示例#1
0
int 
HYPRE_VectorInitialize( HYPRE_Vector vector )
{
   return ( hypre_SeqVectorInitialize( (hypre_Vector *) vector ) );
}
示例#2
0
文件: amg_solve.c 项目: LLNL/COGENT
HYPRE_Int
hypre_AMGSolve( void            *amg_vdata,
                hypre_CSRMatrix *A,
                hypre_Vector    *f,
                hypre_Vector    *u         )
{
   hypre_AMGData   *amg_data = amg_vdata;
   
   /* Data Structure variables */

   HYPRE_Int      amg_ioutdat;
   HYPRE_Int     *num_coeffs;
   HYPRE_Int     *num_variables;
   /* HYPRE_Int      cycle_op_count; */
   HYPRE_Int      num_levels;
   /* HYPRE_Int      num_functions; */
   double   tol;
   /* char    *file_name; */
   hypre_CSRMatrix **A_array;
   hypre_Vector    **F_array;
   hypre_Vector    **U_array;

   /*  Local variables  */

   HYPRE_Int      j;
   HYPRE_Int      Solve_err_flag;
   HYPRE_Int      max_iter;
   HYPRE_Int      cycle_count;
   HYPRE_Int      total_coeffs;
   HYPRE_Int      total_variables;

   double   alpha = 1.0;
   double   beta = -1.0;
   /* double   cycle_cmplxty; */
   double   operat_cmplxty;
   double   grid_cmplxty;
   double   conv_factor;
   double   resid_nrm;
   double   resid_nrm_init;
   double   relative_resid;
   double   rhs_norm;
   double   old_resid;

   hypre_Vector  *Vtemp;

   amg_ioutdat   = hypre_AMGDataIOutDat(amg_data);
   /* file_name     = hypre_AMGDataLogFileName(amg_data); */
   /* num_functions  = hypre_AMGDataNumFunctions(amg_data); */
   num_levels    = hypre_AMGDataNumLevels(amg_data);
   A_array       = hypre_AMGDataAArray(amg_data);
   F_array       = hypre_AMGDataFArray(amg_data);
   U_array       = hypre_AMGDataUArray(amg_data);

   tol           = hypre_AMGDataTol(amg_data);
   max_iter      = hypre_AMGDataMaxIter(amg_data);

   num_coeffs = hypre_CTAlloc(HYPRE_Int, num_levels);
   num_variables = hypre_CTAlloc(HYPRE_Int, num_levels);
   num_coeffs[0]    = hypre_CSRMatrixNumNonzeros(A_array[0]);
   num_variables[0] = hypre_CSRMatrixNumRows(A_array[0]);
 
   A_array[0] = A;
   F_array[0] = f;
   U_array[0] = u;

   Vtemp = hypre_SeqVectorCreate(num_variables[0]);
   hypre_SeqVectorInitialize(Vtemp);
   hypre_AMGDataVtemp(amg_data) = Vtemp;

   for (j = 1; j < num_levels; j++)
   {
      num_coeffs[j]    = hypre_CSRMatrixNumNonzeros(A_array[j]);
      num_variables[j] = hypre_CSRMatrixNumRows(A_array[j]);
   }

   /*-----------------------------------------------------------------------
    *    Write the solver parameters
    *-----------------------------------------------------------------------*/

   /*if (amg_ioutdat > 0)
      hypre_WriteSolverParams(amg_data); */


   /*-----------------------------------------------------------------------
    *    Initialize the solver error flag and assorted bookkeeping variables
    *-----------------------------------------------------------------------*/

   Solve_err_flag = 0;

   total_coeffs = 0;
   total_variables = 0;
   cycle_count = 0;
   operat_cmplxty = 0;
   grid_cmplxty = 0;

   /*-----------------------------------------------------------------------
    *     open the log file and write some initial info
    *-----------------------------------------------------------------------*/

   if (amg_ioutdat > 1)
   { 

      hypre_printf("\n\nAMG SOLUTION INFO:\n");

   }

   /*-----------------------------------------------------------------------
    *    Compute initial fine-grid residual and print to logfile
    *-----------------------------------------------------------------------*/

   hypre_SeqVectorCopy(F_array[0],Vtemp);
   hypre_CSRMatrixMatvec(alpha,A_array[0],U_array[0],beta,Vtemp);
   resid_nrm = sqrt(hypre_SeqVectorInnerProd(Vtemp,Vtemp));

   resid_nrm_init = resid_nrm;
   rhs_norm = sqrt(hypre_SeqVectorInnerProd(f,f));
   relative_resid = 9999;
   if (rhs_norm)
   {
      relative_resid = resid_nrm_init / rhs_norm;
   }
   else
   {
      relative_resid = resid_nrm_init;
   }
   

   if (amg_ioutdat == 2 || amg_ioutdat == 3)
   {     
      hypre_printf("                                            relative\n");
      hypre_printf("               residual        factor       residual\n");
      hypre_printf("               --------        ------       --------\n");
      hypre_printf("    Initial    %e                 %e\n",resid_nrm_init,
              relative_resid);
   }

   /*-----------------------------------------------------------------------
    *    Main V-cycle loop
    *-----------------------------------------------------------------------*/
   
   while (relative_resid >= tol && cycle_count < max_iter 
          && Solve_err_flag == 0)
   {
      hypre_AMGDataCycleOpCount(amg_data) = 0;   
      /* Op count only needed for one cycle */

      Solve_err_flag = hypre_AMGCycle(amg_data, F_array, U_array); 

      old_resid = resid_nrm;

      /*---------------------------------------------------------------
       *    Compute  fine-grid residual and residual norm
       *----------------------------------------------------------------*/

      hypre_SeqVectorCopy(F_array[0],Vtemp);
      hypre_CSRMatrixMatvec(alpha,A_array[0],U_array[0],beta,Vtemp);
      resid_nrm = sqrt(hypre_SeqVectorInnerProd(Vtemp,Vtemp));

      conv_factor = resid_nrm / old_resid;
      relative_resid = 9999;
      if (rhs_norm)
      {
         relative_resid = resid_nrm / rhs_norm;
      }
      else
      {
         relative_resid = resid_nrm;
      }

      ++cycle_count;

      if (amg_ioutdat == 2 || amg_ioutdat == 3)
      { 
         hypre_printf("    Cycle %2d   %e    %f     %e \n",cycle_count,
                 resid_nrm,conv_factor,relative_resid);
      }
   }

   if (cycle_count == max_iter) Solve_err_flag = 1;

   /*-----------------------------------------------------------------------
    *    Compute closing statistics
    *-----------------------------------------------------------------------*/

   conv_factor = pow((resid_nrm/resid_nrm_init),(1.0/((double) cycle_count)));


   for (j=0;j<hypre_AMGDataNumLevels(amg_data);j++)
   {
      total_coeffs += num_coeffs[j];
      total_variables += num_variables[j];
   }

   /* cycle_op_count = hypre_AMGDataCycleOpCount(amg_data); */

   grid_cmplxty = ((double) total_variables) / ((double) num_variables[0]);
   operat_cmplxty = ((double) total_coeffs) / ((double) num_coeffs[0]);
   /* cycle_cmplxty = ((double) cycle_op_count) / ((double) num_coeffs[0]); */

   if (amg_ioutdat > 1)
   {
      if (Solve_err_flag == 1)
      {
         hypre_printf("\n\n==============================================");
         hypre_printf("\n NOTE: Convergence tolerance was not achieved\n");
         hypre_printf("      within the allowed %d V-cycles\n",max_iter);
         hypre_printf("==============================================");
      }
      hypre_printf("\n\n Average Convergence Factor = %f",conv_factor);
      hypre_printf("\n\n     Complexity:    grid = %f\n",grid_cmplxty);
      hypre_printf("                operator = %f\n",operat_cmplxty);
      /*  hypre_printf("                   cycle = %f\n\n",cycle_cmplxty); */
   }

   /*----------------------------------------------------------
    * Close the output file (if open)
    *----------------------------------------------------------*/

   hypre_TFree(num_coeffs);
   hypre_TFree(num_variables);

   return(Solve_err_flag);
}
示例#3
0
文件: par_vector.c 项目: LLNL/COGENT
hypre_Vector *
hypre_ParVectorToVectorAll (hypre_ParVector *par_v)
{
   MPI_Comm		comm = hypre_ParVectorComm(par_v);
   HYPRE_Int 			global_size = hypre_ParVectorGlobalSize(par_v);
#ifndef HYPRE_NO_GLOBAL_PARTITION
   HYPRE_Int 			*vec_starts = hypre_ParVectorPartitioning(par_v);
#endif
   hypre_Vector     	*local_vector = hypre_ParVectorLocalVector(par_v);
   HYPRE_Int  		num_procs, my_id;
   HYPRE_Int                  num_vectors = hypre_ParVectorNumVectors(par_v);
   hypre_Vector  	*vector;
   double		*vector_data;
   double		*local_data;
   HYPRE_Int 			local_size;
   hypre_MPI_Request		*requests;
   hypre_MPI_Status		*status;
   HYPRE_Int			i, j;
   HYPRE_Int			*used_procs;
   HYPRE_Int			num_types, num_requests;
   HYPRE_Int			vec_len, proc_id;

#ifdef HYPRE_NO_GLOBAL_PARTITION

   HYPRE_Int *new_vec_starts;
   
   HYPRE_Int num_contacts;
   HYPRE_Int contact_proc_list[1];
   HYPRE_Int contact_send_buf[1];
   HYPRE_Int contact_send_buf_starts[2];
   HYPRE_Int max_response_size;
   HYPRE_Int *response_recv_buf=NULL;
   HYPRE_Int *response_recv_buf_starts = NULL;
   hypre_DataExchangeResponse response_obj;
   hypre_ProcListElements send_proc_obj;
   
   HYPRE_Int *send_info = NULL;
   hypre_MPI_Status  status1;
   HYPRE_Int count, tag1 = 112, tag2 = 223;
   HYPRE_Int start;
   
#endif


   hypre_MPI_Comm_size(comm, &num_procs);
   hypre_MPI_Comm_rank(comm, &my_id);

#ifdef HYPRE_NO_GLOBAL_PARTITION

  local_size = hypre_ParVectorLastIndex(par_v) - 
     hypre_ParVectorFirstIndex(par_v) + 1;

 

/* determine procs which hold data of par_v and store ids in used_procs */
/* we need to do an exchange data for this.  If I own row then I will contact
   processor 0 with the endpoint of my local range */


   if (local_size > 0)
   {
      num_contacts = 1;
      contact_proc_list[0] = 0;
      contact_send_buf[0] =  hypre_ParVectorLastIndex(par_v);
      contact_send_buf_starts[0] = 0;
      contact_send_buf_starts[1] = 1;
   }
   else
   {
      num_contacts = 0;
      contact_send_buf_starts[0] = 0;
      contact_send_buf_starts[1] = 0;
   }

   /*build the response object*/
   /*send_proc_obj will  be for saving info from contacts */
   send_proc_obj.length = 0;
   send_proc_obj.storage_length = 10;
   send_proc_obj.id = hypre_CTAlloc(HYPRE_Int, send_proc_obj.storage_length);
   send_proc_obj.vec_starts = hypre_CTAlloc(HYPRE_Int, send_proc_obj.storage_length + 1); 
   send_proc_obj.vec_starts[0] = 0;
   send_proc_obj.element_storage_length = 10;
   send_proc_obj.elements = hypre_CTAlloc(HYPRE_Int, send_proc_obj.element_storage_length);

   max_response_size = 0; /* each response is null */
   response_obj.fill_response = hypre_FillResponseParToVectorAll;
   response_obj.data1 = NULL;
   response_obj.data2 = &send_proc_obj; /*this is where we keep info from contacts*/
  
   
   hypre_DataExchangeList(num_contacts, 
                          contact_proc_list, contact_send_buf, 
                          contact_send_buf_starts, sizeof(HYPRE_Int), 
                          sizeof(HYPRE_Int), &response_obj, 
                          max_response_size, 1,
                          comm, (void**) &response_recv_buf,	   
                          &response_recv_buf_starts);

 /* now processor 0 should have a list of ranges for processors that have rows -
      these are in send_proc_obj - it needs to create the new list of processors
      and also an array of vec starts - and send to those who own row*/
   if (my_id)
   {
      if (local_size)      
      {
         /* look for a message from processor 0 */         
         hypre_MPI_Probe(0, tag1, comm, &status1);
         hypre_MPI_Get_count(&status1, HYPRE_MPI_INT, &count);
         
         send_info = hypre_CTAlloc(HYPRE_Int, count);
         hypre_MPI_Recv(send_info, count, HYPRE_MPI_INT, 0, tag1, comm, &status1);

         /* now unpack */  
         num_types = send_info[0];
         used_procs =  hypre_CTAlloc(HYPRE_Int, num_types);  
         new_vec_starts = hypre_CTAlloc(HYPRE_Int, num_types+1);

         for (i=1; i<= num_types; i++)
         {
            used_procs[i-1] = send_info[i];
         }
         for (i=num_types+1; i< count; i++)
         {
            new_vec_starts[i-num_types-1] = send_info[i] ;
         }
      }
      else /* clean up and exit */
      {
         hypre_TFree(send_proc_obj.vec_starts);
         hypre_TFree(send_proc_obj.id);
         hypre_TFree(send_proc_obj.elements);
         if(response_recv_buf)        hypre_TFree(response_recv_buf);
         if(response_recv_buf_starts) hypre_TFree(response_recv_buf_starts);
         return NULL;
      }
   }
   else /* my_id ==0 */
   {
      num_types = send_proc_obj.length;
      used_procs =  hypre_CTAlloc(HYPRE_Int, num_types);  
      new_vec_starts = hypre_CTAlloc(HYPRE_Int, num_types+1);
      
      new_vec_starts[0] = 0;
      for (i=0; i< num_types; i++)
      {
         used_procs[i] = send_proc_obj.id[i];
         new_vec_starts[i+1] = send_proc_obj.elements[i]+1;
      }
      qsort0(used_procs, 0, num_types-1);
      qsort0(new_vec_starts, 0, num_types);
      /*now we need to put into an array to send */
      count =  2*num_types+2;
      send_info = hypre_CTAlloc(HYPRE_Int, count);
      send_info[0] = num_types;
      for (i=1; i<= num_types; i++)
      {
         send_info[i] = used_procs[i-1];
      }
      for (i=num_types+1; i< count; i++)
      {
         send_info[i] = new_vec_starts[i-num_types-1];
      }
      requests = hypre_CTAlloc(hypre_MPI_Request, num_types);
      status =  hypre_CTAlloc(hypre_MPI_Status, num_types);

      /* don't send to myself  - these are sorted so my id would be first*/
      start = 0;
      if (used_procs[0] == 0)
      {
         start = 1;
      }
   
      
      for (i=start; i < num_types; i++)
      {
         hypre_MPI_Isend(send_info, count, HYPRE_MPI_INT, used_procs[i], tag1, comm, &requests[i-start]);
      }
      hypre_MPI_Waitall(num_types-start, requests, status);

      hypre_TFree(status);
      hypre_TFree(requests);
   }

   /* clean up */
   hypre_TFree(send_proc_obj.vec_starts);
   hypre_TFree(send_proc_obj.id);
   hypre_TFree(send_proc_obj.elements);
   hypre_TFree(send_info);
   if(response_recv_buf)        hypre_TFree(response_recv_buf);
   if(response_recv_buf_starts) hypre_TFree(response_recv_buf_starts);

   /* now proc 0 can exit if it has no rows */
   if (!local_size) {
      hypre_TFree(used_procs);
      hypre_TFree(new_vec_starts);
      return NULL;
   }
   
   /* everyone left has rows and knows: new_vec_starts, num_types, and used_procs */

  /* this vector should be rather small */

   local_data = hypre_VectorData(local_vector);
   vector = hypre_SeqVectorCreate(global_size);
   hypre_VectorNumVectors(vector) = num_vectors;
   hypre_SeqVectorInitialize(vector);
   vector_data = hypre_VectorData(vector);

   num_requests = 2*num_types;

   requests = hypre_CTAlloc(hypre_MPI_Request, num_requests);
   status = hypre_CTAlloc(hypre_MPI_Status, num_requests);

/* initialize data exchange among used_procs and generate vector  - here we 
   send to ourself also*/
 
   j = 0;
   for (i = 0; i < num_types; i++)
   {
        proc_id = used_procs[i];
        vec_len = new_vec_starts[i+1] - new_vec_starts[i];
        hypre_MPI_Irecv(&vector_data[new_vec_starts[i]], num_vectors*vec_len, hypre_MPI_DOUBLE,
                                proc_id, tag2, comm, &requests[j++]);
   }
   for (i = 0; i < num_types; i++)
   {
        hypre_MPI_Isend(local_data, num_vectors*local_size, hypre_MPI_DOUBLE, used_procs[i],
                          tag2, comm, &requests[j++]);
   }
 
   hypre_MPI_Waitall(num_requests, requests, status);


   if (num_requests)
   {
   	hypre_TFree(requests);
   	hypre_TFree(status); 
        hypre_TFree(used_procs);
   }

   hypre_TFree(new_vec_starts);
   


#else
   local_size = vec_starts[my_id+1] - vec_starts[my_id];

/* if my_id contains no data, return NULL  */

   if (!local_size)
	return NULL;
 
   local_data = hypre_VectorData(local_vector);
   vector = hypre_SeqVectorCreate(global_size);
   hypre_VectorNumVectors(vector) = num_vectors;
   hypre_SeqVectorInitialize(vector);
   vector_data = hypre_VectorData(vector);

/* determine procs which hold data of par_v and store ids in used_procs */

   num_types = -1;
   for (i=0; i < num_procs; i++)
        if (vec_starts[i+1]-vec_starts[i])
                num_types++;
   num_requests = 2*num_types;
 
   used_procs = hypre_CTAlloc(HYPRE_Int, num_types);
   j = 0;
   for (i=0; i < num_procs; i++)
        if (vec_starts[i+1]-vec_starts[i] && i-my_id)
                used_procs[j++] = i;
 
   requests = hypre_CTAlloc(hypre_MPI_Request, num_requests);
   status = hypre_CTAlloc(hypre_MPI_Status, num_requests);

/* initialize data exchange among used_procs and generate vector */
 
   j = 0;
   for (i = 0; i < num_types; i++)
   {
        proc_id = used_procs[i];
        vec_len = vec_starts[proc_id+1] - vec_starts[proc_id];
        hypre_MPI_Irecv(&vector_data[vec_starts[proc_id]], num_vectors*vec_len, hypre_MPI_DOUBLE,
                                proc_id, 0, comm, &requests[j++]);
   }
   for (i = 0; i < num_types; i++)
   {
        hypre_MPI_Isend(local_data, num_vectors*local_size, hypre_MPI_DOUBLE, used_procs[i],
                          0, comm, &requests[j++]);
   }
 
   for (i=0; i < num_vectors*local_size; i++)
        vector_data[vec_starts[my_id]+i] = local_data[i];
 
   hypre_MPI_Waitall(num_requests, requests, status);

   if (num_requests)
   {
   	hypre_TFree(used_procs);
   	hypre_TFree(requests);
   	hypre_TFree(status); 
   }


#endif

   return vector;
}
示例#4
0
HYPRE_Int hypre_CreateDinv(void *amg_vdata)
{
   hypre_ParAMGData *amg_data = amg_vdata;

   /* Data Structure variables */
   hypre_ParCSRMatrix **A_array;
   hypre_ParVector    **F_array;
   hypre_ParVector    **U_array;

   hypre_ParCSRMatrix *A_tmp;
   hypre_CSRMatrix *A_tmp_diag;
   hypre_ParVector *Xtilde;
   hypre_ParVector *Rtilde;
   hypre_Vector *Xtilde_local;
   hypre_Vector *Rtilde_local;
   HYPRE_Real    *x_data;
   HYPRE_Real    *r_data;
   HYPRE_Real    *tmp_data;
   HYPRE_Real    *D_inv = NULL;
   HYPRE_Real    *relax_weight = NULL;
   HYPRE_Real     relax_type;

   HYPRE_Int       addlvl;
   HYPRE_Int       num_levels;
   HYPRE_Int       num_add_lvls;
   HYPRE_Int       num_rows_L;
   HYPRE_Int       num_rows_A;
   HYPRE_Int       num_rows_tmp;
   HYPRE_Int       level, i;

 /* Local variables  */ 
   HYPRE_Int       Solve_err_flag = 0;
   HYPRE_Int       num_threads;

   HYPRE_Real  **l1_norms_ptr = NULL;
   HYPRE_Real  *l1_norms;
   HYPRE_Int l1_start;

   /* Acquire data and allocate storage */

   num_threads = hypre_NumThreads();

   A_array           = hypre_ParAMGDataAArray(amg_data);
   F_array           = hypre_ParAMGDataFArray(amg_data);
   U_array           = hypre_ParAMGDataUArray(amg_data);
   addlvl            = hypre_ParAMGDataSimple(amg_data);
   num_levels        = hypre_ParAMGDataNumLevels(amg_data);
   relax_weight      = hypre_ParAMGDataRelaxWeight(amg_data);
   relax_type        = hypre_ParAMGDataGridRelaxType(amg_data)[1];
   num_rows_A        = hypre_CSRMatrixNumRows(hypre_ParCSRMatrixDiag(A_array[0]));

   l1_norms_ptr      = hypre_ParAMGDataL1Norms(amg_data); 
   /* smooth_option       = hypre_ParAMGDataSmoothOption(amg_data); */

   num_add_lvls = num_levels+1-addlvl;
  
   num_rows_L  = 0;
   for (i=addlvl; i < num_levels; i++)
   {
      A_tmp = A_array[i];
      A_tmp_diag = hypre_ParCSRMatrixDiag(A_tmp);
      num_rows_tmp = hypre_CSRMatrixNumRows(A_tmp_diag);
      num_rows_L += num_rows_tmp;
   }

   Rtilde = hypre_CTAlloc(hypre_ParVector, 1);
   Rtilde_local = hypre_SeqVectorCreate(num_rows_L);   
   hypre_SeqVectorInitialize(Rtilde_local);
   hypre_ParVectorLocalVector(Rtilde) = Rtilde_local;   
   hypre_ParVectorOwnsData(Rtilde) = 1;

   Xtilde = hypre_CTAlloc(hypre_ParVector, 1);
   Xtilde_local = hypre_SeqVectorCreate(num_rows_L);   
   hypre_SeqVectorInitialize(Xtilde_local);
   hypre_ParVectorLocalVector(Xtilde) = Xtilde_local;   
   hypre_ParVectorOwnsData(Xtilde) = 1;
      
   x_data = hypre_VectorData(hypre_ParVectorLocalVector(Xtilde));
   r_data = hypre_VectorData(hypre_ParVectorLocalVector(Rtilde));
   D_inv = hypre_CTAlloc(HYPRE_Real, num_rows_L);

   l1_start = 0;
   for (level=addlvl; level < num_levels; level++)
   {
      if (level != 0)
      {
         tmp_data = hypre_VectorData(hypre_ParVectorLocalVector(F_array[level]));
         if (tmp_data) hypre_TFree(tmp_data);
         hypre_VectorData(hypre_ParVectorLocalVector(F_array[level])) = &r_data[l1_start];
         hypre_VectorOwnsData(hypre_ParVectorLocalVector(F_array[level])) = 0;
         tmp_data = hypre_VectorData(hypre_ParVectorLocalVector(U_array[level]));
         if (tmp_data) hypre_TFree(tmp_data);
         hypre_VectorData(hypre_ParVectorLocalVector(U_array[level])) = &x_data[l1_start];
         hypre_VectorOwnsData(hypre_ParVectorLocalVector(U_array[level])) = 0;
      }

      A_tmp = A_array[level];
      A_tmp_diag = hypre_ParCSRMatrixDiag(A_tmp);
      num_rows_tmp = hypre_CSRMatrixNumRows(A_tmp_diag);

      if (relax_type == 0)
      {
         HYPRE_Real rlx_wt = relax_weight[level];
         HYPRE_Int *A_tmp_diag_i = hypre_CSRMatrixI(A_tmp_diag);
         HYPRE_Real *A_tmp_diag_data = hypre_CSRMatrixData(A_tmp_diag);
#ifdef HYPRE_USING_OPENMP
#pragma omp for private(i) HYPRE_SMP_SCHEDULE
#endif
         for (i=0; i < num_rows_tmp; i++)
            D_inv[l1_start+i] = rlx_wt/A_tmp_diag_data[A_tmp_diag_i[i]];
      }
      else
      {
         l1_norms = l1_norms_ptr[level];
#ifdef HYPRE_USING_OPENMP
#pragma omp for private(i) HYPRE_SMP_SCHEDULE
#endif
         for (i=0; i < num_rows_tmp; i++)
            D_inv[l1_start+i] = 1.0/l1_norms[i];
      }
      l1_start += num_rows_tmp;
   }

   hypre_ParAMGDataDinv(amg_data) = D_inv;
   hypre_ParAMGDataRtilde(amg_data) = Rtilde;
   hypre_ParAMGDataXtilde(amg_data) = Xtilde;

   return Solve_err_flag;
}
示例#5
0
HYPRE_Int hypre_CreateLambda(void *amg_vdata)
{
   hypre_ParAMGData *amg_data = amg_vdata;

   /* Data Structure variables */
   MPI_Comm comm;
   hypre_ParCSRMatrix **A_array;
   hypre_ParVector    **F_array;
   hypre_ParVector    **U_array;

   hypre_ParCSRMatrix *A_tmp;
   hypre_ParCSRMatrix *Lambda;
   hypre_CSRMatrix *L_diag;
   hypre_CSRMatrix *L_offd;
   hypre_CSRMatrix *A_tmp_diag;
   hypre_CSRMatrix *A_tmp_offd;
   hypre_ParVector *Xtilde;
   hypre_ParVector *Rtilde;
   hypre_Vector *Xtilde_local;
   hypre_Vector *Rtilde_local;
   hypre_ParCSRCommPkg *comm_pkg;
   hypre_ParCSRCommPkg *L_comm_pkg = NULL;
   hypre_ParCSRCommHandle *comm_handle;
   HYPRE_Real    *L_diag_data;
   HYPRE_Real    *L_offd_data;
   HYPRE_Real    *buf_data = NULL;
   HYPRE_Real    *tmp_data;
   HYPRE_Real    *x_data;
   HYPRE_Real    *r_data;
   HYPRE_Real    *l1_norms;
   HYPRE_Real    *A_tmp_diag_data;
   HYPRE_Real    *A_tmp_offd_data;
   HYPRE_Real    *D_data = NULL;
   HYPRE_Real    *D_data_offd = NULL;
   HYPRE_Int *L_diag_i;
   HYPRE_Int *L_diag_j;
   HYPRE_Int *L_offd_i;
   HYPRE_Int *L_offd_j;
   HYPRE_Int *A_tmp_diag_i;
   HYPRE_Int *A_tmp_offd_i;
   HYPRE_Int *A_tmp_diag_j;
   HYPRE_Int *A_tmp_offd_j;
   HYPRE_Int *L_recv_ptr = NULL;
   HYPRE_Int *L_send_ptr = NULL;
   HYPRE_Int *L_recv_procs = NULL;
   HYPRE_Int *L_send_procs = NULL;
   HYPRE_Int *L_send_map_elmts = NULL;
   HYPRE_Int *recv_procs;
   HYPRE_Int *send_procs;
   HYPRE_Int *send_map_elmts;
   HYPRE_Int *send_map_starts;
   HYPRE_Int *recv_vec_starts;
   HYPRE_Int *all_send_procs = NULL;
   HYPRE_Int *all_recv_procs = NULL;
   HYPRE_Int *remap = NULL;
   HYPRE_Int *level_start;

   HYPRE_Int       addlvl;
   HYPRE_Int       additive;
   HYPRE_Int       mult_additive;
   HYPRE_Int       num_levels;
   HYPRE_Int       num_add_lvls;
   HYPRE_Int       num_procs;
   HYPRE_Int       num_sends, num_recvs;
   HYPRE_Int       num_sends_L = 0;
   HYPRE_Int       num_recvs_L = 0;
   HYPRE_Int       send_data_L = 0;
   HYPRE_Int       num_rows_L = 0;
   HYPRE_Int       num_rows_tmp = 0;
   HYPRE_Int       num_cols_offd_L = 0;
   HYPRE_Int       num_cols_offd = 0;
   HYPRE_Int       level, i, j, k;
   HYPRE_Int       this_proc, cnt, cnt_diag, cnt_offd;
   HYPRE_Int       cnt_recv, cnt_send, cnt_row, row_start;
   HYPRE_Int       start_diag, start_offd, indx, cnt_map;
   HYPRE_Int       start, j_indx, index, cnt_level;
   HYPRE_Int       max_sends, max_recvs;

 /* Local variables  */ 
   HYPRE_Int       Solve_err_flag = 0;
   HYPRE_Int       num_threads;
   HYPRE_Int       num_nonzeros_diag;
   HYPRE_Int       num_nonzeros_offd;

   HYPRE_Real  **l1_norms_ptr = NULL;
   HYPRE_Real   *relax_weight = NULL;
   HYPRE_Real    relax_type;

   /* Acquire data and allocate storage */

   num_threads = hypre_NumThreads();

   A_array           = hypre_ParAMGDataAArray(amg_data);
   F_array           = hypre_ParAMGDataFArray(amg_data);
   U_array           = hypre_ParAMGDataUArray(amg_data);
   additive          = hypre_ParAMGDataAdditive(amg_data);
   mult_additive     = hypre_ParAMGDataMultAdditive(amg_data);
   num_levels        = hypre_ParAMGDataNumLevels(amg_data);
   relax_weight      = hypre_ParAMGDataRelaxWeight(amg_data);
   relax_type        = hypre_ParAMGDataGridRelaxType(amg_data)[1];
   comm              = hypre_ParCSRMatrixComm(A_array[0]);

   hypre_MPI_Comm_size(comm,&num_procs);

   l1_norms_ptr      = hypre_ParAMGDataL1Norms(amg_data); 

   addlvl = hypre_max(additive, mult_additive);
   num_add_lvls = num_levels+1-addlvl;

   level_start = hypre_CTAlloc(HYPRE_Int, num_add_lvls+1);
   send_data_L = 0;
   num_rows_L  = 0;
   num_cols_offd_L = 0;
   num_nonzeros_diag = 0;
   num_nonzeros_offd = 0;
   level_start[0] = 0; 
   cnt = 1;
   max_sends = 0;
   max_recvs = 0;
   for (i=addlvl; i < num_levels; i++)
   {
      A_tmp = A_array[i];
      A_tmp_diag = hypre_ParCSRMatrixDiag(A_tmp);
      A_tmp_offd = hypre_ParCSRMatrixOffd(A_tmp);
      A_tmp_diag_i = hypre_CSRMatrixI(A_tmp_diag);
      A_tmp_offd_i = hypre_CSRMatrixI(A_tmp_offd);
      num_rows_tmp = hypre_CSRMatrixNumRows(A_tmp_diag);
      num_cols_offd = hypre_CSRMatrixNumCols(A_tmp_offd);
      num_rows_L += num_rows_tmp;
      level_start[cnt] = level_start[cnt-1] + num_rows_tmp;
      cnt++;
      num_cols_offd_L += num_cols_offd;
      num_nonzeros_diag += A_tmp_diag_i[num_rows_tmp];
      num_nonzeros_offd += A_tmp_offd_i[num_rows_tmp];
      comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
      if (comm_pkg)
      {
         num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
         max_sends += num_sends;
         if (num_sends) 
	    send_data_L += hypre_ParCSRCommPkgSendMapStart(comm_pkg,num_sends);
         max_recvs += hypre_ParCSRCommPkgNumRecvs(comm_pkg);
      }
   }
   if (max_sends >= num_procs ||max_recvs >= num_procs)
   {
         max_sends = num_procs;
         max_recvs = num_procs;
   }
   if (max_sends) all_send_procs = hypre_CTAlloc(HYPRE_Int, max_sends);
   if (max_recvs) all_recv_procs = hypre_CTAlloc(HYPRE_Int, max_recvs);

   cnt_send = 0;
   cnt_recv = 0;
   if (max_sends || max_recvs)
   {
      if (max_sends < num_procs && max_recvs < num_procs)
      {
         for (i=addlvl; i < num_levels; i++)
         {
            A_tmp = A_array[i];
            comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
            if (comm_pkg)
            {
               num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
               num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
               send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
               recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
               for (j = 0; j < num_sends; j++)
	          all_send_procs[cnt_send++] = send_procs[j];
               for (j = 0; j < num_recvs; j++)
	          all_recv_procs[cnt_recv++] = recv_procs[j];
            }
         }
         if (max_sends)
         {
            qsort0(all_send_procs, 0, max_sends-1);
            num_sends_L = 1;
            this_proc = all_send_procs[0];
            for (i=1; i < max_sends; i++)
            {
               if (all_send_procs[i] > this_proc)
               {
                  this_proc = all_send_procs[i];
                  all_send_procs[num_sends_L++] = this_proc;
               }
            }
            L_send_procs = hypre_CTAlloc(HYPRE_Int, num_sends_L);
            for (j=0; j < num_sends_L; j++)
	       L_send_procs[j] = all_send_procs[j];
	    hypre_TFree(all_send_procs);
         }
         if (max_recvs)
         {
            qsort0(all_recv_procs, 0, max_recvs-1);
            num_recvs_L = 1;
            this_proc = all_recv_procs[0];
            for (i=1; i < max_recvs; i++)
            {
               if (all_recv_procs[i] > this_proc)
               {
                  this_proc = all_recv_procs[i];
                  all_recv_procs[num_recvs_L++] = this_proc;
               }
            }
            L_recv_procs = hypre_CTAlloc(HYPRE_Int, num_recvs_L);
            for (j=0; j < num_recvs_L; j++)
	       L_recv_procs[j] = all_recv_procs[j];
	    hypre_TFree(all_recv_procs);
         }

         L_recv_ptr = hypre_CTAlloc(HYPRE_Int, num_recvs_L+1);
         L_send_ptr = hypre_CTAlloc(HYPRE_Int, num_sends_L+1);

         for (i=addlvl; i < num_levels; i++)
         {
            A_tmp = A_array[i];
            comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
            if (comm_pkg)
            {
               num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
               num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
               send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
               recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
               send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
               recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
            }
            else
            {
               num_sends = 0;
               num_recvs = 0;
            }
            for (k = 0; k < num_sends; k++)
            {
               this_proc = hypre_BinarySearch(L_send_procs,send_procs[k],num_sends_L);
               L_send_ptr[this_proc+1] += send_map_starts[k+1]-send_map_starts[k];
            }
            for (k = 0; k < num_recvs; k++)
            {
               this_proc = hypre_BinarySearch(L_recv_procs,recv_procs[k],num_recvs_L);
               L_recv_ptr[this_proc+1] += recv_vec_starts[k+1]-recv_vec_starts[k];
            }
         }

         L_recv_ptr[0] = 0;
         for (i=1; i < num_recvs_L; i++)
            L_recv_ptr[i+1] += L_recv_ptr[i];

         L_send_ptr[0] = 0;
         for (i=1; i < num_sends_L; i++)
            L_send_ptr[i+1] += L_send_ptr[i];
      }
      else
      {
         num_recvs_L = 0;
         num_sends_L = 0;
         for (i=addlvl; i < num_levels; i++)
         {
            A_tmp = A_array[i];
            comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
            if (comm_pkg)
            {
               num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
               num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
               send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
               recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
               send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
               recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
               for (j = 0; j < num_sends; j++)
               {
                  this_proc = send_procs[j];
	          if (all_send_procs[this_proc] == 0)
		      num_sends_L++;
                  all_send_procs[this_proc] += send_map_starts[j+1]-send_map_starts[j];
               }
               for (j = 0; j < num_recvs; j++)
               {
                  this_proc = recv_procs[j];
	          if (all_recv_procs[this_proc] == 0)
		      num_recvs_L++;
                  all_recv_procs[this_proc] += recv_vec_starts[j+1]-recv_vec_starts[j];
               }
            }
         }
         if (max_sends)
         {
            L_send_procs = hypre_CTAlloc(HYPRE_Int, num_sends_L);
            L_send_ptr = hypre_CTAlloc(HYPRE_Int, num_sends_L+1);
            num_sends_L = 0;
            for (j=0; j < num_procs; j++)
            {
	       this_proc = all_send_procs[j];
	       if (this_proc)
	       {
	           L_send_procs[num_sends_L++] = j;
	           L_send_ptr[num_sends_L] = this_proc + L_send_ptr[num_sends_L-1];
	       }
            }
         }
         if (max_recvs)
         {
            L_recv_procs = hypre_CTAlloc(HYPRE_Int, num_recvs_L);
            L_recv_ptr = hypre_CTAlloc(HYPRE_Int, num_recvs_L+1);
            num_recvs_L = 0;
            for (j=0; j < num_procs; j++)
            {
	       this_proc = all_recv_procs[j];
	       if (this_proc)
	       {
	           L_recv_procs[num_recvs_L++] = j;
	           L_recv_ptr[num_recvs_L] = this_proc + L_recv_ptr[num_recvs_L-1];
	       }
            }
         }
      } 
   }
   if (max_sends) hypre_TFree(all_send_procs);
   if (max_recvs) hypre_TFree(all_recv_procs);

   L_diag = hypre_CSRMatrixCreate(num_rows_L, num_rows_L, num_nonzeros_diag);
   L_offd = hypre_CSRMatrixCreate(num_rows_L, num_cols_offd_L, num_nonzeros_offd);
   hypre_CSRMatrixInitialize(L_diag);
   hypre_CSRMatrixInitialize(L_offd);
   if (num_nonzeros_diag)
   {
      L_diag_data = hypre_CSRMatrixData(L_diag);
      L_diag_j = hypre_CSRMatrixJ(L_diag);
   }
   L_diag_i = hypre_CSRMatrixI(L_diag);
   if (num_nonzeros_offd)
   {
      L_offd_data = hypre_CSRMatrixData(L_offd);
      L_offd_j = hypre_CSRMatrixJ(L_offd);
   }
   L_offd_i = hypre_CSRMatrixI(L_offd);

   if (num_rows_L) D_data = hypre_CTAlloc(HYPRE_Real,num_rows_L);
   if (send_data_L)
   {
      L_send_map_elmts = hypre_CTAlloc(HYPRE_Int, send_data_L);
      buf_data = hypre_CTAlloc(HYPRE_Real,send_data_L);
   }
   if (num_cols_offd_L)
   {
      D_data_offd = hypre_CTAlloc(HYPRE_Real,num_cols_offd_L);
      /*L_col_map_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd_L);*/
      remap = hypre_CTAlloc(HYPRE_Int, num_cols_offd_L);
   }

   Rtilde = hypre_CTAlloc(hypre_ParVector, 1);
   Rtilde_local = hypre_SeqVectorCreate(num_rows_L);   
   hypre_SeqVectorInitialize(Rtilde_local);
   hypre_ParVectorLocalVector(Rtilde) = Rtilde_local;   
   hypre_ParVectorOwnsData(Rtilde) = 1;

   Xtilde = hypre_CTAlloc(hypre_ParVector, 1);
   Xtilde_local = hypre_SeqVectorCreate(num_rows_L);   
   hypre_SeqVectorInitialize(Xtilde_local);
   hypre_ParVectorLocalVector(Xtilde) = Xtilde_local;   
   hypre_ParVectorOwnsData(Xtilde) = 1;
      
   x_data = hypre_VectorData(hypre_ParVectorLocalVector(Xtilde));
   r_data = hypre_VectorData(hypre_ParVectorLocalVector(Rtilde));

   cnt = 0;
   cnt_level = 0;
   cnt_diag = 0; 
   cnt_offd = 0; 
   cnt_row = 1; 
   L_diag_i[0] = 0;
   L_offd_i[0] = 0;
   for (level=addlvl; level < num_levels; level++)
   {
      row_start = level_start[cnt_level];
      if (level != 0)
      {
         tmp_data = hypre_VectorData(hypre_ParVectorLocalVector(F_array[level]));
         if (tmp_data) hypre_TFree(tmp_data);
         hypre_VectorData(hypre_ParVectorLocalVector(F_array[level])) = &r_data[row_start];
         hypre_VectorOwnsData(hypre_ParVectorLocalVector(F_array[level])) = 0;
         tmp_data = hypre_VectorData(hypre_ParVectorLocalVector(U_array[level]));
         if (tmp_data) hypre_TFree(tmp_data);
         hypre_VectorData(hypre_ParVectorLocalVector(U_array[level])) = &x_data[row_start];
         hypre_VectorOwnsData(hypre_ParVectorLocalVector(U_array[level])) = 0;
      }
      cnt_level++;

      start_diag = L_diag_i[cnt_row-1];
      start_offd = L_offd_i[cnt_row-1];
      A_tmp = A_array[level];
      A_tmp_diag = hypre_ParCSRMatrixDiag(A_tmp);
      A_tmp_offd = hypre_ParCSRMatrixOffd(A_tmp);
      comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
      A_tmp_diag_i = hypre_CSRMatrixI(A_tmp_diag);
      A_tmp_offd_i = hypre_CSRMatrixI(A_tmp_offd);
      A_tmp_diag_j = hypre_CSRMatrixJ(A_tmp_diag);
      A_tmp_offd_j = hypre_CSRMatrixJ(A_tmp_offd);
      A_tmp_diag_data = hypre_CSRMatrixData(A_tmp_diag);
      A_tmp_offd_data = hypre_CSRMatrixData(A_tmp_offd);
      num_rows_tmp = hypre_CSRMatrixNumRows(A_tmp_diag);
      if (comm_pkg)
      {
         num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
         num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
         send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
         recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
         send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
         send_map_elmts = hypre_ParCSRCommPkgSendMapElmts(comm_pkg);
         recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
      }
      else
      {
         num_sends = 0;
         num_recvs = 0;
      }
   
      /* Compute new combined communication package */
      for (i=0; i < num_sends; i++)
      {
         this_proc = hypre_BinarySearch(L_send_procs,send_procs[i],num_sends_L);
         indx = L_send_ptr[this_proc];
         for (j=send_map_starts[i]; j < send_map_starts[i+1]; j++)
         {
	    L_send_map_elmts[indx++] = row_start + send_map_elmts[j];
         }
         L_send_ptr[this_proc] = indx;
      }
            
      cnt_map = 0;
      for (i = 0; i < num_recvs; i++)
      {
         this_proc = hypre_BinarySearch(L_recv_procs,recv_procs[i],num_recvs_L);
         indx = L_recv_ptr[this_proc];
         for (j=recv_vec_starts[i]; j < recv_vec_starts[i+1]; j++)
         {
	    remap[cnt_map++] = indx++;
         }
         L_recv_ptr[this_proc] = indx;
      }
   
      /* Compute Lambda */ 
      if (relax_type == 0)
      {
        HYPRE_Real rlx_wt = relax_weight[level];
#ifdef HYPRE_USING_OPENMP
#pragma omp for private(i) HYPRE_SMP_SCHEDULE
#endif
         for (i=0; i < num_rows_tmp; i++)
        {
           D_data[i] = rlx_wt/A_tmp_diag_data[A_tmp_diag_i[i]];
           L_diag_i[cnt_row+i] = start_diag + A_tmp_diag_i[i+1];
           L_offd_i[cnt_row+i] = start_offd + A_tmp_offd_i[i+1];
        }
      }
      else
      {
        l1_norms = l1_norms_ptr[level];
#ifdef HYPRE_USING_OPENMP
#pragma omp for private(i) HYPRE_SMP_SCHEDULE
#endif
        for (i=0; i < num_rows_tmp; i++)
        {
           D_data[i] = 1.0/l1_norms[i];
           L_diag_i[cnt_row+i] = start_diag + A_tmp_diag_i[i+1];
           L_offd_i[cnt_row+i] = start_offd + A_tmp_offd_i[i+1];
        }
      }
 
      if (num_procs > 1)
      {
         index = 0;
         for (i=0; i < num_sends; i++)
         {
            start = send_map_starts[i];
            for (j=start; j < send_map_starts[i+1]; j++)
              buf_data[index++] = D_data[send_map_elmts[j]];
         }

         comm_handle = hypre_ParCSRCommHandleCreate(1, comm_pkg,
                        buf_data, D_data_offd);
         hypre_ParCSRCommHandleDestroy(comm_handle);
      }

      for (i = 0; i < num_rows_tmp; i++)
      {
         j_indx = A_tmp_diag_i[i];
         L_diag_data[cnt_diag] = (2.0 - A_tmp_diag_data[j_indx]*D_data[i])*D_data[i];
         L_diag_j[cnt_diag++] = i+row_start;
         for (j=A_tmp_diag_i[i]+1; j < A_tmp_diag_i[i+1]; j++)
         {
             j_indx = A_tmp_diag_j[j];
             L_diag_data[cnt_diag] = (- A_tmp_diag_data[j]*D_data[j_indx])*D_data[i];
             L_diag_j[cnt_diag++] = j_indx+row_start;
         }
         for (j=A_tmp_offd_i[i]; j < A_tmp_offd_i[i+1]; j++)
         {
             j_indx = A_tmp_offd_j[j];
             L_offd_data[cnt_offd] = (- A_tmp_offd_data[j]*D_data_offd[j_indx])*D_data[i];
             L_offd_j[cnt_offd++] = remap[j_indx];
         }
      }
      cnt_row += num_rows_tmp;
   }

   if (L_send_ptr)
   {
      for (i=num_sends_L-1; i > 0; i--)
         L_send_ptr[i] = L_send_ptr[i-1];
      L_send_ptr[0] = 0;
   }
   else
      L_send_ptr = hypre_CTAlloc(HYPRE_Int,1);

   if (L_recv_ptr)
   {
      for (i=num_recvs_L-1; i > 0; i--)
         L_recv_ptr[i] = L_recv_ptr[i-1];
      L_recv_ptr[0] = 0;
   }
   else
      L_recv_ptr = hypre_CTAlloc(HYPRE_Int,1);

   L_comm_pkg = hypre_CTAlloc(hypre_ParCSRCommPkg,1);

   hypre_ParCSRCommPkgNumRecvs(L_comm_pkg) = num_recvs_L;
   hypre_ParCSRCommPkgNumSends(L_comm_pkg) = num_sends_L;
   hypre_ParCSRCommPkgRecvProcs(L_comm_pkg) = L_recv_procs;
   hypre_ParCSRCommPkgSendProcs(L_comm_pkg) = L_send_procs;
   hypre_ParCSRCommPkgRecvVecStarts(L_comm_pkg) = L_recv_ptr;
   hypre_ParCSRCommPkgSendMapStarts(L_comm_pkg) = L_send_ptr;
   hypre_ParCSRCommPkgSendMapElmts(L_comm_pkg) = L_send_map_elmts;
   hypre_ParCSRCommPkgComm(L_comm_pkg) = comm;


   Lambda = hypre_CTAlloc(hypre_ParCSRMatrix, 1);
   hypre_ParCSRMatrixDiag(Lambda) = L_diag;
   hypre_ParCSRMatrixOffd(Lambda) = L_offd;
   hypre_ParCSRMatrixCommPkg(Lambda) = L_comm_pkg;
   hypre_ParCSRMatrixComm(Lambda) = comm;
   hypre_ParCSRMatrixOwnsData(Lambda) = 1;

   hypre_ParAMGDataLambda(amg_data) = Lambda;
   hypre_ParAMGDataRtilde(amg_data) = Rtilde;
   hypre_ParAMGDataXtilde(amg_data) = Xtilde;

   hypre_TFree(D_data_offd);
   hypre_TFree(D_data);
   if (num_procs > 1) hypre_TFree(buf_data);
   hypre_TFree(remap);
   hypre_TFree(buf_data);
   hypre_TFree(level_start);

   return Solve_err_flag;
}
示例#6
0
HYPRE_Int
main( HYPRE_Int   argc,
      char *argv[] )
{
   hypre_ParVector   *vector1;
   hypre_ParVector   *vector2;
   hypre_ParVector   *tmp_vector;

   HYPRE_Int          num_procs, my_id;
   HYPRE_Int	 	global_size = 20;
   HYPRE_Int		local_size;
   HYPRE_Int		first_index;
   HYPRE_Int 		i;
   HYPRE_Int 		*partitioning;
   HYPRE_Complex	prod;
   HYPRE_Complex 	*data, *data2;
   hypre_Vector *vector; 
   hypre_Vector *local_vector; 
   hypre_Vector *local_vector2;
 
   /* Initialize MPI */
   hypre_MPI_Init(&argc, &argv);

   hypre_MPI_Comm_size(hypre_MPI_COMM_WORLD, &num_procs );
   hypre_MPI_Comm_rank(hypre_MPI_COMM_WORLD, &my_id );

   hypre_printf(" my_id: %d num_procs: %d\n", my_id, num_procs);
 
   partitioning = NULL;
   vector1 = hypre_ParVectorCreate(hypre_MPI_COMM_WORLD,global_size,partitioning);
   partitioning = hypre_ParVectorPartitioning(vector1);
   hypre_ParVectorInitialize(vector1);
   local_vector = hypre_ParVectorLocalVector(vector1);
   data = hypre_VectorData(local_vector);
   local_size = hypre_VectorSize(local_vector);
   first_index = partitioning[my_id];

   for (i=0; i < local_size; i++)
   	data[i] = first_index+i;
/*
   hypre_ParVectorPrint(vector1, "Vector");
*/
   local_vector2 = hypre_SeqVectorCreate(global_size);
   hypre_SeqVectorInitialize(local_vector2);
   data2 = hypre_VectorData(local_vector2);
   for (i=0; i < global_size; i++)
	data2[i] = i+1;

/*   partitioning = hypre_CTAlloc(HYPRE_Int,4);
   partitioning[0] = 0;
   partitioning[1] = 10;
   partitioning[2] = 10;
   partitioning[3] = 20;
*/
   vector2 = hypre_VectorToParVector(hypre_MPI_COMM_WORLD,local_vector2,partitioning);
   hypre_ParVectorSetPartitioningOwner(vector2,0);

   hypre_ParVectorPrint(vector2, "Convert");

   vector = hypre_ParVectorToVectorAll(vector2);

   /*-----------------------------------------------------------
    * Copy the vector into tmp_vector
    *-----------------------------------------------------------*/

   tmp_vector = hypre_ParVectorRead(hypre_MPI_COMM_WORLD, "Convert");
/*
   tmp_vector = hypre_ParVectorCreate(hypre_MPI_COMM_WORLD,global_size,partitioning);
   hypre_ParVectorSetPartitioningOwner(tmp_vector,0);
   hypre_ParVectorInitialize(tmp_vector);
   hypre_ParVectorCopy(vector1, tmp_vector);

   hypre_ParVectorPrint(tmp_vector,"Copy");
*/
   /*-----------------------------------------------------------
    * Scale tmp_vector
    *-----------------------------------------------------------*/

   hypre_ParVectorScale(2.0, tmp_vector);
/*
   hypre_ParVectorPrint(tmp_vector,"Scale");
*/
   /*-----------------------------------------------------------
    * Do an Axpy (2*vector - vector) = vector
    *-----------------------------------------------------------*/

   hypre_ParVectorAxpy(-1.0, vector1, tmp_vector);
/*
   hypre_ParVectorPrint(tmp_vector,"Axpy");
*/
   /*-----------------------------------------------------------
    * Do an inner product vector* tmp_vector
    *-----------------------------------------------------------*/

   prod = hypre_ParVectorInnerProd(vector1, tmp_vector);

   hypre_printf (" prod: %8.2f \n", prod);

   /*-----------------------------------------------------------
    * Finalize things
    *-----------------------------------------------------------*/

   hypre_ParVectorDestroy(vector1);
   hypre_ParVectorDestroy(vector2); 
   hypre_ParVectorDestroy(tmp_vector);
   hypre_SeqVectorDestroy(local_vector2); 
   if (vector) hypre_SeqVectorDestroy(vector); 

   /* Finalize MPI */
   hypre_MPI_Finalize();

   return 0;
}
示例#7
0
文件: coarsenCR.c 项目: LLNL/COGENT
/**************************************************************
 *
 *      Coarsening routine
 *
 **************************************************************/
HYPRE_Int
hypre_AMGCoarsenCR( hypre_CSRMatrix    *A,
                  double              strength_threshold,
                  double	      relax_weight,
                  HYPRE_Int		      relax_type,
                  HYPRE_Int		      num_relax_steps,
                  HYPRE_Int               **CF_marker_ptr,
                  HYPRE_Int                *coarse_size_ptr     )
{
   HYPRE_Int              num_variables = hypre_CSRMatrixNumRows(A);
                  
   HYPRE_Int             *CF_marker;
   HYPRE_Int              coarse_size;

   double          *measure_array;
   hypre_Vector    *measure_vector;
   hypre_Vector    *zero_vector;
   hypre_Vector    *tmp_vector;
   HYPRE_Int             *graph_array;
   /* HYPRE_Int             *tmp_array; */
   HYPRE_Int              graph_size;
   /* HYPRE_Int              tmp_size; */

   HYPRE_Int              i, ig;

   HYPRE_Int              ierr = 0;

#if 0 /* debugging */
   char  filename[256];
   FILE *fp;
   HYPRE_Int   iter = 0;
#endif

   /*---------------------------------------------------
    * Initialize the C/F marker array
    *---------------------------------------------------*/

   CF_marker = hypre_CTAlloc(HYPRE_Int, num_variables);

   measure_vector = hypre_SeqVectorCreate(num_variables);
   zero_vector = hypre_SeqVectorCreate(num_variables);
   tmp_vector = hypre_SeqVectorCreate(num_variables);
   hypre_SeqVectorInitialize(measure_vector);
   hypre_SeqVectorInitialize(zero_vector);
   hypre_SeqVectorInitialize(tmp_vector);
   hypre_SeqVectorSetConstantValues(measure_vector, 1.0);
   measure_array = hypre_VectorData(measure_vector);

   for (i=0; i < num_relax_steps; i++)
   {
      hypre_AMGRelax (A, zero_vector, CF_marker, relax_type, 0, relax_weight, 
			measure_vector, tmp_vector);
   }

   /*---------------------------------------------------
    * Initialize the graph array
    *---------------------------------------------------*/

   graph_array   = hypre_CTAlloc(HYPRE_Int, num_variables);
   coarse_size = 0;
   graph_size = 0;
 
   /* intialize measure array and graph array */

   for (i = 0; i < num_variables; i++)
   {
      if (measure_array[i] < strength_threshold)
      {
	 measure_array[i] = 0;
	 CF_marker[i] = -1;
      }
      else
 	 graph_array[graph_size++] = i;
   }

/*  for second path of coarse point determination if needed */
/*   tmp_array   = hypre_CTAlloc(HYPRE_Int, graph_size);  */

   while (graph_size)
   {

      hypre_InitAMGIndepSet(A, measure_array, 0.001);
      hypre_AMGIndepSet (A, measure_array, 0.001,
			graph_array, graph_size, CF_marker);

/*  for second path of coarse point determination if needed */
/*      tmp_size = 0;
      for (ig = 0; ig < graph_size; ig++)
      {
         i = graph_array[ig];
         if (CF_marker[i] == 1)
         {
            tmp_array[tmp_size++] = i;
         }
      }

      hypre_AMGIndepSet (A, measure_array, 0.001,
			tmp_array, tmp_size, CF_marker);
*/

      hypre_SeqVectorSetConstantValues(measure_vector, 0.0);

      for (i = 0; i < num_variables; i++)
      {
         if (CF_marker[i] == 0) 
         {
   	    CF_marker[i] = -2;  
   	    measure_array[i] = 1.0;
         }
      }

      for (i=0; i < num_relax_steps; i++)
      {
         hypre_AMGRelax (A, zero_vector, CF_marker, relax_type, -2, 
			relax_weight, measure_vector, tmp_vector);
      }

      for (ig = 0; ig < graph_size; ig++)
      {
         i = graph_array[ig];
         if (CF_marker[i] == 1)
         {
	    measure_array[i] = 0;
 	    graph_size--;
 	    coarse_size++;
	    graph_array[ig] = graph_array[graph_size];
	    ig--;
         }
         else if (measure_array[i] < strength_threshold)
         {
	    measure_array[i] = 0;
	    CF_marker[i] = -1;
 	    graph_size--;
	    graph_array[ig] = graph_array[graph_size];
   	    ig--;
         }
	 else
	    CF_marker[i] = 0;
      }
   }

   /*---------------------------------------------------
    * Clean up and return
    *---------------------------------------------------*/

   hypre_SeqVectorDestroy(measure_vector);
   hypre_SeqVectorDestroy(zero_vector);
   hypre_SeqVectorDestroy(tmp_vector);
   hypre_TFree(graph_array);
/*    hypre_TFree(tmp_array); */

   *CF_marker_ptr   = CF_marker;
   *coarse_size_ptr = coarse_size;

   return (ierr);
}
示例#8
0
HYPRE_Int
main( HYPRE_Int   argc,
      char *argv[] )
{
   hypre_ParVector   *vector1;
   hypre_ParVector   *vector2;
   hypre_ParVector   *tmp_vector;

   HYPRE_Int          num_procs, my_id;
   HYPRE_Int	 	global_size = 20;
   HYPRE_Int		local_size;
   HYPRE_Int		first_index;
   HYPRE_Int          num_vectors, vecstride, idxstride;
   HYPRE_Int 		i, j;
   HYPRE_Int 		*partitioning;
   double	prod;
   double 	*data, *data2;
   hypre_Vector *vector; 
   hypre_Vector *local_vector; 
   hypre_Vector *local_vector2;
 
   /* Initialize MPI */
   hypre_MPI_Init(&argc, &argv);

   hypre_MPI_Comm_size(hypre_MPI_COMM_WORLD, &num_procs );
   hypre_MPI_Comm_rank(hypre_MPI_COMM_WORLD, &my_id );

   hypre_printf(" my_id: %d num_procs: %d\n", my_id, num_procs);
 
   partitioning = NULL;
   num_vectors = 3;
   vector1 = hypre_ParMultiVectorCreate
      ( hypre_MPI_COMM_WORLD, global_size, partitioning, num_vectors );
   partitioning = hypre_ParVectorPartitioning(vector1);

   hypre_ParVectorInitialize(vector1);
   local_vector = hypre_ParVectorLocalVector(vector1);
   data = hypre_VectorData(local_vector);
   local_size = hypre_VectorSize(local_vector);
   vecstride = hypre_VectorVectorStride(local_vector);
   idxstride = hypre_VectorIndexStride(local_vector);
   first_index = partitioning[my_id];

   hypre_printf("vecstride=%i idxstride=%i local_size=%i num_vectors=%i",
          vecstride, idxstride, local_size, num_vectors );
   for (j=0; j<num_vectors; ++j )
      for (i=0; i < local_size; i++)
         data[ j*vecstride + i*idxstride ] = first_index+i + 100*j;

   hypre_ParVectorPrint(vector1, "Vector");

   local_vector2 = hypre_SeqMultiVectorCreate( global_size, num_vectors );
   hypre_SeqVectorInitialize(local_vector2);
   data2 = hypre_VectorData(local_vector2);
   vecstride = hypre_VectorVectorStride(local_vector2);
   idxstride = hypre_VectorIndexStride(local_vector2);
   for (j=0; j<num_vectors; ++j )
      for (i=0; i < global_size; i++)
         data2[ j*vecstride + i*idxstride ] = i + 100*j;

/*   partitioning = hypre_CTAlloc(HYPRE_Int,4);
   partitioning[0] = 0;
   partitioning[1] = 10;
   partitioning[2] = 10;
   partitioning[3] = 20;
*/
   partitioning = hypre_CTAlloc(HYPRE_Int,1+num_procs);
   hypre_GeneratePartitioning( global_size, num_procs, &partitioning );

   vector2 = hypre_VectorToParVector(hypre_MPI_COMM_WORLD,local_vector2,partitioning);
   hypre_ParVectorSetPartitioningOwner(vector2,0);

   hypre_ParVectorPrint(vector2, "Convert");

   vector = hypre_ParVectorToVectorAll(vector2);

   /*-----------------------------------------------------------
    * Copy the vector into tmp_vector
    *-----------------------------------------------------------*/

/* Read doesn't work for multivectors yet...
   tmp_vector = hypre_ParVectorRead(hypre_MPI_COMM_WORLD, "Convert");*/
   tmp_vector = hypre_ParMultiVectorCreate
      ( hypre_MPI_COMM_WORLD, global_size, partitioning, num_vectors );
   hypre_ParVectorInitialize( tmp_vector );
   hypre_ParVectorCopy( vector2, tmp_vector );
/*
   tmp_vector = hypre_ParVectorCreate(hypre_MPI_COMM_WORLD,global_size,partitioning);
   hypre_ParVectorSetPartitioningOwner(tmp_vector,0);
   hypre_ParVectorInitialize(tmp_vector);
   hypre_ParVectorCopy(vector1, tmp_vector);

   hypre_ParVectorPrint(tmp_vector,"Copy");
*/
   /*-----------------------------------------------------------
    * Scale tmp_vector
    *-----------------------------------------------------------*/

   hypre_ParVectorScale(2.0, tmp_vector);
   hypre_ParVectorPrint(tmp_vector,"Scale");

   /*-----------------------------------------------------------
    * Do an Axpy (2*vector - vector) = vector
    *-----------------------------------------------------------*/

   hypre_ParVectorAxpy(-1.0, vector1, tmp_vector);
   hypre_ParVectorPrint(tmp_vector,"Axpy");

   /*-----------------------------------------------------------
    * Do an inner product vector* tmp_vector
    *-----------------------------------------------------------*/

   prod = hypre_ParVectorInnerProd(vector1, tmp_vector);

   hypre_printf (" prod: %8.2f \n", prod);

   /*-----------------------------------------------------------
    * Finalize things
    *-----------------------------------------------------------*/

   hypre_ParVectorDestroy(vector1);
   hypre_ParVectorDestroy(vector2); 
   hypre_ParVectorDestroy(tmp_vector);
   hypre_SeqVectorDestroy(local_vector2); 
   if (vector) hypre_SeqVectorDestroy(vector); 

   /* Finalize MPI */
   hypre_MPI_Finalize();

   return 0;
}