Actual source code: superlu_dist.c
petsc-3.15.0 2021-03-30
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      1: /*
      2:         Provides an interface to the SuperLU_DIST sparse solver
      3: */

      5: #include <../src/mat/impls/aij/seq/aij.h>
      6: #include <../src/mat/impls/aij/mpi/mpiaij.h>
      7: #include <petscpkg_version.h>

      9: EXTERN_C_BEGIN
     10: #if defined(PETSC_USE_COMPLEX)
     11: #include <superlu_zdefs.h>
     12: #if PETSC_PKG_SUPERLU_DIST_VERSION_GE(6,3,0)
     13: #define LUstructInit zLUstructInit
     14: #define ScalePermstructInit zScalePermstructInit
     15: #define ScalePermstructFree zScalePermstructFree
     16: #define LUstructFree zLUstructFree
     17: #define Destroy_LU zDestroy_LU
     18: #define ScalePermstruct_t zScalePermstruct_t
     19: #define LUstruct_t zLUstruct_t
     20: #define SOLVEstruct_t zSOLVEstruct_t
     21: #endif
     22: #else
     23: #include <superlu_ddefs.h>
     24: #if PETSC_PKG_SUPERLU_DIST_VERSION_GE(6,3,0)
     25: #define LUstructInit dLUstructInit
     26: #define ScalePermstructInit dScalePermstructInit
     27: #define ScalePermstructFree dScalePermstructFree
     28: #define LUstructFree dLUstructFree
     29: #define Destroy_LU dDestroy_LU
     30: #define ScalePermstruct_t dScalePermstruct_t
     31: #define LUstruct_t dLUstruct_t
     32: #define SOLVEstruct_t dSOLVEstruct_t
     33: #endif
     34: #endif
     35: EXTERN_C_END

     37: typedef struct {
     38:   int_t                  nprow,npcol,*row,*col;
     39:   gridinfo_t             grid;
     40:   superlu_dist_options_t options;
     41:   SuperMatrix            A_sup;
     42:   ScalePermstruct_t      ScalePermstruct;
     43:   LUstruct_t             LUstruct;
     44:   int                    StatPrint;
     45:   SOLVEstruct_t          SOLVEstruct;
     46:   fact_t                 FactPattern;
     47:   MPI_Comm               comm_superlu;
     48: #if defined(PETSC_USE_COMPLEX)
     49:   doublecomplex          *val;
     50: #else
     51:   double                 *val;
     52: #endif
     53:   PetscBool              matsolve_iscalled,matmatsolve_iscalled;
     54:   PetscBool              CleanUpSuperLU_Dist;  /* Flag to clean up (non-global) SuperLU objects during Destroy */
     55: } Mat_SuperLU_DIST;

     58: PetscErrorCode MatSuperluDistGetDiagU_SuperLU_DIST(Mat F,PetscScalar *diagU)
     59: {
     60:   Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data;

     63: #if defined(PETSC_USE_COMPLEX)
     64:   PetscStackCall("SuperLU_DIST:pzGetDiagU",pzGetDiagU(F->rmap->N,&lu->LUstruct,&lu->grid,(doublecomplex*)diagU));
     65: #else
     66:   PetscStackCall("SuperLU_DIST:pdGetDiagU",pdGetDiagU(F->rmap->N,&lu->LUstruct,&lu->grid,diagU));
     67: #endif
     68:   return(0);
     69: }

     71: PetscErrorCode MatSuperluDistGetDiagU(Mat F,PetscScalar *diagU)
     72: {

     77:   PetscTryMethod(F,"MatSuperluDistGetDiagU_C",(Mat,PetscScalar*),(F,diagU));
     78:   return(0);
     79: }

     81: /*  This allows reusing the Superlu_DIST communicator and grid when only a single SuperLU_DIST matrix is used at a time */
     82: typedef struct {
     83:   MPI_Comm   comm;
     84:   PetscBool  busy;
     85:   gridinfo_t grid;
     86: } PetscSuperLU_DIST;
     87: static PetscMPIInt Petsc_Superlu_dist_keyval = MPI_KEYVAL_INVALID;

     89: PETSC_EXTERN PetscMPIInt MPIAPI Petsc_Superlu_dist_keyval_Delete_Fn(MPI_Comm comm,PetscMPIInt keyval,void *attr_val,void *extra_state)
     90: {
     91:   PetscErrorCode    ierr;
     92:   PetscSuperLU_DIST *context = (PetscSuperLU_DIST *) attr_val;

     95:   if (keyval != Petsc_Superlu_dist_keyval) SETERRMPI(PETSC_COMM_SELF,PETSC_ERR_ARG_CORRUPT,"Unexpected keyval");
     96:   PetscInfo(NULL,"Removing Petsc_Superlu_dist_keyval attribute from communicator that is being freed\n");
     97:   PetscStackCall("SuperLU_DIST:superlu_gridexit",superlu_gridexit(&context->grid));
     98:   MPI_Comm_free(&context->comm);
     99:   PetscFree(context);
    100:   PetscFunctionReturn(MPI_SUCCESS);
    101: }

    103: /*
    104:    Performs MPI_Comm_free_keyval() on Petsc_Superlu_dist_keyval but keeps the global variable for
    105:    users who do not destroy all PETSc objects before PetscFinalize().

    107:    The value Petsc_Superlu_dist_keyval is retained so that Petsc_Superlu_dist_keyval_Delete_Fn()
    108:    can still check that the keyval associated with the MPI communicator is correct when the MPI
    109:    communicator is destroyed.

    111:    This is called in PetscFinalize()
    112: */
    113: static PetscErrorCode Petsc_Superlu_dist_keyval_free(void)
    114: {
    116:   PetscMPIInt    Petsc_Superlu_dist_keyval_temp = Petsc_Superlu_dist_keyval;

    119:   PetscInfo(NULL,"Freeing Petsc_Superlu_dist_keyval\n");
    120:   MPI_Comm_free_keyval(&Petsc_Superlu_dist_keyval_temp);
    121:   return(0);
    122: }

    124: static PetscErrorCode MatDestroy_SuperLU_DIST(Mat A)
    125: {
    126:   PetscErrorCode   ierr;
    127:   Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data;

    130:   if (lu->CleanUpSuperLU_Dist) {
    131:     /* Deallocate SuperLU_DIST storage */
    132:     PetscStackCall("SuperLU_DIST:Destroy_CompRowLoc_Matrix_dist",Destroy_CompRowLoc_Matrix_dist(&lu->A_sup));
    133:     if (lu->options.SolveInitialized) {
    134: #if defined(PETSC_USE_COMPLEX)
    135:       PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct));
    136: #else
    137:       PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct));
    138: #endif
    139:     }
    140:     PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(A->cmap->N, &lu->grid, &lu->LUstruct));
    141:     PetscStackCall("SuperLU_DIST:ScalePermstructFree",ScalePermstructFree(&lu->ScalePermstruct));
    142:     PetscStackCall("SuperLU_DIST:LUstructFree",LUstructFree(&lu->LUstruct));

    144:     /* Release the SuperLU_DIST process grid. Only if the matrix has its own copy, this is it is not in the communicator context */
    145:     if (lu->comm_superlu) {
    146:       PetscStackCall("SuperLU_DIST:superlu_gridexit",superlu_gridexit(&lu->grid));
    147:       MPI_Comm_free(&(lu->comm_superlu));
    148:     } else {
    149:       PetscSuperLU_DIST *context;
    150:       MPI_Comm          comm;
    151:       PetscMPIInt       flg;

    153:       PetscObjectGetComm((PetscObject)A,&comm);
    154:       MPI_Comm_get_attr(comm,Petsc_Superlu_dist_keyval,&context,&flg);
    155:       if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Communicator does not have expected Petsc_Superlu_dist_keyval attribute");
    156:       context->busy = PETSC_FALSE;
    157:     }
    158:   }
    159:   PetscFree(A->data);
    160:   /* clear composed functions */
    161:   PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);
    162:   PetscObjectComposeFunction((PetscObject)A,"MatSuperluDistGetDiagU_C",NULL);

    164:   return(0);
    165: }

    167: static PetscErrorCode MatSolve_SuperLU_DIST(Mat A,Vec b_mpi,Vec x)
    168: {
    169:   Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data;
    170:   PetscErrorCode   ierr;
    171:   PetscInt         m=A->rmap->n;
    172:   SuperLUStat_t    stat;
    173:   double           berr[1];
    174:   PetscScalar      *bptr=NULL;
    175:   int              info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */
    176:   static PetscBool cite = PETSC_FALSE;

    179:   if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact must equal FACTORED");
    180:   PetscCitationsRegister("@article{lidemmel03,\n  author = {Xiaoye S. Li and James W. Demmel},\n  title = {{SuperLU_DIST}: A Scalable Distributed-Memory Sparse Direct\n           Solver for Unsymmetric Linear Systems},\n  journal = {ACM Trans. Mathematical Software},\n  volume = {29},\n  number = {2},\n  pages = {110-140},\n  year = 2003\n}\n",&cite);

    182:   if (lu->options.SolveInitialized && !lu->matsolve_iscalled) {
    183:     /* see comments in MatMatSolve() */
    184: #if defined(PETSC_USE_COMPLEX)
    185:     PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct));
    186: #else
    187:     PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct));
    188: #endif
    189:     lu->options.SolveInitialized = NO;
    190:   }
    191:   VecCopy(b_mpi,x);
    192:   VecGetArray(x,&bptr);

    194:   PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat));        /* Initialize the statistics variables. */
    195: #if defined(PETSC_USE_COMPLEX)
    196:   PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,1,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info));
    197: #else
    198:   PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,1,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info));
    199: #endif
    200:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info);

    202:   if (lu->options.PrintStat) PetscStackCall("SuperLU_DIST:PStatPrint",PStatPrint(&lu->options, &stat, &lu->grid));  /* Print the statistics. */
    203:   PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat));

    205:   VecRestoreArray(x,&bptr);
    206:   lu->matsolve_iscalled    = PETSC_TRUE;
    207:   lu->matmatsolve_iscalled = PETSC_FALSE;
    208:   return(0);
    209: }

    211: static PetscErrorCode MatMatSolve_SuperLU_DIST(Mat A,Mat B_mpi,Mat X)
    212: {
    213:   Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data;
    214:   PetscErrorCode   ierr;
    215:   PetscInt         m=A->rmap->n,nrhs;
    216:   SuperLUStat_t    stat;
    217:   double           berr[1];
    218:   PetscScalar      *bptr;
    219:   int              info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */
    220:   PetscBool        flg;

    223:   if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact must equal FACTORED");
    224:   PetscObjectTypeCompareAny((PetscObject)B_mpi,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
    225:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix");
    226:   if (X != B_mpi) {
    227:     PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
    228:     if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix");
    229:   }

    231:   if (lu->options.SolveInitialized && !lu->matmatsolve_iscalled) {
    232:     /* communication pattern of SOLVEstruct is unlikely created for matmatsolve,
    233:        thus destroy it and create a new SOLVEstruct.
    234:        Otherwise it may result in memory corruption or incorrect solution
    235:        See src/mat/tests/ex125.c */
    236: #if defined(PETSC_USE_COMPLEX)
    237:     PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct));
    238: #else
    239:     PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct));
    240: #endif
    241:     lu->options.SolveInitialized = NO;
    242:   }
    243:   if (X != B_mpi) {
    244:     MatCopy(B_mpi,X,SAME_NONZERO_PATTERN);
    245:   }

    247:   MatGetSize(B_mpi,NULL,&nrhs);

    249:   PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat));        /* Initialize the statistics variables. */
    250:   MatDenseGetArray(X,&bptr);

    252: #if defined(PETSC_USE_COMPLEX)
    253:   PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,nrhs,&lu->grid, &lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info));
    254: #else
    255:   PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info));
    256: #endif

    258:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info);
    259:   MatDenseRestoreArray(X,&bptr);

    261:   if (lu->options.PrintStat) PetscStackCall("SuperLU_DIST:PStatPrint",PStatPrint(&lu->options, &stat, &lu->grid));  /* Print the statistics. */
    262:   PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat));
    263:   lu->matsolve_iscalled    = PETSC_FALSE;
    264:   lu->matmatsolve_iscalled = PETSC_TRUE;
    265:   return(0);
    266: }

    268: /*
    269:   input:
    270:    F:        numeric Cholesky factor
    271:   output:
    272:    nneg:     total number of negative pivots
    273:    nzero:    total number of zero pivots
    274:    npos:     (global dimension of F) - nneg - nzero
    275: */
    276: static PetscErrorCode MatGetInertia_SuperLU_DIST(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos)
    277: {
    278:   PetscErrorCode   ierr;
    279:   Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data;
    280:   PetscScalar      *diagU=NULL;
    281:   PetscInt         M,i,neg=0,zero=0,pos=0;
    282:   PetscReal        r;

    285:   if (!F->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Matrix factor F is not assembled");
    286:   if (lu->options.RowPerm != NOROWPERM) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must set NOROWPERM");
    287:   MatGetSize(F,&M,NULL);
    288:   PetscMalloc1(M,&diagU);
    289:   MatSuperluDistGetDiagU(F,diagU);
    290:   for (i=0; i<M; i++) {
    291: #if defined(PETSC_USE_COMPLEX)
    292:     r = PetscImaginaryPart(diagU[i])/10.0;
    293:     if (r< -PETSC_MACHINE_EPSILON || r>PETSC_MACHINE_EPSILON) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"diagU[%d]=%g + i %g is non-real",i,PetscRealPart(diagU[i]),r*10.0);
    294:     r = PetscRealPart(diagU[i]);
    295: #else
    296:     r = diagU[i];
    297: #endif
    298:     if (r > 0) {
    299:       pos++;
    300:     } else if (r < 0) {
    301:       neg++;
    302:     } else zero++;
    303:   }

    305:   PetscFree(diagU);
    306:   if (nneg)  *nneg  = neg;
    307:   if (nzero) *nzero = zero;
    308:   if (npos)  *npos  = pos;
    309:   return(0);
    310: }

    312: static PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat F,Mat A,const MatFactorInfo *info)
    313: {
    314:   Mat_SuperLU_DIST  *lu = (Mat_SuperLU_DIST*)F->data;
    315:   Mat               Aloc;
    316:   const PetscScalar *av;
    317:   const PetscInt    *ai=NULL,*aj=NULL;
    318:   PetscInt          nz,dummy;
    319:   int               sinfo;   /* SuperLU_Dist info flag is always an int even with long long indices */
    320:   SuperLUStat_t     stat;
    321:   double            *berr=0;
    322:   PetscBool         ismpiaij,isseqaij,flg;
    323:   PetscErrorCode    ierr;

    326:   PetscObjectBaseTypeCompare((PetscObject)A,MATSEQAIJ,&isseqaij);
    327:   PetscObjectBaseTypeCompare((PetscObject)A,MATMPIAIJ,&ismpiaij);
    328:   if (ismpiaij) {
    329:     MatMPIAIJGetLocalMat(A,MAT_INITIAL_MATRIX,&Aloc);
    330:   } else if (isseqaij) {
    331:     PetscObjectReference((PetscObject)A);
    332:     Aloc = A;
    333:   } else SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Not for type %s",((PetscObject)A)->type_name);

    335:   MatGetRowIJ(Aloc,0,PETSC_FALSE,PETSC_FALSE,&dummy,&ai,&aj,&flg);
    336:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GetRowIJ failed");
    337:   MatSeqAIJGetArrayRead(Aloc,&av);
    338:   nz   = ai[Aloc->rmap->n];

    340:   /* Allocations for A_sup */
    341:   if (lu->options.Fact == DOFACT) { /* first numeric factorization */
    342: #if defined(PETSC_USE_COMPLEX)
    343:     PetscStackCall("SuperLU_DIST:zallocateA_dist",zallocateA_dist(Aloc->rmap->n, nz, &lu->val, &lu->col, &lu->row));
    344: #else
    345:     PetscStackCall("SuperLU_DIST:dallocateA_dist",dallocateA_dist(Aloc->rmap->n, nz, &lu->val, &lu->col, &lu->row));
    346: #endif
    347:   } else { /* successive numeric factorization, sparsity pattern and perm_c are reused. */
    348:     if (lu->FactPattern == SamePattern_SameRowPerm) {
    349:       lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */
    350:     } else if (lu->FactPattern == SamePattern) {
    351:       PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(A->rmap->N, &lu->grid, &lu->LUstruct)); /* Deallocate L and U matrices. */
    352:       lu->options.Fact = SamePattern;
    353:     } else if (lu->FactPattern == DOFACT) {
    354:       PetscStackCall("SuperLU_DIST:Destroy_CompRowLoc_Matrix_dist",Destroy_CompRowLoc_Matrix_dist(&lu->A_sup));
    355:       PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(A->rmap->N, &lu->grid, &lu->LUstruct));
    356:       lu->options.Fact = DOFACT;

    358: #if defined(PETSC_USE_COMPLEX)
    359:       PetscStackCall("SuperLU_DIST:zallocateA_dist",zallocateA_dist(Aloc->rmap->n, nz, &lu->val, &lu->col, &lu->row));
    360: #else
    361:       PetscStackCall("SuperLU_DIST:dallocateA_dist",dallocateA_dist(Aloc->rmap->n, nz, &lu->val, &lu->col, &lu->row));
    362: #endif
    363:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"options.Fact must be one of SamePattern SamePattern_SameRowPerm DOFACT");
    364:   }

    366:   /* Copy AIJ matrix to superlu_dist matrix */
    367:   PetscArraycpy(lu->row,ai,Aloc->rmap->n+1);
    368:   PetscArraycpy(lu->col,aj,nz);
    369:   PetscArraycpy(lu->val,av,nz);
    370:   MatRestoreRowIJ(Aloc,0,PETSC_FALSE,PETSC_FALSE,&dummy,&ai,&aj,&flg);
    371:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"RestoreRowIJ failed");
    372:   MatSeqAIJRestoreArrayRead(Aloc,&av);
    373:   MatDestroy(&Aloc);

    375:   /* Create and setup A_sup */
    376:   if (lu->options.Fact == DOFACT) {
    377: #if defined(PETSC_USE_COMPLEX)
    378:     PetscStackCall("SuperLU_DIST:zCreate_CompRowLoc_Matrix_dist",zCreate_CompRowLoc_Matrix_dist(&lu->A_sup, A->rmap->N, A->cmap->N, nz, A->rmap->n, A->rmap->rstart, lu->val, lu->col, lu->row, SLU_NR_loc, SLU_Z, SLU_GE));
    379: #else
    380:     PetscStackCall("SuperLU_DIST:dCreate_CompRowLoc_Matrix_dist",dCreate_CompRowLoc_Matrix_dist(&lu->A_sup, A->rmap->N, A->cmap->N, nz, A->rmap->n, A->rmap->rstart, lu->val, lu->col, lu->row, SLU_NR_loc, SLU_D, SLU_GE));
    381: #endif
    382:   }

    384:   /* Factor the matrix. */
    385:   PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat));   /* Initialize the statistics variables. */
    386: #if defined(PETSC_USE_COMPLEX)
    387:   PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, A->rmap->n, 0, &lu->grid, &lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo));
    388: #else
    389:   PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, A->rmap->n, 0, &lu->grid, &lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo));
    390: #endif

    392:   if (sinfo > 0) {
    393:     if (A->erroriffailure) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot in row %D",sinfo);
    394:     else {
    395:       if (sinfo <= lu->A_sup.ncol) {
    396:         F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    397:         PetscInfo1(F,"U(i,i) is exactly zero, i= %D\n",sinfo);
    398:       } else if (sinfo > lu->A_sup.ncol) {
    399:         /*
    400:          number of bytes allocated when memory allocation
    401:          failure occurred, plus A->ncol.
    402:          */
    403:         F->factorerrortype = MAT_FACTOR_OUTMEMORY;
    404:         PetscInfo1(F,"Number of bytes allocated when memory allocation fails %D\n",sinfo);
    405:       }
    406:     }
    407:   } else if (sinfo < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB, "info = %D, argument in p*gssvx() had an illegal value", sinfo);

    409:   if (lu->options.PrintStat) {
    410:     PetscStackCall("SuperLU_DIST:PStatPrint",PStatPrint(&lu->options, &stat, &lu->grid));  /* Print the statistics. */
    411:   }
    412:   PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat));
    413:   F->assembled     = PETSC_TRUE;
    414:   F->preallocated  = PETSC_TRUE;
    415:   lu->options.Fact = FACTORED; /* The factored form of A is supplied. Local option used by this func. only */
    416:   return(0);
    417: }

    419: /* Note the Petsc r and c permutations are ignored */
    420: static PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
    421: {
    422:   Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data;
    423:   PetscInt         M   = A->rmap->N,N=A->cmap->N;

    426:   /* Initialize ScalePermstruct and LUstruct. */
    427:   PetscStackCall("SuperLU_DIST:ScalePermstructInit",ScalePermstructInit(M, N, &lu->ScalePermstruct));
    428:   PetscStackCall("SuperLU_DIST:LUstructInit",LUstructInit(N, &lu->LUstruct));
    429:   F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU_DIST;
    430:   F->ops->solve           = MatSolve_SuperLU_DIST;
    431:   F->ops->matsolve        = MatMatSolve_SuperLU_DIST;
    432:   F->ops->getinertia      = NULL;

    434:   if (A->symmetric || A->hermitian) F->ops->getinertia = MatGetInertia_SuperLU_DIST;
    435:   lu->CleanUpSuperLU_Dist = PETSC_TRUE;
    436:   return(0);
    437: }

    439: static PetscErrorCode MatCholeskyFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,const MatFactorInfo *info)
    440: {

    444:   MatLUFactorSymbolic_SuperLU_DIST(F,A,r,r,info);
    445:   F->ops->choleskyfactornumeric = MatLUFactorNumeric_SuperLU_DIST;
    446:   return(0);
    447: }

    449: static PetscErrorCode MatFactorGetSolverType_aij_superlu_dist(Mat A,MatSolverType *type)
    450: {
    452:   *type = MATSOLVERSUPERLU_DIST;
    453:   return(0);
    454: }

    456: static PetscErrorCode MatView_Info_SuperLU_DIST(Mat A,PetscViewer viewer)
    457: {
    458:   Mat_SuperLU_DIST       *lu=(Mat_SuperLU_DIST*)A->data;
    459:   superlu_dist_options_t options;
    460:   PetscErrorCode         ierr;

    463:   /* check if matrix is superlu_dist type */
    464:   if (A->ops->solve != MatSolve_SuperLU_DIST) return(0);

    466:   options = lu->options;
    467:   PetscViewerASCIIPrintf(viewer,"SuperLU_DIST run parameters:\n");
    468:   PetscViewerASCIIPrintf(viewer,"  Process grid nprow %D x npcol %D \n",lu->nprow,lu->npcol);
    469:   PetscViewerASCIIPrintf(viewer,"  Equilibrate matrix %s \n",PetscBools[options.Equil != NO]);
    470:   PetscViewerASCIIPrintf(viewer,"  Replace tiny pivots %s \n",PetscBools[options.ReplaceTinyPivot != NO]);
    471:   PetscViewerASCIIPrintf(viewer,"  Use iterative refinement %s \n",PetscBools[options.IterRefine == SLU_DOUBLE]);
    472:   PetscViewerASCIIPrintf(viewer,"  Processors in row %d col partition %d \n",lu->nprow,lu->npcol);

    474:   switch (options.RowPerm) {
    475:   case NOROWPERM:
    476:     PetscViewerASCIIPrintf(viewer,"  Row permutation NOROWPERM\n");
    477:     break;
    478:   case LargeDiag_MC64:
    479:     PetscViewerASCIIPrintf(viewer,"  Row permutation LargeDiag_MC64\n");
    480:     break;
    481:   case LargeDiag_AWPM:
    482:     PetscViewerASCIIPrintf(viewer,"  Row permutation LargeDiag_AWPM\n");
    483:     break;
    484:   case MY_PERMR:
    485:     PetscViewerASCIIPrintf(viewer,"  Row permutation MY_PERMR\n");
    486:     break;
    487:   default:
    488:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation");
    489:   }

    491:   switch (options.ColPerm) {
    492:   case NATURAL:
    493:     PetscViewerASCIIPrintf(viewer,"  Column permutation NATURAL\n");
    494:     break;
    495:   case MMD_AT_PLUS_A:
    496:     PetscViewerASCIIPrintf(viewer,"  Column permutation MMD_AT_PLUS_A\n");
    497:     break;
    498:   case MMD_ATA:
    499:     PetscViewerASCIIPrintf(viewer,"  Column permutation MMD_ATA\n");
    500:     break;
    501:   /*  Even though this is called METIS, the SuperLU_DIST code sets this by default if PARMETIS is defined, not METIS */
    502:   case METIS_AT_PLUS_A:
    503:     PetscViewerASCIIPrintf(viewer,"  Column permutation METIS_AT_PLUS_A\n");
    504:     break;
    505:   case PARMETIS:
    506:     PetscViewerASCIIPrintf(viewer,"  Column permutation PARMETIS\n");
    507:     break;
    508:   default:
    509:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation");
    510:   }

    512:   PetscViewerASCIIPrintf(viewer,"  Parallel symbolic factorization %s \n",PetscBools[options.ParSymbFact != NO]);

    514:   if (lu->FactPattern == SamePattern) {
    515:     PetscViewerASCIIPrintf(viewer,"  Repeated factorization SamePattern\n");
    516:   } else if (lu->FactPattern == SamePattern_SameRowPerm) {
    517:     PetscViewerASCIIPrintf(viewer,"  Repeated factorization SamePattern_SameRowPerm\n");
    518:   } else if (lu->FactPattern == DOFACT) {
    519:     PetscViewerASCIIPrintf(viewer,"  Repeated factorization DOFACT\n");
    520:   } else {
    521:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown factorization pattern");
    522:   }
    523:   return(0);
    524: }

    526: static PetscErrorCode MatView_SuperLU_DIST(Mat A,PetscViewer viewer)
    527: {
    528:   PetscErrorCode    ierr;
    529:   PetscBool         iascii;
    530:   PetscViewerFormat format;

    533:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    534:   if (iascii) {
    535:     PetscViewerGetFormat(viewer,&format);
    536:     if (format == PETSC_VIEWER_ASCII_INFO) {
    537:       MatView_Info_SuperLU_DIST(A,viewer);
    538:     }
    539:   }
    540:   return(0);
    541: }

    543: static PetscErrorCode MatGetFactor_aij_superlu_dist(Mat A,MatFactorType ftype,Mat *F)
    544: {
    545:   Mat                    B;
    546:   Mat_SuperLU_DIST       *lu;
    547:   PetscErrorCode         ierr;
    548:   PetscInt               M=A->rmap->N,N=A->cmap->N,indx;
    549:   PetscMPIInt            size;
    550:   superlu_dist_options_t options;
    551:   PetscBool              flg;
    552:   const char             *colperm[]     = {"NATURAL","MMD_AT_PLUS_A","MMD_ATA","METIS_AT_PLUS_A","PARMETIS"};
    553:   const char             *rowperm[]     = {"NOROWPERM","LargeDiag_MC64","LargeDiag_AWPM","MY_PERMR"};
    554:   const char             *factPattern[] = {"SamePattern","SamePattern_SameRowPerm","DOFACT"};
    555:   PetscBool              set;

    558:   /* Create the factorization matrix */
    559:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    560:   MatSetSizes(B,A->rmap->n,A->cmap->n,M,N);
    561:   PetscStrallocpy("superlu_dist",&((PetscObject)B)->type_name);
    562:   MatSetUp(B);
    563:   B->ops->getinfo = MatGetInfo_External;
    564:   B->ops->view    = MatView_SuperLU_DIST;
    565:   B->ops->destroy = MatDestroy_SuperLU_DIST;

    567:   /* Set the default input options:
    568:      options.Fact              = DOFACT;
    569:      options.Equil             = YES;
    570:      options.ParSymbFact       = NO;
    571:      options.ColPerm           = METIS_AT_PLUS_A;
    572:      options.RowPerm           = LargeDiag_MC64;
    573:      options.ReplaceTinyPivot  = YES;
    574:      options.IterRefine        = DOUBLE;
    575:      options.Trans             = NOTRANS;
    576:      options.SolveInitialized  = NO; -hold the communication pattern used MatSolve() and MatMatSolve()
    577:      options.RefineInitialized = NO;
    578:      options.PrintStat         = YES;
    579:      options.SymPattern        = NO;
    580:   */
    581:   set_default_options_dist(&options);

    583:   if (ftype == MAT_FACTOR_LU) {
    584:     B->factortype = MAT_FACTOR_LU;
    585:     B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST;
    586:   } else {
    587:     B->factortype = MAT_FACTOR_CHOLESKY;
    588:     B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SuperLU_DIST;
    589:     options.SymPattern = YES;
    590:   }

    592:   /* set solvertype */
    593:   PetscFree(B->solvertype);
    594:   PetscStrallocpy(MATSOLVERSUPERLU_DIST,&B->solvertype);

    596:   PetscNewLog(B,&lu);
    597:   B->data = lu;
    598:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);

    600:   {
    601:     PetscMPIInt       flg;
    602:     MPI_Comm          comm;
    603:     PetscSuperLU_DIST *context = NULL;

    605:     PetscObjectGetComm((PetscObject)A,&comm);
    606:     if (Petsc_Superlu_dist_keyval == MPI_KEYVAL_INVALID) {
    607:       MPI_Comm_create_keyval(MPI_COMM_NULL_COPY_FN,Petsc_Superlu_dist_keyval_Delete_Fn,&Petsc_Superlu_dist_keyval,(void*)0);
    608:       PetscRegisterFinalize(Petsc_Superlu_dist_keyval_free);
    609:     }
    610:     MPI_Comm_get_attr(comm,Petsc_Superlu_dist_keyval,&context,&flg);
    611:     if (!flg || context->busy) {
    612:       if (!flg) {
    613:         PetscNew(&context);
    614:         context->busy = PETSC_TRUE;
    615:         MPI_Comm_dup(comm,&context->comm);
    616:         MPI_Comm_set_attr(comm,Petsc_Superlu_dist_keyval,context);
    617:       } else {
    618:         MPI_Comm_dup(comm,&lu->comm_superlu);
    619:       }

    621:       /* Default num of process columns and rows */
    622:       lu->nprow = (int_t) (0.5 + PetscSqrtReal((PetscReal)size));
    623:       if (!lu->nprow) lu->nprow = 1;
    624:       while (lu->nprow > 0) {
    625:         lu->npcol = (int_t) (size/lu->nprow);
    626:         if (size == lu->nprow * lu->npcol) break;
    627:         lu->nprow--;
    628:       }
    629:       PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU_Dist Options","Mat");
    630:       PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,(PetscInt*)&lu->nprow,NULL);
    631:       PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,(PetscInt*)&lu->npcol,NULL);
    632:       PetscOptionsEnd();
    633:       if (size != lu->nprow * lu->npcol) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol);
    634:       PetscStackCall("SuperLU_DIST:superlu_gridinit",superlu_gridinit(context ? context->comm : lu->comm_superlu, lu->nprow, lu->npcol, &lu->grid));
    635:       if (context) context->grid = lu->grid;
    636:       PetscInfo(NULL,"Duplicating a communicator for SuperLU_DIST and calling superlu_gridinit()\n");
    637:       if (!flg) {
    638:         PetscInfo(NULL,"Storing communicator and SuperLU_DIST grid in communicator attribute\n");
    639:       } else {
    640:         PetscInfo(NULL,"Communicator attribute already in use so not saving communicator and SuperLU_DIST grid in communicator attribute \n");
    641:       }
    642:     } else {
    643:       PetscInfo(NULL,"Reusing communicator and superlu_gridinit() for SuperLU_DIST from communicator attribute.");
    644:       context->busy = PETSC_TRUE;
    645:       lu->grid      = context->grid;
    646:     }
    647:   }

    649:   PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU_Dist Options","Mat");
    650:   PetscOptionsBool("-mat_superlu_dist_equil","Equilibrate matrix","None",options.Equil ? PETSC_TRUE : PETSC_FALSE,&flg,&set);
    651:   if (set && !flg) options.Equil = NO;

    653:   PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",rowperm,4,rowperm[1],&indx,&flg);
    654:   if (flg) {
    655:     switch (indx) {
    656:     case 0:
    657:       options.RowPerm = NOROWPERM;
    658:       break;
    659:     case 1:
    660:       options.RowPerm = LargeDiag_MC64;
    661:       break;
    662:     case 2:
    663:       options.RowPerm = LargeDiag_AWPM;
    664:       break;
    665:     case 3:
    666:       options.RowPerm = MY_PERMR;
    667:       break;
    668:     default:
    669:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown row permutation");
    670:     }
    671:   }

    673:   PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",colperm,5,colperm[3],&indx,&flg);
    674:   if (flg) {
    675:     switch (indx) {
    676:     case 0:
    677:       options.ColPerm = NATURAL;
    678:       break;
    679:     case 1:
    680:       options.ColPerm = MMD_AT_PLUS_A;
    681:       break;
    682:     case 2:
    683:       options.ColPerm = MMD_ATA;
    684:       break;
    685:     case 3:
    686:       options.ColPerm = METIS_AT_PLUS_A;
    687:       break;
    688:     case 4:
    689:       options.ColPerm = PARMETIS;   /* only works for np>1 */
    690:       break;
    691:     default:
    692:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation");
    693:     }
    694:   }

    696:   options.ReplaceTinyPivot = NO;
    697:   PetscOptionsBool("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",options.ReplaceTinyPivot ? PETSC_TRUE : PETSC_FALSE,&flg,&set);
    698:   if (set && flg) options.ReplaceTinyPivot = YES;

    700:   options.ParSymbFact = NO;
    701:   PetscOptionsBool("-mat_superlu_dist_parsymbfact","Parallel symbolic factorization","None",PETSC_FALSE,&flg,&set);
    702:   if (set && flg && size>1) {
    703: #if defined(PETSC_HAVE_PARMETIS)
    704:     options.ParSymbFact = YES;
    705:     options.ColPerm     = PARMETIS;   /* in v2.2, PARMETIS is forced for ParSymbFact regardless of user ordering setting */
    706: #else
    707:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"parsymbfact needs PARMETIS");
    708: #endif
    709:   }

    711:   lu->FactPattern = SamePattern;
    712:   PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,3,factPattern[0],&indx,&flg);
    713:   if (flg) {
    714:     switch (indx) {
    715:     case 0:
    716:       lu->FactPattern = SamePattern;
    717:       break;
    718:     case 1:
    719:       lu->FactPattern = SamePattern_SameRowPerm;
    720:       break;
    721:     case 2:
    722:       lu->FactPattern = DOFACT;
    723:       break;
    724:     }
    725:   }

    727:   options.IterRefine = NOREFINE;
    728:   PetscOptionsBool("-mat_superlu_dist_iterrefine","Use iterative refinement","None",options.IterRefine == NOREFINE ? PETSC_FALSE : PETSC_TRUE ,&flg,&set);
    729:   if (set) {
    730:     if (flg) options.IterRefine = SLU_DOUBLE;
    731:     else options.IterRefine = NOREFINE;
    732:   }

    734:   if (PetscLogPrintInfo) options.PrintStat = YES;
    735:   else options.PrintStat = NO;
    736:   PetscOptionsBool("-mat_superlu_dist_statprint","Print factorization information","None",(PetscBool)options.PrintStat,(PetscBool*)&options.PrintStat,NULL);
    737:   PetscOptionsEnd();

    739:   lu->options              = options;
    740:   lu->options.Fact         = DOFACT;
    741:   lu->matsolve_iscalled    = PETSC_FALSE;
    742:   lu->matmatsolve_iscalled = PETSC_FALSE;

    744:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_aij_superlu_dist);
    745:   PetscObjectComposeFunction((PetscObject)B,"MatSuperluDistGetDiagU_C",MatSuperluDistGetDiagU_SuperLU_DIST);

    747:   *F = B;
    748:   return(0);
    749: }

    751: PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_SuperLU_DIST(void)
    752: {
    755:   MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ,MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);
    756:   MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);
    757:   MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_superlu_dist);
    758:   MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_superlu_dist);
    759:   return(0);
    760: }

    762: /*MC
    763:   MATSOLVERSUPERLU_DIST - Parallel direct solver package for LU factorization

    765:   Use ./configure --download-superlu_dist --download-parmetis --download-metis --download-ptscotch  to have PETSc installed with SuperLU_DIST

    767:   Use -pc_type lu -pc_factor_mat_solver_type superlu_dist to use this direct solver

    769:    Works with AIJ matrices

    771:   Options Database Keys:
    772: + -mat_superlu_dist_r <n> - number of rows in processor partition
    773: . -mat_superlu_dist_c <n> - number of columns in processor partition
    774: . -mat_superlu_dist_equil - equilibrate the matrix
    775: . -mat_superlu_dist_rowperm <NOROWPERM,LargeDiag_MC64,LargeDiag_AWPM,MY_PERMR> - row permutation
    776: . -mat_superlu_dist_colperm <NATURAL,MMD_AT_PLUS_A,MMD_ATA,METIS_AT_PLUS_A,PARMETIS> - column permutation
    777: . -mat_superlu_dist_replacetinypivot - replace tiny pivots
    778: . -mat_superlu_dist_fact <SamePattern> - (choose one of) SamePattern SamePattern_SameRowPerm DOFACT
    779: . -mat_superlu_dist_iterrefine - use iterative refinement
    780: - -mat_superlu_dist_statprint - print factorization information

    782:    Level: beginner

    784: .seealso: PCLU

    786: .seealso: PCFactorSetMatSolverType(), MatSolverType

    788: M*/