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 (*getseqnonzerostructure)(Mat, Mat *);
164: PetscErrorCode (*create)(Mat);
165: PetscErrorCode (*getghosts)(Mat, PetscInt *, const PetscInt *[]);
166: PetscErrorCode (*getlocalsubmatrix)(Mat, IS, IS, Mat *);
167: PetscErrorCode (*restorelocalsubmatrix)(Mat, IS, IS, Mat *);
168: /*109*/
169: PetscErrorCode (*multdiagonalblock)(Mat, Vec, Vec);
170: PetscErrorCode (*hermitiantranspose)(Mat, MatReuse, Mat *);
171: PetscErrorCode (*multhermitiantranspose)(Mat, Vec, Vec);
172: PetscErrorCode (*multhermitiantransposeadd)(Mat, Vec, Vec, Vec);
173: PetscErrorCode (*getmultiprocblock)(Mat, MPI_Comm, MatReuse, Mat *);
174: /*114*/
175: PetscErrorCode (*findnonzerorows)(Mat, IS *);
176: PetscErrorCode (*getcolumnreductions)(Mat, PetscInt, PetscReal *);
177: PetscErrorCode (*invertblockdiagonal)(Mat, const PetscScalar **);
178: PetscErrorCode (*invertvariableblockdiagonal)(Mat, PetscInt, const PetscInt *, PetscScalar *);
179: PetscErrorCode (*createsubmatricesmpi)(Mat, PetscInt, const IS[], const IS[], MatReuse, Mat **);
180: /*119*/
181: PetscErrorCode (*setvaluesbatch)(Mat, PetscInt, PetscInt, PetscInt *, const PetscScalar *);
182: PetscErrorCode (*transposematmultsymbolic)(Mat, Mat, PetscReal, Mat);
183: PetscErrorCode (*transposematmultnumeric)(Mat, Mat, Mat);
184: PetscErrorCode (*transposecoloringcreate)(Mat, ISColoring, MatTransposeColoring);
185: PetscErrorCode (*transcoloringapplysptoden)(MatTransposeColoring, Mat, Mat);
186: /*124*/
187: PetscErrorCode (*transcoloringapplydentosp)(MatTransposeColoring, Mat, Mat);
188: PetscErrorCode (*rartnumeric)(Mat, Mat, Mat); /* double dispatch wrapper routine */
189: PetscErrorCode (*setblocksizes)(Mat, PetscInt, PetscInt);
190: PetscErrorCode (*residual)(Mat, Vec, Vec, Vec);
191: PetscErrorCode (*fdcoloringsetup)(Mat, ISColoring, MatFDColoring);
192: /*129*/
193: PetscErrorCode (*findoffblockdiagonalentries)(Mat, IS *);
194: PetscErrorCode (*creatempimatconcatenateseqmat)(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);
195: PetscErrorCode (*destroysubmatrices)(PetscInt, Mat *[]);
196: PetscErrorCode (*mattransposesolve)(Mat, Mat, Mat);
197: PetscErrorCode (*getvalueslocal)(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], PetscScalar[]);
198: /*134*/
199: PetscErrorCode (*creategraph)(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
200: PetscErrorCode (*transposesymbolic)(Mat, Mat *);
201: PetscErrorCode (*eliminatezeros)(Mat, PetscBool);
202: PetscErrorCode (*getrowsumabs)(Mat, Vec);
203: PetscErrorCode (*getfactor)(Mat, MatSolverType, MatFactorType, Mat *);
204: /*139*/
205: PetscErrorCode (*getblockdiagonal)(Mat, Mat *); // NOTE: the caller of get{block, vblock}diagonal owns the returned matrix;
206: PetscErrorCode (*getvblockdiagonal)(Mat, Mat *); // they must destroy it after use
207: PetscErrorCode (*copyhashtoxaij)(Mat, Mat);
208: PetscErrorCode (*getcurrentmemtype)(Mat, PetscMemType *);
209: PetscErrorCode (*zerorowscolumnslocal)(Mat, PetscInt, const PetscInt[], PetscScalar, Vec, Vec);
210: };
211: /*
212: If you add MatOps entries above also add them to the MATOP enum
213: in include/petscmat.h
214: */
216: #include <petscsys.h>
218: typedef struct _p_MatRootName *MatRootName;
219: struct _p_MatRootName {
220: char *rname, *sname, *mname;
221: MatRootName next;
222: };
224: PETSC_EXTERN MatRootName MatRootNameList;
226: /*
227: Utility private matrix routines used outside Mat
228: */
229: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat, PetscBool, PetscReal, IS *);
230: PETSC_EXTERN PetscErrorCode MatShellGetScalingShifts(Mat, PetscScalar *, PetscScalar *, Vec *, Vec *, Vec *, Mat *, IS *, IS *);
232: #define MAT_SHELL_NOT_ALLOWED (void *)-1
234: /*
235: Utility private matrix routines
236: */
237: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat, MatType, MatReuse, Mat *);
238: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat, MatType, MatReuse, Mat *);
239: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat, MatType, MatReuse, Mat *);
240: PETSC_INTERN PetscErrorCode MatShellSetContext_Immutable(Mat, void *);
241: PETSC_INTERN PetscErrorCode MatShellSetContextDestroy_Immutable(Mat, PetscCtxDestroyFn *);
242: PETSC_INTERN PetscErrorCode MatShellSetManageScalingShifts_Immutable(Mat);
243: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat, Mat, MatStructure);
244: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat, Vec, InsertMode);
245: #if defined(PETSC_HAVE_SCALAPACK) && (defined(PETSC_USE_REAL_SINGLE) || defined(PETSC_USE_REAL_DOUBLE))
246: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
247: #endif
248: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_Basic(Mat, PetscCount, PetscInt[], PetscInt[]);
249: PETSC_INTERN PetscErrorCode MatSetValuesCOO_Basic(Mat, const PetscScalar[], InsertMode);
251: /* Scattering of dense matrices with strided PetscSF */
252: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatDenseScatter_Private(PetscSF, Mat, Mat, InsertMode, ScatterMode);
254: /* This can be moved to the public header after implementing some missing MatProducts */
255: PETSC_INTERN PetscErrorCode MatCreateFromISLocalToGlobalMapping(ISLocalToGlobalMapping, Mat, PetscBool, PetscBool, MatType, Mat *);
257: /* these callbacks rely on the old matrix function pointers for
258: matmat operations. They are unsafe, and should be removed.
259: However, the amount of work needed to clean up all the
260: implementations is not negligible */
261: PETSC_INTERN PetscErrorCode MatProductSymbolic_AB(Mat);
262: PETSC_INTERN PetscErrorCode MatProductNumeric_AB(Mat);
263: PETSC_INTERN PetscErrorCode MatProductSymbolic_AtB(Mat);
264: PETSC_INTERN PetscErrorCode MatProductNumeric_AtB(Mat);
265: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABt(Mat);
266: PETSC_INTERN PetscErrorCode MatProductNumeric_ABt(Mat);
267: PETSC_INTERN PetscErrorCode MatProductNumeric_PtAP(Mat);
268: PETSC_INTERN PetscErrorCode MatProductNumeric_RARt(Mat);
269: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC(Mat);
270: PETSC_INTERN PetscErrorCode MatProductNumeric_ABC(Mat);
272: PETSC_INTERN PetscErrorCode MatProductCreate_Private(Mat, Mat, Mat, Mat);
273: /* this callback handles all the different triple products and
274: does not rely on the function pointers; used by cuSPARSE/hipSPARSE and KOKKOS-KERNELS */
275: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC_Basic(Mat);
277: /* CreateGraph is common to AIJ seq and mpi */
278: PETSC_INTERN PetscErrorCode MatCreateGraph_Simple_AIJ(Mat, PetscBool, PetscBool, PetscReal, PetscInt, PetscInt[], Mat *);
280: #if defined(PETSC_CLANG_STATIC_ANALYZER)
281: template <typename Tm>
282: extern void MatCheckPreallocated(Tm, int);
283: template <typename Tm>
284: extern void MatCheckProduct(Tm, int);
285: #else /* PETSC_CLANG_STATIC_ANALYZER */
286: #define MatCheckPreallocated(A, arg) \
287: do { \
288: if (!(A)->preallocated) PetscCall(MatSetUp(A)); \
289: } while (0)
291: #if defined(PETSC_USE_DEBUG)
292: #define MatCheckProduct(A, arg) \
293: do { \
294: PetscCheck((A)->product, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Argument %d \"%s\" is not a matrix obtained from MatProductCreate()", (arg), #A); \
295: } while (0)
296: #else
297: #define MatCheckProduct(A, arg) \
298: do { \
299: } while (0)
300: #endif
301: #endif /* PETSC_CLANG_STATIC_ANALYZER */
303: /*
304: The stash is used to temporarily store inserted matrix values that
305: belong to another processor. During the assembly phase the stashed
306: values are moved to the correct processor and
307: */
309: typedef struct _MatStashSpace *PetscMatStashSpace;
311: struct _MatStashSpace {
312: PetscMatStashSpace next;
313: PetscScalar *space_head, *val;
314: PetscInt *idx, *idy;
315: PetscInt total_space_size;
316: PetscInt local_used;
317: PetscInt local_remaining;
318: };
320: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt, PetscInt, PetscMatStashSpace *);
321: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt, PetscMatStashSpace *, PetscScalar *, PetscInt *, PetscInt *);
322: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace *);
324: typedef struct {
325: PetscInt count;
326: } MatStashHeader;
328: typedef struct {
329: void *buffer; /* Of type blocktype, dynamically constructed */
330: PetscInt count;
331: char pending;
332: } MatStashFrame;
334: typedef struct _MatStash MatStash;
335: struct _MatStash {
336: PetscInt nmax; /* maximum stash size */
337: PetscInt umax; /* user specified max-size */
338: PetscInt oldnmax; /* the nmax value used previously */
339: PetscInt n; /* stash size */
340: PetscInt bs; /* block size of the stash */
341: PetscInt reallocs; /* preserve the no of mallocs invoked */
342: PetscMatStashSpace space_head, space; /* linked list to hold stashed global row/column numbers and matrix values */
344: PetscErrorCode (*ScatterBegin)(Mat, MatStash *, PetscInt *);
345: PetscErrorCode (*ScatterGetMesg)(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
346: PetscErrorCode (*ScatterEnd)(MatStash *);
347: PetscErrorCode (*ScatterDestroy)(MatStash *);
349: /* The following variables are used for communication */
350: MPI_Comm comm;
351: PetscMPIInt size, rank;
352: PetscMPIInt tag1, tag2;
353: MPI_Request *send_waits; /* array of send requests */
354: MPI_Request *recv_waits; /* array of receive requests */
355: MPI_Status *send_status; /* array of send status */
356: PetscMPIInt nsends, nrecvs; /* numbers of sends and receives */
357: PetscScalar *svalues; /* sending data */
358: PetscInt *sindices;
359: PetscScalar **rvalues; /* receiving data (values) */
360: PetscInt **rindices; /* receiving data (indices) */
361: PetscMPIInt nprocessed; /* number of messages already processed */
362: PetscMPIInt *flg_v; /* indicates what messages have arrived so far and from whom */
363: PetscBool reproduce;
364: PetscMPIInt reproduce_count;
366: /* The following variables are used for BTS communication */
367: PetscBool first_assembly_done; /* Is the first time matrix assembly done? */
368: PetscBool use_status; /* Use MPI_Status to determine number of items in each message */
369: PetscMPIInt nsendranks;
370: PetscMPIInt nrecvranks;
371: PetscMPIInt *sendranks;
372: PetscMPIInt *recvranks;
373: MatStashHeader *sendhdr, *recvhdr;
374: MatStashFrame *sendframes; /* pointers to the main messages */
375: MatStashFrame *recvframes;
376: MatStashFrame *recvframe_active;
377: PetscInt recvframe_i; /* index of block within active frame */
378: PetscInt recvframe_count; /* Count actually sent for current frame */
379: PetscMPIInt recvcount; /* Number of receives processed so far */
380: PetscMPIInt *some_indices; /* From last call to MPI_Waitsome */
381: MPI_Status *some_statuses; /* Statuses from last call to MPI_Waitsome */
382: PetscMPIInt some_count; /* Number of requests completed in last call to MPI_Waitsome */
383: PetscMPIInt some_i; /* Index of request currently being processed */
384: MPI_Request *sendreqs;
385: MPI_Request *recvreqs;
386: PetscSegBuffer segsendblocks;
387: PetscSegBuffer segrecvframe;
388: PetscSegBuffer segrecvblocks;
389: MPI_Datatype blocktype;
390: size_t blocktype_size;
391: InsertMode *insertmode; /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
392: };
394: #if !defined(PETSC_HAVE_MPIUNI)
395: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash *);
396: #endif
397: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm, PetscInt, MatStash *);
398: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash *);
399: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash *);
400: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash *, PetscInt);
401: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash *, PetscInt *, PetscInt *);
402: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscBool);
403: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscBool);
404: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
405: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash *, PetscInt, PetscInt, const PetscInt[], const PetscScalar[], PetscInt, PetscInt, PetscInt);
406: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat, MatStash *, PetscInt *);
407: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash *, PetscMPIInt *, PetscInt **, PetscInt **, PetscScalar **, PetscInt *);
408: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat, MatInfoType, MatInfo *);
410: typedef struct {
411: PetscInt dim;
412: PetscInt dims[4];
413: PetscInt starts[4];
414: PetscBool noc; /* this is a single component problem, hence user will not set MatStencil.c */
415: } MatStencilInfo;
417: /* Info about using compressed row format */
418: typedef struct {
419: PetscBool use; /* indicates compressed rows have been checked and will be used */
420: PetscInt nrows; /* number of non-zero rows */
421: PetscInt *i; /* compressed row pointer */
422: PetscInt *rindex; /* compressed row index */
423: } Mat_CompressedRow;
424: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat, PetscInt, Mat_CompressedRow *, PetscInt *, PetscInt, PetscReal);
426: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
427: PetscInt nzlocal, nsends, nrecvs;
428: PetscMPIInt *send_rank, *recv_rank;
429: PetscInt *sbuf_nz, *rbuf_nz, *sbuf_j, **rbuf_j;
430: PetscScalar *sbuf_a, **rbuf_a;
431: MPI_Comm subcomm; /* when user does not provide a subcomm */
432: IS isrow, iscol;
433: Mat *matseq;
434: } Mat_Redundant;
436: typedef struct { /* used by MatProduct() */
437: MatProductType type;
438: char *alg;
439: Mat A, B, C, Dwork;
440: 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, .. */
441: 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 .. */
442: PetscBool symbolic_used_the_fact_C_is_symmetric; /* MatMatMult(A,B,MAT_REUSE_MATRIX,..&C) is still legitimate), we need to redo symbolic! */
443: PetscObjectParameterDeclare(PetscReal, fill);
444: 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 */
445: PetscBool setfromoptionscalled;
447: /* Some products may display the information on the algorithm used */
448: PetscErrorCode (*view)(Mat, PetscViewer);
450: /* many products have intermediate data structures, each specific to Mat types and product type */
451: PetscBool clear; /* whether or not to clear the data structures after MatProductNumeric has been called */
452: void *data; /* where to stash those structures */
453: PetscCtxDestroyFn *destroy; /* freeing data */
454: } Mat_Product;
456: struct _p_Mat {
457: PETSCHEADER(struct _MatOps);
458: PetscLayout rmap, cmap;
459: void *data; /* implementation-specific data */
460: MatFactorType factortype; /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
461: PetscBool trivialsymbolic; /* indicates the symbolic factorization doesn't actually do a symbolic factorization, it is delayed to the numeric factorization */
462: PetscBool canuseordering; /* factorization can use ordering provide to routine (most PETSc implementations) */
463: MatOrderingType preferredordering[MAT_FACTOR_NUM_TYPES]; /* what is the preferred (or default) ordering for the matrix solver type */
464: PetscBool assembled; /* is the matrix assembled? */
465: PetscBool was_assembled; /* new values inserted into assembled mat */
466: PetscInt num_ass; /* number of times matrix has been assembled */
467: PetscObjectState nonzerostate; /* each time new nonzeros locations are introduced into the matrix this is updated */
468: PetscObjectState ass_nonzerostate; /* nonzero state at last assembly */
469: MatInfo info; /* matrix information */
470: InsertMode insertmode; /* have values been inserted in matrix or added? */
471: MatStash stash, bstash; /* used for assembling off-proc mat emements */
472: MatNullSpace nullsp; /* null space (operator is singular) */
473: MatNullSpace transnullsp; /* null space of transpose of operator */
474: MatNullSpace nearnullsp; /* near null space to be used by multigrid methods */
475: PetscInt congruentlayouts; /* are the rows and columns layouts congruent? */
476: PetscBool preallocated;
477: MatStencilInfo stencil; /* information for structured grid */
478: PetscBool3 symmetric, hermitian, structurally_symmetric, spd;
479: PetscBool symmetry_eternal, structural_symmetry_eternal, spd_eternal;
480: PetscBool nooffprocentries, nooffproczerorows;
481: PetscBool assembly_subset; /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
482: PetscBool submat_singleis; /* for efficient PCSetUp_ASM() */
483: PetscBool structure_only;
484: PetscBool sortedfull; /* full, sorted rows are inserted */
485: PetscBool force_diagonals; /* set by MAT_FORCE_DIAGONAL_ENTRIES */
486: #if defined(PETSC_HAVE_DEVICE)
487: PetscOffloadMask offloadmask; /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
488: PetscBool boundtocpu;
489: PetscBool bindingpropagates;
490: #endif
491: char *defaultrandtype;
492: void *spptr; /* pointer for special library like SuperLU */
493: char *solvertype;
494: PetscBool checksymmetryonassembly, checknullspaceonassembly;
495: PetscReal checksymmetrytol;
496: Mat schur; /* Schur complement matrix */
497: MatFactorSchurStatus schur_status; /* status of the Schur complement matrix */
498: Mat_Redundant *redundant; /* used by MatCreateRedundantMatrix() */
499: PetscBool erroriffailure; /* Generate an error if detected (for example a zero pivot) instead of returning */
500: MatFactorError factorerrortype; /* type of error in factorization */
501: PetscReal factorerror_zeropivot_value; /* If numerical zero pivot was detected this is the computed value */
502: PetscInt factorerror_zeropivot_row; /* Row where zero pivot was detected */
503: PetscInt nblocks, *bsizes; /* support for MatSetVariableBlockSizes() */
504: PetscInt p_cstart, p_rank, p_cend, n_rank; /* Information from parallel MatComputeVariableBlockEnvelope() */
505: PetscBool p_parallel;
506: char *defaultvectype;
507: Mat_Product *product;
508: PetscBool form_explicit_transpose; /* hint to generate an explicit mat tranpsose for operations like MatMultTranspose() */
509: PetscBool transupdated; /* whether or not the explicitly generated transpose is up-to-date */
510: char *factorprefix; /* the prefix to use with factored matrix that is created */
511: PetscBool hash_active; /* indicates MatSetValues() is being handled by hashing */
512: };
514: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat, PetscScalar, Mat, MatStructure);
515: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat, Mat, PetscScalar, Mat, MatStructure);
516: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat, Mat, Mat *);
517: PETSC_INTERN PetscErrorCode MatAXPY_Dense_Nest(Mat, PetscScalar, Mat);
519: PETSC_INTERN PetscErrorCode MatSetUp_Default(Mat);
521: /*
522: Utility for MatZeroRows
523: */
524: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat, PetscInt, const PetscInt *, PetscInt *, PetscInt **);
526: /*
527: Utility for MatView/MatLoad
528: */
529: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat, PetscViewer);
530: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat, PetscViewer);
532: /*
533: Object for partitioning graphs
534: */
536: typedef struct _MatPartitioningOps *MatPartitioningOps;
537: struct _MatPartitioningOps {
538: PetscErrorCode (*apply)(MatPartitioning, IS *);
539: PetscErrorCode (*applynd)(MatPartitioning, IS *);
540: PetscErrorCode (*setfromoptions)(MatPartitioning, PetscOptionItems);
541: PetscErrorCode (*destroy)(MatPartitioning);
542: PetscErrorCode (*view)(MatPartitioning, PetscViewer);
543: PetscErrorCode (*improve)(MatPartitioning, IS *);
544: };
546: struct _p_MatPartitioning {
547: PETSCHEADER(struct _MatPartitioningOps);
548: Mat adj;
549: PetscInt *vertex_weights;
550: PetscReal *part_weights;
551: PetscInt n; /* number of partitions */
552: PetscInt ncon; /* number of vertex weights per vertex */
553: void *data;
554: PetscBool use_edge_weights; /* A flag indicates whether or not to use edge weights */
555: };
557: /* needed for parallel nested dissection by ParMetis and PTSCOTCH */
558: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt, PetscInt[], PetscInt[], PetscInt[]);
560: /*
561: Object for coarsen graphs
562: */
563: typedef struct _MatCoarsenOps *MatCoarsenOps;
564: struct _MatCoarsenOps {
565: PetscErrorCode (*apply)(MatCoarsen);
566: PetscErrorCode (*setfromoptions)(MatCoarsen, PetscOptionItems);
567: PetscErrorCode (*destroy)(MatCoarsen);
568: PetscErrorCode (*view)(MatCoarsen, PetscViewer);
569: };
571: #define MAT_COARSEN_STRENGTH_INDEX_SIZE 3
572: struct _p_MatCoarsen {
573: PETSCHEADER(struct _MatCoarsenOps);
574: Mat graph;
575: void *subctx;
576: /* */
577: PetscBool strict_aggs;
578: IS perm;
579: PetscCoarsenData *agg_lists;
580: PetscInt max_it; /* number of iterations in HEM */
581: PetscReal threshold; /* HEM can filter interim graphs */
582: PetscInt strength_index_size;
583: PetscInt strength_index[MAT_COARSEN_STRENGTH_INDEX_SIZE];
584: };
586: PETSC_EXTERN PetscErrorCode MatCoarsenMISKSetDistance(MatCoarsen, PetscInt);
587: PETSC_EXTERN PetscErrorCode MatCoarsenMISKGetDistance(MatCoarsen, PetscInt *);
589: /*
590: Used in aijdevice.h
591: */
592: typedef struct {
593: PetscInt *i;
594: PetscInt *j;
595: PetscScalar *a;
596: PetscInt n;
597: PetscInt ignorezeroentries;
598: } PetscCSRDataStructure;
600: /*
601: MatFDColoring is used to compute Jacobian matrices efficiently
602: via coloring. The data structure is explained below in an example.
604: Color = 0 1 0 2 | 2 3 0
605: ---------------------------------------------------
606: 00 01 | 05
607: 10 11 | 14 15 Processor 0
608: 22 23 | 25
609: 32 33 |
610: ===================================================
611: | 44 45 46
612: 50 | 55 Processor 1
613: | 64 66
614: ---------------------------------------------------
616: ncolors = 4;
618: ncolumns = {2,1,1,0}
619: columns = {{0,2},{1},{3},{}}
620: nrows = {4,2,3,3}
621: rows = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
622: vwscale = {dx(0),dx(1),dx(2),dx(3)} MPI Vec
623: vscale = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)} Seq Vec
625: ncolumns = {1,0,1,1}
626: columns = {{6},{},{4},{5}}
627: nrows = {3,0,2,2}
628: rows = {{0,1,2},{},{1,2},{1,2}}
629: vwscale = {dx(4),dx(5),dx(6)} MPI Vec
630: vscale = {dx(0),dx(4),dx(5),dx(6)} Seq Vec
632: See the routine MatFDColoringApply() for how this data is used
633: to compute the Jacobian.
635: */
636: typedef struct {
637: PetscInt row;
638: PetscInt col;
639: PetscScalar *valaddr; /* address of value */
640: } MatEntry;
642: typedef struct {
643: PetscInt row;
644: PetscScalar *valaddr; /* address of value */
645: } MatEntry2;
647: struct _p_MatFDColoring {
648: PETSCHEADER(int);
649: PetscInt M, N, m; /* total rows, columns; local rows */
650: PetscInt rstart; /* first row owned by local processor */
651: PetscInt ncolors; /* number of colors */
652: PetscInt *ncolumns; /* number of local columns for a color */
653: PetscInt **columns; /* lists the local columns of each color (using global column numbering) */
654: IS *isa; /* these are the IS that contain the column values given in columns */
655: PetscInt *nrows; /* number of local rows for each color */
656: MatEntry *matentry; /* holds (row, column, address of value) for Jacobian matrix entry */
657: MatEntry2 *matentry2; /* holds (row, address of value) for Jacobian matrix entry */
658: PetscScalar *dy; /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
659: PetscReal error_rel; /* square root of relative error in computing function */
660: PetscReal umin; /* minimum allowable u'dx value */
661: Vec w1, w2, w3; /* work vectors used in computing Jacobian */
662: PetscBool fset; /* indicates that the initial function value F(X) is set */
663: MatFDColoringFn *f; /* function that defines Jacobian */
664: void *fctx; /* optional user-defined context for use by the function f */
665: Vec vscale; /* holds FD scaling, i.e. 1/dx for each perturbed column */
666: PetscInt currentcolor; /* color for which function evaluation is being done now */
667: const char *htype; /* "wp" or "ds" */
668: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
669: PetscInt brows, bcols; /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
670: PetscBool setupcalled; /* true if setup has been called */
671: PetscBool viewed; /* true if the -mat_fd_coloring_view has been triggered already */
672: PetscFortranCallbackFn *ftn_func_pointer; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
673: void *ftn_func_cntx;
674: PetscObjectId matid; /* matrix this object was created with, must always be the same */
675: };
677: typedef struct _MatColoringOps *MatColoringOps;
678: struct _MatColoringOps {
679: PetscErrorCode (*destroy)(MatColoring);
680: PetscErrorCode (*setfromoptions)(MatColoring, PetscOptionItems);
681: PetscErrorCode (*view)(MatColoring, PetscViewer);
682: PetscErrorCode (*apply)(MatColoring, ISColoring *);
683: PetscErrorCode (*weights)(MatColoring, PetscReal **, PetscInt **);
684: };
686: struct _p_MatColoring {
687: PETSCHEADER(struct _MatColoringOps);
688: Mat mat;
689: PetscInt dist; /* distance of the coloring */
690: PetscInt maxcolors; /* the maximum number of colors returned, maxcolors=1 for MIS */
691: void *data; /* inner context */
692: PetscBool valid; /* check to see if what is produced is a valid coloring */
693: MatColoringWeightType weight_type; /* type of weight computation to be performed */
694: PetscReal *user_weights; /* custom weights and permutation */
695: PetscInt *user_lperm;
696: PetscBool valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
697: };
699: struct _p_MatTransposeColoring {
700: PETSCHEADER(int);
701: PetscInt M, N, m; /* total rows, columns; local rows */
702: PetscInt rstart; /* first row owned by local processor */
703: PetscInt ncolors; /* number of colors */
704: PetscInt *ncolumns; /* number of local columns for a color */
705: PetscInt *nrows; /* number of local rows for each color */
706: PetscInt currentcolor; /* color for which function evaluation is being done now */
707: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
709: PetscInt *colorforrow, *colorforcol; /* pointer to rows and columns */
710: PetscInt *rows; /* lists the local rows for each color (using the local row numbering) */
711: PetscInt *den2sp; /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
712: PetscInt *columns; /* lists the local columns of each color (using global column numbering) */
713: PetscInt brows; /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
714: PetscInt *lstart; /* array used for loop over row blocks of Csparse */
715: };
717: /*
718: Null space context for preconditioner/operators
719: */
720: struct _p_MatNullSpace {
721: PETSCHEADER(int);
722: PetscBool has_cnst;
723: PetscInt n;
724: Vec *vecs;
725: PetscScalar *alpha; /* for projections */
726: MatNullSpaceRemoveFn *remove; /* for user provided removal function */
727: void *rmctx; /* context for remove() function */
728: };
730: /*
731: Internal data structure for MATMPIDENSE
732: */
733: typedef struct {
734: Mat A; /* local submatrix */
736: /* The following variables are used for matrix assembly */
737: PetscBool donotstash; /* Flag indicating if values should be stashed */
738: MPI_Request *send_waits; /* array of send requests */
739: MPI_Request *recv_waits; /* array of receive requests */
740: PetscInt nsends, nrecvs; /* numbers of sends and receives */
741: PetscScalar *svalues, *rvalues; /* sending and receiving data */
742: PetscInt rmax; /* maximum message length */
744: /* The following variables are used for matrix-vector products */
745: Vec lvec; /* local vector */
746: PetscSF Mvctx; /* for mat-mult communications */
747: PetscBool roworiented; /* if true, row-oriented input (default) */
749: /* Support for MatDenseGetColumnVec and MatDenseGetSubMatrix */
750: Mat cmat; /* matrix representation of a given subset of columns */
751: Vec cvec; /* vector representation of a given column */
752: const PetscScalar *ptrinuse; /* holds array to be restored (just a placeholder) */
753: PetscInt vecinuse; /* if cvec is in use (col = vecinuse-1) */
754: PetscInt matinuse; /* if cmat is in use (cbegin = matinuse-1) */
755: /* if this is from MatDenseGetSubMatrix, which columns and rows does it correspond to? */
756: PetscInt sub_rbegin;
757: PetscInt sub_rend;
758: PetscInt sub_cbegin;
759: PetscInt sub_cend;
760: } Mat_MPIDense;
762: /*
763: Checking zero pivot for LU, ILU preconditioners.
764: */
765: typedef struct {
766: PetscInt nshift, nshift_max;
767: PetscReal shift_amount, shift_lo, shift_hi, shift_top, shift_fraction;
768: PetscBool newshift;
769: PetscReal rs; /* active row sum of abs(off-diagonals) */
770: PetscScalar pv; /* pivot of the active row */
771: } FactorShiftCtx;
773: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatTransposeCheckNonzeroState_Private(Mat, Mat);
775: /*
776: Used by MatTranspose() and potentially other functions to track the matrix used in the generation of another matrix
777: */
778: typedef struct {
779: PetscObjectId id;
780: PetscObjectState state;
781: PetscObjectState nonzerostate;
782: } MatParentState;
784: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
785: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat, PetscInt, PetscInt);
787: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatShift_Basic(Mat, PetscScalar);
789: static inline PetscErrorCode MatPivotCheck_nz(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
790: {
791: PetscReal _rs = sctx->rs;
792: PetscReal _zero = info->zeropivot * _rs;
794: PetscFunctionBegin;
795: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
796: /* force |diag| > zeropivot*rs */
797: if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
798: else sctx->shift_amount *= 2.0;
799: sctx->newshift = PETSC_TRUE;
800: (sctx->nshift)++;
801: } else {
802: sctx->newshift = PETSC_FALSE;
803: }
804: PetscFunctionReturn(PETSC_SUCCESS);
805: }
807: static inline PetscErrorCode MatPivotCheck_pd(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
808: {
809: PetscReal _rs = sctx->rs;
810: PetscReal _zero = info->zeropivot * _rs;
812: PetscFunctionBegin;
813: if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
814: /* force matfactor to be diagonally dominant */
815: if (sctx->nshift == sctx->nshift_max) {
816: sctx->shift_fraction = sctx->shift_hi;
817: } else {
818: sctx->shift_lo = sctx->shift_fraction;
819: sctx->shift_fraction = (sctx->shift_hi + sctx->shift_lo) / (PetscReal)2.;
820: }
821: sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
822: sctx->nshift++;
823: sctx->newshift = PETSC_TRUE;
824: } else {
825: sctx->newshift = PETSC_FALSE;
826: }
827: PetscFunctionReturn(PETSC_SUCCESS);
828: }
830: static inline PetscErrorCode MatPivotCheck_inblocks(PETSC_UNUSED Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PETSC_UNUSED PetscInt row)
831: {
832: PetscReal _zero = info->zeropivot;
834: PetscFunctionBegin;
835: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
836: sctx->pv += info->shiftamount;
837: sctx->shift_amount = 0.0;
838: sctx->nshift++;
839: }
840: sctx->newshift = PETSC_FALSE;
841: PetscFunctionReturn(PETSC_SUCCESS);
842: }
844: static inline PetscErrorCode MatPivotCheck_none(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
845: {
846: PetscReal _zero = info->zeropivot;
848: PetscFunctionBegin;
849: sctx->newshift = PETSC_FALSE;
850: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
851: 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);
852: PetscCall(PetscInfo(mat, "Detected zero pivot in factorization in row %" PetscInt_FMT " value %g tolerance %g\n", row, (double)PetscAbsScalar(sctx->pv), (double)_zero));
853: fact->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
854: fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
855: fact->factorerror_zeropivot_row = row;
856: }
857: PetscFunctionReturn(PETSC_SUCCESS);
858: }
860: static inline PetscErrorCode MatPivotCheck(Mat fact, Mat mat, const MatFactorInfo *info, FactorShiftCtx *sctx, PetscInt row)
861: {
862: PetscFunctionBegin;
863: if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) PetscCall(MatPivotCheck_nz(mat, info, sctx, row));
864: else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) PetscCall(MatPivotCheck_pd(mat, info, sctx, row));
865: else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) PetscCall(MatPivotCheck_inblocks(mat, info, sctx, row));
866: else PetscCall(MatPivotCheck_none(fact, mat, info, sctx, row));
867: PetscFunctionReturn(PETSC_SUCCESS);
868: }
870: #include <petscbt.h>
871: /*
872: Create and initialize a linked list
873: Input Parameters:
874: idx_start - starting index of the list
875: lnk_max - max value of lnk indicating the end of the list
876: nlnk - max length of the list
877: Output Parameters:
878: lnk - list initialized
879: bt - PetscBT (bitarray) with all bits set to false
880: lnk_empty - flg indicating the list is empty
881: */
882: #define PetscLLCreate(idx_start, lnk_max, nlnk, lnk, bt) ((PetscErrorCode)(PetscMalloc1(nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, PETSC_SUCCESS)))
884: #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)))
886: 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)
887: {
888: PetscInt location;
890: PetscFunctionBegin;
891: /* start from the beginning if entry < previous entry */
892: if (!assume_sorted && k && entry < *lnkdata) *lnkdata = idx_start;
893: /* search for insertion location */
894: do {
895: location = *lnkdata;
896: *lnkdata = lnk[location];
897: } while (entry > *lnkdata);
898: /* insertion location is found, add entry into lnk */
899: lnk[location] = entry;
900: lnk[entry] = *lnkdata;
901: ++(*nlnk);
902: *lnkdata = entry; /* next search starts from here if next_entry > entry */
903: PetscFunctionReturn(PETSC_SUCCESS);
904: }
906: 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)
907: {
908: PetscFunctionBegin;
909: *nlnk = 0;
910: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
911: const PetscInt entry = indices[k];
913: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk));
914: }
915: PetscFunctionReturn(PETSC_SUCCESS);
916: }
918: /*
919: Add an index set into a sorted linked list
920: Input Parameters:
921: nidx - number of input indices
922: indices - integer array
923: idx_start - starting index of the list
924: lnk - linked list(an integer array) that is created
925: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
926: output Parameters:
927: nlnk - number of newly added indices
928: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
929: bt - updated PetscBT (bitarray)
930: */
931: static inline PetscErrorCode PetscLLAdd(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
932: {
933: PetscFunctionBegin;
934: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_FALSE));
935: PetscFunctionReturn(PETSC_SUCCESS);
936: }
938: /*
939: Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata = idx_start;'
940: Input Parameters:
941: nidx - number of input indices
942: indices - sorted integer array
943: idx_start - starting index of the list
944: lnk - linked list(an integer array) that is created
945: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
946: output Parameters:
947: nlnk - number of newly added indices
948: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
949: bt - updated PetscBT (bitarray)
950: */
951: static inline PetscErrorCode PetscLLAddSorted(PetscInt nidx, const PetscInt *PETSC_RESTRICT indices, PetscInt idx_start, PetscInt *PETSC_RESTRICT nlnk, PetscInt *PETSC_RESTRICT lnk, PetscBT bt)
952: {
953: PetscFunctionBegin;
954: PetscCall(PetscLLAdd_Private(nidx, indices, idx_start, nlnk, lnk, bt, PETSC_TRUE));
955: PetscFunctionReturn(PETSC_SUCCESS);
956: }
958: /*
959: Add a permuted index set into a sorted linked list
960: Input Parameters:
961: nidx - number of input indices
962: indices - integer array
963: perm - permutation of indices
964: idx_start - starting index of the list
965: lnk - linked list(an integer array) that is created
966: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
967: output Parameters:
968: nlnk - number of newly added indices
969: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
970: bt - updated PetscBT (bitarray)
971: */
972: 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)
973: {
974: PetscFunctionBegin;
975: *nlnk = 0;
976: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
977: const PetscInt entry = perm[indices[k]];
979: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk));
980: }
981: PetscFunctionReturn(PETSC_SUCCESS);
982: }
984: #if 0
985: /* this appears to be unused? */
986: static inline PetscErrorCode PetscLLAddSorted_new(PetscInt nidx, PetscInt *indices, PetscInt idx_start, PetscBool *lnk_empty, PetscInt *nlnk, PetscInt *lnk, PetscBT bt)
987: {
988: PetscInt lnkdata = idx_start;
990: PetscFunctionBegin;
991: if (*lnk_empty) {
992: for (PetscInt k = 0; k < nidx; ++k) {
993: const PetscInt entry = indices[k], location = lnkdata;
995: PetscCall(PetscBTSet(bt,entry)); /* mark the new entry */
996: lnkdata = lnk[location];
997: /* insertion location is found, add entry into lnk */
998: lnk[location] = entry;
999: lnk[entry] = lnkdata;
1000: lnkdata = entry; /* next search starts from here */
1001: }
1002: /* lnk[indices[nidx-1]] = lnk[idx_start];
1003: lnk[idx_start] = indices[0];
1004: PetscCall(PetscBTSet(bt,indices[0]));
1005: for (_k=1; _k<nidx; _k++) {
1006: PetscCall(PetscBTSet(bt,indices[_k]));
1007: lnk[indices[_k-1]] = indices[_k];
1008: }
1009: */
1010: *nlnk = nidx;
1011: *lnk_empty = PETSC_FALSE;
1012: } else {
1013: *nlnk = 0;
1014: for (PetscInt k = 0; k < nidx; ++k) {
1015: const PetscInt entry = indices[k];
1017: if (!PetscBTLookupSet(bt,entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE,k,idx_start,entry,nlnk,&lnkdata,lnk));
1018: }
1019: }
1020: PetscFunctionReturn(PETSC_SUCCESS);
1021: }
1022: #endif
1024: /*
1025: Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
1026: Same as PetscLLAddSorted() with an additional operation:
1027: count the number of input indices that are no larger than 'diag'
1028: Input Parameters:
1029: indices - sorted integer array
1030: idx_start - starting index of the list, index of pivot row
1031: lnk - linked list(an integer array) that is created
1032: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1033: diag - index of the active row in LUFactorSymbolic
1034: nzbd - number of input indices with indices <= idx_start
1035: im - im[idx_start] is initialized as num of nonzero entries in row=idx_start
1036: output Parameters:
1037: nlnk - number of newly added indices
1038: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
1039: bt - updated PetscBT (bitarray)
1040: im - im[idx_start]: unchanged if diag is not an entry
1041: : num of entries with indices <= diag if diag is an entry
1042: */
1043: 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)
1044: {
1045: const PetscInt nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */
1047: PetscFunctionBegin;
1048: *nlnk = 0;
1049: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1050: const PetscInt entry = indices[k];
1052: ++nzbd;
1053: if (entry == diag) im[idx_start] = nzbd;
1054: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscLLInsertLocation_Private(PETSC_TRUE, k, idx_start, entry, nlnk, &lnkdata, lnk));
1055: }
1056: PetscFunctionReturn(PETSC_SUCCESS);
1057: }
1059: /*
1060: Copy data on the list into an array, then initialize the list
1061: Input Parameters:
1062: idx_start - starting index of the list
1063: lnk_max - max value of lnk indicating the end of the list
1064: nlnk - number of data on the list to be copied
1065: lnk - linked list
1066: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1067: output Parameters:
1068: indices - array that contains the copied data
1069: lnk - linked list that is cleaned and initialize
1070: bt - PetscBT (bitarray) with all bits set to false
1071: */
1072: static inline PetscErrorCode PetscLLClean(PetscInt idx_start, PetscInt lnk_max, PetscInt nlnk, PetscInt *PETSC_RESTRICT lnk, PetscInt *PETSC_RESTRICT indices, PetscBT bt)
1073: {
1074: PetscFunctionBegin;
1075: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1076: idx = lnk[idx];
1077: indices[j] = idx;
1078: PetscCall(PetscBTClear(bt, idx));
1079: }
1080: lnk[idx_start] = lnk_max;
1081: PetscFunctionReturn(PETSC_SUCCESS);
1082: }
1084: /*
1085: Free memories used by the list
1086: */
1087: #define PetscLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1089: /* Routines below are used for incomplete matrix factorization */
1090: /*
1091: Create and initialize a linked list and its levels
1092: Input Parameters:
1093: idx_start - starting index of the list
1094: lnk_max - max value of lnk indicating the end of the list
1095: nlnk - max length of the list
1096: Output Parameters:
1097: lnk - list initialized
1098: lnk_lvl - array of size nlnk for storing levels of lnk
1099: bt - PetscBT (bitarray) with all bits set to false
1100: */
1101: #define PetscIncompleteLLCreate(idx_start, lnk_max, nlnk, lnk, lnk_lvl, bt) \
1102: ((PetscErrorCode)(PetscIntMultError(2, nlnk, NULL) || PetscMalloc1(2 * nlnk, &lnk) || PetscBTCreate(nlnk, &(bt)) || (lnk[idx_start] = lnk_max, lnk_lvl = lnk + nlnk, PETSC_SUCCESS)))
1104: 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)
1105: {
1106: PetscFunctionBegin;
1107: PetscCall(PetscLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, lnkdata, lnk));
1108: lnklvl[entry] = newval;
1109: PetscFunctionReturn(PETSC_SUCCESS);
1110: }
1112: /*
1113: Initialize a sorted linked list used for ILU and ICC
1114: Input Parameters:
1115: nidx - number of input idx
1116: idx - integer array used for storing column indices
1117: idx_start - starting index of the list
1118: perm - indices of an IS
1119: lnk - linked list(an integer array) that is created
1120: lnklvl - levels of lnk
1121: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1122: output Parameters:
1123: nlnk - number of newly added idx
1124: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1125: lnklvl - levels of lnk
1126: bt - updated PetscBT (bitarray)
1127: */
1128: 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)
1129: {
1130: PetscFunctionBegin;
1131: *nlnk = 0;
1132: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1133: const PetscInt entry = perm[idx[k]];
1135: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(PETSC_FALSE, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, 0));
1136: }
1137: PetscFunctionReturn(PETSC_SUCCESS);
1138: }
1140: 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)
1141: {
1142: PetscFunctionBegin;
1143: *nlnk = 0;
1144: for (PetscInt k = 0, lnkdata = idx_start; k < nidx; ++k) {
1145: const PetscInt incrlev = idxlvl[k] + prow_offset + 1;
1147: if (incrlev <= level) {
1148: const PetscInt entry = idx[k];
1150: if (!PetscBTLookupSet(bt, entry)) PetscCall(PetscIncompleteLLInsertLocation_Private(assume_sorted, k, idx_start, entry, nlnk, &lnkdata, lnk, lnklvl, incrlev));
1151: else if (lnklvl[entry] > incrlev) lnklvl[entry] = incrlev; /* existing entry */
1152: }
1153: }
1154: PetscFunctionReturn(PETSC_SUCCESS);
1155: }
1157: /*
1158: Add a SORTED index set into a sorted linked list for ICC
1159: Input Parameters:
1160: nidx - number of input indices
1161: idx - sorted integer array used for storing column indices
1162: level - level of fill, e.g., ICC(level)
1163: idxlvl - level of idx
1164: idx_start - starting index of the list
1165: lnk - linked list(an integer array) that is created
1166: lnklvl - levels of lnk
1167: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1168: idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1169: output Parameters:
1170: nlnk - number of newly added indices
1171: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1172: lnklvl - levels of lnk
1173: bt - updated PetscBT (bitarray)
1174: Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1175: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1176: */
1177: 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)
1178: {
1179: PetscFunctionBegin;
1180: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, idxlvl_prow, PETSC_TRUE));
1181: PetscFunctionReturn(PETSC_SUCCESS);
1182: }
1184: /*
1185: Add a SORTED index set into a sorted linked list for ILU
1186: Input Parameters:
1187: nidx - number of input indices
1188: idx - sorted integer array used for storing column indices
1189: level - level of fill, e.g., ICC(level)
1190: idxlvl - level of idx
1191: idx_start - starting index of the list
1192: lnk - linked list(an integer array) that is created
1193: lnklvl - levels of lnk
1194: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1195: prow - the row number of idx
1196: output Parameters:
1197: nlnk - number of newly added idx
1198: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1199: lnklvl - levels of lnk
1200: bt - updated PetscBT (bitarray)
1202: Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1203: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1204: */
1205: 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)
1206: {
1207: PetscFunctionBegin;
1208: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, lnklvl[prow], PETSC_TRUE));
1209: PetscFunctionReturn(PETSC_SUCCESS);
1210: }
1212: /*
1213: Add a index set into a sorted linked list
1214: Input Parameters:
1215: nidx - number of input idx
1216: idx - integer array used for storing column indices
1217: level - level of fill, e.g., ICC(level)
1218: idxlvl - level of idx
1219: idx_start - starting index of the list
1220: lnk - linked list(an integer array) that is created
1221: lnklvl - levels of lnk
1222: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1223: output Parameters:
1224: nlnk - number of newly added idx
1225: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1226: lnklvl - levels of lnk
1227: bt - updated PetscBT (bitarray)
1228: */
1229: 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)
1230: {
1231: PetscFunctionBegin;
1232: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_FALSE));
1233: PetscFunctionReturn(PETSC_SUCCESS);
1234: }
1236: /*
1237: Add a SORTED index set into a sorted linked list
1238: Input Parameters:
1239: nidx - number of input indices
1240: idx - sorted integer array used for storing column indices
1241: level - level of fill, e.g., ICC(level)
1242: idxlvl - level of idx
1243: idx_start - starting index of the list
1244: lnk - linked list(an integer array) that is created
1245: lnklvl - levels of lnk
1246: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1247: output Parameters:
1248: nlnk - number of newly added idx
1249: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1250: lnklvl - levels of lnk
1251: bt - updated PetscBT (bitarray)
1252: */
1253: 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)
1254: {
1255: PetscFunctionBegin;
1256: PetscCall(PetscIncompleteLLAdd_Private(nidx, idx, level, idxlvl, idx_start, nlnk, lnk, lnklvl, bt, 0, PETSC_TRUE));
1257: PetscFunctionReturn(PETSC_SUCCESS);
1258: }
1260: /*
1261: Copy data on the list into an array, then initialize the list
1262: Input Parameters:
1263: idx_start - starting index of the list
1264: lnk_max - max value of lnk indicating the end of the list
1265: nlnk - number of data on the list to be copied
1266: lnk - linked list
1267: lnklvl - level of lnk
1268: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1269: output Parameters:
1270: indices - array that contains the copied data
1271: lnk - linked list that is cleaned and initialize
1272: lnklvl - level of lnk that is reinitialized
1273: bt - PetscBT (bitarray) with all bits set to false
1274: */
1275: 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)
1276: {
1277: PetscFunctionBegin;
1278: for (PetscInt j = 0, idx = idx_start; j < nlnk; ++j) {
1279: idx = lnk[idx];
1280: indices[j] = idx;
1281: indiceslvl[j] = lnklvl[idx];
1282: lnklvl[idx] = -1;
1283: PetscCall(PetscBTClear(bt, idx));
1284: }
1285: lnk[idx_start] = lnk_max;
1286: PetscFunctionReturn(PETSC_SUCCESS);
1287: }
1289: /*
1290: Free memories used by the list
1291: */
1292: #define PetscIncompleteLLDestroy(lnk, bt) ((PetscErrorCode)(PetscFree(lnk) || PetscBTDestroy(&(bt))))
1294: #if !defined(PETSC_CLANG_STATIC_ANALYZER)
1295: #define MatCheckSameLocalSize(A, ar1, B, ar2) \
1296: do { \
1297: PetscCheckSameComm(A, ar1, B, ar2); \
1298: 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, \
1299: (A)->rmap->n, (A)->cmap->n, ar2, (B)->rmap->n, (B)->cmap->n); \
1300: } while (0)
1301: #define MatCheckSameSize(A, ar1, B, ar2) \
1302: do { \
1303: 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, \
1304: (A)->rmap->N, (A)->cmap->N, ar2, (B)->rmap->N, (B)->cmap->N); \
1305: MatCheckSameLocalSize(A, ar1, B, ar2); \
1306: } while (0)
1307: #else
1308: template <typename Tm>
1309: extern void MatCheckSameLocalSize(Tm, int, Tm, int);
1310: template <typename Tm>
1311: extern void MatCheckSameSize(Tm, int, Tm, int);
1312: #endif
1314: #define VecCheckMatCompatible(M, x, ar1, b, ar2) \
1315: do { \
1316: 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, \
1317: (M)->cmap->N); \
1318: 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, \
1319: (M)->rmap->N); \
1320: } while (0)
1322: /*
1323: Create and initialize a condensed linked list -
1324: same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1325: Barry suggested this approach (Dec. 6, 2011):
1326: I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1327: (it may be faster than the O(N) even sequentially due to less crazy memory access).
1329: 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
1330: 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
1331: 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
1332: 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.
1333: 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
1334: to each other so memory access is much better than using the big array.
1336: Example:
1337: nlnk_max=5, lnk_max=36:
1338: Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1339: here, head_node has index 2 with value lnk[2]=lnk_max=36,
1340: 0-th entry is used to store the number of entries in the list,
1341: The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.
1343: Now adding a sorted set {2,4}, the list becomes
1344: [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1345: represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.
1347: Then adding a sorted set {0,3,35}, the list
1348: [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1349: represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.
1351: Input Parameters:
1352: nlnk_max - max length of the list
1353: lnk_max - max value of the entries
1354: Output Parameters:
1355: lnk - list created and initialized
1356: bt - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1357: */
1358: static inline PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max, PetscInt lnk_max, PetscInt **lnk, PetscBT *bt)
1359: {
1360: PetscInt *llnk, lsize = 0;
1362: PetscFunctionBegin;
1363: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1364: PetscCall(PetscMalloc1(lsize, lnk));
1365: PetscCall(PetscBTCreate(lnk_max, bt));
1366: llnk = *lnk;
1367: llnk[0] = 0; /* number of entries on the list */
1368: llnk[2] = lnk_max; /* value in the head node */
1369: llnk[3] = 2; /* next for the head node */
1370: PetscFunctionReturn(PETSC_SUCCESS);
1371: }
1373: /*
1374: Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1375: Input Parameters:
1376: nidx - number of input indices
1377: indices - sorted integer array
1378: lnk - condensed linked list(an integer array) that is created
1379: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1380: output Parameters:
1381: lnk - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1382: bt - updated PetscBT (bitarray)
1383: */
1384: static inline PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx, const PetscInt indices[], PetscInt lnk[], PetscBT bt)
1385: {
1386: PetscInt location = 2; /* head */
1387: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1389: PetscFunctionBegin;
1390: for (PetscInt k = 0; k < nidx; k++) {
1391: const PetscInt entry = indices[k];
1392: if (!PetscBTLookupSet(bt, entry)) { /* new entry */
1393: PetscInt next, lnkdata;
1395: /* search for insertion location */
1396: do {
1397: next = location + 1; /* link from previous node to next node */
1398: location = lnk[next]; /* idx of next node */
1399: lnkdata = lnk[location]; /* value of next node */
1400: } while (entry > lnkdata);
1401: /* insertion location is found, add entry into lnk */
1402: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1403: lnk[next] = newnode; /* connect previous node to the new node */
1404: lnk[newnode] = entry; /* set value of the new node */
1405: lnk[newnode + 1] = location; /* connect new node to next node */
1406: location = newnode; /* next search starts from the new node */
1407: nlnk++;
1408: }
1409: }
1410: lnk[0] = nlnk; /* number of entries in the list */
1411: PetscFunctionReturn(PETSC_SUCCESS);
1412: }
1414: static inline PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max, PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt lnk[], PetscBT bt)
1415: {
1416: const PetscInt nlnk = lnk[0]; /* num of entries on the list */
1417: PetscInt next = lnk[3]; /* head node */
1419: PetscFunctionBegin;
1420: for (PetscInt k = 0; k < nlnk; k++) {
1421: indices[k] = lnk[next];
1422: next = lnk[next + 1];
1423: PetscCall(PetscBTClear(bt, indices[k]));
1424: }
1425: lnk[0] = 0; /* num of entries on the list */
1426: lnk[2] = lnk_max; /* initialize head node */
1427: lnk[3] = 2; /* head node */
1428: PetscFunctionReturn(PETSC_SUCCESS);
1429: }
1431: static inline PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1432: {
1433: PetscFunctionBegin;
1434: PetscCall(PetscPrintf(PETSC_COMM_SELF, "LLCondensed of size %" PetscInt_FMT ", (val, next)\n", lnk[0]));
1435: 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]));
1436: PetscFunctionReturn(PETSC_SUCCESS);
1437: }
1439: /*
1440: Free memories used by the list
1441: */
1442: static inline PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk, PetscBT bt)
1443: {
1444: PetscFunctionBegin;
1445: PetscCall(PetscFree(lnk));
1446: PetscCall(PetscBTDestroy(&bt));
1447: PetscFunctionReturn(PETSC_SUCCESS);
1448: }
1450: /*
1451: Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1452: Input Parameters:
1453: nlnk_max - max length of the list
1454: Output Parameters:
1455: lnk - list created and initialized
1456: */
1457: static inline PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1458: {
1459: PetscInt *llnk, lsize = 0;
1461: PetscFunctionBegin;
1462: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1463: PetscCall(PetscMalloc1(lsize, lnk));
1464: llnk = *lnk;
1465: llnk[0] = 0; /* number of entries on the list */
1466: llnk[2] = PETSC_INT_MAX; /* value in the head node */
1467: llnk[3] = 2; /* next for the head node */
1468: PetscFunctionReturn(PETSC_SUCCESS);
1469: }
1471: static inline PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max, PetscInt **lnk)
1472: {
1473: PetscInt lsize = 0;
1475: PetscFunctionBegin;
1476: PetscCall(PetscIntMultError(2, nlnk_max + 2, &lsize));
1477: PetscCall(PetscRealloc(lsize * sizeof(PetscInt), lnk));
1478: PetscFunctionReturn(PETSC_SUCCESS);
1479: }
1481: static inline PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1482: {
1483: PetscInt location = 2; /* head */
1484: PetscInt nlnk = lnk[0]; /* num of entries on the input lnk */
1486: for (PetscInt k = 0; k < nidx; k++) {
1487: const PetscInt entry = indices[k];
1488: PetscInt next, lnkdata;
1490: /* search for insertion location */
1491: do {
1492: next = location + 1; /* link from previous node to next node */
1493: location = lnk[next]; /* idx of next node */
1494: lnkdata = lnk[location]; /* value of next node */
1495: } while (entry > lnkdata);
1496: if (entry < lnkdata) {
1497: /* insertion location is found, add entry into lnk */
1498: const PetscInt newnode = 2 * (nlnk + 2); /* index for this new node */
1499: lnk[next] = newnode; /* connect previous node to the new node */
1500: lnk[newnode] = entry; /* set value of the new node */
1501: lnk[newnode + 1] = location; /* connect new node to next node */
1502: location = newnode; /* next search starts from the new node */
1503: nlnk++;
1504: }
1505: }
1506: lnk[0] = nlnk; /* number of entries in the list */
1507: return PETSC_SUCCESS;
1508: }
1510: static inline PetscErrorCode PetscLLCondensedClean_Scalable(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1511: {
1512: const PetscInt nlnk = lnk[0];
1513: PetscInt next = lnk[3]; /* head node */
1515: for (PetscInt k = 0; k < nlnk; k++) {
1516: indices[k] = lnk[next];
1517: next = lnk[next + 1];
1518: }
1519: lnk[0] = 0; /* num of entries on the list */
1520: lnk[3] = 2; /* head node */
1521: return PETSC_SUCCESS;
1522: }
1524: static inline PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1525: {
1526: return PetscFree(lnk);
1527: }
1529: /*
1530: lnk[0] number of links
1531: lnk[1] number of entries
1532: lnk[3n] value
1533: lnk[3n+1] len
1534: lnk[3n+2] link to next value
1536: The next three are always the first link
1538: lnk[3] PETSC_INT_MIN+1
1539: lnk[4] 1
1540: lnk[5] link to first real entry
1542: The next three are always the last link
1544: lnk[6] PETSC_INT_MAX - 1
1545: lnk[7] 1
1546: lnk[8] next valid link (this is the same as lnk[0] but without the decreases)
1547: */
1549: static inline PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max, PetscInt **lnk)
1550: {
1551: PetscInt *llnk;
1552: PetscInt lsize = 0;
1554: PetscFunctionBegin;
1555: PetscCall(PetscIntMultError(3, nlnk_max + 3, &lsize));
1556: PetscCall(PetscMalloc1(lsize, lnk));
1557: llnk = *lnk;
1558: llnk[0] = 0; /* nlnk: number of entries on the list */
1559: llnk[1] = 0; /* number of integer entries represented in list */
1560: llnk[3] = PETSC_INT_MIN + 1; /* value in the first node */
1561: llnk[4] = 1; /* count for the first node */
1562: llnk[5] = 6; /* next for the first node */
1563: llnk[6] = PETSC_INT_MAX - 1; /* value in the last node */
1564: llnk[7] = 1; /* count for the last node */
1565: llnk[8] = 0; /* next valid node to be used */
1566: PetscFunctionReturn(PETSC_SUCCESS);
1567: }
1569: static inline PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx, const PetscInt indices[], PetscInt lnk[])
1570: {
1571: for (PetscInt k = 0, prev = 3 /* first value */; k < nidx; k++) {
1572: const PetscInt entry = indices[k];
1573: PetscInt next = lnk[prev + 2];
1575: /* search for insertion location */
1576: while (entry >= lnk[next]) {
1577: prev = next;
1578: next = lnk[next + 2];
1579: }
1580: /* entry is in range of previous list */
1581: if (entry < lnk[prev] + lnk[prev + 1]) continue;
1582: lnk[1]++;
1583: /* entry is right after previous list */
1584: if (entry == lnk[prev] + lnk[prev + 1]) {
1585: lnk[prev + 1]++;
1586: if (lnk[next] == entry + 1) { /* combine two contiguous strings */
1587: lnk[prev + 1] += lnk[next + 1];
1588: lnk[prev + 2] = lnk[next + 2];
1589: next = lnk[next + 2];
1590: lnk[0]--;
1591: }
1592: continue;
1593: }
1594: /* entry is right before next list */
1595: if (entry == lnk[next] - 1) {
1596: lnk[next]--;
1597: lnk[next + 1]++;
1598: prev = next;
1599: next = lnk[prev + 2];
1600: continue;
1601: }
1602: /* add entry into lnk */
1603: lnk[prev + 2] = 3 * ((lnk[8]++) + 3); /* connect previous node to the new node */
1604: prev = lnk[prev + 2];
1605: lnk[prev] = entry; /* set value of the new node */
1606: lnk[prev + 1] = 1; /* number of values in contiguous string is one to start */
1607: lnk[prev + 2] = next; /* connect new node to next node */
1608: lnk[0]++;
1609: }
1610: return PETSC_SUCCESS;
1611: }
1613: static inline PetscErrorCode PetscLLCondensedClean_fast(PETSC_UNUSED PetscInt nidx, PetscInt *indices, PetscInt *lnk)
1614: {
1615: const PetscInt nlnk = lnk[0];
1616: PetscInt next = lnk[5]; /* first node */
1618: for (PetscInt k = 0, cnt = 0; k < nlnk; k++) {
1619: for (PetscInt j = 0; j < lnk[next + 1]; j++) indices[cnt++] = lnk[next] + j;
1620: next = lnk[next + 2];
1621: }
1622: lnk[0] = 0; /* nlnk: number of links */
1623: lnk[1] = 0; /* number of integer entries represented in list */
1624: lnk[3] = PETSC_INT_MIN + 1; /* value in the first node */
1625: lnk[4] = 1; /* count for the first node */
1626: lnk[5] = 6; /* next for the first node */
1627: lnk[6] = PETSC_INT_MAX - 1; /* value in the last node */
1628: lnk[7] = 1; /* count for the last node */
1629: lnk[8] = 0; /* next valid location to make link */
1630: return PETSC_SUCCESS;
1631: }
1633: static inline PetscErrorCode PetscLLCondensedView_fast(const PetscInt *lnk)
1634: {
1635: const PetscInt nlnk = lnk[0];
1636: PetscInt next = lnk[5]; /* first node */
1638: for (PetscInt k = 0; k < nlnk; k++) {
1639: #if 0 /* Debugging code */
1640: printf("%d value %d len %d next %d\n", next, lnk[next], lnk[next + 1], lnk[next + 2]);
1641: #endif
1642: next = lnk[next + 2];
1643: }
1644: return PETSC_SUCCESS;
1645: }
1647: static inline PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1648: {
1649: return PetscFree(lnk);
1650: }
1652: PETSC_EXTERN PetscErrorCode PetscCDCreate(PetscInt, PetscCoarsenData **);
1653: PETSC_EXTERN PetscErrorCode PetscCDDestroy(PetscCoarsenData *);
1654: PETSC_EXTERN PetscErrorCode PetscCDIntNdSetID(PetscCDIntNd *, PetscInt);
1655: PETSC_EXTERN PetscErrorCode PetscCDIntNdGetID(const PetscCDIntNd *, PetscInt *);
1656: PETSC_EXTERN PetscErrorCode PetscCDAppendID(PetscCoarsenData *, PetscInt, PetscInt);
1657: PETSC_EXTERN PetscErrorCode PetscCDMoveAppend(PetscCoarsenData *, PetscInt, PetscInt);
1658: PETSC_EXTERN PetscErrorCode PetscCDAppendNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1659: PETSC_EXTERN PetscErrorCode PetscCDRemoveNextNode(PetscCoarsenData *, PetscInt, PetscCDIntNd *);
1660: PETSC_EXTERN PetscErrorCode PetscCDCountAt(const PetscCoarsenData *, PetscInt, PetscInt *);
1661: PETSC_EXTERN PetscErrorCode PetscCDIsEmptyAt(const PetscCoarsenData *, PetscInt, PetscBool *);
1662: PETSC_EXTERN PetscErrorCode PetscCDSetChunkSize(PetscCoarsenData *, PetscInt);
1663: PETSC_EXTERN PetscErrorCode PetscCDPrint(const PetscCoarsenData *, PetscInt, MPI_Comm);
1664: PETSC_EXTERN PetscErrorCode PetscCDGetNonemptyIS(PetscCoarsenData *, IS *);
1665: PETSC_EXTERN PetscErrorCode PetscCDGetMat(PetscCoarsenData *, Mat *);
1666: PETSC_EXTERN PetscErrorCode PetscCDSetMat(PetscCoarsenData *, Mat);
1667: PETSC_EXTERN PetscErrorCode PetscCDClearMat(PetscCoarsenData *);
1668: PETSC_EXTERN PetscErrorCode PetscCDRemoveAllAt(PetscCoarsenData *, PetscInt);
1669: PETSC_EXTERN PetscErrorCode PetscCDCount(const PetscCoarsenData *, PetscInt *_sz);
1671: PETSC_EXTERN PetscErrorCode PetscCDGetHeadPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1672: PETSC_EXTERN PetscErrorCode PetscCDGetNextPos(const PetscCoarsenData *, PetscInt, PetscCDIntNd **);
1673: PETSC_EXTERN PetscErrorCode PetscCDGetASMBlocks(const PetscCoarsenData *, const PetscInt, PetscInt *, IS **);
1675: PETSC_SINGLE_LIBRARY_VISIBILITY_INTERNAL PetscErrorCode MatFDColoringApply_AIJ(Mat, MatFDColoring, Vec, void *);
1677: PETSC_EXTERN PetscLogEvent MAT_Mult;
1678: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1679: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1680: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTranspose;
1681: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1682: PETSC_EXTERN PetscLogEvent MAT_MultHermitianTransposeAdd;
1683: PETSC_EXTERN PetscLogEvent MAT_Solve;
1684: PETSC_EXTERN PetscLogEvent MAT_Solves;
1685: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1686: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1687: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1688: PETSC_EXTERN PetscLogEvent MAT_SOR;
1689: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1690: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1691: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1692: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1693: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1694: PETSC_EXTERN PetscLogEvent MAT_QRFactor;
1695: PETSC_EXTERN PetscLogEvent MAT_QRFactorSymbolic;
1696: PETSC_EXTERN PetscLogEvent MAT_QRFactorNumeric;
1697: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1698: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1699: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1700: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1701: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1702: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1703: PETSC_EXTERN PetscLogEvent MAT_Copy;
1704: PETSC_EXTERN PetscLogEvent MAT_Convert;
1705: PETSC_EXTERN PetscLogEvent MAT_Scale;
1706: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1707: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1708: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1709: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1710: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1711: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1712: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1713: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1714: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1715: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1716: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1717: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1718: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1719: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1720: PETSC_EXTERN PetscLogEvent MAT_Load;
1721: PETSC_EXTERN PetscLogEvent MAT_View;
1722: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1723: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1724: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1725: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1726: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1727: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1728: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1729: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1730: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1731: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1732: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1733: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1734: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1735: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1736: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1737: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1738: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1739: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1740: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1741: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1742: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1743: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1744: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1745: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1746: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1747: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1748: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1749: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1750: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1751: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1752: PETSC_EXTERN PetscLogEvent MAT_GetSeqNonzeroStructure;
1753: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1754: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1755: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1756: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyFromGPU;
1757: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
1758: PETSC_EXTERN PetscLogEvent MAT_CUSPARSESolveAnalysis;
1759: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyToGPU;
1760: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSECopyFromGPU;
1761: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSEGenerateTranspose;
1762: PETSC_EXTERN PetscLogEvent MAT_HIPSPARSESolveAnalysis;
1763: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1764: PETSC_EXTERN PetscLogEvent MAT_CreateGraph;
1765: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1766: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1767: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1768: PETSC_EXTERN PetscLogEvent MAT_Merge;
1769: PETSC_EXTERN PetscLogEvent MAT_Residual;
1770: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1771: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1772: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1773: PETSC_EXTERN PetscLogEvent MAT_PreallCOO;
1774: PETSC_EXTERN PetscLogEvent MAT_SetVCOO;
1775: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1776: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1777: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1778: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1779: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1780: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;
1781: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Build;
1782: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Compress;
1783: PETSC_EXTERN PetscLogEvent MAT_H2Opus_Orthog;
1784: PETSC_EXTERN PetscLogEvent MAT_H2Opus_LR;
1785: PETSC_EXTERN PetscLogEvent MAT_CUDACopyToGPU;
1786: PETSC_EXTERN PetscLogEvent MAT_HIPCopyToGPU;
1788: #if defined(PETSC_CLANG_STATIC_ANALYZER)
1789: #define MatGetDiagonalMarkers(SeqXXX, bs)
1790: #else
1791: /*
1792: Adds diagonal pointers to sparse matrix nonzero structure and determines if all diagonal entries are present
1794: Rechecks the matrix data structure automatically if the nonzero structure of the matrix changed since the last call
1796: Potential optimization: since the a->j[j] are sorted this could use bisection to find the diagonal
1798: Developer Note:
1799: Uses the C preprocessor as a template mechanism to produce MatGetDiagonal_Seq[SB]AIJ() to avoid duplicate code
1800: */
1801: #define MatGetDiagonalMarkers(SeqXXX, bs) \
1802: PetscErrorCode MatGetDiagonalMarkers_##SeqXXX(Mat A, const PetscInt **diag, PetscBool *diagDense) \
1803: { \
1804: Mat_##SeqXXX *a = (Mat_##SeqXXX *)A->data; \
1805: \
1806: PetscFunctionBegin; \
1807: if (A->factortype != MAT_FACTOR_NONE) { \
1808: if (diagDense) *diagDense = PETSC_TRUE; \
1809: if (diag) *diag = a->diag; \
1810: PetscFunctionReturn(PETSC_SUCCESS); \
1811: } \
1812: PetscCheck(diag || diagDense, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "At least one of diag or diagDense must be requested"); \
1813: if (a->diagNonzeroState != A->nonzerostate || (diag && !a->diag)) { \
1814: const PetscInt m = A->rmap->n / bs; \
1815: \
1816: if (!diag && !a->diag) { \
1817: a->diagDense = PETSC_TRUE; \
1818: for (PetscInt i = 0; i < m; i++) { \
1819: PetscBool found = PETSC_FALSE; \
1820: \
1821: for (PetscInt j = a->i[i]; j < a->i[i + 1]; j++) { \
1822: if (a->j[j] == i) { \
1823: found = PETSC_TRUE; \
1824: break; \
1825: } \
1826: } \
1827: if (!found) { \
1828: a->diagDense = PETSC_FALSE; \
1829: *diagDense = a->diagDense; \
1830: a->diagNonzeroState = A->nonzerostate; \
1831: PetscFunctionReturn(PETSC_SUCCESS); \
1832: } \
1833: } \
1834: } else { \
1835: if (!a->diag) PetscCall(PetscMalloc1(m, &a->diag)); \
1836: a->diagDense = PETSC_TRUE; \
1837: for (PetscInt i = 0; i < m; i++) { \
1838: PetscBool found = PETSC_FALSE; \
1839: \
1840: a->diag[i] = a->i[i + 1]; \
1841: for (PetscInt j = a->i[i]; j < a->i[i + 1]; j++) { \
1842: if (a->j[j] == i) { \
1843: a->diag[i] = j; \
1844: found = PETSC_TRUE; \
1845: break; \
1846: } \
1847: } \
1848: if (!found) a->diagDense = PETSC_FALSE; \
1849: } \
1850: } \
1851: a->diagNonzeroState = A->nonzerostate; \
1852: } \
1853: if (diag) *diag = a->diag; \
1854: if (diagDense) *diagDense = a->diagDense; \
1855: PetscFunctionReturn(PETSC_SUCCESS); \
1856: }
1857: #endif