Actual source code: matimpl.h

petsc-master 2020-11-24
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  2: #ifndef __MATIMPL_H

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

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

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

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

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

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

227: PETSC_EXTERN MatRootName MatRootNameList;

229: /*
230:    Utility private matrix routines
231: */
232: PETSC_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat,PetscBool,PetscReal,IS*);
233: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat,MatType,MatReuse,Mat*);
234: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat,MatType,MatReuse,Mat*);
235: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat,MatType,MatReuse,Mat*);
236: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat,Mat,MatStructure);
237: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat,Vec,InsertMode);
238: #if defined(PETSC_HAVE_SCALAPACK)
239: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
240: #endif
241: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_Basic(Mat,PetscInt,const PetscInt[],const PetscInt[]);
242: PETSC_INTERN PetscErrorCode MatSetValuesCOO_Basic(Mat,const PetscScalar[],InsertMode);

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

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

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

272: /*
273:   The stash is used to temporarily store inserted matrix values that
274:   belong to another processor. During the assembly phase the stashed
275:   values are moved to the correct processor and
276: */

278: typedef struct _MatStashSpace *PetscMatStashSpace;

280: struct _MatStashSpace {
281:   PetscMatStashSpace next;
282:   PetscScalar        *space_head,*val;
283:   PetscInt           *idx,*idy;
284:   PetscInt           total_space_size;
285:   PetscInt           local_used;
286:   PetscInt           local_remaining;
287: };

289: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt,PetscInt,PetscMatStashSpace *);
290: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt,PetscMatStashSpace *,PetscScalar *,PetscInt *,PetscInt *);
291: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace*);

293: typedef struct {
294:   PetscInt    count;
295: } MatStashHeader;

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

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

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

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

335:   /* The following variables are used for BTS communication */
336:   PetscBool      first_assembly_done;   /* Is the first time matrix assembly done? */
337:   PetscBool      use_status;            /* Use MPI_Status to determine number of items in each message */
338:   PetscMPIInt    nsendranks;
339:   PetscMPIInt    nrecvranks;
340:   PetscMPIInt    *sendranks;
341:   PetscMPIInt    *recvranks;
342:   MatStashHeader *sendhdr,*recvhdr;
343:   MatStashFrame  *sendframes;   /* pointers to the main messages */
344:   MatStashFrame  *recvframes;
345:   MatStashFrame  *recvframe_active;
346:   PetscInt       recvframe_i;     /* index of block within active frame */
347:   PetscMPIInt    recvframe_count; /* Count actually sent for current frame */
348:   PetscInt       recvcount;       /* Number of receives processed so far */
349:   PetscMPIInt    *some_indices;   /* From last call to MPI_Waitsome */
350:   MPI_Status     *some_statuses;  /* Statuses from last call to MPI_Waitsome */
351:   PetscMPIInt    some_count;      /* Number of requests completed in last call to MPI_Waitsome */
352:   PetscMPIInt    some_i;          /* Index of request currently being processed */
353:   MPI_Request    *sendreqs;
354:   MPI_Request    *recvreqs;
355:   PetscSegBuffer segsendblocks;
356:   PetscSegBuffer segrecvframe;
357:   PetscSegBuffer segrecvblocks;
358:   MPI_Datatype   blocktype;
359:   size_t         blocktype_size;
360:   InsertMode     *insertmode;   /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
361: };

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

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

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

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

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

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

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

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

428: typedef struct {
429:   CSRDataStructure(PetscScalar)
430: } PetscCSRDataStructure;

432: struct _p_SplitCSRMat {
433:   PetscInt              cstart,cend,rstart,rend;
434:   PetscCSRDataStructure diag,offdiag;
435:   PetscInt              *colmap;
436:   PetscBool             seq;
437:   PetscMPIInt           rank;
438:   PetscInt              nonzerostate;
439: };

441: struct _p_Mat {
442:   PETSCHEADER(struct _MatOps);
443:   PetscLayout            rmap,cmap;
444:   void                   *data;            /* implementation-specific data */
445:   MatFactorType          factortype;       /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
446:   PetscBool              useordering;      /* factorization using ordering provide to routine (most PETSc implementations) */
447:   PetscBool              assembled;        /* is the matrix assembled? */
448:   PetscBool              was_assembled;    /* new values inserted into assembled mat */
449:   PetscInt               num_ass;          /* number of times matrix has been assembled */
450:   PetscObjectState       nonzerostate;     /* each time new nonzeros locations are introduced into the matrix this is updated */
451:   PetscObjectState       ass_nonzerostate; /* nonzero state at last assembly */
452:   MatInfo                info;             /* matrix information */
453:   InsertMode             insertmode;       /* have values been inserted in matrix or added? */
454:   MatStash               stash,bstash;     /* used for assembling off-proc mat emements */
455:   MatNullSpace           nullsp;           /* null space (operator is singular) */
456:   MatNullSpace           transnullsp;      /* null space of transpose of operator */
457:   MatNullSpace           nearnullsp;       /* near null space to be used by multigrid methods */
458:   PetscInt               congruentlayouts; /* are the rows and columns layouts congruent? */
459:   PetscBool              preallocated;
460:   MatStencilInfo         stencil;          /* information for structured grid */
461:   PetscBool              symmetric,hermitian,structurally_symmetric,spd;
462:   PetscBool              symmetric_set,hermitian_set,structurally_symmetric_set,spd_set; /* if true, then corresponding flag is correct*/
463:   PetscBool              symmetric_eternal;
464:   PetscBool              nooffprocentries,nooffproczerorows;
465:   PetscBool              assembly_subset;  /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
466:   PetscBool              submat_singleis;  /* for efficient PCSetUp_ASM() */
467:   PetscBool              structure_only;
468:   PetscBool              sortedfull;       /* full, sorted rows are inserted */
469: #if defined(PETSC_HAVE_DEVICE)
470:   PetscOffloadMask       offloadmask;      /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
471:   PetscBool              boundtocpu;
472: #endif
473:   void                   *spptr;          /* pointer for special library like SuperLU */
474:   char                   *solvertype;
475:   PetscBool              checksymmetryonassembly,checknullspaceonassembly;
476:   PetscReal              checksymmetrytol;
477:   Mat                    schur;             /* Schur complement matrix */
478:   MatFactorSchurStatus   schur_status;      /* status of the Schur complement matrix */
479:   Mat_Redundant          *redundant;        /* used by MatCreateRedundantMatrix() */
480:   PetscBool              erroriffailure;    /* Generate an error if detected (for example a zero pivot) instead of returning */
481:   MatFactorError         factorerrortype;               /* type of error in factorization */
482:   PetscReal              factorerror_zeropivot_value;   /* If numerical zero pivot was detected this is the computed value */
483:   PetscInt               factorerror_zeropivot_row;     /* Row where zero pivot was detected */
484:   PetscInt               nblocks,*bsizes;   /* support for MatSetVariableBlockSizes() */
485:   char                   *defaultvectype;
486:   Mat_Product            *product;
487: };

489: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat,PetscScalar,Mat,MatStructure);
490: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat,Mat,PetscScalar,Mat,MatStructure);
491: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat,Mat,Mat*);

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

501: /*
502:     Utility for MatZeroRows
503: */
504: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat,PetscInt,const PetscInt*,PetscInt*,PetscInt**);

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


513: /*
514:     Object for partitioning graphs
515: */

517: typedef struct _MatPartitioningOps *MatPartitioningOps;
518: struct _MatPartitioningOps {
519:   PetscErrorCode (*apply)(MatPartitioning,IS*);
520:   PetscErrorCode (*applynd)(MatPartitioning,IS*);
521:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatPartitioning);
522:   PetscErrorCode (*destroy)(MatPartitioning);
523:   PetscErrorCode (*view)(MatPartitioning,PetscViewer);
524:   PetscErrorCode (*improve)(MatPartitioning,IS*);
525: };

527: struct _p_MatPartitioning {
528:   PETSCHEADER(struct _MatPartitioningOps);
529:   Mat         adj;
530:   PetscInt    *vertex_weights;
531:   PetscReal   *part_weights;
532:   PetscInt    n;                                 /* number of partitions */
533:   void        *data;
534:   PetscInt    setupcalled;
535:   PetscBool   use_edge_weights;  /* A flag indicates whether or not to use edge weights */
536: };

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

541: /*
542:     Object for coarsen graphs
543: */
544: typedef struct _MatCoarsenOps *MatCoarsenOps;
545: struct _MatCoarsenOps {
546:   PetscErrorCode (*apply)(MatCoarsen);
547:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatCoarsen);
548:   PetscErrorCode (*destroy)(MatCoarsen);
549:   PetscErrorCode (*view)(MatCoarsen,PetscViewer);
550: };

552: struct _p_MatCoarsen {
553:   PETSCHEADER(struct _MatCoarsenOps);
554:   Mat              graph;
555:   void             *subctx;
556:   /* */
557:   PetscBool        strict_aggs;
558:   IS               perm;
559:   PetscCoarsenData *agg_lists;
560: };

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

566:    Color =   0    1     0    2   |   2      3       0
567:    ---------------------------------------------------
568:             00   01              |          05
569:             10   11              |   14     15               Processor  0
570:                        22    23  |          25
571:                        32    33  |
572:    ===================================================
573:                                  |   44     45     46
574:             50                   |          55               Processor 1
575:                                  |   64            66
576:    ---------------------------------------------------

578:     ncolors = 4;

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

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

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

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

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

609: struct  _p_MatFDColoring{
610:   PETSCHEADER(int);
611:   PetscInt       M,N,m;            /* total rows, columns; local rows */
612:   PetscInt       rstart;           /* first row owned by local processor */
613:   PetscInt       ncolors;          /* number of colors */
614:   PetscInt       *ncolumns;        /* number of local columns for a color */
615:   PetscInt       **columns;        /* lists the local columns of each color (using global column numbering) */
616:   IS             *isa;             /* these are the IS that contain the column values given in columns */
617:   PetscInt       *nrows;           /* number of local rows for each color */
618:   MatEntry       *matentry;        /* holds (row, column, address of value) for Jacobian matrix entry */
619:   MatEntry2      *matentry2;       /* holds (row, address of value) for Jacobian matrix entry */
620:   PetscScalar    *dy;              /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
621:   PetscReal      error_rel;        /* square root of relative error in computing function */
622:   PetscReal      umin;             /* minimum allowable u'dx value */
623:   Vec            w1,w2,w3;         /* work vectors used in computing Jacobian */
624:   PetscBool      fset;             /* indicates that the initial function value F(X) is set */
625:   PetscErrorCode (*f)(void);       /* function that defines Jacobian */
626:   void           *fctx;            /* optional user-defined context for use by the function f */
627:   Vec            vscale;           /* holds FD scaling, i.e. 1/dx for each perturbed column */
628:   PetscInt       currentcolor;     /* color for which function evaluation is being done now */
629:   const char     *htype;           /* "wp" or "ds" */
630:   ISColoringType ctype;            /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
631:   PetscInt       brows,bcols;      /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
632:   PetscBool      setupcalled;      /* true if setup has been called */
633:   PetscBool      viewed;           /* true if the -mat_fd_coloring_view has been triggered already */
634:   void           (*ftn_func_pointer)(void),*ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
635:   PetscObjectId  matid;            /* matrix this object was created with, must always be the same */
636: };

638: typedef struct _MatColoringOps *MatColoringOps;
639: struct _MatColoringOps {
640:   PetscErrorCode (*destroy)(MatColoring);
641:   PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatColoring);
642:   PetscErrorCode (*view)(MatColoring,PetscViewer);
643:   PetscErrorCode (*apply)(MatColoring,ISColoring*);
644:   PetscErrorCode (*weights)(MatColoring,PetscReal**,PetscInt**);
645: };

647: struct _p_MatColoring {
648:   PETSCHEADER(struct _MatColoringOps);
649:   Mat                   mat;
650:   PetscInt              dist;             /* distance of the coloring */
651:   PetscInt              maxcolors;        /* the maximum number of colors returned, maxcolors=1 for MIS */
652:   void                  *data;            /* inner context */
653:   PetscBool             valid;            /* check to see if what is produced is a valid coloring */
654:   MatColoringWeightType weight_type;      /* type of weight computation to be performed */
655:   PetscReal             *user_weights;    /* custom weights and permutation */
656:   PetscInt              *user_lperm;
657:   PetscBool             valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
658: };

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

670:   PetscInt       *colorforrow,*colorforcol;  /* pointer to rows and columns */
671:   PetscInt       *rows;                      /* lists the local rows for each color (using the local row numbering) */
672:   PetscInt       *den2sp;                    /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
673:   PetscInt       *columns;                   /* lists the local columns of each color (using global column numbering) */
674:   PetscInt       brows;                      /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
675:   PetscInt       *lstart;                    /* array used for loop over row blocks of Csparse */
676: };

678: /*
679:    Null space context for preconditioner/operators
680: */
681: struct _p_MatNullSpace {
682:   PETSCHEADER(int);
683:   PetscBool      has_cnst;
684:   PetscInt       n;
685:   Vec*           vecs;
686:   PetscScalar*   alpha;                 /* for projections */
687:   PetscErrorCode (*remove)(MatNullSpace,Vec,void*);  /* for user provided removal function */
688:   void*          rmctx;                 /* context for remove() function */
689: };

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

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

726:   PetscErrorCode (*destroy)(Mat);
727: } Mat_SubSppt;

729: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
730: PETSC_INTERN PetscErrorCode MatShift_Basic(Mat,PetscScalar);
731: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat,PetscInt,PetscInt);

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

739:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
740:     /* force |diag| > zeropivot*rs */
741:     if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
742:     else sctx->shift_amount *= 2.0;
743:     sctx->newshift = PETSC_TRUE;
744:     (sctx->nshift)++;
745:   } else {
746:     sctx->newshift = PETSC_FALSE;
747:   }
748:   return(0);
749: }

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

757:   if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
758:     /* force matfactor to be diagonally dominant */
759:     if (sctx->nshift == sctx->nshift_max) {
760:       sctx->shift_fraction = sctx->shift_hi;
761:     } else {
762:       sctx->shift_lo = sctx->shift_fraction;
763:       sctx->shift_fraction = (sctx->shift_hi+sctx->shift_lo)/2.;
764:     }
765:     sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
766:     sctx->nshift++;
767:     sctx->newshift = PETSC_TRUE;
768:   } else {
769:     sctx->newshift = PETSC_FALSE;
770:   }
771:   return(0);
772: }

774: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_inblocks(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
775: {
776:   PetscReal _zero = info->zeropivot;

779:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
780:     sctx->pv          += info->shiftamount;
781:     sctx->shift_amount = 0.0;
782:     sctx->nshift++;
783:   }
784:   sctx->newshift = PETSC_FALSE;
785:   return(0);
786: }

788: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_none(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
789: {
790:   PetscReal      _zero = info->zeropivot;

794:   sctx->newshift = PETSC_FALSE;
795:   if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
796:     if (!mat->erroriffailure) {
797:       PetscInfo3(mat,"Detected zero pivot in factorization in row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
798:       fact->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
799:       fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
800:       fact->factorerror_zeropivot_row   = row;
801:     } 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);
802:   }
803:   return(0);
804: }

806: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
807: {

811:   if (info->shifttype == (PetscReal) MAT_SHIFT_NONZERO){
812:     MatPivotCheck_nz(mat,info,sctx,row);
813:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_POSITIVE_DEFINITE){
814:     MatPivotCheck_pd(mat,info,sctx,row);
815:   } else if (info->shifttype == (PetscReal) MAT_SHIFT_INBLOCKS){
816:     MatPivotCheck_inblocks(mat,info,sctx,row);
817:   } else {
818:     MatPivotCheck_none(fact,mat,info,sctx,row);
819:   }
820:   return(0);
821: }

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

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

840: /*
841:   Add an index set into a sorted linked list
842:   Input Parameters:
843:     nidx      - number of input indices
844:     indices   - integer array
845:     idx_start - starting index of the list
846:     lnk       - linked list(an integer array) that is created
847:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
848:   output Parameters:
849:     nlnk      - number of newly added indices
850:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
851:     bt        - updated PetscBT (bitarray)
852: */
853: #define PetscLLAdd(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
854: {\
855:   PetscInt _k,_entry,_location,_lnkdata;\
856:   nlnk     = 0;\
857:   _lnkdata = idx_start;\
858:   for (_k=0; _k<nidx; _k++){\
859:     _entry = indices[_k];\
860:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
861:       /* search for insertion location */\
862:       /* start from the beginning if _entry < previous _entry */\
863:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
864:       do {\
865:         _location = _lnkdata;\
866:         _lnkdata  = lnk[_location];\
867:       } while (_entry > _lnkdata);\
868:       /* insertion location is found, add entry into lnk */\
869:       lnk[_location] = _entry;\
870:       lnk[_entry]    = _lnkdata;\
871:       nlnk++;\
872:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
873:     }\
874:   }\
875: }

877: /*
878:   Add a permuted index set into a sorted linked list
879:   Input Parameters:
880:     nidx      - number of input indices
881:     indices   - integer array
882:     perm      - permutation of indices
883:     idx_start - starting index of the list
884:     lnk       - linked list(an integer array) that is created
885:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
886:   output Parameters:
887:     nlnk      - number of newly added indices
888:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
889:     bt        - updated PetscBT (bitarray)
890: */
891: #define PetscLLAddPerm(nidx,indices,perm,idx_start,nlnk,lnk,bt) 0;\
892: {\
893:   PetscInt _k,_entry,_location,_lnkdata;\
894:   nlnk     = 0;\
895:   _lnkdata = idx_start;\
896:   for (_k=0; _k<nidx; _k++){\
897:     _entry = perm[indices[_k]];\
898:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
899:       /* search for insertion location */\
900:       /* start from the beginning if _entry < previous _entry */\
901:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
902:       do {\
903:         _location = _lnkdata;\
904:         _lnkdata  = lnk[_location];\
905:       } while (_entry > _lnkdata);\
906:       /* insertion location is found, add entry into lnk */\
907:       lnk[_location] = _entry;\
908:       lnk[_entry]    = _lnkdata;\
909:       nlnk++;\
910:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
911:     }\
912:   }\
913: }

915: /*
916:   Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata  = idx_start;'
917:   Input Parameters:
918:     nidx      - number of input indices
919:     indices   - sorted integer array
920:     idx_start - starting index of the list
921:     lnk       - linked list(an integer array) that is created
922:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
923:   output Parameters:
924:     nlnk      - number of newly added indices
925:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
926:     bt        - updated PetscBT (bitarray)
927: */
928: #define PetscLLAddSorted(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
929: {\
930:   PetscInt _k,_entry,_location,_lnkdata;\
931:   nlnk      = 0;\
932:   _lnkdata  = idx_start;\
933:   for (_k=0; _k<nidx; _k++){\
934:     _entry = indices[_k];\
935:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
936:       /* search for insertion location */\
937:       do {\
938:         _location = _lnkdata;\
939:         _lnkdata  = lnk[_location];\
940:       } while (_entry > _lnkdata);\
941:       /* insertion location is found, add entry into lnk */\
942:       lnk[_location] = _entry;\
943:       lnk[_entry]    = _lnkdata;\
944:       nlnk++;\
945:       _lnkdata = _entry; /* next search starts from here */\
946:     }\
947:   }\
948: }

950: #define PetscLLAddSorted_new(nidx,indices,idx_start,lnk_empty,nlnk,lnk,bt) 0; \
951: {\
952:   PetscInt _k,_entry,_location,_lnkdata;\
953:   if (lnk_empty){\
954:     _lnkdata  = idx_start;                      \
955:     for (_k=0; _k<nidx; _k++){                  \
956:       _entry = indices[_k];                             \
957:       PetscBTSet(bt,_entry);  /* mark the new entry */          \
958:           _location = _lnkdata;                                 \
959:           _lnkdata  = lnk[_location];                           \
960:         /* insertion location is found, add entry into lnk */   \
961:         lnk[_location] = _entry;                                \
962:         lnk[_entry]    = _lnkdata;                              \
963:         _lnkdata = _entry; /* next search starts from here */   \
964:     }                                                           \
965:     /*\
966:     lnk[indices[nidx-1]] = lnk[idx_start];\
967:     lnk[idx_start]       = indices[0];\
968:     PetscBTSet(bt,indices[0]);  \
969:     for (_k=1; _k<nidx; _k++){                  \
970:       PetscBTSet(bt,indices[_k]);                                          \
971:       lnk[indices[_k-1]] = indices[_k];                                  \
972:     }                                                           \
973:      */\
974:     nlnk      = nidx;\
975:     lnk_empty = PETSC_FALSE;\
976:   } else {\
977:     nlnk      = 0;                              \
978:     _lnkdata  = idx_start;                      \
979:     for (_k=0; _k<nidx; _k++){                  \
980:       _entry = indices[_k];                             \
981:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */       \
982:         /* search for insertion location */                     \
983:         do {                                                    \
984:           _location = _lnkdata;                                 \
985:           _lnkdata  = lnk[_location];                           \
986:         } while (_entry > _lnkdata);                            \
987:         /* insertion location is found, add entry into lnk */   \
988:         lnk[_location] = _entry;                                \
989:         lnk[_entry]    = _lnkdata;                              \
990:         nlnk++;                                                 \
991:         _lnkdata = _entry; /* next search starts from here */   \
992:       }                                                         \
993:     }                                                           \
994:   }                                                             \
995: }

997: /*
998:   Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
999:   Same as PetscLLAddSorted() with an additional operation:
1000:        count the number of input indices that are no larger than 'diag'
1001:   Input Parameters:
1002:     indices   - sorted integer array
1003:     idx_start - starting index of the list, index of pivot row
1004:     lnk       - linked list(an integer array) that is created
1005:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1006:     diag      - index of the active row in LUFactorSymbolic
1007:     nzbd      - number of input indices with indices <= idx_start
1008:     im        - im[idx_start] is initialized as num of nonzero entries in row=idx_start
1009:   output Parameters:
1010:     nlnk      - number of newly added indices
1011:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from indices
1012:     bt        - updated PetscBT (bitarray)
1013:     im        - im[idx_start]: unchanged if diag is not an entry
1014:                              : num of entries with indices <= diag if diag is an entry
1015: */
1016: #define PetscLLAddSortedLU(indices,idx_start,nlnk,lnk,bt,diag,nzbd,im) 0;\
1017: {\
1018:   PetscInt _k,_entry,_location,_lnkdata,_nidx;\
1019:   nlnk     = 0;\
1020:   _lnkdata = idx_start;\
1021:   _nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */\
1022:   for (_k=0; _k<_nidx; _k++){\
1023:     _entry = indices[_k];\
1024:     nzbd++;\
1025:     if (_entry== diag) im[idx_start] = nzbd;\
1026:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1027:       /* search for insertion location */\
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:       nlnk++;\
1036:       _lnkdata = _entry; /* next search starts from here */\
1037:     }\
1038:   }\
1039: }

1041: /*
1042:   Copy data on the list into an array, then initialize the list
1043:   Input Parameters:
1044:     idx_start - starting index of the list
1045:     lnk_max   - max value of lnk indicating the end of the list
1046:     nlnk      - number of data on the list to be copied
1047:     lnk       - linked list
1048:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1049:   output Parameters:
1050:     indices   - array that contains the copied data
1051:     lnk       - linked list that is cleaned and initialize
1052:     bt        - PetscBT (bitarray) with all bits set to false
1053: */
1054: #define PetscLLClean(idx_start,lnk_max,nlnk,lnk,indices,bt) 0;\
1055: {\
1056:   PetscInt _j,_idx=idx_start;\
1057:   for (_j=0; _j<nlnk; _j++){\
1058:     _idx = lnk[_idx];\
1059:     indices[_j] = _idx;\
1060:     PetscBTClear(bt,_idx);\
1061:   }\
1062:   lnk[idx_start] = lnk_max;\
1063: }
1064: /*
1065:   Free memories used by the list
1066: */
1067: #define PetscLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

1069: /* Routines below are used for incomplete matrix factorization */
1070: /*
1071:   Create and initialize a linked list and its levels
1072:   Input Parameters:
1073:     idx_start - starting index of the list
1074:     lnk_max   - max value of lnk indicating the end of the list
1075:     nlnk      - max length of the list
1076:   Output Parameters:
1077:     lnk       - list initialized
1078:     lnk_lvl   - array of size nlnk for storing levels of lnk
1079:     bt        - PetscBT (bitarray) with all bits set to false
1080: */
1081: #define PetscIncompleteLLCreate(idx_start,lnk_max,nlnk,lnk,lnk_lvl,bt)\
1082:   (PetscIntMultError(2,nlnk,NULL) || PetscMalloc1(2*nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,lnk_lvl = lnk + nlnk,0))

1084: /*
1085:   Initialize a sorted linked list used for ILU and ICC
1086:   Input Parameters:
1087:     nidx      - number of input idx
1088:     idx       - integer array used for storing column indices
1089:     idx_start - starting index of the list
1090:     perm      - indices of an IS
1091:     lnk       - linked list(an integer array) that is created
1092:     lnklvl    - levels of lnk
1093:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1094:   output Parameters:
1095:     nlnk     - number of newly added idx
1096:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1097:     lnklvl   - levels of lnk
1098:     bt       - updated PetscBT (bitarray)
1099: */
1100: #define PetscIncompleteLLInit(nidx,idx,idx_start,perm,nlnk,lnk,lnklvl,bt) 0;\
1101: {\
1102:   PetscInt _k,_entry,_location,_lnkdata;\
1103:   nlnk     = 0;\
1104:   _lnkdata = idx_start;\
1105:   for (_k=0; _k<nidx; _k++){\
1106:     _entry = perm[idx[_k]];\
1107:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1108:       /* search for insertion location */\
1109:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
1110:       do {\
1111:         _location = _lnkdata;\
1112:         _lnkdata  = lnk[_location];\
1113:       } while (_entry > _lnkdata);\
1114:       /* insertion location is found, add entry into lnk */\
1115:       lnk[_location]  = _entry;\
1116:       lnk[_entry]     = _lnkdata;\
1117:       lnklvl[_entry] = 0;\
1118:       nlnk++;\
1119:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1120:     }\
1121:   }\
1122: }

1124: /*
1125:   Add a SORTED index set into a sorted linked list for ILU
1126:   Input Parameters:
1127:     nidx      - number of input indices
1128:     idx       - sorted integer array used for storing column indices
1129:     level     - level of fill, e.g., ICC(level)
1130:     idxlvl    - level of idx
1131:     idx_start - starting index of the list
1132:     lnk       - linked list(an integer array) that is created
1133:     lnklvl    - levels of lnk
1134:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1135:     prow      - the row number of idx
1136:   output Parameters:
1137:     nlnk     - number of newly added idx
1138:     lnk      - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1139:     lnklvl   - levels of lnk
1140:     bt       - updated PetscBT (bitarray)

1142:   Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1143:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1144: */
1145: #define PetscILULLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,lnklvl_prow) 0;\
1146: {\
1147:   PetscInt _k,_entry,_location,_lnkdata,_incrlev,_lnklvl_prow=lnklvl[prow];\
1148:   nlnk     = 0;\
1149:   _lnkdata = idx_start;\
1150:   for (_k=0; _k<nidx; _k++){\
1151:     _incrlev = idxlvl[_k] + _lnklvl_prow + 1;\
1152:     if (_incrlev > level) continue;\
1153:     _entry = idx[_k];\
1154:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1155:       /* search for insertion location */\
1156:       do {\
1157:         _location = _lnkdata;\
1158:         _lnkdata  = lnk[_location];\
1159:       } while (_entry > _lnkdata);\
1160:       /* insertion location is found, add entry into lnk */\
1161:       lnk[_location]  = _entry;\
1162:       lnk[_entry]     = _lnkdata;\
1163:       lnklvl[_entry] = _incrlev;\
1164:       nlnk++;\
1165:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1166:     } else { /* existing entry: update lnklvl */\
1167:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1168:     }\
1169:   }\
1170: }

1172: /*
1173:   Add a index set into a sorted linked list
1174:   Input Parameters:
1175:     nidx      - number of input idx
1176:     idx   - integer array used for storing column indices
1177:     level     - level of fill, e.g., ICC(level)
1178:     idxlvl - level of idx
1179:     idx_start - starting index of the list
1180:     lnk       - linked list(an integer array) that is created
1181:     lnklvl   - levels of lnk
1182:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1183:   output Parameters:
1184:     nlnk      - number of newly added idx
1185:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1186:     lnklvl   - levels of lnk
1187:     bt        - updated PetscBT (bitarray)
1188: */
1189: #define PetscIncompleteLLAdd(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1190: {\
1191:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1192:   nlnk     = 0;\
1193:   _lnkdata = idx_start;\
1194:   for (_k=0; _k<nidx; _k++){\
1195:     _incrlev = idxlvl[_k] + 1;\
1196:     if (_incrlev > level) continue;\
1197:     _entry = idx[_k];\
1198:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1199:       /* search for insertion location */\
1200:       if (_k && _entry < _lnkdata) _lnkdata  = idx_start;\
1201:       do {\
1202:         _location = _lnkdata;\
1203:         _lnkdata  = lnk[_location];\
1204:       } while (_entry > _lnkdata);\
1205:       /* insertion location is found, add entry into lnk */\
1206:       lnk[_location]  = _entry;\
1207:       lnk[_entry]     = _lnkdata;\
1208:       lnklvl[_entry] = _incrlev;\
1209:       nlnk++;\
1210:       _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1211:     } else { /* existing entry: update lnklvl */\
1212:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1213:     }\
1214:   }\
1215: }

1217: /*
1218:   Add a SORTED index set into a sorted linked list
1219:   Input Parameters:
1220:     nidx      - number of input indices
1221:     idx   - sorted integer array used for storing column indices
1222:     level     - level of fill, e.g., ICC(level)
1223:     idxlvl - level of idx
1224:     idx_start - starting index of the list
1225:     lnk       - linked list(an integer array) that is created
1226:     lnklvl    - levels of lnk
1227:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1228:   output Parameters:
1229:     nlnk      - number of newly added idx
1230:     lnk       - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1231:     lnklvl    - levels of lnk
1232:     bt        - updated PetscBT (bitarray)
1233: */
1234: #define PetscIncompleteLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1235: {\
1236:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1237:   nlnk = 0;\
1238:   _lnkdata = idx_start;\
1239:   for (_k=0; _k<nidx; _k++){\
1240:     _incrlev = idxlvl[_k] + 1;\
1241:     if (_incrlev > level) continue;\
1242:     _entry = idx[_k];\
1243:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1244:       /* search for insertion location */\
1245:       do {\
1246:         _location = _lnkdata;\
1247:         _lnkdata  = lnk[_location];\
1248:       } while (_entry > _lnkdata);\
1249:       /* insertion location is found, add entry into lnk */\
1250:       lnk[_location] = _entry;\
1251:       lnk[_entry]    = _lnkdata;\
1252:       lnklvl[_entry] = _incrlev;\
1253:       nlnk++;\
1254:       _lnkdata = _entry; /* next search starts from here */\
1255:     } else { /* existing entry: update lnklvl */\
1256:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1257:     }\
1258:   }\
1259: }

1261: /*
1262:   Add a SORTED index set into a sorted linked list for ICC
1263:   Input Parameters:
1264:     nidx      - number of input indices
1265:     idx       - sorted integer array used for storing column indices
1266:     level     - level of fill, e.g., ICC(level)
1267:     idxlvl    - level of idx
1268:     idx_start - starting index of the list
1269:     lnk       - linked list(an integer array) that is created
1270:     lnklvl    - levels of lnk
1271:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1272:     idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1273:   output Parameters:
1274:     nlnk   - number of newly added indices
1275:     lnk    - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1276:     lnklvl - levels of lnk
1277:     bt     - updated PetscBT (bitarray)
1278:   Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1279:         where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1280: */
1281: #define PetscICCLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,idxlvl_prow) 0;\
1282: {\
1283:   PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1284:   nlnk = 0;\
1285:   _lnkdata = idx_start;\
1286:   for (_k=0; _k<nidx; _k++){\
1287:     _incrlev = idxlvl[_k] + idxlvl_prow + 1;\
1288:     if (_incrlev > level) continue;\
1289:     _entry = idx[_k];\
1290:     if (!PetscBTLookupSet(bt,_entry)){  /* new entry */\
1291:       /* search for insertion location */\
1292:       do {\
1293:         _location = _lnkdata;\
1294:         _lnkdata  = lnk[_location];\
1295:       } while (_entry > _lnkdata);\
1296:       /* insertion location is found, add entry into lnk */\
1297:       lnk[_location] = _entry;\
1298:       lnk[_entry]    = _lnkdata;\
1299:       lnklvl[_entry] = _incrlev;\
1300:       nlnk++;\
1301:       _lnkdata = _entry; /* next search starts from here */\
1302:     } else { /* existing entry: update lnklvl */\
1303:       if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1304:     }\
1305:   }\
1306: }

1308: /*
1309:   Copy data on the list into an array, then initialize the list
1310:   Input Parameters:
1311:     idx_start - starting index of the list
1312:     lnk_max   - max value of lnk indicating the end of the list
1313:     nlnk      - number of data on the list to be copied
1314:     lnk       - linked list
1315:     lnklvl    - level of lnk
1316:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1317:   output Parameters:
1318:     indices - array that contains the copied data
1319:     lnk     - linked list that is cleaned and initialize
1320:     lnklvl  - level of lnk that is reinitialized
1321:     bt      - PetscBT (bitarray) with all bits set to false
1322: */
1323: #define PetscIncompleteLLClean(idx_start,lnk_max,nlnk,lnk,lnklvl,indices,indiceslvl,bt) 0;\
1324: do {\
1325:   PetscInt _j,_idx=idx_start;\
1326:   for (_j=0; _j<nlnk; _j++){\
1327:     _idx = lnk[_idx];\
1328:     *(indices+_j) = _idx;\
1329:     *(indiceslvl+_j) = lnklvl[_idx];\
1330:     lnklvl[_idx] = -1;\
1331:     PetscBTClear(bt,_idx);\
1332:   }\
1333:   lnk[idx_start] = lnk_max;\
1334: } while (0)
1335: /*
1336:   Free memories used by the list
1337: */
1338: #define PetscIncompleteLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))

1340: #define MatCheckSameLocalSize(A,ar1,B,ar2) do { \
1342:   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)

1344: #define MatCheckSameSize(A,ar1,B,ar2) do { \
1345:   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);\
1346:   MatCheckSameLocalSize(A,ar1,B,ar2);} while (0)

1348: #define VecCheckMatCompatible(M,x,ar1,b,ar2) do { \
1349:   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); \
1350:   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)

1352: /* -------------------------------------------------------------------------------------------------------*/
1353: #include <petscbt.h>
1354: /*
1355:   Create and initialize a condensed linked list -
1356:     same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1357:     Barry suggested this approach (Dec. 6, 2011):
1358:       I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1359:       (it may be faster than the O(N) even sequentially due to less crazy memory access).

1361:       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
1362:       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
1363:       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
1364:       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.
1365:       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
1366:       to each other so memory access is much better than using the big array.

1368:   Example:
1369:      nlnk_max=5, lnk_max=36:
1370:      Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1371:      here, head_node has index 2 with value lnk[2]=lnk_max=36,
1372:            0-th entry is used to store the number of entries in the list,
1373:      The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.

1375:      Now adding a sorted set {2,4}, the list becomes
1376:      [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1377:      represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.

1379:      Then adding a sorted set {0,3,35}, the list
1380:      [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1381:      represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.

1383:   Input Parameters:
1384:     nlnk_max  - max length of the list
1385:     lnk_max   - max value of the entries
1386:   Output Parameters:
1387:     lnk       - list created and initialized
1388:     bt        - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1389: */
1390: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max,PetscInt lnk_max,PetscInt **lnk,PetscBT *bt)
1391: {
1393:   PetscInt       *llnk,lsize = 0;

1396:   PetscIntMultError(2,nlnk_max+2,&lsize);
1397:   PetscMalloc1(lsize,lnk);
1398:   PetscBTCreate(lnk_max,bt);
1399:   llnk = *lnk;
1400:   llnk[0] = 0;         /* number of entries on the list */
1401:   llnk[2] = lnk_max;   /* value in the head node */
1402:   llnk[3] = 2;         /* next for the head node */
1403:   return(0);
1404: }

1406: /*
1407:   Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1408:   Input Parameters:
1409:     nidx      - number of input indices
1410:     indices   - sorted integer array
1411:     lnk       - condensed linked list(an integer array) that is created
1412:     bt        - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1413:   output Parameters:
1414:     lnk       - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1415:     bt        - updated PetscBT (bitarray)
1416: */
1417: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx,const PetscInt indices[],PetscInt lnk[],PetscBT bt)
1418: {
1419:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;

1422:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
1423:   _location = 2; /* head */
1424:     for (_k=0; _k<nidx; _k++){
1425:       _entry = indices[_k];
1426:       if (!PetscBTLookupSet(bt,_entry)){  /* new entry */
1427:         /* search for insertion location */
1428:         do {
1429:           _next     = _location + 1; /* link from previous node to next node */
1430:           _location = lnk[_next];    /* idx of next node */
1431:           _lnkdata  = lnk[_location];/* value of next node */
1432:         } while (_entry > _lnkdata);
1433:         /* insertion location is found, add entry into lnk */
1434:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
1435:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
1436:         lnk[_newnode]   = _entry;        /* set value of the new node */
1437:         lnk[_newnode+1] = _location;     /* connect new node to next node */
1438:         _location       = _newnode;      /* next search starts from the new node */
1439:         _nlnk++;
1440:       }   \
1441:     }\
1442:   lnk[0]   = _nlnk;   /* number of entries in the list */
1443:   return(0);
1444: }

1446: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max,PetscInt nidx,PetscInt *indices,PetscInt lnk[],PetscBT bt)
1447: {
1449:   PetscInt       _k,_next,_nlnk;

1452:   _next = lnk[3];       /* head node */
1453:   _nlnk = lnk[0];       /* num of entries on the list */
1454:   for (_k=0; _k<_nlnk; _k++){
1455:     indices[_k] = lnk[_next];
1456:     _next       = lnk[_next + 1];
1457:     PetscBTClear(bt,indices[_k]);
1458:   }
1459:   lnk[0] = 0;          /* num of entries on the list */
1460:   lnk[2] = lnk_max;    /* initialize head node */
1461:   lnk[3] = 2;          /* head node */
1462:   return(0);
1463: }

1465: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1466: {
1468:   PetscInt       k;

1471:   PetscPrintf(PETSC_COMM_SELF,"LLCondensed of size %D, (val,  next)\n",lnk[0]);
1472:   for (k=2; k< lnk[0]+2; k++){
1473:     PetscPrintf(PETSC_COMM_SELF," %D: (%D, %D)\n",2*k,lnk[2*k],lnk[2*k+1]);
1474:   }
1475:   return(0);
1476: }

1478: /*
1479:   Free memories used by the list
1480: */
1481: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk,PetscBT bt)
1482: {

1486:   PetscFree(lnk);
1487:   PetscBTDestroy(&bt);
1488:   return(0);
1489: }

1491: /* -------------------------------------------------------------------------------------------------------*/
1492: /*
1493:  Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1494:   Input Parameters:
1495:     nlnk_max  - max length of the list
1496:   Output Parameters:
1497:     lnk       - list created and initialized
1498: */
1499: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1500: {
1502:   PetscInt       *llnk,lsize = 0;

1505:   PetscIntMultError(2,nlnk_max+2,&lsize);
1506:   PetscMalloc1(lsize,lnk);
1507:   llnk = *lnk;
1508:   llnk[0] = 0;               /* number of entries on the list */
1509:   llnk[2] = PETSC_MAX_INT;   /* value in the head node */
1510:   llnk[3] = 2;               /* next for the head node */
1511:   return(0);
1512: }

1514: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1515: {
1517:   PetscInt       lsize = 0;

1520:   PetscIntMultError(2,nlnk_max+2,&lsize);
1521:   PetscRealloc(lsize*sizeof(PetscInt),lnk);
1522:   return(0);
1523: }

1525: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1526: {
1527:   PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
1528:   _nlnk     = lnk[0]; /* num of entries on the input lnk */
1529:   _location = 2; /* head */ \
1530:     for (_k=0; _k<nidx; _k++){
1531:       _entry = indices[_k];
1532:       /* search for insertion location */
1533:       do {
1534:         _next     = _location + 1; /* link from previous node to next node */
1535:         _location = lnk[_next];    /* idx of next node */
1536:         _lnkdata  = lnk[_location];/* value of next node */
1537:       } while (_entry > _lnkdata);
1538:       if (_entry < _lnkdata) {
1539:         /* insertion location is found, add entry into lnk */
1540:         _newnode        = 2*(_nlnk+2);   /* index for this new node */
1541:         lnk[_next]      = _newnode;      /* connect previous node to the new node */
1542:         lnk[_newnode]   = _entry;        /* set value of the new node */
1543:         lnk[_newnode+1] = _location;     /* connect new node to next node */
1544:         _location       = _newnode;      /* next search starts from the new node */
1545:         _nlnk++;
1546:       }
1547:     }
1548:   lnk[0]   = _nlnk;   /* number of entries in the list */
1549:   return 0;
1550: }

1552: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_Scalable(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1553: {
1554:   PetscInt _k,_next,_nlnk;
1555:   _next = lnk[3];       /* head node */
1556:   _nlnk = lnk[0];
1557:   for (_k=0; _k<_nlnk; _k++){
1558:     indices[_k] = lnk[_next];
1559:     _next       = lnk[_next + 1];
1560:   }
1561:   lnk[0] = 0;          /* num of entries on the list */
1562:   lnk[3] = 2;          /* head node */
1563:   return 0;
1564: }

1566: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1567: {
1568:   return PetscFree(lnk);
1569: }

1571: /* -------------------------------------------------------------------------------------------------------*/
1572: /*
1573:       lnk[0]   number of links
1574:       lnk[1]   number of entries
1575:       lnk[3n]  value
1576:       lnk[3n+1] len
1577:       lnk[3n+2] link to next value

1579:       The next three are always the first link

1581:       lnk[3]    PETSC_MIN_INT+1
1582:       lnk[4]    1
1583:       lnk[5]    link to first real entry

1585:       The next three are always the last link

1587:       lnk[6]    PETSC_MAX_INT - 1
1588:       lnk[7]    1
1589:       lnk[8]    next valid link (this is the same as lnk[0] but without the decreases)
1590: */

1592: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max,PetscInt **lnk)
1593: {
1595:   PetscInt       *llnk,lsize = 0;

1598:   PetscIntMultError(3,nlnk_max+3,&lsize);
1599:   PetscMalloc1(lsize,lnk);
1600:   llnk = *lnk;
1601:   llnk[0] = 0;   /* nlnk: number of entries on the list */
1602:   llnk[1] = 0;          /* number of integer entries represented in list */
1603:   llnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
1604:   llnk[4] = 1;           /* count for the first node */
1605:   llnk[5] = 6;         /* next for the first node */
1606:   llnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
1607:   llnk[7] = 1;           /* count for the last node */
1608:   llnk[8] = 0;         /* next valid node to be used */
1609:   return(0);
1610: }

1612: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1613: {
1614:   PetscInt k,entry,prev,next;
1615:   prev      = 3;      /* first value */
1616:   next      = lnk[prev+2];
1617:   for (k=0; k<nidx; k++){
1618:     entry = indices[k];
1619:     /* search for insertion location */
1620:     while (entry >= lnk[next]) {
1621:       prev = next;
1622:       next = lnk[next+2];
1623:     }
1624:     /* entry is in range of previous list */
1625:     if (entry < lnk[prev]+lnk[prev+1]) continue;
1626:     lnk[1]++;
1627:     /* entry is right after previous list */
1628:     if (entry == lnk[prev]+lnk[prev+1]) {
1629:       lnk[prev+1]++;
1630:       if (lnk[next] == entry+1) { /* combine two contiguous strings */
1631:         lnk[prev+1] += lnk[next+1];
1632:         lnk[prev+2]  = lnk[next+2];
1633:         next         = lnk[next+2];
1634:         lnk[0]--;
1635:       }
1636:       continue;
1637:     }
1638:     /* entry is right before next list */
1639:     if (entry == lnk[next]-1) {
1640:       lnk[next]--;
1641:       lnk[next+1]++;
1642:       prev = next;
1643:       next = lnk[prev+2];
1644:       continue;
1645:     }
1646:     /*  add entry into lnk */
1647:     lnk[prev+2]    = 3*((lnk[8]++)+3);      /* connect previous node to the new node */
1648:     prev           = lnk[prev+2];
1649:     lnk[prev]      = entry;        /* set value of the new node */
1650:     lnk[prev+1]    = 1;             /* number of values in contiguous string is one to start */
1651:     lnk[prev+2]    = next;          /* connect new node to next node */
1652:     lnk[0]++;
1653:   }
1654:   return 0;
1655: }

1657: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_fast(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1658: {
1659:   PetscInt _k,_next,_nlnk,cnt,j;
1660:   _next = lnk[5];       /* first node */
1661:   _nlnk = lnk[0];
1662:   cnt   = 0;
1663:   for (_k=0; _k<_nlnk; _k++){
1664:     for (j=0; j<lnk[_next+1]; j++) {
1665:       indices[cnt++] = lnk[_next] + j;
1666:     }
1667:     _next       = lnk[_next + 2];
1668:   }
1669:   lnk[0] = 0;   /* nlnk: number of links */
1670:   lnk[1] = 0;          /* number of integer entries represented in list */
1671:   lnk[3] = PETSC_MIN_INT+1;   /* value in the first node */
1672:   lnk[4] = 1;           /* count for the first node */
1673:   lnk[5] = 6;         /* next for the first node */
1674:   lnk[6] = PETSC_MAX_INT-1;   /* value in the last node */
1675:   lnk[7] = 1;           /* count for the last node */
1676:   lnk[8] = 0;         /* next valid location to make link */
1677:   return 0;
1678: }

1680: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView_fast(PetscInt *lnk)
1681: {
1682:   PetscInt k,next,nlnk;
1683:   next = lnk[5];       /* first node */
1684:   nlnk = lnk[0];
1685:   for (k=0; k<nlnk; k++){
1686: #if 0                           /* Debugging code */
1687:     printf("%d value %d len %d next %d\n",next,lnk[next],lnk[next+1],lnk[next+2]);
1688: #endif
1689:     next = lnk[next + 2];
1690:   }
1691:   return 0;
1692: }

1694: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1695: {
1696:   return PetscFree(lnk);
1697: }

1699: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
1700: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,void*);

1702: PETSC_EXTERN PetscLogEvent MAT_Mult;
1703: PETSC_EXTERN PetscLogEvent MAT_MultMatrixFree;
1704: PETSC_EXTERN PetscLogEvent MAT_Mults;
1705: PETSC_EXTERN PetscLogEvent MAT_MultConstrained;
1706: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1707: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1708: PETSC_EXTERN PetscLogEvent MAT_MultTransposeConstrained;
1709: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1710: PETSC_EXTERN PetscLogEvent MAT_Solve;
1711: PETSC_EXTERN PetscLogEvent MAT_Solves;
1712: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1713: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1714: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1715: PETSC_EXTERN PetscLogEvent MAT_SOR;
1716: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1717: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1718: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1719: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1720: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1721: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1722: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1723: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1724: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1725: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1726: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1727: PETSC_EXTERN PetscLogEvent MAT_Copy;
1728: PETSC_EXTERN PetscLogEvent MAT_Convert;
1729: PETSC_EXTERN PetscLogEvent MAT_Scale;
1730: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1731: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1732: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1733: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1734: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1735: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1736: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1737: PETSC_EXTERN PetscLogEvent MAT_GetColoring;
1738: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1739: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1740: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1741: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1742: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1743: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1744: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1745: PETSC_EXTERN PetscLogEvent MAT_Load;
1746: PETSC_EXTERN PetscLogEvent MAT_View;
1747: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1748: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1749: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1750: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1751: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1752: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1753: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1754: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1755: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1756: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1757: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1758: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1759: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1760: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1761: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1762: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1763: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1764: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1765: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1766: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1767: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1768: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1769: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1770: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1771: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1772: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1773: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1774: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1775: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1776: PETSC_EXTERN PetscLogEvent MAT_Applypapt;
1777: PETSC_EXTERN PetscLogEvent MAT_Applypapt_symbolic;
1778: PETSC_EXTERN PetscLogEvent MAT_Applypapt_numeric;
1779: PETSC_EXTERN PetscLogEvent MAT_Getsymtranspose;
1780: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1781: PETSC_EXTERN PetscLogEvent MAT_GetSequentialNonzeroStructure;
1782: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1783: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1784: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1785: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyFromGPU;
1786: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
1787: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEPreallCOO;
1788: PETSC_EXTERN PetscLogEvent MAT_CUSPARSESetVCOO;
1789: PETSC_EXTERN PetscLogEvent MAT_CUSPARSESolveAnalysis;
1790: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1791: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1792: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1793: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1794: PETSC_EXTERN PetscLogEvent MAT_Merge;
1795: PETSC_EXTERN PetscLogEvent MAT_Residual;
1796: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1797: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1798: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1799: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1800: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1801: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1802: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1803: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1804: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;

1806: #endif