear); // In the following we set up the matrix for the edge centered curl operator // All the steps are described in detail in the AZTEC manual. // first: allocate space for the first matrix. bindxA = (int *) malloc((N_update*MAX_NZ_ROW+1)*sizeof(int)); valA = (double *) malloc((N_update*MAX_NZ_ROW+1)*sizeof(double)); if (valA == NULL) perror("Error: Not enough space to create matrix"); // Initialize the index for the first off diagonal element bindxA[0] = N_update+1; // Create the matrix row by row. Each processor creates only rows appearing // in update[] (using global col. numbers). for (i = 0; i < N_update; i++) create_curl_matrix_row_edge(update[i], i, valA, bindxA); // convert matrix to a local distributed matrix AZ_transform(proc_config, &externalA, bindxA, valA, update, &update_indexA, &extern_indexA, &data_orgA, N_update, NULL, NULL, NULL, NULL, AZ_MSR_MATRIX); // convert the matrix arrays into a matrix structure, used in the // matrix vector multiplication mat_curl_edge = AZ_matrix_create(data_orgA[AZ_N_internal] + data_orgA[AZ_N_border]); AZ_set_MSR(mat_curl_edge, bindxA, valA, data_orgA, 0, NULL, AZ_LOCAL); // at this point the edge centered curl matrix is completed. // In the following we set up the matrix for the face centered curl operator // All the steps are described in detail in the AZTEC manual. // first: allocate space for the first matrix. bindxB = (int *) malloc((N_update*MAX_NZ_ROW+1)*sizeof(int)); valB = (double *) malloc((N_update*MAX_NZ_ROW+1)*sizeof(double)); if (valB == NULL) perror("Error: Not enough space to create matrix"); // Initialize the index for the first off diagonal element bindxB[0] = N_update+1; // Create the matrix row by row. Each processor creates only rows appearing // in update[] (using global col. numbers). for (i = 0; i < N_update; i++) create_curl_matrix_row_face(update[i], i, valB, bindxB); // convert matrix to a local distributed matrix AZ_transform(proc_config, &externalB, bindxB, valB, update, &update_indexB, &extern_indexB, &data_orgB, N_update, NULL, NULL, NULL, NULL, AZ_MSR_MATRIX); // convert the matrix arrays into a matrix structure, used in the // matrix vector multiplication mat_curl_face = AZ_matrix_create(data_orgB[AZ_N_internal] + data_orgB[AZ_N_border]); AZ_set_MSR(mat_curl_face, bindxB, valB, data_orgB, 0, NULL, AZ_LOCAL); // at this point the face centered curl matrix is completed. // allocate memory for the fields and a temporary vector vec_len = N_update + data_orgA[AZ_N_external]; efield = (double *) malloc(vec_len*sizeof(double)); bfield = (double *) malloc(vec_len*sizeof(double)); epsilon = (double *) malloc(vec_len*sizeof(double)); tmp_vec = (double *) malloc(vec_len*sizeof(double)); tmp_vec2 = (double *) malloc(vec_len*sizeof(double)); // setup the boundary condition. We will get an arry that tells us // which positions need to be updated and where the results needs // to be stored in the E field. setup_bc(update, update_indexB, N_update, &bc_indx, &n_bc); // initialize the field vectors for(k = 0; k < vec_len; k++){ efield[k] = 0.; bfield[k] = 0.; epsilon[k] = 1.; tmp_vec[k] = 0.; } // initialize the dielectric structure. Ugly hard-coded stuff, // needs to be cleaned out... for(y=45; y<55; y++){ for(x = y; x<100; x++) epsilon[compZ + pos_to_row(x, y, 0)] = 0.95; } // reorder the dielectric vector in order to align with the B field AZ_reorder_vec(epsilon, data_orgA, update_indexA, NULL); printf("Begin iteration \n"); // just some timing ... startTime = currentTimeMillis(); // ******************* // begin of the time stepping loop // ******************* for( t = 0; t < nsteps; t++){ // first we do the e field update // convert the B field to the H field for(k = 0 ; k < vec_len; k++) bfield[k] *= epsilon[k]; // setup the initial condition for( k = 0; k < n_bc; k++){ x = bc_indx[4*k]; y = bc_indx[4*k+1]; z = bc_indx[4*k+2]; efield[bc_indx[4*k+3]] = sin((double) y * 5. * 3.14159 / (double) ny) * sin(omega * dt * (double) (t + 1)); } // E field update: // tmp_vec = Curl_Op * bfield // efield = efield + c^2 * dt * tmp_vec AZ_MSR_matvec_mult( bfield, tmp_vec, mat_curl_edge, proc_config); // reorder the result in tmp_vec so that it aligns with the // decomposition of the E field AZ_invorder_vec(tmp_vec, data_orgA, update_indexA, NULL, tmp_vec2); AZ_reorder_vec(tmp_vec2, data_orgB, update_indexB, NULL); // update the efield for(k = 0 ; k < N_update; k++) efield[k] = efield[k] + c2 * tmp_vec2[k] * dt; // bfield update : // tmp_vec = DualCurl_Op * efield // bfield = bfield - tmp_vec * dt AZ_MSR_matvec_mult( efield, tmp_vec, mat_curl_face, proc_config); // reorder the result so that it fits the decomposition of the bfield AZ_invorder_vec(tmp_vec, data_orgB, update_indexB, NULL, tmp_vec2); AZ_reorder_vec(tmp_vec2, data_orgA, update_indexA, NULL); // update the b field for(k = 0; k < N_update; k++) bfield[k] = bfield[k] - tmp_vec2[k] * dt; if(myrank == 0) printf("Taking step %d at time %g\n", t, (double) (currentTimeMillis() - startTime) / 1000.); } // ****************** // end of timestepping loop // ***************** endTime = currentTimeMillis(); printf("After iteration: %g\n", (double)(endTime - startTime) / 1000. ); #if 1 system("rm efield.txt bfield.txt"); // dump filed data: efield AZ_invorder_vec(efield, data_orgB, update_indexB, NULL, tmp_vec); write_file("efield.txt", tmp_vec, N_update); // dump filed data: bfield AZ_invorder_vec(bfield, data_orgA, update_indexA, NULL, tmp_vec); write_file("bfield.txt", tmp_vec, N_update); #endif /* Free allocated memory */ AZ_matrix_destroy( &mat_curl_edge); free((void *) update); free((void *) update_indexA); free((void *) externalA); free((void *) extern_indexA); free((void *) bindxA); free((void *) valA); free((void *) data_orgA); AZ_matrix_destroy( &mat_curl_face); free((void *) externalB); free((void *) extern_indexB); free((void *) bindxB); free((void *) valB); free((void *) data_orgB); free((void *) efield); free((void *) bfield); free((void *) tmp_vec); free((void *) tmp_vec2); #ifdef AZ_MPI MPI_Finalize(); #endif return(1); }
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[]) { int num_PDE_eqns=5, N_levels=3; /* int nsmooth=1; */ 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 */ int *data_org = NULL, *update = NULL, *external = NULL; int *update_index = NULL, *extern_index = NULL; int *cpntr = NULL; int *bindx = NULL, N_update, iii; double *val = NULL; double *xxx, *rhs; AZ_MATRIX *Amat; AZ_PRECOND *Pmat = NULL; ML *ml; FILE *fp; int ch,i; struct AZ_SCALING *scaling; double solve_time, setup_time, start_time; ML_Aggregate *ag; int *ivec; #ifdef VBR_VERSION ML_Operator *B, *C, *D; int *vbr_cnptr, *vbr_rnptr, *vbr_indx, *vbr_bindx, *vbr_bnptr, total_blk_rows; int total_blk_cols, blk_space, nz_space; double *vbr_val; struct ML_CSR_MSRdata *csr_data; #endif #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); #else AZ_set_proc_config(proc_config, AZ_NOT_MPI); #endif #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); 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. */ AZ_read_update(&N_update, &update, proc_config, N_grid_pts, num_PDE_eqns, AZ_linear); 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(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 ); #ifndef VBR_VERSION 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]; #else total_blk_rows = N_update/num_PDE_eqns; total_blk_cols = total_blk_rows; blk_space = total_blk_rows*20; nz_space = blk_space*num_PDE_eqns*num_PDE_eqns; vbr_cnptr = (int *) ML_allocate(sizeof(int )*(total_blk_cols+1)); vbr_rnptr = (int *) ML_allocate(sizeof(int )*(total_blk_cols+1)); vbr_bnptr = (int *) ML_allocate(sizeof(int )*(total_blk_cols+2)); vbr_indx = (int *) ML_allocate(sizeof(int )*(blk_space+1)); vbr_bindx = (int *) ML_allocate(sizeof(int )*(blk_space+1)); vbr_val = (double *) ML_allocate(sizeof(double)*(nz_space+1)); for (i = 0; i <= total_blk_cols; i++) vbr_cnptr[i] = num_PDE_eqns; AZ_msr2vbr(vbr_val, vbr_indx, vbr_rnptr, vbr_cnptr, vbr_bnptr, vbr_bindx, bindx, val, total_blk_rows, total_blk_cols, blk_space, nz_space, -1); data_org[AZ_N_rows] = data_org[AZ_N_internal] + data_org[AZ_N_border]; data_org[AZ_N_int_blk] = data_org[AZ_N_internal]/num_PDE_eqns; data_org[AZ_N_bord_blk] = data_org[AZ_N_bord_blk]/num_PDE_eqns; data_org[AZ_N_ext_blk] = data_org[AZ_N_ext_blk]/num_PDE_eqns; data_org[AZ_matrix_type] = AZ_VBR_MATRIX; AZ_set_VBR(Amat, vbr_rnptr, vbr_cnptr, vbr_bnptr, vbr_indx, vbr_bindx, vbr_val, data_org, 0, NULL, AZ_LOCAL); Amat->matrix_type = data_org[AZ_matrix_type]; #endif start_time = AZ_second(); ML_Create(&ml, N_levels); ML_Set_PrintLevel(3); /* set up discretization matrix and matrix vector function */ AZ_ML_Set_Amat(ml, N_levels-1, N_update, N_update, Amat, proc_config); ML_Aggregate_Create( &ag ); ML_Aggregate_Set_Threshold(ag,0.0); ML_Set_SpectralNormScheme_PowerMethod(ml); /* To run SA: a) set damping factor to 1 and use power method ML_Aggregate_Set_DampingFactor(ag, 4./3.); To run NSA: a) set damping factor to 0 ML_Aggregate_Set_DampingFactor(ag, 0.); To run NSR a) set damping factor to 1 and use power method ML_Aggregate_Set_DampingFactor(ag, 1.); ag->Restriction_smoothagg_transpose = ML_FALSE; ag->keep_agg_information=1; ag->keep_P_tentative=1; b) hack code so it calls the energy minimizing restriction line 2973 of ml_agg_genP.c c) turn on the NSR flag in ml_agg_energy_min.cpp To run Emin a) set min_eneryg = 2 and keep_agg_info = 1; ag->minimizing_energy=2; ag->keep_agg_information=1; ag->cheap_minimizing_energy = 0; ag->block_scaled_SA = 1; */ ag->minimizing_energy=2; ag->keep_agg_information=1; ag->block_scaled_SA = 1; ML_Aggregate_Set_NullSpace(ag, num_PDE_eqns, num_PDE_eqns, NULL, N_update); ML_Aggregate_Set_MaxCoarseSize( ag, 20); /* ML_Aggregate_Set_RandomOrdering( ag ); ML_Aggregate_Set_DampingFactor(ag, .1); ag->drop_tol_for_smoothing = 1.0e-3; ML_Aggregate_Set_Threshold(ag, 1.0e-3); ML_Aggregate_Set_MaxCoarseSize( ag, 300); */ coarsest_level = ML_Gen_MultiLevelHierarchy_UsingAggregation(ml, N_levels-1, ML_DECREASING, ag); coarsest_level = N_levels - coarsest_level; if ( proc_config[AZ_node] == 0 ) printf("Coarse level = %d \n", coarsest_level); /* set up smoothers */ AZ_defaults(options, params); for (level = N_levels-1; level > coarsest_level; level--) { /* This is the Aztec domain decomp/ilu smoother that we */ /* usually use for this problem. */ /* options[AZ_precond] = AZ_dom_decomp; options[AZ_subdomain_solve] = AZ_ilut; params[AZ_ilut_fill] = 1.0; options[AZ_reorder] = 1; ML_Gen_SmootherAztec(ml, level, options, params, proc_config, status, AZ_ONLY_PRECONDITIONER, ML_PRESMOOTHER,NULL); */ /* 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); parasails_thresh /= 4.; */ /* This is the symmetric Gauss-Seidel smoothing. 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_SymGaussSeidel(ml,level,ML_PRESMOOTHER, nsmooth,1.); ML_Gen_Smoother_SymGaussSeidel(ml,level,ML_POSTSMOOTHER,nsmooth,1.); */ /* Block Gauss-Seidel with block size equal to #DOF per node. */ /* 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_BlockGaussSeidel(ml,level,ML_PRESMOOTHER, nsmooth,0.67, num_PDE_eqns); ML_Gen_Smoother_BlockGaussSeidel(ml,level,ML_POSTSMOOTHER, nsmooth, 0.67, num_PDE_eqns); */ ML_Gen_Smoother_SymBlockGaussSeidel(ml,level,ML_POSTSMOOTHER, 1, 1.0, num_PDE_eqns); } ML_Gen_CoarseSolverSuperLU( ml, coarsest_level); ML_Gen_Solver(ml, ML_MGW, N_levels-1, coarsest_level); AZ_defaults(options, params); options[AZ_solver] = AZ_gmres; options[AZ_scaling] = AZ_none; options[AZ_precond] = AZ_user_precond; /* options[AZ_conv] = AZ_r0; */ options[AZ_output] = 1; options[AZ_max_iter] = 1500; options[AZ_poly_ord] = 5; options[AZ_kspace] = 130; params[AZ_tol] = 1.0e-8; /* options[AZ_precond] = AZ_dom_decomp; options[AZ_subdomain_solve] = AZ_ilut; params[AZ_ilut_fill] = 2.0; */ AZ_set_ML_preconditioner(&Pmat, Amat, ml, options); setup_time = AZ_second() - start_time; xxx = (double *) malloc( leng*sizeof(double)); rhs=(double *)malloc(leng*sizeof(double)); for (iii = 0; iii < leng; iii++) xxx[iii] = 0.0; /* Set rhs */ fp = fopen("AZ_capture_rhs.mat","r"); if (fp == NULL) { if (proc_config[AZ_node] == 0) printf("taking random vector for rhs\n"); AZ_random_vector(rhs, data_org, proc_config); AZ_reorder_vec(rhs, data_org, update_index, NULL); } else { fclose(fp); ivec =(int *)malloc((leng+1)*sizeof(int)); AZ_input_msr_matrix("AZ_capture_rhs.mat", update, &rhs, &ivec, N_update, proc_config); free(ivec); AZ_reorder_vec(rhs, data_org, update_index, NULL); } /* Set x */ fp = fopen("AZ_capture_init_guess.mat","r"); if (fp != NULL) { fclose(fp); ivec =(int *)malloc((leng+1)*sizeof(int)); AZ_input_msr_matrix("AZ_capture_init_guess.mat",update, &xxx, &ivec, N_update, proc_config); free(ivec); 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); 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; }