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: };
222: /*
223: If you add MatOps entries above also add them to the MATOP enum
224: in include/petscmat.h and src/mat/f90-mod/petscmat.h
225: */
227: #include <petscsys.h>
229: typedef struct _p_MatRootName *MatRootName;
230: struct _p_MatRootName {
231: char *rname, *sname, *mname;
232: MatRootName next;
233: };
235: PETSC_EXTERN MatRootName MatRootNameList;
237: /*
238: Utility private matrix routines used outside Mat
239: */
240: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat, PetscBool, PetscReal, IS *);
242: /*
243: Utility private matrix routines
244: */
245: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat, MatType, MatReuse, Mat *);
246: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat, MatType, MatReuse, Mat *);
247: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat, MatType, MatReuse, Mat *);
248: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat, Mat, MatStructure);
249: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat, Vec, InsertMode);
250: #if defined(PETSC_HAVE_SCALAPACK)
251: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
252: #endif
253: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_Basic(Mat, PetscCount, PetscInt[], PetscInt[]);
254: PETSC_INTERN PetscErrorCode MatSetValuesCOO_Basic(Mat, const PetscScalar[], InsertMode);
256: /* This can be moved to the public header after implementing some missing MatProducts */
257: PETSC_INTERN PetscErrorCode MatCreateFromISLocalToGlobalMapping(ISLocalToGlobalMapping, Mat, PetscBool, PetscBool, MatType, Mat *);
259: /* these callbacks rely on the old matrix function pointers for
260: matmat operations. They are unsafe, and should be removed.
261: However, the amount of work needed to clean up all the
262: implementations is not negligible */
263: PETSC_INTERN PetscErrorCode MatProductSymbolic_AB(Mat);
264: PETSC_INTERN PetscErrorCode MatProductNumeric_AB(Mat);
265: PETSC_INTERN PetscErrorCode MatProductSymbolic_AtB(Mat);
266: PETSC_INTERN PetscErrorCode MatProductNumeric_AtB(Mat);
267: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABt(Mat);
268: PETSC_INTERN PetscErrorCode MatProductNumeric_ABt(Mat);
269: PETSC_INTERN PetscErrorCode MatProductNumeric_PtAP(Mat);
270: PETSC_INTERN PetscErrorCode MatProductNumeric_RARt(Mat);
271: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC(Mat);
272: PETSC_INTERN PetscErrorCode MatProductNumeric_ABC(Mat);
274: PETSC_INTERN PetscErrorCode MatProductCreate_Private(Mat, Mat, Mat, Mat);
275: /* this callback handles all the different triple products and
276: does not rely on the function pointers; used by cuSPARSE/hipSPARSE and KOKKOS-KERNELS */
277: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC_Basic(Mat);
279: /* CreateGraph is common to AIJ seq and mpi */
280: PETSC_INTERN PetscErrorCode MatCreateGraph_Simple_AIJ(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
282: #if defined(PETSC_CLANG_STATIC_ANALYZER)
283: template <typename Tm>
284: extern void MatCheckPreallocated(Tm, int);
285: template <typename Tm>
286: extern void MatCheckProduct(Tm, int);
287: #else /* PETSC_CLANG_STATIC_ANALYZER */
288: #define MatCheckPreallocated(A, arg) \
289: do { \
290: if (!(A)->preallocated) PetscCall(MatSetUp(A)); \
291: } while (0)
293: #if defined(PETSC_USE_DEBUG)
294: #define MatCheckProduct(A, arg) \
295: do { \
296: PetscCheck((A)->product, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Argument %d \"%s\" is not a matrix obtained from MatProductCreate()", (arg), #A); \
297: } while (0)
298: #else
299: #define MatCheckProduct(A, arg) \
300: do { \
301: } while (0)
302: #endif
303: #endif /* PETSC_CLANG_STATIC_ANALYZER */
305: /*
306: The stash is used to temporarily store inserted matrix values that
307: belong to another processor. During the assembly phase the stashed
308: values are moved to the correct processor and
309: */
311: typedef struct _MatStashSpace *PetscMatStashSpace;
313: struct _MatStashSpace {
314: PetscMatStashSpace next;
315: PetscScalar *space_head, *val;
316: PetscInt *idx, *idy;
317: PetscInt total_space_size;
318: PetscInt local_used;
319: PetscInt local_remaining;
320: };
322: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt, PetscInt, PetscMatStashSpace *);
323: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt, PetscMatStashSpace *, PetscScalar *, PetscInt *, PetscInt *);
324: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace *);
326: typedef struct {
327: PetscInt count;
328: } MatStashHeader;
330: typedef struct {
331: void *buffer; /* Of type blocktype, dynamically constructed */
332: PetscInt count;
333: char pending;
334: } MatStashFrame;
336: typedef struct _MatStash MatStash;
337: struct _MatStash {
338: PetscInt nmax; /* maximum stash size */
339: PetscInt umax; /* user specified max-size */
340: PetscInt oldnmax; /* the nmax value used previously */
341: PetscInt n; /* stash size */
342: PetscInt bs; /* block size of the stash */
343: PetscInt reallocs; /* preserve the no of mallocs invoked */
344: PetscMatStashSpace space_head, space; /* linked list to hold stashed global row/column numbers and matrix values */
346: PetscErrorCode (*ScatterBegin)(Mat, MatStash *, PetscInt *);
347: PetscErrorCode (*ScatterGetMesg)(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
348: PetscErrorCode (*ScatterEnd)(MatStash *);
349: PetscErrorCode (*ScatterDestroy)(MatStash *);
351: /* The following variables are used for communication */
352: MPI_Comm comm;
353: PetscMPIInt size, rank;
354: PetscMPIInt tag1, tag2;
355: MPI_Request *send_waits; /* array of send requests */
356: MPI_Request *recv_waits; /* array of receive requests */
357: MPI_Status *send_status; /* array of send status */
358: PetscInt nsends, nrecvs; /* numbers of sends and receives */
359: PetscScalar *svalues; /* sending data */
360: PetscInt *sindices;
361: PetscScalar **rvalues; /* receiving data (values) */
362: PetscInt **rindices; /* receiving data (indices) */
363: PetscInt nprocessed; /* number of messages already processed */
364: PetscMPIInt *flg_v; /* indicates what messages have arrived so far and from whom */
365: PetscBool reproduce;
366: PetscInt reproduce_count;
368: /* The following variables are used for BTS communication */
369: PetscBool first_assembly_done; /* Is the first time matrix assembly done? */
370: PetscBool use_status; /* Use MPI_Status to determine number of items in each message */
371: PetscMPIInt nsendranks;
372: PetscMPIInt nrecvranks;
373: PetscMPIInt *sendranks;
374: PetscMPIInt *recvranks;
375: MatStashHeader *sendhdr, *recvhdr;
376: MatStashFrame *sendframes; /* pointers to the main messages */
377: MatStashFrame *recvframes;
378: MatStashFrame *recvframe_active;
379: PetscInt recvframe_i; /* index of block within active frame */
380: PetscMPIInt recvframe_count; /* Count actually sent for current frame */
381: PetscInt recvcount; /* Number of receives processed so far */
382: PetscMPIInt *some_indices; /* From last call to MPI_Waitsome */
383: MPI_Status *some_statuses; /* Statuses from last call to MPI_Waitsome */
384: PetscMPIInt some_count; /* Number of requests completed in last call to MPI_Waitsome */
385: PetscMPIInt some_i; /* Index of request currently being processed */
386: MPI_Request *sendreqs;
387: MPI_Request *recvreqs;
388: PetscSegBuffer segsendblocks;
389: PetscSegBuffer segrecvframe;
390: PetscSegBuffer segrecvblocks;
391: MPI_Datatype blocktype;
392: size_t blocktype_size;
393: InsertMode *insertmode; /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
394: };
396: #if !defined(PETSC_HAVE_MPIUNI)
397: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash *);
398: #endif
399: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm, PetscInt, MatStash *);
400: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash *);
401: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash *);
402: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash *, PetscInt);
403: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash *, PetscInt *, PetscInt *);
404: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscBool);
405: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscBool);
406: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
407: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
408: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat, MatStash *, PetscInt *);
409: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
410: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat, MatInfoType, MatInfo *);
412: typedef struct {
413: PetscInt dim;
414: PetscInt dims[4];
415: PetscInt starts[4];
416: PetscBool noc; /* this is a single component problem, hence user will not set MatStencil.c */
417: } MatStencilInfo;
419: /* Info about using compressed row format */
420: typedef struct {
421: PetscBool use; /* indicates compressed rows have been checked and will be used */
422: PetscInt nrows; /* number of non-zero rows */
423: PetscInt *i; /* compressed row pointer */
424: PetscInt *rindex; /* compressed row index */
425: } Mat_CompressedRow;
426: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat, PetscInt, Mat_CompressedRow *, PetscInt *, PetscInt, PetscReal);
428: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
429: PetscInt nzlocal, nsends, nrecvs;
430: PetscMPIInt *send_rank, *recv_rank;
431: PetscInt *sbuf_nz, *rbuf_nz, *sbuf_j, **rbuf_j;
432: PetscScalar *sbuf_a, **rbuf_a;
433: MPI_Comm subcomm; /* when user does not provide a subcomm */
434: IS isrow, iscol;
435: Mat *matseq;
436: } Mat_Redundant;
438: typedef struct { /* used by MatProduct() */
439: MatProductType type;
440: char *alg;
441: Mat A, B, C, Dwork;
442: 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, .. */
443: 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 .. */
444: PetscBool symbolic_used_the_fact_C_is_symmetric; /* MatMatMult(A,B,MAT_REUSE_MATRIX,..&C) is still legitimate), we need to redo symbolic! */
445: PetscReal fill;
446: 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 */
447: PetscBool setfromoptionscalled;
449: /* Some products may display the information on the algorithm used */
450: PetscErrorCode (*view)(Mat, PetscViewer);
452: /* many products have intermediate data structures, each specific to Mat types and product type */
453: PetscBool clear; /* whether or not to clear the data structures after MatProductNumeric has been called */
454: void *data; /* where to stash those structures */
455: PetscErrorCode (*destroy)(void *); /* destroy routine */
456: } Mat_Product;
458: struct _p_Mat {
459: PETSCHEADER(struct _MatOps);
460: PetscLayout rmap, cmap;
461: void *data; /* implementation-specific data */
462: MatFactorType factortype; /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
463: PetscBool trivialsymbolic; /* indicates the symbolic factorization doesn't actually do a symbolic factorization, it is delayed to the numeric factorization */
464: PetscBool canuseordering; /* factorization can use ordering provide to routine (most PETSc implementations) */
465: MatOrderingType preferredordering[MAT_FACTOR_NUM_TYPES]; /* what is the preferred (or default) ordering for the matrix solver type */
466: PetscBool assembled; /* is the matrix assembled? */
467: PetscBool was_assembled; /* new values inserted into assembled mat */
468: PetscInt num_ass; /* number of times matrix has been assembled */
469: PetscObjectState nonzerostate; /* each time new nonzeros locations are introduced into the matrix this is updated */
470: PetscObjectState ass_nonzerostate; /* nonzero state at last assembly */
471: MatInfo info; /* matrix information */
472: InsertMode insertmode; /* have values been inserted in matrix or added? */
473: MatStash stash, bstash; /* used for assembling off-proc mat emements */
474: MatNullSpace nullsp; /* null space (operator is singular) */
475: MatNullSpace transnullsp; /* null space of transpose of operator */
476: MatNullSpace nearnullsp; /* near null space to be used by multigrid methods */
477: PetscInt congruentlayouts; /* are the rows and columns layouts congruent? */
478: PetscBool preallocated;
479: MatStencilInfo stencil; /* information for structured grid */
480: PetscBool3 symmetric, hermitian, structurally_symmetric, spd;
481: PetscBool symmetry_eternal, structural_symmetry_eternal, spd_eternal;
482: PetscBool nooffprocentries, nooffproczerorows;
483: PetscBool assembly_subset; /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
484: PetscBool submat_singleis; /* for efficient PCSetUp_ASM() */
485: PetscBool structure_only;
486: PetscBool sortedfull; /* full, sorted rows are inserted */
487: PetscBool force_diagonals; /* set by MAT_FORCE_DIAGONAL_ENTRIES */
488: #if defined(PETSC_HAVE_DEVICE)
489: PetscOffloadMask offloadmask; /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
490: PetscBool boundtocpu;
491: PetscBool bindingpropagates;
492: #endif
493: char *defaultrandtype;
494: void *spptr; /* pointer for special library like SuperLU */
495: char *solvertype;
496: PetscBool checksymmetryonassembly, checknullspaceonassembly;
497: PetscReal checksymmetrytol;
498: Mat schur; /* Schur complement matrix */
499: MatFactorSchurStatus schur_status; /* status of the Schur complement matrix */
500: Mat_Redundant *redundant; /* used by MatCreateRedundantMatrix() */
501: PetscBool erroriffailure; /* Generate an error if detected (for example a zero pivot) instead of returning */
502: MatFactorError factorerrortype; /* type of error in factorization */
503: PetscReal factorerror_zeropivot_value; /* If numerical zero pivot was detected this is the computed value */
504: PetscInt factorerror_zeropivot_row; /* Row where zero pivot was detected */
505: PetscInt nblocks, *bsizes; /* support for MatSetVariableBlockSizes() */
506: PetscInt p_cstart, p_rank, p_cend, n_rank; /* Information from parallel MatComputeVariableBlockEnvelope() */
507: PetscBool p_parallel;
508: char *defaultvectype;
509: Mat_Product *product;
510: PetscBool form_explicit_transpose; /* hint to generate an explicit mat tranpsose for operations like MatMultTranspose() */
511: PetscBool transupdated; /* whether or not the explicitly generated transpose is up-to-date */
512: char *factorprefix; /* the prefix to use with factored matrix that is created */
513: PetscBool hash_active; /* indicates MatSetValues() is being handled by hashing */
514: };
516: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat, PetscScalar, Mat, MatStructure);
517: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat, Mat, PetscScalar, Mat, MatStructure);
518: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat, Mat, Mat *);
519: PETSC_INTERN PetscErrorCode MatAXPY_Dense_Nest(Mat, PetscScalar, Mat);
521: PETSC_INTERN PetscErrorCode MatSetUp_Default(Mat);
523: /*
524: Utility for MatZeroRows
525: */
526: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat, PetscInt, const PetscInt *, PetscInt *, PetscInt **);
528: /*
529: Utility for MatView/MatLoad
530: */
531: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat, PetscViewer);
532: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat, PetscViewer);
534: /*
535: Object for partitioning graphs
536: */
538: typedef struct _MatPartitioningOps *MatPartitioningOps;
539: struct _MatPartitioningOps {
540: PetscErrorCode (*apply)(MatPartitioning, IS *);
541: PetscErrorCode (*applynd)(MatPartitioning, IS *);
542: PetscErrorCode (*setfromoptions)(MatPartitioning, PetscOptionItems *);
543: PetscErrorCode (*destroy)(MatPartitioning);
544: PetscErrorCode (*view)(MatPartitioning, PetscViewer);
545: PetscErrorCode (*improve)(MatPartitioning, IS *);
546: };
548: struct _p_MatPartitioning {
549: PETSCHEADER(struct _MatPartitioningOps);
550: Mat adj;
551: PetscInt *vertex_weights;
552: PetscReal *part_weights;
553: PetscInt n; /* number of partitions */
554: PetscInt ncon; /* number of vertex weights per vertex */
555: void *data;
556: PetscInt setupcalled;
557: PetscBool use_edge_weights; /* A flag indicates whether or not to use edge weights */
558: };
560: /* needed for parallel nested dissection by ParMetis and PTSCOTCH */
561: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt, PetscInt[], PetscInt[], PetscInt[]);
563: /*
564: Object for coarsen graphs
565: */
566: typedef struct _MatCoarsenOps *MatCoarsenOps;
567: struct _MatCoarsenOps {
568: PetscErrorCode (*apply)(MatCoarsen);
569: PetscErrorCode (*setfromoptions)(MatCoarsen, PetscOptionItems *);
570: PetscErrorCode (*destroy)(MatCoarsen);
571: PetscErrorCode (*view)(MatCoarsen, PetscViewer);
572: };
574: #define MAT_COARSEN_STRENGTH_INDEX_SIZE 3
575: struct _p_MatCoarsen {
576: PETSCHEADER(struct _MatCoarsenOps);
577: Mat graph;
578: void *subctx;
579: /* */
580: PetscBool strict_aggs;
581: IS perm;
582: PetscCoarsenData *agg_lists;
583: PetscInt max_it; /* number of iterations in HEM */
584: PetscReal threshold; /* HEM can filter interim graphs */
585: PetscInt strength_index_size;
586: PetscInt strength_index[MAT_COARSEN_STRENGTH_INDEX_SIZE];
587: };
589: PETSC_EXTERN PetscErrorCode MatCoarsenMISKSetDistance(MatCoarsen, PetscInt);
590: PETSC_EXTERN PetscErrorCode MatCoarsenMISKGetDistance(MatCoarsen, PetscInt *);
592: /*
593: Used in aijdevice.h
594: */
595: typedef struct {
596: PetscInt *i;
597: PetscInt *j;
598: PetscScalar *a;
599: PetscInt n;
600: PetscInt ignorezeroentries;
601: } PetscCSRDataStructure;
603: /*
604: MatFDColoring is used to compute Jacobian matrices efficiently
605: via coloring. The data structure is explained below in an example.
607: Color = 0 1 0 2 | 2 3 0
608: ---------------------------------------------------
609: 00 01 | 05
610: 10 11 | 14 15 Processor 0
611: 22 23 | 25
612: 32 33 |
613: ===================================================
614: | 44 45 46
615: 50 | 55 Processor 1
616: | 64 66
617: ---------------------------------------------------
619: ncolors = 4;
621: ncolumns = {2,1,1,0}
622: columns = {{0,2},{1},{3},{}}
623: nrows = {4,2,3,3}
624: rows = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
625: vwscale = {dx(0),dx(1),dx(2),dx(3)} MPI Vec
626: vscale = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)} Seq Vec
628: ncolumns = {1,0,1,1}
629: columns = {{6},{},{4},{5}}
630: nrows = {3,0,2,2}
631: rows = {{0,1,2},{},{1,2},{1,2}}
632: vwscale = {dx(4),dx(5),dx(6)} MPI Vec
633: vscale = {dx(0),dx(4),dx(5),dx(6)} Seq Vec
635: See the routine MatFDColoringApply() for how this data is used
636: to compute the Jacobian.
638: */
639: typedef struct {
640: PetscInt row;
641: PetscInt col;
642: PetscScalar *valaddr; /* address of value */
643: } MatEntry;
645: typedef struct {
646: PetscInt row;
647: PetscScalar *valaddr; /* address of value */
648: } MatEntry2;
650: struct _p_MatFDColoring {
651: PETSCHEADER(int);
652: PetscInt M, N, m; /* total rows, columns; local rows */
653: PetscInt rstart; /* first row owned by local processor */
654: PetscInt ncolors; /* number of colors */
655: PetscInt *ncolumns; /* number of local columns for a color */
656: PetscInt **columns; /* lists the local columns of each color (using global column numbering) */
657: IS *isa; /* these are the IS that contain the column values given in columns */
658: PetscInt *nrows; /* number of local rows for each color */
659: MatEntry *matentry; /* holds (row, column, address of value) for Jacobian matrix entry */
660: MatEntry2 *matentry2; /* holds (row, address of value) for Jacobian matrix entry */
661: PetscScalar *dy; /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
662: PetscReal error_rel; /* square root of relative error in computing function */
663: PetscReal umin; /* minimum allowable u'dx value */
664: Vec w1, w2, w3; /* work vectors used in computing Jacobian */
665: PetscBool fset; /* indicates that the initial function value F(X) is set */
666: PetscErrorCode (*f)(void); /* function that defines Jacobian */
667: void *fctx; /* optional user-defined context for use by the function f */
668: Vec vscale; /* holds FD scaling, i.e. 1/dx for each perturbed column */
669: PetscInt currentcolor; /* color for which function evaluation is being done now */
670: const char *htype; /* "wp" or "ds" */
671: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
672: PetscInt brows, bcols; /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
673: PetscBool setupcalled; /* true if setup has been called */
674: PetscBool viewed; /* true if the -mat_fd_coloring_view has been triggered already */
675: void (*ftn_func_pointer)(void), *ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
676: PetscObjectId matid; /* matrix this object was created with, must always be the same */
677: };
679: typedef struct _MatColoringOps *MatColoringOps;
680: struct _MatColoringOps {
681: PetscErrorCode (*destroy)(MatColoring);
682: PetscErrorCode (*setfromoptions)(MatColoring, PetscOptionItems *);
683: PetscErrorCode (*view)(MatColoring, PetscViewer);
684: PetscErrorCode (*apply)(MatColoring, ISColoring *);
685: PetscErrorCode (*weights)(MatColoring, PetscReal **, PetscInt **);
686: };
688: struct _p_MatColoring {
689: PETSCHEADER(struct _MatColoringOps);
690: Mat mat;
691: PetscInt dist; /* distance of the coloring */
692: PetscInt maxcolors; /* the maximum number of colors returned, maxcolors=1 for MIS */
693: void *data; /* inner context */
694: PetscBool valid; /* check to see if what is produced is a valid coloring */
695: MatColoringWeightType weight_type; /* type of weight computation to be performed */
696: PetscReal *user_weights; /* custom weights and permutation */
697: PetscInt *user_lperm;
698: PetscBool valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
699: };
701: struct _p_MatTransposeColoring {
702: PETSCHEADER(int);
703: PetscInt M, N, m; /* total rows, columns; local rows */
704: PetscInt rstart; /* first row owned by local processor */
705: PetscInt ncolors; /* number of colors */
706: PetscInt *ncolumns; /* number of local columns for a color */
707: PetscInt *nrows; /* number of local rows for each color */
708: PetscInt currentcolor; /* color for which function evaluation is being done now */
709: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
711: PetscInt *colorforrow, *colorforcol; /* pointer to rows and columns */
712: PetscInt *rows; /* lists the local rows for each color (using the local row numbering) */
713: PetscInt *den2sp; /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
714: PetscInt *columns; /* lists the local columns of each color (using global column numbering) */
715: PetscInt brows; /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
716: PetscInt *lstart; /* array used for loop over row blocks of Csparse */
717: };
719: /*
720: Null space context for preconditioner/operators
721: */
722: struct _p_MatNullSpace {
723: PETSCHEADER(int);
724: PetscBool has_cnst;
725: PetscInt n;
726: Vec *vecs;
727: PetscScalar *alpha; /* for projections */
728: PetscErrorCode (*remove)(MatNullSpace, Vec, void *); /* for user provided removal function */
729: void *rmctx; /* context for remove() function */
730: };
732: /*
733: Checking zero pivot for LU, ILU preconditioners.
734: */
735: typedef struct {
736: PetscInt nshift, nshift_max;
737: PetscReal shift_amount, shift_lo, shift_hi, shift_top, shift_fraction;
738: PetscBool newshift;
739: PetscReal rs; /* active row sum of abs(off-diagonals) */
740: PetscScalar pv; /* pivot of the active row */
741: } FactorShiftCtx;
743: PETSC_EXTERN PetscErrorCode MatTransposeCheckNonzeroState_Private(Mat, Mat);
745: /*
746: Used by MatTranspose() and potentially other functions to track the matrix used in the generation of another matrix
747: */
748: typedef struct {
749: PetscObjectId id;
750: PetscObjectState state;
751: PetscObjectState nonzerostate;
752: } MatParentState;
754: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
755: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat, PetscInt, PetscInt);
757: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatShift_Basic(Mat, PetscScalar);
759: static inline PetscErrorCode MatPivotCheck_nz(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
760: {
761: PetscReal _rs = sctx->rs;
762: PetscReal _zero = info->zeropivot * _rs;
764: PetscFunctionBegin;
765: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
766: /* force |diag| > zeropivot*rs */
767: if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
768: else sctx->shift_amount *= 2.0;
769: sctx->newshift = PETSC_TRUE;
770: (sctx->nshift)++;
771: } else {
772: sctx->newshift = PETSC_FALSE;
773: }
774: PetscFunctionReturn(PETSC_SUCCESS);
775: }
777: static inline PetscErrorCode MatPivotCheck_pd(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
778: {
779: PetscReal _rs = sctx->rs;
780: PetscReal _zero = info->zeropivot * _rs;
782: PetscFunctionBegin;
783: if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
784: /* force matfactor to be diagonally dominant */
785: if (sctx->nshift == sctx->nshift_max) {
786: sctx->shift_fraction = sctx->shift_hi;
787: } else {
788: sctx->shift_lo = sctx->shift_fraction;
789: sctx->shift_fraction = (sctx->shift_hi + sctx->shift_lo) / (PetscReal)2.;
790: }
791: sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
792: sctx->nshift++;
793: sctx->newshift = PETSC_TRUE;
794: } else {
795: sctx->newshift = PETSC_FALSE;
796: }
797: PetscFunctionReturn(PETSC_SUCCESS);
798: }
800: static inline PetscErrorCode MatPivotCheck_inblocks(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
801: {
802: PetscReal _zero = info->zeropivot;
804: PetscFunctionBegin;
805: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
806: sctx->pv += info->shiftamount;
807: sctx->shift_amount = 0.0;
808: sctx->nshift++;
809: }
810: sctx->newshift = PETSC_FALSE;
811: PetscFunctionReturn(PETSC_SUCCESS);
812: }
814: static inline PetscErrorCode MatPivotCheck_none(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
815: {
816: PetscReal _zero = info->zeropivot;
818: PetscFunctionBegin;
819: sctx->newshift = PETSC_FALSE;
820: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
821: 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);
822: PetscCall(PetscInfo(mat, "Detected zero pivot in factorization in row %" PetscInt_FMT " value %g tolerance %g\n", row, (double)PetscAbsScalar(sctx->pv), (double)_zero));
823: fact->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
824: fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
825: fact->factorerror_zeropivot_row = row;
826: }
827: PetscFunctionReturn(PETSC_SUCCESS);
828: }
830: static inline PetscErrorCode MatPivotCheck(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
831: {
832: PetscFunctionBegin;
833: if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) PetscCall(MatPivotCheck_nz(mat, info, sctx, row));
834: else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) PetscCall(MatPivotCheck_pd(mat, info, sctx, row));
835: else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) PetscCall(MatPivotCheck_inblocks(mat, info, sctx, row));
836: else PetscCall(MatPivotCheck_none(fact, mat, info, sctx, row));
837: PetscFunctionReturn(PETSC_SUCCESS);
838: }
840: #include <petscbt.h>
841: /*
842: Create and initialize a linked list
843: Input Parameters:
844: idx_start - starting index of the list
845: lnk_max - max value of lnk indicating the end of the list
846: nlnk - max length of the list
847: Output Parameters:
848: lnk - list initialized
849: bt - PetscBT (bitarray) with all bits set to false
850: lnk_empty - flg indicating the list is empty
851: */
852: #define PetscLLCreate(idx_start, lnk_max, nlnk, lnk, bt) ((PetscErrorCode)(PetscMalloc1(nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, PETSC_SUCCESS)))
854: #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)))
856: 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)
857: {
858: PetscInt location;
860: PetscFunctionBegin;
861: /* start from the beginning if entry < previous entry */
862: if (!assume_sorted && k && entry < *lnkdata) *lnkdata = idx_start;
863: /* search for insertion location */
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: PetscFunctionReturn(PETSC_SUCCESS);
874: }
876: 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)
877: {
878: PetscFunctionBegin;
879: *nlnk = 0;
880: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
881: const PetscInt entry = indices[k];
883: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk));
884: }
885: PetscFunctionReturn(PETSC_SUCCESS);
886: }
888: /*
889: Add an index set into a sorted linked list
890: Input Parameters:
891: nidx - number of input indices
892: indices - integer array
893: idx_start - starting index of the list
894: lnk - linked list(an integer array) that is created
895: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
896: output Parameters:
897: nlnk - number of newly added indices
898: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
899: bt - updated PetscBT (bitarray)
900: */
901: static inline PetscErrorCode PetscLLAdd(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
902: {
903: PetscFunctionBegin;
904: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_FALSE));
905: PetscFunctionReturn(PETSC_SUCCESS);
906: }
908: /*
909: Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata = idx_start;'
910: Input Parameters:
911: nidx - number of input indices
912: indices - sorted integer array
913: idx_start - starting index of the list
914: lnk - linked list(an integer array) that is created
915: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
916: output Parameters:
917: nlnk - number of newly added indices
918: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
919: bt - updated PetscBT (bitarray)
920: */
921: static inline PetscErrorCode PetscLLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
922: {
923: PetscFunctionBegin;
924: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_TRUE));
925: PetscFunctionReturn(PETSC_SUCCESS);
926: }
928: /*
929: Add a permuted index set into a sorted linked list
930: Input Parameters:
931: nidx - number of input indices
932: indices - integer array
933: perm - permutation of indices
934: idx_start - starting index of the list
935: lnk - linked list(an integer array) that is created
936: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
937: output Parameters:
938: nlnk - number of newly added indices
939: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
940: bt - updated PetscBT (bitarray)
941: */
942: 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)
943: {
944: PetscFunctionBegin;
945: *nlnk = 0;
946: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
947: const PetscInt entry = perm[indices[k]];
949: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk));
950: }
951: PetscFunctionReturn(PETSC_SUCCESS);
952: }
954: #if 0
955: /* this appears to be unused? */
956: static inline PetscErrorCode PetscLLAddSorted_new(PetscInt nidx, PetscInt *indices, PetscInt idx_start, PetscBool *lnk_empty, PetscInt *nlnk, PetscInt *lnk, PetscBT bt)
957: {
958: PetscInt lnkdata = idx_start;
960: PetscFunctionBegin;
961: if (*lnk_empty) {
962: for (PetscInt k = 0; k < nidx; ++k) {
963: const PetscInt entry = indices[k], location = lnkdata;
965: PetscCall(PetscBTSet(bt,entry)); /* mark the new entry */
966: lnkdata = lnk[location];
967: /* insertion location is found, add entry into lnk */
968: lnk[location] = entry;
969: lnk[entry] = lnkdata;
970: lnkdata = entry; /* next search starts from here */
971: }
972: /* lnk[indices[nidx-1]] = lnk[idx_start];
973: lnk[idx_start] = indices[0];
974: PetscCall(PetscBTSet(bt,indices[0]));
975: for (_k=1; _k<nidx; _k++) {
976: PetscCall(PetscBTSet(bt,indices[_k]));
977: lnk[indices[_k-1]] = indices[_k];
978: }
979: */
980: *nlnk = nidx;
981: *lnk_empty = PETSC_FALSE;
982: } else {
983: *nlnk = 0;
984: for (PetscInt k = 0; k < nidx; ++k) {
985: const PetscInt entry = indices[k];
987: if (!PetscBTLookupSet(bt,entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE,k,idx_start,entry,nlnk,&lnkdata,lnk));
988: }
989: }
990: PetscFunctionReturn(PETSC_SUCCESS);
991: }
992: #endif
994: /*
995: Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
996: Same as PetscLLAddSorted() with an additional operation:
997: count the number of input indices that are no larger than 'diag'
998: Input Parameters:
999: indices - sorted integer array
1000: idx_start - starting index of the list, index of pivot row
1001: lnk - linked list(an integer array) that is created
1002: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1003: diag - index of the active row in LUFactorSymbolic
1004: nzbd - number of input indices with indices <= idx_start
1005: im - im[idx_start] is initialized as num of nonzero entries in row=idx_start
1006: output Parameters:
1007: nlnk - number of newly added indices
1008: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
1009: bt - updated PetscBT (bitarray)
1010: im - im[idx_start]: unchanged if diag is not an entry
1011: : num of entries with indices <= diag if diag is an entry
1012: */
1013: 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)
1014: {
1015: const PetscInt nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */
1017: PetscFunctionBegin;
1018: *nlnk = 0;
1019: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1020: const PetscInt entry = indices[k];
1022: ++nzbd;
1023: if (entry == diag) im[idx_start] = nzbd;
1024: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE, k, idx_start, entry, nlnk, &lnkdata, lnk));
1025: }
1026: PetscFunctionReturn(PETSC_SUCCESS);
1027: }
1029: /*
1030: Copy data on the list into an array, then initialize the list
1031: Input Parameters:
1032: idx_start - starting index of the list
1033: lnk_max - max value of lnk indicating the end of the list
1034: nlnk - number of data on the list to be copied
1035: lnk - linked list
1036: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1037: output Parameters:
1038: indices - array that contains the copied data
1039: lnk - linked list that is cleaned and initialize
1040: bt - PetscBT (bitarray) with all bits set to false
1041: */
1042: static inline PetscErrorCode PetscLLClean(PetscInt idx_start, PetscInt lnk_max, PetscInt nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT indices, PetscBT bt)
1043: {
1044: PetscFunctionBegin;
1045: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1046: idx = lnk[idx];
1047: indices[j] = idx;
1048: PetscCall(PetscBTClear(bt, idx));
1049: }
1050: lnk[idx_start] = lnk_max;
1051: PetscFunctionReturn(PETSC_SUCCESS);
1052: }
1054: /*
1055: Free memories used by the list
1056: */
1057: #define PetscLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1059: /* Routines below are used for incomplete matrix factorization */
1060: /*
1061: Create and initialize a linked list and its levels
1062: Input Parameters:
1063: idx_start - starting index of the list
1064: lnk_max - max value of lnk indicating the end of the list
1065: nlnk - max length of the list
1066: Output Parameters:
1067: lnk - list initialized
1068: lnk_lvl - array of size nlnk for storing levels of lnk
1069: bt - PetscBT (bitarray) with all bits set to false
1070: */
1071: #define PetscIncompleteLLCreate(idx_start, lnk_max, nlnk, lnk, lnk_lvl, bt) \
1072: ((PetscErrorCode)(PetscIntMultError(2, nlnk, NULL) || PetscMalloc1(2 * nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, lnk_lvl = lnk + nlnk, PETSC_SUCCESS)))
1074: 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)
1075: {
1076: PetscFunctionBegin;
1077: PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, lnkdata, lnk));
1078: lnklvl[entry] = newval;
1079: PetscFunctionReturn(PETSC_SUCCESS);
1080: }
1082: /*
1083: Initialize a sorted linked list used for ILU and ICC
1084: Input Parameters:
1085: nidx - number of input idx
1086: idx - integer array used for storing column indices
1087: idx_start - starting index of the list
1088: perm - indices of an IS
1089: lnk - linked list(an integer array) that is created
1090: lnklvl - levels of lnk
1091: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1092: output Parameters:
1093: nlnk - number of newly added idx
1094: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1095: lnklvl - levels of lnk
1096: bt - updated PetscBT (bitarray)
1097: */
1098: 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)
1099: {
1100: PetscFunctionBegin;
1101: *nlnk = 0;
1102: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1103: const PetscInt entry = perm[idx[k]];
1105: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, 0));
1106: }
1107: PetscFunctionReturn(PETSC_SUCCESS);
1108: }
1110: 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)
1111: {
1112: PetscFunctionBegin;
1113: *nlnk = 0;
1114: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1115: const PetscInt incrlev = idxlvl[k] + prow_offset + 1;
1117: if (incrlev <= level) {
1118: const PetscInt entry = idx[k];
1120: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, incrlev));
1121: else if (lnklvl[entry] > incrlev) lnklvl[entry] = incrlev; /* existing entry */
1122: }
1123: }
1124: PetscFunctionReturn(PETSC_SUCCESS);
1125: }
1127: /*
1128: Add a SORTED index set into a sorted linked list for ICC
1129: Input Parameters:
1130: nidx - number of input indices
1131: idx - sorted integer array used for storing column indices
1132: level - level of fill, e.g., ICC(level)
1133: idxlvl - level of idx
1134: idx_start - starting index of the list
1135: lnk - linked list(an integer array) that is created
1136: lnklvl - levels of lnk
1137: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1138: idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1139: output Parameters:
1140: nlnk - number of newly added indices
1141: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1142: lnklvl - levels of lnk
1143: bt - updated PetscBT (bitarray)
1144: Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1145: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1146: */
1147: 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)
1148: {
1149: PetscFunctionBegin;
1150: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, idxlvl_prow, PETSC_TRUE));
1151: PetscFunctionReturn(PETSC_SUCCESS);
1152: }
1154: /*
1155: Add a SORTED index set into a sorted linked list for ILU
1156: Input Parameters:
1157: nidx - number of input indices
1158: idx - sorted integer array used for storing column indices
1159: level - level of fill, e.g., ICC(level)
1160: idxlvl - level of idx
1161: idx_start - starting index of the list
1162: lnk - linked list(an integer array) that is created
1163: lnklvl - levels of lnk
1164: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1165: prow - the row number of idx
1166: output Parameters:
1167: nlnk - number of newly added idx
1168: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1169: lnklvl - levels of lnk
1170: bt - updated PetscBT (bitarray)
1172: Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1173: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1174: */
1175: 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)
1176: {
1177: PetscFunctionBegin;
1178: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, lnklvl[prow], PETSC_TRUE));
1179: PetscFunctionReturn(PETSC_SUCCESS);
1180: }
1182: /*
1183: Add a index set into a sorted linked list
1184: Input Parameters:
1185: nidx - number of input idx
1186: idx - integer array used for storing column indices
1187: level - level of fill, e.g., ICC(level)
1188: idxlvl - level of idx
1189: idx_start - starting index of the list
1190: lnk - linked list(an integer array) that is created
1191: lnklvl - levels of lnk
1192: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1193: output Parameters:
1194: nlnk - number of newly added idx
1195: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1196: lnklvl - levels of lnk
1197: bt - updated PetscBT (bitarray)
1198: */
1199: 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)
1200: {
1201: PetscFunctionBegin;
1202: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_FALSE));
1203: PetscFunctionReturn(PETSC_SUCCESS);
1204: }
1206: /*
1207: Add a SORTED index set into a sorted linked list
1208: Input Parameters:
1209: nidx - number of input indices
1210: idx - sorted integer array used for storing column indices
1211: level - level of fill, e.g., ICC(level)
1212: idxlvl - level of idx
1213: idx_start - starting index of the list
1214: lnk - linked list(an integer array) that is created
1215: lnklvl - levels of lnk
1216: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1217: output Parameters:
1218: nlnk - number of newly added idx
1219: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1220: lnklvl - levels of lnk
1221: bt - updated PetscBT (bitarray)
1222: */
1223: 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)
1224: {
1225: PetscFunctionBegin;
1226: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_TRUE));
1227: PetscFunctionReturn(PETSC_SUCCESS);
1228: }
1230: /*
1231: Copy data on the list into an array, then initialize the list
1232: Input Parameters:
1233: idx_start - starting index of the list
1234: lnk_max - max value of lnk indicating the end of the list
1235: nlnk - number of data on the list to be copied
1236: lnk - linked list
1237: lnklvl - level of lnk
1238: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1239: output Parameters:
1240: indices - array that contains the copied data
1241: lnk - linked list that is cleaned and initialize
1242: lnklvl - level of lnk that is reinitialized
1243: bt - PetscBT (bitarray) with all bits set to false
1244: */
1245: 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)
1246: {
1247: PetscFunctionBegin;
1248: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1249: idx = lnk[idx];
1250: indices[j] = idx;
1251: indiceslvl[j] = lnklvl[idx];
1252: lnklvl[idx] = -1;
1253: PetscCall(PetscBTClear(bt, idx));
1254: }
1255: lnk[idx_start] = lnk_max;
1256: PetscFunctionReturn(PETSC_SUCCESS);
1257: }
1259: /*
1260: Free memories used by the list
1261: */
1262: #define PetscIncompleteLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1264: #if !defined(PETSC_CLANG_STATIC_ANALYZER)
1265: #define MatCheckSameLocalSize(A, ar1, B, ar2) \
1266: do { \
1267: PetscCheckSameComm(A, ar1, B, ar2); \
1268: 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, \
1269: (A)->rmap->n, (A)->cmap->n, ar2, (B)->rmap->n, (B)->cmap->n); \
1270: } while (0)
1271: #define MatCheckSameSize(A, ar1, B, ar2) \
1272: do { \
1273: 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, \
1274: (A)->rmap->N, (A)->cmap->N, ar2, (B)->rmap->N, (B)->cmap->N); \
1275: MatCheckSameLocalSize(A, ar1, B, ar2); \
1276: } while (0)
1277: #else
1278: template <typename Tm>
1279: extern void MatCheckSameLocalSize(Tm, int, Tm, int);
1280: template <typename Tm>
1281: extern void MatCheckSameSize(Tm, int, Tm, int);
1282: #endif
1284: #define VecCheckMatCompatible(M, x, ar1, b, ar2) \
1285: do { \
1286: 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, \
1287: (M)->cmap->N); \
1288: 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, \
1289: (M)->rmap->N); \
1290: } while (0)
1292: /* -------------------------------------------------------------------------------------------------------*/
1293: /*
1294: Create and initialize a condensed linked list -
1295: same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1296: Barry suggested this approach (Dec. 6, 2011):
1297: I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1298: (it may be faster than the O(N) even sequentially due to less crazy memory access).
1300: 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
1301: 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
1302: 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
1303: 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.
1304: 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
1305: to each other so memory access is much better than using the big array.
1307: Example:
1308: nlnk_max=5, lnk_max=36:
1309: Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1310: here, head_node has index 2 with value lnk[2]=lnk_max=36,
1311: 0-th entry is used to store the number of entries in the list,
1312: The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.
1314: Now adding a sorted set {2,4}, the list becomes
1315: [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1316: represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.
1318: Then adding a sorted set {0,3,35}, the list
1319: [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1320: represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.
1322: Input Parameters:
1323: nlnk_max - max length of the list
1324: lnk_max - max value of the entries
1325: Output Parameters:
1326: lnk - list created and initialized
1327: bt - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1328: */
1329: static inline PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max, PetscInt lnk_max, PetscInt **lnk, PetscBT *bt)
1330: {
1331: PetscInt *llnk, lsize = 0;
1333: PetscFunctionBegin;
1334: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1335: PetscCall(PetscMalloc1(lsize, lnk));
1336: PetscCall(PetscBTCreate(lnk_max, bt));
1337: llnk = *lnk;
1338: llnk[0] = 0; /* number of entries on the list */
1339: llnk[2] = lnk_max; /* value in the head node */
1340: llnk[3] = 2; /* next for the head node */
1341: PetscFunctionReturn(PETSC_SUCCESS);
1342: }
1344: /*
1345: Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1346: Input Parameters:
1347: nidx - number of input indices
1348: indices - sorted integer array
1349: lnk - condensed linked list(an integer array) that is created
1350: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1351: output Parameters:
1352: lnk - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1353: bt - updated PetscBT (bitarray)
1354: */
1355: static inline PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx, const PetscInt indices[], PetscInt lnk[], PetscBT bt)
1356: {
1357: PetscInt location = 2; /* head */
1358: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1360: PetscFunctionBegin;
1361: for (PetscInt k = 0; k < nidx; k++) {
1362: const PetscInt entry = indices[k];
1363: if (!PetscBTLookupSet(bt, entry)) { /* new entry */
1364: PetscInt next, lnkdata;
1366: /* search for insertion location */
1367: do {
1368: next = location + 1; /* link from previous node to next node */
1369: location = lnk[next]; /* idx of next node */
1370: lnkdata = lnk[location]; /* value of next node */
1371: } while (entry > lnkdata);
1372: /* insertion location is found, add entry into lnk */
1373: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1374: lnk[next] = newnode; /* connect previous node to the new node */
1375: lnk[newnode] = entry; /* set value of the new node */
1376: lnk[newnode + 1] = location; /* connect new node to next node */
1377: location = newnode; /* next search starts from the new node */
1378: nlnk++;
1379: }
1380: }
1381: lnk[0] = nlnk; /* number of entries in the list */
1382: PetscFunctionReturn(PETSC_SUCCESS);
1383: }
1385: static inline PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max, PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt lnk[], PetscBT bt)
1386: {
1387: const PetscInt nlnk = lnk[0]; /* num of entries on the list */
1388: PetscInt next = lnk[3]; /* head node */
1390: PetscFunctionBegin;
1391: for (PetscInt k = 0; k < nlnk; k++) {
1392: indices[k] = lnk[next];
1393: next = lnk[next + 1];
1394: PetscCall(PetscBTClear(bt, indices[k]));
1395: }
1396: lnk[0] = 0; /* num of entries on the list */
1397: lnk[2] = lnk_max; /* initialize head node */
1398: lnk[3] = 2; /* head node */
1399: PetscFunctionReturn(PETSC_SUCCESS);
1400: }
1402: static inline PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1403: {
1404: PetscFunctionBegin;
1405: PetscCall(PetscPrintf(PETSC_COMM_SELF, "LLCondensed of size %" PetscInt_FMT ", (val, next)\n", lnk[0]));
1406: 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]));
1407: PetscFunctionReturn(PETSC_SUCCESS);
1408: }
1410: /*
1411: Free memories used by the list
1412: */
1413: static inline PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk, PetscBT bt)
1414: {
1415: PetscFunctionBegin;
1416: PetscCall(PetscFree(lnk));
1417: PetscCall(PetscBTDestroy(&bt));
1418: PetscFunctionReturn(PETSC_SUCCESS);
1419: }
1421: /* -------------------------------------------------------------------------------------------------------*/
1422: /*
1423: Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1424: Input Parameters:
1425: nlnk_max - max length of the list
1426: Output Parameters:
1427: lnk - list created and initialized
1428: */
1429: static inline PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1430: {
1431: PetscInt *llnk, lsize = 0;
1433: PetscFunctionBegin;
1434: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1435: PetscCall(PetscMalloc1(lsize, lnk));
1436: llnk = *lnk;
1437: llnk[0] = 0; /* number of entries on the list */
1438: llnk[2] = PETSC_MAX_INT; /* value in the head node */
1439: llnk[3] = 2; /* next for the head node */
1440: PetscFunctionReturn(PETSC_SUCCESS);
1441: }
1443: static inline PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1444: {
1445: PetscInt lsize = 0;
1447: PetscFunctionBegin;
1448: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1449: PetscCall(PetscRealloc(lsize * sizeof(PetscInt), lnk));
1450: PetscFunctionReturn(PETSC_SUCCESS);
1451: }
1453: static inline PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1454: {
1455: PetscInt location = 2; /* head */
1456: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1458: for (PetscInt k = 0; k < nidx; k++) {
1459: const PetscInt entry = indices[k];
1460: PetscInt next, lnkdata;
1462: /* search for insertion location */
1463: do {
1464: next = location + 1; /* link from previous node to next node */
1465: location = lnk[next]; /* idx of next node */
1466: lnkdata = lnk[location]; /* value of next node */
1467: } while (entry > lnkdata);
1468: if (entry < lnkdata) {
1469: /* insertion location is found, add entry into lnk */
1470: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1471: lnk[next] = newnode; /* connect previous node to the new node */
1472: lnk[newnode] = entry; /* set value of the new node */
1473: lnk[newnode + 1] = location; /* connect new node to next node */
1474: location = newnode; /* next search starts from the new node */
1475: nlnk++;
1476: }
1477: }
1478: lnk[0] = nlnk; /* number of entries in the list */
1479: return PETSC_SUCCESS;
1480: }
1482: static inline PetscErrorCode PetscLLCondensedClean_Scalable(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1483: {
1484: const PetscInt nlnk = lnk[0];
1485: PetscInt next = lnk[3]; /* head node */
1487: for (PetscInt k = 0; k < nlnk; k++) {
1488: indices[k] = lnk[next];
1489: next = lnk[next + 1];
1490: }
1491: lnk[0] = 0; /* num of entries on the list */
1492: lnk[3] = 2; /* head node */
1493: return PETSC_SUCCESS;
1494: }
1496: static inline PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1497: {
1498: return PetscFree(lnk);
1499: }
1501: /* -------------------------------------------------------------------------------------------------------*/
1502: /*
1503: lnk[0] number of links
1504: lnk[1] number of entries
1505: lnk[3n] value
1506: lnk[3n+1] len
1507: lnk[3n+2] link to next value
1509: The next three are always the first link
1511: lnk[3] PETSC_MIN_INT+1
1512: lnk[4] 1
1513: lnk[5] link to first real entry
1515: The next three are always the last link
1517: lnk[6] PETSC_MAX_INT - 1
1518: lnk[7] 1
1519: lnk[8] next valid link (this is the same as lnk[0] but without the decreases)
1520: */
1522: static inline PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max, PetscInt **lnk)
1523: {
1524: PetscInt *llnk;
1525: PetscInt lsize = 0;
1527: PetscFunctionBegin;
1528: PetscCall(PetscIntMultError(3, nlnk_max + 3, &lsize));
1529: PetscCall(PetscMalloc1(lsize, lnk));
1530: llnk = *lnk;
1531: llnk[0] = 0; /* nlnk: number of entries on the list */
1532: llnk[1] = 0; /* number of integer entries represented in list */
1533: llnk[3] = PETSC_MIN_INT + 1; /* value in the first node */
1534: llnk[4] = 1; /* count for the first node */
1535: llnk[5] = 6; /* next for the first node */
1536: llnk[6] = PETSC_MAX_INT - 1; /* value in the last node */
1537: llnk[7] = 1; /* count for the last node */
1538: llnk[8] = 0; /* next valid node to be used */
1539: PetscFunctionReturn(PETSC_SUCCESS);
1540: }
1542: static inline PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1543: {
1544: for (PetscInt k = 0, prev = 3 /* first value */; k < nidx; k++) {
1545: const PetscInt entry = indices[k];
1546: PetscInt next = lnk[prev + 2];
1548: /* search for insertion location */
1549: while (entry >= lnk[next]) {
1550: prev = next;
1551: next = lnk[next + 2];
1552: }
1553: /* entry is in range of previous list */
1554: if (entry < lnk[prev] + lnk[prev + 1]) continue;
1555: lnk[1]++;
1556: /* entry is right after previous list */
1557: if (entry == lnk[prev] + lnk[prev + 1]) {
1558: lnk[prev + 1]++;
1559: if (lnk[next] == entry + 1) { /* combine two contiguous strings */
1560: lnk[prev + 1] += lnk[next + 1];
1561: lnk[prev + 2] = lnk[next + 2];
1562: next = lnk[next + 2];
1563: lnk[0]--;
1564: }
1565: continue;
1566: }
1567: /* entry is right before next list */
1568: if (entry == lnk[next] - 1) {
1569: lnk[next]--;
1570: lnk[next + 1]++;
1571: prev = next;
1572: next = lnk[prev + 2];
1573: continue;
1574: }
1575: /* add entry into lnk */
1576: lnk[prev + 2] = 3 * ((lnk[8]++) + 3); /* connect previous node to the new node */
1577: prev = lnk[prev + 2];
1578: lnk[prev] = entry; /* set value of the new node */
1579: lnk[prev + 1] = 1; /* number of values in contiguous string is one to start */
1580: lnk[prev + 2] = next; /* connect new node to next node */
1581: lnk[0]++;
1582: }
1583: return PETSC_SUCCESS;
1584: }
1586: static inline PetscErrorCode PetscLLCondensedClean_fast(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1587: {
1588: const PetscInt nlnk = lnk[0];
1589: PetscInt next = lnk[5]; /* first node */
1591: for (PetscInt k = 0, cnt = 0; k < nlnk; k++) {
1592: for (PetscInt j = 0; j < lnk[next + 1]; j++) indices[cnt++] = lnk[next] + j;
1593: next = lnk[next + 2];
1594: }
1595: lnk[0] = 0; /* nlnk: number of links */
1596: lnk[1] = 0; /* number of integer entries represented in list */
1597: lnk[3] = PETSC_MIN_INT + 1; /* value in the first node */
1598: lnk[4] = 1; /* count for the first node */
1599: lnk[5] = 6; /* next for the first node */
1600: lnk[6] = PETSC_MAX_INT - 1; /* value in the last node */
1601: lnk[7] = 1; /* count for the last node */
1602: lnk[8] = 0; /* next valid location to make link */
1603: return PETSC_SUCCESS;
1604: }
1606: static inline PetscErrorCode PetscLLCondensedView_fast(const PetscInt *lnk)
1607: {
1608: const PetscInt nlnk = lnk[0];
1609: PetscInt next = lnk[5]; /* first node */
1611: for (PetscInt k = 0; k < nlnk; k++) {
1612: #if 0 /* Debugging code */
1613: printf("%d value %d len %d next %d\n", next, lnk[next], lnk[next + 1], lnk[next + 2]);
1614: #endif
1615: next = lnk[next + 2];
1616: }
1617: return PETSC_SUCCESS;
1618: }
1620: static inline PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1621: {
1622: return PetscFree(lnk);
1623: }
1625: PETSC_EXTERN PetscErrorCode PetscCDCreate(PetscInt, PetscCoarsenData **);
1626: PETSC_EXTERN PetscErrorCode PetscCDDestroy(PetscCoarsenData *);
1627: PETSC_EXTERN PetscErrorCode PetscCDIntNdSetID(PetscCDIntNd *, PetscInt);
1628: PETSC_EXTERN PetscErrorCode PetscCDIntNdGetID(const PetscCDIntNd *, PetscInt *);
1629: PETSC_EXTERN PetscErrorCode PetscCDAppendID(PetscCoarsenData *, PetscInt, PetscInt);
1630: PETSC_EXTERN PetscErrorCode PetscCDMoveAppend(PetscCoarsenData *, PetscInt, PetscInt);
1631: PETSC_EXTERN PetscErrorCode PetscCDAppendNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1632: PETSC_EXTERN PetscErrorCode PetscCDRemoveNextNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1633: PETSC_EXTERN PetscErrorCode PetscCDCountAt(const PetscCoarsenData *, PetscInt, PetscInt *);
1634: PETSC_EXTERN PetscErrorCode PetscCDIsEmptyAt(const PetscCoarsenData *, PetscInt, PetscBool *);
1635: PETSC_EXTERN PetscErrorCode PetscCDSetChunkSize(PetscCoarsenData *, PetscInt);
1636: PETSC_EXTERN PetscErrorCode PetscCDPrint(const PetscCoarsenData *, PetscInt, MPI_Comm);
1637: PETSC_EXTERN PetscErrorCode PetscCDGetNonemptyIS(PetscCoarsenData *, IS *);
1638: PETSC_EXTERN PetscErrorCode PetscCDGetMat(PetscCoarsenData *, Mat *);
1639: PETSC_EXTERN PetscErrorCode PetscCDSetMat(PetscCoarsenData *, Mat);
1640: PETSC_EXTERN PetscErrorCode PetscCDClearMat(PetscCoarsenData *);
1641: PETSC_EXTERN PetscErrorCode PetscCDRemoveAllAt(PetscCoarsenData *, PetscInt);
1642: PETSC_EXTERN PetscErrorCode PetscCDCount(const PetscCoarsenData *, PetscInt *_sz);
1644: PETSC_EXTERN PetscErrorCode PetscCDGetHeadPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1645: PETSC_EXTERN PetscErrorCode PetscCDGetNextPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1646: PETSC_EXTERN PetscErrorCode PetscCDGetASMBlocks(const PetscCoarsenData *, const PetscInt, PetscInt *, IS **);
1648: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
1649: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat, MatFDColoring, Vec, void *);
1651: PETSC_EXTERN PetscLogEvent MAT_Mult;
1652: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1653: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1654: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTranspose;
1655: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1656: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTransposeAdd;
1657: PETSC_EXTERN PetscLogEvent MAT_Solve;
1658: PETSC_EXTERN PetscLogEvent MAT_Solves;
1659: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1660: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1661: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1662: PETSC_EXTERN PetscLogEvent MAT_SOR;
1663: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1664: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1665: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1666: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1667: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1668: PETSC_EXTERN PetscLogEvent MAT_QRFactor;
1669: PETSC_EXTERN PetscLogEvent MAT_QRFactorSymbolic;
1670: PETSC_EXTERN PetscLogEvent MAT_QRFactorNumeric;
1671: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1672: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1673: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1674: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1675: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1676: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1677: PETSC_EXTERN PetscLogEvent MAT_Copy;
1678: PETSC_EXTERN PetscLogEvent MAT_Convert;
1679: PETSC_EXTERN PetscLogEvent MAT_Scale;
1680: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1681: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1682: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1683: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1684: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1685: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1686: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1687: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1688: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1689: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1690: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1691: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1692: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1693: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1694: PETSC_EXTERN PetscLogEvent MAT_Load;
1695: PETSC_EXTERN PetscLogEvent MAT_View;
1696: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1697: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1698: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1699: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1700: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1701: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1702: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1703: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1704: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1705: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1706: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1707: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1708: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1709: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1710: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1711: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1712: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1713: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1714: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1715: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1716: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1717: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1718: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1719: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1720: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1721: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1722: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1723: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1724: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1725: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1726: PETSC_EXTERN PetscLogEvent MAT_GetSeqNonzeroStructure;
1727: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1728: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1729: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1730: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyFromGPU;
1731: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
1732: PETSC_EXTERN PetscLogEvent MAT_CUSPARSESolveAnalysis;
1733: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyToGPU;
1734: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyFromGPU;
1735: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSEGenerateTranspose;
1736: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSESolveAnalysis;
1737: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1738: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1739: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1740: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1741: PETSC_EXTERN PetscLogEvent MAT_Merge;
1742: PETSC_EXTERN PetscLogEvent MAT_Residual;
1743: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1744: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1745: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1746: PETSC_EXTERN PetscLogEvent MAT_PreallCOO;
1747: PETSC_EXTERN PetscLogEvent MAT_SetVCOO;
1748: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1749: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1750: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1751: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1752: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1753: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;
1754: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Build;
1755: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Compress;
1756: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Orthog;
1757: PETSC_EXTERN PetscLogEvent MAT_H2Opus_LR;
1758: PETSC_EXTERN PetscLogEvent MAT_CUDACopyToGPU;
1759: PETSC_EXTERN PetscLogEvent MAT_HIPCopyToGPU;