Actual source code: matimpl.h

petsc-master 2020-03-28
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  2: #ifndef __MATIMPL_H

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

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

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

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

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

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

227: PETSC_EXTERN MatRootName MatRootNameList;

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

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

251: #if defined(PETSC_USE_DEBUG)
252: #  define MatCheckPreallocated(A,arg) do {                              \
253:     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); \
254:   } while (0)
255: #else
256: #  define MatCheckPreallocated(A,arg) do {} while (0)
257: #endif

259: /*
260:   The stash is used to temporarily store inserted matrix values that
261:   belong to another processor. During the assembly phase the stashed
262:   values are moved to the correct processor and
263: */

265: typedef struct _MatStashSpace *PetscMatStashSpace;

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

452: /*
453:     Utility for MatFactor (Schur complement)
454: */
455: PETSC_INTERN PetscErrorCode MatFactorFactorizeSchurComplement_Private(Mat);
456: PETSC_INTERN PetscErrorCode MatFactorInvertSchurComplement_Private(Mat);
457: PETSC_INTERN PetscErrorCode MatFactorUpdateSchurStatus_Private(Mat);
458: PETSC_INTERN PetscErrorCode MatFactorSetUpInPlaceSchur_Private(Mat);

460: /*
461:     Utility for MatZeroRows
462: */
463: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat,PetscInt,const PetscInt*,PetscInt*,PetscInt**);

465: /*
466:     Utility for MatView/MatLoad
467: */
468: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat,PetscViewer);
469: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat,PetscViewer);


472: /*
473:     Object for partitioning graphs
474: */

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

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

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

500: /*
501:     Object for coarsen graphs
502: */
503: typedef struct _MatCoarsenOps *MatCoarsenOps;
504: struct _MatCoarsenOps {
505:   PetscErrorCode (*apply)(MatCoarsen);
506:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatCoarsen);
507:   PetscErrorCode (*destroy)(MatCoarsen);
508:   PetscErrorCode (*view)(MatCoarsen,PetscViewer);
509: };

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

522: /*
523:     MatFDColoring is used to compute Jacobian matrices efficiently
524:   via coloring. The data structure is explained below in an example.

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

538:     ncolors = 4;

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

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

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

557: */
558: typedef struct {
559:   PetscInt     row;
560:   PetscInt     col;
561:   PetscScalar  *valaddr;   /* address of value */
562: } MatEntry;

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

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

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

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

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

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

638: /*
639:    Null space context for preconditioner/operators
640: */
641: struct _p_MatNullSpace {
642:   PETSCHEADER(int);
643:   PetscBool      has_cnst;
644:   PetscInt       n;
645:   Vec*           vecs;
646:   PetscScalar*   alpha;                 /* for projections */
647:   PetscErrorCode (*remove)(MatNullSpace,Vec,void*);  /* for user provided removal function */
648:   void*          rmctx;                 /* context for remove() function */
649: };

651: /*
652:    Checking zero pivot for LU, ILU preconditioners.
653: */
654: typedef struct {
655:   PetscInt       nshift,nshift_max;
656:   PetscReal      shift_amount,shift_lo,shift_hi,shift_top,shift_fraction;
657:   PetscBool      newshift;
658:   PetscReal      rs;  /* active row sum of abs(offdiagonals) */
659:   PetscScalar    pv;  /* pivot of the active row */
660: } FactorShiftCtx;

662: /*
663:  Used by MatCreateSubMatrices_MPIXAIJ_Local()
664: */
665:  #include <petscctable.h>
666: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
667:   PetscInt   id;   /* index of submats, only submats[0] is responsible for deleting some arrays below */
668:   PetscInt   nrqs,nrqr;
669:   PetscInt   **rbuf1,**rbuf2,**rbuf3,**sbuf1,**sbuf2;
670:   PetscInt   **ptr;
671:   PetscInt   *tmp;
672:   PetscInt   *ctr;
673:   PetscInt   *pa; /* proc array */
674:   PetscInt   *req_size,*req_source1,*req_source2;
675:   PetscBool  allcolumns,allrows;
676:   PetscBool  singleis;
677:   PetscInt   *row2proc; /* row to proc map */
678:   PetscInt   nstages;
679: #if defined(PETSC_USE_CTABLE)
680:   PetscTable cmap,rmap;
681:   PetscInt   *cmap_loc,*rmap_loc;
682: #else
683:   PetscInt   *cmap,*rmap;
684: #endif

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

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

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

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

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

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

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

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

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

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

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

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

783: /*
784:   Create and initialize a linked list
785:   Input Parameters:
786:     idx_start - starting index of the list
787:     lnk_max   - max value of lnk indicating the end of the list
788:     nlnk      - max length of the list
789:   Output Parameters:
790:     lnk       - list initialized
791:     bt        - PetscBT (bitarray) with all bits set to false
792:     lnk_empty - flg indicating the list is empty
793: */
794: #define PetscLLCreate(idx_start,lnk_max,nlnk,lnk,bt) \
795:   (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,0))

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

800: /*
801:   Add an index set into a sorted linked list
802:   Input Parameters:
803:     nidx      - number of input indices
804:     indices   - integer array
805:     idx_start - starting index of the list
806:     lnk       - linked list(an integer array) that is created
807:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
808:   output Parameters:
809:     nlnk      - number of newly added indices
810:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
811:     bt        - updated PetscBT (bitarray)
812: */
813: #define PetscLLAdd(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
814: {\
815:   PetscInt _k,_entry,_location,_lnkdata;\
816:   nlnk     = 0;\
817:   _lnkdata = idx_start;\
818:   for (_k=0; _k<nidx; _k++){\
819:     _entry = indices[_k];\
820:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
821:       /* search for insertion location */\
822:       /* start from the beginning if _entry < previous _entry */\
823:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
824:       do {\
825:         _location = _lnkdata;\
826:         _lnkdata  = lnk[_location];\
827:       } while (_entry > _lnkdata);\
828:       /* insertion location is found, add entry into lnk */\
829:       lnk[_location] = _entry;\
830:       lnk[_entry]    = _lnkdata;\
831:       nlnk++;\
832:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
833:     }\
834:   }\
835: }

837: /*
838:   Add a permuted index set into a sorted linked list
839:   Input Parameters:
840:     nidx      - number of input indices
841:     indices   - integer array
842:     perm      - permutation of indices
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 PetscLLAddPerm(nidx,indices,perm,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 = perm[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 SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata  = idx_start;'
877:   Input Parameters:
878:     nidx      - number of input indices
879:     indices   - sorted integer array
880:     idx_start - starting index of the list
881:     lnk       - linked list(an integer array) that is created
882:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
883:   output Parameters:
884:     nlnk      - number of newly added indices
885:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
886:     bt        - updated PetscBT (bitarray)
887: */
888: #define PetscLLAddSorted(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
889: {\
890:   PetscInt _k,_entry,_location,_lnkdata;\
891:   nlnk      = 0;\
892:   _lnkdata  = idx_start;\
893:   for (_k=0; _k<nidx; _k++){\
894:     _entry = indices[_k];\
895:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
896:       /* search for insertion location */\
897:       do {\
898:         _location = _lnkdata;\
899:         _lnkdata  = lnk[_location];\
900:       } while (_entry > _lnkdata);\
901:       /* insertion location is found, add entry into lnk */\
902:       lnk[_location] = _entry;\
903:       lnk[_entry]    = _lnkdata;\
904:       nlnk++;\
905:       _lnkdata = _entry; /* next search starts from here */\
906:     }\
907:   }\
908: }

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

957: /*
958:   Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
959:   Same as PetscLLAddSorted() with an additional operation:
960:        count the number of input indices that are no larger than 'diag'
961:   Input Parameters:
962:     indices   - sorted integer array
963:     idx_start - starting index of the list, index of pivot row
964:     lnk       - linked list(an integer array) that is created
965:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
966:     diag      - index of the active row in LUFactorSymbolic
967:     nzbd      - number of input indices with indices <= idx_start
968:     im        - im[idx_start] is initialized as num of nonzero entries in row=idx_start
969:   output Parameters:
970:     nlnk      - number of newly added indices
971:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
972:     bt        - updated PetscBT (bitarray)
973:     im        - im[idx_start]: unchanged if diag is not an entry
974:                              : num of entries with indices <= diag if diag is an entry
975: */
976: #define PetscLLAddSortedLU(indices,idx_start,nlnk,lnk,bt,diag,nzbd,im) 0;\
977: {\
978:   PetscInt _k,_entry,_location,_lnkdata,_nidx;\
979:   nlnk     = 0;\
980:   _lnkdata = idx_start;\
981:   _nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */\
982:   for (_k=0; _k<_nidx; _k++){\
983:     _entry = indices[_k];\
984:     nzbd++;\
985:     if ( _entry== diag) im[idx_start] = nzbd;\
986:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
987:       /* search for insertion location */\
988:       do {\
989:         _location = _lnkdata;\
990:         _lnkdata  = lnk[_location];\
991:       } while (_entry > _lnkdata);\
992:       /* insertion location is found, add entry into lnk */\
993:       lnk[_location] = _entry;\
994:       lnk[_entry]    = _lnkdata;\
995:       nlnk++;\
996:       _lnkdata = _entry; /* next search starts from here */\
997:     }\
998:   }\
999: }

1001: /*
1002:   Copy data on the list into an array, then initialize the list
1003:   Input Parameters:
1004:     idx_start - starting index of the list
1005:     lnk_max   - max value of lnk indicating the end of the list
1006:     nlnk      - number of data on the list to be copied
1007:     lnk       - linked list
1008:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1009:   output Parameters:
1010:     indices   - array that contains the copied data
1011:     lnk       - linked list that is cleaned and initialize
1012:     bt        - PetscBT (bitarray) with all bits set to false
1013: */
1014: #define PetscLLClean(idx_start,lnk_max,nlnk,lnk,indices,bt) 0;\
1015: {\
1016:   PetscInt _j,_idx=idx_start;\
1017:   for (_j=0; _j<nlnk; _j++){\
1018:     _idx = lnk[_idx];\
1019:     indices[_j] = _idx;\
1020:     PetscBTClear(bt,_idx);\
1021:   }\
1022:   lnk[idx_start] = lnk_max;\
1023: }
1024: /*
1025:   Free memories used by the list
1026: */
1027: #define PetscLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

1029: /* Routines below are used for incomplete matrix factorization */
1030: /*
1031:   Create and initialize a linked list and its levels
1032:   Input Parameters:
1033:     idx_start - starting index of the list
1034:     lnk_max   - max value of lnk indicating the end of the list
1035:     nlnk      - max length of the list
1036:   Output Parameters:
1037:     lnk       - list initialized
1038:     lnk_lvl   - array of size nlnk for storing levels of lnk
1039:     bt        - PetscBT (bitarray) with all bits set to false
1040: */
1041: #define PetscIncompleteLLCreate(idx_start,lnk_max,nlnk,lnk,lnk_lvl,bt)\
1042:   (PetscIntMultError(2,nlnk,NULL) || PetscMalloc1(2*nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,lnk_lvl = lnk + nlnk,0))

1044: /*
1045:   Initialize a sorted linked list used for ILU and ICC
1046:   Input Parameters:
1047:     nidx      - number of input idx
1048:     idx       - integer array used for storing column indices
1049:     idx_start - starting index of the list
1050:     perm      - indices of an IS
1051:     lnk       - linked list(an integer array) that is created
1052:     lnklvl    - levels of lnk
1053:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
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)
1059: */
1060: #define PetscIncompleteLLInit(nidx,idx,idx_start,perm,nlnk,lnk,lnklvl,bt) 0;\
1061: {\
1062:   PetscInt _k,_entry,_location,_lnkdata;\
1063:   nlnk     = 0;\
1064:   _lnkdata = idx_start;\
1065:   for (_k=0; _k<nidx; _k++){\
1066:     _entry = perm[idx[_k]];\
1067:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1068:       /* search for insertion location */\
1069:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
1070:       do {\
1071:         _location = _lnkdata;\
1072:         _lnkdata  = lnk[_location];\
1073:       } while (_entry > _lnkdata);\
1074:       /* insertion location is found, add entry into lnk */\
1075:       lnk[_location]  = _entry;\
1076:       lnk[_entry]     = _lnkdata;\
1077:       lnklvl[_entry] = 0;\
1078:       nlnk++;\
1079:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1080:     }\
1081:   }\
1082: }

1084: /*
1085:   Add a SORTED index set into a sorted linked list for ILU
1086:   Input Parameters:
1087:     nidx      - number of input indices
1088:     idx       - sorted integer array used for storing column indices
1089:     level     - level of fill, e.g., ICC(level)
1090:     idxlvl    - level of idx
1091:     idx_start - starting index of the list
1092:     lnk       - linked list(an integer array) that is created
1093:     lnklvl    - levels of lnk
1094:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1095:     prow      - the row number of idx
1096:   output Parameters:
1097:     nlnk     - number of newly added idx
1098:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1099:     lnklvl   - levels of lnk
1100:     bt       - updated PetscBT (bitarray)

1102:   Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1103:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1104: */
1105: #define PetscILULLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,lnklvl_prow) 0;\
1106: {\
1107:   PetscInt _k,_entry,_location,_lnkdata,_incrlev,_lnklvl_prow=lnklvl[prow];\
1108:   nlnk     = 0;\
1109:   _lnkdata = idx_start;\
1110:   for (_k=0; _k<nidx; _k++){\
1111:     _incrlev = idxlvl[_k] + _lnklvl_prow + 1;\
1112:     if (_incrlev > level) continue;\
1113:     _entry = idx[_k];\
1114:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1115:       /* search for insertion location */\
1116:       do {\
1117:         _location = _lnkdata;\
1118:         _lnkdata  = lnk[_location];\
1119:       } while (_entry > _lnkdata);\
1120:       /* insertion location is found, add entry into lnk */\
1121:       lnk[_location]  = _entry;\
1122:       lnk[_entry]     = _lnkdata;\
1123:       lnklvl[_entry] = _incrlev;\
1124:       nlnk++;\
1125:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1126:     } else { /* existing entry: update lnklvl */\
1127:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1128:     }\
1129:   }\
1130: }

1132: /*
1133:   Add a index set into a sorted linked list
1134:   Input Parameters:
1135:     nidx      - number of input idx
1136:     idx   - integer array used for storing column indices
1137:     level     - level of fill, e.g., ICC(level)
1138:     idxlvl - level of idx
1139:     idx_start - starting index of the list
1140:     lnk       - linked list(an integer array) that is created
1141:     lnklvl   - levels of lnk
1142:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1143:   output Parameters:
1144:     nlnk      - number of newly added idx
1145:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1146:     lnklvl   - levels of lnk
1147:     bt        - updated PetscBT (bitarray)
1148: */
1149: #define PetscIncompleteLLAdd(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1150: {\
1151:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1152:   nlnk     = 0;\
1153:   _lnkdata = idx_start;\
1154:   for (_k=0; _k<nidx; _k++){\
1155:     _incrlev = idxlvl[_k] + 1;\
1156:     if (_incrlev > level) continue;\
1157:     _entry = idx[_k];\
1158:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1159:       /* search for insertion location */\
1160:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
1161:       do {\
1162:         _location = _lnkdata;\
1163:         _lnkdata  = lnk[_location];\
1164:       } while (_entry > _lnkdata);\
1165:       /* insertion location is found, add entry into lnk */\
1166:       lnk[_location]  = _entry;\
1167:       lnk[_entry]     = _lnkdata;\
1168:       lnklvl[_entry] = _incrlev;\
1169:       nlnk++;\
1170:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1171:     } else { /* existing entry: update lnklvl */\
1172:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1173:     }\
1174:   }\
1175: }

1177: /*
1178:   Add a SORTED index set into a sorted linked list
1179:   Input Parameters:
1180:     nidx      - number of input indices
1181:     idx   - sorted integer array used for storing column indices
1182:     level     - level of fill, e.g., ICC(level)
1183:     idxlvl - level of idx
1184:     idx_start - starting index of the list
1185:     lnk       - linked list(an integer array) that is created
1186:     lnklvl    - levels of lnk
1187:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1188:   output Parameters:
1189:     nlnk      - number of newly added idx
1190:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1191:     lnklvl    - levels of lnk
1192:     bt        - updated PetscBT (bitarray)
1193: */
1194: #define PetscIncompleteLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1195: {\
1196:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1197:   nlnk = 0;\
1198:   _lnkdata = idx_start;\
1199:   for (_k=0; _k<nidx; _k++){\
1200:     _incrlev = idxlvl[_k] + 1;\
1201:     if (_incrlev > level) continue;\
1202:     _entry = idx[_k];\
1203:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1204:       /* search for insertion location */\
1205:       do {\
1206:         _location = _lnkdata;\
1207:         _lnkdata  = lnk[_location];\
1208:       } while (_entry > _lnkdata);\
1209:       /* insertion location is found, add entry into lnk */\
1210:       lnk[_location] = _entry;\
1211:       lnk[_entry]    = _lnkdata;\
1212:       lnklvl[_entry] = _incrlev;\
1213:       nlnk++;\
1214:       _lnkdata = _entry; /* next search starts from here */\
1215:     } else { /* existing entry: update lnklvl */\
1216:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1217:     }\
1218:   }\
1219: }

1221: /*
1222:   Add a SORTED index set into a sorted linked list for ICC
1223:   Input Parameters:
1224:     nidx      - number of input indices
1225:     idx       - sorted integer array used for storing column indices
1226:     level     - level of fill, e.g., ICC(level)
1227:     idxlvl    - level of idx
1228:     idx_start - starting index of the list
1229:     lnk       - linked list(an integer array) that is created
1230:     lnklvl    - levels of lnk
1231:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1232:     idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1233:   output Parameters:
1234:     nlnk   - number of newly added indices
1235:     lnk    - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1236:     lnklvl - levels of lnk
1237:     bt     - updated PetscBT (bitarray)
1238:   Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1239:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1240: */
1241: #define PetscICCLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,idxlvl_prow) 0;\
1242: {\
1243:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1244:   nlnk = 0;\
1245:   _lnkdata = idx_start;\
1246:   for (_k=0; _k<nidx; _k++){\
1247:     _incrlev = idxlvl[_k] + idxlvl_prow + 1;\
1248:     if (_incrlev > level) continue;\
1249:     _entry = idx[_k];\
1250:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1251:       /* search for insertion location */\
1252:       do {\
1253:         _location = _lnkdata;\
1254:         _lnkdata  = lnk[_location];\
1255:       } while (_entry > _lnkdata);\
1256:       /* insertion location is found, add entry into lnk */\
1257:       lnk[_location] = _entry;\
1258:       lnk[_entry]    = _lnkdata;\
1259:       lnklvl[_entry] = _incrlev;\
1260:       nlnk++;\
1261:       _lnkdata = _entry; /* next search starts from here */\
1262:     } else { /* existing entry: update lnklvl */\
1263:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1264:     }\
1265:   }\
1266: }

1268: /*
1269:   Copy data on the list into an array, then initialize the list
1270:   Input Parameters:
1271:     idx_start - starting index of the list
1272:     lnk_max   - max value of lnk indicating the end of the list
1273:     nlnk      - number of data on the list to be copied
1274:     lnk       - linked list
1275:     lnklvl    - level of lnk
1276:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1277:   output Parameters:
1278:     indices - array that contains the copied data
1279:     lnk     - linked list that is cleaned and initialize
1280:     lnklvl  - level of lnk that is reinitialized
1281:     bt      - PetscBT (bitarray) with all bits set to false
1282: */
1283: #define PetscIncompleteLLClean(idx_start,lnk_max,nlnk,lnk,lnklvl,indices,indiceslvl,bt) 0;\
1284: do {\
1285:   PetscInt _j,_idx=idx_start;\
1286:   for (_j=0; _j<nlnk; _j++){\
1287:     _idx = lnk[_idx];\
1288:     *(indices+_j) = _idx;\
1289:     *(indiceslvl+_j) = lnklvl[_idx];\
1290:     lnklvl[_idx] = -1;\
1291:     PetscBTClear(bt,_idx);\
1292:   }\
1293:   lnk[idx_start] = lnk_max;\
1294: } while (0)
1295: /*
1296:   Free memories used by the list
1297: */
1298: #define PetscIncompleteLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

1300: #define MatCheckSameLocalSize(A,ar1,B,ar2) do { \
1302:   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)

1304: #define MatCheckSameSize(A,ar1,B,ar2) do { \
1305:   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);\
1306:   MatCheckSameLocalSize(A,ar1,B,ar2);} while (0)

1308: #define VecCheckMatCompatible(M,x,ar1,b,ar2) do { \
1309:   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); \
1310:   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)

1312: /* -------------------------------------------------------------------------------------------------------*/
1313:  #include <petscbt.h>
1314: /*
1315:   Create and initialize a condensed linked list -
1316:     same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1317:     Barry suggested this approach (Dec. 6, 2011):
1318:       I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1319:       (it may be faster than the O(N) even sequentially due to less crazy memory access).

1321:       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
1322:       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
1323:       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
1324:       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.
1325:       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
1326:       to each other so memory access is much better than using the big array.

1328:   Example:
1329:      nlnk_max=5, lnk_max=36:
1330:      Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1331:      here, head_node has index 2 with value lnk[2]=lnk_max=36,
1332:            0-th entry is used to store the number of entries in the list,
1333:      The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.

1335:      Now adding a sorted set {2,4}, the list becomes
1336:      [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1337:      represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.

1339:      Then adding a sorted set {0,3,35}, the list
1340:      [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1341:      represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.

1343:   Input Parameters:
1344:     nlnk_max  - max length of the list
1345:     lnk_max   - max value of the entries
1346:   Output Parameters:
1347:     lnk       - list created and initialized
1348:     bt        - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1349: */
1350: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max,PetscInt lnk_max,PetscInt **lnk,PetscBT *bt)
1351: {
1353:   PetscInt       *llnk,lsize = 0;

1356:   PetscIntMultError(2,nlnk_max+2,&lsize);
1357:   PetscMalloc1(lsize,lnk);
1358:   PetscBTCreate(lnk_max,bt);
1359:   llnk = *lnk;
1360:   llnk[0] = 0;         /* number of entries on the list */
1361:   llnk[2] = lnk_max;   /* value in the head node */
1362:   llnk[3] = 2;         /* next for the head node */
1363:   return(0);
1364: }

1366: /*
1367:   Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1368:   Input Parameters:
1369:     nidx      - number of input indices
1370:     indices   - sorted integer array
1371:     lnk       - condensed linked list(an integer array) that is created
1372:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1373:   output Parameters:
1374:     lnk       - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1375:     bt        - updated PetscBT (bitarray)
1376: */
1377: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx,const PetscInt indices[],PetscInt lnk[],PetscBT bt)
1378: {
1379:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;

1382:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
1383:   _location = 2; /* head */
1384:     for (_k=0; _k<nidx; _k++){
1385:       _entry = indices[_k];
1386:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */
1387:         /* search for insertion location */
1388:         do {
1389:           _next     = _location + 1; /* link from previous node to next node */
1390:           _location = lnk[_next];    /* idx of next node */
1391:           _lnkdata  = lnk[_location];/* value of next node */
1392:         } while (_entry > _lnkdata);
1393:         /* insertion location is found, add entry into lnk */
1394:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
1395:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
1396:         lnk[_newnode]   = _entry;        /* set value of the new node */
1397:         lnk[_newnode+1] = _location;     /* connect new node to next node */
1398:         _location       = _newnode;      /* next search starts from the new node */
1399:         _nlnk++;
1400:       }   \
1401:     }\
1402:   lnk[0]   = _nlnk;   /* number of entries in the list */
1403:   return(0);
1404: }

1406: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max,PetscInt nidx,PetscInt *indices,PetscInt lnk[],PetscBT bt)
1407: {
1409:   PetscInt       _k,_next,_nlnk;

1412:   _next = lnk[3];       /* head node */
1413:   _nlnk = lnk[0];       /* num of entries on the list */
1414:   for (_k=0; _k<_nlnk; _k++){
1415:     indices[_k] = lnk[_next];
1416:     _next       = lnk[_next + 1];
1417:     PetscBTClear(bt,indices[_k]);
1418:   }
1419:   lnk[0] = 0;          /* num of entries on the list */
1420:   lnk[2] = lnk_max;    /* initialize head node */
1421:   lnk[3] = 2;          /* head node */
1422:   return(0);
1423: }

1425: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1426: {
1428:   PetscInt       k;

1431:   PetscPrintf(PETSC_COMM_SELF,"LLCondensed of size %D, (val,  next)\n",lnk[0]);
1432:   for (k=2; k< lnk[0]+2; k++){
1433:     PetscPrintf(PETSC_COMM_SELF," %D: (%D, %D)\n",2*k,lnk[2*k],lnk[2*k+1]);
1434:   }
1435:   return(0);
1436: }

1438: /*
1439:   Free memories used by the list
1440: */
1441: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk,PetscBT bt)
1442: {

1446:   PetscFree(lnk);
1447:   PetscBTDestroy(&bt);
1448:   return(0);
1449: }

1451: /* -------------------------------------------------------------------------------------------------------*/
1452: /*
1453:  Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1454:   Input Parameters:
1455:     nlnk_max  - max length of the list
1456:   Output Parameters:
1457:     lnk       - list created and initialized
1458: */
1459: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1460: {
1462:   PetscInt       *llnk,lsize = 0;

1465:   PetscIntMultError(2,nlnk_max+2,&lsize);
1466:   PetscMalloc1(lsize,lnk);
1467:   llnk = *lnk;
1468:   llnk[0] = 0;               /* number of entries on the list */
1469:   llnk[2] = PETSC_MAX_INT;   /* value in the head node */
1470:   llnk[3] = 2;               /* next for the head node */
1471:   return(0);
1472: }

1474: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1475: {
1477:   PetscInt       lsize = 0;

1480:   PetscIntMultError(2,nlnk_max+2,&lsize);
1481:   PetscRealloc(lsize*sizeof(PetscInt),lnk);
1482:   return(0);
1483: }

1485: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1486: {
1487:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
1488:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
1489:   _location = 2; /* head */ \
1490:     for (_k=0; _k<nidx; _k++){
1491:       _entry = indices[_k];
1492:       /* search for insertion location */
1493:       do {
1494:         _next     = _location + 1; /* link from previous node to next node */
1495:         _location = lnk[_next];    /* idx of next node */
1496:         _lnkdata  = lnk[_location];/* value of next node */
1497:       } while (_entry > _lnkdata);
1498:       if (_entry < _lnkdata) {
1499:         /* insertion location is found, add entry into lnk */
1500:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
1501:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
1502:         lnk[_newnode]   = _entry;        /* set value of the new node */
1503:         lnk[_newnode+1] = _location;     /* connect new node to next node */
1504:         _location       = _newnode;      /* next search starts from the new node */
1505:         _nlnk++;
1506:       }
1507:     }
1508:   lnk[0]   = _nlnk;   /* number of entries in the list */
1509:   return 0;
1510: }

1512: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_Scalable(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1513: {
1514:   PetscInt _k,_next,_nlnk;
1515:   _next = lnk[3];       /* head node */
1516:   _nlnk = lnk[0];
1517:   for (_k=0; _k<_nlnk; _k++){
1518:     indices[_k] = lnk[_next];
1519:     _next       = lnk[_next + 1];
1520:   }
1521:   lnk[0] = 0;          /* num of entries on the list */
1522:   lnk[3] = 2;          /* head node */
1523:   return 0;
1524: }

1526: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1527: {
1528:   return PetscFree(lnk);
1529: }

1531: /* -------------------------------------------------------------------------------------------------------*/
1532: /*
1533:       lnk[0]   number of links
1534:       lnk[1]   number of entries
1535:       lnk[3n]  value
1536:       lnk[3n+1] len
1537:       lnk[3n+2] link to next value

1539:       The next three are always the first link

1541:       lnk[3]    PETSC_MIN_INT+1
1542:       lnk[4]    1
1543:       lnk[5]    link to first real entry

1545:       The next three are always the last link

1547:       lnk[6]    PETSC_MAX_INT - 1
1548:       lnk[7]    1
1549:       lnk[8]    next valid link (this is the same as lnk[0] but without the decreases)
1550: */

1552: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max,PetscInt **lnk)
1553: {
1555:   PetscInt       *llnk,lsize = 0;

1558:   PetscIntMultError(3,nlnk_max+3,&lsize);
1559:   PetscMalloc1(lsize,lnk);
1560:   llnk = *lnk;
1561:   llnk[0] = 0;   /* nlnk: number of entries on the list */
1562:   llnk[1] = 0;          /* number of integer entries represented in list */
1563:   llnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
1564:   llnk[4] = 1;           /* count for the first node */
1565:   llnk[5] = 6;         /* next for the first node */
1566:   llnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
1567:   llnk[7] = 1;           /* count for the last node */
1568:   llnk[8] = 0;         /* next valid node to be used */
1569:   return(0);
1570: }

1572: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1573: {
1574:   PetscInt k,entry,prev,next;
1575:   prev      = 3;      /* first value */
1576:   next      = lnk[prev+2];
1577:   for (k=0; k<nidx; k++){
1578:     entry = indices[k];
1579:     /* search for insertion location */
1580:     while (entry >= lnk[next]) {
1581:       prev = next;
1582:       next = lnk[next+2];
1583:     }
1584:     /* entry is in range of previous list */
1585:     if (entry < lnk[prev]+lnk[prev+1]) continue;
1586:     lnk[1]++;
1587:     /* entry is right after previous list */
1588:     if (entry == lnk[prev]+lnk[prev+1]) {
1589:       lnk[prev+1]++;
1590:       if (lnk[next] == entry+1) { /* combine two contiguous strings */
1591:         lnk[prev+1] += lnk[next+1];
1592:         lnk[prev+2]  = lnk[next+2];
1593:         next         = lnk[next+2];
1594:         lnk[0]--;
1595:       }
1596:       continue;
1597:     }
1598:     /* entry is right before next list */
1599:     if (entry == lnk[next]-1) {
1600:       lnk[next]--;
1601:       lnk[next+1]++;
1602:       prev = next;
1603:       next = lnk[prev+2];
1604:       continue;
1605:     }
1606:     /*  add entry into lnk */
1607:     lnk[prev+2]    = 3*((lnk[8]++)+3);      /* connect previous node to the new node */
1608:     prev           = lnk[prev+2];
1609:     lnk[prev]      = entry;        /* set value of the new node */
1610:     lnk[prev+1]    = 1;             /* number of values in contiguous string is one to start */
1611:     lnk[prev+2]    = next;          /* connect new node to next node */
1612:     lnk[0]++;
1613:   }
1614:   return 0;
1615: }

1617: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_fast(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1618: {
1619:   PetscInt _k,_next,_nlnk,cnt,j;
1620:   _next = lnk[5];       /* first node */
1621:   _nlnk = lnk[0];
1622:   cnt   = 0;
1623:   for (_k=0; _k<_nlnk; _k++){
1624:     for (j=0; j<lnk[_next+1]; j++) {
1625:       indices[cnt++] = lnk[_next] + j;
1626:     }
1627:     _next       = lnk[_next + 2];
1628:   }
1629:   lnk[0] = 0;   /* nlnk: number of links */
1630:   lnk[1] = 0;          /* number of integer entries represented in list */
1631:   lnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
1632:   lnk[4] = 1;           /* count for the first node */
1633:   lnk[5] = 6;         /* next for the first node */
1634:   lnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
1635:   lnk[7] = 1;           /* count for the last node */
1636:   lnk[8] = 0;         /* next valid location to make link */
1637:   return 0;
1638: }

1640: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView_fast(PetscInt *lnk)
1641: {
1642:   PetscInt k,next,nlnk;
1643:   next = lnk[5];       /* first node */
1644:   nlnk = lnk[0];
1645:   for (k=0; k<nlnk; k++){
1646: #if 0                           /* Debugging code */
1647:     printf("%d value %d len %d next %d\n",next,lnk[next],lnk[next+1],lnk[next+2]);
1648: #endif
1649:     next = lnk[next + 2];
1650:   }
1651:   return 0;
1652: }

1654: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1655: {
1656:   return PetscFree(lnk);
1657: }

1659: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
1660: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,void*);

1662: PETSC_EXTERN PetscLogEvent MAT_Mult;
1663: PETSC_EXTERN PetscLogEvent MAT_MultMatrixFree;
1664: PETSC_EXTERN PetscLogEvent MAT_Mults;
1665: PETSC_EXTERN PetscLogEvent MAT_MultConstrained;
1666: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1667: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1668: PETSC_EXTERN PetscLogEvent MAT_MultTransposeConstrained;
1669: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1670: PETSC_EXTERN PetscLogEvent MAT_Solve;
1671: PETSC_EXTERN PetscLogEvent MAT_Solves;
1672: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1673: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1674: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1675: PETSC_EXTERN PetscLogEvent MAT_SOR;
1676: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1677: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1678: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1679: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1680: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1681: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1682: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1683: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1684: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1685: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1686: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1687: PETSC_EXTERN PetscLogEvent MAT_Copy;
1688: PETSC_EXTERN PetscLogEvent MAT_Convert;
1689: PETSC_EXTERN PetscLogEvent MAT_Scale;
1690: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1691: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1692: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1693: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1694: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1695: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1696: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1697: PETSC_EXTERN PetscLogEvent MAT_GetColoring;
1698: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1699: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1700: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1701: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1702: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1703: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1704: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1705: PETSC_EXTERN PetscLogEvent MAT_Load;
1706: PETSC_EXTERN PetscLogEvent MAT_View;
1707: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1708: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1709: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1710: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1711: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1712: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1713: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1714: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1715: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1716: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1717: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1718: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1719: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1720: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1721: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1722: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1723: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1724: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1725: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1726: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1727: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1728: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1729: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1730: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1731: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1732: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1733: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1734: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1735: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1736: PETSC_EXTERN PetscLogEvent MAT_Applypapt;
1737: PETSC_EXTERN PetscLogEvent MAT_Applypapt_symbolic;
1738: PETSC_EXTERN PetscLogEvent MAT_Applypapt_numeric;
1739: PETSC_EXTERN PetscLogEvent MAT_Getsymtranspose;
1740: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1741: PETSC_EXTERN PetscLogEvent MAT_GetSequentialNonzeroStructure;
1742: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1743: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1744: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1745: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1746: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1747: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1748: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1749: PETSC_EXTERN PetscLogEvent MAT_Merge;
1750: PETSC_EXTERN PetscLogEvent MAT_Residual;
1751: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1752: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1753: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1754: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1755: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1756: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1757: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1758: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1759: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;

1761: #endif