Actual source code: matimpl.h
petsc-3.13.6 2020-09-29
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      2: #ifndef __MATIMPL_H

      5:  #include <petscmat.h>
      6:  #include <petscmatcoarsen.h>
      7:  #include <petsc/private/petscimpl.h>

      9: PETSC_EXTERN PetscBool MatRegisterAllCalled;
     10: PETSC_EXTERN PetscBool MatSeqAIJRegisterAllCalled;
     11: PETSC_EXTERN PetscBool MatOrderingRegisterAllCalled;
     12: PETSC_EXTERN PetscBool MatColoringRegisterAllCalled;
     13: PETSC_EXTERN PetscBool MatPartitioningRegisterAllCalled;
     14: PETSC_EXTERN PetscBool MatCoarsenRegisterAllCalled;
     15: PETSC_EXTERN PetscErrorCode MatRegisterAll(void);
     16: PETSC_EXTERN PetscErrorCode MatOrderingRegisterAll(void);
     17: PETSC_EXTERN PetscErrorCode MatColoringRegisterAll(void);
     18: PETSC_EXTERN PetscErrorCode MatPartitioningRegisterAll(void);
     19: PETSC_EXTERN PetscErrorCode MatCoarsenRegisterAll(void);
     20: PETSC_EXTERN PetscErrorCode MatSeqAIJRegisterAll(void);

     22: /*
     23:   This file defines the parts of the matrix data structure that are
     24:   shared by all matrix types.
     25: */

     27: /*
     28:     If you add entries here also add them to the MATOP enum
     29:     in include/petscmat.h and src/mat/f90-mod/petscmat.h
     30: */
     31: typedef struct _MatOps *MatOps;
     32: struct _MatOps {
     33:   /* 0*/
     34:   PetscErrorCode (*setvalues)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
     35:   PetscErrorCode (*getrow)(Mat,PetscInt,PetscInt *,PetscInt*[],PetscScalar*[]);
     36:   PetscErrorCode (*restorerow)(Mat,PetscInt,PetscInt *,PetscInt *[],PetscScalar *[]);
     37:   PetscErrorCode (*mult)(Mat,Vec,Vec);
     38:   PetscErrorCode (*multadd)(Mat,Vec,Vec,Vec);
     39:   /* 5*/
     40:   PetscErrorCode (*multtranspose)(Mat,Vec,Vec);
     41:   PetscErrorCode (*multtransposeadd)(Mat,Vec,Vec,Vec);
     42:   PetscErrorCode (*solve)(Mat,Vec,Vec);
     43:   PetscErrorCode (*solveadd)(Mat,Vec,Vec,Vec);
     44:   PetscErrorCode (*solvetranspose)(Mat,Vec,Vec);
     45:   /*10*/
     46:   PetscErrorCode (*solvetransposeadd)(Mat,Vec,Vec,Vec);
     47:   PetscErrorCode (*lufactor)(Mat,IS,IS,const MatFactorInfo*);
     48:   PetscErrorCode (*choleskyfactor)(Mat,IS,const MatFactorInfo*);
     49:   PetscErrorCode (*sor)(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
     50:   PetscErrorCode (*transpose)(Mat,MatReuse,Mat *);
     51:   /*15*/
     52:   PetscErrorCode (*getinfo)(Mat,MatInfoType,MatInfo*);
     53:   PetscErrorCode (*equal)(Mat,Mat,PetscBool  *);
     54:   PetscErrorCode (*getdiagonal)(Mat,Vec);
     55:   PetscErrorCode (*diagonalscale)(Mat,Vec,Vec);
     56:   PetscErrorCode (*norm)(Mat,NormType,PetscReal*);
     57:   /*20*/
     58:   PetscErrorCode (*assemblybegin)(Mat,MatAssemblyType);
     59:   PetscErrorCode (*assemblyend)(Mat,MatAssemblyType);
     60:   PetscErrorCode (*setoption)(Mat,MatOption,PetscBool );
     61:   PetscErrorCode (*zeroentries)(Mat);
     62:   /*24*/
     63:   PetscErrorCode (*zerorows)(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
     64:   PetscErrorCode (*lufactorsymbolic)(Mat,Mat,IS,IS,const MatFactorInfo*);
     65:   PetscErrorCode (*lufactornumeric)(Mat,Mat,const MatFactorInfo*);
     66:   PetscErrorCode (*choleskyfactorsymbolic)(Mat,Mat,IS,const MatFactorInfo*);
     67:   PetscErrorCode (*choleskyfactornumeric)(Mat,Mat,const MatFactorInfo*);
     68:   /*29*/
     69:   PetscErrorCode (*setup)(Mat);
     70:   PetscErrorCode (*ilufactorsymbolic)(Mat,Mat,IS,IS,const MatFactorInfo*);
     71:   PetscErrorCode (*iccfactorsymbolic)(Mat,Mat,IS,const MatFactorInfo*);
     72:   PetscErrorCode (*getdiagonalblock)(Mat,Mat*);
     73:   PetscErrorCode (*freeintermediatedatastructures)(Mat);
     74:   /*34*/
     75:   PetscErrorCode (*duplicate)(Mat,MatDuplicateOption,Mat*);
     76:   PetscErrorCode (*forwardsolve)(Mat,Vec,Vec);
     77:   PetscErrorCode (*backwardsolve)(Mat,Vec,Vec);
     78:   PetscErrorCode (*ilufactor)(Mat,IS,IS,const MatFactorInfo*);
     79:   PetscErrorCode (*iccfactor)(Mat,IS,const MatFactorInfo*);
     80:   /*39*/
     81:   PetscErrorCode (*axpy)(Mat,PetscScalar,Mat,MatStructure);
     82:   PetscErrorCode (*createsubmatrices)(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
     83:   PetscErrorCode (*increaseoverlap)(Mat,PetscInt,IS[],PetscInt);
     84:   PetscErrorCode (*getvalues)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
     85:   PetscErrorCode (*copy)(Mat,Mat,MatStructure);
     86:   /*44*/
     87:   PetscErrorCode (*getrowmax)(Mat,Vec,PetscInt[]);
     88:   PetscErrorCode (*scale)(Mat,PetscScalar);
     89:   PetscErrorCode (*shift)(Mat,PetscScalar);
     90:   PetscErrorCode (*diagonalset)(Mat,Vec,InsertMode);
     91:   PetscErrorCode (*zerorowscolumns)(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
     92:   /*49*/
     93:   PetscErrorCode (*setrandom)(Mat,PetscRandom);
     94:   PetscErrorCode (*getrowij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool  *);
     95:   PetscErrorCode (*restorerowij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt *,const PetscInt *[],const PetscInt *[],PetscBool  *);
     96:   PetscErrorCode (*getcolumnij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool  *);
     97:   PetscErrorCode (*restorecolumnij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool  *);
     98:   /*54*/
     99:   PetscErrorCode (*fdcoloringcreate)(Mat,ISColoring,MatFDColoring);
    100:   PetscErrorCode (*coloringpatch)(Mat,PetscInt,PetscInt,ISColoringValue[],ISColoring*);
    101:   PetscErrorCode (*setunfactored)(Mat);
    102:   PetscErrorCode (*permute)(Mat,IS,IS,Mat*);
    103:   PetscErrorCode (*setvaluesblocked)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    104:   /*59*/
    105:   PetscErrorCode (*createsubmatrix)(Mat,IS,IS,MatReuse,Mat*);
    106:   PetscErrorCode (*destroy)(Mat);
    107:   PetscErrorCode (*view)(Mat,PetscViewer);
    108:   PetscErrorCode (*convertfrom)(Mat,MatType,MatReuse,Mat*);
    109:   PetscErrorCode (*placeholder_63)(Mat);
    110:   /*64*/
    111:   PetscErrorCode (*matmatmultsymbolic)(Mat,Mat,Mat,PetscReal,Mat);
    112:   PetscErrorCode (*matmatmultnumeric)(Mat,Mat,Mat,Mat);
    113:   PetscErrorCode (*setlocaltoglobalmapping)(Mat,ISLocalToGlobalMapping,ISLocalToGlobalMapping);
    114:   PetscErrorCode (*setvalueslocal)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    115:   PetscErrorCode (*zerorowslocal)(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
    116:   /*69*/
    117:   PetscErrorCode (*getrowmaxabs)(Mat,Vec,PetscInt[]);
    118:   PetscErrorCode (*getrowminabs)(Mat,Vec,PetscInt[]);
    119:   PetscErrorCode (*convert)(Mat, MatType,MatReuse,Mat*);
    120:   PetscErrorCode (*hasoperation)(Mat,MatOperation,PetscBool*);
    121:   PetscErrorCode (*placeholder_73)(Mat,void*);
    122:   /*74*/
    123:   PetscErrorCode (*setvaluesadifor)(Mat,PetscInt,void*);
    124:   PetscErrorCode (*fdcoloringapply)(Mat,MatFDColoring,Vec,void*);
    125:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,Mat);
    126:   PetscErrorCode (*multconstrained)(Mat,Vec,Vec);
    127:   PetscErrorCode (*multtransposeconstrained)(Mat,Vec,Vec);
    128:   /*79*/
    129:   PetscErrorCode (*findzerodiagonals)(Mat,IS*);
    130:   PetscErrorCode (*mults)(Mat, Vecs, Vecs);
    131:   PetscErrorCode (*solves)(Mat, Vecs, Vecs);
    132:   PetscErrorCode (*getinertia)(Mat,PetscInt*,PetscInt*,PetscInt*);
    133:   PetscErrorCode (*load)(Mat, PetscViewer);
    134:   /*84*/
    135:   PetscErrorCode (*issymmetric)(Mat,PetscReal,PetscBool *);
    136:   PetscErrorCode (*ishermitian)(Mat,PetscReal,PetscBool *);
    137:   PetscErrorCode (*isstructurallysymmetric)(Mat,PetscBool *);
    138:   PetscErrorCode (*setvaluesblockedlocal)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    139:   PetscErrorCode (*getvecs)(Mat,Vec*,Vec*);
    140:   /*89*/
    141:   PetscErrorCode (*placeholder_89)(Mat,void*);
    142:   PetscErrorCode (*matmultsymbolic)(Mat,Mat,PetscReal,Mat);
    143:   PetscErrorCode (*matmultnumeric)(Mat,Mat,Mat);
    144:   PetscErrorCode (*placeholder_92)(Mat,void*);
    145:   PetscErrorCode (*ptapsymbolic)(Mat,Mat,PetscReal,Mat); /* double dispatch wrapper routine */
    146:   /*94*/
    147:   PetscErrorCode (*ptapnumeric)(Mat,Mat,Mat);            /* double dispatch wrapper routine */
    148:   PetscErrorCode (*placeholder_95)(Mat,void*);
    149:   PetscErrorCode (*mattransposemultsymbolic)(Mat,Mat,PetscReal,Mat);
    150:   PetscErrorCode (*mattransposemultnumeric)(Mat,Mat,Mat);
    151:   PetscErrorCode (*bindtocpu)(Mat,PetscBool);
    152:   /*99*/
    153:   PetscErrorCode (*productsetfromoptions)(Mat);
    154:   PetscErrorCode (*productsymbolic)(Mat);
    155:   PetscErrorCode (*productnumeric)(Mat);
    156:   PetscErrorCode (*conjugate)(Mat);                              /* complex conjugate */
    157:   PetscErrorCode (*viewnative)(Mat,PetscViewer);
    158:   /*104*/
    159:   PetscErrorCode (*setvaluesrow)(Mat,PetscInt,const PetscScalar[]);
    160:   PetscErrorCode (*realpart)(Mat);
    161:   PetscErrorCode (*imaginarypart)(Mat);
    162:   PetscErrorCode (*getrowuppertriangular)(Mat);
    163:   PetscErrorCode (*restorerowuppertriangular)(Mat);
    164:   /*109*/
    165:   PetscErrorCode (*matsolve)(Mat,Mat,Mat);
    166:   PetscErrorCode (*matsolvetranspose)(Mat,Mat,Mat);
    167:   PetscErrorCode (*getrowmin)(Mat,Vec,PetscInt[]);
    168:   PetscErrorCode (*getcolumnvector)(Mat,Vec,PetscInt);
    169:   PetscErrorCode (*missingdiagonal)(Mat,PetscBool *,PetscInt*);
    170:   /*114*/
    171:   PetscErrorCode (*getseqnonzerostructure)(Mat,Mat *);
    172:   PetscErrorCode (*create)(Mat);
    173:   PetscErrorCode (*getghosts)(Mat,PetscInt*,const PetscInt *[]);
    174:   PetscErrorCode (*getlocalsubmatrix)(Mat,IS,IS,Mat*);
    175:   PetscErrorCode (*restorelocalsubmatrix)(Mat,IS,IS,Mat*);
    176:   /*119*/
    177:   PetscErrorCode (*multdiagonalblock)(Mat,Vec,Vec);
    178:   PetscErrorCode (*hermitiantranspose)(Mat,MatReuse,Mat*);
    179:   PetscErrorCode (*multhermitiantranspose)(Mat,Vec,Vec);
    180:   PetscErrorCode (*multhermitiantransposeadd)(Mat,Vec,Vec,Vec);
    181:   PetscErrorCode (*getmultiprocblock)(Mat,MPI_Comm,MatReuse,Mat*);
    182:   /*124*/
    183:   PetscErrorCode (*findnonzerorows)(Mat,IS*);
    184:   PetscErrorCode (*getcolumnnorms)(Mat,NormType,PetscReal*);
    185:   PetscErrorCode (*invertblockdiagonal)(Mat,const PetscScalar**);
    186:   PetscErrorCode (*invertvariableblockdiagonal)(Mat,PetscInt,const PetscInt*,PetscScalar*);
    187:   PetscErrorCode (*createsubmatricesmpi)(Mat,PetscInt,const IS[], const IS[], MatReuse, Mat**);
    188:   /*129*/
    189:   PetscErrorCode (*setvaluesbatch)(Mat,PetscInt,PetscInt,PetscInt*,const PetscScalar*);
    190:   PetscErrorCode (*placeholder_130)(Mat,void*);
    191:   PetscErrorCode (*transposematmultsymbolic)(Mat,Mat,PetscReal,Mat);
    192:   PetscErrorCode (*transposematmultnumeric)(Mat,Mat,Mat);
    193:   PetscErrorCode (*transposecoloringcreate)(Mat,ISColoring,MatTransposeColoring);
    194:   /*134*/
    195:   PetscErrorCode (*transcoloringapplysptoden)(MatTransposeColoring,Mat,Mat);
    196:   PetscErrorCode (*transcoloringapplydentosp)(MatTransposeColoring,Mat,Mat);
    197:   PetscErrorCode (*placeholder_136)(Mat,void*);
    198:   PetscErrorCode (*rartsymbolic)(Mat,Mat,PetscReal,Mat); /* double dispatch wrapper routine */
    199:   PetscErrorCode (*rartnumeric)(Mat,Mat,Mat);            /* double dispatch wrapper routine */
    200:   /*139*/
    201:   PetscErrorCode (*setblocksizes)(Mat,PetscInt,PetscInt);
    202:   PetscErrorCode (*aypx)(Mat,PetscScalar,Mat,MatStructure);
    203:   PetscErrorCode (*residual)(Mat,Vec,Vec,Vec);
    204:   PetscErrorCode (*fdcoloringsetup)(Mat,ISColoring,MatFDColoring);
    205:   PetscErrorCode (*findoffblockdiagonalentries)(Mat,IS*);
    206:   PetscErrorCode (*creatempimatconcatenateseqmat)(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
    207:   /*145*/
    208:   PetscErrorCode (*destroysubmatrices)(PetscInt,Mat*[]);
    209:   PetscErrorCode (*mattransposesolve)(Mat,Mat,Mat);
    210:   PetscErrorCode (*getvalueslocal)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar[]);
    211: };
    212: /*
    213:     If you add MatOps entries above also add them to the MATOP enum
    214:     in include/petscmat.h and src/mat/f90-mod/petscmat.h
    215: */

    217:  #include <petscsys.h>
    218: PETSC_EXTERN PetscErrorCode MatRegisterOp(MPI_Comm, const char[], PetscVoidFunction, const char[], PetscInt, ...);
    219: PETSC_EXTERN PetscErrorCode MatQueryOp(MPI_Comm, PetscVoidFunction*, const char[], PetscInt, ...);

    221: typedef struct _p_MatRootName* MatRootName;
    222: struct _p_MatRootName {
    223:   char        *rname,*sname,*mname;
    224:   MatRootName next;
    225: };

    227: PETSC_EXTERN MatRootName MatRootNameList;

    229: /*
    230:    Utility private matrix routines
    231: */
    232: PETSC_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat,PetscBool,PetscReal,IS*);
    233: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat,MatType,MatReuse,Mat*);
    234: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat,MatType,MatReuse,Mat*);
    235: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat,MatType,MatReuse,Mat*);
    236: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat,Mat,MatStructure);
    237: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat,Vec,InsertMode);

    239: PETSC_INTERN PetscErrorCode MatProductSymbolic_Basic(Mat);
    240: PETSC_EXTERN PetscErrorCode MatProductSymbolic_AB(Mat);
    241: PETSC_EXTERN PetscErrorCode MatProductNumeric_AB(Mat);
    242: PETSC_EXTERN PetscErrorCode MatProductSymbolic_AtB(Mat);
    243: PETSC_EXTERN PetscErrorCode MatProductNumeric_AtB(Mat);
    244: PETSC_EXTERN PetscErrorCode MatProductSymbolic_ABt(Mat);
    245: PETSC_EXTERN PetscErrorCode MatProductNumeric_ABt(Mat);
    246: PETSC_EXTERN PetscErrorCode MatProductNumeric_PtAP(Mat);
    247: PETSC_EXTERN PetscErrorCode MatProductNumeric_RARt(Mat);
    248: PETSC_EXTERN PetscErrorCode MatProductSymbolic_ABC(Mat);
    249: PETSC_EXTERN PetscErrorCode MatProductNumeric_ABC(Mat);
    250: PETSC_EXTERN PetscErrorCode MatProductCreate_Private(Mat,Mat,Mat,Mat);

    252: #if defined(PETSC_USE_DEBUG)
    253: #  define MatCheckPreallocated(A,arg) do {                              \
    254:     if (PetscUnlikely(!(A)->preallocated)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatXXXSetPreallocation() or MatSetUp() on argument %D \"%s\" before %s()",(arg),#A,PETSC_FUNCTION_NAME); \
    255:   } while (0)
    256: #else
    257: #  define MatCheckPreallocated(A,arg) do {} while (0)
    258: #endif

    260: /*
    261:   The stash is used to temporarily store inserted matrix values that
    262:   belong to another processor. During the assembly phase the stashed
    263:   values are moved to the correct processor and
    264: */

    266: typedef struct _MatStashSpace *PetscMatStashSpace;

    268: struct _MatStashSpace {
    269:   PetscMatStashSpace next;
    270:   PetscScalar        *space_head,*val;
    271:   PetscInt           *idx,*idy;
    272:   PetscInt           total_space_size;
    273:   PetscInt           local_used;
    274:   PetscInt           local_remaining;
    275: };

    277: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt,PetscInt,PetscMatStashSpace *);
    278: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt,PetscMatStashSpace *,PetscScalar *,PetscInt *,PetscInt *);
    279: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace*);

    281: typedef struct {
    282:   PetscInt    count;
    283: } MatStashHeader;

    285: typedef struct {
    286:   void        *buffer;          /* Of type blocktype, dynamically constructed  */
    287:   PetscInt    count;
    288:   char        pending;
    289: } MatStashFrame;

    291: typedef struct _MatStash MatStash;
    292: struct _MatStash {
    293:   PetscInt      nmax;                   /* maximum stash size */
    294:   PetscInt      umax;                   /* user specified max-size */
    295:   PetscInt      oldnmax;                /* the nmax value used previously */
    296:   PetscInt      n;                      /* stash size */
    297:   PetscInt      bs;                     /* block size of the stash */
    298:   PetscInt      reallocs;               /* preserve the no of mallocs invoked */
    299:   PetscMatStashSpace space_head,space;  /* linked list to hold stashed global row/column numbers and matrix values */

    301:   PetscErrorCode (*ScatterBegin)(Mat,MatStash*,PetscInt*);
    302:   PetscErrorCode (*ScatterGetMesg)(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
    303:   PetscErrorCode (*ScatterEnd)(MatStash*);
    304:   PetscErrorCode (*ScatterDestroy)(MatStash*);

    306:   /* The following variables are used for communication */
    307:   MPI_Comm      comm;
    308:   PetscMPIInt   size,rank;
    309:   PetscMPIInt   tag1,tag2;
    310:   MPI_Request   *send_waits;            /* array of send requests */
    311:   MPI_Request   *recv_waits;            /* array of receive requests */
    312:   MPI_Status    *send_status;           /* array of send status */
    313:   PetscInt      nsends,nrecvs;          /* numbers of sends and receives */
    314:   PetscScalar   *svalues;               /* sending data */
    315:   PetscInt      *sindices;
    316:   PetscScalar   **rvalues;              /* receiving data (values) */
    317:   PetscInt      **rindices;             /* receiving data (indices) */
    318:   PetscInt      nprocessed;             /* number of messages already processed */
    319:   PetscMPIInt   *flg_v;                 /* indicates what messages have arrived so far and from whom */
    320:   PetscBool     reproduce;
    321:   PetscInt      reproduce_count;

    323:   /* The following variables are used for BTS communication */
    324:   PetscBool      first_assembly_done;   /* Is the first time matrix assembly done? */
    325:   PetscBool      use_status;            /* Use MPI_Status to determine number of items in each message */
    326:   PetscMPIInt    nsendranks;
    327:   PetscMPIInt    nrecvranks;
    328:   PetscMPIInt    *sendranks;
    329:   PetscMPIInt    *recvranks;
    330:   MatStashHeader *sendhdr,*recvhdr;
    331:   MatStashFrame  *sendframes;   /* pointers to the main messages */
    332:   MatStashFrame  *recvframes;
    333:   MatStashFrame  *recvframe_active;
    334:   PetscInt       recvframe_i;     /* index of block within active frame */
    335:   PetscMPIInt    recvframe_count; /* Count actually sent for current frame */
    336:   PetscInt       recvcount;       /* Number of receives processed so far */
    337:   PetscMPIInt    *some_indices;   /* From last call to MPI_Waitsome */
    338:   MPI_Status     *some_statuses;  /* Statuses from last call to MPI_Waitsome */
    339:   PetscMPIInt    some_count;      /* Number of requests completed in last call to MPI_Waitsome */
    340:   PetscMPIInt    some_i;          /* Index of request currently being processed */
    341:   MPI_Request    *sendreqs;
    342:   MPI_Request    *recvreqs;
    343:   PetscSegBuffer segsendblocks;
    344:   PetscSegBuffer segrecvframe;
    345:   PetscSegBuffer segrecvblocks;
    346:   MPI_Datatype   blocktype;
    347:   size_t         blocktype_size;
    348:   InsertMode     *insertmode;   /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
    349: };

    351: #if !defined(PETSC_HAVE_MPIUNI)
    352: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash*);
    353: #endif
    354: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm,PetscInt,MatStash*);
    355: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash*);
    356: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash*);
    357: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash*,PetscInt);
    358: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash*,PetscInt*,PetscInt*);
    359: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscBool );
    360: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscBool );
    361: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
    362: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
    363: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat,MatStash*,PetscInt*);
    364: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
    365: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat,MatInfoType,MatInfo*);

    367: typedef struct {
    368:   PetscInt   dim;
    369:   PetscInt   dims[4];
    370:   PetscInt   starts[4];
    371:   PetscBool  noc;        /* this is a single component problem, hence user will not set MatStencil.c */
    372: } MatStencilInfo;

    374: /* Info about using compressed row format */
    375: typedef struct {
    376:   PetscBool  use;                           /* indicates compressed rows have been checked and will be used */
    377:   PetscInt   nrows;                         /* number of non-zero rows */
    378:   PetscInt   *i;                            /* compressed row pointer  */
    379:   PetscInt   *rindex;                       /* compressed row index               */
    380: } Mat_CompressedRow;
    381: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat,PetscInt,Mat_CompressedRow*,PetscInt*,PetscInt,PetscReal);

    383: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
    384:   PetscInt     nzlocal,nsends,nrecvs;
    385:   PetscMPIInt  *send_rank,*recv_rank;
    386:   PetscInt     *sbuf_nz,*rbuf_nz,*sbuf_j,**rbuf_j;
    387:   PetscScalar  *sbuf_a,**rbuf_a;
    388:   MPI_Comm     subcomm;   /* when user does not provide a subcomm */
    389:   IS           isrow,iscol;
    390:   Mat          *matseq;
    391: } Mat_Redundant;

    393: typedef struct { /* used by MatProduct() */
    394:   MatProductType       type;
    395:   MatProductAlgorithm  alg;
    396:   Mat                  A,B,C,Dwork;
    397:   PetscReal            fill;
    398:   PetscBool            Areplaced,Breplaced; /* if an internal implementation changes user's input A or B, these matrices cannot be called by MatProductReplaceMats(). */
    399:   PetscBool            api_user; /* used by MatProductSetFromOptions_xxx() */
    400: } Mat_Product;

    402: struct _p_Mat {
    403:   PETSCHEADER(struct _MatOps);
    404:   PetscLayout            rmap,cmap;
    405:   void                   *data;            /* implementation-specific data */
    406:   MatFactorType          factortype;       /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
    407:   PetscBool              assembled;        /* is the matrix assembled? */
    408:   PetscBool              was_assembled;    /* new values inserted into assembled mat */
    409:   PetscInt               num_ass;          /* number of times matrix has been assembled */
    410:   PetscObjectState       nonzerostate;     /* each time new nonzeros locations are introduced into the matrix this is updated */
    411:   PetscObjectState       ass_nonzerostate; /* nonzero state at last assembly */
    412:   MatInfo                info;             /* matrix information */
    413:   InsertMode             insertmode;       /* have values been inserted in matrix or added? */
    414:   MatStash               stash,bstash;     /* used for assembling off-proc mat emements */
    415:   MatNullSpace           nullsp;           /* null space (operator is singular) */
    416:   MatNullSpace           transnullsp;      /* null space of transpose of operator */
    417:   MatNullSpace           nearnullsp;       /* near null space to be used by multigrid methods */
    418:   PetscInt               congruentlayouts; /* are the rows and columns layouts congruent? */
    419:   PetscBool              preallocated;
    420:   MatStencilInfo         stencil;          /* information for structured grid */
    421:   PetscBool              symmetric,hermitian,structurally_symmetric,spd;
    422:   PetscBool              symmetric_set,hermitian_set,structurally_symmetric_set,spd_set; /* if true, then corresponding flag is correct*/
    423:   PetscBool              symmetric_eternal;
    424:   PetscBool              nooffprocentries,nooffproczerorows;
    425:   PetscBool              assembly_subset;  /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
    426:   PetscBool              submat_singleis;  /* for efficient PCSetUp_ASM() */
    427:   PetscBool              structure_only;
    428:   PetscBool              sortedfull;       /* full, sorted rows are inserted */
    429: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
    430:   PetscOffloadMask       offloadmask;      /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
    431:   PetscBool              boundtocpu;
    432: #endif
    433:   void                   *spptr;          /* pointer for special library like SuperLU */
    434:   char                   *solvertype;
    435:   PetscBool              checksymmetryonassembly,checknullspaceonassembly;
    436:   PetscReal              checksymmetrytol;
    437:   Mat                    schur;             /* Schur complement matrix */
    438:   MatFactorSchurStatus   schur_status;      /* status of the Schur complement matrix */
    439:   Mat_Redundant          *redundant;        /* used by MatCreateRedundantMatrix() */
    440:   PetscBool              erroriffailure;    /* Generate an error if detected (for example a zero pivot) instead of returning */
    441:   MatFactorError         factorerrortype;               /* type of error in factorization */
    442:   PetscReal              factorerror_zeropivot_value;   /* If numerical zero pivot was detected this is the computed value */
    443:   PetscInt               factorerror_zeropivot_row;     /* Row where zero pivot was detected */
    444:   PetscInt               nblocks,*bsizes;   /* support for MatSetVariableBlockSizes() */
    445:   char                   *defaultvectype;
    446:   Mat_Product            *product;
    447: };

    449: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat,PetscScalar,Mat,MatStructure);
    450: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat,Mat,PetscScalar,Mat,MatStructure);
    451: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat,Mat,Mat*);

    453: /*
    454:     Utility for MatFactor (Schur complement)
    455: */
    456: PETSC_INTERN PetscErrorCode MatFactorFactorizeSchurComplement_Private(Mat);
    457: PETSC_INTERN PetscErrorCode MatFactorInvertSchurComplement_Private(Mat);
    458: PETSC_INTERN PetscErrorCode MatFactorUpdateSchurStatus_Private(Mat);
    459: PETSC_INTERN PetscErrorCode MatFactorSetUpInPlaceSchur_Private(Mat);

    461: /*
    462:     Utility for MatZeroRows
    463: */
    464: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat,PetscInt,const PetscInt*,PetscInt*,PetscInt**);

    466: /*
    467:     Utility for MatView/MatLoad
    468: */
    469: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat,PetscViewer);
    470: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat,PetscViewer);

    473: /*
    474:     Object for partitioning graphs
    475: */

    477: typedef struct _MatPartitioningOps *MatPartitioningOps;
    478: struct _MatPartitioningOps {
    479:   PetscErrorCode (*apply)(MatPartitioning,IS*);
    480:   PetscErrorCode (*applynd)(MatPartitioning,IS*);
    481:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatPartitioning);
    482:   PetscErrorCode (*destroy)(MatPartitioning);
    483:   PetscErrorCode (*view)(MatPartitioning,PetscViewer);
    484:   PetscErrorCode (*improve)(MatPartitioning,IS*);
    485: };

    487: struct _p_MatPartitioning {
    488:   PETSCHEADER(struct _MatPartitioningOps);
    489:   Mat         adj;
    490:   PetscInt    *vertex_weights;
    491:   PetscReal   *part_weights;
    492:   PetscInt    n;                                 /* number of partitions */
    493:   void        *data;
    494:   PetscInt    setupcalled;
    495:   PetscBool   use_edge_weights;  /* A flag indicates whether or not to use edge weights */
    496: };

    498: /* needed for parallel nested dissection by ParMetis and PTSCOTCH */
    499: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt,PetscInt[],PetscInt[],PetscInt[]);

    501: /*
    502:     Object for coarsen graphs
    503: */
    504: typedef struct _MatCoarsenOps *MatCoarsenOps;
    505: struct _MatCoarsenOps {
    506:   PetscErrorCode (*apply)(MatCoarsen);
    507:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatCoarsen);
    508:   PetscErrorCode (*destroy)(MatCoarsen);
    509:   PetscErrorCode (*view)(MatCoarsen,PetscViewer);
    510: };

    512: struct _p_MatCoarsen {
    513:   PETSCHEADER(struct _MatCoarsenOps);
    514:   Mat              graph;
    515:   PetscInt         setupcalled;
    516:   void             *subctx;
    517:   /* */
    518:   PetscBool        strict_aggs;
    519:   IS               perm;
    520:   PetscCoarsenData *agg_lists;
    521: };

    523: /*
    524:     MatFDColoring is used to compute Jacobian matrices efficiently
    525:   via coloring. The data structure is explained below in an example.

    527:    Color =   0    1     0    2   |   2      3       0
    528:    ---------------------------------------------------
    529:             00   01              |          05
    530:             10   11              |   14     15               Processor  0
    531:                        22    23  |          25
    532:                        32    33  |
    533:    ===================================================
    534:                                  |   44     45     46
    535:             50                   |          55               Processor 1
    536:                                  |   64            66
    537:    ---------------------------------------------------

    539:     ncolors = 4;

    541:     ncolumns      = {2,1,1,0}
    542:     columns       = {{0,2},{1},{3},{}}
    543:     nrows         = {4,2,3,3}
    544:     rows          = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
    545:     vwscale       = {dx(0),dx(1),dx(2),dx(3)}               MPI Vec
    546:     vscale        = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)}   Seq Vec

    548:     ncolumns      = {1,0,1,1}
    549:     columns       = {{6},{},{4},{5}}
    550:     nrows         = {3,0,2,2}
    551:     rows          = {{0,1,2},{},{1,2},{1,2}}
    552:     vwscale       = {dx(4),dx(5),dx(6)}              MPI Vec
    553:     vscale        = {dx(0),dx(4),dx(5),dx(6)}        Seq Vec

    555:     See the routine MatFDColoringApply() for how this data is used
    556:     to compute the Jacobian.

    558: */
    559: typedef struct {
    560:   PetscInt     row;
    561:   PetscInt     col;
    562:   PetscScalar  *valaddr;   /* address of value */
    563: } MatEntry;

    565: typedef struct {
    566:   PetscInt     row;
    567:   PetscScalar  *valaddr;   /* address of value */
    568: } MatEntry2;

    570: struct  _p_MatFDColoring{
    571:   PETSCHEADER(int);
    572:   PetscInt       M,N,m;            /* total rows, columns; local rows */
    573:   PetscInt       rstart;           /* first row owned by local processor */
    574:   PetscInt       ncolors;          /* number of colors */
    575:   PetscInt       *ncolumns;        /* number of local columns for a color */
    576:   PetscInt       **columns;        /* lists the local columns of each color (using global column numbering) */
    577:   IS             *isa;             /* these are the IS that contain the column values given in columns */
    578:   PetscInt       *nrows;           /* number of local rows for each color */
    579:   MatEntry       *matentry;        /* holds (row, column, address of value) for Jacobian matrix entry */
    580:   MatEntry2      *matentry2;       /* holds (row, address of value) for Jacobian matrix entry */
    581:   PetscScalar    *dy;              /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
    582:   PetscReal      error_rel;        /* square root of relative error in computing function */
    583:   PetscReal      umin;             /* minimum allowable u'dx value */
    584:   Vec            w1,w2,w3;         /* work vectors used in computing Jacobian */
    585:   PetscBool      fset;             /* indicates that the initial function value F(X) is set */
    586:   PetscErrorCode (*f)(void);       /* function that defines Jacobian */
    587:   void           *fctx;            /* optional user-defined context for use by the function f */
    588:   Vec            vscale;           /* holds FD scaling, i.e. 1/dx for each perturbed column */
    589:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
    590:   const char     *htype;           /* "wp" or "ds" */
    591:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
    592:   PetscInt       brows,bcols;      /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
    593:   PetscBool      setupcalled;      /* true if setup has been called */
    594:   PetscBool      viewed;           /* true if the -mat_fd_coloring_view has been triggered already */
    595:   void           (*ftn_func_pointer)(void),*ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
    596:   PetscObjectId  matid;            /* matrix this object was created with, must always be the same */
    597: };

    599: typedef struct _MatColoringOps *MatColoringOps;
    600: struct _MatColoringOps {
    601:   PetscErrorCode (*destroy)(MatColoring);
    602:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatColoring);
    603:   PetscErrorCode (*view)(MatColoring,PetscViewer);
    604:   PetscErrorCode (*apply)(MatColoring,ISColoring*);
    605:   PetscErrorCode (*weights)(MatColoring,PetscReal**,PetscInt**);
    606: };

    608: struct _p_MatColoring {
    609:   PETSCHEADER(struct _MatColoringOps);
    610:   Mat                   mat;
    611:   PetscInt              dist;             /* distance of the coloring */
    612:   PetscInt              maxcolors;        /* the maximum number of colors returned, maxcolors=1 for MIS */
    613:   void                  *data;            /* inner context */
    614:   PetscBool             valid;            /* check to see if what is produced is a valid coloring */
    615:   MatColoringWeightType weight_type;      /* type of weight computation to be performed */
    616:   PetscReal             *user_weights;    /* custom weights and permutation */
    617:   PetscInt              *user_lperm;
    618:   PetscBool             valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
    619: };

    621: struct  _p_MatTransposeColoring{
    622:   PETSCHEADER(int);
    623:   PetscInt       M,N,m;            /* total rows, columns; local rows */
    624:   PetscInt       rstart;           /* first row owned by local processor */
    625:   PetscInt       ncolors;          /* number of colors */
    626:   PetscInt       *ncolumns;        /* number of local columns for a color */
    627:   PetscInt       *nrows;           /* number of local rows for each color */
    628:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
    629:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */

    631:   PetscInt       *colorforrow,*colorforcol;  /* pointer to rows and columns */
    632:   PetscInt       *rows;                      /* lists the local rows for each color (using the local row numbering) */
    633:   PetscInt       *den2sp;                    /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
    634:   PetscInt       *columns;                   /* lists the local columns of each color (using global column numbering) */
    635:   PetscInt       brows;                      /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
    636:   PetscInt       *lstart;                    /* array used for loop over row blocks of Csparse */
    637: };

    639: /*
    640:    Null space context for preconditioner/operators
    641: */
    642: struct _p_MatNullSpace {
    643:   PETSCHEADER(int);
    644:   PetscBool      has_cnst;
    645:   PetscInt       n;
    646:   Vec*           vecs;
    647:   PetscScalar*   alpha;                 /* for projections */
    648:   PetscErrorCode (*remove)(MatNullSpace,Vec,void*);  /* for user provided removal function */
    649:   void*          rmctx;                 /* context for remove() function */
    650: };

    652: /*
    653:    Checking zero pivot for LU, ILU preconditioners.
    654: */
    655: typedef struct {
    656:   PetscInt       nshift,nshift_max;
    657:   PetscReal      shift_amount,shift_lo,shift_hi,shift_top,shift_fraction;
    658:   PetscBool      newshift;
    659:   PetscReal      rs;  /* active row sum of abs(offdiagonals) */
    660:   PetscScalar    pv;  /* pivot of the active row */
    661: } FactorShiftCtx;

    663: /*
    664:  Used by MatCreateSubMatrices_MPIXAIJ_Local()
    665: */
    666:  #include <petscctable.h>
    667: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
    668:   PetscInt   id;   /* index of submats, only submats[0] is responsible for deleting some arrays below */
    669:   PetscInt   nrqs,nrqr;
    670:   PetscInt   **rbuf1,**rbuf2,**rbuf3,**sbuf1,**sbuf2;
    671:   PetscInt   **ptr;
    672:   PetscInt   *tmp;
    673:   PetscInt   *ctr;
    674:   PetscInt   *pa; /* proc array */
    675:   PetscInt   *req_size,*req_source1,*req_source2;
    676:   PetscBool  allcolumns,allrows;
    677:   PetscBool  singleis;
    678:   PetscInt   *row2proc; /* row to proc map */
    679:   PetscInt   nstages;
    680: #if defined(PETSC_USE_CTABLE)
    681:   PetscTable cmap,rmap;
    682:   PetscInt   *cmap_loc,*rmap_loc;
    683: #else
    684:   PetscInt   *cmap,*rmap;
    685: #endif

    687:   PetscErrorCode (*destroy)(Mat);
    688: } Mat_SubSppt;

    690: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
    691: PETSC_INTERN PetscErrorCode MatShift_Basic(Mat,PetscScalar);
    692: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat,PetscInt,PetscInt);

    694: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_nz(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    695: {
    696:   PetscReal _rs   = sctx->rs;
    697:   PetscReal _zero = info->zeropivot*_rs;

    700:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
    701:     /* force |diag| > zeropivot*rs */
    702:     if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
    703:     else sctx->shift_amount *= 2.0;
    704:     sctx->newshift = PETSC_TRUE;
    705:     (sctx->nshift)++;
    706:   } else {
    707:     sctx->newshift = PETSC_FALSE;
    708:   }
    709:   return(0);
    710: }

    712: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_pd(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    713: {
    714:   PetscReal _rs   = sctx->rs;
    715:   PetscReal _zero = info->zeropivot*_rs;

    718:   if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
    719:     /* force matfactor to be diagonally dominant */
    720:     if (sctx->nshift == sctx->nshift_max) {
    721:       sctx->shift_fraction = sctx->shift_hi;
    722:     } else {
    723:       sctx->shift_lo = sctx->shift_fraction;
    724:       sctx->shift_fraction = (sctx->shift_hi+sctx->shift_lo)/2.;
    725:     }
    726:     sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
    727:     sctx->nshift++;
    728:     sctx->newshift = PETSC_TRUE;
    729:   } else {
    730:     sctx->newshift = PETSC_FALSE;
    731:   }
    732:   return(0);
    733: }

    735: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_inblocks(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    736: {
    737:   PetscReal _zero = info->zeropivot;

    740:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
    741:     sctx->pv          += info->shiftamount;
    742:     sctx->shift_amount = 0.0;
    743:     sctx->nshift++;
    744:   }
    745:   sctx->newshift = PETSC_FALSE;
    746:   return(0);
    747: }

    749: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_none(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    750: {
    751:   PetscReal      _zero = info->zeropivot;

    755:   sctx->newshift = PETSC_FALSE;
    756:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
    757:     if (!mat->erroriffailure) {
    758:       PetscInfo3(mat,"Detected zero pivot in factorization in row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
    759:       fact->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    760:       fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
    761:       fact->factorerror_zeropivot_row   = row;
    762:     } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
    763:   }
    764:   return(0);
    765: }

    767: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    768: {

    772:   if (info->shifttype == (PetscReal) MAT_SHIFT_NONZERO){
    773:     MatPivotCheck_nz(mat,info,sctx,row);
    774:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_POSITIVE_DEFINITE){
    775:     MatPivotCheck_pd(mat,info,sctx,row);
    776:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_INBLOCKS){
    777:     MatPivotCheck_inblocks(mat,info,sctx,row);
    778:   } else {
    779:     MatPivotCheck_none(fact,mat,info,sctx,row);
    780:   }
    781:   return(0);
    782: }

    784: /*
    785:   Create and initialize a linked list
    786:   Input Parameters:
    787:     idx_start - starting index of the list
    788:     lnk_max   - max value of lnk indicating the end of the list
    789:     nlnk      - max length of the list
    790:   Output Parameters:
    791:     lnk       - list initialized
    792:     bt        - PetscBT (bitarray) with all bits set to false
    793:     lnk_empty - flg indicating the list is empty
    794: */
    795: #define PetscLLCreate(idx_start,lnk_max,nlnk,lnk,bt) \
    796:   (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,0))

    798: #define PetscLLCreate_new(idx_start,lnk_max,nlnk,lnk,bt,lnk_empty)\
    799:   (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk_empty = PETSC_TRUE,0) ||(lnk[idx_start] = lnk_max,0))

    801: /*
    802:   Add an index set into a sorted linked list
    803:   Input Parameters:
    804:     nidx      - number of input indices
    805:     indices   - integer array
    806:     idx_start - starting index of the list
    807:     lnk       - linked list(an integer array) that is created
    808:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    809:   output Parameters:
    810:     nlnk      - number of newly added indices
    811:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
    812:     bt        - updated PetscBT (bitarray)
    813: */
    814: #define PetscLLAdd(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
    815: {\
    816:   PetscInt _k,_entry,_location,_lnkdata;\
    817:   nlnk     = 0;\
    818:   _lnkdata = idx_start;\
    819:   for (_k=0; _k<nidx; _k++){\
    820:     _entry = indices[_k];\
    821:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    822:       /* search for insertion location */\
    823:       /* start from the beginning if _entry < previous _entry */\
    824:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    825:       do {\
    826:         _location = _lnkdata;\
    827:         _lnkdata  = lnk[_location];\
    828:       } while (_entry > _lnkdata);\
    829:       /* insertion location is found, add entry into lnk */\
    830:       lnk[_location] = _entry;\
    831:       lnk[_entry]    = _lnkdata;\
    832:       nlnk++;\
    833:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    834:     }\
    835:   }\
    836: }

    838: /*
    839:   Add a permuted index set into a sorted linked list
    840:   Input Parameters:
    841:     nidx      - number of input indices
    842:     indices   - integer array
    843:     perm      - permutation of indices
    844:     idx_start - starting index of the list
    845:     lnk       - linked list(an integer array) that is created
    846:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    847:   output Parameters:
    848:     nlnk      - number of newly added indices
    849:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
    850:     bt        - updated PetscBT (bitarray)
    851: */
    852: #define PetscLLAddPerm(nidx,indices,perm,idx_start,nlnk,lnk,bt) 0;\
    853: {\
    854:   PetscInt _k,_entry,_location,_lnkdata;\
    855:   nlnk     = 0;\
    856:   _lnkdata = idx_start;\
    857:   for (_k=0; _k<nidx; _k++){\
    858:     _entry = perm[indices[_k]];\
    859:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    860:       /* search for insertion location */\
    861:       /* start from the beginning if _entry < previous _entry */\
    862:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    863:       do {\
    864:         _location = _lnkdata;\
    865:         _lnkdata  = lnk[_location];\
    866:       } while (_entry > _lnkdata);\
    867:       /* insertion location is found, add entry into lnk */\
    868:       lnk[_location] = _entry;\
    869:       lnk[_entry]    = _lnkdata;\
    870:       nlnk++;\
    871:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    872:     }\
    873:   }\
    874: }

    876: /*
    877:   Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata  = idx_start;'
    878:   Input Parameters:
    879:     nidx      - number of input indices
    880:     indices   - sorted integer array
    881:     idx_start - starting index of the list
    882:     lnk       - linked list(an integer array) that is created
    883:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    884:   output Parameters:
    885:     nlnk      - number of newly added indices
    886:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
    887:     bt        - updated PetscBT (bitarray)
    888: */
    889: #define PetscLLAddSorted(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
    890: {\
    891:   PetscInt _k,_entry,_location,_lnkdata;\
    892:   nlnk      = 0;\
    893:   _lnkdata  = idx_start;\
    894:   for (_k=0; _k<nidx; _k++){\
    895:     _entry = indices[_k];\
    896:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    897:       /* search for insertion location */\
    898:       do {\
    899:         _location = _lnkdata;\
    900:         _lnkdata  = lnk[_location];\
    901:       } while (_entry > _lnkdata);\
    902:       /* insertion location is found, add entry into lnk */\
    903:       lnk[_location] = _entry;\
    904:       lnk[_entry]    = _lnkdata;\
    905:       nlnk++;\
    906:       _lnkdata = _entry; /* next search starts from here */\
    907:     }\
    908:   }\
    909: }

    911: #define PetscLLAddSorted_new(nidx,indices,idx_start,lnk_empty,nlnk,lnk,bt) 0; \
    912: {\
    913:   PetscInt _k,_entry,_location,_lnkdata;\
    914:   if (lnk_empty){\
    915:     _lnkdata  = idx_start;                      \
    916:     for (_k=0; _k<nidx; _k++){                  \
    917:       _entry = indices[_k];                             \
    918:       PetscBTSet(bt,_entry);  /* mark the new entry */          \
    919:           _location = _lnkdata;                                 \
    920:           _lnkdata  = lnk[_location];                           \
    921:         /* insertion location is found, add entry into lnk */   \
    922:         lnk[_location] = _entry;                                \
    923:         lnk[_entry]    = _lnkdata;                              \
    924:         _lnkdata = _entry; /* next search starts from here */   \
    925:     }                                                           \
    926:     /*\
    927:     lnk[indices[nidx-1]] = lnk[idx_start];\
    928:     lnk[idx_start]       = indices[0];\
    929:     PetscBTSet(bt,indices[0]);  \
    930:     for (_k=1; _k<nidx; _k++){                  \
    931:       PetscBTSet(bt,indices[_k]);                                          \
    932:       lnk[indices[_k-1]] = indices[_k];                                  \
    933:     }                                                           \
    934:      */\
    935:     nlnk      = nidx;\
    936:     lnk_empty = PETSC_FALSE;\
    937:   } else {\
    938:     nlnk      = 0;                              \
    939:     _lnkdata  = idx_start;                      \
    940:     for (_k=0; _k<nidx; _k++){                  \
    941:       _entry = indices[_k];                             \
    942:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */       \
    943:         /* search for insertion location */                     \
    944:         do {                                                    \
    945:           _location = _lnkdata;                                 \
    946:           _lnkdata  = lnk[_location];                           \
    947:         } while (_entry > _lnkdata);                            \
    948:         /* insertion location is found, add entry into lnk */   \
    949:         lnk[_location] = _entry;                                \
    950:         lnk[_entry]    = _lnkdata;                              \
    951:         nlnk++;                                                 \
    952:         _lnkdata = _entry; /* next search starts from here */   \
    953:       }                                                         \
    954:     }                                                           \
    955:   }                                                             \
    956: }

    958: /*
    959:   Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
    960:   Same as PetscLLAddSorted() with an additional operation:
    961:        count the number of input indices that are no larger than 'diag'
    962:   Input Parameters:
    963:     indices   - sorted integer array
    964:     idx_start - starting index of the list, index of pivot row
    965:     lnk       - linked list(an integer array) that is created
    966:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    967:     diag      - index of the active row in LUFactorSymbolic
    968:     nzbd      - number of input indices with indices <= idx_start
    969:     im        - im[idx_start] is initialized as num of nonzero entries in row=idx_start
    970:   output Parameters:
    971:     nlnk      - number of newly added indices
    972:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
    973:     bt        - updated PetscBT (bitarray)
    974:     im        - im[idx_start]: unchanged if diag is not an entry
    975:                              : num of entries with indices <= diag if diag is an entry
    976: */
    977: #define PetscLLAddSortedLU(indices,idx_start,nlnk,lnk,bt,diag,nzbd,im) 0;\
    978: {\
    979:   PetscInt _k,_entry,_location,_lnkdata,_nidx;\
    980:   nlnk     = 0;\
    981:   _lnkdata = idx_start;\
    982:   _nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */\
    983:   for (_k=0; _k<_nidx; _k++){\
    984:     _entry = indices[_k];\
    985:     nzbd++;\
    986:     if ( _entry== diag) im[idx_start] = nzbd;\
    987:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    988:       /* search for insertion location */\
    989:       do {\
    990:         _location = _lnkdata;\
    991:         _lnkdata  = lnk[_location];\
    992:       } while (_entry > _lnkdata);\
    993:       /* insertion location is found, add entry into lnk */\
    994:       lnk[_location] = _entry;\
    995:       lnk[_entry]    = _lnkdata;\
    996:       nlnk++;\
    997:       _lnkdata = _entry; /* next search starts from here */\
    998:     }\
    999:   }\
    1000: }

    1002: /*
    1003:   Copy data on the list into an array, then initialize the list
    1004:   Input Parameters:
    1005:     idx_start - starting index of the list
    1006:     lnk_max   - max value of lnk indicating the end of the list
    1007:     nlnk      - number of data on the list to be copied
    1008:     lnk       - linked list
    1009:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1010:   output Parameters:
    1011:     indices   - array that contains the copied data
    1012:     lnk       - linked list that is cleaned and initialize
    1013:     bt        - PetscBT (bitarray) with all bits set to false
    1014: */
    1015: #define PetscLLClean(idx_start,lnk_max,nlnk,lnk,indices,bt) 0;\
    1016: {\
    1017:   PetscInt _j,_idx=idx_start;\
    1018:   for (_j=0; _j<nlnk; _j++){\
    1019:     _idx = lnk[_idx];\
    1020:     indices[_j] = _idx;\
    1021:     PetscBTClear(bt,_idx);\
    1022:   }\
    1023:   lnk[idx_start] = lnk_max;\
    1024: }
    1025: /*
    1026:   Free memories used by the list
    1027: */
    1028: #define PetscLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

    1030: /* Routines below are used for incomplete matrix factorization */
    1031: /*
    1032:   Create and initialize a linked list and its levels
    1033:   Input Parameters:
    1034:     idx_start - starting index of the list
    1035:     lnk_max   - max value of lnk indicating the end of the list
    1036:     nlnk      - max length of the list
    1037:   Output Parameters:
    1038:     lnk       - list initialized
    1039:     lnk_lvl   - array of size nlnk for storing levels of lnk
    1040:     bt        - PetscBT (bitarray) with all bits set to false
    1041: */
    1042: #define PetscIncompleteLLCreate(idx_start,lnk_max,nlnk,lnk,lnk_lvl,bt)\
    1043:   (PetscIntMultError(2,nlnk,NULL) || PetscMalloc1(2*nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,lnk_lvl = lnk + nlnk,0))

    1045: /*
    1046:   Initialize a sorted linked list used for ILU and ICC
    1047:   Input Parameters:
    1048:     nidx      - number of input idx
    1049:     idx       - integer array used for storing column indices
    1050:     idx_start - starting index of the list
    1051:     perm      - indices of an IS
    1052:     lnk       - linked list(an integer array) that is created
    1053:     lnklvl    - levels of lnk
    1054:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1055:   output Parameters:
    1056:     nlnk     - number of newly added idx
    1057:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1058:     lnklvl   - levels of lnk
    1059:     bt       - updated PetscBT (bitarray)
    1060: */
    1061: #define PetscIncompleteLLInit(nidx,idx,idx_start,perm,nlnk,lnk,lnklvl,bt) 0;\
    1062: {\
    1063:   PetscInt _k,_entry,_location,_lnkdata;\
    1064:   nlnk     = 0;\
    1065:   _lnkdata = idx_start;\
    1066:   for (_k=0; _k<nidx; _k++){\
    1067:     _entry = perm[idx[_k]];\
    1068:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1069:       /* search for insertion location */\
    1070:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    1071:       do {\
    1072:         _location = _lnkdata;\
    1073:         _lnkdata  = lnk[_location];\
    1074:       } while (_entry > _lnkdata);\
    1075:       /* insertion location is found, add entry into lnk */\
    1076:       lnk[_location]  = _entry;\
    1077:       lnk[_entry]     = _lnkdata;\
    1078:       lnklvl[_entry] = 0;\
    1079:       nlnk++;\
    1080:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    1081:     }\
    1082:   }\
    1083: }

    1085: /*
    1086:   Add a SORTED index set into a sorted linked list for ILU
    1087:   Input Parameters:
    1088:     nidx      - number of input indices
    1089:     idx       - sorted integer array used for storing column indices
    1090:     level     - level of fill, e.g., ICC(level)
    1091:     idxlvl    - level of idx
    1092:     idx_start - starting index of the list
    1093:     lnk       - linked list(an integer array) that is created
    1094:     lnklvl    - levels of lnk
    1095:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1096:     prow      - the row number of idx
    1097:   output Parameters:
    1098:     nlnk     - number of newly added idx
    1099:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1100:     lnklvl   - levels of lnk
    1101:     bt       - updated PetscBT (bitarray)

    1103:   Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
    1104:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
    1105: */
    1106: #define PetscILULLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,lnklvl_prow) 0;\
    1107: {\
    1108:   PetscInt _k,_entry,_location,_lnkdata,_incrlev,_lnklvl_prow=lnklvl[prow];\
    1109:   nlnk     = 0;\
    1110:   _lnkdata = idx_start;\
    1111:   for (_k=0; _k<nidx; _k++){\
    1112:     _incrlev = idxlvl[_k] + _lnklvl_prow + 1;\
    1113:     if (_incrlev > level) continue;\
    1114:     _entry = idx[_k];\
    1115:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1116:       /* search for insertion location */\
    1117:       do {\
    1118:         _location = _lnkdata;\
    1119:         _lnkdata  = lnk[_location];\
    1120:       } while (_entry > _lnkdata);\
    1121:       /* insertion location is found, add entry into lnk */\
    1122:       lnk[_location]  = _entry;\
    1123:       lnk[_entry]     = _lnkdata;\
    1124:       lnklvl[_entry] = _incrlev;\
    1125:       nlnk++;\
    1126:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    1127:     } else { /* existing entry: update lnklvl */\
    1128:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1129:     }\
    1130:   }\
    1131: }

    1133: /*
    1134:   Add a index set into a sorted linked list
    1135:   Input Parameters:
    1136:     nidx      - number of input idx
    1137:     idx   - integer array used for storing column indices
    1138:     level     - level of fill, e.g., ICC(level)
    1139:     idxlvl - level of idx
    1140:     idx_start - starting index of the list
    1141:     lnk       - linked list(an integer array) that is created
    1142:     lnklvl   - levels of lnk
    1143:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1144:   output Parameters:
    1145:     nlnk      - number of newly added idx
    1146:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1147:     lnklvl   - levels of lnk
    1148:     bt        - updated PetscBT (bitarray)
    1149: */
    1150: #define PetscIncompleteLLAdd(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
    1151: {\
    1152:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
    1153:   nlnk     = 0;\
    1154:   _lnkdata = idx_start;\
    1155:   for (_k=0; _k<nidx; _k++){\
    1156:     _incrlev = idxlvl[_k] + 1;\
    1157:     if (_incrlev > level) continue;\
    1158:     _entry = idx[_k];\
    1159:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1160:       /* search for insertion location */\
    1161:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    1162:       do {\
    1163:         _location = _lnkdata;\
    1164:         _lnkdata  = lnk[_location];\
    1165:       } while (_entry > _lnkdata);\
    1166:       /* insertion location is found, add entry into lnk */\
    1167:       lnk[_location]  = _entry;\
    1168:       lnk[_entry]     = _lnkdata;\
    1169:       lnklvl[_entry] = _incrlev;\
    1170:       nlnk++;\
    1171:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    1172:     } else { /* existing entry: update lnklvl */\
    1173:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1174:     }\
    1175:   }\
    1176: }

    1178: /*
    1179:   Add a SORTED index set into a sorted linked list
    1180:   Input Parameters:
    1181:     nidx      - number of input indices
    1182:     idx   - sorted integer array used for storing column indices
    1183:     level     - level of fill, e.g., ICC(level)
    1184:     idxlvl - level of idx
    1185:     idx_start - starting index of the list
    1186:     lnk       - linked list(an integer array) that is created
    1187:     lnklvl    - levels of lnk
    1188:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1189:   output Parameters:
    1190:     nlnk      - number of newly added idx
    1191:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1192:     lnklvl    - levels of lnk
    1193:     bt        - updated PetscBT (bitarray)
    1194: */
    1195: #define PetscIncompleteLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
    1196: {\
    1197:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
    1198:   nlnk = 0;\
    1199:   _lnkdata = idx_start;\
    1200:   for (_k=0; _k<nidx; _k++){\
    1201:     _incrlev = idxlvl[_k] + 1;\
    1202:     if (_incrlev > level) continue;\
    1203:     _entry = idx[_k];\
    1204:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1205:       /* search for insertion location */\
    1206:       do {\
    1207:         _location = _lnkdata;\
    1208:         _lnkdata  = lnk[_location];\
    1209:       } while (_entry > _lnkdata);\
    1210:       /* insertion location is found, add entry into lnk */\
    1211:       lnk[_location] = _entry;\
    1212:       lnk[_entry]    = _lnkdata;\
    1213:       lnklvl[_entry] = _incrlev;\
    1214:       nlnk++;\
    1215:       _lnkdata = _entry; /* next search starts from here */\
    1216:     } else { /* existing entry: update lnklvl */\
    1217:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1218:     }\
    1219:   }\
    1220: }

    1222: /*
    1223:   Add a SORTED index set into a sorted linked list for ICC
    1224:   Input Parameters:
    1225:     nidx      - number of input indices
    1226:     idx       - sorted integer array used for storing column indices
    1227:     level     - level of fill, e.g., ICC(level)
    1228:     idxlvl    - level of idx
    1229:     idx_start - starting index of the list
    1230:     lnk       - linked list(an integer array) that is created
    1231:     lnklvl    - levels of lnk
    1232:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1233:     idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
    1234:   output Parameters:
    1235:     nlnk   - number of newly added indices
    1236:     lnk    - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1237:     lnklvl - levels of lnk
    1238:     bt     - updated PetscBT (bitarray)
    1239:   Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
    1240:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
    1241: */
    1242: #define PetscICCLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,idxlvl_prow) 0;\
    1243: {\
    1244:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
    1245:   nlnk = 0;\
    1246:   _lnkdata = idx_start;\
    1247:   for (_k=0; _k<nidx; _k++){\
    1248:     _incrlev = idxlvl[_k] + idxlvl_prow + 1;\
    1249:     if (_incrlev > level) continue;\
    1250:     _entry = idx[_k];\
    1251:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1252:       /* search for insertion location */\
    1253:       do {\
    1254:         _location = _lnkdata;\
    1255:         _lnkdata  = lnk[_location];\
    1256:       } while (_entry > _lnkdata);\
    1257:       /* insertion location is found, add entry into lnk */\
    1258:       lnk[_location] = _entry;\
    1259:       lnk[_entry]    = _lnkdata;\
    1260:       lnklvl[_entry] = _incrlev;\
    1261:       nlnk++;\
    1262:       _lnkdata = _entry; /* next search starts from here */\
    1263:     } else { /* existing entry: update lnklvl */\
    1264:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1265:     }\
    1266:   }\
    1267: }

    1269: /*
    1270:   Copy data on the list into an array, then initialize the list
    1271:   Input Parameters:
    1272:     idx_start - starting index of the list
    1273:     lnk_max   - max value of lnk indicating the end of the list
    1274:     nlnk      - number of data on the list to be copied
    1275:     lnk       - linked list
    1276:     lnklvl    - level of lnk
    1277:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1278:   output Parameters:
    1279:     indices - array that contains the copied data
    1280:     lnk     - linked list that is cleaned and initialize
    1281:     lnklvl  - level of lnk that is reinitialized
    1282:     bt      - PetscBT (bitarray) with all bits set to false
    1283: */
    1284: #define PetscIncompleteLLClean(idx_start,lnk_max,nlnk,lnk,lnklvl,indices,indiceslvl,bt) 0;\
    1285: do {\
    1286:   PetscInt _j,_idx=idx_start;\
    1287:   for (_j=0; _j<nlnk; _j++){\
    1288:     _idx = lnk[_idx];\
    1289:     *(indices+_j) = _idx;\
    1290:     *(indiceslvl+_j) = lnklvl[_idx];\
    1291:     lnklvl[_idx] = -1;\
    1292:     PetscBTClear(bt,_idx);\
    1293:   }\
    1294:   lnk[idx_start] = lnk_max;\
    1295: } while (0)
    1296: /*
    1297:   Free memories used by the list
    1298: */
    1299: #define PetscIncompleteLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

    1301: #define MatCheckSameLocalSize(A,ar1,B,ar2) do { \
    1303:   if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n)) SETERRQ6(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Incompatible matrix local sizes: parameter # %d (%D x %D) != parameter # %d (%D x %D)",ar1,A->rmap->n,A->cmap->n,ar2,B->rmap->n,B->cmap->n);} while (0)

    1305: #define MatCheckSameSize(A,ar1,B,ar2) do { \
    1306:   if ((A->rmap->N != B->rmap->N) || (A->cmap->N != B->cmap->N)) SETERRQ6(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_INCOMP,"Incompatible matrix global sizes: parameter # %d (%D x %D) != parameter # %d (%D x %D)",ar1,A->rmap->N,A->cmap->N,ar2,B->rmap->N,B->cmap->N);\
    1307:   MatCheckSameLocalSize(A,ar1,B,ar2);} while (0)

    1309: #define VecCheckMatCompatible(M,x,ar1,b,ar2) do { \
    1310:   if (M->cmap->N != x->map->N) SETERRQ3(PetscObjectComm((PetscObject)M),PETSC_ERR_ARG_SIZ,"Vector global length incompatible with matrix: parameter # %d global size %D != matrix column global size %D",ar1,x->map->N,M->cmap->N); \
    1311:   if (M->rmap->N != b->map->N) SETERRQ3(PetscObjectComm((PetscObject)M),PETSC_ERR_ARG_SIZ,"Vector global length incompatible with matrix: parameter # %d global size %D != matrix row global size %D",ar2,b->map->N,M->rmap->N);} while (0)

    1313: /* -------------------------------------------------------------------------------------------------------*/
    1314:  #include <petscbt.h>
    1315: /*
    1316:   Create and initialize a condensed linked list -
    1317:     same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
    1318:     Barry suggested this approach (Dec. 6, 2011):
    1319:       I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
    1320:       (it may be faster than the O(N) even sequentially due to less crazy memory access).

    1322:       Instead of having some like  a  2  -> 4 -> 11 ->  22  list that uses slot 2  4 11 and 22 in a big array use a small array with two slots
    1323:       for each entry for example  [ 2 1 | 4 3 | 22 -1 | 11 2]   so the first number (of the pair) is the value while the second tells you where
    1324:       in the list the next entry is. Inserting a new link means just append another pair at the end. For example say we want to insert 13 into the
    1325:       list it would then become [2 1 | 4 3 | 22 -1 | 11 4 | 13 2 ] you just add a pair at the end and fix the point for the one that points to it.
    1326:       That is 11 use to point to the 2 slot, after the change 11 points to the 4th slot which has the value 13. Note that values are always next
    1327:       to each other so memory access is much better than using the big array.

    1329:   Example:
    1330:      nlnk_max=5, lnk_max=36:
    1331:      Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
    1332:      here, head_node has index 2 with value lnk[2]=lnk_max=36,
    1333:            0-th entry is used to store the number of entries in the list,
    1334:      The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.

    1336:      Now adding a sorted set {2,4}, the list becomes
    1337:      [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
    1338:      represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.

    1340:      Then adding a sorted set {0,3,35}, the list
    1341:      [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
    1342:      represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.

    1344:   Input Parameters:
    1345:     nlnk_max  - max length of the list
    1346:     lnk_max   - max value of the entries
    1347:   Output Parameters:
    1348:     lnk       - list created and initialized
    1349:     bt        - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
    1350: */
    1351: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max,PetscInt lnk_max,PetscInt **lnk,PetscBT *bt)
    1352: {
    1354:   PetscInt       *llnk,lsize = 0;

    1357:   PetscIntMultError(2,nlnk_max+2,&lsize);
    1358:   PetscMalloc1(lsize,lnk);
    1359:   PetscBTCreate(lnk_max,bt);
    1360:   llnk = *lnk;
    1361:   llnk[0] = 0;         /* number of entries on the list */
    1362:   llnk[2] = lnk_max;   /* value in the head node */
    1363:   llnk[3] = 2;         /* next for the head node */
    1364:   return(0);
    1365: }

    1367: /*
    1368:   Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
    1369:   Input Parameters:
    1370:     nidx      - number of input indices
    1371:     indices   - sorted integer array
    1372:     lnk       - condensed linked list(an integer array) that is created
    1373:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1374:   output Parameters:
    1375:     lnk       - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
    1376:     bt        - updated PetscBT (bitarray)
    1377: */
    1378: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx,const PetscInt indices[],PetscInt lnk[],PetscBT bt)
    1379: {
    1380:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;

    1383:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
    1384:   _location = 2; /* head */
    1385:     for (_k=0; _k<nidx; _k++){
    1386:       _entry = indices[_k];
    1387:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */
    1388:         /* search for insertion location */
    1389:         do {
    1390:           _next     = _location + 1; /* link from previous node to next node */
    1391:           _location = lnk[_next];    /* idx of next node */
    1392:           _lnkdata  = lnk[_location];/* value of next node */
    1393:         } while (_entry > _lnkdata);
    1394:         /* insertion location is found, add entry into lnk */
    1395:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
    1396:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
    1397:         lnk[_newnode]   = _entry;        /* set value of the new node */
    1398:         lnk[_newnode+1] = _location;     /* connect new node to next node */
    1399:         _location       = _newnode;      /* next search starts from the new node */
    1400:         _nlnk++;
    1401:       }   \
    1402:     }\
    1403:   lnk[0]   = _nlnk;   /* number of entries in the list */
    1404:   return(0);
    1405: }

    1407: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max,PetscInt nidx,PetscInt *indices,PetscInt lnk[],PetscBT bt)
    1408: {
    1410:   PetscInt       _k,_next,_nlnk;

    1413:   _next = lnk[3];       /* head node */
    1414:   _nlnk = lnk[0];       /* num of entries on the list */
    1415:   for (_k=0; _k<_nlnk; _k++){
    1416:     indices[_k] = lnk[_next];
    1417:     _next       = lnk[_next + 1];
    1418:     PetscBTClear(bt,indices[_k]);
    1419:   }
    1420:   lnk[0] = 0;          /* num of entries on the list */
    1421:   lnk[2] = lnk_max;    /* initialize head node */
    1422:   lnk[3] = 2;          /* head node */
    1423:   return(0);
    1424: }

    1426: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
    1427: {
    1429:   PetscInt       k;

    1432:   PetscPrintf(PETSC_COMM_SELF,"LLCondensed of size %D, (val,  next)\n",lnk[0]);
    1433:   for (k=2; k< lnk[0]+2; k++){
    1434:     PetscPrintf(PETSC_COMM_SELF," %D: (%D, %D)\n",2*k,lnk[2*k],lnk[2*k+1]);
    1435:   }
    1436:   return(0);
    1437: }

    1439: /*
    1440:   Free memories used by the list
    1441: */
    1442: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk,PetscBT bt)
    1443: {

    1447:   PetscFree(lnk);
    1448:   PetscBTDestroy(&bt);
    1449:   return(0);
    1450: }

    1452: /* -------------------------------------------------------------------------------------------------------*/
    1453: /*
    1454:  Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
    1455:   Input Parameters:
    1456:     nlnk_max  - max length of the list
    1457:   Output Parameters:
    1458:     lnk       - list created and initialized
    1459: */
    1460: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max,PetscInt **lnk)
    1461: {
    1463:   PetscInt       *llnk,lsize = 0;

    1466:   PetscIntMultError(2,nlnk_max+2,&lsize);
    1467:   PetscMalloc1(lsize,lnk);
    1468:   llnk = *lnk;
    1469:   llnk[0] = 0;               /* number of entries on the list */
    1470:   llnk[2] = PETSC_MAX_INT;   /* value in the head node */
    1471:   llnk[3] = 2;               /* next for the head node */
    1472:   return(0);
    1473: }

    1475: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max,PetscInt **lnk)
    1476: {
    1478:   PetscInt       lsize = 0;

    1481:   PetscIntMultError(2,nlnk_max+2,&lsize);
    1482:   PetscRealloc(lsize*sizeof(PetscInt),lnk);
    1483:   return(0);
    1484: }

    1486: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
    1487: {
    1488:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
    1489:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
    1490:   _location = 2; /* head */ \
    1491:     for (_k=0; _k<nidx; _k++){
    1492:       _entry = indices[_k];
    1493:       /* search for insertion location */
    1494:       do {
    1495:         _next     = _location + 1; /* link from previous node to next node */
    1496:         _location = lnk[_next];    /* idx of next node */
    1497:         _lnkdata  = lnk[_location];/* value of next node */
    1498:       } while (_entry > _lnkdata);
    1499:       if (_entry < _lnkdata) {
    1500:         /* insertion location is found, add entry into lnk */
    1501:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
    1502:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
    1503:         lnk[_newnode]   = _entry;        /* set value of the new node */
    1504:         lnk[_newnode+1] = _location;     /* connect new node to next node */
    1505:         _location       = _newnode;      /* next search starts from the new node */
    1506:         _nlnk++;
    1507:       }
    1508:     }
    1509:   lnk[0]   = _nlnk;   /* number of entries in the list */
    1510:   return 0;
    1511: }

    1513: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_Scalable(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
    1514: {
    1515:   PetscInt _k,_next,_nlnk;
    1516:   _next = lnk[3];       /* head node */
    1517:   _nlnk = lnk[0];
    1518:   for (_k=0; _k<_nlnk; _k++){
    1519:     indices[_k] = lnk[_next];
    1520:     _next       = lnk[_next + 1];
    1521:   }
    1522:   lnk[0] = 0;          /* num of entries on the list */
    1523:   lnk[3] = 2;          /* head node */
    1524:   return 0;
    1525: }

    1527: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
    1528: {
    1529:   return PetscFree(lnk);
    1530: }

    1532: /* -------------------------------------------------------------------------------------------------------*/
    1533: /*
    1534:       lnk[0]   number of links
    1535:       lnk[1]   number of entries
    1536:       lnk[3n]  value
    1537:       lnk[3n+1] len
    1538:       lnk[3n+2] link to next value

    1540:       The next three are always the first link

    1542:       lnk[3]    PETSC_MIN_INT+1
    1543:       lnk[4]    1
    1544:       lnk[5]    link to first real entry

    1546:       The next three are always the last link

    1548:       lnk[6]    PETSC_MAX_INT - 1
    1549:       lnk[7]    1
    1550:       lnk[8]    next valid link (this is the same as lnk[0] but without the decreases)
    1551: */

    1553: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max,PetscInt **lnk)
    1554: {
    1556:   PetscInt       *llnk,lsize = 0;

    1559:   PetscIntMultError(3,nlnk_max+3,&lsize);
    1560:   PetscMalloc1(lsize,lnk);
    1561:   llnk = *lnk;
    1562:   llnk[0] = 0;   /* nlnk: number of entries on the list */
    1563:   llnk[1] = 0;          /* number of integer entries represented in list */
    1564:   llnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
    1565:   llnk[4] = 1;           /* count for the first node */
    1566:   llnk[5] = 6;         /* next for the first node */
    1567:   llnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
    1568:   llnk[7] = 1;           /* count for the last node */
    1569:   llnk[8] = 0;         /* next valid node to be used */
    1570:   return(0);
    1571: }

    1573: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
    1574: {
    1575:   PetscInt k,entry,prev,next;
    1576:   prev      = 3;      /* first value */
    1577:   next      = lnk[prev+2];
    1578:   for (k=0; k<nidx; k++){
    1579:     entry = indices[k];
    1580:     /* search for insertion location */
    1581:     while (entry >= lnk[next]) {
    1582:       prev = next;
    1583:       next = lnk[next+2];
    1584:     }
    1585:     /* entry is in range of previous list */
    1586:     if (entry < lnk[prev]+lnk[prev+1]) continue;
    1587:     lnk[1]++;
    1588:     /* entry is right after previous list */
    1589:     if (entry == lnk[prev]+lnk[prev+1]) {
    1590:       lnk[prev+1]++;
    1591:       if (lnk[next] == entry+1) { /* combine two contiguous strings */
    1592:         lnk[prev+1] += lnk[next+1];
    1593:         lnk[prev+2]  = lnk[next+2];
    1594:         next         = lnk[next+2];
    1595:         lnk[0]--;
    1596:       }
    1597:       continue;
    1598:     }
    1599:     /* entry is right before next list */
    1600:     if (entry == lnk[next]-1) {
    1601:       lnk[next]--;
    1602:       lnk[next+1]++;
    1603:       prev = next;
    1604:       next = lnk[prev+2];
    1605:       continue;
    1606:     }
    1607:     /*  add entry into lnk */
    1608:     lnk[prev+2]    = 3*((lnk[8]++)+3);      /* connect previous node to the new node */
    1609:     prev           = lnk[prev+2];
    1610:     lnk[prev]      = entry;        /* set value of the new node */
    1611:     lnk[prev+1]    = 1;             /* number of values in contiguous string is one to start */
    1612:     lnk[prev+2]    = next;          /* connect new node to next node */
    1613:     lnk[0]++;
    1614:   }
    1615:   return 0;
    1616: }

    1618: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_fast(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
    1619: {
    1620:   PetscInt _k,_next,_nlnk,cnt,j;
    1621:   _next = lnk[5];       /* first node */
    1622:   _nlnk = lnk[0];
    1623:   cnt   = 0;
    1624:   for (_k=0; _k<_nlnk; _k++){
    1625:     for (j=0; j<lnk[_next+1]; j++) {
    1626:       indices[cnt++] = lnk[_next] + j;
    1627:     }
    1628:     _next       = lnk[_next + 2];
    1629:   }
    1630:   lnk[0] = 0;   /* nlnk: number of links */
    1631:   lnk[1] = 0;          /* number of integer entries represented in list */
    1632:   lnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
    1633:   lnk[4] = 1;           /* count for the first node */
    1634:   lnk[5] = 6;         /* next for the first node */
    1635:   lnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
    1636:   lnk[7] = 1;           /* count for the last node */
    1637:   lnk[8] = 0;         /* next valid location to make link */
    1638:   return 0;
    1639: }

    1641: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView_fast(PetscInt *lnk)
    1642: {
    1643:   PetscInt k,next,nlnk;
    1644:   next = lnk[5];       /* first node */
    1645:   nlnk = lnk[0];
    1646:   for (k=0; k<nlnk; k++){
    1647: #if 0                           /* Debugging code */
    1648:     printf("%d value %d len %d next %d\n",next,lnk[next],lnk[next+1],lnk[next+2]);
    1649: #endif
    1650:     next = lnk[next + 2];
    1651:   }
    1652:   return 0;
    1653: }

    1655: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
    1656: {
    1657:   return PetscFree(lnk);
    1658: }

    1660: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
    1661: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,void*);

    1663: PETSC_EXTERN PetscLogEvent MAT_Mult;
    1664: PETSC_EXTERN PetscLogEvent MAT_MultMatrixFree;
    1665: PETSC_EXTERN PetscLogEvent MAT_Mults;
    1666: PETSC_EXTERN PetscLogEvent MAT_MultConstrained;
    1667: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
    1668: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
    1669: PETSC_EXTERN PetscLogEvent MAT_MultTransposeConstrained;
    1670: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
    1671: PETSC_EXTERN PetscLogEvent MAT_Solve;
    1672: PETSC_EXTERN PetscLogEvent MAT_Solves;
    1673: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
    1674: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
    1675: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
    1676: PETSC_EXTERN PetscLogEvent MAT_SOR;
    1677: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
    1678: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
    1679: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
    1680: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
    1681: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
    1682: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
    1683: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
    1684: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
    1685: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
    1686: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
    1687: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
    1688: PETSC_EXTERN PetscLogEvent MAT_Copy;
    1689: PETSC_EXTERN PetscLogEvent MAT_Convert;
    1690: PETSC_EXTERN PetscLogEvent MAT_Scale;
    1691: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
    1692: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
    1693: PETSC_EXTERN PetscLogEvent MAT_SetValues;
    1694: PETSC_EXTERN PetscLogEvent MAT_GetValues;
    1695: PETSC_EXTERN PetscLogEvent MAT_GetRow;
    1696: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
    1697: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
    1698: PETSC_EXTERN PetscLogEvent MAT_GetColoring;
    1699: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
    1700: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
    1701: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
    1702: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
    1703: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
    1704: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
    1705: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
    1706: PETSC_EXTERN PetscLogEvent MAT_Load;
    1707: PETSC_EXTERN PetscLogEvent MAT_View;
    1708: PETSC_EXTERN PetscLogEvent MAT_AXPY;
    1709: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
    1710: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
    1711: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
    1712: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
    1713: PETSC_EXTERN PetscLogEvent MAT_Transpose;
    1714: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
    1715: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
    1716: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
    1717: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
    1718: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
    1719: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
    1720: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
    1721: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
    1722: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
    1723: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
    1724: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
    1725: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
    1726: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
    1727: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
    1728: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
    1729: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
    1730: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
    1731: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
    1732: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
    1733: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
    1734: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
    1735: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
    1736: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
    1737: PETSC_EXTERN PetscLogEvent MAT_Applypapt;
    1738: PETSC_EXTERN PetscLogEvent MAT_Applypapt_symbolic;
    1739: PETSC_EXTERN PetscLogEvent MAT_Applypapt_numeric;
    1740: PETSC_EXTERN PetscLogEvent MAT_Getsymtranspose;
    1741: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
    1742: PETSC_EXTERN PetscLogEvent MAT_GetSequentialNonzeroStructure;
    1743: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
    1744: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
    1745: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
    1746: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
    1747: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
    1748: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
    1749: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
    1750: PETSC_EXTERN PetscLogEvent MAT_Merge;
    1751: PETSC_EXTERN PetscLogEvent MAT_Residual;
    1752: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
    1753: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
    1754: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
    1755: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
    1756: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
    1757: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
    1758: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
    1759: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
    1760: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;

    1762: #endif