HYPRE_Int hypre_BoomerAMGCycleT( void *amg_vdata, hypre_ParVector **F_array, hypre_ParVector **U_array ) { hypre_ParAMGData *amg_data = amg_vdata; /* Data Structure variables */ hypre_ParCSRMatrix **A_array; hypre_ParCSRMatrix **P_array; hypre_ParCSRMatrix **R_array; hypre_ParVector *Vtemp; HYPRE_Int **CF_marker_array; /* HYPRE_Int **unknown_map_array; */ /* HYPRE_Int **point_map_array; */ /* HYPRE_Int **v_at_point_array; */ HYPRE_Real cycle_op_count; HYPRE_Int cycle_type; HYPRE_Int num_levels; HYPRE_Int max_levels; HYPRE_Real *num_coeffs; HYPRE_Int *num_grid_sweeps; HYPRE_Int *grid_relax_type; HYPRE_Int **grid_relax_points; /* Local variables */ HYPRE_Int *lev_counter; HYPRE_Int Solve_err_flag; HYPRE_Int k; HYPRE_Int j; HYPRE_Int level; HYPRE_Int cycle_param; HYPRE_Int coarse_grid; HYPRE_Int fine_grid; HYPRE_Int Not_Finished; HYPRE_Int num_sweep; HYPRE_Int relax_type; HYPRE_Int relax_points; HYPRE_Real *relax_weight; HYPRE_Int relax_local; HYPRE_Int relax_order; HYPRE_Int old_version = 0; HYPRE_Real alpha; HYPRE_Real beta; #if 0 HYPRE_Real *D_mat; HYPRE_Real *S_vec; #endif /* Acquire data and allocate storage */ A_array = hypre_ParAMGDataAArray(amg_data); P_array = hypre_ParAMGDataPArray(amg_data); R_array = hypre_ParAMGDataRArray(amg_data); CF_marker_array = hypre_ParAMGDataCFMarkerArray(amg_data); /* unknown_map_array = hypre_ParAMGDataUnknownMapArray(amg_data); */ /* point_map_array = hypre_ParAMGDataPointMapArray(amg_data); */ /* v_at_point_array = hypre_ParAMGDataVatPointArray(amg_data); */ Vtemp = hypre_ParAMGDataVtemp(amg_data); num_levels = hypre_ParAMGDataNumLevels(amg_data); max_levels = hypre_ParAMGDataMaxLevels(amg_data); cycle_type = hypre_ParAMGDataCycleType(amg_data); /* num_unknowns = hypre_ParCSRMatrixNumRows(A_array[0]); */ num_grid_sweeps = hypre_ParAMGDataNumGridSweeps(amg_data); grid_relax_type = hypre_ParAMGDataGridRelaxType(amg_data); grid_relax_points = hypre_ParAMGDataGridRelaxPoints(amg_data); relax_weight = hypre_ParAMGDataRelaxWeight(amg_data); relax_order = hypre_ParAMGDataRelaxOrder(amg_data); cycle_op_count = hypre_ParAMGDataCycleOpCount(amg_data); lev_counter = hypre_CTAlloc(HYPRE_Int, num_levels); /* Initialize */ Solve_err_flag = 0; if (grid_relax_points) old_version = 1; num_coeffs = hypre_CTAlloc(HYPRE_Real, num_levels); num_coeffs[0] = hypre_ParCSRMatrixDNumNonzeros(A_array[0]); for (j = 1; j < num_levels; j++) num_coeffs[j] = hypre_ParCSRMatrixDNumNonzeros(A_array[j]); /*--------------------------------------------------------------------- * Initialize cycling control counter * * Cycling is controlled using a level counter: lev_counter[k] * * Each time relaxation is performed on level k, the * counter is decremented by 1. If the counter is then * negative, we go to the next finer level. If non- * negative, we go to the next coarser level. The * following actions control cycling: * * a. lev_counter[0] is initialized to 1. * b. lev_counter[k] is initialized to cycle_type for k>0. * * c. During cycling, when going down to level k, lev_counter[k] * is set to the max of (lev_counter[k],cycle_type) *---------------------------------------------------------------------*/ Not_Finished = 1; lev_counter[0] = 1; for (k = 1; k < num_levels; ++k) { lev_counter[k] = cycle_type; } level = 0; cycle_param = 0; /*--------------------------------------------------------------------- * Main loop of cycling *--------------------------------------------------------------------*/ while (Not_Finished) { num_sweep = num_grid_sweeps[cycle_param]; relax_type = grid_relax_type[cycle_param]; if (relax_type != 7 && relax_type != 9) relax_type = 7; /*------------------------------------------------------------------ * Do the relaxation num_sweep times *-----------------------------------------------------------------*/ for (j = 0; j < num_sweep; j++) { if (num_levels == 1 && max_levels > 1) { relax_points = 0; relax_local = 0; } else { if (old_version) relax_points = grid_relax_points[cycle_param][j]; relax_local = relax_order; } /*----------------------------------------------- * VERY sloppy approximation to cycle complexity *-----------------------------------------------*/ if (old_version && level < num_levels -1) { switch (relax_points) { case 1: cycle_op_count += num_coeffs[level+1]; break; case -1: cycle_op_count += (num_coeffs[level]-num_coeffs[level+1]); break; } } else { cycle_op_count += num_coeffs[level]; } /* note: this does not use relax_points, so it doesn't matter if its the "old version" */ Solve_err_flag = hypre_BoomerAMGRelaxT(A_array[level], F_array[level], CF_marker_array[level], relax_type, relax_points, relax_weight[level], U_array[level], Vtemp); if (Solve_err_flag != 0) { hypre_TFree(lev_counter); hypre_TFree(num_coeffs); return(Solve_err_flag); } } /*------------------------------------------------------------------ * Decrement the control counter and determine which grid to visit next *-----------------------------------------------------------------*/ --lev_counter[level]; if (lev_counter[level] >= 0 && level != num_levels-1) { /*--------------------------------------------------------------- * Visit coarser level next. Compute residual using hypre_ParCSRMatrixMatvec. * Use interpolation (since transpose i.e. P^TATR instead of * RAP) using hypre_ParCSRMatrixMatvecT. * Reset counters and cycling parameters for coarse level *--------------------------------------------------------------*/ fine_grid = level; coarse_grid = level + 1; hypre_ParVectorSetConstantValues(U_array[coarse_grid], 0.0); hypre_ParVectorCopy(F_array[fine_grid],Vtemp); alpha = -1.0; beta = 1.0; hypre_ParCSRMatrixMatvecT(alpha, A_array[fine_grid], U_array[fine_grid], beta, Vtemp); alpha = 1.0; beta = 0.0; hypre_ParCSRMatrixMatvecT(alpha,P_array[fine_grid],Vtemp, beta,F_array[coarse_grid]); ++level; lev_counter[level] = hypre_max(lev_counter[level],cycle_type); cycle_param = 1; if (level == num_levels-1) cycle_param = 3; } else if (level != 0) { /*--------------------------------------------------------------- * Visit finer level next. * Use restriction (since transpose i.e. P^TA^TR instead of RAP) * and add correction using hypre_ParCSRMatrixMatvec. * Reset counters and cycling parameters for finer level. *--------------------------------------------------------------*/ fine_grid = level - 1; coarse_grid = level; alpha = 1.0; beta = 1.0; hypre_ParCSRMatrixMatvec(alpha, R_array[fine_grid], U_array[coarse_grid], beta, U_array[fine_grid]); --level; cycle_param = 2; if (level == 0) cycle_param = 0; } else { Not_Finished = 0; } } hypre_ParAMGDataCycleOpCount(amg_data) = cycle_op_count; hypre_TFree(lev_counter); hypre_TFree(num_coeffs); return(Solve_err_flag); }
int hypre_BoomerAMGSetupStats( void *amg_vdata, hypre_ParCSRMatrix *A ) { MPI_Comm comm = hypre_ParCSRMatrixComm(A); hypre_ParAMGData *amg_data = (hypre_ParAMGData*)amg_vdata; /*hypre_SeqAMGData *seq_data = hypre_ParAMGDataSeqData(amg_data);*/ /* Data Structure variables */ hypre_ParCSRMatrix **A_array; hypre_ParCSRMatrix **P_array; hypre_CSRMatrix *A_diag; double *A_diag_data; int *A_diag_i; hypre_CSRMatrix *A_offd; double *A_offd_data; int *A_offd_i; hypre_CSRMatrix *P_diag; double *P_diag_data; int *P_diag_i; hypre_CSRMatrix *P_offd; double *P_offd_data; int *P_offd_i; int numrows; HYPRE_BigInt *row_starts; int num_levels; int coarsen_type; int interp_type; int measure_type; double global_nonzeros; double *send_buff; double *gather_buff; /* Local variables */ int level; int j; HYPRE_BigInt fine_size; int min_entries; int max_entries; int num_procs,my_id, num_threads; double min_rowsum; double max_rowsum; double sparse; int i; HYPRE_BigInt coarse_size; int entries; double avg_entries; double rowsum; double min_weight; double max_weight; int global_min_e; int global_max_e; double global_min_rsum; double global_max_rsum; double global_min_wt; double global_max_wt; double *num_coeffs; double *num_variables; double total_variables; double operat_cmplxty; double grid_cmplxty; /* amg solve params */ int max_iter; int cycle_type; int *num_grid_sweeps; int *grid_relax_type; int relax_order; int **grid_relax_points; double *relax_weight; double *omega; double tol; int one = 1; int minus_one = -1; int zero = 0; int smooth_type; int smooth_num_levels; int agg_num_levels; /*int seq_cg = 0;*/ /*if (seq_data) seq_cg = 1;*/ MPI_Comm_size(comm, &num_procs); MPI_Comm_rank(comm,&my_id); num_threads = hypre_NumThreads(); if (my_id == 0) printf("\nNumber of MPI processes: %d , Number of OpenMP threads: %d\n", num_procs, num_threads); A_array = hypre_ParAMGDataAArray(amg_data); P_array = hypre_ParAMGDataPArray(amg_data); num_levels = hypre_ParAMGDataNumLevels(amg_data); coarsen_type = hypre_ParAMGDataCoarsenType(amg_data); interp_type = hypre_ParAMGDataInterpType(amg_data); measure_type = hypre_ParAMGDataMeasureType(amg_data); smooth_type = hypre_ParAMGDataSmoothType(amg_data); smooth_num_levels = hypre_ParAMGDataSmoothNumLevels(amg_data); agg_num_levels = hypre_ParAMGDataAggNumLevels(amg_data); /*---------------------------------------------------------- * Get the amg_data data *----------------------------------------------------------*/ num_levels = hypre_ParAMGDataNumLevels(amg_data); max_iter = hypre_ParAMGDataMaxIter(amg_data); cycle_type = hypre_ParAMGDataCycleType(amg_data); num_grid_sweeps = hypre_ParAMGDataNumGridSweeps(amg_data); grid_relax_type = hypre_ParAMGDataGridRelaxType(amg_data); grid_relax_points = hypre_ParAMGDataGridRelaxPoints(amg_data); relax_weight = hypre_ParAMGDataRelaxWeight(amg_data); relax_order = hypre_ParAMGDataRelaxOrder(amg_data); omega = hypre_ParAMGDataOmega(amg_data); tol = hypre_ParAMGDataTol(amg_data); /*block_mode = hypre_ParAMGDataBlockMode(amg_data);*/ send_buff = hypre_CTAlloc(double, 6); #ifdef HYPRE_NO_GLOBAL_PARTITION gather_buff = hypre_CTAlloc(double,6); #else gather_buff = hypre_CTAlloc(double,6*num_procs); #endif if (my_id==0) { printf("\nBoomerAMG SETUP PARAMETERS:\n\n"); printf(" Max levels = %d\n",hypre_ParAMGDataMaxLevels(amg_data)); printf(" Num levels = %d\n\n",num_levels); printf(" Strength Threshold = %f\n", hypre_ParAMGDataStrongThreshold(amg_data)); printf(" Interpolation Truncation Factor = %f\n", hypre_ParAMGDataTruncFactor(amg_data)); printf(" Maximum Row Sum Threshold for Dependency Weakening = %f\n\n", hypre_ParAMGDataMaxRowSum(amg_data)); if (coarsen_type == 0) { printf(" Coarsening Type = Cleary-Luby-Jones-Plassman\n"); } else if (abs(coarsen_type) == 1) { printf(" Coarsening Type = Ruge\n"); } else if (abs(coarsen_type) == 2) { printf(" Coarsening Type = Ruge2B\n"); } else if (abs(coarsen_type) == 3) { printf(" Coarsening Type = Ruge3\n"); } else if (abs(coarsen_type) == 4) { printf(" Coarsening Type = Ruge 3c \n"); } else if (abs(coarsen_type) == 5) { printf(" Coarsening Type = Ruge relax special points \n"); } else if (abs(coarsen_type) == 6) { printf(" Coarsening Type = Falgout-CLJP \n"); } else if (abs(coarsen_type) == 8) { printf(" Coarsening Type = PMIS \n"); } else if (abs(coarsen_type) == 10) { printf(" Coarsening Type = HMIS \n"); } else if (abs(coarsen_type) == 11) { printf(" Coarsening Type = Ruge 1st pass only \n"); } else if (abs(coarsen_type) == 9) { printf(" Coarsening Type = PMIS fixed random \n"); } else if (abs(coarsen_type) == 7) { printf(" Coarsening Type = CLJP, fixed random \n"); } if (coarsen_type > 0) { printf(" Hybrid Coarsening (switch to CLJP when coarsening slows)\n"); } if (coarsen_type) printf(" measures are determined %s\n\n", (measure_type ? "globally" : "locally")); if (agg_num_levels) printf(" no. of levels of aggressive coarsening: %d\n\n", agg_num_levels); #ifdef HYPRE_NO_GLOBAL_PARTITION printf( "\n No global partition option chosen.\n\n"); #endif if (interp_type == 0) { printf(" Interpolation = modified classical interpolation\n"); } else if (interp_type == 1) { printf(" Interpolation = LS interpolation \n"); } else if (interp_type == 2) { printf(" Interpolation = modified classical interpolation for hyperbolic PDEs\n"); } else if (interp_type == 3) { printf(" Interpolation = direct interpolation with separation of weights\n"); } else if (interp_type == 4) { printf(" Interpolation = multipass interpolation\n"); } else if (interp_type == 5) { printf(" Interpolation = multipass interpolation with separation of weights\n"); } else if (interp_type == 6) { printf(" Interpolation = extended+i interpolation\n"); } else if (interp_type == 7) { printf(" Interpolation = extended+i interpolation (only when needed)\n"); } else if (interp_type == 8) { printf(" Interpolation = standard interpolation\n"); } else if (interp_type == 9) { printf(" Interpolation = standard interpolation with separation of weights\n"); } else if (interp_type == 12) { printf(" FF interpolation \n"); } else if (interp_type == 13) { printf(" FF1 interpolation \n"); } { printf( "\nOperator Matrix Information:\n\n"); } #if HYPRE_LONG_LONG printf(" nonzero entries p"); printf("er row row sums\n"); printf("lev rows entries sparse min max "); printf("avg min max\n"); printf("======================================="); printf("==================================\n"); #else printf(" nonzero entries p"); printf("er row row sums\n"); printf("lev rows entries sparse min max "); printf("avg min max\n"); printf("======================================="); printf("============================\n"); #endif } /*----------------------------------------------------- * Enter Statistics Loop *-----------------------------------------------------*/ num_coeffs = hypre_CTAlloc(double,num_levels); num_variables = hypre_CTAlloc(double,num_levels); for (level = 0; level < num_levels; level++) { { A_diag = hypre_ParCSRMatrixDiag(A_array[level]); A_diag_data = hypre_CSRMatrixData(A_diag); A_diag_i = hypre_CSRMatrixI(A_diag); A_offd = hypre_ParCSRMatrixOffd(A_array[level]); A_offd_data = hypre_CSRMatrixData(A_offd); A_offd_i = hypre_CSRMatrixI(A_offd); row_starts = hypre_ParCSRMatrixRowStarts(A_array[level]); fine_size = hypre_ParCSRMatrixGlobalNumRows(A_array[level]); global_nonzeros = hypre_ParCSRMatrixDNumNonzeros(A_array[level]); num_coeffs[level] = global_nonzeros; num_variables[level] = (double) fine_size; sparse = global_nonzeros /((double) fine_size * (double) fine_size); min_entries = 0; max_entries = 0; min_rowsum = 0.0; max_rowsum = 0.0; if (hypre_CSRMatrixNumRows(A_diag)) { min_entries = (A_diag_i[1]-A_diag_i[0])+(A_offd_i[1]-A_offd_i[0]); for (j = A_diag_i[0]; j < A_diag_i[1]; j++) min_rowsum += A_diag_data[j]; for (j = A_offd_i[0]; j < A_offd_i[1]; j++) min_rowsum += A_offd_data[j]; max_rowsum = min_rowsum; for (j = 0; j < hypre_CSRMatrixNumRows(A_diag); j++) { entries = (A_diag_i[j+1]-A_diag_i[j])+(A_offd_i[j+1]-A_offd_i[j]); min_entries = hypre_min(entries, min_entries); max_entries = hypre_max(entries, max_entries); rowsum = 0.0; for (i = A_diag_i[j]; i < A_diag_i[j+1]; i++) rowsum += A_diag_data[i]; for (i = A_offd_i[j]; i < A_offd_i[j+1]; i++) rowsum += A_offd_data[i]; min_rowsum = hypre_min(rowsum, min_rowsum); max_rowsum = hypre_max(rowsum, max_rowsum); } } avg_entries = global_nonzeros / ((double) fine_size); } #ifdef HYPRE_NO_GLOBAL_PARTITION numrows = (int)(row_starts[1]-row_starts[0]); if (!numrows) /* if we don't have any rows, then don't have this count toward min row sum or min num entries */ { min_entries = 1000000; min_rowsum = 1.0e7; } send_buff[0] = - (double) min_entries; send_buff[1] = (double) max_entries; send_buff[2] = - min_rowsum; send_buff[3] = max_rowsum; MPI_Reduce(send_buff, gather_buff, 4, MPI_DOUBLE, MPI_MAX, 0, comm); if (my_id ==0) { global_min_e = - gather_buff[0]; global_max_e = gather_buff[1]; global_min_rsum = - gather_buff[2]; global_max_rsum = gather_buff[3]; #ifdef HYPRE_LONG_LONG printf( "%2d %12lld %8.0f %0.3f %4d %4d", level, fine_size, global_nonzeros, sparse, global_min_e, global_max_e); #else printf( "%2d %7d %8.0f %0.3f %4d %4d", level, fine_size, global_nonzeros, sparse, global_min_e, global_max_e); #endif printf(" %4.1f %10.3e %10.3e\n", avg_entries, global_min_rsum, global_max_rsum); } #else send_buff[0] = (double) min_entries; send_buff[1] = (double) max_entries; send_buff[2] = min_rowsum; send_buff[3] = max_rowsum; MPI_Gather(send_buff,4,MPI_DOUBLE,gather_buff,4,MPI_DOUBLE,0,comm); if (my_id == 0) { global_min_e = 1000000; global_max_e = 0; global_min_rsum = 1.0e7; global_max_rsum = 0.0; for (j = 0; j < num_procs; j++) { numrows = row_starts[j+1]-row_starts[j]; if (numrows) { global_min_e = hypre_min(global_min_e, (int) gather_buff[j*4]); global_min_rsum = hypre_min(global_min_rsum, gather_buff[j*4 +2]); } global_max_e = hypre_max(global_max_e, (int) gather_buff[j*4 +1]); global_max_rsum = hypre_max(global_max_rsum, gather_buff[j*4 +3]); } #ifdef HYPRE_LONG_LONG printf( "%2d %12lld %8.0f %0.3f %4d %4d", level, fine_size, global_nonzeros, sparse, global_min_e, global_max_e); #else printf( "%2d %7d %8.0f %0.3f %4d %4d", level, fine_size, global_nonzeros, sparse, global_min_e, global_max_e); #endif printf(" %4.1f %10.3e %10.3e\n", avg_entries, global_min_rsum, global_max_rsum); } #endif } if (my_id == 0) { { printf( "\n\nInterpolation Matrix Information:\n\n"); } #if HYPRE_LONG_LONG printf(" entries/row min max"); printf(" row sums\n"); printf("lev rows x cols min max "); printf(" weight weight min max \n"); printf("======================================="); printf("======================================\n"); #else printf(" entries/row min max"); printf(" row sums\n"); printf("lev rows cols min max "); printf(" weight weight min max \n"); printf("======================================="); printf("==========================\n"); #endif } /*----------------------------------------------------- * Enter Statistics Loop *-----------------------------------------------------*/ for (level = 0; level < num_levels-1; level++) { { P_diag = hypre_ParCSRMatrixDiag(P_array[level]); P_diag_data = hypre_CSRMatrixData(P_diag); P_diag_i = hypre_CSRMatrixI(P_diag); P_offd = hypre_ParCSRMatrixOffd(P_array[level]); P_offd_data = hypre_CSRMatrixData(P_offd); P_offd_i = hypre_CSRMatrixI(P_offd); row_starts = hypre_ParCSRMatrixRowStarts(P_array[level]); fine_size = hypre_ParCSRMatrixGlobalNumRows(P_array[level]); coarse_size = hypre_ParCSRMatrixGlobalNumCols(P_array[level]); global_nonzeros = hypre_ParCSRMatrixNumNonzeros(P_array[level]); min_weight = 1.0; max_weight = 0.0; max_rowsum = 0.0; min_rowsum = 0.0; min_entries = 0; max_entries = 0; if (hypre_CSRMatrixNumRows(P_diag)) { if (hypre_CSRMatrixNumCols(P_diag)) min_weight = P_diag_data[0]; for (j = P_diag_i[0]; j < P_diag_i[1]; j++) { min_weight = hypre_min(min_weight, P_diag_data[j]); if (P_diag_data[j] != 1.0) max_weight = hypre_max(max_weight, P_diag_data[j]); min_rowsum += P_diag_data[j]; } for (j = P_offd_i[0]; j < P_offd_i[1]; j++) { min_weight = hypre_min(min_weight, P_offd_data[j]); if (P_offd_data[j] != 1.0) max_weight = hypre_max(max_weight, P_offd_data[j]); min_rowsum += P_offd_data[j]; } max_rowsum = min_rowsum; min_entries = (P_diag_i[1]-P_diag_i[0])+(P_offd_i[1]-P_offd_i[0]); max_entries = 0; for (j = 0; j < hypre_CSRMatrixNumRows(P_diag); j++) { entries = (P_diag_i[j+1]-P_diag_i[j])+(P_offd_i[j+1]-P_offd_i[j]); min_entries = hypre_min(entries, min_entries); max_entries = hypre_max(entries, max_entries); rowsum = 0.0; for (i = P_diag_i[j]; i < P_diag_i[j+1]; i++) { min_weight = hypre_min(min_weight, P_diag_data[i]); if (P_diag_data[i] != 1.0) max_weight = hypre_max(max_weight, P_diag_data[i]); rowsum += P_diag_data[i]; } for (i = P_offd_i[j]; i < P_offd_i[j+1]; i++) { min_weight = hypre_min(min_weight, P_offd_data[i]); if (P_offd_data[i] != 1.0) max_weight = hypre_max(max_weight, P_offd_data[i]); rowsum += P_offd_data[i]; } min_rowsum = hypre_min(rowsum, min_rowsum); max_rowsum = hypre_max(rowsum, max_rowsum); } } avg_entries = ((double) global_nonzeros) / ((double) fine_size); } #ifdef HYPRE_NO_GLOBAL_PARTITION numrows = (int)(row_starts[1]-row_starts[0]); if (!numrows) /* if we don't have any rows, then don't have this count toward min row sum or min num entries */ { min_entries = 1000000; min_rowsum = 1.0e7; min_weight = 1.0e7; } send_buff[0] = - (double) min_entries; send_buff[1] = (double) max_entries; send_buff[2] = - min_rowsum; send_buff[3] = max_rowsum; send_buff[4] = - min_weight; send_buff[5] = max_weight; MPI_Reduce(send_buff, gather_buff, 6, MPI_DOUBLE, MPI_MAX, 0, comm); if (my_id == 0) { global_min_e = - gather_buff[0]; global_max_e = gather_buff[1]; global_min_rsum = -gather_buff[2]; global_max_rsum = gather_buff[3]; global_min_wt = -gather_buff[4]; global_max_wt = gather_buff[5]; #ifdef HYPRE_LONG_LONG printf( "%2d %12lld x %-12lld %3d %3d", level, fine_size, coarse_size, global_min_e, global_max_e); #else printf( "%2d %5d x %-5d %3d %3d", level, fine_size, coarse_size, global_min_e, global_max_e); #endif printf(" %10.3e %9.3e %9.3e %9.3e\n", global_min_wt, global_max_wt, global_min_rsum, global_max_rsum); } #else send_buff[0] = (double) min_entries; send_buff[1] = (double) max_entries; send_buff[2] = min_rowsum; send_buff[3] = max_rowsum; send_buff[4] = min_weight; send_buff[5] = max_weight; MPI_Gather(send_buff,6,MPI_DOUBLE,gather_buff,6,MPI_DOUBLE,0,comm); if (my_id == 0) { global_min_e = 1000000; global_max_e = 0; global_min_rsum = 1.0e7; global_max_rsum = 0.0; global_min_wt = 1.0e7; global_max_wt = 0.0; for (j = 0; j < num_procs; j++) { numrows = row_starts[j+1] - row_starts[j]; if (numrows) { global_min_e = hypre_min(global_min_e, (int) gather_buff[j*6]); global_min_rsum = hypre_min(global_min_rsum, gather_buff[j*6+2]); global_min_wt = hypre_min(global_min_wt, gather_buff[j*6+4]); } global_max_e = hypre_max(global_max_e, (int) gather_buff[j*6+1]); global_max_rsum = hypre_max(global_max_rsum, gather_buff[j*6+3]); global_max_wt = hypre_max(global_max_wt, gather_buff[j*6+5]); } #ifdef HYPRE_LONG_LONG printf( "%2d %12lld x %-12lld %3d %3d", level, fine_size, coarse_size, global_min_e, global_max_e); #else printf( "%2d %5d x %-5d %3d %3d", level, fine_size, coarse_size, global_min_e, global_max_e); #endif printf(" %10.3e %9.3e %9.3e %9.3e\n", global_min_wt, global_max_wt, global_min_rsum, global_max_rsum); } #endif } total_variables = 0; operat_cmplxty = 0; for (j=0;j<hypre_ParAMGDataNumLevels(amg_data);j++) { operat_cmplxty += num_coeffs[j] / num_coeffs[0]; total_variables += num_variables[j]; } if (num_variables[0] != 0) grid_cmplxty = total_variables / num_variables[0]; if (my_id == 0 ) { printf("\n\n Complexity: grid = %f\n",grid_cmplxty); printf(" operator = %f\n",operat_cmplxty); } if (my_id == 0) printf("\n\n"); if (my_id == 0) { printf("\n\nBoomerAMG SOLVER PARAMETERS:\n\n"); printf( " Maximum number of cycles: %d \n",max_iter); printf( " Stopping Tolerance: %e \n",tol); printf( " Cycle type (1 = V, 2 = W, etc.): %d\n\n", cycle_type); printf( " Relaxation Parameters:\n"); printf( " Visiting Grid: down up coarse\n"); printf( " Number of partial sweeps: %4d %2d %4d \n", num_grid_sweeps[1], num_grid_sweeps[2],num_grid_sweeps[3]); printf( " Type 0=Jac, 3=hGS, 6=hSGS, 9=GE: %4d %2d %4d \n", grid_relax_type[1], grid_relax_type[2],grid_relax_type[3]); #if 1 /* TO DO: may not want this to print if CG in the coarse grid */ printf( " Point types, partial sweeps (1=C, -1=F):\n"); if (grid_relax_points) { printf( " Pre-CG relaxation (down):"); for (j = 0; j < num_grid_sweeps[1]; j++) printf(" %2d", grid_relax_points[1][j]); printf( "\n"); printf( " Post-CG relaxation (up):"); for (j = 0; j < num_grid_sweeps[2]; j++) printf(" %2d", grid_relax_points[2][j]); printf( "\n"); printf( " Coarsest grid:"); for (j = 0; j < num_grid_sweeps[3]; j++) printf(" %2d", grid_relax_points[3][j]); printf( "\n\n"); } else if (relax_order == 1) { printf( " Pre-CG relaxation (down):"); for (j = 0; j < num_grid_sweeps[1]; j++) printf(" %2d %2d", one, minus_one); printf( "\n"); printf( " Post-CG relaxation (up):"); for (j = 0; j < num_grid_sweeps[2]; j++) printf(" %2d %2d", minus_one, one); printf( "\n"); printf( " Coarsest grid:"); for (j = 0; j < num_grid_sweeps[3]; j++) printf(" %2d", zero); printf( "\n\n"); } else { printf( " Pre-CG relaxation (down):"); for (j = 0; j < num_grid_sweeps[1]; j++) printf(" %2d", zero); printf( "\n"); printf( " Post-CG relaxation (up):"); for (j = 0; j < num_grid_sweeps[2]; j++) printf(" %2d", zero); printf( "\n"); printf( " Coarsest grid:"); for (j = 0; j < num_grid_sweeps[3]; j++) printf(" %2d", zero); printf( "\n\n"); } #endif if (smooth_type == 6) for (j=0; j < smooth_num_levels; j++) printf( " Schwarz Relaxation Weight %f level %d\n", hypre_ParAMGDataSchwarzRlxWeight(amg_data),j); for (j=0; j < num_levels; j++) if (relax_weight[j] != 1) printf( " Relaxation Weight %f level %d\n",relax_weight[j],j); for (j=0; j < num_levels; j++) if (omega[j] != 1) printf( " Outer relaxation weight %f level %d\n",omega[j],j); } /*if (seq_cg) { hypre_seqAMGSetupStats(amg_data,num_coeffs[0],num_variables[0], operat_cmplxty, grid_cmplxty ); }*/ hypre_TFree(num_coeffs); hypre_TFree(num_variables); hypre_TFree(send_buff); hypre_TFree(gather_buff); return(0); }
int hypre_BoomerAMGWriteSolverParams(void* data) { hypre_ParAMGData *amg_data = (hypre_ParAMGData*)data; /* amg solve params */ int num_levels; int max_iter; int cycle_type; int *num_grid_sweeps; int *grid_relax_type; int **grid_relax_points; int relax_order; double *relax_weight; double *omega; double tol; int smooth_type; int smooth_num_levels; /* amg output params */ int amg_print_level; int j; int one = 1; int minus_one = -1; int zero = 0; /*---------------------------------------------------------- * Get the amg_data data *----------------------------------------------------------*/ num_levels = hypre_ParAMGDataNumLevels(amg_data); max_iter = hypre_ParAMGDataMaxIter(amg_data); cycle_type = hypre_ParAMGDataCycleType(amg_data); num_grid_sweeps = hypre_ParAMGDataNumGridSweeps(amg_data); grid_relax_type = hypre_ParAMGDataGridRelaxType(amg_data); grid_relax_points = hypre_ParAMGDataGridRelaxPoints(amg_data); relax_order = hypre_ParAMGDataRelaxOrder(amg_data); relax_weight = hypre_ParAMGDataRelaxWeight(amg_data); omega = hypre_ParAMGDataOmega(amg_data); smooth_type = hypre_ParAMGDataSmoothType(amg_data); smooth_num_levels = hypre_ParAMGDataSmoothNumLevels(amg_data); tol = hypre_ParAMGDataTol(amg_data); amg_print_level = hypre_ParAMGDataPrintLevel(amg_data); /*---------------------------------------------------------- * AMG info *----------------------------------------------------------*/ if (amg_print_level == 1 || amg_print_level == 3) { printf("\n\nBoomerAMG SOLVER PARAMETERS:\n\n"); printf( " Maximum number of cycles: %d \n",max_iter); printf( " Stopping Tolerance: %e \n",tol); printf( " Cycle type (1 = V, 2 = W, etc.): %d\n\n", cycle_type); printf( " Relaxation Parameters:\n"); printf( " Visiting Grid: down up coarse\n"); printf( " Visiting Grid: down up coarse\n"); printf( " Number of partial sweeps: %4d %2d %4d \n", num_grid_sweeps[1], num_grid_sweeps[2],num_grid_sweeps[3]); printf( " Type 0=Jac, 3=hGS, 6=hSGS, 9=GE: %4d %2d %4d \n", grid_relax_type[1], grid_relax_type[2],grid_relax_type[3]); printf( " Point types, partial sweeps (1=C, -1=F):\n"); if (grid_relax_points) { printf( " Pre-CG relaxation (down):"); for (j = 0; j < num_grid_sweeps[1]; j++) printf(" %2d", grid_relax_points[1][j]); printf( "\n"); printf( " Post-CG relaxation (up):"); for (j = 0; j < num_grid_sweeps[2]; j++) printf(" %2d", grid_relax_points[2][j]); printf( "\n"); printf( " Coarsest grid:"); for (j = 0; j < num_grid_sweeps[3]; j++) printf(" %2d", grid_relax_points[3][j]); printf( "\n\n"); } else if (relax_order == 1) { printf( " Pre-CG relaxation (down):"); for (j = 0; j < num_grid_sweeps[1]; j++) printf(" %2d %2d", one, minus_one); printf( "\n"); printf( " Post-CG relaxation (up):"); for (j = 0; j < num_grid_sweeps[2]; j++) printf(" %2d %2d", minus_one, one); printf( "\n"); printf( " Coarsest grid:"); for (j = 0; j < num_grid_sweeps[3]; j++) printf(" %2d", zero); printf( "\n\n"); } else { printf( " Pre-CG relaxation (down):"); for (j = 0; j < num_grid_sweeps[1]; j++) printf(" %2d", zero); printf( "\n"); printf( " Post-CG relaxation (up):"); for (j = 0; j < num_grid_sweeps[2]; j++) printf(" %2d", zero); printf( "\n"); printf( " Coarsest grid:"); for (j = 0; j < num_grid_sweeps[3]; j++) printf(" %2d", zero); printf( "\n\n"); } if (smooth_type == 6) for (j=0; j < smooth_num_levels; j++) printf( " Schwarz Relaxation Weight %f level %d\n", hypre_ParAMGDataSchwarzRlxWeight(amg_data),j); for (j=0; j < num_levels; j++) if (relax_weight[j] != 1) printf( " Relaxation Weight %f level %d\n",relax_weight[j],j); for (j=0; j < num_levels; j++) if (omega[j] != 1) printf( " Outer relaxation weight %f level %d\n",omega[j],j); printf( " Output flag (print_level): %d \n", amg_print_level); } return 0; }
HYPRE_Int hypre_BoomerAMGCycle( void *amg_vdata, hypre_ParVector **F_array, hypre_ParVector **U_array ) { hypre_ParAMGData *amg_data = amg_vdata; HYPRE_Solver *smoother; /* Data Structure variables */ hypre_ParCSRMatrix **A_array; hypre_ParCSRMatrix **P_array; hypre_ParCSRMatrix **R_array; hypre_ParVector *Utemp; hypre_ParVector *Vtemp; hypre_ParVector *Rtemp; hypre_ParVector *Ptemp; hypre_ParVector *Ztemp; hypre_ParVector *Aux_U; hypre_ParVector *Aux_F; hypre_ParCSRBlockMatrix **A_block_array; hypre_ParCSRBlockMatrix **P_block_array; hypre_ParCSRBlockMatrix **R_block_array; HYPRE_Real *Ztemp_data; HYPRE_Real *Ptemp_data; HYPRE_Int **CF_marker_array; /* HYPRE_Int **unknown_map_array; HYPRE_Int **point_map_array; HYPRE_Int **v_at_point_array; */ HYPRE_Real cycle_op_count; HYPRE_Int cycle_type; HYPRE_Int num_levels; HYPRE_Int max_levels; HYPRE_Real *num_coeffs; HYPRE_Int *num_grid_sweeps; HYPRE_Int *grid_relax_type; HYPRE_Int **grid_relax_points; HYPRE_Int block_mode; HYPRE_Real *max_eig_est; HYPRE_Real *min_eig_est; HYPRE_Int cheby_order; HYPRE_Real cheby_fraction; /* Local variables */ HYPRE_Int *lev_counter; HYPRE_Int Solve_err_flag; HYPRE_Int k; HYPRE_Int i, j, jj; HYPRE_Int level; HYPRE_Int cycle_param; HYPRE_Int coarse_grid; HYPRE_Int fine_grid; HYPRE_Int Not_Finished; HYPRE_Int num_sweep; HYPRE_Int cg_num_sweep = 1; HYPRE_Int relax_type; HYPRE_Int relax_points; HYPRE_Int relax_order; HYPRE_Int relax_local; HYPRE_Int old_version = 0; HYPRE_Real *relax_weight; HYPRE_Real *omega; HYPRE_Real alfa, beta, gammaold; HYPRE_Real gamma = 1.0; HYPRE_Int local_size; /* HYPRE_Int *smooth_option; */ HYPRE_Int smooth_type; HYPRE_Int smooth_num_levels; HYPRE_Int num_threads, my_id; HYPRE_Real alpha; HYPRE_Real **l1_norms = NULL; HYPRE_Real *l1_norms_level; HYPRE_Int seq_cg = 0; MPI_Comm comm; #if 0 HYPRE_Real *D_mat; HYPRE_Real *S_vec; #endif /* Acquire data and allocate storage */ num_threads = hypre_NumThreads(); A_array = hypre_ParAMGDataAArray(amg_data); P_array = hypre_ParAMGDataPArray(amg_data); R_array = hypre_ParAMGDataRArray(amg_data); CF_marker_array = hypre_ParAMGDataCFMarkerArray(amg_data); Vtemp = hypre_ParAMGDataVtemp(amg_data); Rtemp = hypre_ParAMGDataRtemp(amg_data); Ptemp = hypre_ParAMGDataPtemp(amg_data); Ztemp = hypre_ParAMGDataZtemp(amg_data); num_levels = hypre_ParAMGDataNumLevels(amg_data); max_levels = hypre_ParAMGDataMaxLevels(amg_data); cycle_type = hypre_ParAMGDataCycleType(amg_data); A_block_array = hypre_ParAMGDataABlockArray(amg_data); P_block_array = hypre_ParAMGDataPBlockArray(amg_data); R_block_array = hypre_ParAMGDataRBlockArray(amg_data); block_mode = hypre_ParAMGDataBlockMode(amg_data); num_grid_sweeps = hypre_ParAMGDataNumGridSweeps(amg_data); grid_relax_type = hypre_ParAMGDataGridRelaxType(amg_data); grid_relax_points = hypre_ParAMGDataGridRelaxPoints(amg_data); relax_order = hypre_ParAMGDataRelaxOrder(amg_data); relax_weight = hypre_ParAMGDataRelaxWeight(amg_data); omega = hypre_ParAMGDataOmega(amg_data); smooth_type = hypre_ParAMGDataSmoothType(amg_data); smooth_num_levels = hypre_ParAMGDataSmoothNumLevels(amg_data); l1_norms = hypre_ParAMGDataL1Norms(amg_data); /* smooth_option = hypre_ParAMGDataSmoothOption(amg_data); */ max_eig_est = hypre_ParAMGDataMaxEigEst(amg_data); min_eig_est = hypre_ParAMGDataMinEigEst(amg_data); cheby_order = hypre_ParAMGDataChebyOrder(amg_data); cheby_fraction = hypre_ParAMGDataChebyFraction(amg_data); cycle_op_count = hypre_ParAMGDataCycleOpCount(amg_data); lev_counter = hypre_CTAlloc(HYPRE_Int, num_levels); if (hypre_ParAMGDataParticipate(amg_data)) seq_cg = 1; /* Initialize */ Solve_err_flag = 0; if (grid_relax_points) old_version = 1; num_coeffs = hypre_CTAlloc(HYPRE_Real, num_levels); num_coeffs[0] = hypre_ParCSRMatrixDNumNonzeros(A_array[0]); comm = hypre_ParCSRMatrixComm(A_array[0]); hypre_MPI_Comm_rank(comm,&my_id); if (block_mode) { for (j = 1; j < num_levels; j++) num_coeffs[j] = hypre_ParCSRBlockMatrixNumNonzeros(A_block_array[j]); } else { for (j = 1; j < num_levels; j++) num_coeffs[j] = hypre_ParCSRMatrixDNumNonzeros(A_array[j]); } /*--------------------------------------------------------------------- * Initialize cycling control counter * * Cycling is controlled using a level counter: lev_counter[k] * * Each time relaxation is performed on level k, the * counter is decremented by 1. If the counter is then * negative, we go to the next finer level. If non- * negative, we go to the next coarser level. The * following actions control cycling: * * a. lev_counter[0] is initialized to 1. * b. lev_counter[k] is initialized to cycle_type for k>0. * * c. During cycling, when going down to level k, lev_counter[k] * is set to the max of (lev_counter[k],cycle_type) *---------------------------------------------------------------------*/ Not_Finished = 1; lev_counter[0] = 1; for (k = 1; k < num_levels; ++k) { lev_counter[k] = cycle_type; } level = 0; cycle_param = 1; smoother = hypre_ParAMGDataSmoother(amg_data); if (smooth_num_levels > 0) { if (smooth_type == 7 || smooth_type == 8 || smooth_type == 17 || smooth_type == 18 || smooth_type == 9 || smooth_type == 19) { HYPRE_Int actual_local_size = hypre_ParVectorActualLocalSize(Vtemp); Utemp = hypre_ParVectorCreate(comm,hypre_ParVectorGlobalSize(Vtemp), hypre_ParVectorPartitioning(Vtemp)); hypre_ParVectorOwnsPartitioning(Utemp) = 0; local_size = hypre_VectorSize(hypre_ParVectorLocalVector(Vtemp)); if (local_size < actual_local_size) { hypre_VectorData(hypre_ParVectorLocalVector(Utemp)) = hypre_CTAlloc(HYPRE_Complex, actual_local_size); hypre_ParVectorActualLocalSize(Utemp) = actual_local_size; } else hypre_ParVectorInitialize(Utemp); } } /*--------------------------------------------------------------------- * Main loop of cycling *--------------------------------------------------------------------*/ while (Not_Finished) { if (num_levels > 1) { local_size = hypre_VectorSize(hypre_ParVectorLocalVector(F_array[level])); hypre_VectorSize(hypre_ParVectorLocalVector(Vtemp)) = local_size; if (smooth_num_levels <= level) { cg_num_sweep = 1; num_sweep = num_grid_sweeps[cycle_param]; Aux_U = U_array[level]; Aux_F = F_array[level]; } else if (smooth_type > 9) { hypre_VectorSize(hypre_ParVectorLocalVector(Ztemp)) = local_size; hypre_VectorSize(hypre_ParVectorLocalVector(Rtemp)) = local_size; hypre_VectorSize(hypre_ParVectorLocalVector(Ptemp)) = local_size; Ztemp_data = hypre_VectorData(hypre_ParVectorLocalVector(Ztemp)); Ptemp_data = hypre_VectorData(hypre_ParVectorLocalVector(Ptemp)); hypre_ParVectorSetConstantValues(Ztemp,0); alpha = -1.0; beta = 1.0; hypre_ParCSRMatrixMatvecOutOfPlace(alpha, A_array[level], U_array[level], beta, F_array[level], Rtemp); cg_num_sweep = hypre_ParAMGDataSmoothNumSweeps(amg_data); num_sweep = num_grid_sweeps[cycle_param]; Aux_U = Ztemp; Aux_F = Rtemp; } else { cg_num_sweep = 1; num_sweep = hypre_ParAMGDataSmoothNumSweeps(amg_data); Aux_U = U_array[level]; Aux_F = F_array[level]; } relax_type = grid_relax_type[cycle_param]; } else /* AB: 4/08: removed the max_levels > 1 check - should do this when max-levels = 1 also */ { /* If no coarsening occurred, apply a simple smoother once */ Aux_U = U_array[level]; Aux_F = F_array[level]; num_sweep = 1; /* TK: Use the user relax type (instead of 0) to allow for setting a convergent smoother (e.g. in the solution of singular problems). */ relax_type = hypre_ParAMGDataUserRelaxType(amg_data); } if (l1_norms != NULL) l1_norms_level = l1_norms[level]; else l1_norms_level = NULL; if (cycle_param == 3 && seq_cg) { hypre_seqAMGCycle(amg_data, level, F_array, U_array); } else { /*------------------------------------------------------------------ * Do the relaxation num_sweep times *-----------------------------------------------------------------*/ for (jj = 0; jj < cg_num_sweep; jj++) { if (smooth_num_levels > level && smooth_type > 9) hypre_ParVectorSetConstantValues(Aux_U,0); for (j = 0; j < num_sweep; j++) { if (num_levels == 1 && max_levels > 1) { relax_points = 0; relax_local = 0; } else { if (old_version) relax_points = grid_relax_points[cycle_param][j]; relax_local = relax_order; } /*----------------------------------------------- * VERY sloppy approximation to cycle complexity *-----------------------------------------------*/ if (old_version && level < num_levels -1) { switch (relax_points) { case 1: cycle_op_count += num_coeffs[level+1]; break; case -1: cycle_op_count += (num_coeffs[level]-num_coeffs[level+1]); break; } } else { cycle_op_count += num_coeffs[level]; } /*----------------------------------------------- Choose Smoother -----------------------------------------------*/ if (smooth_num_levels > level && (smooth_type == 7 || smooth_type == 8 || smooth_type == 9 || smooth_type == 19 || smooth_type == 17 || smooth_type == 18)) { hypre_VectorSize(hypre_ParVectorLocalVector(Utemp)) = local_size; alpha = -1.0; beta = 1.0; hypre_ParCSRMatrixMatvecOutOfPlace(alpha, A_array[level], U_array[level], beta, Aux_F, Vtemp); if (smooth_type == 8 || smooth_type == 18) HYPRE_ParCSRParaSailsSolve(smoother[level], (HYPRE_ParCSRMatrix) A_array[level], (HYPRE_ParVector) Vtemp, (HYPRE_ParVector) Utemp); else if (smooth_type == 7 || smooth_type == 17) HYPRE_ParCSRPilutSolve(smoother[level], (HYPRE_ParCSRMatrix) A_array[level], (HYPRE_ParVector) Vtemp, (HYPRE_ParVector) Utemp); else if (smooth_type == 9 || smooth_type == 19) HYPRE_EuclidSolve(smoother[level], (HYPRE_ParCSRMatrix) A_array[level], (HYPRE_ParVector) Vtemp, (HYPRE_ParVector) Utemp); hypre_ParVectorAxpy(relax_weight[level],Utemp,Aux_U); } else if (smooth_num_levels > level && (smooth_type == 6 || smooth_type == 16)) { HYPRE_SchwarzSolve(smoother[level], (HYPRE_ParCSRMatrix) A_array[level], (HYPRE_ParVector) Aux_F, (HYPRE_ParVector) Aux_U); } /*else if (relax_type == 99)*/ else if (relax_type == 9 || relax_type == 99) { /* Gaussian elimination */ hypre_GaussElimSolve(amg_data, level, relax_type); } else if (relax_type == 18) { /* L1 - Jacobi*/ if (relax_order == 1 && cycle_param < 3) { /* need to do CF - so can't use the AMS one */ HYPRE_Int i; HYPRE_Int loc_relax_points[2]; if (cycle_type < 2) { loc_relax_points[0] = 1; loc_relax_points[1] = -1; } else { loc_relax_points[0] = -1; loc_relax_points[1] = 1; } for (i=0; i < 2; i++) hypre_ParCSRRelax_L1_Jacobi(A_array[level], Aux_F, CF_marker_array[level], loc_relax_points[i], relax_weight[level], l1_norms[level], Aux_U, Vtemp); } else /* not CF - so use through AMS */ { if (num_threads == 1) hypre_ParCSRRelax(A_array[level], Aux_F, 1, 1, l1_norms_level, relax_weight[level], omega[level],0,0,0,0, Aux_U, Vtemp, Ztemp); else hypre_ParCSRRelaxThreads(A_array[level], Aux_F, 1, 1, l1_norms_level, relax_weight[level], omega[level], Aux_U, Vtemp, Ztemp); } } else if (relax_type == 15) { /* CG */ if (j ==0) /* do num sweep iterations of CG */ hypre_ParCSRRelax_CG( smoother[level], A_array[level], Aux_F, Aux_U, num_sweep); } else if (relax_type == 16) { /* scaled Chebyshev */ HYPRE_Int scale = 1; HYPRE_Int variant = 0; hypre_ParCSRRelax_Cheby(A_array[level], Aux_F, max_eig_est[level], min_eig_est[level], cheby_fraction, cheby_order, scale, variant, Aux_U, Vtemp, Ztemp ); } else if (relax_type ==17) { hypre_BoomerAMGRelax_FCFJacobi(A_array[level], Aux_F, CF_marker_array[level], relax_weight[level], Aux_U, Vtemp); } else if (old_version) { Solve_err_flag = hypre_BoomerAMGRelax(A_array[level], Aux_F, CF_marker_array[level], relax_type, relax_points, relax_weight[level], omega[level], l1_norms_level, Aux_U, Vtemp, Ztemp); } else { /* smoother than can have CF ordering */ if (block_mode) { Solve_err_flag = hypre_BoomerAMGBlockRelaxIF(A_block_array[level], Aux_F, CF_marker_array[level], relax_type, relax_local, cycle_param, relax_weight[level], omega[level], Aux_U, Vtemp); } else { Solve_err_flag = hypre_BoomerAMGRelaxIF(A_array[level], Aux_F, CF_marker_array[level], relax_type, relax_local, cycle_param, relax_weight[level], omega[level], l1_norms_level, Aux_U, Vtemp, Ztemp); } } if (Solve_err_flag != 0) return(Solve_err_flag); } if (smooth_num_levels > level && smooth_type > 9) { gammaold = gamma; gamma = hypre_ParVectorInnerProd(Rtemp,Ztemp); if (jj == 0) hypre_ParVectorCopy(Ztemp,Ptemp); else { beta = gamma/gammaold; for (i=0; i < local_size; i++) Ptemp_data[i] = Ztemp_data[i] + beta*Ptemp_data[i]; } hypre_ParCSRMatrixMatvec(1.0,A_array[level],Ptemp,0.0,Vtemp); alfa = gamma /hypre_ParVectorInnerProd(Ptemp,Vtemp); hypre_ParVectorAxpy(alfa,Ptemp,U_array[level]); hypre_ParVectorAxpy(-alfa,Vtemp,Rtemp); } } } /*------------------------------------------------------------------ * Decrement the control counter and determine which grid to visit next *-----------------------------------------------------------------*/ --lev_counter[level]; if (lev_counter[level] >= 0 && level != num_levels-1) { /*--------------------------------------------------------------- * Visit coarser level next. * Compute residual using hypre_ParCSRMatrixMatvec. * Perform restriction using hypre_ParCSRMatrixMatvecT. * Reset counters and cycling parameters for coarse level *--------------------------------------------------------------*/ fine_grid = level; coarse_grid = level + 1; hypre_ParVectorSetConstantValues(U_array[coarse_grid], 0.0); alpha = -1.0; beta = 1.0; if (block_mode) { hypre_ParVectorCopy(F_array[fine_grid],Vtemp); hypre_ParCSRBlockMatrixMatvec(alpha, A_block_array[fine_grid], U_array[fine_grid], beta, Vtemp); } else { // JSP: avoid unnecessary copy using out-of-place version of SpMV hypre_ParCSRMatrixMatvecOutOfPlace(alpha, A_array[fine_grid], U_array[fine_grid], beta, F_array[fine_grid], Vtemp); } alpha = 1.0; beta = 0.0; if (block_mode) { hypre_ParCSRBlockMatrixMatvecT(alpha,R_block_array[fine_grid],Vtemp, beta,F_array[coarse_grid]); } else { hypre_ParCSRMatrixMatvecT(alpha,R_array[fine_grid],Vtemp, beta,F_array[coarse_grid]); } ++level; lev_counter[level] = hypre_max(lev_counter[level],cycle_type); cycle_param = 1; if (level == num_levels-1) cycle_param = 3; } else if (level != 0) { /*--------------------------------------------------------------- * Visit finer level next. * Interpolate and add correction using hypre_ParCSRMatrixMatvec. * Reset counters and cycling parameters for finer level. *--------------------------------------------------------------*/ fine_grid = level - 1; coarse_grid = level; alpha = 1.0; beta = 1.0; if (block_mode) { hypre_ParCSRBlockMatrixMatvec(alpha, P_block_array[fine_grid], U_array[coarse_grid], beta, U_array[fine_grid]); } else { hypre_ParCSRMatrixMatvec(alpha, P_array[fine_grid], U_array[coarse_grid], beta, U_array[fine_grid]); } --level; cycle_param = 2; } else { Not_Finished = 0; } } hypre_ParAMGDataCycleOpCount(amg_data) = cycle_op_count; hypre_TFree(lev_counter); hypre_TFree(num_coeffs); if (smooth_num_levels > 0) { if (smooth_type == 7 || smooth_type == 8 || smooth_type == 9 || smooth_type == 17 || smooth_type == 18 || smooth_type == 19 ) hypre_ParVectorDestroy(Utemp); } return(Solve_err_flag); }