Actual source code: matimpl.h

petsc-3.10.4 2019-02-26
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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 include/petsc/finclude/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 (*placeholder_33)(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 (*matmatmult)(Mat,Mat,Mat,MatReuse,PetscReal,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 (*matmult)(Mat,Mat,MatReuse,PetscReal,Mat*);
142:   PetscErrorCode (*matmultsymbolic)(Mat,Mat,PetscReal,Mat*);
143:   PetscErrorCode (*matmultnumeric)(Mat,Mat,Mat);
144:   PetscErrorCode (*ptap)(Mat,Mat,MatReuse,PetscReal,Mat*);
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 (*mattransposemult)(Mat,Mat,MatReuse,PetscReal,Mat*);
149:   PetscErrorCode (*mattransposemultsymbolic)(Mat,Mat,PetscReal,Mat*);
150:   PetscErrorCode (*mattransposemultnumeric)(Mat,Mat,Mat);
151:   PetscErrorCode (*placeholder_98)(Mat);
152:   /*99*/
153:   PetscErrorCode (*placeholder_99)(Mat);
154:   PetscErrorCode (*placeholder_100)(Mat);
155:   PetscErrorCode (*placeholder_101)(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 (*transposematmult)(Mat,Mat,MatReuse,PetscReal,Mat*);
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 (*rart)(Mat,Mat,MatReuse,PetscReal,Mat*);
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:   /*144*/
207:   PetscErrorCode (*creatempimatconcatenateseqmat)(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
208:   PetscErrorCode (*destroysubmatrices)(PetscInt,Mat*[]);
209:   PetscErrorCode (*mattransposesolve)(Mat,Mat,Mat);
210: };
211: /*
212:     If you add MatOps entries above also add them to the MATOP enum
213:     in include/petscmat.h and include/petsc/finclude/petscmat.h
214: */

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

220: typedef struct _p_MatBaseName* MatBaseName;
221: struct _p_MatBaseName {
222:   char        *bname,*sname,*mname;
223:   MatBaseName next;
224: };

226: PETSC_EXTERN MatBaseName MatBaseNameList;

228: /*
229:    Utility private matrix routines
230: */
231: PETSC_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat,PetscBool,PetscReal,IS*);
232: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat,MatType,MatReuse,Mat*);
233: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat, MatType,MatReuse,Mat*);
234: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat,Mat,MatStructure);
235: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat,Vec,InsertMode);

237: #if defined(PETSC_USE_DEBUG)
238: #  define MatCheckPreallocated(A,arg) do {                              \
239:     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); \
240:   } while (0)
241: #else
242: #  define MatCheckPreallocated(A,arg) do {} while (0)
243: #endif

245: /*
246:   The stash is used to temporarily store inserted matrix values that
247:   belong to another processor. During the assembly phase the stashed
248:   values are moved to the correct processor and
249: */

251: typedef struct _MatStashSpace *PetscMatStashSpace;

253: struct _MatStashSpace {
254:   PetscMatStashSpace next;
255:   PetscScalar        *space_head,*val;
256:   PetscInt           *idx,*idy;
257:   PetscInt           total_space_size;
258:   PetscInt           local_used;
259:   PetscInt           local_remaining;
260: };

262: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt,PetscInt,PetscMatStashSpace *);
263: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt,PetscMatStashSpace *,PetscScalar *,PetscInt *,PetscInt *);
264: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace*);

266: typedef struct {
267:   PetscInt    count;
268: } MatStashHeader;

270: typedef struct {
271:   void        *buffer;          /* Of type blocktype, dynamically constructed  */
272:   PetscInt    count;
273:   char        pending;
274: } MatStashFrame;

276: typedef struct _MatStash MatStash;
277: struct _MatStash {
278:   PetscInt      nmax;                   /* maximum stash size */
279:   PetscInt      umax;                   /* user specified max-size */
280:   PetscInt      oldnmax;                /* the nmax value used previously */
281:   PetscInt      n;                      /* stash size */
282:   PetscInt      bs;                     /* block size of the stash */
283:   PetscInt      reallocs;               /* preserve the no of mallocs invoked */
284:   PetscMatStashSpace space_head,space;  /* linked list to hold stashed global row/column numbers and matrix values */

286:   PetscErrorCode (*ScatterBegin)(Mat,MatStash*,PetscInt*);
287:   PetscErrorCode (*ScatterGetMesg)(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
288:   PetscErrorCode (*ScatterEnd)(MatStash*);
289:   PetscErrorCode (*ScatterDestroy)(MatStash*);

291:   /* The following variables are used for communication */
292:   MPI_Comm      comm;
293:   PetscMPIInt   size,rank;
294:   PetscMPIInt   tag1,tag2;
295:   MPI_Request   *send_waits;            /* array of send requests */
296:   MPI_Request   *recv_waits;            /* array of receive requests */
297:   MPI_Status    *send_status;           /* array of send status */
298:   PetscInt      nsends,nrecvs;          /* numbers of sends and receives */
299:   PetscScalar   *svalues;               /* sending data */
300:   PetscInt      *sindices;
301:   PetscScalar   **rvalues;              /* receiving data (values) */
302:   PetscInt      **rindices;             /* receiving data (indices) */
303:   PetscInt      nprocessed;             /* number of messages already processed */
304:   PetscMPIInt   *flg_v;                 /* indicates what messages have arrived so far and from whom */
305:   PetscBool     reproduce;
306:   PetscInt      reproduce_count;

308:   /* The following variables are used for BTS communication */
309:   PetscBool      subset_off_proc; /* Subsequent assemblies will set a subset (perhaps equal) of off-process entries set on first assembly */
310:   PetscBool      use_status;      /* Use MPI_Status to determine number of items in each message */
311:   PetscMPIInt    nsendranks;
312:   PetscMPIInt    nrecvranks;
313:   PetscMPIInt    *sendranks;
314:   PetscMPIInt    *recvranks;
315:   MatStashHeader *sendhdr,*recvhdr;
316:   MatStashFrame  *sendframes;   /* pointers to the main messages */
317:   MatStashFrame  *recvframes;
318:   MatStashFrame  *recvframe_active;
319:   PetscInt       recvframe_i;     /* index of block within active frame */
320:   PetscMPIInt    recvframe_count; /* Count actually sent for current frame */
321:   PetscInt       recvcount;       /* Number of receives processed so far */
322:   PetscMPIInt    *some_indices;   /* From last call to MPI_Waitsome */
323:   MPI_Status     *some_statuses;  /* Statuses from last call to MPI_Waitsome */
324:   PetscMPIInt    some_count;      /* Number of requests completed in last call to MPI_Waitsome */
325:   PetscMPIInt    some_i;          /* Index of request currently being processed */
326:   MPI_Request    *sendreqs;
327:   MPI_Request    *recvreqs;
328:   PetscSegBuffer segsendblocks;
329:   PetscSegBuffer segrecvframe;
330:   PetscSegBuffer segrecvblocks;
331:   MPI_Datatype   blocktype;
332:   size_t         blocktype_size;
333:   InsertMode     *insertmode;   /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
334: };

336: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm,PetscInt,MatStash*);
337: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash*);
338: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash*);
339: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash*,PetscInt);
340: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash*,PetscInt*,PetscInt*);
341: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscBool );
342: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscBool );
343: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
344: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
345: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat,MatStash*,PetscInt*);
346: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
347: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat,MatInfoType,MatInfo*);

349: typedef struct {
350:   PetscInt   dim;
351:   PetscInt   dims[4];
352:   PetscInt   starts[4];
353:   PetscBool  noc;        /* this is a single component problem, hence user will not set MatStencil.c */
354: } MatStencilInfo;

356: /* Info about using compressed row format */
357: typedef struct {
358:   PetscBool  use;                           /* indicates compressed rows have been checked and will be used */
359:   PetscInt   nrows;                         /* number of non-zero rows */
360:   PetscInt   *i;                            /* compressed row pointer  */
361:   PetscInt   *rindex;                       /* compressed row index               */
362: } Mat_CompressedRow;
363: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat,PetscInt,Mat_CompressedRow*,PetscInt*,PetscInt,PetscReal);

365: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
366:   PetscInt     nzlocal,nsends,nrecvs;
367:   PetscMPIInt  *send_rank,*recv_rank;
368:   PetscInt     *sbuf_nz,*rbuf_nz,*sbuf_j,**rbuf_j;
369:   PetscScalar  *sbuf_a,**rbuf_a;
370:   MPI_Comm     subcomm;   /* when user does not provide a subcomm */
371:   IS           isrow,iscol;
372:   Mat          *matseq;
373: } Mat_Redundant;

375: struct _p_Mat {
376:   PETSCHEADER(struct _MatOps);
377:   PetscLayout            rmap,cmap;
378:   void                   *data;            /* implementation-specific data */
379:   MatFactorType          factortype;       /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
380:   PetscBool              assembled;        /* is the matrix assembled? */
381:   PetscBool              was_assembled;    /* new values inserted into assembled mat */
382:   PetscInt               num_ass;          /* number of times matrix has been assembled */
383:   PetscObjectState       nonzerostate;     /* each time new nonzeros locations are introduced into the matrix this is updated */
384:   MatInfo                info;             /* matrix information */
385:   InsertMode             insertmode;       /* have values been inserted in matrix or added? */
386:   MatStash               stash,bstash;     /* used for assembling off-proc mat emements */
387:   MatNullSpace           nullsp;           /* null space (operator is singular) */
388:   MatNullSpace           transnullsp;      /* null space of transpose of operator */
389:   MatNullSpace           nearnullsp;       /* near null space to be used by multigrid methods */
390:   PetscInt               congruentlayouts; /* are the rows and columns layouts congruent? */
391:   PetscBool              preallocated;
392:   MatStencilInfo         stencil;          /* information for structured grid */
393:   PetscBool              symmetric,hermitian,structurally_symmetric,spd;
394:   PetscBool              symmetric_set,hermitian_set,structurally_symmetric_set,spd_set; /* if true, then corresponding flag is correct*/
395:   PetscBool              symmetric_eternal;
396:   PetscBool              nooffprocentries,nooffproczerorows;
397:   PetscBool              subsetoffprocentries;
398:   PetscBool              submat_singleis; /* for efficient PCSetUP_ASM() */
399:   PetscBool              structure_only;
400: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_VECCUDA)
401:   PetscOffloadFlag       valid_GPU_matrix; /* flag pointing to the matrix on the gpu*/
402: #endif
403:   void                   *spptr;          /* pointer for special library like SuperLU */
404:   char                   *solvertype;
405:   PetscBool              checksymmetryonassembly,checknullspaceonassembly;
406:   PetscReal              checksymmetrytol;
407:   Mat                    schur;             /* Schur complement matrix */
408:   MatFactorSchurStatus   schur_status;      /* status of the Schur complement matrix */
409:   Mat_Redundant          *redundant;        /* used by MatCreateRedundantMatrix() */
410:   PetscBool              erroriffailure;    /* Generate an error if detected (for example a zero pivot) instead of returning */
411:   MatFactorError         factorerrortype;               /* type of error in factorization */
412:   PetscReal              factorerror_zeropivot_value;   /* If numerical zero pivot was detected this is the computed value */
413:   PetscInt               factorerror_zeropivot_row;     /* Row where zero pivot was detected */
414:   PetscInt               nblocks,*bsizes;   /* support for MatSetVariableBlockSizes() */
415:   char                   *defaultvectype;
416: };

418: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat,PetscScalar,Mat,MatStructure);
419: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat,Mat,PetscScalar,Mat,MatStructure);

421: /*
422:     Utility for MatFactor (Schur complement)
423: */
424: PETSC_INTERN PetscErrorCode MatFactorFactorizeSchurComplement_Private(Mat);
425: PETSC_INTERN PetscErrorCode MatFactorInvertSchurComplement_Private(Mat);
426: PETSC_INTERN PetscErrorCode MatFactorUpdateSchurStatus_Private(Mat);
427: PETSC_INTERN PetscErrorCode MatFactorSetUpInPlaceSchur_Private(Mat);

429: /*
430:     Utility for MatZeroRows
431: */
432: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat,PetscInt,const PetscInt*,PetscInt*,PetscInt**);

434: /*
435:     Object for partitioning graphs
436: */

438: typedef struct _MatPartitioningOps *MatPartitioningOps;
439: struct _MatPartitioningOps {
440:   PetscErrorCode (*apply)(MatPartitioning,IS*);
441:   PetscErrorCode (*applynd)(MatPartitioning,IS*);
442:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatPartitioning);
443:   PetscErrorCode (*destroy)(MatPartitioning);
444:   PetscErrorCode (*view)(MatPartitioning,PetscViewer);
445: };

447: struct _p_MatPartitioning {
448:   PETSCHEADER(struct _MatPartitioningOps);
449:   Mat         adj;
450:   PetscInt    *vertex_weights;
451:   PetscReal   *part_weights;
452:   PetscInt    n;                                 /* number of partitions */
453:   void        *data;
454:   PetscInt    setupcalled;
455: };

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

460: /*
461:     Object for coarsen graphs
462: */
463: typedef struct _MatCoarsenOps *MatCoarsenOps;
464: struct _MatCoarsenOps {
465:   PetscErrorCode (*apply)(MatCoarsen);
466:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatCoarsen);
467:   PetscErrorCode (*destroy)(MatCoarsen);
468:   PetscErrorCode (*view)(MatCoarsen,PetscViewer);
469: };

471: struct _p_MatCoarsen {
472:   PETSCHEADER(struct _MatCoarsenOps);
473:   Mat              graph;
474:   PetscInt         setupcalled;
475:   void             *subctx;
476:   /* */
477:   PetscBool        strict_aggs;
478:   IS               perm;
479:   PetscCoarsenData *agg_lists;
480: };

482: /*
483:     MatFDColoring is used to compute Jacobian matrices efficiently
484:   via coloring. The data structure is explained below in an example.

486:    Color =   0    1     0    2   |   2      3       0
487:    ---------------------------------------------------
488:             00   01              |          05
489:             10   11              |   14     15               Processor  0
490:                        22    23  |          25
491:                        32    33  |
492:    ===================================================
493:                                  |   44     45     46
494:             50                   |          55               Processor 1
495:                                  |   64            66
496:    ---------------------------------------------------

498:     ncolors = 4;

500:     ncolumns      = {2,1,1,0}
501:     columns       = {{0,2},{1},{3},{}}
502:     nrows         = {4,2,3,3}
503:     rows          = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
504:     vwscale       = {dx(0),dx(1),dx(2),dx(3)}               MPI Vec
505:     vscale        = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)}   Seq Vec

507:     ncolumns      = {1,0,1,1}
508:     columns       = {{6},{},{4},{5}}
509:     nrows         = {3,0,2,2}
510:     rows          = {{0,1,2},{},{1,2},{1,2}}
511:     vwscale       = {dx(4),dx(5),dx(6)}              MPI Vec
512:     vscale        = {dx(0),dx(4),dx(5),dx(6)}        Seq Vec

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

517: */
518: typedef struct {
519:   PetscInt     row;
520:   PetscInt     col;
521:   PetscScalar  *valaddr;   /* address of value */
522: } MatEntry;

524: typedef struct {
525:   PetscInt     row;
526:   PetscScalar  *valaddr;   /* address of value */
527: } MatEntry2;

529: struct  _p_MatFDColoring{
530:   PETSCHEADER(int);
531:   PetscInt       M,N,m;            /* total rows, columns; local rows */
532:   PetscInt       rstart;           /* first row owned by local processor */
533:   PetscInt       ncolors;          /* number of colors */
534:   PetscInt       *ncolumns;        /* number of local columns for a color */
535:   PetscInt       **columns;        /* lists the local columns of each color (using global column numbering) */
536:   PetscInt       *nrows;           /* number of local rows for each color */
537:   MatEntry       *matentry;        /* holds (row, column, address of value) for Jacobian matrix entry */
538:   MatEntry2      *matentry2;       /* holds (row, address of value) for Jacobian matrix entry */
539:   PetscScalar    *dy;              /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
540:   PetscReal      error_rel;        /* square root of relative error in computing function */
541:   PetscReal      umin;             /* minimum allowable u'dx value */
542:   Vec            w1,w2,w3;         /* work vectors used in computing Jacobian */
543:   PetscBool      fset;             /* indicates that the initial function value F(X) is set */
544:   PetscErrorCode (*f)(void);       /* function that defines Jacobian */
545:   void           *fctx;            /* optional user-defined context for use by the function f */
546:   Vec            vscale;           /* holds FD scaling, i.e. 1/dx for each perturbed column */
547:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
548:   const char     *htype;           /* "wp" or "ds" */
549:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
550:   PetscInt       brows,bcols;      /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
551:   PetscBool      setupcalled;      /* true if setup has been called */
552:   PetscBool      viewed;           /* true if the -mat_fd_coloring_view has been triggered already */
553:   void           (*ftn_func_pointer)(void),*ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
554: };

556: typedef struct _MatColoringOps *MatColoringOps;
557: struct _MatColoringOps {
558:   PetscErrorCode (*destroy)(MatColoring);
559:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatColoring);
560:   PetscErrorCode (*view)(MatColoring,PetscViewer);
561:   PetscErrorCode (*apply)(MatColoring,ISColoring*);
562:   PetscErrorCode (*weights)(MatColoring,PetscReal**,PetscInt**);
563: };

565: struct _p_MatColoring {
566:   PETSCHEADER(struct _MatColoringOps);
567:   Mat                   mat;
568:   PetscInt              dist;             /* distance of the coloring */
569:   PetscInt              maxcolors;        /* the maximum number of colors returned, maxcolors=1 for MIS */
570:   void                  *data;            /* inner context */
571:   PetscBool             valid;            /* check to see if what is produced is a valid coloring */
572:   MatColoringWeightType weight_type;      /* type of weight computation to be performed */
573:   PetscReal             *user_weights;    /* custom weights and permutation */
574:   PetscInt              *user_lperm;
575:   PetscBool             valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
576: };

578: struct  _p_MatTransposeColoring{
579:   PETSCHEADER(int);
580:   PetscInt       M,N,m;            /* total rows, columns; local rows */
581:   PetscInt       rstart;           /* first row owned by local processor */
582:   PetscInt       ncolors;          /* number of colors */
583:   PetscInt       *ncolumns;        /* number of local columns for a color */
584:   PetscInt       *nrows;           /* number of local rows for each color */
585:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
586:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */

588:   PetscInt       *colorforrow,*colorforcol;  /* pointer to rows and columns */
589:   PetscInt       *rows;                      /* lists the local rows for each color (using the local row numbering) */
590:   PetscInt       *den2sp;                    /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
591:   PetscInt       *columns;                   /* lists the local columns of each color (using global column numbering) */
592:   PetscInt       brows;                      /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
593:   PetscInt       *lstart;                    /* array used for loop over row blocks of Csparse */
594: };

596: /*
597:    Null space context for preconditioner/operators
598: */
599: struct _p_MatNullSpace {
600:   PETSCHEADER(int);
601:   PetscBool      has_cnst;
602:   PetscInt       n;
603:   Vec*           vecs;
604:   PetscScalar*   alpha;                 /* for projections */
605:   PetscErrorCode (*remove)(MatNullSpace,Vec,void*);  /* for user provided removal function */
606:   void*          rmctx;                 /* context for remove() function */
607: };

609: /*
610:    Checking zero pivot for LU, ILU preconditioners.
611: */
612: typedef struct {
613:   PetscInt       nshift,nshift_max;
614:   PetscReal      shift_amount,shift_lo,shift_hi,shift_top,shift_fraction;
615:   PetscBool      newshift;
616:   PetscReal      rs;  /* active row sum of abs(offdiagonals) */
617:   PetscScalar    pv;  /* pivot of the active row */
618: } FactorShiftCtx;

620: /*
621:  Used by MatCreateSubMatrices_MPIXAIJ_Local()
622: */
623:  #include <petscctable.h>
624: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
625:   PetscInt   id;   /* index of submats, only submats[0] is responsible for deleting some arrays below */
626:   PetscInt   nrqs,nrqr;
627:   PetscInt   **rbuf1,**rbuf2,**rbuf3,**sbuf1,**sbuf2;
628:   PetscInt   **ptr;
629:   PetscInt   *tmp;
630:   PetscInt   *ctr;
631:   PetscInt   *pa; /* proc array */
632:   PetscInt   *req_size,*req_source1,*req_source2;
633:   PetscBool  allcolumns,allrows;
634:   PetscBool  singleis;
635:   PetscInt   *row2proc; /* row to proc map */
636:   PetscInt   nstages;
637: #if defined(PETSC_USE_CTABLE)
638:   PetscTable cmap,rmap;
639:   PetscInt   *cmap_loc,*rmap_loc;
640: #else
641:   PetscInt   *cmap,*rmap;
642: #endif

644:   PetscErrorCode (*destroy)(Mat);
645: } Mat_SubSppt;

647: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
648: PETSC_INTERN PetscErrorCode MatShift_Basic(Mat,PetscScalar);
649: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat,PetscInt,PetscInt);

651: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_nz(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
652: {
653:   PetscReal _rs   = sctx->rs;
654:   PetscReal _zero = info->zeropivot*_rs;

657:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
658:     /* force |diag| > zeropivot*rs */
659:     if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
660:     else sctx->shift_amount *= 2.0;
661:     sctx->newshift = PETSC_TRUE;
662:     (sctx->nshift)++;
663:   } else {
664:     sctx->newshift = PETSC_FALSE;
665:   }
666:   return(0);
667: }

669: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_pd(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
670: {
671:   PetscReal _rs   = sctx->rs;
672:   PetscReal _zero = info->zeropivot*_rs;

675:   if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
676:     /* force matfactor to be diagonally dominant */
677:     if (sctx->nshift == sctx->nshift_max) {
678:       sctx->shift_fraction = sctx->shift_hi;
679:     } else {
680:       sctx->shift_lo = sctx->shift_fraction;
681:       sctx->shift_fraction = (sctx->shift_hi+sctx->shift_lo)/2.;
682:     }
683:     sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
684:     sctx->nshift++;
685:     sctx->newshift = PETSC_TRUE;
686:   } else {
687:     sctx->newshift = PETSC_FALSE;
688:   }
689:   return(0);
690: }

692: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_inblocks(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
693: {
694:   PetscReal _zero = info->zeropivot;

697:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
698:     sctx->pv          += info->shiftamount;
699:     sctx->shift_amount = 0.0;
700:     sctx->nshift++;
701:   }
702:   sctx->newshift = PETSC_FALSE;
703:   return(0);
704: }

706: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_none(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
707: {
708:   PetscReal      _zero = info->zeropivot;

712:   sctx->newshift = PETSC_FALSE;
713:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
714:     if (!mat->erroriffailure) {
715:       PetscInfo3(mat,"Detected zero pivot in factorization in row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
716:       fact->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
717:       fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
718:       fact->factorerror_zeropivot_row   = row;
719:     } 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);
720:   }
721:   return(0);
722: }

724: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
725: {

729:   if (info->shifttype == (PetscReal) MAT_SHIFT_NONZERO){
730:     MatPivotCheck_nz(mat,info,sctx,row);
731:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_POSITIVE_DEFINITE){
732:     MatPivotCheck_pd(mat,info,sctx,row);
733:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_INBLOCKS){
734:     MatPivotCheck_inblocks(mat,info,sctx,row);
735:   } else {
736:     MatPivotCheck_none(fact,mat,info,sctx,row);
737:   }
738:   return(0);
739: }

741: /*
742:   Create and initialize a linked list
743:   Input Parameters:
744:     idx_start - starting index of the list
745:     lnk_max   - max value of lnk indicating the end of the list
746:     nlnk      - max length of the list
747:   Output Parameters:
748:     lnk       - list initialized
749:     bt        - PetscBT (bitarray) with all bits set to false
750:     lnk_empty - flg indicating the list is empty
751: */
752: #define PetscLLCreate(idx_start,lnk_max,nlnk,lnk,bt) \
753:   (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,0))

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

758: /*
759:   Add an index set into a sorted linked list
760:   Input Parameters:
761:     nidx      - number of input indices
762:     indices   - integer array
763:     idx_start - starting index of the list
764:     lnk       - linked list(an integer array) that is created
765:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
766:   output Parameters:
767:     nlnk      - number of newly added indices
768:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
769:     bt        - updated PetscBT (bitarray)
770: */
771: #define PetscLLAdd(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
772: {\
773:   PetscInt _k,_entry,_location,_lnkdata;\
774:   nlnk     = 0;\
775:   _lnkdata = idx_start;\
776:   for (_k=0; _k<nidx; _k++){\
777:     _entry = indices[_k];\
778:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
779:       /* search for insertion location */\
780:       /* start from the beginning if _entry < previous _entry */\
781:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
782:       do {\
783:         _location = _lnkdata;\
784:         _lnkdata  = lnk[_location];\
785:       } while (_entry > _lnkdata);\
786:       /* insertion location is found, add entry into lnk */\
787:       lnk[_location] = _entry;\
788:       lnk[_entry]    = _lnkdata;\
789:       nlnk++;\
790:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
791:     }\
792:   }\
793: }

795: /*
796:   Add a permuted index set into a sorted linked list
797:   Input Parameters:
798:     nidx      - number of input indices
799:     indices   - integer array
800:     perm      - permutation of indices
801:     idx_start - starting index of the list
802:     lnk       - linked list(an integer array) that is created
803:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
804:   output Parameters:
805:     nlnk      - number of newly added indices
806:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
807:     bt        - updated PetscBT (bitarray)
808: */
809: #define PetscLLAddPerm(nidx,indices,perm,idx_start,nlnk,lnk,bt) 0;\
810: {\
811:   PetscInt _k,_entry,_location,_lnkdata;\
812:   nlnk     = 0;\
813:   _lnkdata = idx_start;\
814:   for (_k=0; _k<nidx; _k++){\
815:     _entry = perm[indices[_k]];\
816:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
817:       /* search for insertion location */\
818:       /* start from the beginning if _entry < previous _entry */\
819:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
820:       do {\
821:         _location = _lnkdata;\
822:         _lnkdata  = lnk[_location];\
823:       } while (_entry > _lnkdata);\
824:       /* insertion location is found, add entry into lnk */\
825:       lnk[_location] = _entry;\
826:       lnk[_entry]    = _lnkdata;\
827:       nlnk++;\
828:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
829:     }\
830:   }\
831: }

833: /*
834:   Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata  = idx_start;'
835:   Input Parameters:
836:     nidx      - number of input indices
837:     indices   - sorted integer array
838:     idx_start - starting index of the list
839:     lnk       - linked list(an integer array) that is created
840:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
841:   output Parameters:
842:     nlnk      - number of newly added indices
843:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
844:     bt        - updated PetscBT (bitarray)
845: */
846: #define PetscLLAddSorted(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
847: {\
848:   PetscInt _k,_entry,_location,_lnkdata;\
849:   nlnk      = 0;\
850:   _lnkdata  = idx_start;\
851:   for (_k=0; _k<nidx; _k++){\
852:     _entry = indices[_k];\
853:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
854:       /* search for insertion location */\
855:       do {\
856:         _location = _lnkdata;\
857:         _lnkdata  = lnk[_location];\
858:       } while (_entry > _lnkdata);\
859:       /* insertion location is found, add entry into lnk */\
860:       lnk[_location] = _entry;\
861:       lnk[_entry]    = _lnkdata;\
862:       nlnk++;\
863:       _lnkdata = _entry; /* next search starts from here */\
864:     }\
865:   }\
866: }

868: #define PetscLLAddSorted_new(nidx,indices,idx_start,lnk_empty,nlnk,lnk,bt) 0; \
869: {\
870:   PetscInt _k,_entry,_location,_lnkdata;\
871:   if (lnk_empty){\
872:     _lnkdata  = idx_start;                      \
873:     for (_k=0; _k<nidx; _k++){                  \
874:       _entry = indices[_k];                             \
875:       PetscBTSet(bt,_entry);  /* mark the new entry */          \
876:           _location = _lnkdata;                                 \
877:           _lnkdata  = lnk[_location];                           \
878:         /* insertion location is found, add entry into lnk */   \
879:         lnk[_location] = _entry;                                \
880:         lnk[_entry]    = _lnkdata;                              \
881:         _lnkdata = _entry; /* next search starts from here */   \
882:     }                                                           \
883:     /*\
884:     lnk[indices[nidx-1]] = lnk[idx_start];\
885:     lnk[idx_start]       = indices[0];\
886:     PetscBTSet(bt,indices[0]);  \
887:     for (_k=1; _k<nidx; _k++){                  \
888:       PetscBTSet(bt,indices[_k]);                                          \
889:       lnk[indices[_k-1]] = indices[_k];                                  \
890:     }                                                           \
891:      */\
892:     nlnk      = nidx;\
893:     lnk_empty = PETSC_FALSE;\
894:   } else {\
895:     nlnk      = 0;                              \
896:     _lnkdata  = idx_start;                      \
897:     for (_k=0; _k<nidx; _k++){                  \
898:       _entry = indices[_k];                             \
899:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */       \
900:         /* search for insertion location */                     \
901:         do {                                                    \
902:           _location = _lnkdata;                                 \
903:           _lnkdata  = lnk[_location];                           \
904:         } while (_entry > _lnkdata);                            \
905:         /* insertion location is found, add entry into lnk */   \
906:         lnk[_location] = _entry;                                \
907:         lnk[_entry]    = _lnkdata;                              \
908:         nlnk++;                                                 \
909:         _lnkdata = _entry; /* next search starts from here */   \
910:       }                                                         \
911:     }                                                           \
912:   }                                                             \
913: }

915: /*
916:   Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
917:   Same as PetscLLAddSorted() with an additional operation:
918:        count the number of input indices that are no larger than 'diag'
919:   Input Parameters:
920:     indices   - sorted integer array
921:     idx_start - starting index of the list, index of pivot row
922:     lnk       - linked list(an integer array) that is created
923:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
924:     diag      - index of the active row in LUFactorSymbolic
925:     nzbd      - number of input indices with indices <= idx_start
926:     im        - im[idx_start] is initialized as num of nonzero entries in row=idx_start
927:   output Parameters:
928:     nlnk      - number of newly added indices
929:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
930:     bt        - updated PetscBT (bitarray)
931:     im        - im[idx_start]: unchanged if diag is not an entry
932:                              : num of entries with indices <= diag if diag is an entry
933: */
934: #define PetscLLAddSortedLU(indices,idx_start,nlnk,lnk,bt,diag,nzbd,im) 0;\
935: {\
936:   PetscInt _k,_entry,_location,_lnkdata,_nidx;\
937:   nlnk     = 0;\
938:   _lnkdata = idx_start;\
939:   _nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */\
940:   for (_k=0; _k<_nidx; _k++){\
941:     _entry = indices[_k];\
942:     nzbd++;\
943:     if ( _entry== diag) im[idx_start] = nzbd;\
944:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
945:       /* search for insertion location */\
946:       do {\
947:         _location = _lnkdata;\
948:         _lnkdata  = lnk[_location];\
949:       } while (_entry > _lnkdata);\
950:       /* insertion location is found, add entry into lnk */\
951:       lnk[_location] = _entry;\
952:       lnk[_entry]    = _lnkdata;\
953:       nlnk++;\
954:       _lnkdata = _entry; /* next search starts from here */\
955:     }\
956:   }\
957: }

959: /*
960:   Copy data on the list into an array, then initialize the list
961:   Input Parameters:
962:     idx_start - starting index of the list
963:     lnk_max   - max value of lnk indicating the end of the list
964:     nlnk      - number of data on the list to be copied
965:     lnk       - linked list
966:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
967:   output Parameters:
968:     indices   - array that contains the copied data
969:     lnk       - linked list that is cleaned and initialize
970:     bt        - PetscBT (bitarray) with all bits set to false
971: */
972: #define PetscLLClean(idx_start,lnk_max,nlnk,lnk,indices,bt) 0;\
973: {\
974:   PetscInt _j,_idx=idx_start;\
975:   for (_j=0; _j<nlnk; _j++){\
976:     _idx = lnk[_idx];\
977:     indices[_j] = _idx;\
978:     PetscBTClear(bt,_idx);\
979:   }\
980:   lnk[idx_start] = lnk_max;\
981: }
982: /*
983:   Free memories used by the list
984: */
985: #define PetscLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

987: /* Routines below are used for incomplete matrix factorization */
988: /*
989:   Create and initialize a linked list and its levels
990:   Input Parameters:
991:     idx_start - starting index of the list
992:     lnk_max   - max value of lnk indicating the end of the list
993:     nlnk      - max length of the list
994:   Output Parameters:
995:     lnk       - list initialized
996:     lnk_lvl   - array of size nlnk for storing levels of lnk
997:     bt        - PetscBT (bitarray) with all bits set to false
998: */
999: #define PetscIncompleteLLCreate(idx_start,lnk_max,nlnk,lnk,lnk_lvl,bt)\
1000:   (PetscIntMultError(2,nlnk,NULL) || PetscMalloc1(2*nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,lnk_lvl = lnk + nlnk,0))

1002: /*
1003:   Initialize a sorted linked list used for ILU and ICC
1004:   Input Parameters:
1005:     nidx      - number of input idx
1006:     idx       - integer array used for storing column indices
1007:     idx_start - starting index of the list
1008:     perm      - indices of an IS
1009:     lnk       - linked list(an integer array) that is created
1010:     lnklvl    - levels of lnk
1011:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1012:   output Parameters:
1013:     nlnk     - number of newly added idx
1014:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1015:     lnklvl   - levels of lnk
1016:     bt       - updated PetscBT (bitarray)
1017: */
1018: #define PetscIncompleteLLInit(nidx,idx,idx_start,perm,nlnk,lnk,lnklvl,bt) 0;\
1019: {\
1020:   PetscInt _k,_entry,_location,_lnkdata;\
1021:   nlnk     = 0;\
1022:   _lnkdata = idx_start;\
1023:   for (_k=0; _k<nidx; _k++){\
1024:     _entry = perm[idx[_k]];\
1025:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1026:       /* search for insertion location */\
1027:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
1028:       do {\
1029:         _location = _lnkdata;\
1030:         _lnkdata  = lnk[_location];\
1031:       } while (_entry > _lnkdata);\
1032:       /* insertion location is found, add entry into lnk */\
1033:       lnk[_location]  = _entry;\
1034:       lnk[_entry]     = _lnkdata;\
1035:       lnklvl[_entry] = 0;\
1036:       nlnk++;\
1037:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1038:     }\
1039:   }\
1040: }

1042: /*
1043:   Add a SORTED index set into a sorted linked list for ILU
1044:   Input Parameters:
1045:     nidx      - number of input indices
1046:     idx       - sorted integer array used for storing column indices
1047:     level     - level of fill, e.g., ICC(level)
1048:     idxlvl    - level of idx
1049:     idx_start - starting index of the list
1050:     lnk       - linked list(an integer array) that is created
1051:     lnklvl    - levels of lnk
1052:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1053:     prow      - the row number of idx
1054:   output Parameters:
1055:     nlnk     - number of newly added idx
1056:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1057:     lnklvl   - levels of lnk
1058:     bt       - updated PetscBT (bitarray)

1060:   Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1061:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1062: */
1063: #define PetscILULLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,lnklvl_prow) 0;\
1064: {\
1065:   PetscInt _k,_entry,_location,_lnkdata,_incrlev,_lnklvl_prow=lnklvl[prow];\
1066:   nlnk     = 0;\
1067:   _lnkdata = idx_start;\
1068:   for (_k=0; _k<nidx; _k++){\
1069:     _incrlev = idxlvl[_k] + _lnklvl_prow + 1;\
1070:     if (_incrlev > level) continue;\
1071:     _entry = idx[_k];\
1072:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1073:       /* search for insertion location */\
1074:       do {\
1075:         _location = _lnkdata;\
1076:         _lnkdata  = lnk[_location];\
1077:       } while (_entry > _lnkdata);\
1078:       /* insertion location is found, add entry into lnk */\
1079:       lnk[_location]  = _entry;\
1080:       lnk[_entry]     = _lnkdata;\
1081:       lnklvl[_entry] = _incrlev;\
1082:       nlnk++;\
1083:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1084:     } else { /* existing entry: update lnklvl */\
1085:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1086:     }\
1087:   }\
1088: }

1090: /*
1091:   Add a index set into a sorted linked list
1092:   Input Parameters:
1093:     nidx      - number of input idx
1094:     idx   - integer array used for storing column indices
1095:     level     - level of fill, e.g., ICC(level)
1096:     idxlvl - level of idx
1097:     idx_start - starting index of the list
1098:     lnk       - linked list(an integer array) that is created
1099:     lnklvl   - levels of lnk
1100:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1101:   output Parameters:
1102:     nlnk      - number of newly added idx
1103:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1104:     lnklvl   - levels of lnk
1105:     bt        - updated PetscBT (bitarray)
1106: */
1107: #define PetscIncompleteLLAdd(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1108: {\
1109:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1110:   nlnk     = 0;\
1111:   _lnkdata = idx_start;\
1112:   for (_k=0; _k<nidx; _k++){\
1113:     _incrlev = idxlvl[_k] + 1;\
1114:     if (_incrlev > level) continue;\
1115:     _entry = idx[_k];\
1116:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1117:       /* search for insertion location */\
1118:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
1119:       do {\
1120:         _location = _lnkdata;\
1121:         _lnkdata  = lnk[_location];\
1122:       } while (_entry > _lnkdata);\
1123:       /* insertion location is found, add entry into lnk */\
1124:       lnk[_location]  = _entry;\
1125:       lnk[_entry]     = _lnkdata;\
1126:       lnklvl[_entry] = _incrlev;\
1127:       nlnk++;\
1128:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1129:     } else { /* existing entry: update lnklvl */\
1130:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1131:     }\
1132:   }\
1133: }

1135: /*
1136:   Add a SORTED index set into a sorted linked list
1137:   Input Parameters:
1138:     nidx      - number of input indices
1139:     idx   - sorted integer array used for storing column indices
1140:     level     - level of fill, e.g., ICC(level)
1141:     idxlvl - level of idx
1142:     idx_start - starting index of the list
1143:     lnk       - linked list(an integer array) that is created
1144:     lnklvl    - levels of lnk
1145:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1146:   output Parameters:
1147:     nlnk      - number of newly added idx
1148:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1149:     lnklvl    - levels of lnk
1150:     bt        - updated PetscBT (bitarray)
1151: */
1152: #define PetscIncompleteLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1153: {\
1154:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1155:   nlnk = 0;\
1156:   _lnkdata = idx_start;\
1157:   for (_k=0; _k<nidx; _k++){\
1158:     _incrlev = idxlvl[_k] + 1;\
1159:     if (_incrlev > level) continue;\
1160:     _entry = idx[_k];\
1161:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1162:       /* search for insertion location */\
1163:       do {\
1164:         _location = _lnkdata;\
1165:         _lnkdata  = lnk[_location];\
1166:       } while (_entry > _lnkdata);\
1167:       /* insertion location is found, add entry into lnk */\
1168:       lnk[_location] = _entry;\
1169:       lnk[_entry]    = _lnkdata;\
1170:       lnklvl[_entry] = _incrlev;\
1171:       nlnk++;\
1172:       _lnkdata = _entry; /* next search starts from here */\
1173:     } else { /* existing entry: update lnklvl */\
1174:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1175:     }\
1176:   }\
1177: }

1179: /*
1180:   Add a SORTED index set into a sorted linked list for ICC
1181:   Input Parameters:
1182:     nidx      - number of input indices
1183:     idx       - sorted integer array used for storing column indices
1184:     level     - level of fill, e.g., ICC(level)
1185:     idxlvl    - level of idx
1186:     idx_start - starting index of the list
1187:     lnk       - linked list(an integer array) that is created
1188:     lnklvl    - levels of lnk
1189:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1190:     idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1191:   output Parameters:
1192:     nlnk   - number of newly added indices
1193:     lnk    - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1194:     lnklvl - levels of lnk
1195:     bt     - updated PetscBT (bitarray)
1196:   Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1197:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1198: */
1199: #define PetscICCLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,idxlvl_prow) 0;\
1200: {\
1201:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1202:   nlnk = 0;\
1203:   _lnkdata = idx_start;\
1204:   for (_k=0; _k<nidx; _k++){\
1205:     _incrlev = idxlvl[_k] + idxlvl_prow + 1;\
1206:     if (_incrlev > level) continue;\
1207:     _entry = idx[_k];\
1208:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1209:       /* search for insertion location */\
1210:       do {\
1211:         _location = _lnkdata;\
1212:         _lnkdata  = lnk[_location];\
1213:       } while (_entry > _lnkdata);\
1214:       /* insertion location is found, add entry into lnk */\
1215:       lnk[_location] = _entry;\
1216:       lnk[_entry]    = _lnkdata;\
1217:       lnklvl[_entry] = _incrlev;\
1218:       nlnk++;\
1219:       _lnkdata = _entry; /* next search starts from here */\
1220:     } else { /* existing entry: update lnklvl */\
1221:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1222:     }\
1223:   }\
1224: }

1226: /*
1227:   Copy data on the list into an array, then initialize the list
1228:   Input Parameters:
1229:     idx_start - starting index of the list
1230:     lnk_max   - max value of lnk indicating the end of the list
1231:     nlnk      - number of data on the list to be copied
1232:     lnk       - linked list
1233:     lnklvl    - level of lnk
1234:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1235:   output Parameters:
1236:     indices - array that contains the copied data
1237:     lnk     - linked list that is cleaned and initialize
1238:     lnklvl  - level of lnk that is reinitialized
1239:     bt      - PetscBT (bitarray) with all bits set to false
1240: */
1241: #define PetscIncompleteLLClean(idx_start,lnk_max,nlnk,lnk,lnklvl,indices,indiceslvl,bt) 0;\
1242: {\
1243:   PetscInt _j,_idx=idx_start;\
1244:   for (_j=0; _j<nlnk; _j++){\
1245:     _idx = lnk[_idx];\
1246:     *(indices+_j) = _idx;\
1247:     *(indiceslvl+_j) = lnklvl[_idx];\
1248:     lnklvl[_idx] = -1;\
1249:     PetscBTClear(bt,_idx);\
1250:   }\
1251:   lnk[idx_start] = lnk_max;\
1252: }
1253: /*
1254:   Free memories used by the list
1255: */
1256: #define PetscIncompleteLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

1258: #define MatCheckSameLocalSize(A,ar1,B,ar2) \
1260:   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);
1261: 
1262: #define MatCheckSameSize(A,ar1,B,ar2) \
1263:   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);\
1264:   MatCheckSameLocalSize(A,ar1,B,ar2);
1265: 
1266: #define VecCheckMatCompatible(M,x,ar1,b,ar2)                               \
1267:   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);\
1268:   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);

1270: /* -------------------------------------------------------------------------------------------------------*/
1271:  #include <petscbt.h>
1272: /*
1273:   Create and initialize a condensed linked list -
1274:     same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1275:     Barry suggested this approach (Dec. 6, 2011):
1276:       I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1277:       (it may be faster than the O(N) even sequentially due to less crazy memory access).

1279:       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
1280:       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
1281:       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
1282:       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.
1283:       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
1284:       to each other so memory access is much better than using the big array.

1286:   Example:
1287:      nlnk_max=5, lnk_max=36:
1288:      Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1289:      here, head_node has index 2 with value lnk[2]=lnk_max=36,
1290:            0-th entry is used to store the number of entries in the list,
1291:      The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.

1293:      Now adding a sorted set {2,4}, the list becomes
1294:      [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1295:      represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.

1297:      Then adding a sorted set {0,3,35}, the list
1298:      [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1299:      represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.

1301:   Input Parameters:
1302:     nlnk_max  - max length of the list
1303:     lnk_max   - max value of the entries
1304:   Output Parameters:
1305:     lnk       - list created and initialized
1306:     bt        - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1307: */
1308: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max,PetscInt lnk_max,PetscInt **lnk,PetscBT *bt)
1309: {
1311:   PetscInt       *llnk,lsize = 0;

1314:   PetscIntMultError(2,nlnk_max+2,&lsize);
1315:   PetscMalloc1(lsize,lnk);
1316:   PetscBTCreate(lnk_max,bt);
1317:   llnk = *lnk;
1318:   llnk[0] = 0;         /* number of entries on the list */
1319:   llnk[2] = lnk_max;   /* value in the head node */
1320:   llnk[3] = 2;         /* next for the head node */
1321:   return(0);
1322: }

1324: /*
1325:   Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1326:   Input Parameters:
1327:     nidx      - number of input indices
1328:     indices   - sorted integer array
1329:     lnk       - condensed linked list(an integer array) that is created
1330:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1331:   output Parameters:
1332:     lnk       - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1333:     bt        - updated PetscBT (bitarray)
1334: */
1335: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx,const PetscInt indices[],PetscInt lnk[],PetscBT bt)
1336: {
1337:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;

1340:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
1341:   _location = 2; /* head */
1342:     for (_k=0; _k<nidx; _k++){
1343:       _entry = indices[_k];
1344:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */
1345:         /* search for insertion location */
1346:         do {
1347:           _next     = _location + 1; /* link from previous node to next node */
1348:           _location = lnk[_next];    /* idx of next node */
1349:           _lnkdata  = lnk[_location];/* value of next node */
1350:         } while (_entry > _lnkdata);
1351:         /* insertion location is found, add entry into lnk */
1352:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
1353:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
1354:         lnk[_newnode]   = _entry;        /* set value of the new node */
1355:         lnk[_newnode+1] = _location;     /* connect new node to next node */
1356:         _location       = _newnode;      /* next search starts from the new node */
1357:         _nlnk++;
1358:       }   \
1359:     }\
1360:   lnk[0]   = _nlnk;   /* number of entries in the list */
1361:   return(0);
1362: }

1364: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max,PetscInt nidx,PetscInt *indices,PetscInt lnk[],PetscBT bt)
1365: {
1367:   PetscInt       _k,_next,_nlnk;

1370:   _next = lnk[3];       /* head node */
1371:   _nlnk = lnk[0];       /* num of entries on the list */
1372:   for (_k=0; _k<_nlnk; _k++){
1373:     indices[_k] = lnk[_next];
1374:     _next       = lnk[_next + 1];
1375:     PetscBTClear(bt,indices[_k]);
1376:   }
1377:   lnk[0] = 0;          /* num of entries on the list */
1378:   lnk[2] = lnk_max;    /* initialize head node */
1379:   lnk[3] = 2;          /* head node */
1380:   return(0);
1381: }

1383: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1384: {
1386:   PetscInt       k;

1389:   PetscPrintf(PETSC_COMM_SELF,"LLCondensed of size %D, (val,  next)\n",lnk[0]);
1390:   for (k=2; k< lnk[0]+2; k++){
1391:     PetscPrintf(PETSC_COMM_SELF," %D: (%D, %D)\n",2*k,lnk[2*k],lnk[2*k+1]);
1392:   }
1393:   return(0);
1394: }

1396: /*
1397:   Free memories used by the list
1398: */
1399: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk,PetscBT bt)
1400: {

1404:   PetscFree(lnk);
1405:   PetscBTDestroy(&bt);
1406:   return(0);
1407: }

1409: /* -------------------------------------------------------------------------------------------------------*/
1410: /*
1411:  Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1412:   Input Parameters:
1413:     nlnk_max  - max length of the list
1414:   Output Parameters:
1415:     lnk       - list created and initialized
1416: */
1417: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1418: {
1420:   PetscInt       *llnk,lsize = 0;

1423:   PetscIntMultError(2,nlnk_max+2,&lsize);
1424:   PetscMalloc1(lsize,lnk);
1425:   llnk = *lnk;
1426:   llnk[0] = 0;               /* number of entries on the list */
1427:   llnk[2] = PETSC_MAX_INT;   /* value in the head node */
1428:   llnk[3] = 2;               /* next for the head node */
1429:   return(0);
1430: }

1432: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1433: {
1435:   PetscInt       lsize = 0;

1438:   PetscIntMultError(2,nlnk_max+2,&lsize);
1439:   PetscRealloc(lsize*sizeof(PetscInt),lnk);
1440:   return(0);
1441: }

1443: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1444: {
1445:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
1446:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
1447:   _location = 2; /* head */ \
1448:     for (_k=0; _k<nidx; _k++){
1449:       _entry = indices[_k];
1450:       /* search for insertion location */
1451:       do {
1452:         _next     = _location + 1; /* link from previous node to next node */
1453:         _location = lnk[_next];    /* idx of next node */
1454:         _lnkdata  = lnk[_location];/* value of next node */
1455:       } while (_entry > _lnkdata);
1456:       if (_entry < _lnkdata) {
1457:         /* insertion location is found, add entry into lnk */
1458:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
1459:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
1460:         lnk[_newnode]   = _entry;        /* set value of the new node */
1461:         lnk[_newnode+1] = _location;     /* connect new node to next node */
1462:         _location       = _newnode;      /* next search starts from the new node */
1463:         _nlnk++;
1464:       }
1465:     }
1466:   lnk[0]   = _nlnk;   /* number of entries in the list */
1467:   return 0;
1468: }

1470: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_Scalable(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1471: {
1472:   PetscInt _k,_next,_nlnk;
1473:   _next = lnk[3];       /* head node */
1474:   _nlnk = lnk[0];
1475:   for (_k=0; _k<_nlnk; _k++){
1476:     indices[_k] = lnk[_next];
1477:     _next       = lnk[_next + 1];
1478:   }
1479:   lnk[0] = 0;          /* num of entries on the list */
1480:   lnk[3] = 2;          /* head node */
1481:   return 0;
1482: }

1484: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1485: {
1486:   return PetscFree(lnk);
1487: }

1489: /* -------------------------------------------------------------------------------------------------------*/
1490: /*
1491:       lnk[0]   number of links
1492:       lnk[1]   number of entries
1493:       lnk[3n]  value
1494:       lnk[3n+1] len
1495:       lnk[3n+2] link to next value

1497:       The next three are always the first link

1499:       lnk[3]    PETSC_MIN_INT+1
1500:       lnk[4]    1
1501:       lnk[5]    link to first real entry

1503:       The next three are always the last link

1505:       lnk[6]    PETSC_MAX_INT - 1
1506:       lnk[7]    1
1507:       lnk[8]    next valid link (this is the same as lnk[0] but without the decreases)
1508: */

1510: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max,PetscInt **lnk)
1511: {
1513:   PetscInt       *llnk,lsize = 0;

1516:   PetscIntMultError(3,nlnk_max+3,&lsize);
1517:   PetscMalloc1(lsize,lnk);
1518:   llnk = *lnk;
1519:   llnk[0] = 0;   /* nlnk: number of entries on the list */
1520:   llnk[1] = 0;          /* number of integer entries represented in list */
1521:   llnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
1522:   llnk[4] = 1;           /* count for the first node */
1523:   llnk[5] = 6;         /* next for the first node */
1524:   llnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
1525:   llnk[7] = 1;           /* count for the last node */
1526:   llnk[8] = 0;         /* next valid node to be used */
1527:   return(0);
1528: }

1530: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1531: {
1532:   PetscInt k,entry,prev,next;
1533:   prev      = 3;      /* first value */
1534:   next      = lnk[prev+2];
1535:   for (k=0; k<nidx; k++){
1536:     entry = indices[k];
1537:     /* search for insertion location */
1538:     while (entry >= lnk[next]) {
1539:       prev = next;
1540:       next = lnk[next+2];
1541:     }
1542:     /* entry is in range of previous list */
1543:     if (entry < lnk[prev]+lnk[prev+1]) continue;
1544:     lnk[1]++;
1545:     /* entry is right after previous list */
1546:     if (entry == lnk[prev]+lnk[prev+1]) {
1547:       lnk[prev+1]++;
1548:       if (lnk[next] == entry+1) { /* combine two contiguous strings */
1549:         lnk[prev+1] += lnk[next+1];
1550:         lnk[prev+2]  = lnk[next+2];
1551:         next         = lnk[next+2];
1552:         lnk[0]--;
1553:       }
1554:       continue;
1555:     }
1556:     /* entry is right before next list */
1557:     if (entry == lnk[next]-1) {
1558:       lnk[next]--;
1559:       lnk[next+1]++;
1560:       prev = next;
1561:       next = lnk[prev+2];
1562:       continue;
1563:     }
1564:     /*  add entry into lnk */
1565:     lnk[prev+2]    = 3*((lnk[8]++)+3);      /* connect previous node to the new node */
1566:     prev           = lnk[prev+2];
1567:     lnk[prev]      = entry;        /* set value of the new node */
1568:     lnk[prev+1]    = 1;             /* number of values in contiguous string is one to start */
1569:     lnk[prev+2]    = next;          /* connect new node to next node */
1570:     lnk[0]++;
1571:   }
1572:   return 0;
1573: }

1575: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_fast(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1576: {
1577:   PetscInt _k,_next,_nlnk,cnt,j;
1578:   _next = lnk[5];       /* first node */
1579:   _nlnk = lnk[0];
1580:   cnt   = 0;
1581:   for (_k=0; _k<_nlnk; _k++){
1582:     for (j=0; j<lnk[_next+1]; j++) {
1583:       indices[cnt++] = lnk[_next] + j;
1584:     }
1585:     _next       = lnk[_next + 2];
1586:   }
1587:   lnk[0] = 0;   /* nlnk: number of links */
1588:   lnk[1] = 0;          /* number of integer entries represented in list */
1589:   lnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
1590:   lnk[4] = 1;           /* count for the first node */
1591:   lnk[5] = 6;         /* next for the first node */
1592:   lnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
1593:   lnk[7] = 1;           /* count for the last node */
1594:   lnk[8] = 0;         /* next valid location to make link */
1595:   return 0;
1596: }

1598: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView_fast(PetscInt *lnk)
1599: {
1600:   PetscInt k,next,nlnk;
1601:   next = lnk[5];       /* first node */
1602:   nlnk = lnk[0];
1603:   for (k=0; k<nlnk; k++){
1604: #if 0                           /* Debugging code */
1605:     printf("%d value %d len %d next %d\n",next,lnk[next],lnk[next+1],lnk[next+2]);
1606: #endif
1607:     next = lnk[next + 2];
1608:   }
1609:   return 0;
1610: }

1612: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1613: {
1614:   return PetscFree(lnk);
1615: }

1617: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
1618: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,void*);

1620: PETSC_EXTERN PetscLogEvent MAT_Mult;
1621: PETSC_EXTERN PetscLogEvent MAT_MultMatrixFree;
1622: PETSC_EXTERN PetscLogEvent MAT_Mults;
1623: PETSC_EXTERN PetscLogEvent MAT_MultConstrained;
1624: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1625: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1626: PETSC_EXTERN PetscLogEvent MAT_MultTransposeConstrained;
1627: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1628: PETSC_EXTERN PetscLogEvent MAT_Solve;
1629: PETSC_EXTERN PetscLogEvent MAT_Solves;
1630: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1631: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1632: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1633: PETSC_EXTERN PetscLogEvent MAT_SOR;
1634: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1635: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1636: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1637: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1638: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1639: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1640: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1641: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1642: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1643: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1644: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1645: PETSC_EXTERN PetscLogEvent MAT_Copy;
1646: PETSC_EXTERN PetscLogEvent MAT_Convert;
1647: PETSC_EXTERN PetscLogEvent MAT_Scale;
1648: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1649: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1650: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1651: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1652: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1653: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1654: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1655: PETSC_EXTERN PetscLogEvent MAT_GetColoring;
1656: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1657: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1658: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1659: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1660: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1661: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1662: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1663: PETSC_EXTERN PetscLogEvent MAT_Load;
1664: PETSC_EXTERN PetscLogEvent MAT_View;
1665: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1666: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1667: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1668: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1669: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1670: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1671: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1672: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1673: PETSC_EXTERN PetscLogEvent MAT_MatMult;
1674: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1675: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1676: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1677: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1678: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1679: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1680: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1681: PETSC_EXTERN PetscLogEvent MAT_PtAP;
1682: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1683: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1684: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1685: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1686: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1687: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1688: PETSC_EXTERN PetscLogEvent MAT_RARt;
1689: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1690: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1691: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMult;
1692: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1693: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1694: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMult;
1695: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1696: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1697: PETSC_EXTERN PetscLogEvent MAT_MatMatMult;
1698: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1699: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1700: PETSC_EXTERN PetscLogEvent MAT_Applypapt;
1701: PETSC_EXTERN PetscLogEvent MAT_Applypapt_symbolic;
1702: PETSC_EXTERN PetscLogEvent MAT_Applypapt_numeric;
1703: PETSC_EXTERN PetscLogEvent MAT_Getsymtranspose;
1704: PETSC_EXTERN PetscLogEvent MAT_Transpose_SeqAIJ;
1705: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1706: PETSC_EXTERN PetscLogEvent MAT_GetSequentialNonzeroStructure;
1707: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1708: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1709: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1710: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1711: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1712: PETSC_EXTERN PetscLogEvent MAT_Merge;
1713: PETSC_EXTERN PetscLogEvent MAT_Residual;
1714: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1715: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1716: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1717: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1718: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1719: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1720: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;

1722: #endif