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_INTERN 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
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 (*matmatmultsymbolic)(Mat, Mat, Mat, PetscReal, Mat);
114: /*64*/
115: PetscErrorCode (*matmatmultnumeric)(Mat, Mat, Mat, Mat);
116: PetscErrorCode (*setlocaltoglobalmapping)(Mat, ISLocalToGlobalMapping, ISLocalToGlobalMapping);
117: PetscErrorCode (*setvalueslocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
118: PetscErrorCode (*zerorowslocal)(Mat, PetscInt, const PetscInt[], PetscScalar, Vec, Vec);
119: PetscErrorCode (*getrowmaxabs)(Mat, Vec, PetscInt[]);
120: /*69*/
121: PetscErrorCode (*getrowminabs)(Mat, Vec, PetscInt[]);
122: PetscErrorCode (*convert)(Mat, MatType, MatReuse, Mat *);
123: PetscErrorCode (*hasoperation)(Mat, MatOperation, PetscBool *);
124: PetscErrorCode (*fdcoloringapply)(Mat, MatFDColoring, Vec, void *);
125: PetscErrorCode (*setfromoptions)(Mat, PetscOptionItems);
126: /*74*/
127: PetscErrorCode (*findzerodiagonals)(Mat, IS *);
128: PetscErrorCode (*mults)(Mat, Vecs, Vecs);
129: PetscErrorCode (*solves)(Mat, Vecs, Vecs);
130: PetscErrorCode (*getinertia)(Mat, PetscInt *, PetscInt *, PetscInt *);
131: PetscErrorCode (*load)(Mat, PetscViewer);
132: /*79*/
133: PetscErrorCode (*issymmetric)(Mat, PetscReal, PetscBool *);
134: PetscErrorCode (*ishermitian)(Mat, PetscReal, PetscBool *);
135: PetscErrorCode (*isstructurallysymmetric)(Mat, PetscBool *);
136: PetscErrorCode (*setvaluesblockedlocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
137: PetscErrorCode (*getvecs)(Mat, Vec *, Vec *);
138: /*84*/
139: PetscErrorCode (*matmultsymbolic)(Mat, Mat, PetscReal, Mat);
140: PetscErrorCode (*matmultnumeric)(Mat, Mat, Mat);
141: PetscErrorCode (*ptapnumeric)(Mat, Mat, Mat); /* double dispatch wrapper routine */
142: PetscErrorCode (*mattransposemultsymbolic)(Mat, Mat, PetscReal, Mat);
143: PetscErrorCode (*mattransposemultnumeric)(Mat, Mat, Mat);
144: /*89*/
145: PetscErrorCode (*bindtocpu)(Mat, PetscBool);
146: PetscErrorCode (*productsetfromoptions)(Mat);
147: PetscErrorCode (*productsymbolic)(Mat);
148: PetscErrorCode (*productnumeric)(Mat);
149: PetscErrorCode (*conjugate)(Mat); /* complex conjugate */
150: /*94*/
151: PetscErrorCode (*viewnative)(Mat, PetscViewer);
152: PetscErrorCode (*setvaluesrow)(Mat, PetscInt, const PetscScalar[]);
153: PetscErrorCode (*realpart)(Mat);
154: PetscErrorCode (*imaginarypart)(Mat);
155: PetscErrorCode (*getrowuppertriangular)(Mat);
156: /*99*/
157: PetscErrorCode (*restorerowuppertriangular)(Mat);
158: PetscErrorCode (*matsolve)(Mat, Mat, Mat);
159: PetscErrorCode (*matsolvetranspose)(Mat, Mat, Mat);
160: PetscErrorCode (*getrowmin)(Mat, Vec, PetscInt[]);
161: PetscErrorCode (*getcolumnvector)(Mat, Vec, PetscInt);
162: /*104*/
163: PetscErrorCode (*missingdiagonal)(Mat, PetscBool *, PetscInt *);
164: PetscErrorCode (*getseqnonzerostructure)(Mat, Mat *);
165: PetscErrorCode (*create)(Mat);
166: PetscErrorCode (*getghosts)(Mat, PetscInt *, const PetscInt *[]);
167: PetscErrorCode (*getlocalsubmatrix)(Mat, IS, IS, Mat *);
168: /*109*/
169: PetscErrorCode (*restorelocalsubmatrix)(Mat, IS, IS, Mat *);
170: PetscErrorCode (*multdiagonalblock)(Mat, Vec, Vec);
171: PetscErrorCode (*hermitiantranspose)(Mat, MatReuse, Mat *);
172: PetscErrorCode (*multhermitiantranspose)(Mat, Vec, Vec);
173: PetscErrorCode (*multhermitiantransposeadd)(Mat, Vec, Vec, Vec);
174: /*114*/
175: PetscErrorCode (*getmultiprocblock)(Mat, MPI_Comm, MatReuse, Mat *);
176: PetscErrorCode (*findnonzerorows)(Mat, IS *);
177: PetscErrorCode (*getcolumnreductions)(Mat, PetscInt, PetscReal *);
178: PetscErrorCode (*invertblockdiagonal)(Mat, const PetscScalar **);
179: PetscErrorCode (*invertvariableblockdiagonal)(Mat, PetscInt, const PetscInt *, PetscScalar *);
180: /*119*/
181: PetscErrorCode (*createsubmatricesmpi)(Mat, PetscInt, const IS[], const IS[], MatReuse, Mat **);
182: PetscErrorCode (*setvaluesbatch)(Mat, PetscInt, PetscInt, PetscInt *, const PetscScalar *);
183: PetscErrorCode (*transposematmultsymbolic)(Mat, Mat, PetscReal, Mat);
184: PetscErrorCode (*transposematmultnumeric)(Mat, Mat, Mat);
185: PetscErrorCode (*transposecoloringcreate)(Mat, ISColoring, MatTransposeColoring);
186: /*124*/
187: PetscErrorCode (*transcoloringapplysptoden)(MatTransposeColoring, Mat, Mat);
188: PetscErrorCode (*transcoloringapplydentosp)(MatTransposeColoring, Mat, Mat);
189: PetscErrorCode (*rartnumeric)(Mat, Mat, Mat); /* double dispatch wrapper routine */
190: PetscErrorCode (*setblocksizes)(Mat, PetscInt, PetscInt);
191: PetscErrorCode (*residual)(Mat, Vec, Vec, Vec);
192: /*129*/
193: PetscErrorCode (*fdcoloringsetup)(Mat, ISColoring, MatFDColoring);
194: PetscErrorCode (*findoffblockdiagonalentries)(Mat, IS *);
195: PetscErrorCode (*creatempimatconcatenateseqmat)(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);
196: PetscErrorCode (*destroysubmatrices)(PetscInt, Mat *[]);
197: PetscErrorCode (*mattransposesolve)(Mat, Mat, Mat);
198: /*134*/
199: PetscErrorCode (*getvalueslocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], PetscScalar[]);
200: PetscErrorCode (*creategraph)(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
201: PetscErrorCode (*transposesymbolic)(Mat, Mat *);
202: PetscErrorCode (*eliminatezeros)(Mat, PetscBool);
203: PetscErrorCode (*getrowsumabs)(Mat, Vec);
204: /*139*/
205: PetscErrorCode (*getfactor)(Mat, MatSolverType, MatFactorType, Mat *);
206: PetscErrorCode (*getblockdiagonal)(Mat, Mat *); // NOTE: the caller of get{block, vblock}diagonal owns the returned matrix;
207: PetscErrorCode (*getvblockdiagonal)(Mat, Mat *); // they must destroy it after use
208: PetscErrorCode (*copyhashtoxaij)(Mat, Mat);
209: PetscErrorCode (*getcurrentmemtype)(Mat, PetscMemType *);
210: /*144*/
211: PetscErrorCode (*zerorowscolumnslocal)(Mat, PetscInt, const PetscInt[], PetscScalar, Vec, Vec);
212: };
213: /*
214: If you add MatOps entries above also add them to the MATOP enum
215: in include/petscmat.h
216: */
218: #include <petscsys.h>
220: typedef struct _p_MatRootName *MatRootName;
221: struct _p_MatRootName {
222: char *rname, *sname, *mname;
223: MatRootName next;
224: };
226: PETSC_EXTERN MatRootName MatRootNameList;
228: /*
229: Utility private matrix routines used outside Mat
230: */
231: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat, PetscBool, PetscReal, IS *);
232: PETSC_EXTERN PetscErrorCode MatShellGetScalingShifts(Mat, PetscScalar *, PetscScalar *, Vec *, Vec *, Vec *, Mat *, IS *, IS *);
234: #define MAT_SHELL_NOT_ALLOWED (void *)-1
236: /*
237: Utility private matrix routines
238: */
239: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat, MatType, MatReuse, Mat *);
240: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat, MatType, MatReuse, Mat *);
241: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat, MatType, MatReuse, Mat *);
242: PETSC_INTERN PetscErrorCode MatShellSetContext_Immutable(Mat, void *);
243: PETSC_INTERN PetscErrorCode MatShellSetContextDestroy_Immutable(Mat, PetscCtxDestroyFn *);
244: PETSC_INTERN PetscErrorCode MatShellSetManageScalingShifts_Immutable(Mat);
245: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat, Mat, MatStructure);
246: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat, Vec, InsertMode);
247: #if defined(PETSC_HAVE_SCALAPACK)
248: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
249: #endif
250: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_Basic(Mat, PetscCount, PetscInt[], PetscInt[]);
251: PETSC_INTERN PetscErrorCode MatSetValuesCOO_Basic(Mat, const PetscScalar[], InsertMode);
253: /* This can be moved to the public header after implementing some missing MatProducts */
254: PETSC_INTERN PetscErrorCode MatCreateFromISLocalToGlobalMapping(ISLocalToGlobalMapping, Mat, PetscBool, PetscBool, MatType, Mat *);
256: /* these callbacks rely on the old matrix function pointers for
257: matmat operations. They are unsafe, and should be removed.
258: However, the amount of work needed to clean up all the
259: implementations is not negligible */
260: PETSC_INTERN PetscErrorCode MatProductSymbolic_AB(Mat);
261: PETSC_INTERN PetscErrorCode MatProductNumeric_AB(Mat);
262: PETSC_INTERN PetscErrorCode MatProductSymbolic_AtB(Mat);
263: PETSC_INTERN PetscErrorCode MatProductNumeric_AtB(Mat);
264: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABt(Mat);
265: PETSC_INTERN PetscErrorCode MatProductNumeric_ABt(Mat);
266: PETSC_INTERN PetscErrorCode MatProductNumeric_PtAP(Mat);
267: PETSC_INTERN PetscErrorCode MatProductNumeric_RARt(Mat);
268: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC(Mat);
269: PETSC_INTERN PetscErrorCode MatProductNumeric_ABC(Mat);
271: PETSC_INTERN PetscErrorCode MatProductCreate_Private(Mat, Mat, Mat, Mat);
272: /* this callback handles all the different triple products and
273: does not rely on the function pointers; used by cuSPARSE/hipSPARSE and KOKKOS-KERNELS */
274: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC_Basic(Mat);
276: /* CreateGraph is common to AIJ seq and mpi */
277: PETSC_INTERN PetscErrorCode MatCreateGraph_Simple_AIJ(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
279: #if defined(PETSC_CLANG_STATIC_ANALYZER)
280: template <typename Tm>
281: extern void MatCheckPreallocated(Tm, int);
282: template <typename Tm>
283: extern void MatCheckProduct(Tm, int);
284: #else /* PETSC_CLANG_STATIC_ANALYZER */
285: #define MatCheckPreallocated(A, arg) \
286: do { \
287: if (!(A)->preallocated) PetscCall(MatSetUp(A)); \
288: } while (0)
290: #if defined(PETSC_USE_DEBUG)
291: #define MatCheckProduct(A, arg) \
292: do { \
293: PetscCheck((A)->product, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Argument %d \"%s\" is not a matrix obtained from MatProductCreate()", (arg), #A); \
294: } while (0)
295: #else
296: #define MatCheckProduct(A, arg) \
297: do { \
298: } while (0)
299: #endif
300: #endif /* PETSC_CLANG_STATIC_ANALYZER */
302: /*
303: The stash is used to temporarily store inserted matrix values that
304: belong to another processor. During the assembly phase the stashed
305: values are moved to the correct processor and
306: */
308: typedef struct _MatStashSpace *PetscMatStashSpace;
310: struct _MatStashSpace {
311: PetscMatStashSpace next;
312: PetscScalar *space_head, *val;
313: PetscInt *idx, *idy;
314: PetscInt total_space_size;
315: PetscInt local_used;
316: PetscInt local_remaining;
317: };
319: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt, PetscInt, PetscMatStashSpace *);
320: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt, PetscMatStashSpace *, PetscScalar *, PetscInt *, PetscInt *);
321: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace *);
323: typedef struct {
324: PetscInt count;
325: } MatStashHeader;
327: typedef struct {
328: void *buffer; /* Of type blocktype, dynamically constructed */
329: PetscInt count;
330: char pending;
331: } MatStashFrame;
333: typedef struct _MatStash MatStash;
334: struct _MatStash {
335: PetscInt nmax; /* maximum stash size */
336: PetscInt umax; /* user specified max-size */
337: PetscInt oldnmax; /* the nmax value used previously */
338: PetscInt n; /* stash size */
339: PetscInt bs; /* block size of the stash */
340: PetscInt reallocs; /* preserve the no of mallocs invoked */
341: PetscMatStashSpace space_head, space; /* linked list to hold stashed global row/column numbers and matrix values */
343: PetscErrorCode (*ScatterBegin)(Mat, MatStash *, PetscInt *);
344: PetscErrorCode (*ScatterGetMesg)(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
345: PetscErrorCode (*ScatterEnd)(MatStash *);
346: PetscErrorCode (*ScatterDestroy)(MatStash *);
348: /* The following variables are used for communication */
349: MPI_Comm comm;
350: PetscMPIInt size, rank;
351: PetscMPIInt tag1, tag2;
352: MPI_Request *send_waits; /* array of send requests */
353: MPI_Request *recv_waits; /* array of receive requests */
354: MPI_Status *send_status; /* array of send status */
355: PetscMPIInt nsends, nrecvs; /* numbers of sends and receives */
356: PetscScalar *svalues; /* sending data */
357: PetscInt *sindices;
358: PetscScalar **rvalues; /* receiving data (values) */
359: PetscInt **rindices; /* receiving data (indices) */
360: PetscMPIInt nprocessed; /* number of messages already processed */
361: PetscMPIInt *flg_v; /* indicates what messages have arrived so far and from whom */
362: PetscBool reproduce;
363: PetscMPIInt reproduce_count;
365: /* The following variables are used for BTS communication */
366: PetscBool first_assembly_done; /* Is the first time matrix assembly done? */
367: PetscBool use_status; /* Use MPI_Status to determine number of items in each message */
368: PetscMPIInt nsendranks;
369: PetscMPIInt nrecvranks;
370: PetscMPIInt *sendranks;
371: PetscMPIInt *recvranks;
372: MatStashHeader *sendhdr, *recvhdr;
373: MatStashFrame *sendframes; /* pointers to the main messages */
374: MatStashFrame *recvframes;
375: MatStashFrame *recvframe_active;
376: PetscInt recvframe_i; /* index of block within active frame */
377: PetscInt recvframe_count; /* Count actually sent for current frame */
378: PetscMPIInt recvcount; /* Number of receives processed so far */
379: PetscMPIInt *some_indices; /* From last call to MPI_Waitsome */
380: MPI_Status *some_statuses; /* Statuses from last call to MPI_Waitsome */
381: PetscMPIInt some_count; /* Number of requests completed in last call to MPI_Waitsome */
382: PetscMPIInt some_i; /* Index of request currently being processed */
383: MPI_Request *sendreqs;
384: MPI_Request *recvreqs;
385: PetscSegBuffer segsendblocks;
386: PetscSegBuffer segrecvframe;
387: PetscSegBuffer segrecvblocks;
388: MPI_Datatype blocktype;
389: size_t blocktype_size;
390: InsertMode *insertmode; /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
391: };
393: #if !defined(PETSC_HAVE_MPIUNI)
394: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash *);
395: #endif
396: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm, PetscInt, MatStash *);
397: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash *);
398: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash *);
399: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash *, PetscInt);
400: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash *, PetscInt *, PetscInt *);
401: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscBool);
402: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscBool);
403: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
404: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
405: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat, MatStash *, PetscInt *);
406: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
407: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat, MatInfoType, MatInfo *);
409: typedef struct {
410: PetscInt dim;
411: PetscInt dims[4];
412: PetscInt starts[4];
413: PetscBool noc; /* this is a single component problem, hence user will not set MatStencil.c */
414: } MatStencilInfo;
416: /* Info about using compressed row format */
417: typedef struct {
418: PetscBool use; /* indicates compressed rows have been checked and will be used */
419: PetscInt nrows; /* number of non-zero rows */
420: PetscInt *i; /* compressed row pointer */
421: PetscInt *rindex; /* compressed row index */
422: } Mat_CompressedRow;
423: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat, PetscInt, Mat_CompressedRow *, PetscInt *, PetscInt, PetscReal);
425: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
426: PetscInt nzlocal, nsends, nrecvs;
427: PetscMPIInt *send_rank, *recv_rank;
428: PetscInt *sbuf_nz, *rbuf_nz, *sbuf_j, **rbuf_j;
429: PetscScalar *sbuf_a, **rbuf_a;
430: MPI_Comm subcomm; /* when user does not provide a subcomm */
431: IS isrow, iscol;
432: Mat *matseq;
433: } Mat_Redundant;
435: typedef struct { /* used by MatProduct() */
436: MatProductType type;
437: char *alg;
438: Mat A, B, C, Dwork;
439: 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, .. */
440: 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 .. */
441: PetscBool symbolic_used_the_fact_C_is_symmetric; /* MatMatMult(A,B,MAT_REUSE_MATRIX,..&C) is still legitimate), we need to redo symbolic! */
442: PetscObjectParameterDeclare(PetscReal, fill);
443: 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 */
444: PetscBool setfromoptionscalled;
446: /* Some products may display the information on the algorithm used */
447: PetscErrorCode (*view)(Mat, PetscViewer);
449: /* many products have intermediate data structures, each specific to Mat types and product type */
450: PetscBool clear; /* whether or not to clear the data structures after MatProductNumeric has been called */
451: void *data; /* where to stash those structures */
452: PetscErrorCode (*destroy)(void *); /* destroy routine */
453: } Mat_Product;
455: struct _p_Mat {
456: PETSCHEADER(struct _MatOps);
457: PetscLayout rmap, cmap;
458: void *data; /* implementation-specific data */
459: MatFactorType factortype; /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
460: PetscBool trivialsymbolic; /* indicates the symbolic factorization doesn't actually do a symbolic factorization, it is delayed to the numeric factorization */
461: PetscBool canuseordering; /* factorization can use ordering provide to routine (most PETSc implementations) */
462: MatOrderingType preferredordering[MAT_FACTOR_NUM_TYPES]; /* what is the preferred (or default) ordering for the matrix solver type */
463: PetscBool assembled; /* is the matrix assembled? */
464: PetscBool was_assembled; /* new values inserted into assembled mat */
465: PetscInt num_ass; /* number of times matrix has been assembled */
466: PetscObjectState nonzerostate; /* each time new nonzeros locations are introduced into the matrix this is updated */
467: PetscObjectState ass_nonzerostate; /* nonzero state at last assembly */
468: MatInfo info; /* matrix information */
469: InsertMode insertmode; /* have values been inserted in matrix or added? */
470: MatStash stash, bstash; /* used for assembling off-proc mat emements */
471: MatNullSpace nullsp; /* null space (operator is singular) */
472: MatNullSpace transnullsp; /* null space of transpose of operator */
473: MatNullSpace nearnullsp; /* near null space to be used by multigrid methods */
474: PetscInt congruentlayouts; /* are the rows and columns layouts congruent? */
475: PetscBool preallocated;
476: MatStencilInfo stencil; /* information for structured grid */
477: PetscBool3 symmetric, hermitian, structurally_symmetric, spd;
478: PetscBool symmetry_eternal, structural_symmetry_eternal, spd_eternal;
479: PetscBool nooffprocentries, nooffproczerorows;
480: PetscBool assembly_subset; /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
481: PetscBool submat_singleis; /* for efficient PCSetUp_ASM() */
482: PetscBool structure_only;
483: PetscBool sortedfull; /* full, sorted rows are inserted */
484: PetscBool force_diagonals; /* set by MAT_FORCE_DIAGONAL_ENTRIES */
485: #if defined(PETSC_HAVE_DEVICE)
486: PetscOffloadMask offloadmask; /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
487: PetscBool boundtocpu;
488: PetscBool bindingpropagates;
489: #endif
490: char *defaultrandtype;
491: void *spptr; /* pointer for special library like SuperLU */
492: char *solvertype;
493: PetscBool checksymmetryonassembly, checknullspaceonassembly;
494: PetscReal checksymmetrytol;
495: Mat schur; /* Schur complement matrix */
496: MatFactorSchurStatus schur_status; /* status of the Schur complement matrix */
497: Mat_Redundant *redundant; /* used by MatCreateRedundantMatrix() */
498: PetscBool erroriffailure; /* Generate an error if detected (for example a zero pivot) instead of returning */
499: MatFactorError factorerrortype; /* type of error in factorization */
500: PetscReal factorerror_zeropivot_value; /* If numerical zero pivot was detected this is the computed value */
501: PetscInt factorerror_zeropivot_row; /* Row where zero pivot was detected */
502: PetscInt nblocks, *bsizes; /* support for MatSetVariableBlockSizes() */
503: PetscInt p_cstart, p_rank, p_cend, n_rank; /* Information from parallel MatComputeVariableBlockEnvelope() */
504: PetscBool p_parallel;
505: char *defaultvectype;
506: Mat_Product *product;
507: PetscBool form_explicit_transpose; /* hint to generate an explicit mat tranpsose for operations like MatMultTranspose() */
508: PetscBool transupdated; /* whether or not the explicitly generated transpose is up-to-date */
509: char *factorprefix; /* the prefix to use with factored matrix that is created */
510: PetscBool hash_active; /* indicates MatSetValues() is being handled by hashing */
511: };
513: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat, PetscScalar, Mat, MatStructure);
514: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat, Mat, PetscScalar, Mat, MatStructure);
515: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat, Mat, Mat *);
516: PETSC_INTERN PetscErrorCode MatAXPY_Dense_Nest(Mat, PetscScalar, Mat);
518: PETSC_INTERN PetscErrorCode MatSetUp_Default(Mat);
520: /*
521: Utility for MatZeroRows
522: */
523: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat, PetscInt, const PetscInt *, PetscInt *, PetscInt **);
525: /*
526: Utility for MatView/MatLoad
527: */
528: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat, PetscViewer);
529: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat, PetscViewer);
531: /*
532: Object for partitioning graphs
533: */
535: typedef struct _MatPartitioningOps *MatPartitioningOps;
536: struct _MatPartitioningOps {
537: PetscErrorCode (*apply)(MatPartitioning, IS *);
538: PetscErrorCode (*applynd)(MatPartitioning, IS *);
539: PetscErrorCode (*setfromoptions)(MatPartitioning, PetscOptionItems);
540: PetscErrorCode (*destroy)(MatPartitioning);
541: PetscErrorCode (*view)(MatPartitioning, PetscViewer);
542: PetscErrorCode (*improve)(MatPartitioning, IS *);
543: };
545: struct _p_MatPartitioning {
546: PETSCHEADER(struct _MatPartitioningOps);
547: Mat adj;
548: PetscInt *vertex_weights;
549: PetscReal *part_weights;
550: PetscInt n; /* number of partitions */
551: PetscInt ncon; /* number of vertex weights per vertex */
552: void *data;
553: PetscBool use_edge_weights; /* A flag indicates whether or not to use edge weights */
554: };
556: /* needed for parallel nested dissection by ParMetis and PTSCOTCH */
557: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt, PetscInt[], PetscInt[], PetscInt[]);
559: /*
560: Object for coarsen graphs
561: */
562: typedef struct _MatCoarsenOps *MatCoarsenOps;
563: struct _MatCoarsenOps {
564: PetscErrorCode (*apply)(MatCoarsen);
565: PetscErrorCode (*setfromoptions)(MatCoarsen, PetscOptionItems);
566: PetscErrorCode (*destroy)(MatCoarsen);
567: PetscErrorCode (*view)(MatCoarsen, PetscViewer);
568: };
570: #define MAT_COARSEN_STRENGTH_INDEX_SIZE 3
571: struct _p_MatCoarsen {
572: PETSCHEADER(struct _MatCoarsenOps);
573: Mat graph;
574: void *subctx;
575: /* */
576: PetscBool strict_aggs;
577: IS perm;
578: PetscCoarsenData *agg_lists;
579: PetscInt max_it; /* number of iterations in HEM */
580: PetscReal threshold; /* HEM can filter interim graphs */
581: PetscInt strength_index_size;
582: PetscInt strength_index[MAT_COARSEN_STRENGTH_INDEX_SIZE];
583: };
585: PETSC_EXTERN PetscErrorCode MatCoarsenMISKSetDistance(MatCoarsen, PetscInt);
586: PETSC_EXTERN PetscErrorCode MatCoarsenMISKGetDistance(MatCoarsen, PetscInt *);
588: /*
589: Used in aijdevice.h
590: */
591: typedef struct {
592: PetscInt *i;
593: PetscInt *j;
594: PetscScalar *a;
595: PetscInt n;
596: PetscInt ignorezeroentries;
597: } PetscCSRDataStructure;
599: /*
600: MatFDColoring is used to compute Jacobian matrices efficiently
601: via coloring. The data structure is explained below in an example.
603: Color = 0 1 0 2 | 2 3 0
604: ---------------------------------------------------
605: 00 01 | 05
606: 10 11 | 14 15 Processor 0
607: 22 23 | 25
608: 32 33 |
609: ===================================================
610: | 44 45 46
611: 50 | 55 Processor 1
612: | 64 66
613: ---------------------------------------------------
615: ncolors = 4;
617: ncolumns = {2,1,1,0}
618: columns = {{0,2},{1},{3},{}}
619: nrows = {4,2,3,3}
620: rows = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
621: vwscale = {dx(0),dx(1),dx(2),dx(3)} MPI Vec
622: vscale = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)} Seq Vec
624: ncolumns = {1,0,1,1}
625: columns = {{6},{},{4},{5}}
626: nrows = {3,0,2,2}
627: rows = {{0,1,2},{},{1,2},{1,2}}
628: vwscale = {dx(4),dx(5),dx(6)} MPI Vec
629: vscale = {dx(0),dx(4),dx(5),dx(6)} Seq Vec
631: See the routine MatFDColoringApply() for how this data is used
632: to compute the Jacobian.
634: */
635: typedef struct {
636: PetscInt row;
637: PetscInt col;
638: PetscScalar *valaddr; /* address of value */
639: } MatEntry;
641: typedef struct {
642: PetscInt row;
643: PetscScalar *valaddr; /* address of value */
644: } MatEntry2;
646: struct _p_MatFDColoring {
647: PETSCHEADER(int);
648: PetscInt M, N, m; /* total rows, columns; local rows */
649: PetscInt rstart; /* first row owned by local processor */
650: PetscInt ncolors; /* number of colors */
651: PetscInt *ncolumns; /* number of local columns for a color */
652: PetscInt **columns; /* lists the local columns of each color (using global column numbering) */
653: IS *isa; /* these are the IS that contain the column values given in columns */
654: PetscInt *nrows; /* number of local rows for each color */
655: MatEntry *matentry; /* holds (row, column, address of value) for Jacobian matrix entry */
656: MatEntry2 *matentry2; /* holds (row, address of value) for Jacobian matrix entry */
657: PetscScalar *dy; /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
658: PetscReal error_rel; /* square root of relative error in computing function */
659: PetscReal umin; /* minimum allowable u'dx value */
660: Vec w1, w2, w3; /* work vectors used in computing Jacobian */
661: PetscBool fset; /* indicates that the initial function value F(X) is set */
662: MatFDColoringFn *f; /* function that defines Jacobian */
663: void *fctx; /* optional user-defined context for use by the function f */
664: Vec vscale; /* holds FD scaling, i.e. 1/dx for each perturbed column */
665: PetscInt currentcolor; /* color for which function evaluation is being done now */
666: const char *htype; /* "wp" or "ds" */
667: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
668: PetscInt brows, bcols; /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
669: PetscBool setupcalled; /* true if setup has been called */
670: PetscBool viewed; /* true if the -mat_fd_coloring_view has been triggered already */
671: PetscFortranCallbackFn *ftn_func_pointer; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
672: void *ftn_func_cntx;
673: PetscObjectId matid; /* matrix this object was created with, must always be the same */
674: };
676: typedef struct _MatColoringOps *MatColoringOps;
677: struct _MatColoringOps {
678: PetscErrorCode (*destroy)(MatColoring);
679: PetscErrorCode (*setfromoptions)(MatColoring, PetscOptionItems);
680: PetscErrorCode (*view)(MatColoring, PetscViewer);
681: PetscErrorCode (*apply)(MatColoring, ISColoring *);
682: PetscErrorCode (*weights)(MatColoring, PetscReal **, PetscInt **);
683: };
685: struct _p_MatColoring {
686: PETSCHEADER(struct _MatColoringOps);
687: Mat mat;
688: PetscInt dist; /* distance of the coloring */
689: PetscInt maxcolors; /* the maximum number of colors returned, maxcolors=1 for MIS */
690: void *data; /* inner context */
691: PetscBool valid; /* check to see if what is produced is a valid coloring */
692: MatColoringWeightType weight_type; /* type of weight computation to be performed */
693: PetscReal *user_weights; /* custom weights and permutation */
694: PetscInt *user_lperm;
695: PetscBool valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
696: };
698: struct _p_MatTransposeColoring {
699: PETSCHEADER(int);
700: PetscInt M, N, m; /* total rows, columns; local rows */
701: PetscInt rstart; /* first row owned by local processor */
702: PetscInt ncolors; /* number of colors */
703: PetscInt *ncolumns; /* number of local columns for a color */
704: PetscInt *nrows; /* number of local rows for each color */
705: PetscInt currentcolor; /* color for which function evaluation is being done now */
706: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
708: PetscInt *colorforrow, *colorforcol; /* pointer to rows and columns */
709: PetscInt *rows; /* lists the local rows for each color (using the local row numbering) */
710: PetscInt *den2sp; /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
711: PetscInt *columns; /* lists the local columns of each color (using global column numbering) */
712: PetscInt brows; /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
713: PetscInt *lstart; /* array used for loop over row blocks of Csparse */
714: };
716: /*
717: Null space context for preconditioner/operators
718: */
719: struct _p_MatNullSpace {
720: PETSCHEADER(int);
721: PetscBool has_cnst;
722: PetscInt n;
723: Vec *vecs;
724: PetscScalar *alpha; /* for projections */
725: MatNullSpaceRemoveFn *remove; /* for user provided removal function */
726: void *rmctx; /* context for remove() function */
727: };
729: /*
730: Internal data structure for MATMPIDENSE
731: */
732: typedef struct {
733: Mat A; /* local submatrix */
735: /* The following variables are used for matrix assembly */
736: PetscBool donotstash; /* Flag indicating if values should be stashed */
737: MPI_Request *send_waits; /* array of send requests */
738: MPI_Request *recv_waits; /* array of receive requests */
739: PetscInt nsends, nrecvs; /* numbers of sends and receives */
740: PetscScalar *svalues, *rvalues; /* sending and receiving data */
741: PetscInt rmax; /* maximum message length */
743: /* The following variables are used for matrix-vector products */
744: Vec lvec; /* local vector */
745: PetscSF Mvctx; /* for mat-mult communications */
746: PetscBool roworiented; /* if true, row-oriented input (default) */
748: /* Support for MatDenseGetColumnVec and MatDenseGetSubMatrix */
749: Mat cmat; /* matrix representation of a given subset of columns */
750: Vec cvec; /* vector representation of a given column */
751: const PetscScalar *ptrinuse; /* holds array to be restored (just a placeholder) */
752: PetscInt vecinuse; /* if cvec is in use (col = vecinuse-1) */
753: PetscInt matinuse; /* if cmat is in use (cbegin = matinuse-1) */
754: /* if this is from MatDenseGetSubMatrix, which columns and rows does it correspond to? */
755: PetscInt sub_rbegin;
756: PetscInt sub_rend;
757: PetscInt sub_cbegin;
758: PetscInt sub_cend;
759: } Mat_MPIDense;
761: /*
762: Checking zero pivot for LU, ILU preconditioners.
763: */
764: typedef struct {
765: PetscInt nshift, nshift_max;
766: PetscReal shift_amount, shift_lo, shift_hi, shift_top, shift_fraction;
767: PetscBool newshift;
768: PetscReal rs; /* active row sum of abs(off-diagonals) */
769: PetscScalar pv; /* pivot of the active row */
770: } FactorShiftCtx;
772: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatTransposeCheckNonzeroState_Private(Mat, Mat);
774: /*
775: Used by MatTranspose() and potentially other functions to track the matrix used in the generation of another matrix
776: */
777: typedef struct {
778: PetscObjectId id;
779: PetscObjectState state;
780: PetscObjectState nonzerostate;
781: } MatParentState;
783: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
784: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat, PetscInt, PetscInt);
786: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatShift_Basic(Mat, PetscScalar);
788: static inline PetscErrorCode MatPivotCheck_nz(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
789: {
790: PetscReal _rs = sctx->rs;
791: PetscReal _zero = info->zeropivot * _rs;
793: PetscFunctionBegin;
794: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
795: /* force |diag| > zeropivot*rs */
796: if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
797: else sctx->shift_amount *= 2.0;
798: sctx->newshift = PETSC_TRUE;
799: (sctx->nshift)++;
800: } else {
801: sctx->newshift = PETSC_FALSE;
802: }
803: PetscFunctionReturn(PETSC_SUCCESS);
804: }
806: static inline PetscErrorCode MatPivotCheck_pd(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
807: {
808: PetscReal _rs = sctx->rs;
809: PetscReal _zero = info->zeropivot * _rs;
811: PetscFunctionBegin;
812: if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
813: /* force matfactor to be diagonally dominant */
814: if (sctx->nshift == sctx->nshift_max) {
815: sctx->shift_fraction = sctx->shift_hi;
816: } else {
817: sctx->shift_lo = sctx->shift_fraction;
818: sctx->shift_fraction = (sctx->shift_hi + sctx->shift_lo) / (PetscReal)2.;
819: }
820: sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
821: sctx->nshift++;
822: sctx->newshift = PETSC_TRUE;
823: } else {
824: sctx->newshift = PETSC_FALSE;
825: }
826: PetscFunctionReturn(PETSC_SUCCESS);
827: }
829: static inline PetscErrorCode MatPivotCheck_inblocks(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
830: {
831: PetscReal _zero = info->zeropivot;
833: PetscFunctionBegin;
834: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
835: sctx->pv += info->shiftamount;
836: sctx->shift_amount = 0.0;
837: sctx->nshift++;
838: }
839: sctx->newshift = PETSC_FALSE;
840: PetscFunctionReturn(PETSC_SUCCESS);
841: }
843: static inline PetscErrorCode MatPivotCheck_none(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
844: {
845: PetscReal _zero = info->zeropivot;
847: PetscFunctionBegin;
848: sctx->newshift = PETSC_FALSE;
849: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
850: 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);
851: PetscCall(PetscInfo(mat, "Detected zero pivot in factorization in row %" PetscInt_FMT " value %g tolerance %g\n", row, (double)PetscAbsScalar(sctx->pv), (double)_zero));
852: fact->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
853: fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
854: fact->factorerror_zeropivot_row = row;
855: }
856: PetscFunctionReturn(PETSC_SUCCESS);
857: }
859: static inline PetscErrorCode MatPivotCheck(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
860: {
861: PetscFunctionBegin;
862: if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) PetscCall(MatPivotCheck_nz(mat, info, sctx, row));
863: else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) PetscCall(MatPivotCheck_pd(mat, info, sctx, row));
864: else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) PetscCall(MatPivotCheck_inblocks(mat, info, sctx, row));
865: else PetscCall(MatPivotCheck_none(fact, mat, info, sctx, row));
866: PetscFunctionReturn(PETSC_SUCCESS);
867: }
869: #include <petscbt.h>
870: /*
871: Create and initialize a linked list
872: Input Parameters:
873: idx_start - starting index of the list
874: lnk_max - max value of lnk indicating the end of the list
875: nlnk - max length of the list
876: Output Parameters:
877: lnk - list initialized
878: bt - PetscBT (bitarray) with all bits set to false
879: lnk_empty - flg indicating the list is empty
880: */
881: #define PetscLLCreate(idx_start, lnk_max, nlnk, lnk, bt) ((PetscErrorCode)(PetscMalloc1(nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, PETSC_SUCCESS)))
883: #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)))
885: 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)
886: {
887: PetscInt location;
889: PetscFunctionBegin;
890: /* start from the beginning if entry < previous entry */
891: if (!assume_sorted && k && entry < *lnkdata) *lnkdata = idx_start;
892: /* search for insertion location */
893: do {
894: location = *lnkdata;
895: *lnkdata = lnk[location];
896: } while (entry > *lnkdata);
897: /* insertion location is found, add entry into lnk */
898: lnk[location] = entry;
899: lnk[entry] = *lnkdata;
900: ++(*nlnk);
901: *lnkdata = entry; /* next search starts from here if next_entry > entry */
902: PetscFunctionReturn(PETSC_SUCCESS);
903: }
905: 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)
906: {
907: PetscFunctionBegin;
908: *nlnk = 0;
909: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
910: const PetscInt entry = indices[k];
912: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk));
913: }
914: PetscFunctionReturn(PETSC_SUCCESS);
915: }
917: /*
918: Add an index set into a sorted linked list
919: Input Parameters:
920: nidx - number of input indices
921: indices - integer array
922: idx_start - starting index of the list
923: lnk - linked list(an integer array) that is created
924: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
925: output Parameters:
926: nlnk - number of newly added indices
927: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
928: bt - updated PetscBT (bitarray)
929: */
930: static inline PetscErrorCode PetscLLAdd(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
931: {
932: PetscFunctionBegin;
933: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_FALSE));
934: PetscFunctionReturn(PETSC_SUCCESS);
935: }
937: /*
938: Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata = idx_start;'
939: Input Parameters:
940: nidx - number of input indices
941: indices - sorted integer array
942: idx_start - starting index of the list
943: lnk - linked list(an integer array) that is created
944: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
945: output Parameters:
946: nlnk - number of newly added indices
947: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
948: bt - updated PetscBT (bitarray)
949: */
950: static inline PetscErrorCode PetscLLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
951: {
952: PetscFunctionBegin;
953: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_TRUE));
954: PetscFunctionReturn(PETSC_SUCCESS);
955: }
957: /*
958: Add a permuted index set into a sorted linked list
959: Input Parameters:
960: nidx - number of input indices
961: indices - integer array
962: perm - permutation of indices
963: idx_start - starting index of the list
964: lnk - linked list(an integer array) that is created
965: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
966: output Parameters:
967: nlnk - number of newly added indices
968: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
969: bt - updated PetscBT (bitarray)
970: */
971: 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)
972: {
973: PetscFunctionBegin;
974: *nlnk = 0;
975: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
976: const PetscInt entry = perm[indices[k]];
978: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk));
979: }
980: PetscFunctionReturn(PETSC_SUCCESS);
981: }
983: #if 0
984: /* this appears to be unused? */
985: static inline PetscErrorCode PetscLLAddSorted_new(PetscInt nidx, PetscInt *indices, PetscInt idx_start, PetscBool *lnk_empty, PetscInt *nlnk, PetscInt *lnk, PetscBT bt)
986: {
987: PetscInt lnkdata = idx_start;
989: PetscFunctionBegin;
990: if (*lnk_empty) {
991: for (PetscInt k = 0; k < nidx; ++k) {
992: const PetscInt entry = indices[k], location = lnkdata;
994: PetscCall(PetscBTSet(bt,entry)); /* mark the new entry */
995: lnkdata = lnk[location];
996: /* insertion location is found, add entry into lnk */
997: lnk[location] = entry;
998: lnk[entry] = lnkdata;
999: lnkdata = entry; /* next search starts from here */
1000: }
1001: /* lnk[indices[nidx-1]] = lnk[idx_start];
1002: lnk[idx_start] = indices[0];
1003: PetscCall(PetscBTSet(bt,indices[0]));
1004: for (_k=1; _k<nidx; _k++) {
1005: PetscCall(PetscBTSet(bt,indices[_k]));
1006: lnk[indices[_k-1]] = indices[_k];
1007: }
1008: */
1009: *nlnk = nidx;
1010: *lnk_empty = PETSC_FALSE;
1011: } else {
1012: *nlnk = 0;
1013: for (PetscInt k = 0; k < nidx; ++k) {
1014: const PetscInt entry = indices[k];
1016: if (!PetscBTLookupSet(bt,entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE,k,idx_start,entry,nlnk,&lnkdata,lnk));
1017: }
1018: }
1019: PetscFunctionReturn(PETSC_SUCCESS);
1020: }
1021: #endif
1023: /*
1024: Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
1025: Same as PetscLLAddSorted() with an additional operation:
1026: count the number of input indices that are no larger than 'diag'
1027: Input Parameters:
1028: indices - sorted integer array
1029: idx_start - starting index of the list, index of pivot row
1030: lnk - linked list(an integer array) that is created
1031: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1032: diag - index of the active row in LUFactorSymbolic
1033: nzbd - number of input indices with indices <= idx_start
1034: im - im[idx_start] is initialized as num of nonzero entries in row=idx_start
1035: output Parameters:
1036: nlnk - number of newly added indices
1037: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
1038: bt - updated PetscBT (bitarray)
1039: im - im[idx_start]: unchanged if diag is not an entry
1040: : num of entries with indices <= diag if diag is an entry
1041: */
1042: 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)
1043: {
1044: const PetscInt nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */
1046: PetscFunctionBegin;
1047: *nlnk = 0;
1048: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1049: const PetscInt entry = indices[k];
1051: ++nzbd;
1052: if (entry == diag) im[idx_start] = nzbd;
1053: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE, k, idx_start, entry, nlnk, &lnkdata, lnk));
1054: }
1055: PetscFunctionReturn(PETSC_SUCCESS);
1056: }
1058: /*
1059: Copy data on the list into an array, then initialize the list
1060: Input Parameters:
1061: idx_start - starting index of the list
1062: lnk_max - max value of lnk indicating the end of the list
1063: nlnk - number of data on the list to be copied
1064: lnk - linked list
1065: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1066: output Parameters:
1067: indices - array that contains the copied data
1068: lnk - linked list that is cleaned and initialize
1069: bt - PetscBT (bitarray) with all bits set to false
1070: */
1071: static inline PetscErrorCode PetscLLClean(PetscInt idx_start, PetscInt lnk_max, PetscInt nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT indices, PetscBT bt)
1072: {
1073: PetscFunctionBegin;
1074: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1075: idx = lnk[idx];
1076: indices[j] = idx;
1077: PetscCall(PetscBTClear(bt, idx));
1078: }
1079: lnk[idx_start] = lnk_max;
1080: PetscFunctionReturn(PETSC_SUCCESS);
1081: }
1083: /*
1084: Free memories used by the list
1085: */
1086: #define PetscLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1088: /* Routines below are used for incomplete matrix factorization */
1089: /*
1090: Create and initialize a linked list and its levels
1091: Input Parameters:
1092: idx_start - starting index of the list
1093: lnk_max - max value of lnk indicating the end of the list
1094: nlnk - max length of the list
1095: Output Parameters:
1096: lnk - list initialized
1097: lnk_lvl - array of size nlnk for storing levels of lnk
1098: bt - PetscBT (bitarray) with all bits set to false
1099: */
1100: #define PetscIncompleteLLCreate(idx_start, lnk_max, nlnk, lnk, lnk_lvl, bt) \
1101: ((PetscErrorCode)(PetscIntMultError(2, nlnk, NULL) || PetscMalloc1(2 * nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, lnk_lvl = lnk + nlnk, PETSC_SUCCESS)))
1103: 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)
1104: {
1105: PetscFunctionBegin;
1106: PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, lnkdata, lnk));
1107: lnklvl[entry] = newval;
1108: PetscFunctionReturn(PETSC_SUCCESS);
1109: }
1111: /*
1112: Initialize a sorted linked list used for ILU and ICC
1113: Input Parameters:
1114: nidx - number of input idx
1115: idx - integer array used for storing column indices
1116: idx_start - starting index of the list
1117: perm - indices of an IS
1118: lnk - linked list(an integer array) that is created
1119: lnklvl - levels of lnk
1120: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1121: output Parameters:
1122: nlnk - number of newly added idx
1123: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1124: lnklvl - levels of lnk
1125: bt - updated PetscBT (bitarray)
1126: */
1127: 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)
1128: {
1129: PetscFunctionBegin;
1130: *nlnk = 0;
1131: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1132: const PetscInt entry = perm[idx[k]];
1134: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, 0));
1135: }
1136: PetscFunctionReturn(PETSC_SUCCESS);
1137: }
1139: 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)
1140: {
1141: PetscFunctionBegin;
1142: *nlnk = 0;
1143: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1144: const PetscInt incrlev = idxlvl[k] + prow_offset + 1;
1146: if (incrlev <= level) {
1147: const PetscInt entry = idx[k];
1149: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, incrlev));
1150: else if (lnklvl[entry] > incrlev) lnklvl[entry] = incrlev; /* existing entry */
1151: }
1152: }
1153: PetscFunctionReturn(PETSC_SUCCESS);
1154: }
1156: /*
1157: Add a SORTED index set into a sorted linked list for ICC
1158: Input Parameters:
1159: nidx - number of input indices
1160: idx - sorted integer array used for storing column indices
1161: level - level of fill, e.g., ICC(level)
1162: idxlvl - level of idx
1163: idx_start - starting index of the list
1164: lnk - linked list(an integer array) that is created
1165: lnklvl - levels of lnk
1166: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1167: idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1168: output Parameters:
1169: nlnk - number of newly added indices
1170: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1171: lnklvl - levels of lnk
1172: bt - updated PetscBT (bitarray)
1173: Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1174: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1175: */
1176: 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)
1177: {
1178: PetscFunctionBegin;
1179: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, idxlvl_prow, PETSC_TRUE));
1180: PetscFunctionReturn(PETSC_SUCCESS);
1181: }
1183: /*
1184: Add a SORTED index set into a sorted linked list for ILU
1185: Input Parameters:
1186: nidx - number of input indices
1187: idx - sorted 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: prow - the row number of idx
1195: output Parameters:
1196: nlnk - number of newly added idx
1197: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1198: lnklvl - levels of lnk
1199: bt - updated PetscBT (bitarray)
1201: Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1202: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1203: */
1204: 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)
1205: {
1206: PetscFunctionBegin;
1207: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, lnklvl[prow], PETSC_TRUE));
1208: PetscFunctionReturn(PETSC_SUCCESS);
1209: }
1211: /*
1212: Add a index set into a sorted linked list
1213: Input Parameters:
1214: nidx - number of input idx
1215: idx - integer array used for storing column indices
1216: level - level of fill, e.g., ICC(level)
1217: idxlvl - level of idx
1218: idx_start - starting index of the list
1219: lnk - linked list(an integer array) that is created
1220: lnklvl - levels of lnk
1221: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1222: output Parameters:
1223: nlnk - number of newly added idx
1224: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1225: lnklvl - levels of lnk
1226: bt - updated PetscBT (bitarray)
1227: */
1228: 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)
1229: {
1230: PetscFunctionBegin;
1231: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_FALSE));
1232: PetscFunctionReturn(PETSC_SUCCESS);
1233: }
1235: /*
1236: Add a SORTED index set into a sorted linked list
1237: Input Parameters:
1238: nidx - number of input indices
1239: idx - sorted integer array used for storing column indices
1240: level - level of fill, e.g., ICC(level)
1241: idxlvl - level of idx
1242: idx_start - starting index of the list
1243: lnk - linked list(an integer array) that is created
1244: lnklvl - levels of lnk
1245: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1246: output Parameters:
1247: nlnk - number of newly added idx
1248: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1249: lnklvl - levels of lnk
1250: bt - updated PetscBT (bitarray)
1251: */
1252: 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)
1253: {
1254: PetscFunctionBegin;
1255: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_TRUE));
1256: PetscFunctionReturn(PETSC_SUCCESS);
1257: }
1259: /*
1260: Copy data on the list into an array, then initialize the list
1261: Input Parameters:
1262: idx_start - starting index of the list
1263: lnk_max - max value of lnk indicating the end of the list
1264: nlnk - number of data on the list to be copied
1265: lnk - linked list
1266: lnklvl - level of lnk
1267: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1268: output Parameters:
1269: indices - array that contains the copied data
1270: lnk - linked list that is cleaned and initialize
1271: lnklvl - level of lnk that is reinitialized
1272: bt - PetscBT (bitarray) with all bits set to false
1273: */
1274: 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)
1275: {
1276: PetscFunctionBegin;
1277: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1278: idx = lnk[idx];
1279: indices[j] = idx;
1280: indiceslvl[j] = lnklvl[idx];
1281: lnklvl[idx] = -1;
1282: PetscCall(PetscBTClear(bt, idx));
1283: }
1284: lnk[idx_start] = lnk_max;
1285: PetscFunctionReturn(PETSC_SUCCESS);
1286: }
1288: /*
1289: Free memories used by the list
1290: */
1291: #define PetscIncompleteLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1293: #if !defined(PETSC_CLANG_STATIC_ANALYZER)
1294: #define MatCheckSameLocalSize(A, ar1, B, ar2) \
1295: do { \
1296: PetscCheckSameComm(A, ar1, B, ar2); \
1297: 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, \
1298: (A)->rmap->n, (A)->cmap->n, ar2, (B)->rmap->n, (B)->cmap->n); \
1299: } while (0)
1300: #define MatCheckSameSize(A, ar1, B, ar2) \
1301: do { \
1302: 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, \
1303: (A)->rmap->N, (A)->cmap->N, ar2, (B)->rmap->N, (B)->cmap->N); \
1304: MatCheckSameLocalSize(A, ar1, B, ar2); \
1305: } while (0)
1306: #else
1307: template <typename Tm>
1308: extern void MatCheckSameLocalSize(Tm, int, Tm, int);
1309: template <typename Tm>
1310: extern void MatCheckSameSize(Tm, int, Tm, int);
1311: #endif
1313: #define VecCheckMatCompatible(M, x, ar1, b, ar2) \
1314: do { \
1315: 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, \
1316: (M)->cmap->N); \
1317: 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, \
1318: (M)->rmap->N); \
1319: } while (0)
1321: /*
1322: Create and initialize a condensed linked list -
1323: same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1324: Barry suggested this approach (Dec. 6, 2011):
1325: I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1326: (it may be faster than the O(N) even sequentially due to less crazy memory access).
1328: 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
1329: 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
1330: 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
1331: 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.
1332: 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
1333: to each other so memory access is much better than using the big array.
1335: Example:
1336: nlnk_max=5, lnk_max=36:
1337: Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1338: here, head_node has index 2 with value lnk[2]=lnk_max=36,
1339: 0-th entry is used to store the number of entries in the list,
1340: The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.
1342: Now adding a sorted set {2,4}, the list becomes
1343: [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1344: represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.
1346: Then adding a sorted set {0,3,35}, the list
1347: [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1348: represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.
1350: Input Parameters:
1351: nlnk_max - max length of the list
1352: lnk_max - max value of the entries
1353: Output Parameters:
1354: lnk - list created and initialized
1355: bt - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1356: */
1357: static inline PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max, PetscInt lnk_max, PetscInt **lnk, PetscBT *bt)
1358: {
1359: PetscInt *llnk, lsize = 0;
1361: PetscFunctionBegin;
1362: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1363: PetscCall(PetscMalloc1(lsize, lnk));
1364: PetscCall(PetscBTCreate(lnk_max, bt));
1365: llnk = *lnk;
1366: llnk[0] = 0; /* number of entries on the list */
1367: llnk[2] = lnk_max; /* value in the head node */
1368: llnk[3] = 2; /* next for the head node */
1369: PetscFunctionReturn(PETSC_SUCCESS);
1370: }
1372: /*
1373: Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1374: Input Parameters:
1375: nidx - number of input indices
1376: indices - sorted integer array
1377: lnk - condensed linked list(an integer array) that is created
1378: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1379: output Parameters:
1380: lnk - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1381: bt - updated PetscBT (bitarray)
1382: */
1383: static inline PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx, const PetscInt indices[], PetscInt lnk[], PetscBT bt)
1384: {
1385: PetscInt location = 2; /* head */
1386: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1388: PetscFunctionBegin;
1389: for (PetscInt k = 0; k < nidx; k++) {
1390: const PetscInt entry = indices[k];
1391: if (!PetscBTLookupSet(bt, entry)) { /* new entry */
1392: PetscInt next, lnkdata;
1394: /* search for insertion location */
1395: do {
1396: next = location + 1; /* link from previous node to next node */
1397: location = lnk[next]; /* idx of next node */
1398: lnkdata = lnk[location]; /* value of next node */
1399: } while (entry > lnkdata);
1400: /* insertion location is found, add entry into lnk */
1401: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1402: lnk[next] = newnode; /* connect previous node to the new node */
1403: lnk[newnode] = entry; /* set value of the new node */
1404: lnk[newnode + 1] = location; /* connect new node to next node */
1405: location = newnode; /* next search starts from the new node */
1406: nlnk++;
1407: }
1408: }
1409: lnk[0] = nlnk; /* number of entries in the list */
1410: PetscFunctionReturn(PETSC_SUCCESS);
1411: }
1413: static inline PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max, PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt lnk[], PetscBT bt)
1414: {
1415: const PetscInt nlnk = lnk[0]; /* num of entries on the list */
1416: PetscInt next = lnk[3]; /* head node */
1418: PetscFunctionBegin;
1419: for (PetscInt k = 0; k < nlnk; k++) {
1420: indices[k] = lnk[next];
1421: next = lnk[next + 1];
1422: PetscCall(PetscBTClear(bt, indices[k]));
1423: }
1424: lnk[0] = 0; /* num of entries on the list */
1425: lnk[2] = lnk_max; /* initialize head node */
1426: lnk[3] = 2; /* head node */
1427: PetscFunctionReturn(PETSC_SUCCESS);
1428: }
1430: static inline PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1431: {
1432: PetscFunctionBegin;
1433: PetscCall(PetscPrintf(PETSC_COMM_SELF, "LLCondensed of size %" PetscInt_FMT ", (val, next)\n", lnk[0]));
1434: 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]));
1435: PetscFunctionReturn(PETSC_SUCCESS);
1436: }
1438: /*
1439: Free memories used by the list
1440: */
1441: static inline PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk, PetscBT bt)
1442: {
1443: PetscFunctionBegin;
1444: PetscCall(PetscFree(lnk));
1445: PetscCall(PetscBTDestroy(&bt));
1446: PetscFunctionReturn(PETSC_SUCCESS);
1447: }
1449: /*
1450: Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1451: Input Parameters:
1452: nlnk_max - max length of the list
1453: Output Parameters:
1454: lnk - list created and initialized
1455: */
1456: static inline PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1457: {
1458: PetscInt *llnk, lsize = 0;
1460: PetscFunctionBegin;
1461: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1462: PetscCall(PetscMalloc1(lsize, lnk));
1463: llnk = *lnk;
1464: llnk[0] = 0; /* number of entries on the list */
1465: llnk[2] = PETSC_INT_MAX; /* value in the head node */
1466: llnk[3] = 2; /* next for the head node */
1467: PetscFunctionReturn(PETSC_SUCCESS);
1468: }
1470: static inline PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1471: {
1472: PetscInt lsize = 0;
1474: PetscFunctionBegin;
1475: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1476: PetscCall(PetscRealloc(lsize * sizeof(PetscInt), lnk));
1477: PetscFunctionReturn(PETSC_SUCCESS);
1478: }
1480: static inline PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1481: {
1482: PetscInt location = 2; /* head */
1483: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1485: for (PetscInt k = 0; k < nidx; k++) {
1486: const PetscInt entry = indices[k];
1487: PetscInt next, lnkdata;
1489: /* search for insertion location */
1490: do {
1491: next = location + 1; /* link from previous node to next node */
1492: location = lnk[next]; /* idx of next node */
1493: lnkdata = lnk[location]; /* value of next node */
1494: } while (entry > lnkdata);
1495: if (entry < lnkdata) {
1496: /* insertion location is found, add entry into lnk */
1497: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1498: lnk[next] = newnode; /* connect previous node to the new node */
1499: lnk[newnode] = entry; /* set value of the new node */
1500: lnk[newnode + 1] = location; /* connect new node to next node */
1501: location = newnode; /* next search starts from the new node */
1502: nlnk++;
1503: }
1504: }
1505: lnk[0] = nlnk; /* number of entries in the list */
1506: return PETSC_SUCCESS;
1507: }
1509: static inline PetscErrorCode PetscLLCondensedClean_Scalable(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1510: {
1511: const PetscInt nlnk = lnk[0];
1512: PetscInt next = lnk[3]; /* head node */
1514: for (PetscInt k = 0; k < nlnk; k++) {
1515: indices[k] = lnk[next];
1516: next = lnk[next + 1];
1517: }
1518: lnk[0] = 0; /* num of entries on the list */
1519: lnk[3] = 2; /* head node */
1520: return PETSC_SUCCESS;
1521: }
1523: static inline PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1524: {
1525: return PetscFree(lnk);
1526: }
1528: /*
1529: lnk[0] number of links
1530: lnk[1] number of entries
1531: lnk[3n] value
1532: lnk[3n+1] len
1533: lnk[3n+2] link to next value
1535: The next three are always the first link
1537: lnk[3] PETSC_INT_MIN+1
1538: lnk[4] 1
1539: lnk[5] link to first real entry
1541: The next three are always the last link
1543: lnk[6] PETSC_INT_MAX - 1
1544: lnk[7] 1
1545: lnk[8] next valid link (this is the same as lnk[0] but without the decreases)
1546: */
1548: static inline PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max, PetscInt **lnk)
1549: {
1550: PetscInt *llnk;
1551: PetscInt lsize = 0;
1553: PetscFunctionBegin;
1554: PetscCall(PetscIntMultError(3, nlnk_max + 3, &lsize));
1555: PetscCall(PetscMalloc1(lsize, lnk));
1556: llnk = *lnk;
1557: llnk[0] = 0; /* nlnk: number of entries on the list */
1558: llnk[1] = 0; /* number of integer entries represented in list */
1559: llnk[3] = PETSC_INT_MIN + 1; /* value in the first node */
1560: llnk[4] = 1; /* count for the first node */
1561: llnk[5] = 6; /* next for the first node */
1562: llnk[6] = PETSC_INT_MAX - 1; /* value in the last node */
1563: llnk[7] = 1; /* count for the last node */
1564: llnk[8] = 0; /* next valid node to be used */
1565: PetscFunctionReturn(PETSC_SUCCESS);
1566: }
1568: static inline PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1569: {
1570: for (PetscInt k = 0, prev = 3 /* first value */; k < nidx; k++) {
1571: const PetscInt entry = indices[k];
1572: PetscInt next = lnk[prev + 2];
1574: /* search for insertion location */
1575: while (entry >= lnk[next]) {
1576: prev = next;
1577: next = lnk[next + 2];
1578: }
1579: /* entry is in range of previous list */
1580: if (entry < lnk[prev] + lnk[prev + 1]) continue;
1581: lnk[1]++;
1582: /* entry is right after previous list */
1583: if (entry == lnk[prev] + lnk[prev + 1]) {
1584: lnk[prev + 1]++;
1585: if (lnk[next] == entry + 1) { /* combine two contiguous strings */
1586: lnk[prev + 1] += lnk[next + 1];
1587: lnk[prev + 2] = lnk[next + 2];
1588: next = lnk[next + 2];
1589: lnk[0]--;
1590: }
1591: continue;
1592: }
1593: /* entry is right before next list */
1594: if (entry == lnk[next] - 1) {
1595: lnk[next]--;
1596: lnk[next + 1]++;
1597: prev = next;
1598: next = lnk[prev + 2];
1599: continue;
1600: }
1601: /* add entry into lnk */
1602: lnk[prev + 2] = 3 * ((lnk[8]++) + 3); /* connect previous node to the new node */
1603: prev = lnk[prev + 2];
1604: lnk[prev] = entry; /* set value of the new node */
1605: lnk[prev + 1] = 1; /* number of values in contiguous string is one to start */
1606: lnk[prev + 2] = next; /* connect new node to next node */
1607: lnk[0]++;
1608: }
1609: return PETSC_SUCCESS;
1610: }
1612: static inline PetscErrorCode PetscLLCondensedClean_fast(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1613: {
1614: const PetscInt nlnk = lnk[0];
1615: PetscInt next = lnk[5]; /* first node */
1617: for (PetscInt k = 0, cnt = 0; k < nlnk; k++) {
1618: for (PetscInt j = 0; j < lnk[next + 1]; j++) indices[cnt++] = lnk[next] + j;
1619: next = lnk[next + 2];
1620: }
1621: lnk[0] = 0; /* nlnk: number of links */
1622: lnk[1] = 0; /* number of integer entries represented in list */
1623: lnk[3] = PETSC_INT_MIN + 1; /* value in the first node */
1624: lnk[4] = 1; /* count for the first node */
1625: lnk[5] = 6; /* next for the first node */
1626: lnk[6] = PETSC_INT_MAX - 1; /* value in the last node */
1627: lnk[7] = 1; /* count for the last node */
1628: lnk[8] = 0; /* next valid location to make link */
1629: return PETSC_SUCCESS;
1630: }
1632: static inline PetscErrorCode PetscLLCondensedView_fast(const PetscInt *lnk)
1633: {
1634: const PetscInt nlnk = lnk[0];
1635: PetscInt next = lnk[5]; /* first node */
1637: for (PetscInt k = 0; k < nlnk; k++) {
1638: #if 0 /* Debugging code */
1639: printf("%d value %d len %d next %d\n", next, lnk[next], lnk[next + 1], lnk[next + 2]);
1640: #endif
1641: next = lnk[next + 2];
1642: }
1643: return PETSC_SUCCESS;
1644: }
1646: static inline PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1647: {
1648: return PetscFree(lnk);
1649: }
1651: PETSC_EXTERN PetscErrorCode PetscCDCreate(PetscInt, PetscCoarsenData **);
1652: PETSC_EXTERN PetscErrorCode PetscCDDestroy(PetscCoarsenData *);
1653: PETSC_EXTERN PetscErrorCode PetscCDIntNdSetID(PetscCDIntNd *, PetscInt);
1654: PETSC_EXTERN PetscErrorCode PetscCDIntNdGetID(const PetscCDIntNd *, PetscInt *);
1655: PETSC_EXTERN PetscErrorCode PetscCDAppendID(PetscCoarsenData *, PetscInt, PetscInt);
1656: PETSC_EXTERN PetscErrorCode PetscCDMoveAppend(PetscCoarsenData *, PetscInt, PetscInt);
1657: PETSC_EXTERN PetscErrorCode PetscCDAppendNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1658: PETSC_EXTERN PetscErrorCode PetscCDRemoveNextNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1659: PETSC_EXTERN PetscErrorCode PetscCDCountAt(const PetscCoarsenData *, PetscInt, PetscInt *);
1660: PETSC_EXTERN PetscErrorCode PetscCDIsEmptyAt(const PetscCoarsenData *, PetscInt, PetscBool *);
1661: PETSC_EXTERN PetscErrorCode PetscCDSetChunkSize(PetscCoarsenData *, PetscInt);
1662: PETSC_EXTERN PetscErrorCode PetscCDPrint(const PetscCoarsenData *, PetscInt, MPI_Comm);
1663: PETSC_EXTERN PetscErrorCode PetscCDGetNonemptyIS(PetscCoarsenData *, IS *);
1664: PETSC_EXTERN PetscErrorCode PetscCDGetMat(PetscCoarsenData *, Mat *);
1665: PETSC_EXTERN PetscErrorCode PetscCDSetMat(PetscCoarsenData *, Mat);
1666: PETSC_EXTERN PetscErrorCode PetscCDClearMat(PetscCoarsenData *);
1667: PETSC_EXTERN PetscErrorCode PetscCDRemoveAllAt(PetscCoarsenData *, PetscInt);
1668: PETSC_EXTERN PetscErrorCode PetscCDCount(const PetscCoarsenData *, PetscInt *_sz);
1670: PETSC_EXTERN PetscErrorCode PetscCDGetHeadPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1671: PETSC_EXTERN PetscErrorCode PetscCDGetNextPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1672: PETSC_EXTERN PetscErrorCode PetscCDGetASMBlocks(const PetscCoarsenData *, const PetscInt, PetscInt *, IS **);
1674: PETSC_SINGLE_LIBRARY_VISIBILITY_INTERNAL PetscErrorCode MatFDColoringApply_AIJ(Mat, MatFDColoring, Vec, void *);
1676: PETSC_EXTERN PetscLogEvent MAT_Mult;
1677: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1678: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1679: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTranspose;
1680: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1681: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTransposeAdd;
1682: PETSC_EXTERN PetscLogEvent MAT_Solve;
1683: PETSC_EXTERN PetscLogEvent MAT_Solves;
1684: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1685: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1686: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1687: PETSC_EXTERN PetscLogEvent MAT_SOR;
1688: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1689: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1690: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1691: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1692: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1693: PETSC_EXTERN PetscLogEvent MAT_QRFactor;
1694: PETSC_EXTERN PetscLogEvent MAT_QRFactorSymbolic;
1695: PETSC_EXTERN PetscLogEvent MAT_QRFactorNumeric;
1696: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1697: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1698: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1699: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1700: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1701: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1702: PETSC_EXTERN PetscLogEvent MAT_Copy;
1703: PETSC_EXTERN PetscLogEvent MAT_Convert;
1704: PETSC_EXTERN PetscLogEvent MAT_Scale;
1705: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1706: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1707: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1708: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1709: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1710: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1711: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1712: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1713: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1714: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1715: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1716: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1717: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1718: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1719: PETSC_EXTERN PetscLogEvent MAT_Load;
1720: PETSC_EXTERN PetscLogEvent MAT_View;
1721: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1722: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1723: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1724: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1725: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1726: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1727: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1728: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1729: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1730: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1731: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1732: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1733: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1734: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1735: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1736: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1737: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1738: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1739: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1740: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1741: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1742: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1743: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1744: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1745: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1746: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1747: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1748: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1749: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1750: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1751: PETSC_EXTERN PetscLogEvent MAT_GetSeqNonzeroStructure;
1752: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1753: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1754: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1755: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyFromGPU;
1756: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
1757: PETSC_EXTERN PetscLogEvent MAT_CUSPARSESolveAnalysis;
1758: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyToGPU;
1759: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyFromGPU;
1760: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSEGenerateTranspose;
1761: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSESolveAnalysis;
1762: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1763: PETSC_EXTERN PetscLogEvent MAT_CreateGraph;
1764: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1765: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1766: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1767: PETSC_EXTERN PetscLogEvent MAT_Merge;
1768: PETSC_EXTERN PetscLogEvent MAT_Residual;
1769: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1770: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1771: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1772: PETSC_EXTERN PetscLogEvent MAT_PreallCOO;
1773: PETSC_EXTERN PetscLogEvent MAT_SetVCOO;
1774: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1775: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1776: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1777: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1778: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1779: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;
1780: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Build;
1781: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Compress;
1782: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Orthog;
1783: PETSC_EXTERN PetscLogEvent MAT_H2Opus_LR;
1784: PETSC_EXTERN PetscLogEvent MAT_CUDACopyToGPU;
1785: PETSC_EXTERN PetscLogEvent MAT_HIPCopyToGPU;