Date: 2021-03-03T22:28:21+00:00

Actual source code: matimpl.h
petsc-3.14.5 2021-03-03
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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 (*setinf)(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)(void);
    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)(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)(void);
    142:   PetscErrorCode (*matmultsymbolic)(Mat,Mat,PetscReal,Mat);
    143:   PetscErrorCode (*matmultnumeric)(Mat,Mat,Mat);
    144:   PetscErrorCode (*placeholder_92)(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)(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)(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)(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);
    238: #if defined(PETSC_HAVE_SCALAPACK)
    239: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
    240: #endif

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

    254: #if defined(PETSC_USE_DEBUG)
    255: #  define MatCheckPreallocated(A,arg) do {                              \
    256:     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); \
    257:   } while (0)
    258: #else
    259: #  define MatCheckPreallocated(A,arg) do {} while (0)
    260: #endif

    262: #if defined(PETSC_USE_DEBUG)
    263: #  define MatCheckProduct(A,arg) do {                              \
    264:     if (PetscUnlikely(!(A)->product)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Argument %D \"%s\" is not a matrix obtained from MatProductCreate()",(arg),#A); \
    265:   } while (0)
    266: #else
    267: #  define MatCheckProduct(A,arg) do {} while (0)
    268: #endif

    270: /*
    271:   The stash is used to temporarily store inserted matrix values that
    272:   belong to another processor. During the assembly phase the stashed
    273:   values are moved to the correct processor and
    274: */

    276: typedef struct _MatStashSpace *PetscMatStashSpace;

    278: struct _MatStashSpace {
    279:   PetscMatStashSpace next;
    280:   PetscScalar        *space_head,*val;
    281:   PetscInt           *idx,*idy;
    282:   PetscInt           total_space_size;
    283:   PetscInt           local_used;
    284:   PetscInt           local_remaining;
    285: };

    287: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt,PetscInt,PetscMatStashSpace *);
    288: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt,PetscMatStashSpace *,PetscScalar *,PetscInt *,PetscInt *);
    289: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace*);

    291: typedef struct {
    292:   PetscInt    count;
    293: } MatStashHeader;

    295: typedef struct {
    296:   void        *buffer;          /* Of type blocktype, dynamically constructed  */
    297:   PetscInt    count;
    298:   char        pending;
    299: } MatStashFrame;

    301: typedef struct _MatStash MatStash;
    302: struct _MatStash {
    303:   PetscInt      nmax;                   /* maximum stash size */
    304:   PetscInt      umax;                   /* user specified max-size */
    305:   PetscInt      oldnmax;                /* the nmax value used previously */
    306:   PetscInt      n;                      /* stash size */
    307:   PetscInt      bs;                     /* block size of the stash */
    308:   PetscInt      reallocs;               /* preserve the no of mallocs invoked */
    309:   PetscMatStashSpace space_head,space;  /* linked list to hold stashed global row/column numbers and matrix values */

    311:   PetscErrorCode (*ScatterBegin)(Mat,MatStash*,PetscInt*);
    312:   PetscErrorCode (*ScatterGetMesg)(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
    313:   PetscErrorCode (*ScatterEnd)(MatStash*);
    314:   PetscErrorCode (*ScatterDestroy)(MatStash*);

    316:   /* The following variables are used for communication */
    317:   MPI_Comm      comm;
    318:   PetscMPIInt   size,rank;
    319:   PetscMPIInt   tag1,tag2;
    320:   MPI_Request   *send_waits;            /* array of send requests */
    321:   MPI_Request   *recv_waits;            /* array of receive requests */
    322:   MPI_Status    *send_status;           /* array of send status */
    323:   PetscInt      nsends,nrecvs;          /* numbers of sends and receives */
    324:   PetscScalar   *svalues;               /* sending data */
    325:   PetscInt      *sindices;
    326:   PetscScalar   **rvalues;              /* receiving data (values) */
    327:   PetscInt      **rindices;             /* receiving data (indices) */
    328:   PetscInt      nprocessed;             /* number of messages already processed */
    329:   PetscMPIInt   *flg_v;                 /* indicates what messages have arrived so far and from whom */
    330:   PetscBool     reproduce;
    331:   PetscInt      reproduce_count;

    333:   /* The following variables are used for BTS communication */
    334:   PetscBool      first_assembly_done;   /* Is the first time matrix assembly done? */
    335:   PetscBool      use_status;            /* Use MPI_Status to determine number of items in each message */
    336:   PetscMPIInt    nsendranks;
    337:   PetscMPIInt    nrecvranks;
    338:   PetscMPIInt    *sendranks;
    339:   PetscMPIInt    *recvranks;
    340:   MatStashHeader *sendhdr,*recvhdr;
    341:   MatStashFrame  *sendframes;   /* pointers to the main messages */
    342:   MatStashFrame  *recvframes;
    343:   MatStashFrame  *recvframe_active;
    344:   PetscInt       recvframe_i;     /* index of block within active frame */
    345:   PetscMPIInt    recvframe_count; /* Count actually sent for current frame */
    346:   PetscInt       recvcount;       /* Number of receives processed so far */
    347:   PetscMPIInt    *some_indices;   /* From last call to MPI_Waitsome */
    348:   MPI_Status     *some_statuses;  /* Statuses from last call to MPI_Waitsome */
    349:   PetscMPIInt    some_count;      /* Number of requests completed in last call to MPI_Waitsome */
    350:   PetscMPIInt    some_i;          /* Index of request currently being processed */
    351:   MPI_Request    *sendreqs;
    352:   MPI_Request    *recvreqs;
    353:   PetscSegBuffer segsendblocks;
    354:   PetscSegBuffer segrecvframe;
    355:   PetscSegBuffer segrecvblocks;
    356:   MPI_Datatype   blocktype;
    357:   size_t         blocktype_size;
    358:   InsertMode     *insertmode;   /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
    359: };

    361: #if !defined(PETSC_HAVE_MPIUNI)
    362: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash*);
    363: #endif
    364: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm,PetscInt,MatStash*);
    365: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash*);
    366: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash*);
    367: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash*,PetscInt);
    368: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash*,PetscInt*,PetscInt*);
    369: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscBool);
    370: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscBool);
    371: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
    372: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
    373: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat,MatStash*,PetscInt*);
    374: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
    375: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat,MatInfoType,MatInfo*);

    377: typedef struct {
    378:   PetscInt   dim;
    379:   PetscInt   dims[4];
    380:   PetscInt   starts[4];
    381:   PetscBool  noc;        /* this is a single component problem, hence user will not set MatStencil.c */
    382: } MatStencilInfo;

    384: /* Info about using compressed row format */
    385: typedef struct {
    386:   PetscBool  use;                           /* indicates compressed rows have been checked and will be used */
    387:   PetscInt   nrows;                         /* number of non-zero rows */
    388:   PetscInt   *i;                            /* compressed row pointer  */
    389:   PetscInt   *rindex;                       /* compressed row index               */
    390: } Mat_CompressedRow;
    391: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat,PetscInt,Mat_CompressedRow*,PetscInt*,PetscInt,PetscReal);

    393: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
    394:   PetscInt     nzlocal,nsends,nrecvs;
    395:   PetscMPIInt  *send_rank,*recv_rank;
    396:   PetscInt     *sbuf_nz,*rbuf_nz,*sbuf_j,**rbuf_j;
    397:   PetscScalar  *sbuf_a,**rbuf_a;
    398:   MPI_Comm     subcomm;   /* when user does not provide a subcomm */
    399:   IS           isrow,iscol;
    400:   Mat          *matseq;
    401: } Mat_Redundant;

    403: typedef struct { /* used by MatProduct() */
    404:   MatProductType type;
    405:   char           *alg;
    406:   Mat            A,B,C,Dwork;
    407:   PetscReal      fill;
    408:   PetscBool      api_user; /* used by MatProductSetFromOptions_xxx() to distinguish command line options */

    410:   /* Some products may display the information on the algorithm used */
    411:   PetscErrorCode (*view)(Mat,PetscViewer);

    413:   /* many products have intermediate data structures, each specific to Mat types and product type */
    414:   PetscBool      clear;             /* whether or not to clear the data structures after MatProductNumeric has been called */
    415:   void           *data;             /* where to stash those structures */
    416:   PetscErrorCode (*destroy)(void*); /* destroy routine */
    417: } Mat_Product;

    419: #define CSRDataStructure(datatype)  \
    420:   int         *i; \
    421:   int         *j; \
    422:   datatype    *a;\
    423:   PetscInt    n;\
    424:   PetscInt    ignorezeroentries;

    426: typedef struct {
    427:   CSRDataStructure(PetscScalar)
    428: } PetscCSRDataStructure;

    430: struct _p_SplitCSRMat {
    431:   PetscInt              cstart,cend,rstart,rend;
    432:   PetscCSRDataStructure diag,offdiag;
    433:   PetscInt              *colmap;
    434:   PetscBool             seq;
    435:   PetscMPIInt           rank;
    436:   PetscInt              nonzerostate;
    437: };

    439: struct _p_Mat {
    440:   PETSCHEADER(struct _MatOps);
    441:   PetscLayout            rmap,cmap;
    442:   void                   *data;            /* implementation-specific data */
    443:   MatFactorType          factortype;       /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
    444:   PetscBool              useordering;      /* factorization using ordering provide to routine (most PETSc implementations) */
    445:   PetscBool              assembled;        /* is the matrix assembled? */
    446:   PetscBool              was_assembled;    /* new values inserted into assembled mat */
    447:   PetscInt               num_ass;          /* number of times matrix has been assembled */
    448:   PetscObjectState       nonzerostate;     /* each time new nonzeros locations are introduced into the matrix this is updated */
    449:   PetscObjectState       ass_nonzerostate; /* nonzero state at last assembly */
    450:   MatInfo                info;             /* matrix information */
    451:   InsertMode             insertmode;       /* have values been inserted in matrix or added? */
    452:   MatStash               stash,bstash;     /* used for assembling off-proc mat emements */
    453:   MatNullSpace           nullsp;           /* null space (operator is singular) */
    454:   MatNullSpace           transnullsp;      /* null space of transpose of operator */
    455:   MatNullSpace           nearnullsp;       /* near null space to be used by multigrid methods */
    456:   PetscInt               congruentlayouts; /* are the rows and columns layouts congruent? */
    457:   PetscBool              preallocated;
    458:   MatStencilInfo         stencil;          /* information for structured grid */
    459:   PetscBool              symmetric,hermitian,structurally_symmetric,spd;
    460:   PetscBool              symmetric_set,hermitian_set,structurally_symmetric_set,spd_set; /* if true, then corresponding flag is correct*/
    461:   PetscBool              symmetric_eternal;
    462:   PetscBool              nooffprocentries,nooffproczerorows;
    463:   PetscBool              assembly_subset;  /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
    464:   PetscBool              submat_singleis;  /* for efficient PCSetUp_ASM() */
    465:   PetscBool              structure_only;
    466:   PetscBool              sortedfull;       /* full, sorted rows are inserted */
    467: #if defined(PETSC_HAVE_DEVICE)
    468:   PetscOffloadMask       offloadmask;      /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
    469:   PetscBool              boundtocpu;
    470: #endif
    471:   void                   *spptr;          /* pointer for special library like SuperLU */
    472:   char                   *solvertype;
    473:   PetscBool              checksymmetryonassembly,checknullspaceonassembly;
    474:   PetscReal              checksymmetrytol;
    475:   Mat                    schur;             /* Schur complement matrix */
    476:   MatFactorSchurStatus   schur_status;      /* status of the Schur complement matrix */
    477:   Mat_Redundant          *redundant;        /* used by MatCreateRedundantMatrix() */
    478:   PetscBool              erroriffailure;    /* Generate an error if detected (for example a zero pivot) instead of returning */
    479:   MatFactorError         factorerrortype;               /* type of error in factorization */
    480:   PetscReal              factorerror_zeropivot_value;   /* If numerical zero pivot was detected this is the computed value */
    481:   PetscInt               factorerror_zeropivot_row;     /* Row where zero pivot was detected */
    482:   PetscInt               nblocks,*bsizes;   /* support for MatSetVariableBlockSizes() */
    483:   char                   *defaultvectype;
    484:   Mat_Product            *product;
    485: };

    487: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat,PetscScalar,Mat,MatStructure);
    488: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat,Mat,PetscScalar,Mat,MatStructure);
    489: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat,Mat,Mat*);

    491: /*
    492:     Utility for MatFactor (Schur complement)
    493: */
    494: PETSC_INTERN PetscErrorCode MatFactorFactorizeSchurComplement_Private(Mat);
    495: PETSC_INTERN PetscErrorCode MatFactorInvertSchurComplement_Private(Mat);
    496: PETSC_INTERN PetscErrorCode MatFactorUpdateSchurStatus_Private(Mat);
    497: PETSC_INTERN PetscErrorCode MatFactorSetUpInPlaceSchur_Private(Mat);

    499: /*
    500:     Utility for MatZeroRows
    501: */
    502: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat,PetscInt,const PetscInt*,PetscInt*,PetscInt**);

    504: /*
    505:     Utility for MatView/MatLoad
    506: */
    507: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat,PetscViewer);
    508: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat,PetscViewer);

    511: /*
    512:     Object for partitioning graphs
    513: */

    515: typedef struct _MatPartitioningOps *MatPartitioningOps;
    516: struct _MatPartitioningOps {
    517:   PetscErrorCode (*apply)(MatPartitioning,IS*);
    518:   PetscErrorCode (*applynd)(MatPartitioning,IS*);
    519:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatPartitioning);
    520:   PetscErrorCode (*destroy)(MatPartitioning);
    521:   PetscErrorCode (*view)(MatPartitioning,PetscViewer);
    522:   PetscErrorCode (*improve)(MatPartitioning,IS*);
    523: };

    525: struct _p_MatPartitioning {
    526:   PETSCHEADER(struct _MatPartitioningOps);
    527:   Mat         adj;
    528:   PetscInt    *vertex_weights;
    529:   PetscReal   *part_weights;
    530:   PetscInt    n;                                 /* number of partitions */
    531:   void        *data;
    532:   PetscInt    setupcalled;
    533:   PetscBool   use_edge_weights;  /* A flag indicates whether or not to use edge weights */
    534: };

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

    539: /*
    540:     Object for coarsen graphs
    541: */
    542: typedef struct _MatCoarsenOps *MatCoarsenOps;
    543: struct _MatCoarsenOps {
    544:   PetscErrorCode (*apply)(MatCoarsen);
    545:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatCoarsen);
    546:   PetscErrorCode (*destroy)(MatCoarsen);
    547:   PetscErrorCode (*view)(MatCoarsen,PetscViewer);
    548: };

    550: struct _p_MatCoarsen {
    551:   PETSCHEADER(struct _MatCoarsenOps);
    552:   Mat              graph;
    553:   void             *subctx;
    554:   /* */
    555:   PetscBool        strict_aggs;
    556:   IS               perm;
    557:   PetscCoarsenData *agg_lists;
    558: };

    560: /*
    561:     MatFDColoring is used to compute Jacobian matrices efficiently
    562:   via coloring. The data structure is explained below in an example.

    564:    Color =   0    1     0    2   |   2      3       0
    565:    ---------------------------------------------------
    566:             00   01              |          05
    567:             10   11              |   14     15               Processor  0
    568:                        22    23  |          25
    569:                        32    33  |
    570:    ===================================================
    571:                                  |   44     45     46
    572:             50                   |          55               Processor 1
    573:                                  |   64            66
    574:    ---------------------------------------------------

    576:     ncolors = 4;

    578:     ncolumns      = {2,1,1,0}
    579:     columns       = {{0,2},{1},{3},{}}
    580:     nrows         = {4,2,3,3}
    581:     rows          = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
    582:     vwscale       = {dx(0),dx(1),dx(2),dx(3)}               MPI Vec
    583:     vscale        = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)}   Seq Vec

    585:     ncolumns      = {1,0,1,1}
    586:     columns       = {{6},{},{4},{5}}
    587:     nrows         = {3,0,2,2}
    588:     rows          = {{0,1,2},{},{1,2},{1,2}}
    589:     vwscale       = {dx(4),dx(5),dx(6)}              MPI Vec
    590:     vscale        = {dx(0),dx(4),dx(5),dx(6)}        Seq Vec

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

    595: */
    596: typedef struct {
    597:   PetscInt     row;
    598:   PetscInt     col;
    599:   PetscScalar  *valaddr;   /* address of value */
    600: } MatEntry;

    602: typedef struct {
    603:   PetscInt     row;
    604:   PetscScalar  *valaddr;   /* address of value */
    605: } MatEntry2;

    607: struct  _p_MatFDColoring{
    608:   PETSCHEADER(int);
    609:   PetscInt       M,N,m;            /* total rows, columns; local rows */
    610:   PetscInt       rstart;           /* first row owned by local processor */
    611:   PetscInt       ncolors;          /* number of colors */
    612:   PetscInt       *ncolumns;        /* number of local columns for a color */
    613:   PetscInt       **columns;        /* lists the local columns of each color (using global column numbering) */
    614:   IS             *isa;             /* these are the IS that contain the column values given in columns */
    615:   PetscInt       *nrows;           /* number of local rows for each color */
    616:   MatEntry       *matentry;        /* holds (row, column, address of value) for Jacobian matrix entry */
    617:   MatEntry2      *matentry2;       /* holds (row, address of value) for Jacobian matrix entry */
    618:   PetscScalar    *dy;              /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
    619:   PetscReal      error_rel;        /* square root of relative error in computing function */
    620:   PetscReal      umin;             /* minimum allowable u'dx value */
    621:   Vec            w1,w2,w3;         /* work vectors used in computing Jacobian */
    622:   PetscBool      fset;             /* indicates that the initial function value F(X) is set */
    623:   PetscErrorCode (*f)(void);       /* function that defines Jacobian */
    624:   void           *fctx;            /* optional user-defined context for use by the function f */
    625:   Vec            vscale;           /* holds FD scaling, i.e. 1/dx for each perturbed column */
    626:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
    627:   const char     *htype;           /* "wp" or "ds" */
    628:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
    629:   PetscInt       brows,bcols;      /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
    630:   PetscBool      setupcalled;      /* true if setup has been called */
    631:   PetscBool      viewed;           /* true if the -mat_fd_coloring_view has been triggered already */
    632:   void           (*ftn_func_pointer)(void),*ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
    633:   PetscObjectId  matid;            /* matrix this object was created with, must always be the same */
    634: };

    636: typedef struct _MatColoringOps *MatColoringOps;
    637: struct _MatColoringOps {
    638:   PetscErrorCode (*destroy)(MatColoring);
    639:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatColoring);
    640:   PetscErrorCode (*view)(MatColoring,PetscViewer);
    641:   PetscErrorCode (*apply)(MatColoring,ISColoring*);
    642:   PetscErrorCode (*weights)(MatColoring,PetscReal**,PetscInt**);
    643: };

    645: struct _p_MatColoring {
    646:   PETSCHEADER(struct _MatColoringOps);
    647:   Mat                   mat;
    648:   PetscInt              dist;             /* distance of the coloring */
    649:   PetscInt              maxcolors;        /* the maximum number of colors returned, maxcolors=1 for MIS */
    650:   void                  *data;            /* inner context */
    651:   PetscBool             valid;            /* check to see if what is produced is a valid coloring */
    652:   MatColoringWeightType weight_type;      /* type of weight computation to be performed */
    653:   PetscReal             *user_weights;    /* custom weights and permutation */
    654:   PetscInt              *user_lperm;
    655:   PetscBool             valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
    656: };

    658: struct  _p_MatTransposeColoring{
    659:   PETSCHEADER(int);
    660:   PetscInt       M,N,m;            /* total rows, columns; local rows */
    661:   PetscInt       rstart;           /* first row owned by local processor */
    662:   PetscInt       ncolors;          /* number of colors */
    663:   PetscInt       *ncolumns;        /* number of local columns for a color */
    664:   PetscInt       *nrows;           /* number of local rows for each color */
    665:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
    666:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */

    668:   PetscInt       *colorforrow,*colorforcol;  /* pointer to rows and columns */
    669:   PetscInt       *rows;                      /* lists the local rows for each color (using the local row numbering) */
    670:   PetscInt       *den2sp;                    /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
    671:   PetscInt       *columns;                   /* lists the local columns of each color (using global column numbering) */
    672:   PetscInt       brows;                      /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
    673:   PetscInt       *lstart;                    /* array used for loop over row blocks of Csparse */
    674: };

    676: /*
    677:    Null space context for preconditioner/operators
    678: */
    679: struct _p_MatNullSpace {
    680:   PETSCHEADER(int);
    681:   PetscBool      has_cnst;
    682:   PetscInt       n;
    683:   Vec*           vecs;
    684:   PetscScalar*   alpha;                 /* for projections */
    685:   PetscErrorCode (*remove)(MatNullSpace,Vec,void*);  /* for user provided removal function */
    686:   void*          rmctx;                 /* context for remove() function */
    687: };

    689: /*
    690:    Checking zero pivot for LU, ILU preconditioners.
    691: */
    692: typedef struct {
    693:   PetscInt       nshift,nshift_max;
    694:   PetscReal      shift_amount,shift_lo,shift_hi,shift_top,shift_fraction;
    695:   PetscBool      newshift;
    696:   PetscReal      rs;  /* active row sum of abs(offdiagonals) */
    697:   PetscScalar    pv;  /* pivot of the active row */
    698: } FactorShiftCtx;

    700: /*
    701:  Used by MatCreateSubMatrices_MPIXAIJ_Local()
    702: */
    703: #include <petscctable.h>
    704: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
    705:   PetscInt   id;   /* index of submats, only submats[0] is responsible for deleting some arrays below */
    706:   PetscInt   nrqs,nrqr;
    707:   PetscInt   **rbuf1,**rbuf2,**rbuf3,**sbuf1,**sbuf2;
    708:   PetscInt   **ptr;
    709:   PetscInt   *tmp;
    710:   PetscInt   *ctr;
    711:   PetscInt   *pa; /* proc array */
    712:   PetscInt   *req_size,*req_source1,*req_source2;
    713:   PetscBool  allcolumns,allrows;
    714:   PetscBool  singleis;
    715:   PetscInt   *row2proc; /* row to proc map */
    716:   PetscInt   nstages;
    717: #if defined(PETSC_USE_CTABLE)
    718:   PetscTable cmap,rmap;
    719:   PetscInt   *cmap_loc,*rmap_loc;
    720: #else
    721:   PetscInt   *cmap,*rmap;
    722: #endif

    724:   PetscErrorCode (*destroy)(Mat);
    725: } Mat_SubSppt;

    727: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
    728: PETSC_INTERN PetscErrorCode MatShift_Basic(Mat,PetscScalar);
    729: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat,PetscInt,PetscInt);

    731: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_nz(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    732: {
    733:   PetscReal _rs   = sctx->rs;
    734:   PetscReal _zero = info->zeropivot*_rs;

    737:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
    738:     /* force |diag| > zeropivot*rs */
    739:     if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
    740:     else sctx->shift_amount *= 2.0;
    741:     sctx->newshift = PETSC_TRUE;
    742:     (sctx->nshift)++;
    743:   } else {
    744:     sctx->newshift = PETSC_FALSE;
    745:   }
    746:   return(0);
    747: }

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

    755:   if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
    756:     /* force matfactor to be diagonally dominant */
    757:     if (sctx->nshift == sctx->nshift_max) {
    758:       sctx->shift_fraction = sctx->shift_hi;
    759:     } else {
    760:       sctx->shift_lo = sctx->shift_fraction;
    761:       sctx->shift_fraction = (sctx->shift_hi+sctx->shift_lo)/2.;
    762:     }
    763:     sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
    764:     sctx->nshift++;
    765:     sctx->newshift = PETSC_TRUE;
    766:   } else {
    767:     sctx->newshift = PETSC_FALSE;
    768:   }
    769:   return(0);
    770: }

    772: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_inblocks(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    773: {
    774:   PetscReal _zero = info->zeropivot;

    777:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
    778:     sctx->pv          += info->shiftamount;
    779:     sctx->shift_amount = 0.0;
    780:     sctx->nshift++;
    781:   }
    782:   sctx->newshift = PETSC_FALSE;
    783:   return(0);
    784: }

    786: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_none(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    787: {
    788:   PetscReal      _zero = info->zeropivot;

    792:   sctx->newshift = PETSC_FALSE;
    793:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
    794:     if (!mat->erroriffailure) {
    795:       PetscInfo3(mat,"Detected zero pivot in factorization in row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
    796:       fact->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    797:       fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
    798:       fact->factorerror_zeropivot_row   = row;
    799:     } 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);
    800:   }
    801:   return(0);
    802: }

    804: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
    805: {

    809:   if (info->shifttype == (PetscReal) MAT_SHIFT_NONZERO){
    810:     MatPivotCheck_nz(mat,info,sctx,row);
    811:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_POSITIVE_DEFINITE){
    812:     MatPivotCheck_pd(mat,info,sctx,row);
    813:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_INBLOCKS){
    814:     MatPivotCheck_inblocks(mat,info,sctx,row);
    815:   } else {
    816:     MatPivotCheck_none(fact,mat,info,sctx,row);
    817:   }
    818:   return(0);
    819: }

    821: /*
    822:   Create and initialize a linked list
    823:   Input Parameters:
    824:     idx_start - starting index of the list
    825:     lnk_max   - max value of lnk indicating the end of the list
    826:     nlnk      - max length of the list
    827:   Output Parameters:
    828:     lnk       - list initialized
    829:     bt        - PetscBT (bitarray) with all bits set to false
    830:     lnk_empty - flg indicating the list is empty
    831: */
    832: #define PetscLLCreate(idx_start,lnk_max,nlnk,lnk,bt) \
    833:   (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,0))

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

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

    875: /*
    876:   Add a permuted index set into a sorted linked list
    877:   Input Parameters:
    878:     nidx      - number of input indices
    879:     indices   - integer array
    880:     perm      - permutation of indices
    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 PetscLLAddPerm(nidx,indices,perm,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 = perm[indices[_k]];\
    896:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    897:       /* search for insertion location */\
    898:       /* start from the beginning if _entry < previous _entry */\
    899:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    900:       do {\
    901:         _location = _lnkdata;\
    902:         _lnkdata  = lnk[_location];\
    903:       } while (_entry > _lnkdata);\
    904:       /* insertion location is found, add entry into lnk */\
    905:       lnk[_location] = _entry;\
    906:       lnk[_entry]    = _lnkdata;\
    907:       nlnk++;\
    908:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    909:     }\
    910:   }\
    911: }

    913: /*
    914:   Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata  = idx_start;'
    915:   Input Parameters:
    916:     nidx      - number of input indices
    917:     indices   - sorted integer array
    918:     idx_start - starting index of the list
    919:     lnk       - linked list(an integer array) that is created
    920:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    921:   output Parameters:
    922:     nlnk      - number of newly added indices
    923:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
    924:     bt        - updated PetscBT (bitarray)
    925: */
    926: #define PetscLLAddSorted(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
    927: {\
    928:   PetscInt _k,_entry,_location,_lnkdata;\
    929:   nlnk      = 0;\
    930:   _lnkdata  = idx_start;\
    931:   for (_k=0; _k<nidx; _k++){\
    932:     _entry = indices[_k];\
    933:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    934:       /* search for insertion location */\
    935:       do {\
    936:         _location = _lnkdata;\
    937:         _lnkdata  = lnk[_location];\
    938:       } while (_entry > _lnkdata);\
    939:       /* insertion location is found, add entry into lnk */\
    940:       lnk[_location] = _entry;\
    941:       lnk[_entry]    = _lnkdata;\
    942:       nlnk++;\
    943:       _lnkdata = _entry; /* next search starts from here */\
    944:     }\
    945:   }\
    946: }

    948: #define PetscLLAddSorted_new(nidx,indices,idx_start,lnk_empty,nlnk,lnk,bt) 0; \
    949: {\
    950:   PetscInt _k,_entry,_location,_lnkdata;\
    951:   if (lnk_empty){\
    952:     _lnkdata  = idx_start;                      \
    953:     for (_k=0; _k<nidx; _k++){                  \
    954:       _entry = indices[_k];                             \
    955:       PetscBTSet(bt,_entry);  /* mark the new entry */          \
    956:           _location = _lnkdata;                                 \
    957:           _lnkdata  = lnk[_location];                           \
    958:         /* insertion location is found, add entry into lnk */   \
    959:         lnk[_location] = _entry;                                \
    960:         lnk[_entry]    = _lnkdata;                              \
    961:         _lnkdata = _entry; /* next search starts from here */   \
    962:     }                                                           \
    963:     /*\
    964:     lnk[indices[nidx-1]] = lnk[idx_start];\
    965:     lnk[idx_start]       = indices[0];\
    966:     PetscBTSet(bt,indices[0]);  \
    967:     for (_k=1; _k<nidx; _k++){                  \
    968:       PetscBTSet(bt,indices[_k]);                                          \
    969:       lnk[indices[_k-1]] = indices[_k];                                  \
    970:     }                                                           \
    971:      */\
    972:     nlnk      = nidx;\
    973:     lnk_empty = PETSC_FALSE;\
    974:   } else {\
    975:     nlnk      = 0;                              \
    976:     _lnkdata  = idx_start;                      \
    977:     for (_k=0; _k<nidx; _k++){                  \
    978:       _entry = indices[_k];                             \
    979:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */       \
    980:         /* search for insertion location */                     \
    981:         do {                                                    \
    982:           _location = _lnkdata;                                 \
    983:           _lnkdata  = lnk[_location];                           \
    984:         } while (_entry > _lnkdata);                            \
    985:         /* insertion location is found, add entry into lnk */   \
    986:         lnk[_location] = _entry;                                \
    987:         lnk[_entry]    = _lnkdata;                              \
    988:         nlnk++;                                                 \
    989:         _lnkdata = _entry; /* next search starts from here */   \
    990:       }                                                         \
    991:     }                                                           \
    992:   }                                                             \
    993: }

    995: /*
    996:   Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
    997:   Same as PetscLLAddSorted() with an additional operation:
    998:        count the number of input indices that are no larger than 'diag'
    999:   Input Parameters:
    1000:     indices   - sorted integer array
    1001:     idx_start - starting index of the list, index of pivot row
    1002:     lnk       - linked list(an integer array) that is created
    1003:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1004:     diag      - index of the active row in LUFactorSymbolic
    1005:     nzbd      - number of input indices with indices <= idx_start
    1006:     im        - im[idx_start] is initialized as num of nonzero entries in row=idx_start
    1007:   output Parameters:
    1008:     nlnk      - number of newly added indices
    1009:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
    1010:     bt        - updated PetscBT (bitarray)
    1011:     im        - im[idx_start]: unchanged if diag is not an entry
    1012:                              : num of entries with indices <= diag if diag is an entry
    1013: */
    1014: #define PetscLLAddSortedLU(indices,idx_start,nlnk,lnk,bt,diag,nzbd,im) 0;\
    1015: {\
    1016:   PetscInt _k,_entry,_location,_lnkdata,_nidx;\
    1017:   nlnk     = 0;\
    1018:   _lnkdata = idx_start;\
    1019:   _nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */\
    1020:   for (_k=0; _k<_nidx; _k++){\
    1021:     _entry = indices[_k];\
    1022:     nzbd++;\
    1023:     if (_entry== diag) im[idx_start] = nzbd;\
    1024:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1025:       /* search for insertion location */\
    1026:       do {\
    1027:         _location = _lnkdata;\
    1028:         _lnkdata  = lnk[_location];\
    1029:       } while (_entry > _lnkdata);\
    1030:       /* insertion location is found, add entry into lnk */\
    1031:       lnk[_location] = _entry;\
    1032:       lnk[_entry]    = _lnkdata;\
    1033:       nlnk++;\
    1034:       _lnkdata = _entry; /* next search starts from here */\
    1035:     }\
    1036:   }\
    1037: }

    1039: /*
    1040:   Copy data on the list into an array, then initialize the list
    1041:   Input Parameters:
    1042:     idx_start - starting index of the list
    1043:     lnk_max   - max value of lnk indicating the end of the list
    1044:     nlnk      - number of data on the list to be copied
    1045:     lnk       - linked list
    1046:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1047:   output Parameters:
    1048:     indices   - array that contains the copied data
    1049:     lnk       - linked list that is cleaned and initialize
    1050:     bt        - PetscBT (bitarray) with all bits set to false
    1051: */
    1052: #define PetscLLClean(idx_start,lnk_max,nlnk,lnk,indices,bt) 0;\
    1053: {\
    1054:   PetscInt _j,_idx=idx_start;\
    1055:   for (_j=0; _j<nlnk; _j++){\
    1056:     _idx = lnk[_idx];\
    1057:     indices[_j] = _idx;\
    1058:     PetscBTClear(bt,_idx);\
    1059:   }\
    1060:   lnk[idx_start] = lnk_max;\
    1061: }
    1062: /*
    1063:   Free memories used by the list
    1064: */
    1065: #define PetscLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

    1067: /* Routines below are used for incomplete matrix factorization */
    1068: /*
    1069:   Create and initialize a linked list and its levels
    1070:   Input Parameters:
    1071:     idx_start - starting index of the list
    1072:     lnk_max   - max value of lnk indicating the end of the list
    1073:     nlnk      - max length of the list
    1074:   Output Parameters:
    1075:     lnk       - list initialized
    1076:     lnk_lvl   - array of size nlnk for storing levels of lnk
    1077:     bt        - PetscBT (bitarray) with all bits set to false
    1078: */
    1079: #define PetscIncompleteLLCreate(idx_start,lnk_max,nlnk,lnk,lnk_lvl,bt)\
    1080:   (PetscIntMultError(2,nlnk,NULL) || PetscMalloc1(2*nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,lnk_lvl = lnk + nlnk,0))

    1082: /*
    1083:   Initialize a sorted linked list used for ILU and ICC
    1084:   Input Parameters:
    1085:     nidx      - number of input idx
    1086:     idx       - integer array used for storing column indices
    1087:     idx_start - starting index of the list
    1088:     perm      - indices of an IS
    1089:     lnk       - linked list(an integer array) that is created
    1090:     lnklvl    - levels of lnk
    1091:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1092:   output Parameters:
    1093:     nlnk     - number of newly added idx
    1094:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1095:     lnklvl   - levels of lnk
    1096:     bt       - updated PetscBT (bitarray)
    1097: */
    1098: #define PetscIncompleteLLInit(nidx,idx,idx_start,perm,nlnk,lnk,lnklvl,bt) 0;\
    1099: {\
    1100:   PetscInt _k,_entry,_location,_lnkdata;\
    1101:   nlnk     = 0;\
    1102:   _lnkdata = idx_start;\
    1103:   for (_k=0; _k<nidx; _k++){\
    1104:     _entry = perm[idx[_k]];\
    1105:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1106:       /* search for insertion location */\
    1107:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    1108:       do {\
    1109:         _location = _lnkdata;\
    1110:         _lnkdata  = lnk[_location];\
    1111:       } while (_entry > _lnkdata);\
    1112:       /* insertion location is found, add entry into lnk */\
    1113:       lnk[_location]  = _entry;\
    1114:       lnk[_entry]     = _lnkdata;\
    1115:       lnklvl[_entry] = 0;\
    1116:       nlnk++;\
    1117:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    1118:     }\
    1119:   }\
    1120: }

    1122: /*
    1123:   Add a SORTED index set into a sorted linked list for ILU
    1124:   Input Parameters:
    1125:     nidx      - number of input indices
    1126:     idx       - sorted integer array used for storing column indices
    1127:     level     - level of fill, e.g., ICC(level)
    1128:     idxlvl    - level of idx
    1129:     idx_start - starting index of the list
    1130:     lnk       - linked list(an integer array) that is created
    1131:     lnklvl    - levels of lnk
    1132:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1133:     prow      - the row number of idx
    1134:   output Parameters:
    1135:     nlnk     - number of newly added idx
    1136:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1137:     lnklvl   - levels of lnk
    1138:     bt       - updated PetscBT (bitarray)

    1140:   Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
    1141:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
    1142: */
    1143: #define PetscILULLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,lnklvl_prow) 0;\
    1144: {\
    1145:   PetscInt _k,_entry,_location,_lnkdata,_incrlev,_lnklvl_prow=lnklvl[prow];\
    1146:   nlnk     = 0;\
    1147:   _lnkdata = idx_start;\
    1148:   for (_k=0; _k<nidx; _k++){\
    1149:     _incrlev = idxlvl[_k] + _lnklvl_prow + 1;\
    1150:     if (_incrlev > level) continue;\
    1151:     _entry = idx[_k];\
    1152:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1153:       /* search for insertion location */\
    1154:       do {\
    1155:         _location = _lnkdata;\
    1156:         _lnkdata  = lnk[_location];\
    1157:       } while (_entry > _lnkdata);\
    1158:       /* insertion location is found, add entry into lnk */\
    1159:       lnk[_location]  = _entry;\
    1160:       lnk[_entry]     = _lnkdata;\
    1161:       lnklvl[_entry] = _incrlev;\
    1162:       nlnk++;\
    1163:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    1164:     } else { /* existing entry: update lnklvl */\
    1165:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1166:     }\
    1167:   }\
    1168: }

    1170: /*
    1171:   Add a index set into a sorted linked list
    1172:   Input Parameters:
    1173:     nidx      - number of input idx
    1174:     idx   - integer array used for storing column indices
    1175:     level     - level of fill, e.g., ICC(level)
    1176:     idxlvl - level of idx
    1177:     idx_start - starting index of the list
    1178:     lnk       - linked list(an integer array) that is created
    1179:     lnklvl   - levels of lnk
    1180:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1181:   output Parameters:
    1182:     nlnk      - number of newly added idx
    1183:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1184:     lnklvl   - levels of lnk
    1185:     bt        - updated PetscBT (bitarray)
    1186: */
    1187: #define PetscIncompleteLLAdd(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
    1188: {\
    1189:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
    1190:   nlnk     = 0;\
    1191:   _lnkdata = idx_start;\
    1192:   for (_k=0; _k<nidx; _k++){\
    1193:     _incrlev = idxlvl[_k] + 1;\
    1194:     if (_incrlev > level) continue;\
    1195:     _entry = idx[_k];\
    1196:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1197:       /* search for insertion location */\
    1198:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
    1199:       do {\
    1200:         _location = _lnkdata;\
    1201:         _lnkdata  = lnk[_location];\
    1202:       } while (_entry > _lnkdata);\
    1203:       /* insertion location is found, add entry into lnk */\
    1204:       lnk[_location]  = _entry;\
    1205:       lnk[_entry]     = _lnkdata;\
    1206:       lnklvl[_entry] = _incrlev;\
    1207:       nlnk++;\
    1208:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
    1209:     } else { /* existing entry: update lnklvl */\
    1210:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1211:     }\
    1212:   }\
    1213: }

    1215: /*
    1216:   Add a SORTED index set into a sorted linked list
    1217:   Input Parameters:
    1218:     nidx      - number of input indices
    1219:     idx   - sorted integer array used for storing column indices
    1220:     level     - level of fill, e.g., ICC(level)
    1221:     idxlvl - level of idx
    1222:     idx_start - starting index of the list
    1223:     lnk       - linked list(an integer array) that is created
    1224:     lnklvl    - levels of lnk
    1225:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1226:   output Parameters:
    1227:     nlnk      - number of newly added idx
    1228:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1229:     lnklvl    - levels of lnk
    1230:     bt        - updated PetscBT (bitarray)
    1231: */
    1232: #define PetscIncompleteLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
    1233: {\
    1234:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
    1235:   nlnk = 0;\
    1236:   _lnkdata = idx_start;\
    1237:   for (_k=0; _k<nidx; _k++){\
    1238:     _incrlev = idxlvl[_k] + 1;\
    1239:     if (_incrlev > level) continue;\
    1240:     _entry = idx[_k];\
    1241:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1242:       /* search for insertion location */\
    1243:       do {\
    1244:         _location = _lnkdata;\
    1245:         _lnkdata  = lnk[_location];\
    1246:       } while (_entry > _lnkdata);\
    1247:       /* insertion location is found, add entry into lnk */\
    1248:       lnk[_location] = _entry;\
    1249:       lnk[_entry]    = _lnkdata;\
    1250:       lnklvl[_entry] = _incrlev;\
    1251:       nlnk++;\
    1252:       _lnkdata = _entry; /* next search starts from here */\
    1253:     } else { /* existing entry: update lnklvl */\
    1254:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1255:     }\
    1256:   }\
    1257: }

    1259: /*
    1260:   Add a SORTED index set into a sorted linked list for ICC
    1261:   Input Parameters:
    1262:     nidx      - number of input indices
    1263:     idx       - sorted integer array used for storing column indices
    1264:     level     - level of fill, e.g., ICC(level)
    1265:     idxlvl    - level of idx
    1266:     idx_start - starting index of the list
    1267:     lnk       - linked list(an integer array) that is created
    1268:     lnklvl    - levels of lnk
    1269:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1270:     idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
    1271:   output Parameters:
    1272:     nlnk   - number of newly added indices
    1273:     lnk    - the sorted(increasing order) linked list containing new and non-redundate entries from idx
    1274:     lnklvl - levels of lnk
    1275:     bt     - updated PetscBT (bitarray)
    1276:   Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
    1277:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
    1278: */
    1279: #define PetscICCLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,idxlvl_prow) 0;\
    1280: {\
    1281:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
    1282:   nlnk = 0;\
    1283:   _lnkdata = idx_start;\
    1284:   for (_k=0; _k<nidx; _k++){\
    1285:     _incrlev = idxlvl[_k] + idxlvl_prow + 1;\
    1286:     if (_incrlev > level) continue;\
    1287:     _entry = idx[_k];\
    1288:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
    1289:       /* search for insertion location */\
    1290:       do {\
    1291:         _location = _lnkdata;\
    1292:         _lnkdata  = lnk[_location];\
    1293:       } while (_entry > _lnkdata);\
    1294:       /* insertion location is found, add entry into lnk */\
    1295:       lnk[_location] = _entry;\
    1296:       lnk[_entry]    = _lnkdata;\
    1297:       lnklvl[_entry] = _incrlev;\
    1298:       nlnk++;\
    1299:       _lnkdata = _entry; /* next search starts from here */\
    1300:     } else { /* existing entry: update lnklvl */\
    1301:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
    1302:     }\
    1303:   }\
    1304: }

    1306: /*
    1307:   Copy data on the list into an array, then initialize the list
    1308:   Input Parameters:
    1309:     idx_start - starting index of the list
    1310:     lnk_max   - max value of lnk indicating the end of the list
    1311:     nlnk      - number of data on the list to be copied
    1312:     lnk       - linked list
    1313:     lnklvl    - level of lnk
    1314:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1315:   output Parameters:
    1316:     indices - array that contains the copied data
    1317:     lnk     - linked list that is cleaned and initialize
    1318:     lnklvl  - level of lnk that is reinitialized
    1319:     bt      - PetscBT (bitarray) with all bits set to false
    1320: */
    1321: #define PetscIncompleteLLClean(idx_start,lnk_max,nlnk,lnk,lnklvl,indices,indiceslvl,bt) 0;\
    1322: do {\
    1323:   PetscInt _j,_idx=idx_start;\
    1324:   for (_j=0; _j<nlnk; _j++){\
    1325:     _idx = lnk[_idx];\
    1326:     *(indices+_j) = _idx;\
    1327:     *(indiceslvl+_j) = lnklvl[_idx];\
    1328:     lnklvl[_idx] = -1;\
    1329:     PetscBTClear(bt,_idx);\
    1330:   }\
    1331:   lnk[idx_start] = lnk_max;\
    1332: } while (0)
    1333: /*
    1334:   Free memories used by the list
    1335: */
    1336: #define PetscIncompleteLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

    1338: #define MatCheckSameLocalSize(A,ar1,B,ar2) do { \
    1340:   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)

    1342: #define MatCheckSameSize(A,ar1,B,ar2) do { \
    1343:   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);\
    1344:   MatCheckSameLocalSize(A,ar1,B,ar2);} while (0)

    1346: #define VecCheckMatCompatible(M,x,ar1,b,ar2) do { \
    1347:   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); \
    1348:   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)

    1350: /* -------------------------------------------------------------------------------------------------------*/
    1351: #include <petscbt.h>
    1352: /*
    1353:   Create and initialize a condensed linked list -
    1354:     same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
    1355:     Barry suggested this approach (Dec. 6, 2011):
    1356:       I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
    1357:       (it may be faster than the O(N) even sequentially due to less crazy memory access).

    1359:       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
    1360:       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
    1361:       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
    1362:       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.
    1363:       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
    1364:       to each other so memory access is much better than using the big array.

    1366:   Example:
    1367:      nlnk_max=5, lnk_max=36:
    1368:      Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
    1369:      here, head_node has index 2 with value lnk[2]=lnk_max=36,
    1370:            0-th entry is used to store the number of entries in the list,
    1371:      The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.

    1373:      Now adding a sorted set {2,4}, the list becomes
    1374:      [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
    1375:      represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.

    1377:      Then adding a sorted set {0,3,35}, the list
    1378:      [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
    1379:      represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.

    1381:   Input Parameters:
    1382:     nlnk_max  - max length of the list
    1383:     lnk_max   - max value of the entries
    1384:   Output Parameters:
    1385:     lnk       - list created and initialized
    1386:     bt        - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
    1387: */
    1388: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max,PetscInt lnk_max,PetscInt **lnk,PetscBT *bt)
    1389: {
    1391:   PetscInt       *llnk,lsize = 0;

    1394:   PetscIntMultError(2,nlnk_max+2,&lsize);
    1395:   PetscMalloc1(lsize,lnk);
    1396:   PetscBTCreate(lnk_max,bt);
    1397:   llnk = *lnk;
    1398:   llnk[0] = 0;         /* number of entries on the list */
    1399:   llnk[2] = lnk_max;   /* value in the head node */
    1400:   llnk[3] = 2;         /* next for the head node */
    1401:   return(0);
    1402: }

    1404: /*
    1405:   Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
    1406:   Input Parameters:
    1407:     nidx      - number of input indices
    1408:     indices   - sorted integer array
    1409:     lnk       - condensed linked list(an integer array) that is created
    1410:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
    1411:   output Parameters:
    1412:     lnk       - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
    1413:     bt        - updated PetscBT (bitarray)
    1414: */
    1415: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx,const PetscInt indices[],PetscInt lnk[],PetscBT bt)
    1416: {
    1417:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;

    1420:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
    1421:   _location = 2; /* head */
    1422:     for (_k=0; _k<nidx; _k++){
    1423:       _entry = indices[_k];
    1424:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */
    1425:         /* search for insertion location */
    1426:         do {
    1427:           _next     = _location + 1; /* link from previous node to next node */
    1428:           _location = lnk[_next];    /* idx of next node */
    1429:           _lnkdata  = lnk[_location];/* value of next node */
    1430:         } while (_entry > _lnkdata);
    1431:         /* insertion location is found, add entry into lnk */
    1432:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
    1433:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
    1434:         lnk[_newnode]   = _entry;        /* set value of the new node */
    1435:         lnk[_newnode+1] = _location;     /* connect new node to next node */
    1436:         _location       = _newnode;      /* next search starts from the new node */
    1437:         _nlnk++;
    1438:       }   \
    1439:     }\
    1440:   lnk[0]   = _nlnk;   /* number of entries in the list */
    1441:   return(0);
    1442: }

    1444: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max,PetscInt nidx,PetscInt *indices,PetscInt lnk[],PetscBT bt)
    1445: {
    1447:   PetscInt       _k,_next,_nlnk;

    1450:   _next = lnk[3];       /* head node */
    1451:   _nlnk = lnk[0];       /* num of entries on the list */
    1452:   for (_k=0; _k<_nlnk; _k++){
    1453:     indices[_k] = lnk[_next];
    1454:     _next       = lnk[_next + 1];
    1455:     PetscBTClear(bt,indices[_k]);
    1456:   }
    1457:   lnk[0] = 0;          /* num of entries on the list */
    1458:   lnk[2] = lnk_max;    /* initialize head node */
    1459:   lnk[3] = 2;          /* head node */
    1460:   return(0);
    1461: }

    1463: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
    1464: {
    1466:   PetscInt       k;

    1469:   PetscPrintf(PETSC_COMM_SELF,"LLCondensed of size %D, (val,  next)\n",lnk[0]);
    1470:   for (k=2; k< lnk[0]+2; k++){
    1471:     PetscPrintf(PETSC_COMM_SELF," %D: (%D, %D)\n",2*k,lnk[2*k],lnk[2*k+1]);
    1472:   }
    1473:   return(0);
    1474: }

    1476: /*
    1477:   Free memories used by the list
    1478: */
    1479: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk,PetscBT bt)
    1480: {

    1484:   PetscFree(lnk);
    1485:   PetscBTDestroy(&bt);
    1486:   return(0);
    1487: }

    1489: /* -------------------------------------------------------------------------------------------------------*/
    1490: /*
    1491:  Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
    1492:   Input Parameters:
    1493:     nlnk_max  - max length of the list
    1494:   Output Parameters:
    1495:     lnk       - list created and initialized
    1496: */
    1497: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max,PetscInt **lnk)
    1498: {
    1500:   PetscInt       *llnk,lsize = 0;

    1503:   PetscIntMultError(2,nlnk_max+2,&lsize);
    1504:   PetscMalloc1(lsize,lnk);
    1505:   llnk = *lnk;
    1506:   llnk[0] = 0;               /* number of entries on the list */
    1507:   llnk[2] = PETSC_MAX_INT;   /* value in the head node */
    1508:   llnk[3] = 2;               /* next for the head node */
    1509:   return(0);
    1510: }

    1512: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max,PetscInt **lnk)
    1513: {
    1515:   PetscInt       lsize = 0;

    1518:   PetscIntMultError(2,nlnk_max+2,&lsize);
    1519:   PetscRealloc(lsize*sizeof(PetscInt),lnk);
    1520:   return(0);
    1521: }

    1523: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
    1524: {
    1525:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
    1526:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
    1527:   _location = 2; /* head */ \
    1528:     for (_k=0; _k<nidx; _k++){
    1529:       _entry = indices[_k];
    1530:       /* search for insertion location */
    1531:       do {
    1532:         _next     = _location + 1; /* link from previous node to next node */
    1533:         _location = lnk[_next];    /* idx of next node */
    1534:         _lnkdata  = lnk[_location];/* value of next node */
    1535:       } while (_entry > _lnkdata);
    1536:       if (_entry < _lnkdata) {
    1537:         /* insertion location is found, add entry into lnk */
    1538:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
    1539:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
    1540:         lnk[_newnode]   = _entry;        /* set value of the new node */
    1541:         lnk[_newnode+1] = _location;     /* connect new node to next node */
    1542:         _location       = _newnode;      /* next search starts from the new node */
    1543:         _nlnk++;
    1544:       }
    1545:     }
    1546:   lnk[0]   = _nlnk;   /* number of entries in the list */
    1547:   return 0;
    1548: }

    1550: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_Scalable(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
    1551: {
    1552:   PetscInt _k,_next,_nlnk;
    1553:   _next = lnk[3];       /* head node */
    1554:   _nlnk = lnk[0];
    1555:   for (_k=0; _k<_nlnk; _k++){
    1556:     indices[_k] = lnk[_next];
    1557:     _next       = lnk[_next + 1];
    1558:   }
    1559:   lnk[0] = 0;          /* num of entries on the list */
    1560:   lnk[3] = 2;          /* head node */
    1561:   return 0;
    1562: }

    1564: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
    1565: {
    1566:   return PetscFree(lnk);
    1567: }

    1569: /* -------------------------------------------------------------------------------------------------------*/
    1570: /*
    1571:       lnk[0]   number of links
    1572:       lnk[1]   number of entries
    1573:       lnk[3n]  value
    1574:       lnk[3n+1] len
    1575:       lnk[3n+2] link to next value

    1577:       The next three are always the first link

    1579:       lnk[3]    PETSC_MIN_INT+1
    1580:       lnk[4]    1
    1581:       lnk[5]    link to first real entry

    1583:       The next three are always the last link

    1585:       lnk[6]    PETSC_MAX_INT - 1
    1586:       lnk[7]    1
    1587:       lnk[8]    next valid link (this is the same as lnk[0] but without the decreases)
    1588: */

    1590: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max,PetscInt **lnk)
    1591: {
    1593:   PetscInt       *llnk,lsize = 0;

    1596:   PetscIntMultError(3,nlnk_max+3,&lsize);
    1597:   PetscMalloc1(lsize,lnk);
    1598:   llnk = *lnk;
    1599:   llnk[0] = 0;   /* nlnk: number of entries on the list */
    1600:   llnk[1] = 0;          /* number of integer entries represented in list */
    1601:   llnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
    1602:   llnk[4] = 1;           /* count for the first node */
    1603:   llnk[5] = 6;         /* next for the first node */
    1604:   llnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
    1605:   llnk[7] = 1;           /* count for the last node */
    1606:   llnk[8] = 0;         /* next valid node to be used */
    1607:   return(0);
    1608: }

    1610: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
    1611: {
    1612:   PetscInt k,entry,prev,next;
    1613:   prev      = 3;      /* first value */
    1614:   next      = lnk[prev+2];
    1615:   for (k=0; k<nidx; k++){
    1616:     entry = indices[k];
    1617:     /* search for insertion location */
    1618:     while (entry >= lnk[next]) {
    1619:       prev = next;
    1620:       next = lnk[next+2];
    1621:     }
    1622:     /* entry is in range of previous list */
    1623:     if (entry < lnk[prev]+lnk[prev+1]) continue;
    1624:     lnk[1]++;
    1625:     /* entry is right after previous list */
    1626:     if (entry == lnk[prev]+lnk[prev+1]) {
    1627:       lnk[prev+1]++;
    1628:       if (lnk[next] == entry+1) { /* combine two contiguous strings */
    1629:         lnk[prev+1] += lnk[next+1];
    1630:         lnk[prev+2]  = lnk[next+2];
    1631:         next         = lnk[next+2];
    1632:         lnk[0]--;
    1633:       }
    1634:       continue;
    1635:     }
    1636:     /* entry is right before next list */
    1637:     if (entry == lnk[next]-1) {
    1638:       lnk[next]--;
    1639:       lnk[next+1]++;
    1640:       prev = next;
    1641:       next = lnk[prev+2];
    1642:       continue;
    1643:     }
    1644:     /*  add entry into lnk */
    1645:     lnk[prev+2]    = 3*((lnk[8]++)+3);      /* connect previous node to the new node */
    1646:     prev           = lnk[prev+2];
    1647:     lnk[prev]      = entry;        /* set value of the new node */
    1648:     lnk[prev+1]    = 1;             /* number of values in contiguous string is one to start */
    1649:     lnk[prev+2]    = next;          /* connect new node to next node */
    1650:     lnk[0]++;
    1651:   }
    1652:   return 0;
    1653: }

    1655: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_fast(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
    1656: {
    1657:   PetscInt _k,_next,_nlnk,cnt,j;
    1658:   _next = lnk[5];       /* first node */
    1659:   _nlnk = lnk[0];
    1660:   cnt   = 0;
    1661:   for (_k=0; _k<_nlnk; _k++){
    1662:     for (j=0; j<lnk[_next+1]; j++) {
    1663:       indices[cnt++] = lnk[_next] + j;
    1664:     }
    1665:     _next       = lnk[_next + 2];
    1666:   }
    1667:   lnk[0] = 0;   /* nlnk: number of links */
    1668:   lnk[1] = 0;          /* number of integer entries represented in list */
    1669:   lnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
    1670:   lnk[4] = 1;           /* count for the first node */
    1671:   lnk[5] = 6;         /* next for the first node */
    1672:   lnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
    1673:   lnk[7] = 1;           /* count for the last node */
    1674:   lnk[8] = 0;         /* next valid location to make link */
    1675:   return 0;
    1676: }

    1678: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView_fast(PetscInt *lnk)
    1679: {
    1680:   PetscInt k,next,nlnk;
    1681:   next = lnk[5];       /* first node */
    1682:   nlnk = lnk[0];
    1683:   for (k=0; k<nlnk; k++){
    1684: #if 0                           /* Debugging code */
    1685:     printf("%d value %d len %d next %d\n",next,lnk[next],lnk[next+1],lnk[next+2]);
    1686: #endif
    1687:     next = lnk[next + 2];
    1688:   }
    1689:   return 0;
    1690: }

    1692: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
    1693: {
    1694:   return PetscFree(lnk);
    1695: }

    1697: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
    1698: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,void*);

    1700: PETSC_EXTERN PetscLogEvent MAT_Mult;
    1701: PETSC_EXTERN PetscLogEvent MAT_MultMatrixFree;
    1702: PETSC_EXTERN PetscLogEvent MAT_Mults;
    1703: PETSC_EXTERN PetscLogEvent MAT_MultConstrained;
    1704: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
    1705: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
    1706: PETSC_EXTERN PetscLogEvent MAT_MultTransposeConstrained;
    1707: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
    1708: PETSC_EXTERN PetscLogEvent MAT_Solve;
    1709: PETSC_EXTERN PetscLogEvent MAT_Solves;
    1710: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
    1711: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
    1712: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
    1713: PETSC_EXTERN PetscLogEvent MAT_SOR;
    1714: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
    1715: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
    1716: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
    1717: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
    1718: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
    1719: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
    1720: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
    1721: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
    1722: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
    1723: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
    1724: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
    1725: PETSC_EXTERN PetscLogEvent MAT_Copy;
    1726: PETSC_EXTERN PetscLogEvent MAT_Convert;
    1727: PETSC_EXTERN PetscLogEvent MAT_Scale;
    1728: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
    1729: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
    1730: PETSC_EXTERN PetscLogEvent MAT_SetValues;
    1731: PETSC_EXTERN PetscLogEvent MAT_GetValues;
    1732: PETSC_EXTERN PetscLogEvent MAT_GetRow;
    1733: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
    1734: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
    1735: PETSC_EXTERN PetscLogEvent MAT_GetColoring;
    1736: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
    1737: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
    1738: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
    1739: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
    1740: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
    1741: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
    1742: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
    1743: PETSC_EXTERN PetscLogEvent MAT_Load;
    1744: PETSC_EXTERN PetscLogEvent MAT_View;
    1745: PETSC_EXTERN PetscLogEvent MAT_AXPY;
    1746: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
    1747: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
    1748: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
    1749: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
    1750: PETSC_EXTERN PetscLogEvent MAT_Transpose;
    1751: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
    1752: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
    1753: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
    1754: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
    1755: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
    1756: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
    1757: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
    1758: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
    1759: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
    1760: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
    1761: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
    1762: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
    1763: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
    1764: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
    1765: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
    1766: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
    1767: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
    1768: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
    1769: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
    1770: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
    1771: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
    1772: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
    1773: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
    1774: PETSC_EXTERN PetscLogEvent MAT_Applypapt;
    1775: PETSC_EXTERN PetscLogEvent MAT_Applypapt_symbolic;
    1776: PETSC_EXTERN PetscLogEvent MAT_Applypapt_numeric;
    1777: PETSC_EXTERN PetscLogEvent MAT_Getsymtranspose;
    1778: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
    1779: PETSC_EXTERN PetscLogEvent MAT_GetSequentialNonzeroStructure;
    1780: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
    1781: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
    1782: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
    1783: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
    1784: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
    1785: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
    1786: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
    1787: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
    1788: PETSC_EXTERN PetscLogEvent MAT_Merge;
    1789: PETSC_EXTERN PetscLogEvent MAT_Residual;
    1790: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
    1791: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
    1792: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
    1793: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
    1794: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
    1795: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
    1796: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
    1797: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
    1798: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;

    1800: #endif