Actual source code: matimpl.h
1: #pragma once
3: #include <petscmat.h>
4: #include <petscmatcoarsen.h>
5: #include <petsc/private/petscimpl.h>
7: PETSC_EXTERN PetscBool MatRegisterAllCalled;
8: PETSC_EXTERN PetscBool MatSeqAIJRegisterAllCalled;
9: PETSC_EXTERN PetscBool MatOrderingRegisterAllCalled;
10: PETSC_EXTERN PetscBool MatColoringRegisterAllCalled;
11: PETSC_EXTERN PetscBool MatPartitioningRegisterAllCalled;
12: PETSC_EXTERN PetscBool MatCoarsenRegisterAllCalled;
13: PETSC_EXTERN PetscErrorCode MatRegisterAll(void);
14: PETSC_EXTERN PetscErrorCode MatOrderingRegisterAll(void);
15: PETSC_EXTERN PetscErrorCode MatColoringRegisterAll(void);
16: PETSC_EXTERN PetscErrorCode MatPartitioningRegisterAll(void);
17: PETSC_EXTERN PetscErrorCode MatCoarsenRegisterAll(void);
18: PETSC_EXTERN PetscErrorCode MatSeqAIJRegisterAll(void);
20: /* Gets the root type of the input matrix's type (e.g., MATAIJ for MATSEQAIJ) */
21: PETSC_EXTERN PetscErrorCode MatGetRootType_Private(Mat, MatType *);
23: /* Gets the MPI type corresponding to the input matrix's type (e.g., MATMPIAIJ for MATSEQAIJ) */
24: PETSC_EXTERN PetscErrorCode MatGetMPIMatType_Private(Mat, MatType *);
26: /*
27: This file defines the parts of the matrix data structure that are
28: shared by all matrix types.
29: */
31: /*
32: If you add entries here also add them to the MATOP enum
33: in include/petscmat.h and src/mat/f90-mod/petscmat.h
34: */
35: typedef struct _MatOps *MatOps;
36: struct _MatOps {
37: /* 0*/
38: PetscErrorCode (*setvalues)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
39: PetscErrorCode (*getrow)(Mat, PetscInt, PetscInt *, PetscInt *[], PetscScalar *[]);
40: PetscErrorCode (*restorerow)(Mat, PetscInt, PetscInt *, PetscInt *[], PetscScalar *[]);
41: PetscErrorCode (*mult)(Mat, Vec, Vec);
42: PetscErrorCode (*multadd)(Mat, Vec, Vec, Vec);
43: /* 5*/
44: PetscErrorCode (*multtranspose)(Mat, Vec, Vec);
45: PetscErrorCode (*multtransposeadd)(Mat, Vec, Vec, Vec);
46: PetscErrorCode (*solve)(Mat, Vec, Vec);
47: PetscErrorCode (*solveadd)(Mat, Vec, Vec, Vec);
48: PetscErrorCode (*solvetranspose)(Mat, Vec, Vec);
49: /*10*/
50: PetscErrorCode (*solvetransposeadd)(Mat, Vec, Vec, Vec);
51: PetscErrorCode (*lufactor)(Mat, IS, IS, const MatFactorInfo *);
52: PetscErrorCode (*choleskyfactor)(Mat, IS, const MatFactorInfo *);
53: PetscErrorCode (*sor)(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec);
54: PetscErrorCode (*transpose)(Mat, MatReuse, Mat *);
55: /*15*/
56: PetscErrorCode (*getinfo)(Mat, MatInfoType, MatInfo *);
57: PetscErrorCode (*equal)(Mat, Mat, PetscBool *);
58: PetscErrorCode (*getdiagonal)(Mat, Vec);
59: PetscErrorCode (*diagonalscale)(Mat, Vec, Vec);
60: PetscErrorCode (*norm)(Mat, NormType, PetscReal *);
61: /*20*/
62: PetscErrorCode (*assemblybegin)(Mat, MatAssemblyType);
63: PetscErrorCode (*assemblyend)(Mat, MatAssemblyType);
64: PetscErrorCode (*setoption)(Mat, MatOption, PetscBool);
65: PetscErrorCode (*zeroentries)(Mat);
66: /*24*/
67: PetscErrorCode (*zerorows)(Mat, PetscInt, const PetscInt[], PetscScalar, Vec, Vec);
68: PetscErrorCode (*lufactorsymbolic)(Mat, Mat, IS, IS, const MatFactorInfo *);
69: PetscErrorCode (*lufactornumeric)(Mat, Mat, const MatFactorInfo *);
70: PetscErrorCode (*choleskyfactorsymbolic)(Mat, Mat, IS, const MatFactorInfo *);
71: PetscErrorCode (*choleskyfactornumeric)(Mat, Mat, const MatFactorInfo *);
72: /*29*/
73: PetscErrorCode (*setup)(Mat);
74: PetscErrorCode (*ilufactorsymbolic)(Mat, Mat, IS, IS, const MatFactorInfo *);
75: PetscErrorCode (*iccfactorsymbolic)(Mat, Mat, IS, const MatFactorInfo *);
76: PetscErrorCode (*getdiagonalblock)(Mat, Mat *);
77: PetscErrorCode (*setinf)(Mat);
78: /*34*/
79: PetscErrorCode (*duplicate)(Mat, MatDuplicateOption, Mat *);
80: PetscErrorCode (*forwardsolve)(Mat, Vec, Vec);
81: PetscErrorCode (*backwardsolve)(Mat, Vec, Vec);
82: PetscErrorCode (*ilufactor)(Mat, IS, IS, const MatFactorInfo *);
83: PetscErrorCode (*iccfactor)(Mat, IS, const MatFactorInfo *);
84: /*39*/
85: PetscErrorCode (*axpy)(Mat, PetscScalar, Mat, MatStructure);
86: PetscErrorCode (*createsubmatrices)(Mat, PetscInt, const IS[], const IS[], MatReuse, Mat *[]);
87: PetscErrorCode (*increaseoverlap)(Mat, PetscInt, IS[], PetscInt);
88: PetscErrorCode (*getvalues)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], PetscScalar[]);
89: PetscErrorCode (*copy)(Mat, Mat, MatStructure);
90: /*44*/
91: PetscErrorCode (*getrowmax)(Mat, Vec, PetscInt[]);
92: PetscErrorCode (*scale)(Mat, PetscScalar);
93: PetscErrorCode (*shift)(Mat, PetscScalar);
94: PetscErrorCode (*diagonalset)(Mat, Vec, InsertMode);
95: PetscErrorCode (*zerorowscolumns)(Mat, PetscInt, const PetscInt[], PetscScalar, Vec, Vec);
96: /*49*/
97: PetscErrorCode (*setrandom)(Mat, PetscRandom);
98: PetscErrorCode (*getrowij)(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
99: PetscErrorCode (*restorerowij)(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
100: PetscErrorCode (*getcolumnij)(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
101: PetscErrorCode (*restorecolumnij)(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
102: /*54*/
103: PetscErrorCode (*fdcoloringcreate)(Mat, ISColoring, MatFDColoring);
104: PetscErrorCode (*coloringpatch)(Mat, PetscInt, PetscInt, ISColoringValue[], ISColoring *);
105: PetscErrorCode (*setunfactored)(Mat);
106: PetscErrorCode (*permute)(Mat, IS, IS, Mat *);
107: PetscErrorCode (*setvaluesblocked)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
108: /*59*/
109: PetscErrorCode (*createsubmatrix)(Mat, IS, IS, MatReuse, Mat *);
110: PetscErrorCode (*destroy)(Mat);
111: PetscErrorCode (*view)(Mat, PetscViewer);
112: PetscErrorCode (*convertfrom)(Mat, MatType, MatReuse, Mat *);
113: PetscErrorCode (*placeholder_63)(void);
114: /*64*/
115: PetscErrorCode (*matmatmultsymbolic)(Mat, Mat, Mat, PetscReal, Mat);
116: PetscErrorCode (*matmatmultnumeric)(Mat, Mat, Mat, Mat);
117: PetscErrorCode (*setlocaltoglobalmapping)(Mat, ISLocalToGlobalMapping, ISLocalToGlobalMapping);
118: PetscErrorCode (*setvalueslocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
119: PetscErrorCode (*zerorowslocal)(Mat, PetscInt, const PetscInt[], PetscScalar, Vec, Vec);
120: /*69*/
121: PetscErrorCode (*getrowmaxabs)(Mat, Vec, PetscInt[]);
122: PetscErrorCode (*getrowminabs)(Mat, Vec, PetscInt[]);
123: PetscErrorCode (*convert)(Mat, MatType, MatReuse, Mat *);
124: PetscErrorCode (*hasoperation)(Mat, MatOperation, PetscBool *);
125: PetscErrorCode (*placeholder_73)(void);
126: /*74*/
127: PetscErrorCode (*setvaluesadifor)(Mat, PetscInt, void *);
128: PetscErrorCode (*fdcoloringapply)(Mat, MatFDColoring, Vec, void *);
129: PetscErrorCode (*setfromoptions)(Mat, PetscOptionItems *);
130: PetscErrorCode (*placeholder_77)(void);
131: PetscErrorCode (*placeholder_78)(void);
132: /*79*/
133: PetscErrorCode (*findzerodiagonals)(Mat, IS *);
134: PetscErrorCode (*mults)(Mat, Vecs, Vecs);
135: PetscErrorCode (*solves)(Mat, Vecs, Vecs);
136: PetscErrorCode (*getinertia)(Mat, PetscInt *, PetscInt *, PetscInt *);
137: PetscErrorCode (*load)(Mat, PetscViewer);
138: /*84*/
139: PetscErrorCode (*issymmetric)(Mat, PetscReal, PetscBool *);
140: PetscErrorCode (*ishermitian)(Mat, PetscReal, PetscBool *);
141: PetscErrorCode (*isstructurallysymmetric)(Mat, PetscBool *);
142: PetscErrorCode (*setvaluesblockedlocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
143: PetscErrorCode (*getvecs)(Mat, Vec *, Vec *);
144: /*89*/
145: PetscErrorCode (*placeholder_89)(void);
146: PetscErrorCode (*matmultsymbolic)(Mat, Mat, PetscReal, Mat);
147: PetscErrorCode (*matmultnumeric)(Mat, Mat, Mat);
148: PetscErrorCode (*placeholder_92)(void);
149: PetscErrorCode (*ptapsymbolic)(Mat, Mat, PetscReal, Mat); /* double dispatch wrapper routine */
150: /*94*/
151: PetscErrorCode (*ptapnumeric)(Mat, Mat, Mat); /* double dispatch wrapper routine */
152: PetscErrorCode (*placeholder_95)(void);
153: PetscErrorCode (*mattransposemultsymbolic)(Mat, Mat, PetscReal, Mat);
154: PetscErrorCode (*mattransposemultnumeric)(Mat, Mat, Mat);
155: PetscErrorCode (*bindtocpu)(Mat, PetscBool);
156: /*99*/
157: PetscErrorCode (*productsetfromoptions)(Mat);
158: PetscErrorCode (*productsymbolic)(Mat);
159: PetscErrorCode (*productnumeric)(Mat);
160: PetscErrorCode (*conjugate)(Mat); /* complex conjugate */
161: PetscErrorCode (*viewnative)(Mat, PetscViewer);
162: /*104*/
163: PetscErrorCode (*setvaluesrow)(Mat, PetscInt, const PetscScalar[]);
164: PetscErrorCode (*realpart)(Mat);
165: PetscErrorCode (*imaginarypart)(Mat);
166: PetscErrorCode (*getrowuppertriangular)(Mat);
167: PetscErrorCode (*restorerowuppertriangular)(Mat);
168: /*109*/
169: PetscErrorCode (*matsolve)(Mat, Mat, Mat);
170: PetscErrorCode (*matsolvetranspose)(Mat, Mat, Mat);
171: PetscErrorCode (*getrowmin)(Mat, Vec, PetscInt[]);
172: PetscErrorCode (*getcolumnvector)(Mat, Vec, PetscInt);
173: PetscErrorCode (*missingdiagonal)(Mat, PetscBool *, PetscInt *);
174: /*114*/
175: PetscErrorCode (*getseqnonzerostructure)(Mat, Mat *);
176: PetscErrorCode (*create)(Mat);
177: PetscErrorCode (*getghosts)(Mat, PetscInt *, const PetscInt *[]);
178: PetscErrorCode (*getlocalsubmatrix)(Mat, IS, IS, Mat *);
179: PetscErrorCode (*restorelocalsubmatrix)(Mat, IS, IS, Mat *);
180: /*119*/
181: PetscErrorCode (*multdiagonalblock)(Mat, Vec, Vec);
182: PetscErrorCode (*hermitiantranspose)(Mat, MatReuse, Mat *);
183: PetscErrorCode (*multhermitiantranspose)(Mat, Vec, Vec);
184: PetscErrorCode (*multhermitiantransposeadd)(Mat, Vec, Vec, Vec);
185: PetscErrorCode (*getmultiprocblock)(Mat, MPI_Comm, MatReuse, Mat *);
186: /*124*/
187: PetscErrorCode (*findnonzerorows)(Mat, IS *);
188: PetscErrorCode (*getcolumnreductions)(Mat, PetscInt, PetscReal *);
189: PetscErrorCode (*invertblockdiagonal)(Mat, const PetscScalar **);
190: PetscErrorCode (*invertvariableblockdiagonal)(Mat, PetscInt, const PetscInt *, PetscScalar *);
191: PetscErrorCode (*createsubmatricesmpi)(Mat, PetscInt, const IS[], const IS[], MatReuse, Mat **);
192: /*129*/
193: PetscErrorCode (*setvaluesbatch)(Mat, PetscInt, PetscInt, PetscInt *, const PetscScalar *);
194: PetscErrorCode (*placeholder_130)(void);
195: PetscErrorCode (*transposematmultsymbolic)(Mat, Mat, PetscReal, Mat);
196: PetscErrorCode (*transposematmultnumeric)(Mat, Mat, Mat);
197: PetscErrorCode (*transposecoloringcreate)(Mat, ISColoring, MatTransposeColoring);
198: /*134*/
199: PetscErrorCode (*transcoloringapplysptoden)(MatTransposeColoring, Mat, Mat);
200: PetscErrorCode (*transcoloringapplydentosp)(MatTransposeColoring, Mat, Mat);
201: PetscErrorCode (*placeholder_136)(void);
202: PetscErrorCode (*rartsymbolic)(Mat, Mat, PetscReal, Mat); /* double dispatch wrapper routine */
203: PetscErrorCode (*rartnumeric)(Mat, Mat, Mat); /* double dispatch wrapper routine */
204: /*139*/
205: PetscErrorCode (*setblocksizes)(Mat, PetscInt, PetscInt);
206: PetscErrorCode (*aypx)(Mat, PetscScalar, Mat, MatStructure);
207: PetscErrorCode (*residual)(Mat, Vec, Vec, Vec);
208: PetscErrorCode (*fdcoloringsetup)(Mat, ISColoring, MatFDColoring);
209: PetscErrorCode (*findoffblockdiagonalentries)(Mat, IS *);
210: PetscErrorCode (*creatempimatconcatenateseqmat)(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);
211: /*145*/
212: PetscErrorCode (*destroysubmatrices)(PetscInt, Mat *[]);
213: PetscErrorCode (*mattransposesolve)(Mat, Mat, Mat);
214: PetscErrorCode (*getvalueslocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], PetscScalar[]);
215: PetscErrorCode (*creategraph)(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
216: PetscErrorCode (*dummy)(Mat);
217: /*150*/
218: PetscErrorCode (*transposesymbolic)(Mat, Mat *);
219: PetscErrorCode (*eliminatezeros)(Mat, PetscBool);
220: PetscErrorCode (*getrowsumabs)(Mat, Vec);
221: PetscErrorCode (*getfactor)(Mat, MatSolverType, MatFactorType, Mat *);
222: };
223: /*
224: If you add MatOps entries above also add them to the MATOP enum
225: in include/petscmat.h and src/mat/f90-mod/petscmat.h
226: */
228: #include <petscsys.h>
230: typedef struct _p_MatRootName *MatRootName;
231: struct _p_MatRootName {
232: char *rname, *sname, *mname;
233: MatRootName next;
234: };
236: PETSC_EXTERN MatRootName MatRootNameList;
238: /*
239: Utility private matrix routines used outside Mat
240: */
241: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat, PetscBool, PetscReal, IS *);
243: /*
244: Utility private matrix routines
245: */
246: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat, MatType, MatReuse, Mat *);
247: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat, MatType, MatReuse, Mat *);
248: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat, MatType, MatReuse, Mat *);
249: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat, Mat, MatStructure);
250: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat, Vec, InsertMode);
251: #if defined(PETSC_HAVE_SCALAPACK)
252: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
253: #endif
254: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_Basic(Mat, PetscCount, PetscInt[], PetscInt[]);
255: PETSC_INTERN PetscErrorCode MatSetValuesCOO_Basic(Mat, const PetscScalar[], InsertMode);
257: /* This can be moved to the public header after implementing some missing MatProducts */
258: PETSC_INTERN PetscErrorCode MatCreateFromISLocalToGlobalMapping(ISLocalToGlobalMapping, Mat, PetscBool, PetscBool, MatType, Mat *);
260: /* these callbacks rely on the old matrix function pointers for
261: matmat operations. They are unsafe, and should be removed.
262: However, the amount of work needed to clean up all the
263: implementations is not negligible */
264: PETSC_INTERN PetscErrorCode MatProductSymbolic_AB(Mat);
265: PETSC_INTERN PetscErrorCode MatProductNumeric_AB(Mat);
266: PETSC_INTERN PetscErrorCode MatProductSymbolic_AtB(Mat);
267: PETSC_INTERN PetscErrorCode MatProductNumeric_AtB(Mat);
268: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABt(Mat);
269: PETSC_INTERN PetscErrorCode MatProductNumeric_ABt(Mat);
270: PETSC_INTERN PetscErrorCode MatProductNumeric_PtAP(Mat);
271: PETSC_INTERN PetscErrorCode MatProductNumeric_RARt(Mat);
272: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC(Mat);
273: PETSC_INTERN PetscErrorCode MatProductNumeric_ABC(Mat);
275: PETSC_INTERN PetscErrorCode MatProductCreate_Private(Mat, Mat, Mat, Mat);
276: /* this callback handles all the different triple products and
277: does not rely on the function pointers; used by cuSPARSE/hipSPARSE and KOKKOS-KERNELS */
278: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC_Basic(Mat);
280: /* CreateGraph is common to AIJ seq and mpi */
281: PETSC_INTERN PetscErrorCode MatCreateGraph_Simple_AIJ(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
283: #if defined(PETSC_CLANG_STATIC_ANALYZER)
284: template <typename Tm>
285: extern void MatCheckPreallocated(Tm, int);
286: template <typename Tm>
287: extern void MatCheckProduct(Tm, int);
288: #else /* PETSC_CLANG_STATIC_ANALYZER */
289: #define MatCheckPreallocated(A, arg) \
290: do { \
291: if (!(A)->preallocated) PetscCall(MatSetUp(A)); \
292: } while (0)
294: #if defined(PETSC_USE_DEBUG)
295: #define MatCheckProduct(A, arg) \
296: do { \
297: PetscCheck((A)->product, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Argument %d \"%s\" is not a matrix obtained from MatProductCreate()", (arg), #A); \
298: } while (0)
299: #else
300: #define MatCheckProduct(A, arg) \
301: do { \
302: } while (0)
303: #endif
304: #endif /* PETSC_CLANG_STATIC_ANALYZER */
306: /*
307: The stash is used to temporarily store inserted matrix values that
308: belong to another processor. During the assembly phase the stashed
309: values are moved to the correct processor and
310: */
312: typedef struct _MatStashSpace *PetscMatStashSpace;
314: struct _MatStashSpace {
315: PetscMatStashSpace next;
316: PetscScalar *space_head, *val;
317: PetscInt *idx, *idy;
318: PetscInt total_space_size;
319: PetscInt local_used;
320: PetscInt local_remaining;
321: };
323: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt, PetscInt, PetscMatStashSpace *);
324: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt, PetscMatStashSpace *, PetscScalar *, PetscInt *, PetscInt *);
325: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace *);
327: typedef struct {
328: PetscInt count;
329: } MatStashHeader;
331: typedef struct {
332: void *buffer; /* Of type blocktype, dynamically constructed */
333: PetscInt count;
334: char pending;
335: } MatStashFrame;
337: typedef struct _MatStash MatStash;
338: struct _MatStash {
339: PetscInt nmax; /* maximum stash size */
340: PetscInt umax; /* user specified max-size */
341: PetscInt oldnmax; /* the nmax value used previously */
342: PetscInt n; /* stash size */
343: PetscInt bs; /* block size of the stash */
344: PetscInt reallocs; /* preserve the no of mallocs invoked */
345: PetscMatStashSpace space_head, space; /* linked list to hold stashed global row/column numbers and matrix values */
347: PetscErrorCode (*ScatterBegin)(Mat, MatStash *, PetscInt *);
348: PetscErrorCode (*ScatterGetMesg)(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
349: PetscErrorCode (*ScatterEnd)(MatStash *);
350: PetscErrorCode (*ScatterDestroy)(MatStash *);
352: /* The following variables are used for communication */
353: MPI_Comm comm;
354: PetscMPIInt size, rank;
355: PetscMPIInt tag1, tag2;
356: MPI_Request *send_waits; /* array of send requests */
357: MPI_Request *recv_waits; /* array of receive requests */
358: MPI_Status *send_status; /* array of send status */
359: PetscInt nsends, nrecvs; /* numbers of sends and receives */
360: PetscScalar *svalues; /* sending data */
361: PetscInt *sindices;
362: PetscScalar **rvalues; /* receiving data (values) */
363: PetscInt **rindices; /* receiving data (indices) */
364: PetscInt nprocessed; /* number of messages already processed */
365: PetscMPIInt *flg_v; /* indicates what messages have arrived so far and from whom */
366: PetscBool reproduce;
367: PetscInt reproduce_count;
369: /* The following variables are used for BTS communication */
370: PetscBool first_assembly_done; /* Is the first time matrix assembly done? */
371: PetscBool use_status; /* Use MPI_Status to determine number of items in each message */
372: PetscMPIInt nsendranks;
373: PetscMPIInt nrecvranks;
374: PetscMPIInt *sendranks;
375: PetscMPIInt *recvranks;
376: MatStashHeader *sendhdr, *recvhdr;
377: MatStashFrame *sendframes; /* pointers to the main messages */
378: MatStashFrame *recvframes;
379: MatStashFrame *recvframe_active;
380: PetscInt recvframe_i; /* index of block within active frame */
381: PetscMPIInt recvframe_count; /* Count actually sent for current frame */
382: PetscInt recvcount; /* Number of receives processed so far */
383: PetscMPIInt *some_indices; /* From last call to MPI_Waitsome */
384: MPI_Status *some_statuses; /* Statuses from last call to MPI_Waitsome */
385: PetscMPIInt some_count; /* Number of requests completed in last call to MPI_Waitsome */
386: PetscMPIInt some_i; /* Index of request currently being processed */
387: MPI_Request *sendreqs;
388: MPI_Request *recvreqs;
389: PetscSegBuffer segsendblocks;
390: PetscSegBuffer segrecvframe;
391: PetscSegBuffer segrecvblocks;
392: MPI_Datatype blocktype;
393: size_t blocktype_size;
394: InsertMode *insertmode; /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
395: };
397: #if !defined(PETSC_HAVE_MPIUNI)
398: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash *);
399: #endif
400: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm, PetscInt, MatStash *);
401: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash *);
402: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash *);
403: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash *, PetscInt);
404: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash *, PetscInt *, PetscInt *);
405: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscBool);
406: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscBool);
407: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
408: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
409: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat, MatStash *, PetscInt *);
410: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
411: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat, MatInfoType, MatInfo *);
413: typedef struct {
414: PetscInt dim;
415: PetscInt dims[4];
416: PetscInt starts[4];
417: PetscBool noc; /* this is a single component problem, hence user will not set MatStencil.c */
418: } MatStencilInfo;
420: /* Info about using compressed row format */
421: typedef struct {
422: PetscBool use; /* indicates compressed rows have been checked and will be used */
423: PetscInt nrows; /* number of non-zero rows */
424: PetscInt *i; /* compressed row pointer */
425: PetscInt *rindex; /* compressed row index */
426: } Mat_CompressedRow;
427: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat, PetscInt, Mat_CompressedRow *, PetscInt *, PetscInt, PetscReal);
429: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
430: PetscInt nzlocal, nsends, nrecvs;
431: PetscMPIInt *send_rank, *recv_rank;
432: PetscInt *sbuf_nz, *rbuf_nz, *sbuf_j, **rbuf_j;
433: PetscScalar *sbuf_a, **rbuf_a;
434: MPI_Comm subcomm; /* when user does not provide a subcomm */
435: IS isrow, iscol;
436: Mat *matseq;
437: } Mat_Redundant;
439: typedef struct { /* used by MatProduct() */
440: MatProductType type;
441: char *alg;
442: Mat A, B, C, Dwork;
443: PetscBool symbolic_used_the_fact_A_is_symmetric; /* Symbolic phase took advantage of the fact that A is symmetric, and optimized e.g. AtB as AB. Then, .. */
444: PetscBool symbolic_used_the_fact_B_is_symmetric; /* .. in the numeric phase, if a new A is not symmetric (but has the same sparsity as the old A therefore .. */
445: PetscBool symbolic_used_the_fact_C_is_symmetric; /* MatMatMult(A,B,MAT_REUSE_MATRIX,..&C) is still legitimate), we need to redo symbolic! */
446: PetscReal fill;
447: PetscBool api_user; /* used to distinguish command line options and to indicate the matrix values are ready to be consumed at symbolic phase if needed */
448: PetscBool setfromoptionscalled;
450: /* Some products may display the information on the algorithm used */
451: PetscErrorCode (*view)(Mat, PetscViewer);
453: /* many products have intermediate data structures, each specific to Mat types and product type */
454: PetscBool clear; /* whether or not to clear the data structures after MatProductNumeric has been called */
455: void *data; /* where to stash those structures */
456: PetscErrorCode (*destroy)(void *); /* destroy routine */
457: } Mat_Product;
459: struct _p_Mat {
460: PETSCHEADER(struct _MatOps);
461: PetscLayout rmap, cmap;
462: void *data; /* implementation-specific data */
463: MatFactorType factortype; /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
464: PetscBool trivialsymbolic; /* indicates the symbolic factorization doesn't actually do a symbolic factorization, it is delayed to the numeric factorization */
465: PetscBool canuseordering; /* factorization can use ordering provide to routine (most PETSc implementations) */
466: MatOrderingType preferredordering[MAT_FACTOR_NUM_TYPES]; /* what is the preferred (or default) ordering for the matrix solver type */
467: PetscBool assembled; /* is the matrix assembled? */
468: PetscBool was_assembled; /* new values inserted into assembled mat */
469: PetscInt num_ass; /* number of times matrix has been assembled */
470: PetscObjectState nonzerostate; /* each time new nonzeros locations are introduced into the matrix this is updated */
471: PetscObjectState ass_nonzerostate; /* nonzero state at last assembly */
472: MatInfo info; /* matrix information */
473: InsertMode insertmode; /* have values been inserted in matrix or added? */
474: MatStash stash, bstash; /* used for assembling off-proc mat emements */
475: MatNullSpace nullsp; /* null space (operator is singular) */
476: MatNullSpace transnullsp; /* null space of transpose of operator */
477: MatNullSpace nearnullsp; /* near null space to be used by multigrid methods */
478: PetscInt congruentlayouts; /* are the rows and columns layouts congruent? */
479: PetscBool preallocated;
480: MatStencilInfo stencil; /* information for structured grid */
481: PetscBool3 symmetric, hermitian, structurally_symmetric, spd;
482: PetscBool symmetry_eternal, structural_symmetry_eternal, spd_eternal;
483: PetscBool nooffprocentries, nooffproczerorows;
484: PetscBool assembly_subset; /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
485: PetscBool submat_singleis; /* for efficient PCSetUp_ASM() */
486: PetscBool structure_only;
487: PetscBool sortedfull; /* full, sorted rows are inserted */
488: PetscBool force_diagonals; /* set by MAT_FORCE_DIAGONAL_ENTRIES */
489: #if defined(PETSC_HAVE_DEVICE)
490: PetscOffloadMask offloadmask; /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
491: PetscBool boundtocpu;
492: PetscBool bindingpropagates;
493: #endif
494: char *defaultrandtype;
495: void *spptr; /* pointer for special library like SuperLU */
496: char *solvertype;
497: PetscBool checksymmetryonassembly, checknullspaceonassembly;
498: PetscReal checksymmetrytol;
499: Mat schur; /* Schur complement matrix */
500: MatFactorSchurStatus schur_status; /* status of the Schur complement matrix */
501: Mat_Redundant *redundant; /* used by MatCreateRedundantMatrix() */
502: PetscBool erroriffailure; /* Generate an error if detected (for example a zero pivot) instead of returning */
503: MatFactorError factorerrortype; /* type of error in factorization */
504: PetscReal factorerror_zeropivot_value; /* If numerical zero pivot was detected this is the computed value */
505: PetscInt factorerror_zeropivot_row; /* Row where zero pivot was detected */
506: PetscInt nblocks, *bsizes; /* support for MatSetVariableBlockSizes() */
507: PetscInt p_cstart, p_rank, p_cend, n_rank; /* Information from parallel MatComputeVariableBlockEnvelope() */
508: PetscBool p_parallel;
509: char *defaultvectype;
510: Mat_Product *product;
511: PetscBool form_explicit_transpose; /* hint to generate an explicit mat tranpsose for operations like MatMultTranspose() */
512: PetscBool transupdated; /* whether or not the explicitly generated transpose is up-to-date */
513: char *factorprefix; /* the prefix to use with factored matrix that is created */
514: PetscBool hash_active; /* indicates MatSetValues() is being handled by hashing */
515: };
517: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat, PetscScalar, Mat, MatStructure);
518: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat, Mat, PetscScalar, Mat, MatStructure);
519: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat, Mat, Mat *);
520: PETSC_INTERN PetscErrorCode MatAXPY_Dense_Nest(Mat, PetscScalar, Mat);
522: PETSC_INTERN PetscErrorCode MatSetUp_Default(Mat);
524: /*
525: Utility for MatZeroRows
526: */
527: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat, PetscInt, const PetscInt *, PetscInt *, PetscInt **);
529: /*
530: Utility for MatView/MatLoad
531: */
532: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat, PetscViewer);
533: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat, PetscViewer);
535: /*
536: Object for partitioning graphs
537: */
539: typedef struct _MatPartitioningOps *MatPartitioningOps;
540: struct _MatPartitioningOps {
541: PetscErrorCode (*apply)(MatPartitioning, IS *);
542: PetscErrorCode (*applynd)(MatPartitioning, IS *);
543: PetscErrorCode (*setfromoptions)(MatPartitioning, PetscOptionItems *);
544: PetscErrorCode (*destroy)(MatPartitioning);
545: PetscErrorCode (*view)(MatPartitioning, PetscViewer);
546: PetscErrorCode (*improve)(MatPartitioning, IS *);
547: };
549: struct _p_MatPartitioning {
550: PETSCHEADER(struct _MatPartitioningOps);
551: Mat adj;
552: PetscInt *vertex_weights;
553: PetscReal *part_weights;
554: PetscInt n; /* number of partitions */
555: PetscInt ncon; /* number of vertex weights per vertex */
556: void *data;
557: PetscInt setupcalled;
558: PetscBool use_edge_weights; /* A flag indicates whether or not to use edge weights */
559: };
561: /* needed for parallel nested dissection by ParMetis and PTSCOTCH */
562: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt, PetscInt[], PetscInt[], PetscInt[]);
564: /*
565: Object for coarsen graphs
566: */
567: typedef struct _MatCoarsenOps *MatCoarsenOps;
568: struct _MatCoarsenOps {
569: PetscErrorCode (*apply)(MatCoarsen);
570: PetscErrorCode (*setfromoptions)(MatCoarsen, PetscOptionItems *);
571: PetscErrorCode (*destroy)(MatCoarsen);
572: PetscErrorCode (*view)(MatCoarsen, PetscViewer);
573: };
575: #define MAT_COARSEN_STRENGTH_INDEX_SIZE 3
576: struct _p_MatCoarsen {
577: PETSCHEADER(struct _MatCoarsenOps);
578: Mat graph;
579: void *subctx;
580: /* */
581: PetscBool strict_aggs;
582: IS perm;
583: PetscCoarsenData *agg_lists;
584: PetscInt max_it; /* number of iterations in HEM */
585: PetscReal threshold; /* HEM can filter interim graphs */
586: PetscInt strength_index_size;
587: PetscInt strength_index[MAT_COARSEN_STRENGTH_INDEX_SIZE];
588: };
590: PETSC_EXTERN PetscErrorCode MatCoarsenMISKSetDistance(MatCoarsen, PetscInt);
591: PETSC_EXTERN PetscErrorCode MatCoarsenMISKGetDistance(MatCoarsen, PetscInt *);
593: /*
594: Used in aijdevice.h
595: */
596: typedef struct {
597: PetscInt *i;
598: PetscInt *j;
599: PetscScalar *a;
600: PetscInt n;
601: PetscInt ignorezeroentries;
602: } PetscCSRDataStructure;
604: /*
605: MatFDColoring is used to compute Jacobian matrices efficiently
606: via coloring. The data structure is explained below in an example.
608: Color = 0 1 0 2 | 2 3 0
609: ---------------------------------------------------
610: 00 01 | 05
611: 10 11 | 14 15 Processor 0
612: 22 23 | 25
613: 32 33 |
614: ===================================================
615: | 44 45 46
616: 50 | 55 Processor 1
617: | 64 66
618: ---------------------------------------------------
620: ncolors = 4;
622: ncolumns = {2,1,1,0}
623: columns = {{0,2},{1},{3},{}}
624: nrows = {4,2,3,3}
625: rows = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
626: vwscale = {dx(0),dx(1),dx(2),dx(3)} MPI Vec
627: vscale = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)} Seq Vec
629: ncolumns = {1,0,1,1}
630: columns = {{6},{},{4},{5}}
631: nrows = {3,0,2,2}
632: rows = {{0,1,2},{},{1,2},{1,2}}
633: vwscale = {dx(4),dx(5),dx(6)} MPI Vec
634: vscale = {dx(0),dx(4),dx(5),dx(6)} Seq Vec
636: See the routine MatFDColoringApply() for how this data is used
637: to compute the Jacobian.
639: */
640: typedef struct {
641: PetscInt row;
642: PetscInt col;
643: PetscScalar *valaddr; /* address of value */
644: } MatEntry;
646: typedef struct {
647: PetscInt row;
648: PetscScalar *valaddr; /* address of value */
649: } MatEntry2;
651: struct _p_MatFDColoring {
652: PETSCHEADER(int);
653: PetscInt M, N, m; /* total rows, columns; local rows */
654: PetscInt rstart; /* first row owned by local processor */
655: PetscInt ncolors; /* number of colors */
656: PetscInt *ncolumns; /* number of local columns for a color */
657: PetscInt **columns; /* lists the local columns of each color (using global column numbering) */
658: IS *isa; /* these are the IS that contain the column values given in columns */
659: PetscInt *nrows; /* number of local rows for each color */
660: MatEntry *matentry; /* holds (row, column, address of value) for Jacobian matrix entry */
661: MatEntry2 *matentry2; /* holds (row, address of value) for Jacobian matrix entry */
662: PetscScalar *dy; /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
663: PetscReal error_rel; /* square root of relative error in computing function */
664: PetscReal umin; /* minimum allowable u'dx value */
665: Vec w1, w2, w3; /* work vectors used in computing Jacobian */
666: PetscBool fset; /* indicates that the initial function value F(X) is set */
667: PetscErrorCode (*f)(void); /* function that defines Jacobian */
668: void *fctx; /* optional user-defined context for use by the function f */
669: Vec vscale; /* holds FD scaling, i.e. 1/dx for each perturbed column */
670: PetscInt currentcolor; /* color for which function evaluation is being done now */
671: const char *htype; /* "wp" or "ds" */
672: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
673: PetscInt brows, bcols; /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
674: PetscBool setupcalled; /* true if setup has been called */
675: PetscBool viewed; /* true if the -mat_fd_coloring_view has been triggered already */
676: void (*ftn_func_pointer)(void), *ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
677: PetscObjectId matid; /* matrix this object was created with, must always be the same */
678: };
680: typedef struct _MatColoringOps *MatColoringOps;
681: struct _MatColoringOps {
682: PetscErrorCode (*destroy)(MatColoring);
683: PetscErrorCode (*setfromoptions)(MatColoring, PetscOptionItems *);
684: PetscErrorCode (*view)(MatColoring, PetscViewer);
685: PetscErrorCode (*apply)(MatColoring, ISColoring *);
686: PetscErrorCode (*weights)(MatColoring, PetscReal **, PetscInt **);
687: };
689: struct _p_MatColoring {
690: PETSCHEADER(struct _MatColoringOps);
691: Mat mat;
692: PetscInt dist; /* distance of the coloring */
693: PetscInt maxcolors; /* the maximum number of colors returned, maxcolors=1 for MIS */
694: void *data; /* inner context */
695: PetscBool valid; /* check to see if what is produced is a valid coloring */
696: MatColoringWeightType weight_type; /* type of weight computation to be performed */
697: PetscReal *user_weights; /* custom weights and permutation */
698: PetscInt *user_lperm;
699: PetscBool valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
700: };
702: struct _p_MatTransposeColoring {
703: PETSCHEADER(int);
704: PetscInt M, N, m; /* total rows, columns; local rows */
705: PetscInt rstart; /* first row owned by local processor */
706: PetscInt ncolors; /* number of colors */
707: PetscInt *ncolumns; /* number of local columns for a color */
708: PetscInt *nrows; /* number of local rows for each color */
709: PetscInt currentcolor; /* color for which function evaluation is being done now */
710: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
712: PetscInt *colorforrow, *colorforcol; /* pointer to rows and columns */
713: PetscInt *rows; /* lists the local rows for each color (using the local row numbering) */
714: PetscInt *den2sp; /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
715: PetscInt *columns; /* lists the local columns of each color (using global column numbering) */
716: PetscInt brows; /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
717: PetscInt *lstart; /* array used for loop over row blocks of Csparse */
718: };
720: /*
721: Null space context for preconditioner/operators
722: */
723: struct _p_MatNullSpace {
724: PETSCHEADER(int);
725: PetscBool has_cnst;
726: PetscInt n;
727: Vec *vecs;
728: PetscScalar *alpha; /* for projections */
729: PetscErrorCode (*remove)(MatNullSpace, Vec, void *); /* for user provided removal function */
730: void *rmctx; /* context for remove() function */
731: };
733: /*
734: Checking zero pivot for LU, ILU preconditioners.
735: */
736: typedef struct {
737: PetscInt nshift, nshift_max;
738: PetscReal shift_amount, shift_lo, shift_hi, shift_top, shift_fraction;
739: PetscBool newshift;
740: PetscReal rs; /* active row sum of abs(off-diagonals) */
741: PetscScalar pv; /* pivot of the active row */
742: } FactorShiftCtx;
744: PETSC_EXTERN PetscErrorCode MatTransposeCheckNonzeroState_Private(Mat, Mat);
746: /*
747: Used by MatTranspose() and potentially other functions to track the matrix used in the generation of another matrix
748: */
749: typedef struct {
750: PetscObjectId id;
751: PetscObjectState state;
752: PetscObjectState nonzerostate;
753: } MatParentState;
755: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
756: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat, PetscInt, PetscInt);
758: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatShift_Basic(Mat, PetscScalar);
760: static inline PetscErrorCode MatPivotCheck_nz(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
761: {
762: PetscReal _rs = sctx->rs;
763: PetscReal _zero = info->zeropivot * _rs;
765: PetscFunctionBegin;
766: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
767: /* force |diag| > zeropivot*rs */
768: if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
769: else sctx->shift_amount *= 2.0;
770: sctx->newshift = PETSC_TRUE;
771: (sctx->nshift)++;
772: } else {
773: sctx->newshift = PETSC_FALSE;
774: }
775: PetscFunctionReturn(PETSC_SUCCESS);
776: }
778: static inline PetscErrorCode MatPivotCheck_pd(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
779: {
780: PetscReal _rs = sctx->rs;
781: PetscReal _zero = info->zeropivot * _rs;
783: PetscFunctionBegin;
784: if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
785: /* force matfactor to be diagonally dominant */
786: if (sctx->nshift == sctx->nshift_max) {
787: sctx->shift_fraction = sctx->shift_hi;
788: } else {
789: sctx->shift_lo = sctx->shift_fraction;
790: sctx->shift_fraction = (sctx->shift_hi + sctx->shift_lo) / (PetscReal)2.;
791: }
792: sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
793: sctx->nshift++;
794: sctx->newshift = PETSC_TRUE;
795: } else {
796: sctx->newshift = PETSC_FALSE;
797: }
798: PetscFunctionReturn(PETSC_SUCCESS);
799: }
801: static inline PetscErrorCode MatPivotCheck_inblocks(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
802: {
803: PetscReal _zero = info->zeropivot;
805: PetscFunctionBegin;
806: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
807: sctx->pv += info->shiftamount;
808: sctx->shift_amount = 0.0;
809: sctx->nshift++;
810: }
811: sctx->newshift = PETSC_FALSE;
812: PetscFunctionReturn(PETSC_SUCCESS);
813: }
815: static inline PetscErrorCode MatPivotCheck_none(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
816: {
817: PetscReal _zero = info->zeropivot;
819: PetscFunctionBegin;
820: sctx->newshift = PETSC_FALSE;
821: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
822: PetscCheck(!mat->erroriffailure, PETSC_COMM_SELF, PETSC_ERR_MAT_LU_ZRPVT, "Zero pivot row %" PetscInt_FMT " value %g tolerance %g", row, (double)PetscAbsScalar(sctx->pv), (double)_zero);
823: PetscCall(PetscInfo(mat, "Detected zero pivot in factorization in row %" PetscInt_FMT " value %g tolerance %g\n", row, (double)PetscAbsScalar(sctx->pv), (double)_zero));
824: fact->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
825: fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
826: fact->factorerror_zeropivot_row = row;
827: }
828: PetscFunctionReturn(PETSC_SUCCESS);
829: }
831: static inline PetscErrorCode MatPivotCheck(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
832: {
833: PetscFunctionBegin;
834: if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) PetscCall(MatPivotCheck_nz(mat, info, sctx, row));
835: else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) PetscCall(MatPivotCheck_pd(mat, info, sctx, row));
836: else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) PetscCall(MatPivotCheck_inblocks(mat, info, sctx, row));
837: else PetscCall(MatPivotCheck_none(fact, mat, info, sctx, row));
838: PetscFunctionReturn(PETSC_SUCCESS);
839: }
841: #include <petscbt.h>
842: /*
843: Create and initialize a linked list
844: Input Parameters:
845: idx_start - starting index of the list
846: lnk_max - max value of lnk indicating the end of the list
847: nlnk - max length of the list
848: Output Parameters:
849: lnk - list initialized
850: bt - PetscBT (bitarray) with all bits set to false
851: lnk_empty - flg indicating the list is empty
852: */
853: #define PetscLLCreate(idx_start, lnk_max, nlnk, lnk, bt) ((PetscErrorCode)(PetscMalloc1(nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, PETSC_SUCCESS)))
855: #define PetscLLCreate_new(idx_start, lnk_max, nlnk, lnk, bt, lnk_empty) ((PetscErrorCode)(PetscMalloc1(nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk_empty = PETSC_TRUE, 0) || (lnk[idx_start] = lnk_max, PETSC_SUCCESS)))
857: static inline PetscErrorCode PetscLLInsertLocation_Private(PetscBool assume_sorted, PetscInt k, PetscInt idx_start, PetscInt entry, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnkdata, PetscInt *PETSC_RESTRICT lnk)
858: {
859: PetscInt location;
861: PetscFunctionBegin;
862: /* start from the beginning if entry < previous entry */
863: if (!assume_sorted && k && entry < *lnkdata) *lnkdata = idx_start;
864: /* search for insertion location */
865: do {
866: location = *lnkdata;
867: *lnkdata = lnk[location];
868: } while (entry > *lnkdata);
869: /* insertion location is found, add entry into lnk */
870: lnk[location] = entry;
871: lnk[entry] = *lnkdata;
872: ++(*nlnk);
873: *lnkdata = entry; /* next search starts from here if next_entry > entry */
874: PetscFunctionReturn(PETSC_SUCCESS);
875: }
877: static inline PetscErrorCode PetscLLAdd_Private(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt, PetscBool assume_sorted)
878: {
879: PetscFunctionBegin;
880: *nlnk = 0;
881: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
882: const PetscInt entry = indices[k];
884: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk));
885: }
886: PetscFunctionReturn(PETSC_SUCCESS);
887: }
889: /*
890: Add an index set into a sorted linked list
891: Input Parameters:
892: nidx - number of input indices
893: indices - integer array
894: idx_start - starting index of the list
895: lnk - linked list(an integer array) that is created
896: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
897: output Parameters:
898: nlnk - number of newly added indices
899: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
900: bt - updated PetscBT (bitarray)
901: */
902: static inline PetscErrorCode PetscLLAdd(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
903: {
904: PetscFunctionBegin;
905: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_FALSE));
906: PetscFunctionReturn(PETSC_SUCCESS);
907: }
909: /*
910: Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata = idx_start;'
911: Input Parameters:
912: nidx - number of input indices
913: indices - sorted integer array
914: idx_start - starting index of the list
915: lnk - linked list(an integer array) that is created
916: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
917: output Parameters:
918: nlnk - number of newly added indices
919: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
920: bt - updated PetscBT (bitarray)
921: */
922: static inline PetscErrorCode PetscLLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
923: {
924: PetscFunctionBegin;
925: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_TRUE));
926: PetscFunctionReturn(PETSC_SUCCESS);
927: }
929: /*
930: Add a permuted index set into a sorted linked list
931: Input Parameters:
932: nidx - number of input indices
933: indices - integer array
934: perm - permutation of indices
935: idx_start - starting index of the list
936: lnk - linked list(an integer array) that is created
937: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
938: output Parameters:
939: nlnk - number of newly added indices
940: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
941: bt - updated PetscBT (bitarray)
942: */
943: static inline PetscErrorCode PetscLLAddPerm(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, const PetscInt *PETSC_RESTRICT perm, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
944: {
945: PetscFunctionBegin;
946: *nlnk = 0;
947: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
948: const PetscInt entry = perm[indices[k]];
950: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk));
951: }
952: PetscFunctionReturn(PETSC_SUCCESS);
953: }
955: #if 0
956: /* this appears to be unused? */
957: static inline PetscErrorCode PetscLLAddSorted_new(PetscInt nidx, PetscInt *indices, PetscInt idx_start, PetscBool *lnk_empty, PetscInt *nlnk, PetscInt *lnk, PetscBT bt)
958: {
959: PetscInt lnkdata = idx_start;
961: PetscFunctionBegin;
962: if (*lnk_empty) {
963: for (PetscInt k = 0; k < nidx; ++k) {
964: const PetscInt entry = indices[k], location = lnkdata;
966: PetscCall(PetscBTSet(bt,entry)); /* mark the new entry */
967: lnkdata = lnk[location];
968: /* insertion location is found, add entry into lnk */
969: lnk[location] = entry;
970: lnk[entry] = lnkdata;
971: lnkdata = entry; /* next search starts from here */
972: }
973: /* lnk[indices[nidx-1]] = lnk[idx_start];
974: lnk[idx_start] = indices[0];
975: PetscCall(PetscBTSet(bt,indices[0]));
976: for (_k=1; _k<nidx; _k++) {
977: PetscCall(PetscBTSet(bt,indices[_k]));
978: lnk[indices[_k-1]] = indices[_k];
979: }
980: */
981: *nlnk = nidx;
982: *lnk_empty = PETSC_FALSE;
983: } else {
984: *nlnk = 0;
985: for (PetscInt k = 0; k < nidx; ++k) {
986: const PetscInt entry = indices[k];
988: if (!PetscBTLookupSet(bt,entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE,k,idx_start,entry,nlnk,&lnkdata,lnk));
989: }
990: }
991: PetscFunctionReturn(PETSC_SUCCESS);
992: }
993: #endif
995: /*
996: Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
997: Same as PetscLLAddSorted() with an additional operation:
998: count the number of input indices that are no larger than 'diag'
999: Input Parameters:
1000: indices - sorted integer array
1001: idx_start - starting index of the list, index of pivot row
1002: lnk - linked list(an integer array) that is created
1003: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1004: diag - index of the active row in LUFactorSymbolic
1005: nzbd - number of input indices with indices <= idx_start
1006: im - im[idx_start] is initialized as num of nonzero entries in row=idx_start
1007: output Parameters:
1008: nlnk - number of newly added indices
1009: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
1010: bt - updated PetscBT (bitarray)
1011: im - im[idx_start]: unchanged if diag is not an entry
1012: : num of entries with indices <= diag if diag is an entry
1013: */
1014: static inline PetscErrorCode PetscLLAddSortedLU(const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt, PetscInt diag, PetscInt nzbd, PetscInt *PETSC_RESTRICT im)
1015: {
1016: const PetscInt nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */
1018: PetscFunctionBegin;
1019: *nlnk = 0;
1020: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1021: const PetscInt entry = indices[k];
1023: ++nzbd;
1024: if (entry == diag) im[idx_start] = nzbd;
1025: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE, k, idx_start, entry, nlnk, &lnkdata, lnk));
1026: }
1027: PetscFunctionReturn(PETSC_SUCCESS);
1028: }
1030: /*
1031: Copy data on the list into an array, then initialize the list
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 - number of data on the list to be copied
1036: lnk - linked list
1037: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1038: output Parameters:
1039: indices - array that contains the copied data
1040: lnk - linked list that is cleaned and initialize
1041: bt - PetscBT (bitarray) with all bits set to false
1042: */
1043: static inline PetscErrorCode PetscLLClean(PetscInt idx_start, PetscInt lnk_max, PetscInt nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT indices, PetscBT bt)
1044: {
1045: PetscFunctionBegin;
1046: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1047: idx = lnk[idx];
1048: indices[j] = idx;
1049: PetscCall(PetscBTClear(bt, idx));
1050: }
1051: lnk[idx_start] = lnk_max;
1052: PetscFunctionReturn(PETSC_SUCCESS);
1053: }
1055: /*
1056: Free memories used by the list
1057: */
1058: #define PetscLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1060: /* Routines below are used for incomplete matrix factorization */
1061: /*
1062: Create and initialize a linked list and its levels
1063: Input Parameters:
1064: idx_start - starting index of the list
1065: lnk_max - max value of lnk indicating the end of the list
1066: nlnk - max length of the list
1067: Output Parameters:
1068: lnk - list initialized
1069: lnk_lvl - array of size nlnk for storing levels of lnk
1070: bt - PetscBT (bitarray) with all bits set to false
1071: */
1072: #define PetscIncompleteLLCreate(idx_start, lnk_max, nlnk, lnk, lnk_lvl, bt) \
1073: ((PetscErrorCode)(PetscIntMultError(2, nlnk, NULL) || PetscMalloc1(2 * nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, lnk_lvl = lnk + nlnk, PETSC_SUCCESS)))
1075: static inline PetscErrorCode PetscIncompleteLLInsertLocation_Private(PetscBool assume_sorted, PetscInt k, PetscInt idx_start, PetscInt entry, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnkdata, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscInt newval)
1076: {
1077: PetscFunctionBegin;
1078: PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, lnkdata, lnk));
1079: lnklvl[entry] = newval;
1080: PetscFunctionReturn(PETSC_SUCCESS);
1081: }
1083: /*
1084: Initialize a sorted linked list used for ILU and ICC
1085: Input Parameters:
1086: nidx - number of input idx
1087: idx - integer array used for storing column indices
1088: idx_start - starting index of the list
1089: perm - indices of an IS
1090: lnk - linked list(an integer array) that is created
1091: lnklvl - levels of lnk
1092: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1093: output Parameters:
1094: nlnk - number of newly added idx
1095: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1096: lnklvl - levels of lnk
1097: bt - updated PetscBT (bitarray)
1098: */
1099: static inline PetscErrorCode PetscIncompleteLLInit(PetscInt nidx, const PetscInt *PETSC_RESTRICT idx, PetscInt idx_start, const PetscInt *PETSC_RESTRICT perm, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscBT bt)
1100: {
1101: PetscFunctionBegin;
1102: *nlnk = 0;
1103: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1104: const PetscInt entry = perm[idx[k]];
1106: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, 0));
1107: }
1108: PetscFunctionReturn(PETSC_SUCCESS);
1109: }
1111: static inline PetscErrorCode PetscIncompleteLLAdd_Private(PetscInt nidx, const PetscInt *PETSC_RESTRICT idx, PetscReal level, const PetscInt *PETSC_RESTRICT idxlvl, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscBT bt, PetscInt prow_offset, PetscBool assume_sorted)
1112: {
1113: PetscFunctionBegin;
1114: *nlnk = 0;
1115: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1116: const PetscInt incrlev = idxlvl[k] + prow_offset + 1;
1118: if (incrlev <= level) {
1119: const PetscInt entry = idx[k];
1121: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, incrlev));
1122: else if (lnklvl[entry] > incrlev) lnklvl[entry] = incrlev; /* existing entry */
1123: }
1124: }
1125: PetscFunctionReturn(PETSC_SUCCESS);
1126: }
1128: /*
1129: Add a SORTED index set into a sorted linked list for ICC
1130: Input Parameters:
1131: nidx - number of input indices
1132: idx - sorted integer array used for storing column indices
1133: level - level of fill, e.g., ICC(level)
1134: idxlvl - level of idx
1135: idx_start - starting index of the list
1136: lnk - linked list(an integer array) that is created
1137: lnklvl - levels of lnk
1138: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1139: idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1140: output Parameters:
1141: nlnk - number of newly added indices
1142: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1143: lnklvl - levels of lnk
1144: bt - updated PetscBT (bitarray)
1145: Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1146: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1147: */
1148: static inline PetscErrorCode PetscICCLLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT idx, PetscReal level, const PetscInt *PETSC_RESTRICT idxlvl, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscBT bt, PetscInt idxlvl_prow)
1149: {
1150: PetscFunctionBegin;
1151: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, idxlvl_prow, PETSC_TRUE));
1152: PetscFunctionReturn(PETSC_SUCCESS);
1153: }
1155: /*
1156: Add a SORTED index set into a sorted linked list for ILU
1157: Input Parameters:
1158: nidx - number of input indices
1159: idx - sorted integer array used for storing column indices
1160: level - level of fill, e.g., ICC(level)
1161: idxlvl - level of idx
1162: idx_start - starting index of the list
1163: lnk - linked list(an integer array) that is created
1164: lnklvl - levels of lnk
1165: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1166: prow - the row number of idx
1167: output Parameters:
1168: nlnk - number of newly added idx
1169: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1170: lnklvl - levels of lnk
1171: bt - updated PetscBT (bitarray)
1173: Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1174: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1175: */
1176: static inline PetscErrorCode PetscILULLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT idx, PetscInt level, const PetscInt *PETSC_RESTRICT idxlvl, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscBT bt, PetscInt prow)
1177: {
1178: PetscFunctionBegin;
1179: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, lnklvl[prow], PETSC_TRUE));
1180: PetscFunctionReturn(PETSC_SUCCESS);
1181: }
1183: /*
1184: Add a index set into a sorted linked list
1185: Input Parameters:
1186: nidx - number of input idx
1187: idx - integer array used for storing column indices
1188: level - level of fill, e.g., ICC(level)
1189: idxlvl - level of idx
1190: idx_start - starting index of the list
1191: lnk - linked list(an integer array) that is created
1192: lnklvl - levels of lnk
1193: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1194: output Parameters:
1195: nlnk - number of newly added idx
1196: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1197: lnklvl - levels of lnk
1198: bt - updated PetscBT (bitarray)
1199: */
1200: static inline PetscErrorCode PetscIncompleteLLAdd(PetscInt nidx, const PetscInt *PETSC_RESTRICT idx, PetscReal level, const PetscInt *PETSC_RESTRICT idxlvl, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscBT bt)
1201: {
1202: PetscFunctionBegin;
1203: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_FALSE));
1204: PetscFunctionReturn(PETSC_SUCCESS);
1205: }
1207: /*
1208: Add a SORTED index set into a sorted linked list
1209: Input Parameters:
1210: nidx - number of input indices
1211: idx - sorted integer array used for storing column indices
1212: level - level of fill, e.g., ICC(level)
1213: idxlvl - level of idx
1214: idx_start - starting index of the list
1215: lnk - linked list(an integer array) that is created
1216: lnklvl - levels of lnk
1217: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1218: output Parameters:
1219: nlnk - number of newly added idx
1220: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1221: lnklvl - levels of lnk
1222: bt - updated PetscBT (bitarray)
1223: */
1224: static inline PetscErrorCode PetscIncompleteLLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT idx, PetscReal level, const PetscInt *PETSC_RESTRICT idxlvl, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscBT bt)
1225: {
1226: PetscFunctionBegin;
1227: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_TRUE));
1228: PetscFunctionReturn(PETSC_SUCCESS);
1229: }
1231: /*
1232: Copy data on the list into an array, then initialize the list
1233: Input Parameters:
1234: idx_start - starting index of the list
1235: lnk_max - max value of lnk indicating the end of the list
1236: nlnk - number of data on the list to be copied
1237: lnk - linked list
1238: lnklvl - level of lnk
1239: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1240: output Parameters:
1241: indices - array that contains the copied data
1242: lnk - linked list that is cleaned and initialize
1243: lnklvl - level of lnk that is reinitialized
1244: bt - PetscBT (bitarray) with all bits set to false
1245: */
1246: static inline PetscErrorCode PetscIncompleteLLClean(PetscInt idx_start, PetscInt lnk_max, PetscInt nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT lnklvl, PetscInt *PETSC_RESTRICT indices, PetscInt *PETSC_RESTRICT indiceslvl, PetscBT bt)
1247: {
1248: PetscFunctionBegin;
1249: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1250: idx = lnk[idx];
1251: indices[j] = idx;
1252: indiceslvl[j] = lnklvl[idx];
1253: lnklvl[idx] = -1;
1254: PetscCall(PetscBTClear(bt, idx));
1255: }
1256: lnk[idx_start] = lnk_max;
1257: PetscFunctionReturn(PETSC_SUCCESS);
1258: }
1260: /*
1261: Free memories used by the list
1262: */
1263: #define PetscIncompleteLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1265: #if !defined(PETSC_CLANG_STATIC_ANALYZER)
1266: #define MatCheckSameLocalSize(A, ar1, B, ar2) \
1267: do { \
1268: PetscCheckSameComm(A, ar1, B, ar2); \
1269: PetscCheck(((A)->rmap->n == (B)->rmap->n) && ((A)->cmap->n == (B)->cmap->n), PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Incompatible matrix local sizes: parameter # %d (%" PetscInt_FMT " x %" PetscInt_FMT ") != parameter # %d (%" PetscInt_FMT " x %" PetscInt_FMT ")", ar1, \
1270: (A)->rmap->n, (A)->cmap->n, ar2, (B)->rmap->n, (B)->cmap->n); \
1271: } while (0)
1272: #define MatCheckSameSize(A, ar1, B, ar2) \
1273: do { \
1274: PetscCheck(((A)->rmap->N == (B)->rmap->N) && ((A)->cmap->N == (B)->cmap->N), PetscObjectComm((PetscObject)(A)), PETSC_ERR_ARG_INCOMP, "Incompatible matrix global sizes: parameter # %d (%" PetscInt_FMT " x %" PetscInt_FMT ") != parameter # %d (%" PetscInt_FMT " x %" PetscInt_FMT ")", ar1, \
1275: (A)->rmap->N, (A)->cmap->N, ar2, (B)->rmap->N, (B)->cmap->N); \
1276: MatCheckSameLocalSize(A, ar1, B, ar2); \
1277: } while (0)
1278: #else
1279: template <typename Tm>
1280: extern void MatCheckSameLocalSize(Tm, int, Tm, int);
1281: template <typename Tm>
1282: extern void MatCheckSameSize(Tm, int, Tm, int);
1283: #endif
1285: #define VecCheckMatCompatible(M, x, ar1, b, ar2) \
1286: do { \
1287: PetscCheck((M)->cmap->N == (x)->map->N, PetscObjectComm((PetscObject)(M)), PETSC_ERR_ARG_SIZ, "Vector global length incompatible with matrix: parameter # %d global size %" PetscInt_FMT " != matrix column global size %" PetscInt_FMT, ar1, (x)->map->N, \
1288: (M)->cmap->N); \
1289: PetscCheck((M)->rmap->N == (b)->map->N, PetscObjectComm((PetscObject)(M)), PETSC_ERR_ARG_SIZ, "Vector global length incompatible with matrix: parameter # %d global size %" PetscInt_FMT " != matrix row global size %" PetscInt_FMT, ar2, (b)->map->N, \
1290: (M)->rmap->N); \
1291: } while (0)
1293: /* -------------------------------------------------------------------------------------------------------*/
1294: /*
1295: Create and initialize a condensed linked list -
1296: same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1297: Barry suggested this approach (Dec. 6, 2011):
1298: I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1299: (it may be faster than the O(N) even sequentially due to less crazy memory access).
1301: 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
1302: 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
1303: 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
1304: 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.
1305: 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
1306: to each other so memory access is much better than using the big array.
1308: Example:
1309: nlnk_max=5, lnk_max=36:
1310: Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1311: here, head_node has index 2 with value lnk[2]=lnk_max=36,
1312: 0-th entry is used to store the number of entries in the list,
1313: The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.
1315: Now adding a sorted set {2,4}, the list becomes
1316: [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1317: represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.
1319: Then adding a sorted set {0,3,35}, the list
1320: [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1321: represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.
1323: Input Parameters:
1324: nlnk_max - max length of the list
1325: lnk_max - max value of the entries
1326: Output Parameters:
1327: lnk - list created and initialized
1328: bt - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1329: */
1330: static inline PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max, PetscInt lnk_max, PetscInt **lnk, PetscBT *bt)
1331: {
1332: PetscInt *llnk, lsize = 0;
1334: PetscFunctionBegin;
1335: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1336: PetscCall(PetscMalloc1(lsize, lnk));
1337: PetscCall(PetscBTCreate(lnk_max, bt));
1338: llnk = *lnk;
1339: llnk[0] = 0; /* number of entries on the list */
1340: llnk[2] = lnk_max; /* value in the head node */
1341: llnk[3] = 2; /* next for the head node */
1342: PetscFunctionReturn(PETSC_SUCCESS);
1343: }
1345: /*
1346: Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1347: Input Parameters:
1348: nidx - number of input indices
1349: indices - sorted integer array
1350: lnk - condensed linked list(an integer array) that is created
1351: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1352: output Parameters:
1353: lnk - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1354: bt - updated PetscBT (bitarray)
1355: */
1356: static inline PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx, const PetscInt indices[], PetscInt lnk[], PetscBT bt)
1357: {
1358: PetscInt location = 2; /* head */
1359: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1361: PetscFunctionBegin;
1362: for (PetscInt k = 0; k < nidx; k++) {
1363: const PetscInt entry = indices[k];
1364: if (!PetscBTLookupSet(bt, entry)) { /* new entry */
1365: PetscInt next, lnkdata;
1367: /* search for insertion location */
1368: do {
1369: next = location + 1; /* link from previous node to next node */
1370: location = lnk[next]; /* idx of next node */
1371: lnkdata = lnk[location]; /* value of next node */
1372: } while (entry > lnkdata);
1373: /* insertion location is found, add entry into lnk */
1374: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1375: lnk[next] = newnode; /* connect previous node to the new node */
1376: lnk[newnode] = entry; /* set value of the new node */
1377: lnk[newnode + 1] = location; /* connect new node to next node */
1378: location = newnode; /* next search starts from the new node */
1379: nlnk++;
1380: }
1381: }
1382: lnk[0] = nlnk; /* number of entries in the list */
1383: PetscFunctionReturn(PETSC_SUCCESS);
1384: }
1386: static inline PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max, PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt lnk[], PetscBT bt)
1387: {
1388: const PetscInt nlnk = lnk[0]; /* num of entries on the list */
1389: PetscInt next = lnk[3]; /* head node */
1391: PetscFunctionBegin;
1392: for (PetscInt k = 0; k < nlnk; k++) {
1393: indices[k] = lnk[next];
1394: next = lnk[next + 1];
1395: PetscCall(PetscBTClear(bt, indices[k]));
1396: }
1397: lnk[0] = 0; /* num of entries on the list */
1398: lnk[2] = lnk_max; /* initialize head node */
1399: lnk[3] = 2; /* head node */
1400: PetscFunctionReturn(PETSC_SUCCESS);
1401: }
1403: static inline PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1404: {
1405: PetscFunctionBegin;
1406: PetscCall(PetscPrintf(PETSC_COMM_SELF, "LLCondensed of size %" PetscInt_FMT ", (val, next)\n", lnk[0]));
1407: for (PetscInt k = 2; k < lnk[0] + 2; ++k) PetscCall(PetscPrintf(PETSC_COMM_SELF, " %" PetscInt_FMT ": (%" PetscInt_FMT ", %" PetscInt_FMT ")\n", 2 * k, lnk[2 * k], lnk[2 * k + 1]));
1408: PetscFunctionReturn(PETSC_SUCCESS);
1409: }
1411: /*
1412: Free memories used by the list
1413: */
1414: static inline PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk, PetscBT bt)
1415: {
1416: PetscFunctionBegin;
1417: PetscCall(PetscFree(lnk));
1418: PetscCall(PetscBTDestroy(&bt));
1419: PetscFunctionReturn(PETSC_SUCCESS);
1420: }
1422: /* -------------------------------------------------------------------------------------------------------*/
1423: /*
1424: Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1425: Input Parameters:
1426: nlnk_max - max length of the list
1427: Output Parameters:
1428: lnk - list created and initialized
1429: */
1430: static inline PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1431: {
1432: PetscInt *llnk, lsize = 0;
1434: PetscFunctionBegin;
1435: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1436: PetscCall(PetscMalloc1(lsize, lnk));
1437: llnk = *lnk;
1438: llnk[0] = 0; /* number of entries on the list */
1439: llnk[2] = PETSC_MAX_INT; /* value in the head node */
1440: llnk[3] = 2; /* next for the head node */
1441: PetscFunctionReturn(PETSC_SUCCESS);
1442: }
1444: static inline PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1445: {
1446: PetscInt lsize = 0;
1448: PetscFunctionBegin;
1449: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1450: PetscCall(PetscRealloc(lsize * sizeof(PetscInt), lnk));
1451: PetscFunctionReturn(PETSC_SUCCESS);
1452: }
1454: static inline PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1455: {
1456: PetscInt location = 2; /* head */
1457: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1459: for (PetscInt k = 0; k < nidx; k++) {
1460: const PetscInt entry = indices[k];
1461: PetscInt next, lnkdata;
1463: /* search for insertion location */
1464: do {
1465: next = location + 1; /* link from previous node to next node */
1466: location = lnk[next]; /* idx of next node */
1467: lnkdata = lnk[location]; /* value of next node */
1468: } while (entry > lnkdata);
1469: if (entry < lnkdata) {
1470: /* insertion location is found, add entry into lnk */
1471: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1472: lnk[next] = newnode; /* connect previous node to the new node */
1473: lnk[newnode] = entry; /* set value of the new node */
1474: lnk[newnode + 1] = location; /* connect new node to next node */
1475: location = newnode; /* next search starts from the new node */
1476: nlnk++;
1477: }
1478: }
1479: lnk[0] = nlnk; /* number of entries in the list */
1480: return PETSC_SUCCESS;
1481: }
1483: static inline PetscErrorCode PetscLLCondensedClean_Scalable(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1484: {
1485: const PetscInt nlnk = lnk[0];
1486: PetscInt next = lnk[3]; /* head node */
1488: for (PetscInt k = 0; k < nlnk; k++) {
1489: indices[k] = lnk[next];
1490: next = lnk[next + 1];
1491: }
1492: lnk[0] = 0; /* num of entries on the list */
1493: lnk[3] = 2; /* head node */
1494: return PETSC_SUCCESS;
1495: }
1497: static inline PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1498: {
1499: return PetscFree(lnk);
1500: }
1502: /* -------------------------------------------------------------------------------------------------------*/
1503: /*
1504: lnk[0] number of links
1505: lnk[1] number of entries
1506: lnk[3n] value
1507: lnk[3n+1] len
1508: lnk[3n+2] link to next value
1510: The next three are always the first link
1512: lnk[3] PETSC_MIN_INT+1
1513: lnk[4] 1
1514: lnk[5] link to first real entry
1516: The next three are always the last link
1518: lnk[6] PETSC_MAX_INT - 1
1519: lnk[7] 1
1520: lnk[8] next valid link (this is the same as lnk[0] but without the decreases)
1521: */
1523: static inline PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max, PetscInt **lnk)
1524: {
1525: PetscInt *llnk;
1526: PetscInt lsize = 0;
1528: PetscFunctionBegin;
1529: PetscCall(PetscIntMultError(3, nlnk_max + 3, &lsize));
1530: PetscCall(PetscMalloc1(lsize, lnk));
1531: llnk = *lnk;
1532: llnk[0] = 0; /* nlnk: number of entries on the list */
1533: llnk[1] = 0; /* number of integer entries represented in list */
1534: llnk[3] = PETSC_MIN_INT + 1; /* value in the first node */
1535: llnk[4] = 1; /* count for the first node */
1536: llnk[5] = 6; /* next for the first node */
1537: llnk[6] = PETSC_MAX_INT - 1; /* value in the last node */
1538: llnk[7] = 1; /* count for the last node */
1539: llnk[8] = 0; /* next valid node to be used */
1540: PetscFunctionReturn(PETSC_SUCCESS);
1541: }
1543: static inline PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1544: {
1545: for (PetscInt k = 0, prev = 3 /* first value */; k < nidx; k++) {
1546: const PetscInt entry = indices[k];
1547: PetscInt next = lnk[prev + 2];
1549: /* search for insertion location */
1550: while (entry >= lnk[next]) {
1551: prev = next;
1552: next = lnk[next + 2];
1553: }
1554: /* entry is in range of previous list */
1555: if (entry < lnk[prev] + lnk[prev + 1]) continue;
1556: lnk[1]++;
1557: /* entry is right after previous list */
1558: if (entry == lnk[prev] + lnk[prev + 1]) {
1559: lnk[prev + 1]++;
1560: if (lnk[next] == entry + 1) { /* combine two contiguous strings */
1561: lnk[prev + 1] += lnk[next + 1];
1562: lnk[prev + 2] = lnk[next + 2];
1563: next = lnk[next + 2];
1564: lnk[0]--;
1565: }
1566: continue;
1567: }
1568: /* entry is right before next list */
1569: if (entry == lnk[next] - 1) {
1570: lnk[next]--;
1571: lnk[next + 1]++;
1572: prev = next;
1573: next = lnk[prev + 2];
1574: continue;
1575: }
1576: /* add entry into lnk */
1577: lnk[prev + 2] = 3 * ((lnk[8]++) + 3); /* connect previous node to the new node */
1578: prev = lnk[prev + 2];
1579: lnk[prev] = entry; /* set value of the new node */
1580: lnk[prev + 1] = 1; /* number of values in contiguous string is one to start */
1581: lnk[prev + 2] = next; /* connect new node to next node */
1582: lnk[0]++;
1583: }
1584: return PETSC_SUCCESS;
1585: }
1587: static inline PetscErrorCode PetscLLCondensedClean_fast(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1588: {
1589: const PetscInt nlnk = lnk[0];
1590: PetscInt next = lnk[5]; /* first node */
1592: for (PetscInt k = 0, cnt = 0; k < nlnk; k++) {
1593: for (PetscInt j = 0; j < lnk[next + 1]; j++) indices[cnt++] = lnk[next] + j;
1594: next = lnk[next + 2];
1595: }
1596: lnk[0] = 0; /* nlnk: number of links */
1597: lnk[1] = 0; /* number of integer entries represented in list */
1598: lnk[3] = PETSC_MIN_INT + 1; /* value in the first node */
1599: lnk[4] = 1; /* count for the first node */
1600: lnk[5] = 6; /* next for the first node */
1601: lnk[6] = PETSC_MAX_INT - 1; /* value in the last node */
1602: lnk[7] = 1; /* count for the last node */
1603: lnk[8] = 0; /* next valid location to make link */
1604: return PETSC_SUCCESS;
1605: }
1607: static inline PetscErrorCode PetscLLCondensedView_fast(const PetscInt *lnk)
1608: {
1609: const PetscInt nlnk = lnk[0];
1610: PetscInt next = lnk[5]; /* first node */
1612: for (PetscInt k = 0; k < nlnk; k++) {
1613: #if 0 /* Debugging code */
1614: printf("%d value %d len %d next %d\n", next, lnk[next], lnk[next + 1], lnk[next + 2]);
1615: #endif
1616: next = lnk[next + 2];
1617: }
1618: return PETSC_SUCCESS;
1619: }
1621: static inline PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1622: {
1623: return PetscFree(lnk);
1624: }
1626: PETSC_EXTERN PetscErrorCode PetscCDCreate(PetscInt, PetscCoarsenData **);
1627: PETSC_EXTERN PetscErrorCode PetscCDDestroy(PetscCoarsenData *);
1628: PETSC_EXTERN PetscErrorCode PetscCDIntNdSetID(PetscCDIntNd *, PetscInt);
1629: PETSC_EXTERN PetscErrorCode PetscCDIntNdGetID(const PetscCDIntNd *, PetscInt *);
1630: PETSC_EXTERN PetscErrorCode PetscCDAppendID(PetscCoarsenData *, PetscInt, PetscInt);
1631: PETSC_EXTERN PetscErrorCode PetscCDMoveAppend(PetscCoarsenData *, PetscInt, PetscInt);
1632: PETSC_EXTERN PetscErrorCode PetscCDAppendNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1633: PETSC_EXTERN PetscErrorCode PetscCDRemoveNextNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1634: PETSC_EXTERN PetscErrorCode PetscCDCountAt(const PetscCoarsenData *, PetscInt, PetscInt *);
1635: PETSC_EXTERN PetscErrorCode PetscCDIsEmptyAt(const PetscCoarsenData *, PetscInt, PetscBool *);
1636: PETSC_EXTERN PetscErrorCode PetscCDSetChunkSize(PetscCoarsenData *, PetscInt);
1637: PETSC_EXTERN PetscErrorCode PetscCDPrint(const PetscCoarsenData *, PetscInt, MPI_Comm);
1638: PETSC_EXTERN PetscErrorCode PetscCDGetNonemptyIS(PetscCoarsenData *, IS *);
1639: PETSC_EXTERN PetscErrorCode PetscCDGetMat(PetscCoarsenData *, Mat *);
1640: PETSC_EXTERN PetscErrorCode PetscCDSetMat(PetscCoarsenData *, Mat);
1641: PETSC_EXTERN PetscErrorCode PetscCDClearMat(PetscCoarsenData *);
1642: PETSC_EXTERN PetscErrorCode PetscCDRemoveAllAt(PetscCoarsenData *, PetscInt);
1643: PETSC_EXTERN PetscErrorCode PetscCDCount(const PetscCoarsenData *, PetscInt *_sz);
1645: PETSC_EXTERN PetscErrorCode PetscCDGetHeadPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1646: PETSC_EXTERN PetscErrorCode PetscCDGetNextPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1647: PETSC_EXTERN PetscErrorCode PetscCDGetASMBlocks(const PetscCoarsenData *, const PetscInt, PetscInt *, IS **);
1649: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
1650: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat, MatFDColoring, Vec, void *);
1652: PETSC_EXTERN PetscLogEvent MAT_Mult;
1653: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1654: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1655: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTranspose;
1656: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1657: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTransposeAdd;
1658: PETSC_EXTERN PetscLogEvent MAT_Solve;
1659: PETSC_EXTERN PetscLogEvent MAT_Solves;
1660: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1661: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1662: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1663: PETSC_EXTERN PetscLogEvent MAT_SOR;
1664: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1665: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1666: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1667: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1668: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1669: PETSC_EXTERN PetscLogEvent MAT_QRFactor;
1670: PETSC_EXTERN PetscLogEvent MAT_QRFactorSymbolic;
1671: PETSC_EXTERN PetscLogEvent MAT_QRFactorNumeric;
1672: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1673: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1674: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1675: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1676: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1677: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1678: PETSC_EXTERN PetscLogEvent MAT_Copy;
1679: PETSC_EXTERN PetscLogEvent MAT_Convert;
1680: PETSC_EXTERN PetscLogEvent MAT_Scale;
1681: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1682: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1683: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1684: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1685: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1686: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1687: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1688: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1689: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1690: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1691: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1692: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1693: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1694: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1695: PETSC_EXTERN PetscLogEvent MAT_Load;
1696: PETSC_EXTERN PetscLogEvent MAT_View;
1697: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1698: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1699: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1700: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1701: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1702: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1703: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1704: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1705: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1706: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1707: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1708: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1709: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1710: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1711: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1712: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1713: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1714: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1715: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1716: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1717: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1718: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1719: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1720: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1721: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1722: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1723: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1724: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1725: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1726: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1727: PETSC_EXTERN PetscLogEvent MAT_GetSeqNonzeroStructure;
1728: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1729: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1730: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1731: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyFromGPU;
1732: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
1733: PETSC_EXTERN PetscLogEvent MAT_CUSPARSESolveAnalysis;
1734: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyToGPU;
1735: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyFromGPU;
1736: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSEGenerateTranspose;
1737: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSESolveAnalysis;
1738: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1739: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1740: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1741: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1742: PETSC_EXTERN PetscLogEvent MAT_Merge;
1743: PETSC_EXTERN PetscLogEvent MAT_Residual;
1744: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1745: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1746: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1747: PETSC_EXTERN PetscLogEvent MAT_PreallCOO;
1748: PETSC_EXTERN PetscLogEvent MAT_SetVCOO;
1749: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1750: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1751: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1752: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1753: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1754: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;
1755: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Build;
1756: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Compress;
1757: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Orthog;
1758: PETSC_EXTERN PetscLogEvent MAT_H2Opus_LR;
1759: PETSC_EXTERN PetscLogEvent MAT_CUDACopyToGPU;
1760: PETSC_EXTERN PetscLogEvent MAT_HIPCopyToGPU;