Actual source code: matimpl.h
petsc-3.14.0 2020-09-29
2: #ifndef __MATIMPL_H
5: #include <petscmat.h>
6: #include <petscmatcoarsen.h>
7: #include <petsc/private/petscimpl.h>
9: PETSC_EXTERN PetscBool MatRegisterAllCalled;
10: PETSC_EXTERN PetscBool MatSeqAIJRegisterAllCalled;
11: PETSC_EXTERN PetscBool MatOrderingRegisterAllCalled;
12: PETSC_EXTERN PetscBool MatColoringRegisterAllCalled;
13: PETSC_EXTERN PetscBool MatPartitioningRegisterAllCalled;
14: PETSC_EXTERN PetscBool MatCoarsenRegisterAllCalled;
15: PETSC_EXTERN PetscErrorCode MatRegisterAll(void);
16: PETSC_EXTERN PetscErrorCode MatOrderingRegisterAll(void);
17: PETSC_EXTERN PetscErrorCode MatColoringRegisterAll(void);
18: PETSC_EXTERN PetscErrorCode MatPartitioningRegisterAll(void);
19: PETSC_EXTERN PetscErrorCode MatCoarsenRegisterAll(void);
20: PETSC_EXTERN PetscErrorCode MatSeqAIJRegisterAll(void);
22: /*
23: This file defines the parts of the matrix data structure that are
24: shared by all matrix types.
25: */
27: /*
28: If you add entries here also add them to the MATOP enum
29: in include/petscmat.h and src/mat/f90-mod/petscmat.h
30: */
31: typedef struct _MatOps *MatOps;
32: struct _MatOps {
33: /* 0*/
34: PetscErrorCode (*setvalues)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
35: PetscErrorCode (*getrow)(Mat,PetscInt,PetscInt *,PetscInt*[],PetscScalar*[]);
36: PetscErrorCode (*restorerow)(Mat,PetscInt,PetscInt *,PetscInt *[],PetscScalar *[]);
37: PetscErrorCode (*mult)(Mat,Vec,Vec);
38: PetscErrorCode (*multadd)(Mat,Vec,Vec,Vec);
39: /* 5*/
40: PetscErrorCode (*multtranspose)(Mat,Vec,Vec);
41: PetscErrorCode (*multtransposeadd)(Mat,Vec,Vec,Vec);
42: PetscErrorCode (*solve)(Mat,Vec,Vec);
43: PetscErrorCode (*solveadd)(Mat,Vec,Vec,Vec);
44: PetscErrorCode (*solvetranspose)(Mat,Vec,Vec);
45: /*10*/
46: PetscErrorCode (*solvetransposeadd)(Mat,Vec,Vec,Vec);
47: PetscErrorCode (*lufactor)(Mat,IS,IS,const MatFactorInfo*);
48: PetscErrorCode (*choleskyfactor)(Mat,IS,const MatFactorInfo*);
49: PetscErrorCode (*sor)(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
50: PetscErrorCode (*transpose)(Mat,MatReuse,Mat*);
51: /*15*/
52: PetscErrorCode (*getinfo)(Mat,MatInfoType,MatInfo*);
53: PetscErrorCode (*equal)(Mat,Mat,PetscBool*);
54: PetscErrorCode (*getdiagonal)(Mat,Vec);
55: PetscErrorCode (*diagonalscale)(Mat,Vec,Vec);
56: PetscErrorCode (*norm)(Mat,NormType,PetscReal*);
57: /*20*/
58: PetscErrorCode (*assemblybegin)(Mat,MatAssemblyType);
59: PetscErrorCode (*assemblyend)(Mat,MatAssemblyType);
60: PetscErrorCode (*setoption)(Mat,MatOption,PetscBool);
61: PetscErrorCode (*zeroentries)(Mat);
62: /*24*/
63: PetscErrorCode (*zerorows)(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
64: PetscErrorCode (*lufactorsymbolic)(Mat,Mat,IS,IS,const MatFactorInfo*);
65: PetscErrorCode (*lufactornumeric)(Mat,Mat,const MatFactorInfo*);
66: PetscErrorCode (*choleskyfactorsymbolic)(Mat,Mat,IS,const MatFactorInfo*);
67: PetscErrorCode (*choleskyfactornumeric)(Mat,Mat,const MatFactorInfo*);
68: /*29*/
69: PetscErrorCode (*setup)(Mat);
70: PetscErrorCode (*ilufactorsymbolic)(Mat,Mat,IS,IS,const MatFactorInfo*);
71: PetscErrorCode (*iccfactorsymbolic)(Mat,Mat,IS,const MatFactorInfo*);
72: PetscErrorCode (*getdiagonalblock)(Mat,Mat*);
73: PetscErrorCode (*setinf)(Mat);
74: /*34*/
75: PetscErrorCode (*duplicate)(Mat,MatDuplicateOption,Mat*);
76: PetscErrorCode (*forwardsolve)(Mat,Vec,Vec);
77: PetscErrorCode (*backwardsolve)(Mat,Vec,Vec);
78: PetscErrorCode (*ilufactor)(Mat,IS,IS,const MatFactorInfo*);
79: PetscErrorCode (*iccfactor)(Mat,IS,const MatFactorInfo*);
80: /*39*/
81: PetscErrorCode (*axpy)(Mat,PetscScalar,Mat,MatStructure);
82: PetscErrorCode (*createsubmatrices)(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
83: PetscErrorCode (*increaseoverlap)(Mat,PetscInt,IS[],PetscInt);
84: PetscErrorCode (*getvalues)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
85: PetscErrorCode (*copy)(Mat,Mat,MatStructure);
86: /*44*/
87: PetscErrorCode (*getrowmax)(Mat,Vec,PetscInt[]);
88: PetscErrorCode (*scale)(Mat,PetscScalar);
89: PetscErrorCode (*shift)(Mat,PetscScalar);
90: PetscErrorCode (*diagonalset)(Mat,Vec,InsertMode);
91: PetscErrorCode (*zerorowscolumns)(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
92: /*49*/
93: PetscErrorCode (*setrandom)(Mat,PetscRandom);
94: PetscErrorCode (*getrowij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool *);
95: PetscErrorCode (*restorerowij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt *,const PetscInt *[],const PetscInt *[],PetscBool *);
96: PetscErrorCode (*getcolumnij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool *);
97: PetscErrorCode (*restorecolumnij)(Mat,PetscInt,PetscBool ,PetscBool ,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool *);
98: /*54*/
99: PetscErrorCode (*fdcoloringcreate)(Mat,ISColoring,MatFDColoring);
100: PetscErrorCode (*coloringpatch)(Mat,PetscInt,PetscInt,ISColoringValue[],ISColoring*);
101: PetscErrorCode (*setunfactored)(Mat);
102: PetscErrorCode (*permute)(Mat,IS,IS,Mat*);
103: PetscErrorCode (*setvaluesblocked)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
104: /*59*/
105: PetscErrorCode (*createsubmatrix)(Mat,IS,IS,MatReuse,Mat*);
106: PetscErrorCode (*destroy)(Mat);
107: PetscErrorCode (*view)(Mat,PetscViewer);
108: PetscErrorCode (*convertfrom)(Mat,MatType,MatReuse,Mat*);
109: PetscErrorCode (*placeholder_63)(void);
110: /*64*/
111: PetscErrorCode (*matmatmultsymbolic)(Mat,Mat,Mat,PetscReal,Mat);
112: PetscErrorCode (*matmatmultnumeric)(Mat,Mat,Mat,Mat);
113: PetscErrorCode (*setlocaltoglobalmapping)(Mat,ISLocalToGlobalMapping,ISLocalToGlobalMapping);
114: PetscErrorCode (*setvalueslocal)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
115: PetscErrorCode (*zerorowslocal)(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
116: /*69*/
117: PetscErrorCode (*getrowmaxabs)(Mat,Vec,PetscInt[]);
118: PetscErrorCode (*getrowminabs)(Mat,Vec,PetscInt[]);
119: PetscErrorCode (*convert)(Mat, MatType,MatReuse,Mat*);
120: PetscErrorCode (*hasoperation)(Mat,MatOperation,PetscBool*);
121: PetscErrorCode (*placeholder_73)(void);
122: /*74*/
123: PetscErrorCode (*setvaluesadifor)(Mat,PetscInt,void*);
124: PetscErrorCode (*fdcoloringapply)(Mat,MatFDColoring,Vec,void*);
125: PetscErrorCode (*setfromoptions)(PetscOptionItems*,Mat);
126: PetscErrorCode (*multconstrained)(Mat,Vec,Vec);
127: PetscErrorCode (*multtransposeconstrained)(Mat,Vec,Vec);
128: /*79*/
129: PetscErrorCode (*findzerodiagonals)(Mat,IS*);
130: PetscErrorCode (*mults)(Mat,Vecs,Vecs);
131: PetscErrorCode (*solves)(Mat,Vecs,Vecs);
132: PetscErrorCode (*getinertia)(Mat,PetscInt*,PetscInt*,PetscInt*);
133: PetscErrorCode (*load)(Mat,PetscViewer);
134: /*84*/
135: PetscErrorCode (*issymmetric)(Mat,PetscReal,PetscBool*);
136: PetscErrorCode (*ishermitian)(Mat,PetscReal,PetscBool*);
137: PetscErrorCode (*isstructurallysymmetric)(Mat,PetscBool *);
138: PetscErrorCode (*setvaluesblockedlocal)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
139: PetscErrorCode (*getvecs)(Mat,Vec*,Vec*);
140: /*89*/
141: PetscErrorCode (*placeholder_89)(void);
142: PetscErrorCode (*matmultsymbolic)(Mat,Mat,PetscReal,Mat);
143: PetscErrorCode (*matmultnumeric)(Mat,Mat,Mat);
144: PetscErrorCode (*placeholder_92)(void);
145: PetscErrorCode (*ptapsymbolic)(Mat,Mat,PetscReal,Mat); /* double dispatch wrapper routine */
146: /*94*/
147: PetscErrorCode (*ptapnumeric)(Mat,Mat,Mat); /* double dispatch wrapper routine */
148: PetscErrorCode (*placeholder_95)(void);
149: PetscErrorCode (*mattransposemultsymbolic)(Mat,Mat,PetscReal,Mat);
150: PetscErrorCode (*mattransposemultnumeric)(Mat,Mat,Mat);
151: PetscErrorCode (*bindtocpu)(Mat,PetscBool);
152: /*99*/
153: PetscErrorCode (*productsetfromoptions)(Mat);
154: PetscErrorCode (*productsymbolic)(Mat);
155: PetscErrorCode (*productnumeric)(Mat);
156: PetscErrorCode (*conjugate)(Mat); /* complex conjugate */
157: PetscErrorCode (*viewnative)(Mat,PetscViewer);
158: /*104*/
159: PetscErrorCode (*setvaluesrow)(Mat,PetscInt,const PetscScalar[]);
160: PetscErrorCode (*realpart)(Mat);
161: PetscErrorCode (*imaginarypart)(Mat);
162: PetscErrorCode (*getrowuppertriangular)(Mat);
163: PetscErrorCode (*restorerowuppertriangular)(Mat);
164: /*109*/
165: PetscErrorCode (*matsolve)(Mat,Mat,Mat);
166: PetscErrorCode (*matsolvetranspose)(Mat,Mat,Mat);
167: PetscErrorCode (*getrowmin)(Mat,Vec,PetscInt[]);
168: PetscErrorCode (*getcolumnvector)(Mat,Vec,PetscInt);
169: PetscErrorCode (*missingdiagonal)(Mat,PetscBool *,PetscInt*);
170: /*114*/
171: PetscErrorCode (*getseqnonzerostructure)(Mat,Mat *);
172: PetscErrorCode (*create)(Mat);
173: PetscErrorCode (*getghosts)(Mat,PetscInt*,const PetscInt *[]);
174: PetscErrorCode (*getlocalsubmatrix)(Mat,IS,IS,Mat*);
175: PetscErrorCode (*restorelocalsubmatrix)(Mat,IS,IS,Mat*);
176: /*119*/
177: PetscErrorCode (*multdiagonalblock)(Mat,Vec,Vec);
178: PetscErrorCode (*hermitiantranspose)(Mat,MatReuse,Mat*);
179: PetscErrorCode (*multhermitiantranspose)(Mat,Vec,Vec);
180: PetscErrorCode (*multhermitiantransposeadd)(Mat,Vec,Vec,Vec);
181: PetscErrorCode (*getmultiprocblock)(Mat,MPI_Comm,MatReuse,Mat*);
182: /*124*/
183: PetscErrorCode (*findnonzerorows)(Mat,IS*);
184: PetscErrorCode (*getcolumnnorms)(Mat,NormType,PetscReal*);
185: PetscErrorCode (*invertblockdiagonal)(Mat,const PetscScalar**);
186: PetscErrorCode (*invertvariableblockdiagonal)(Mat,PetscInt,const PetscInt*,PetscScalar*);
187: PetscErrorCode (*createsubmatricesmpi)(Mat,PetscInt,const IS[], const IS[], MatReuse, Mat**);
188: /*129*/
189: PetscErrorCode (*setvaluesbatch)(Mat,PetscInt,PetscInt,PetscInt*,const PetscScalar*);
190: PetscErrorCode (*placeholder_130)(void);
191: PetscErrorCode (*transposematmultsymbolic)(Mat,Mat,PetscReal,Mat);
192: PetscErrorCode (*transposematmultnumeric)(Mat,Mat,Mat);
193: PetscErrorCode (*transposecoloringcreate)(Mat,ISColoring,MatTransposeColoring);
194: /*134*/
195: PetscErrorCode (*transcoloringapplysptoden)(MatTransposeColoring,Mat,Mat);
196: PetscErrorCode (*transcoloringapplydentosp)(MatTransposeColoring,Mat,Mat);
197: PetscErrorCode (*placeholder_136)(void);
198: PetscErrorCode (*rartsymbolic)(Mat,Mat,PetscReal,Mat); /* double dispatch wrapper routine */
199: PetscErrorCode (*rartnumeric)(Mat,Mat,Mat); /* double dispatch wrapper routine */
200: /*139*/
201: PetscErrorCode (*setblocksizes)(Mat,PetscInt,PetscInt);
202: PetscErrorCode (*aypx)(Mat,PetscScalar,Mat,MatStructure);
203: PetscErrorCode (*residual)(Mat,Vec,Vec,Vec);
204: PetscErrorCode (*fdcoloringsetup)(Mat,ISColoring,MatFDColoring);
205: PetscErrorCode (*findoffblockdiagonalentries)(Mat,IS*);
206: PetscErrorCode (*creatempimatconcatenateseqmat)(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
207: /*145*/
208: PetscErrorCode (*destroysubmatrices)(PetscInt,Mat*[]);
209: PetscErrorCode (*mattransposesolve)(Mat,Mat,Mat);
210: PetscErrorCode (*getvalueslocal)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar[]);
211: };
212: /*
213: If you add MatOps entries above also add them to the MATOP enum
214: in include/petscmat.h and src/mat/f90-mod/petscmat.h
215: */
217: #include <petscsys.h>
218: PETSC_EXTERN PetscErrorCode MatRegisterOp(MPI_Comm, const char[], PetscVoidFunction, const char[], PetscInt, ...);
219: PETSC_EXTERN PetscErrorCode MatQueryOp(MPI_Comm, PetscVoidFunction*, const char[], PetscInt, ...);
221: typedef struct _p_MatRootName* MatRootName;
222: struct _p_MatRootName {
223: char *rname,*sname,*mname;
224: MatRootName next;
225: };
227: PETSC_EXTERN MatRootName MatRootNameList;
229: /*
230: Utility private matrix routines
231: */
232: PETSC_INTERN PetscErrorCode MatFindNonzeroRowsOrCols_Basic(Mat,PetscBool,PetscReal,IS*);
233: PETSC_INTERN PetscErrorCode MatConvert_Basic(Mat,MatType,MatReuse,Mat*);
234: PETSC_INTERN PetscErrorCode MatConvert_Shell(Mat,MatType,MatReuse,Mat*);
235: PETSC_INTERN PetscErrorCode MatConvertFrom_Shell(Mat,MatType,MatReuse,Mat*);
236: PETSC_INTERN PetscErrorCode MatCopy_Basic(Mat,Mat,MatStructure);
237: PETSC_INTERN PetscErrorCode MatDiagonalSet_Default(Mat,Vec,InsertMode);
238: #if defined(PETSC_HAVE_SCALAPACK)
239: PETSC_INTERN PetscErrorCode MatConvert_Dense_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
240: #endif
242: PETSC_INTERN PetscErrorCode MatProductSymbolic_AB(Mat);
243: PETSC_INTERN PetscErrorCode MatProductNumeric_AB(Mat);
244: PETSC_INTERN PetscErrorCode MatProductSymbolic_AtB(Mat);
245: PETSC_INTERN PetscErrorCode MatProductNumeric_AtB(Mat);
246: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABt(Mat);
247: PETSC_INTERN PetscErrorCode MatProductNumeric_ABt(Mat);
248: PETSC_INTERN PetscErrorCode MatProductNumeric_PtAP(Mat);
249: PETSC_INTERN PetscErrorCode MatProductNumeric_RARt(Mat);
250: PETSC_INTERN PetscErrorCode MatProductSymbolic_ABC(Mat);
251: PETSC_INTERN PetscErrorCode MatProductNumeric_ABC(Mat);
252: PETSC_INTERN PetscErrorCode MatProductCreate_Private(Mat,Mat,Mat,Mat);
254: #if defined(PETSC_USE_DEBUG)
255: # define MatCheckPreallocated(A,arg) do { \
256: if (PetscUnlikely(!(A)->preallocated)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatXXXSetPreallocation() or MatSetUp() on argument %D \"%s\" before %s()",(arg),#A,PETSC_FUNCTION_NAME); \
257: } while (0)
258: #else
259: # define MatCheckPreallocated(A,arg) do {} while (0)
260: #endif
262: #if defined(PETSC_USE_DEBUG)
263: # define MatCheckProduct(A,arg) do { \
264: if (PetscUnlikely(!(A)->product)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Argument %D \"%s\" is not a matrix obtained from MatProductCreate()",(arg),#A); \
265: } while (0)
266: #else
267: # define MatCheckProduct(A,arg) do {} while (0)
268: #endif
270: /*
271: The stash is used to temporarily store inserted matrix values that
272: belong to another processor. During the assembly phase the stashed
273: values are moved to the correct processor and
274: */
276: typedef struct _MatStashSpace *PetscMatStashSpace;
278: struct _MatStashSpace {
279: PetscMatStashSpace next;
280: PetscScalar *space_head,*val;
281: PetscInt *idx,*idy;
282: PetscInt total_space_size;
283: PetscInt local_used;
284: PetscInt local_remaining;
285: };
287: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceGet(PetscInt,PetscInt,PetscMatStashSpace *);
288: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceContiguous(PetscInt,PetscMatStashSpace *,PetscScalar *,PetscInt *,PetscInt *);
289: PETSC_EXTERN PetscErrorCode PetscMatStashSpaceDestroy(PetscMatStashSpace*);
291: typedef struct {
292: PetscInt count;
293: } MatStashHeader;
295: typedef struct {
296: void *buffer; /* Of type blocktype, dynamically constructed */
297: PetscInt count;
298: char pending;
299: } MatStashFrame;
301: typedef struct _MatStash MatStash;
302: struct _MatStash {
303: PetscInt nmax; /* maximum stash size */
304: PetscInt umax; /* user specified max-size */
305: PetscInt oldnmax; /* the nmax value used previously */
306: PetscInt n; /* stash size */
307: PetscInt bs; /* block size of the stash */
308: PetscInt reallocs; /* preserve the no of mallocs invoked */
309: PetscMatStashSpace space_head,space; /* linked list to hold stashed global row/column numbers and matrix values */
311: PetscErrorCode (*ScatterBegin)(Mat,MatStash*,PetscInt*);
312: PetscErrorCode (*ScatterGetMesg)(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
313: PetscErrorCode (*ScatterEnd)(MatStash*);
314: PetscErrorCode (*ScatterDestroy)(MatStash*);
316: /* The following variables are used for communication */
317: MPI_Comm comm;
318: PetscMPIInt size,rank;
319: PetscMPIInt tag1,tag2;
320: MPI_Request *send_waits; /* array of send requests */
321: MPI_Request *recv_waits; /* array of receive requests */
322: MPI_Status *send_status; /* array of send status */
323: PetscInt nsends,nrecvs; /* numbers of sends and receives */
324: PetscScalar *svalues; /* sending data */
325: PetscInt *sindices;
326: PetscScalar **rvalues; /* receiving data (values) */
327: PetscInt **rindices; /* receiving data (indices) */
328: PetscInt nprocessed; /* number of messages already processed */
329: PetscMPIInt *flg_v; /* indicates what messages have arrived so far and from whom */
330: PetscBool reproduce;
331: PetscInt reproduce_count;
333: /* The following variables are used for BTS communication */
334: PetscBool first_assembly_done; /* Is the first time matrix assembly done? */
335: PetscBool use_status; /* Use MPI_Status to determine number of items in each message */
336: PetscMPIInt nsendranks;
337: PetscMPIInt nrecvranks;
338: PetscMPIInt *sendranks;
339: PetscMPIInt *recvranks;
340: MatStashHeader *sendhdr,*recvhdr;
341: MatStashFrame *sendframes; /* pointers to the main messages */
342: MatStashFrame *recvframes;
343: MatStashFrame *recvframe_active;
344: PetscInt recvframe_i; /* index of block within active frame */
345: PetscMPIInt recvframe_count; /* Count actually sent for current frame */
346: PetscInt recvcount; /* Number of receives processed so far */
347: PetscMPIInt *some_indices; /* From last call to MPI_Waitsome */
348: MPI_Status *some_statuses; /* Statuses from last call to MPI_Waitsome */
349: PetscMPIInt some_count; /* Number of requests completed in last call to MPI_Waitsome */
350: PetscMPIInt some_i; /* Index of request currently being processed */
351: MPI_Request *sendreqs;
352: MPI_Request *recvreqs;
353: PetscSegBuffer segsendblocks;
354: PetscSegBuffer segrecvframe;
355: PetscSegBuffer segrecvblocks;
356: MPI_Datatype blocktype;
357: size_t blocktype_size;
358: InsertMode *insertmode; /* Pointer to check mat->insertmode and set upon message arrival in case no local values have been set. */
359: };
361: #if !defined(PETSC_HAVE_MPIUNI)
362: PETSC_INTERN PetscErrorCode MatStashScatterDestroy_BTS(MatStash*);
363: #endif
364: PETSC_INTERN PetscErrorCode MatStashCreate_Private(MPI_Comm,PetscInt,MatStash*);
365: PETSC_INTERN PetscErrorCode MatStashDestroy_Private(MatStash*);
366: PETSC_INTERN PetscErrorCode MatStashScatterEnd_Private(MatStash*);
367: PETSC_INTERN PetscErrorCode MatStashSetInitialSize_Private(MatStash*,PetscInt);
368: PETSC_INTERN PetscErrorCode MatStashGetInfo_Private(MatStash*,PetscInt*,PetscInt*);
369: PETSC_INTERN PetscErrorCode MatStashValuesRow_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscBool);
370: PETSC_INTERN PetscErrorCode MatStashValuesCol_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscBool);
371: PETSC_INTERN PetscErrorCode MatStashValuesRowBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
372: PETSC_INTERN PetscErrorCode MatStashValuesColBlocked_Private(MatStash*,PetscInt,PetscInt,const PetscInt[],const PetscScalar[],PetscInt,PetscInt,PetscInt);
373: PETSC_INTERN PetscErrorCode MatStashScatterBegin_Private(Mat,MatStash*,PetscInt*);
374: PETSC_INTERN PetscErrorCode MatStashScatterGetMesg_Private(MatStash*,PetscMPIInt*,PetscInt**,PetscInt**,PetscScalar**,PetscInt*);
375: PETSC_INTERN PetscErrorCode MatGetInfo_External(Mat,MatInfoType,MatInfo*);
377: typedef struct {
378: PetscInt dim;
379: PetscInt dims[4];
380: PetscInt starts[4];
381: PetscBool noc; /* this is a single component problem, hence user will not set MatStencil.c */
382: } MatStencilInfo;
384: /* Info about using compressed row format */
385: typedef struct {
386: PetscBool use; /* indicates compressed rows have been checked and will be used */
387: PetscInt nrows; /* number of non-zero rows */
388: PetscInt *i; /* compressed row pointer */
389: PetscInt *rindex; /* compressed row index */
390: } Mat_CompressedRow;
391: PETSC_EXTERN PetscErrorCode MatCheckCompressedRow(Mat,PetscInt,Mat_CompressedRow*,PetscInt*,PetscInt,PetscReal);
393: typedef struct { /* used by MatCreateRedundantMatrix() for reusing matredundant */
394: PetscInt nzlocal,nsends,nrecvs;
395: PetscMPIInt *send_rank,*recv_rank;
396: PetscInt *sbuf_nz,*rbuf_nz,*sbuf_j,**rbuf_j;
397: PetscScalar *sbuf_a,**rbuf_a;
398: MPI_Comm subcomm; /* when user does not provide a subcomm */
399: IS isrow,iscol;
400: Mat *matseq;
401: } Mat_Redundant;
403: typedef struct { /* used by MatProduct() */
404: MatProductType type;
405: char *alg;
406: Mat A,B,C,Dwork;
407: PetscReal fill;
408: PetscBool api_user; /* used by MatProductSetFromOptions_xxx() to distinguish command line options */
410: /* Some products may display the information on the algorithm used */
411: PetscErrorCode (*view)(Mat,PetscViewer);
413: /* many products have intermediate data structures, each specific to Mat types and product type */
414: PetscBool clear; /* whether or not to clear the data structures after MatProductNumeric has been called */
415: void *data; /* where to stash those structures */
416: PetscErrorCode (*destroy)(void*); /* destroy routine */
417: } Mat_Product;
419: #define CSRDataStructure(datatype) \
420: int *i; \
421: int *j; \
422: datatype *a;\
423: PetscInt n;\
424: PetscInt ignorezeroentries;
426: typedef struct {
427: CSRDataStructure(PetscScalar)
428: } PetscCSRDataStructure;
430: struct _p_SplitCSRMat {
431: PetscInt cstart,cend,rstart,rend;
432: PetscCSRDataStructure diag,offdiag;
433: PetscInt *colmap;
434: PetscBool seq;
435: PetscMPIInt rank;
436: PetscInt nonzerostate;
437: };
439: struct _p_Mat {
440: PETSCHEADER(struct _MatOps);
441: PetscLayout rmap,cmap;
442: void *data; /* implementation-specific data */
443: MatFactorType factortype; /* MAT_FACTOR_LU, ILU, CHOLESKY or ICC */
444: PetscBool useordering; /* factorization using ordering provide to routine (most PETSc implementations) */
445: PetscBool assembled; /* is the matrix assembled? */
446: PetscBool was_assembled; /* new values inserted into assembled mat */
447: PetscInt num_ass; /* number of times matrix has been assembled */
448: PetscObjectState nonzerostate; /* each time new nonzeros locations are introduced into the matrix this is updated */
449: PetscObjectState ass_nonzerostate; /* nonzero state at last assembly */
450: MatInfo info; /* matrix information */
451: InsertMode insertmode; /* have values been inserted in matrix or added? */
452: MatStash stash,bstash; /* used for assembling off-proc mat emements */
453: MatNullSpace nullsp; /* null space (operator is singular) */
454: MatNullSpace transnullsp; /* null space of transpose of operator */
455: MatNullSpace nearnullsp; /* near null space to be used by multigrid methods */
456: PetscInt congruentlayouts; /* are the rows and columns layouts congruent? */
457: PetscBool preallocated;
458: MatStencilInfo stencil; /* information for structured grid */
459: PetscBool symmetric,hermitian,structurally_symmetric,spd;
460: PetscBool symmetric_set,hermitian_set,structurally_symmetric_set,spd_set; /* if true, then corresponding flag is correct*/
461: PetscBool symmetric_eternal;
462: PetscBool nooffprocentries,nooffproczerorows;
463: PetscBool assembly_subset; /* set by MAT_SUBSET_OFF_PROC_ENTRIES */
464: PetscBool submat_singleis; /* for efficient PCSetUp_ASM() */
465: PetscBool structure_only;
466: PetscBool sortedfull; /* full, sorted rows are inserted */
467: #if defined(PETSC_HAVE_DEVICE)
468: PetscOffloadMask offloadmask; /* a mask which indicates where the valid matrix data is (GPU, CPU or both) */
469: PetscBool boundtocpu;
470: #endif
471: void *spptr; /* pointer for special library like SuperLU */
472: char *solvertype;
473: PetscBool checksymmetryonassembly,checknullspaceonassembly;
474: PetscReal checksymmetrytol;
475: Mat schur; /* Schur complement matrix */
476: MatFactorSchurStatus schur_status; /* status of the Schur complement matrix */
477: Mat_Redundant *redundant; /* used by MatCreateRedundantMatrix() */
478: PetscBool erroriffailure; /* Generate an error if detected (for example a zero pivot) instead of returning */
479: MatFactorError factorerrortype; /* type of error in factorization */
480: PetscReal factorerror_zeropivot_value; /* If numerical zero pivot was detected this is the computed value */
481: PetscInt factorerror_zeropivot_row; /* Row where zero pivot was detected */
482: PetscInt nblocks,*bsizes; /* support for MatSetVariableBlockSizes() */
483: char *defaultvectype;
484: Mat_Product *product;
485: };
487: PETSC_INTERN PetscErrorCode MatAXPY_Basic(Mat,PetscScalar,Mat,MatStructure);
488: PETSC_INTERN PetscErrorCode MatAXPY_BasicWithPreallocation(Mat,Mat,PetscScalar,Mat,MatStructure);
489: PETSC_INTERN PetscErrorCode MatAXPY_Basic_Preallocate(Mat,Mat,Mat*);
491: /*
492: Utility for MatFactor (Schur complement)
493: */
494: PETSC_INTERN PetscErrorCode MatFactorFactorizeSchurComplement_Private(Mat);
495: PETSC_INTERN PetscErrorCode MatFactorInvertSchurComplement_Private(Mat);
496: PETSC_INTERN PetscErrorCode MatFactorUpdateSchurStatus_Private(Mat);
497: PETSC_INTERN PetscErrorCode MatFactorSetUpInPlaceSchur_Private(Mat);
499: /*
500: Utility for MatZeroRows
501: */
502: PETSC_INTERN PetscErrorCode MatZeroRowsMapLocal_Private(Mat,PetscInt,const PetscInt*,PetscInt*,PetscInt**);
504: /*
505: Utility for MatView/MatLoad
506: */
507: PETSC_INTERN PetscErrorCode MatView_Binary_BlockSizes(Mat,PetscViewer);
508: PETSC_INTERN PetscErrorCode MatLoad_Binary_BlockSizes(Mat,PetscViewer);
511: /*
512: Object for partitioning graphs
513: */
515: typedef struct _MatPartitioningOps *MatPartitioningOps;
516: struct _MatPartitioningOps {
517: PetscErrorCode (*apply)(MatPartitioning,IS*);
518: PetscErrorCode (*applynd)(MatPartitioning,IS*);
519: PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatPartitioning);
520: PetscErrorCode (*destroy)(MatPartitioning);
521: PetscErrorCode (*view)(MatPartitioning,PetscViewer);
522: PetscErrorCode (*improve)(MatPartitioning,IS*);
523: };
525: struct _p_MatPartitioning {
526: PETSCHEADER(struct _MatPartitioningOps);
527: Mat adj;
528: PetscInt *vertex_weights;
529: PetscReal *part_weights;
530: PetscInt n; /* number of partitions */
531: void *data;
532: PetscInt setupcalled;
533: PetscBool use_edge_weights; /* A flag indicates whether or not to use edge weights */
534: };
536: /* needed for parallel nested dissection by ParMetis and PTSCOTCH */
537: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt,PetscInt[],PetscInt[],PetscInt[]);
539: /*
540: Object for coarsen graphs
541: */
542: typedef struct _MatCoarsenOps *MatCoarsenOps;
543: struct _MatCoarsenOps {
544: PetscErrorCode (*apply)(MatCoarsen);
545: PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatCoarsen);
546: PetscErrorCode (*destroy)(MatCoarsen);
547: PetscErrorCode (*view)(MatCoarsen,PetscViewer);
548: };
550: struct _p_MatCoarsen {
551: PETSCHEADER(struct _MatCoarsenOps);
552: Mat graph;
553: PetscInt setupcalled;
554: void *subctx;
555: /* */
556: PetscBool strict_aggs;
557: IS perm;
558: PetscCoarsenData *agg_lists;
559: };
561: /*
562: MatFDColoring is used to compute Jacobian matrices efficiently
563: via coloring. The data structure is explained below in an example.
565: Color = 0 1 0 2 | 2 3 0
566: ---------------------------------------------------
567: 00 01 | 05
568: 10 11 | 14 15 Processor 0
569: 22 23 | 25
570: 32 33 |
571: ===================================================
572: | 44 45 46
573: 50 | 55 Processor 1
574: | 64 66
575: ---------------------------------------------------
577: ncolors = 4;
579: ncolumns = {2,1,1,0}
580: columns = {{0,2},{1},{3},{}}
581: nrows = {4,2,3,3}
582: rows = {{0,1,2,3},{0,1},{1,2,3},{0,1,2}}
583: vwscale = {dx(0),dx(1),dx(2),dx(3)} MPI Vec
584: vscale = {dx(0),dx(1),dx(2),dx(3),dx(4),dx(5)} Seq Vec
586: ncolumns = {1,0,1,1}
587: columns = {{6},{},{4},{5}}
588: nrows = {3,0,2,2}
589: rows = {{0,1,2},{},{1,2},{1,2}}
590: vwscale = {dx(4),dx(5),dx(6)} MPI Vec
591: vscale = {dx(0),dx(4),dx(5),dx(6)} Seq Vec
593: See the routine MatFDColoringApply() for how this data is used
594: to compute the Jacobian.
596: */
597: typedef struct {
598: PetscInt row;
599: PetscInt col;
600: PetscScalar *valaddr; /* address of value */
601: } MatEntry;
603: typedef struct {
604: PetscInt row;
605: PetscScalar *valaddr; /* address of value */
606: } MatEntry2;
608: struct _p_MatFDColoring{
609: PETSCHEADER(int);
610: PetscInt M,N,m; /* total rows, columns; local rows */
611: PetscInt rstart; /* first row owned by local processor */
612: PetscInt ncolors; /* number of colors */
613: PetscInt *ncolumns; /* number of local columns for a color */
614: PetscInt **columns; /* lists the local columns of each color (using global column numbering) */
615: IS *isa; /* these are the IS that contain the column values given in columns */
616: PetscInt *nrows; /* number of local rows for each color */
617: MatEntry *matentry; /* holds (row, column, address of value) for Jacobian matrix entry */
618: MatEntry2 *matentry2; /* holds (row, address of value) for Jacobian matrix entry */
619: PetscScalar *dy; /* store a block of F(x+dx)-F(x) when J is in BAIJ format */
620: PetscReal error_rel; /* square root of relative error in computing function */
621: PetscReal umin; /* minimum allowable u'dx value */
622: Vec w1,w2,w3; /* work vectors used in computing Jacobian */
623: PetscBool fset; /* indicates that the initial function value F(X) is set */
624: PetscErrorCode (*f)(void); /* function that defines Jacobian */
625: void *fctx; /* optional user-defined context for use by the function f */
626: Vec vscale; /* holds FD scaling, i.e. 1/dx for each perturbed column */
627: PetscInt currentcolor; /* color for which function evaluation is being done now */
628: const char *htype; /* "wp" or "ds" */
629: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
630: PetscInt brows,bcols; /* number of block rows or columns for speedup inserting the dense matrix into sparse Jacobian */
631: PetscBool setupcalled; /* true if setup has been called */
632: PetscBool viewed; /* true if the -mat_fd_coloring_view has been triggered already */
633: void (*ftn_func_pointer)(void),*ftn_func_cntx; /* serve the same purpose as *fortran_func_pointers in PETSc objects */
634: PetscObjectId matid; /* matrix this object was created with, must always be the same */
635: };
637: typedef struct _MatColoringOps *MatColoringOps;
638: struct _MatColoringOps {
639: PetscErrorCode (*destroy)(MatColoring);
640: PetscErrorCode (*setfromoptions)(PetscOptionItems*,MatColoring);
641: PetscErrorCode (*view)(MatColoring,PetscViewer);
642: PetscErrorCode (*apply)(MatColoring,ISColoring*);
643: PetscErrorCode (*weights)(MatColoring,PetscReal**,PetscInt**);
644: };
646: struct _p_MatColoring {
647: PETSCHEADER(struct _MatColoringOps);
648: Mat mat;
649: PetscInt dist; /* distance of the coloring */
650: PetscInt maxcolors; /* the maximum number of colors returned, maxcolors=1 for MIS */
651: void *data; /* inner context */
652: PetscBool valid; /* check to see if what is produced is a valid coloring */
653: MatColoringWeightType weight_type; /* type of weight computation to be performed */
654: PetscReal *user_weights; /* custom weights and permutation */
655: PetscInt *user_lperm;
656: PetscBool valid_iscoloring; /* check to see if matcoloring is produced a valid iscoloring */
657: };
659: struct _p_MatTransposeColoring{
660: PETSCHEADER(int);
661: PetscInt M,N,m; /* total rows, columns; local rows */
662: PetscInt rstart; /* first row owned by local processor */
663: PetscInt ncolors; /* number of colors */
664: PetscInt *ncolumns; /* number of local columns for a color */
665: PetscInt *nrows; /* number of local rows for each color */
666: PetscInt currentcolor; /* color for which function evaluation is being done now */
667: ISColoringType ctype; /* IS_COLORING_GLOBAL or IS_COLORING_LOCAL */
669: PetscInt *colorforrow,*colorforcol; /* pointer to rows and columns */
670: PetscInt *rows; /* lists the local rows for each color (using the local row numbering) */
671: PetscInt *den2sp; /* maps (row,color) in the dense matrix to index of sparse matrix array a->a */
672: PetscInt *columns; /* lists the local columns of each color (using global column numbering) */
673: PetscInt brows; /* number of rows for efficient implementation of MatTransColoringApplyDenToSp() */
674: PetscInt *lstart; /* array used for loop over row blocks of Csparse */
675: };
677: /*
678: Null space context for preconditioner/operators
679: */
680: struct _p_MatNullSpace {
681: PETSCHEADER(int);
682: PetscBool has_cnst;
683: PetscInt n;
684: Vec* vecs;
685: PetscScalar* alpha; /* for projections */
686: PetscErrorCode (*remove)(MatNullSpace,Vec,void*); /* for user provided removal function */
687: void* rmctx; /* context for remove() function */
688: };
690: /*
691: Checking zero pivot for LU, ILU preconditioners.
692: */
693: typedef struct {
694: PetscInt nshift,nshift_max;
695: PetscReal shift_amount,shift_lo,shift_hi,shift_top,shift_fraction;
696: PetscBool newshift;
697: PetscReal rs; /* active row sum of abs(offdiagonals) */
698: PetscScalar pv; /* pivot of the active row */
699: } FactorShiftCtx;
701: /*
702: Used by MatCreateSubMatrices_MPIXAIJ_Local()
703: */
704: #include <petscctable.h>
705: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
706: PetscInt id; /* index of submats, only submats[0] is responsible for deleting some arrays below */
707: PetscInt nrqs,nrqr;
708: PetscInt **rbuf1,**rbuf2,**rbuf3,**sbuf1,**sbuf2;
709: PetscInt **ptr;
710: PetscInt *tmp;
711: PetscInt *ctr;
712: PetscInt *pa; /* proc array */
713: PetscInt *req_size,*req_source1,*req_source2;
714: PetscBool allcolumns,allrows;
715: PetscBool singleis;
716: PetscInt *row2proc; /* row to proc map */
717: PetscInt nstages;
718: #if defined(PETSC_USE_CTABLE)
719: PetscTable cmap,rmap;
720: PetscInt *cmap_loc,*rmap_loc;
721: #else
722: PetscInt *cmap,*rmap;
723: #endif
725: PetscErrorCode (*destroy)(Mat);
726: } Mat_SubSppt;
728: PETSC_EXTERN PetscErrorCode MatFactorDumpMatrix(Mat);
729: PETSC_INTERN PetscErrorCode MatShift_Basic(Mat,PetscScalar);
730: PETSC_INTERN PetscErrorCode MatSetBlockSizes_Default(Mat,PetscInt,PetscInt);
732: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_nz(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
733: {
734: PetscReal _rs = sctx->rs;
735: PetscReal _zero = info->zeropivot*_rs;
738: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
739: /* force |diag| > zeropivot*rs */
740: if (!sctx->nshift) sctx->shift_amount = info->shiftamount;
741: else sctx->shift_amount *= 2.0;
742: sctx->newshift = PETSC_TRUE;
743: (sctx->nshift)++;
744: } else {
745: sctx->newshift = PETSC_FALSE;
746: }
747: return(0);
748: }
750: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_pd(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
751: {
752: PetscReal _rs = sctx->rs;
753: PetscReal _zero = info->zeropivot*_rs;
756: if (PetscRealPart(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
757: /* force matfactor to be diagonally dominant */
758: if (sctx->nshift == sctx->nshift_max) {
759: sctx->shift_fraction = sctx->shift_hi;
760: } else {
761: sctx->shift_lo = sctx->shift_fraction;
762: sctx->shift_fraction = (sctx->shift_hi+sctx->shift_lo)/2.;
763: }
764: sctx->shift_amount = sctx->shift_fraction * sctx->shift_top;
765: sctx->nshift++;
766: sctx->newshift = PETSC_TRUE;
767: } else {
768: sctx->newshift = PETSC_FALSE;
769: }
770: return(0);
771: }
773: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_inblocks(Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
774: {
775: PetscReal _zero = info->zeropivot;
778: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)){
779: sctx->pv += info->shiftamount;
780: sctx->shift_amount = 0.0;
781: sctx->nshift++;
782: }
783: sctx->newshift = PETSC_FALSE;
784: return(0);
785: }
787: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck_none(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
788: {
789: PetscReal _zero = info->zeropivot;
793: sctx->newshift = PETSC_FALSE;
794: if (PetscAbsScalar(sctx->pv) <= _zero && !PetscIsNanScalar(sctx->pv)) {
795: if (!mat->erroriffailure) {
796: PetscInfo3(mat,"Detected zero pivot in factorization in row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
797: fact->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
798: fact->factorerror_zeropivot_value = PetscAbsScalar(sctx->pv);
799: fact->factorerror_zeropivot_row = row;
800: } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot row %D value %g tolerance %g\n",row,(double)PetscAbsScalar(sctx->pv),(double)_zero);
801: }
802: return(0);
803: }
805: PETSC_STATIC_INLINE PetscErrorCode MatPivotCheck(Mat fact,Mat mat,const MatFactorInfo *info,FactorShiftCtx *sctx,PetscInt row)
806: {
810: if (info->shifttype == (PetscReal) MAT_SHIFT_NONZERO){
811: MatPivotCheck_nz(mat,info,sctx,row);
812: } else if (info->shifttype == (PetscReal) MAT_SHIFT_POSITIVE_DEFINITE){
813: MatPivotCheck_pd(mat,info,sctx,row);
814: } else if (info->shifttype == (PetscReal) MAT_SHIFT_INBLOCKS){
815: MatPivotCheck_inblocks(mat,info,sctx,row);
816: } else {
817: MatPivotCheck_none(fact,mat,info,sctx,row);
818: }
819: return(0);
820: }
822: /*
823: Create and initialize a linked list
824: Input Parameters:
825: idx_start - starting index of the list
826: lnk_max - max value of lnk indicating the end of the list
827: nlnk - max length of the list
828: Output Parameters:
829: lnk - list initialized
830: bt - PetscBT (bitarray) with all bits set to false
831: lnk_empty - flg indicating the list is empty
832: */
833: #define PetscLLCreate(idx_start,lnk_max,nlnk,lnk,bt) \
834: (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,0))
836: #define PetscLLCreate_new(idx_start,lnk_max,nlnk,lnk,bt,lnk_empty)\
837: (PetscMalloc1(nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk_empty = PETSC_TRUE,0) ||(lnk[idx_start] = lnk_max,0))
839: /*
840: Add an index set into a sorted linked list
841: Input Parameters:
842: nidx - number of input indices
843: indices - integer array
844: idx_start - starting index of the list
845: lnk - linked list(an integer array) that is created
846: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
847: output Parameters:
848: nlnk - number of newly added indices
849: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
850: bt - updated PetscBT (bitarray)
851: */
852: #define PetscLLAdd(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
853: {\
854: PetscInt _k,_entry,_location,_lnkdata;\
855: nlnk = 0;\
856: _lnkdata = idx_start;\
857: for (_k=0; _k<nidx; _k++){\
858: _entry = indices[_k];\
859: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
860: /* search for insertion location */\
861: /* start from the beginning if _entry < previous _entry */\
862: if (_k && _entry < _lnkdata) _lnkdata = idx_start;\
863: do {\
864: _location = _lnkdata;\
865: _lnkdata = lnk[_location];\
866: } while (_entry > _lnkdata);\
867: /* insertion location is found, add entry into lnk */\
868: lnk[_location] = _entry;\
869: lnk[_entry] = _lnkdata;\
870: nlnk++;\
871: _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
872: }\
873: }\
874: }
876: /*
877: Add a permuted index set into a sorted linked list
878: Input Parameters:
879: nidx - number of input indices
880: indices - integer array
881: perm - permutation of indices
882: idx_start - starting index of the list
883: lnk - linked list(an integer array) that is created
884: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
885: output Parameters:
886: nlnk - number of newly added indices
887: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
888: bt - updated PetscBT (bitarray)
889: */
890: #define PetscLLAddPerm(nidx,indices,perm,idx_start,nlnk,lnk,bt) 0;\
891: {\
892: PetscInt _k,_entry,_location,_lnkdata;\
893: nlnk = 0;\
894: _lnkdata = idx_start;\
895: for (_k=0; _k<nidx; _k++){\
896: _entry = perm[indices[_k]];\
897: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
898: /* search for insertion location */\
899: /* start from the beginning if _entry < previous _entry */\
900: if (_k && _entry < _lnkdata) _lnkdata = idx_start;\
901: do {\
902: _location = _lnkdata;\
903: _lnkdata = lnk[_location];\
904: } while (_entry > _lnkdata);\
905: /* insertion location is found, add entry into lnk */\
906: lnk[_location] = _entry;\
907: lnk[_entry] = _lnkdata;\
908: nlnk++;\
909: _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
910: }\
911: }\
912: }
914: /*
915: Add a SORTED ascending index set into a sorted linked list - same as PetscLLAdd() bus skip 'if (_k && _entry < _lnkdata) _lnkdata = idx_start;'
916: Input Parameters:
917: nidx - number of input indices
918: indices - sorted integer array
919: idx_start - starting index of the list
920: lnk - linked list(an integer array) that is created
921: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
922: output Parameters:
923: nlnk - number of newly added indices
924: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
925: bt - updated PetscBT (bitarray)
926: */
927: #define PetscLLAddSorted(nidx,indices,idx_start,nlnk,lnk,bt) 0;\
928: {\
929: PetscInt _k,_entry,_location,_lnkdata;\
930: nlnk = 0;\
931: _lnkdata = idx_start;\
932: for (_k=0; _k<nidx; _k++){\
933: _entry = indices[_k];\
934: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
935: /* search for insertion location */\
936: do {\
937: _location = _lnkdata;\
938: _lnkdata = lnk[_location];\
939: } while (_entry > _lnkdata);\
940: /* insertion location is found, add entry into lnk */\
941: lnk[_location] = _entry;\
942: lnk[_entry] = _lnkdata;\
943: nlnk++;\
944: _lnkdata = _entry; /* next search starts from here */\
945: }\
946: }\
947: }
949: #define PetscLLAddSorted_new(nidx,indices,idx_start,lnk_empty,nlnk,lnk,bt) 0; \
950: {\
951: PetscInt _k,_entry,_location,_lnkdata;\
952: if (lnk_empty){\
953: _lnkdata = idx_start; \
954: for (_k=0; _k<nidx; _k++){ \
955: _entry = indices[_k]; \
956: PetscBTSet(bt,_entry); /* mark the new entry */ \
957: _location = _lnkdata; \
958: _lnkdata = lnk[_location]; \
959: /* insertion location is found, add entry into lnk */ \
960: lnk[_location] = _entry; \
961: lnk[_entry] = _lnkdata; \
962: _lnkdata = _entry; /* next search starts from here */ \
963: } \
964: /*\
965: lnk[indices[nidx-1]] = lnk[idx_start];\
966: lnk[idx_start] = indices[0];\
967: PetscBTSet(bt,indices[0]); \
968: for (_k=1; _k<nidx; _k++){ \
969: PetscBTSet(bt,indices[_k]); \
970: lnk[indices[_k-1]] = indices[_k]; \
971: } \
972: */\
973: nlnk = nidx;\
974: lnk_empty = PETSC_FALSE;\
975: } else {\
976: nlnk = 0; \
977: _lnkdata = idx_start; \
978: for (_k=0; _k<nidx; _k++){ \
979: _entry = indices[_k]; \
980: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */ \
981: /* search for insertion location */ \
982: do { \
983: _location = _lnkdata; \
984: _lnkdata = lnk[_location]; \
985: } while (_entry > _lnkdata); \
986: /* insertion location is found, add entry into lnk */ \
987: lnk[_location] = _entry; \
988: lnk[_entry] = _lnkdata; \
989: nlnk++; \
990: _lnkdata = _entry; /* next search starts from here */ \
991: } \
992: } \
993: } \
994: }
996: /*
997: Add a SORTED index set into a sorted linked list used for LUFactorSymbolic()
998: Same as PetscLLAddSorted() with an additional operation:
999: count the number of input indices that are no larger than 'diag'
1000: Input Parameters:
1001: indices - sorted integer array
1002: idx_start - starting index of the list, index of pivot row
1003: lnk - linked list(an integer array) that is created
1004: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1005: diag - index of the active row in LUFactorSymbolic
1006: nzbd - number of input indices with indices <= idx_start
1007: im - im[idx_start] is initialized as num of nonzero entries in row=idx_start
1008: output Parameters:
1009: nlnk - number of newly added indices
1010: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from indices
1011: bt - updated PetscBT (bitarray)
1012: im - im[idx_start]: unchanged if diag is not an entry
1013: : num of entries with indices <= diag if diag is an entry
1014: */
1015: #define PetscLLAddSortedLU(indices,idx_start,nlnk,lnk,bt,diag,nzbd,im) 0;\
1016: {\
1017: PetscInt _k,_entry,_location,_lnkdata,_nidx;\
1018: nlnk = 0;\
1019: _lnkdata = idx_start;\
1020: _nidx = im[idx_start] - nzbd; /* num of entries with idx_start < index <= diag */\
1021: for (_k=0; _k<_nidx; _k++){\
1022: _entry = indices[_k];\
1023: nzbd++;\
1024: if (_entry== diag) im[idx_start] = nzbd;\
1025: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
1026: /* search for insertion location */\
1027: do {\
1028: _location = _lnkdata;\
1029: _lnkdata = lnk[_location];\
1030: } while (_entry > _lnkdata);\
1031: /* insertion location is found, add entry into lnk */\
1032: lnk[_location] = _entry;\
1033: lnk[_entry] = _lnkdata;\
1034: nlnk++;\
1035: _lnkdata = _entry; /* next search starts from here */\
1036: }\
1037: }\
1038: }
1040: /*
1041: Copy data on the list into an array, then initialize the list
1042: Input Parameters:
1043: idx_start - starting index of the list
1044: lnk_max - max value of lnk indicating the end of the list
1045: nlnk - number of data on the list to be copied
1046: lnk - linked list
1047: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1048: output Parameters:
1049: indices - array that contains the copied data
1050: lnk - linked list that is cleaned and initialize
1051: bt - PetscBT (bitarray) with all bits set to false
1052: */
1053: #define PetscLLClean(idx_start,lnk_max,nlnk,lnk,indices,bt) 0;\
1054: {\
1055: PetscInt _j,_idx=idx_start;\
1056: for (_j=0; _j<nlnk; _j++){\
1057: _idx = lnk[_idx];\
1058: indices[_j] = _idx;\
1059: PetscBTClear(bt,_idx);\
1060: }\
1061: lnk[idx_start] = lnk_max;\
1062: }
1063: /*
1064: Free memories used by the list
1065: */
1066: #define PetscLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))
1068: /* Routines below are used for incomplete matrix factorization */
1069: /*
1070: Create and initialize a linked list and its levels
1071: Input Parameters:
1072: idx_start - starting index of the list
1073: lnk_max - max value of lnk indicating the end of the list
1074: nlnk - max length of the list
1075: Output Parameters:
1076: lnk - list initialized
1077: lnk_lvl - array of size nlnk for storing levels of lnk
1078: bt - PetscBT (bitarray) with all bits set to false
1079: */
1080: #define PetscIncompleteLLCreate(idx_start,lnk_max,nlnk,lnk,lnk_lvl,bt)\
1081: (PetscIntMultError(2,nlnk,NULL) || PetscMalloc1(2*nlnk,&lnk) || PetscBTCreate(nlnk,&(bt)) || (lnk[idx_start] = lnk_max,lnk_lvl = lnk + nlnk,0))
1083: /*
1084: Initialize a sorted linked list used for ILU and ICC
1085: Input Parameters:
1086: nidx - number of input idx
1087: idx - integer array used for storing column indices
1088: idx_start - starting index of the list
1089: perm - indices of an IS
1090: lnk - linked list(an integer array) that is created
1091: lnklvl - levels of lnk
1092: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1093: output Parameters:
1094: nlnk - number of newly added idx
1095: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1096: lnklvl - levels of lnk
1097: bt - updated PetscBT (bitarray)
1098: */
1099: #define PetscIncompleteLLInit(nidx,idx,idx_start,perm,nlnk,lnk,lnklvl,bt) 0;\
1100: {\
1101: PetscInt _k,_entry,_location,_lnkdata;\
1102: nlnk = 0;\
1103: _lnkdata = idx_start;\
1104: for (_k=0; _k<nidx; _k++){\
1105: _entry = perm[idx[_k]];\
1106: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
1107: /* search for insertion location */\
1108: if (_k && _entry < _lnkdata) _lnkdata = idx_start;\
1109: do {\
1110: _location = _lnkdata;\
1111: _lnkdata = lnk[_location];\
1112: } while (_entry > _lnkdata);\
1113: /* insertion location is found, add entry into lnk */\
1114: lnk[_location] = _entry;\
1115: lnk[_entry] = _lnkdata;\
1116: lnklvl[_entry] = 0;\
1117: nlnk++;\
1118: _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1119: }\
1120: }\
1121: }
1123: /*
1124: Add a SORTED index set into a sorted linked list for ILU
1125: Input Parameters:
1126: nidx - number of input indices
1127: idx - sorted integer array used for storing column indices
1128: level - level of fill, e.g., ICC(level)
1129: idxlvl - level of idx
1130: idx_start - starting index of the list
1131: lnk - linked list(an integer array) that is created
1132: lnklvl - levels of lnk
1133: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1134: prow - the row number of idx
1135: output Parameters:
1136: nlnk - number of newly added idx
1137: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1138: lnklvl - levels of lnk
1139: bt - updated PetscBT (bitarray)
1141: Note: the level of factor(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(i,prow)+lvl(prow,j)+1)
1142: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1143: */
1144: #define PetscILULLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,lnklvl_prow) 0;\
1145: {\
1146: PetscInt _k,_entry,_location,_lnkdata,_incrlev,_lnklvl_prow=lnklvl[prow];\
1147: nlnk = 0;\
1148: _lnkdata = idx_start;\
1149: for (_k=0; _k<nidx; _k++){\
1150: _incrlev = idxlvl[_k] + _lnklvl_prow + 1;\
1151: if (_incrlev > level) continue;\
1152: _entry = idx[_k];\
1153: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
1154: /* search for insertion location */\
1155: do {\
1156: _location = _lnkdata;\
1157: _lnkdata = lnk[_location];\
1158: } while (_entry > _lnkdata);\
1159: /* insertion location is found, add entry into lnk */\
1160: lnk[_location] = _entry;\
1161: lnk[_entry] = _lnkdata;\
1162: lnklvl[_entry] = _incrlev;\
1163: nlnk++;\
1164: _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1165: } else { /* existing entry: update lnklvl */\
1166: if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1167: }\
1168: }\
1169: }
1171: /*
1172: Add a index set into a sorted linked list
1173: Input Parameters:
1174: nidx - number of input idx
1175: idx - integer array used for storing column indices
1176: level - level of fill, e.g., ICC(level)
1177: idxlvl - level of idx
1178: idx_start - starting index of the list
1179: lnk - linked list(an integer array) that is created
1180: lnklvl - levels of lnk
1181: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1182: output Parameters:
1183: nlnk - number of newly added idx
1184: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1185: lnklvl - levels of lnk
1186: bt - updated PetscBT (bitarray)
1187: */
1188: #define PetscIncompleteLLAdd(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1189: {\
1190: PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1191: nlnk = 0;\
1192: _lnkdata = idx_start;\
1193: for (_k=0; _k<nidx; _k++){\
1194: _incrlev = idxlvl[_k] + 1;\
1195: if (_incrlev > level) continue;\
1196: _entry = idx[_k];\
1197: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
1198: /* search for insertion location */\
1199: if (_k && _entry < _lnkdata) _lnkdata = idx_start;\
1200: do {\
1201: _location = _lnkdata;\
1202: _lnkdata = lnk[_location];\
1203: } while (_entry > _lnkdata);\
1204: /* insertion location is found, add entry into lnk */\
1205: lnk[_location] = _entry;\
1206: lnk[_entry] = _lnkdata;\
1207: lnklvl[_entry] = _incrlev;\
1208: nlnk++;\
1209: _lnkdata = _entry; /* next search starts from here if next_entry > _entry */\
1210: } else { /* existing entry: update lnklvl */\
1211: if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1212: }\
1213: }\
1214: }
1216: /*
1217: Add a SORTED index set into a sorted linked list
1218: Input Parameters:
1219: nidx - number of input indices
1220: idx - sorted integer array used for storing column indices
1221: level - level of fill, e.g., ICC(level)
1222: idxlvl - level of idx
1223: idx_start - starting index of the list
1224: lnk - linked list(an integer array) that is created
1225: lnklvl - levels of lnk
1226: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1227: output Parameters:
1228: nlnk - number of newly added idx
1229: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1230: lnklvl - levels of lnk
1231: bt - updated PetscBT (bitarray)
1232: */
1233: #define PetscIncompleteLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt) 0;\
1234: {\
1235: PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1236: nlnk = 0;\
1237: _lnkdata = idx_start;\
1238: for (_k=0; _k<nidx; _k++){\
1239: _incrlev = idxlvl[_k] + 1;\
1240: if (_incrlev > level) continue;\
1241: _entry = idx[_k];\
1242: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
1243: /* search for insertion location */\
1244: do {\
1245: _location = _lnkdata;\
1246: _lnkdata = lnk[_location];\
1247: } while (_entry > _lnkdata);\
1248: /* insertion location is found, add entry into lnk */\
1249: lnk[_location] = _entry;\
1250: lnk[_entry] = _lnkdata;\
1251: lnklvl[_entry] = _incrlev;\
1252: nlnk++;\
1253: _lnkdata = _entry; /* next search starts from here */\
1254: } else { /* existing entry: update lnklvl */\
1255: if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1256: }\
1257: }\
1258: }
1260: /*
1261: Add a SORTED index set into a sorted linked list for ICC
1262: Input Parameters:
1263: nidx - number of input indices
1264: idx - sorted integer array used for storing column indices
1265: level - level of fill, e.g., ICC(level)
1266: idxlvl - level of idx
1267: idx_start - starting index of the list
1268: lnk - linked list(an integer array) that is created
1269: lnklvl - levels of lnk
1270: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1271: idxlvl_prow - idxlvl[prow], where prow is the row number of the idx
1272: output Parameters:
1273: nlnk - number of newly added indices
1274: lnk - the sorted(increasing order) linked list containing new and non-redundate entries from idx
1275: lnklvl - levels of lnk
1276: bt - updated PetscBT (bitarray)
1277: Note: the level of U(i,j) is set as lvl(i,j) = min{ lvl(i,j), lvl(prow,i)+lvl(prow,j)+1)
1278: where idx = non-zero columns of U(prow,prow+1:n-1), prow<i
1279: */
1280: #define PetscICCLLAddSorted(nidx,idx,level,idxlvl,idx_start,nlnk,lnk,lnklvl,bt,idxlvl_prow) 0;\
1281: {\
1282: PetscInt _k,_entry,_location,_lnkdata,_incrlev;\
1283: nlnk = 0;\
1284: _lnkdata = idx_start;\
1285: for (_k=0; _k<nidx; _k++){\
1286: _incrlev = idxlvl[_k] + idxlvl_prow + 1;\
1287: if (_incrlev > level) continue;\
1288: _entry = idx[_k];\
1289: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */\
1290: /* search for insertion location */\
1291: do {\
1292: _location = _lnkdata;\
1293: _lnkdata = lnk[_location];\
1294: } while (_entry > _lnkdata);\
1295: /* insertion location is found, add entry into lnk */\
1296: lnk[_location] = _entry;\
1297: lnk[_entry] = _lnkdata;\
1298: lnklvl[_entry] = _incrlev;\
1299: nlnk++;\
1300: _lnkdata = _entry; /* next search starts from here */\
1301: } else { /* existing entry: update lnklvl */\
1302: if (lnklvl[_entry] > _incrlev) lnklvl[_entry] = _incrlev;\
1303: }\
1304: }\
1305: }
1307: /*
1308: Copy data on the list into an array, then initialize the list
1309: Input Parameters:
1310: idx_start - starting index of the list
1311: lnk_max - max value of lnk indicating the end of the list
1312: nlnk - number of data on the list to be copied
1313: lnk - linked list
1314: lnklvl - level of lnk
1315: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1316: output Parameters:
1317: indices - array that contains the copied data
1318: lnk - linked list that is cleaned and initialize
1319: lnklvl - level of lnk that is reinitialized
1320: bt - PetscBT (bitarray) with all bits set to false
1321: */
1322: #define PetscIncompleteLLClean(idx_start,lnk_max,nlnk,lnk,lnklvl,indices,indiceslvl,bt) 0;\
1323: do {\
1324: PetscInt _j,_idx=idx_start;\
1325: for (_j=0; _j<nlnk; _j++){\
1326: _idx = lnk[_idx];\
1327: *(indices+_j) = _idx;\
1328: *(indiceslvl+_j) = lnklvl[_idx];\
1329: lnklvl[_idx] = -1;\
1330: PetscBTClear(bt,_idx);\
1331: }\
1332: lnk[idx_start] = lnk_max;\
1333: } while (0)
1334: /*
1335: Free memories used by the list
1336: */
1337: #define PetscIncompleteLLDestroy(lnk,bt) (PetscFree(lnk) || PetscBTDestroy(&(bt)))
1339: #define MatCheckSameLocalSize(A,ar1,B,ar2) do { \
1341: if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n)) SETERRQ6(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Incompatible matrix local sizes: parameter # %d (%D x %D) != parameter # %d (%D x %D)",ar1,A->rmap->n,A->cmap->n,ar2,B->rmap->n,B->cmap->n);} while (0)
1343: #define MatCheckSameSize(A,ar1,B,ar2) do { \
1344: if ((A->rmap->N != B->rmap->N) || (A->cmap->N != B->cmap->N)) SETERRQ6(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_INCOMP,"Incompatible matrix global sizes: parameter # %d (%D x %D) != parameter # %d (%D x %D)",ar1,A->rmap->N,A->cmap->N,ar2,B->rmap->N,B->cmap->N);\
1345: MatCheckSameLocalSize(A,ar1,B,ar2);} while (0)
1347: #define VecCheckMatCompatible(M,x,ar1,b,ar2) do { \
1348: if (M->cmap->N != x->map->N) SETERRQ3(PetscObjectComm((PetscObject)M),PETSC_ERR_ARG_SIZ,"Vector global length incompatible with matrix: parameter # %d global size %D != matrix column global size %D",ar1,x->map->N,M->cmap->N); \
1349: if (M->rmap->N != b->map->N) SETERRQ3(PetscObjectComm((PetscObject)M),PETSC_ERR_ARG_SIZ,"Vector global length incompatible with matrix: parameter # %d global size %D != matrix row global size %D",ar2,b->map->N,M->rmap->N);} while (0)
1351: /* -------------------------------------------------------------------------------------------------------*/
1352: #include <petscbt.h>
1353: /*
1354: Create and initialize a condensed linked list -
1355: same as PetscLLCreate(), but uses a scalable array 'lnk' with size of max number of entries, not O(N).
1356: Barry suggested this approach (Dec. 6, 2011):
1357: I've thought of an alternative way of representing a linked list that is efficient but doesn't have the O(N) scaling issue
1358: (it may be faster than the O(N) even sequentially due to less crazy memory access).
1360: 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
1361: 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
1362: 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
1363: 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.
1364: 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
1365: to each other so memory access is much better than using the big array.
1367: Example:
1368: nlnk_max=5, lnk_max=36:
1369: Initial list: [0, 0 | 36, 2 | 0, 0 | 0, 0 | 0, 0 | 0, 0 | 0, 0]
1370: here, head_node has index 2 with value lnk[2]=lnk_max=36,
1371: 0-th entry is used to store the number of entries in the list,
1372: The initial lnk represents head -> tail(marked by 36) with number of entries = lnk[0]=0.
1374: Now adding a sorted set {2,4}, the list becomes
1375: [2, 0 | 36, 4 |2, 6 | 4, 2 | 0, 0 | 0, 0 | 0, 0 ]
1376: represents head -> 2 -> 4 -> tail with number of entries = lnk[0]=2.
1378: Then adding a sorted set {0,3,35}, the list
1379: [5, 0 | 36, 8 | 2, 10 | 4, 12 | 0, 4 | 3, 6 | 35, 2 ]
1380: represents head -> 0 -> 2 -> 3 -> 4 -> 35 -> tail with number of entries = lnk[0]=5.
1382: Input Parameters:
1383: nlnk_max - max length of the list
1384: lnk_max - max value of the entries
1385: Output Parameters:
1386: lnk - list created and initialized
1387: bt - PetscBT (bitarray) with all bits set to false. Note: bt has size lnk_max, not nln_max!
1388: */
1389: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate(PetscInt nlnk_max,PetscInt lnk_max,PetscInt **lnk,PetscBT *bt)
1390: {
1392: PetscInt *llnk,lsize = 0;
1395: PetscIntMultError(2,nlnk_max+2,&lsize);
1396: PetscMalloc1(lsize,lnk);
1397: PetscBTCreate(lnk_max,bt);
1398: llnk = *lnk;
1399: llnk[0] = 0; /* number of entries on the list */
1400: llnk[2] = lnk_max; /* value in the head node */
1401: llnk[3] = 2; /* next for the head node */
1402: return(0);
1403: }
1405: /*
1406: Add a SORTED ascending index set into a sorted linked list. See PetscLLCondensedCreate() for detailed description.
1407: Input Parameters:
1408: nidx - number of input indices
1409: indices - sorted integer array
1410: lnk - condensed linked list(an integer array) that is created
1411: bt - PetscBT (bitarray), bt[idx]=true marks idx is in lnk
1412: output Parameters:
1413: lnk - the sorted(increasing order) linked list containing previous and newly added non-redundate indices
1414: bt - updated PetscBT (bitarray)
1415: */
1416: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted(PetscInt nidx,const PetscInt indices[],PetscInt lnk[],PetscBT bt)
1417: {
1418: PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
1421: _nlnk = lnk[0]; /* num of entries on the input lnk */
1422: _location = 2; /* head */
1423: for (_k=0; _k<nidx; _k++){
1424: _entry = indices[_k];
1425: if (!PetscBTLookupSet(bt,_entry)){ /* new entry */
1426: /* search for insertion location */
1427: do {
1428: _next = _location + 1; /* link from previous node to next node */
1429: _location = lnk[_next]; /* idx of next node */
1430: _lnkdata = lnk[_location];/* value of next node */
1431: } while (_entry > _lnkdata);
1432: /* insertion location is found, add entry into lnk */
1433: _newnode = 2*(_nlnk+2); /* index for this new node */
1434: lnk[_next] = _newnode; /* connect previous node to the new node */
1435: lnk[_newnode] = _entry; /* set value of the new node */
1436: lnk[_newnode+1] = _location; /* connect new node to next node */
1437: _location = _newnode; /* next search starts from the new node */
1438: _nlnk++;
1439: } \
1440: }\
1441: lnk[0] = _nlnk; /* number of entries in the list */
1442: return(0);
1443: }
1445: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean(PetscInt lnk_max,PetscInt nidx,PetscInt *indices,PetscInt lnk[],PetscBT bt)
1446: {
1448: PetscInt _k,_next,_nlnk;
1451: _next = lnk[3]; /* head node */
1452: _nlnk = lnk[0]; /* num of entries on the list */
1453: for (_k=0; _k<_nlnk; _k++){
1454: indices[_k] = lnk[_next];
1455: _next = lnk[_next + 1];
1456: PetscBTClear(bt,indices[_k]);
1457: }
1458: lnk[0] = 0; /* num of entries on the list */
1459: lnk[2] = lnk_max; /* initialize head node */
1460: lnk[3] = 2; /* head node */
1461: return(0);
1462: }
1464: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView(PetscInt *lnk)
1465: {
1467: PetscInt k;
1470: PetscPrintf(PETSC_COMM_SELF,"LLCondensed of size %D, (val, next)\n",lnk[0]);
1471: for (k=2; k< lnk[0]+2; k++){
1472: PetscPrintf(PETSC_COMM_SELF," %D: (%D, %D)\n",2*k,lnk[2*k],lnk[2*k+1]);
1473: }
1474: return(0);
1475: }
1477: /*
1478: Free memories used by the list
1479: */
1480: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy(PetscInt *lnk,PetscBT bt)
1481: {
1485: PetscFree(lnk);
1486: PetscBTDestroy(&bt);
1487: return(0);
1488: }
1490: /* -------------------------------------------------------------------------------------------------------*/
1491: /*
1492: Same as PetscLLCondensedCreate(), but does not use non-scalable O(lnk_max) bitarray
1493: Input Parameters:
1494: nlnk_max - max length of the list
1495: Output Parameters:
1496: lnk - list created and initialized
1497: */
1498: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1499: {
1501: PetscInt *llnk,lsize = 0;
1504: PetscIntMultError(2,nlnk_max+2,&lsize);
1505: PetscMalloc1(lsize,lnk);
1506: llnk = *lnk;
1507: llnk[0] = 0; /* number of entries on the list */
1508: llnk[2] = PETSC_MAX_INT; /* value in the head node */
1509: llnk[3] = 2; /* next for the head node */
1510: return(0);
1511: }
1513: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedExpand_Scalable(PetscInt nlnk_max,PetscInt **lnk)
1514: {
1516: PetscInt lsize = 0;
1519: PetscIntMultError(2,nlnk_max+2,&lsize);
1520: PetscRealloc(lsize*sizeof(PetscInt),lnk);
1521: return(0);
1522: }
1524: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_Scalable(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1525: {
1526: PetscInt _k,_entry,_location,_next,_lnkdata,_nlnk,_newnode;
1527: _nlnk = lnk[0]; /* num of entries on the input lnk */
1528: _location = 2; /* head */ \
1529: for (_k=0; _k<nidx; _k++){
1530: _entry = indices[_k];
1531: /* search for insertion location */
1532: do {
1533: _next = _location + 1; /* link from previous node to next node */
1534: _location = lnk[_next]; /* idx of next node */
1535: _lnkdata = lnk[_location];/* value of next node */
1536: } while (_entry > _lnkdata);
1537: if (_entry < _lnkdata) {
1538: /* insertion location is found, add entry into lnk */
1539: _newnode = 2*(_nlnk+2); /* index for this new node */
1540: lnk[_next] = _newnode; /* connect previous node to the new node */
1541: lnk[_newnode] = _entry; /* set value of the new node */
1542: lnk[_newnode+1] = _location; /* connect new node to next node */
1543: _location = _newnode; /* next search starts from the new node */
1544: _nlnk++;
1545: }
1546: }
1547: lnk[0] = _nlnk; /* number of entries in the list */
1548: return 0;
1549: }
1551: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_Scalable(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1552: {
1553: PetscInt _k,_next,_nlnk;
1554: _next = lnk[3]; /* head node */
1555: _nlnk = lnk[0];
1556: for (_k=0; _k<_nlnk; _k++){
1557: indices[_k] = lnk[_next];
1558: _next = lnk[_next + 1];
1559: }
1560: lnk[0] = 0; /* num of entries on the list */
1561: lnk[3] = 2; /* head node */
1562: return 0;
1563: }
1565: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_Scalable(PetscInt *lnk)
1566: {
1567: return PetscFree(lnk);
1568: }
1570: /* -------------------------------------------------------------------------------------------------------*/
1571: /*
1572: lnk[0] number of links
1573: lnk[1] number of entries
1574: lnk[3n] value
1575: lnk[3n+1] len
1576: lnk[3n+2] link to next value
1578: The next three are always the first link
1580: lnk[3] PETSC_MIN_INT+1
1581: lnk[4] 1
1582: lnk[5] link to first real entry
1584: The next three are always the last link
1586: lnk[6] PETSC_MAX_INT - 1
1587: lnk[7] 1
1588: lnk[8] next valid link (this is the same as lnk[0] but without the decreases)
1589: */
1591: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedCreate_fast(PetscInt nlnk_max,PetscInt **lnk)
1592: {
1594: PetscInt *llnk,lsize = 0;
1597: PetscIntMultError(3,nlnk_max+3,&lsize);
1598: PetscMalloc1(lsize,lnk);
1599: llnk = *lnk;
1600: llnk[0] = 0; /* nlnk: number of entries on the list */
1601: llnk[1] = 0; /* number of integer entries represented in list */
1602: llnk[3] = PETSC_MIN_INT+1; /* value in the first node */
1603: llnk[4] = 1; /* count for the first node */
1604: llnk[5] = 6; /* next for the first node */
1605: llnk[6] = PETSC_MAX_INT-1; /* value in the last node */
1606: llnk[7] = 1; /* count for the last node */
1607: llnk[8] = 0; /* next valid node to be used */
1608: return(0);
1609: }
1611: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedAddSorted_fast(PetscInt nidx,const PetscInt indices[],PetscInt lnk[])
1612: {
1613: PetscInt k,entry,prev,next;
1614: prev = 3; /* first value */
1615: next = lnk[prev+2];
1616: for (k=0; k<nidx; k++){
1617: entry = indices[k];
1618: /* search for insertion location */
1619: while (entry >= lnk[next]) {
1620: prev = next;
1621: next = lnk[next+2];
1622: }
1623: /* entry is in range of previous list */
1624: if (entry < lnk[prev]+lnk[prev+1]) continue;
1625: lnk[1]++;
1626: /* entry is right after previous list */
1627: if (entry == lnk[prev]+lnk[prev+1]) {
1628: lnk[prev+1]++;
1629: if (lnk[next] == entry+1) { /* combine two contiguous strings */
1630: lnk[prev+1] += lnk[next+1];
1631: lnk[prev+2] = lnk[next+2];
1632: next = lnk[next+2];
1633: lnk[0]--;
1634: }
1635: continue;
1636: }
1637: /* entry is right before next list */
1638: if (entry == lnk[next]-1) {
1639: lnk[next]--;
1640: lnk[next+1]++;
1641: prev = next;
1642: next = lnk[prev+2];
1643: continue;
1644: }
1645: /* add entry into lnk */
1646: lnk[prev+2] = 3*((lnk[8]++)+3); /* connect previous node to the new node */
1647: prev = lnk[prev+2];
1648: lnk[prev] = entry; /* set value of the new node */
1649: lnk[prev+1] = 1; /* number of values in contiguous string is one to start */
1650: lnk[prev+2] = next; /* connect new node to next node */
1651: lnk[0]++;
1652: }
1653: return 0;
1654: }
1656: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedClean_fast(PetscInt nidx,PetscInt *indices,PetscInt *lnk)
1657: {
1658: PetscInt _k,_next,_nlnk,cnt,j;
1659: _next = lnk[5]; /* first node */
1660: _nlnk = lnk[0];
1661: cnt = 0;
1662: for (_k=0; _k<_nlnk; _k++){
1663: for (j=0; j<lnk[_next+1]; j++) {
1664: indices[cnt++] = lnk[_next] + j;
1665: }
1666: _next = lnk[_next + 2];
1667: }
1668: lnk[0] = 0; /* nlnk: number of links */
1669: lnk[1] = 0; /* number of integer entries represented in list */
1670: lnk[3] = PETSC_MIN_INT+1; /* value in the first node */
1671: lnk[4] = 1; /* count for the first node */
1672: lnk[5] = 6; /* next for the first node */
1673: lnk[6] = PETSC_MAX_INT-1; /* value in the last node */
1674: lnk[7] = 1; /* count for the last node */
1675: lnk[8] = 0; /* next valid location to make link */
1676: return 0;
1677: }
1679: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedView_fast(PetscInt *lnk)
1680: {
1681: PetscInt k,next,nlnk;
1682: next = lnk[5]; /* first node */
1683: nlnk = lnk[0];
1684: for (k=0; k<nlnk; k++){
1685: #if 0 /* Debugging code */
1686: printf("%d value %d len %d next %d\n",next,lnk[next],lnk[next+1],lnk[next+2]);
1687: #endif
1688: next = lnk[next + 2];
1689: }
1690: return 0;
1691: }
1693: PETSC_STATIC_INLINE PetscErrorCode PetscLLCondensedDestroy_fast(PetscInt *lnk)
1694: {
1695: return PetscFree(lnk);
1696: }
1698: /* this is extern because it is used in MatFDColoringUseDM() which is in the DM library */
1699: PETSC_EXTERN PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,void*);
1701: PETSC_EXTERN PetscLogEvent MAT_Mult;
1702: PETSC_EXTERN PetscLogEvent MAT_MultMatrixFree;
1703: PETSC_EXTERN PetscLogEvent MAT_Mults;
1704: PETSC_EXTERN PetscLogEvent MAT_MultConstrained;
1705: PETSC_EXTERN PetscLogEvent MAT_MultAdd;
1706: PETSC_EXTERN PetscLogEvent MAT_MultTranspose;
1707: PETSC_EXTERN PetscLogEvent MAT_MultTransposeConstrained;
1708: PETSC_EXTERN PetscLogEvent MAT_MultTransposeAdd;
1709: PETSC_EXTERN PetscLogEvent MAT_Solve;
1710: PETSC_EXTERN PetscLogEvent MAT_Solves;
1711: PETSC_EXTERN PetscLogEvent MAT_SolveAdd;
1712: PETSC_EXTERN PetscLogEvent MAT_SolveTranspose;
1713: PETSC_EXTERN PetscLogEvent MAT_SolveTransposeAdd;
1714: PETSC_EXTERN PetscLogEvent MAT_SOR;
1715: PETSC_EXTERN PetscLogEvent MAT_ForwardSolve;
1716: PETSC_EXTERN PetscLogEvent MAT_BackwardSolve;
1717: PETSC_EXTERN PetscLogEvent MAT_LUFactor;
1718: PETSC_EXTERN PetscLogEvent MAT_LUFactorSymbolic;
1719: PETSC_EXTERN PetscLogEvent MAT_LUFactorNumeric;
1720: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactor;
1721: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorSymbolic;
1722: PETSC_EXTERN PetscLogEvent MAT_CholeskyFactorNumeric;
1723: PETSC_EXTERN PetscLogEvent MAT_ILUFactor;
1724: PETSC_EXTERN PetscLogEvent MAT_ILUFactorSymbolic;
1725: PETSC_EXTERN PetscLogEvent MAT_ICCFactorSymbolic;
1726: PETSC_EXTERN PetscLogEvent MAT_Copy;
1727: PETSC_EXTERN PetscLogEvent MAT_Convert;
1728: PETSC_EXTERN PetscLogEvent MAT_Scale;
1729: PETSC_EXTERN PetscLogEvent MAT_AssemblyBegin;
1730: PETSC_EXTERN PetscLogEvent MAT_AssemblyEnd;
1731: PETSC_EXTERN PetscLogEvent MAT_SetValues;
1732: PETSC_EXTERN PetscLogEvent MAT_GetValues;
1733: PETSC_EXTERN PetscLogEvent MAT_GetRow;
1734: PETSC_EXTERN PetscLogEvent MAT_GetRowIJ;
1735: PETSC_EXTERN PetscLogEvent MAT_CreateSubMats;
1736: PETSC_EXTERN PetscLogEvent MAT_GetColoring;
1737: PETSC_EXTERN PetscLogEvent MAT_GetOrdering;
1738: PETSC_EXTERN PetscLogEvent MAT_RedundantMat;
1739: PETSC_EXTERN PetscLogEvent MAT_IncreaseOverlap;
1740: PETSC_EXTERN PetscLogEvent MAT_Partitioning;
1741: PETSC_EXTERN PetscLogEvent MAT_PartitioningND;
1742: PETSC_EXTERN PetscLogEvent MAT_Coarsen;
1743: PETSC_EXTERN PetscLogEvent MAT_ZeroEntries;
1744: PETSC_EXTERN PetscLogEvent MAT_Load;
1745: PETSC_EXTERN PetscLogEvent MAT_View;
1746: PETSC_EXTERN PetscLogEvent MAT_AXPY;
1747: PETSC_EXTERN PetscLogEvent MAT_FDColoringCreate;
1748: PETSC_EXTERN PetscLogEvent MAT_TransposeColoringCreate;
1749: PETSC_EXTERN PetscLogEvent MAT_FDColoringSetUp;
1750: PETSC_EXTERN PetscLogEvent MAT_FDColoringApply;
1751: PETSC_EXTERN PetscLogEvent MAT_Transpose;
1752: PETSC_EXTERN PetscLogEvent MAT_FDColoringFunction;
1753: PETSC_EXTERN PetscLogEvent MAT_CreateSubMat;
1754: PETSC_EXTERN PetscLogEvent MAT_MatSolve;
1755: PETSC_EXTERN PetscLogEvent MAT_MatTrSolve;
1756: PETSC_EXTERN PetscLogEvent MAT_MatMultSymbolic;
1757: PETSC_EXTERN PetscLogEvent MAT_MatMultNumeric;
1758: PETSC_EXTERN PetscLogEvent MAT_Getlocalmatcondensed;
1759: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAcols;
1760: PETSC_EXTERN PetscLogEvent MAT_GetBrowsOfAocols;
1761: PETSC_EXTERN PetscLogEvent MAT_PtAPSymbolic;
1762: PETSC_EXTERN PetscLogEvent MAT_PtAPNumeric;
1763: PETSC_EXTERN PetscLogEvent MAT_Seqstompinum;
1764: PETSC_EXTERN PetscLogEvent MAT_Seqstompisym;
1765: PETSC_EXTERN PetscLogEvent MAT_Seqstompi;
1766: PETSC_EXTERN PetscLogEvent MAT_Getlocalmat;
1767: PETSC_EXTERN PetscLogEvent MAT_RARtSymbolic;
1768: PETSC_EXTERN PetscLogEvent MAT_RARtNumeric;
1769: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultSymbolic;
1770: PETSC_EXTERN PetscLogEvent MAT_MatTransposeMultNumeric;
1771: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultSymbolic;
1772: PETSC_EXTERN PetscLogEvent MAT_TransposeMatMultNumeric;
1773: PETSC_EXTERN PetscLogEvent MAT_MatMatMultSymbolic;
1774: PETSC_EXTERN PetscLogEvent MAT_MatMatMultNumeric;
1775: PETSC_EXTERN PetscLogEvent MAT_Applypapt;
1776: PETSC_EXTERN PetscLogEvent MAT_Applypapt_symbolic;
1777: PETSC_EXTERN PetscLogEvent MAT_Applypapt_numeric;
1778: PETSC_EXTERN PetscLogEvent MAT_Getsymtranspose;
1779: PETSC_EXTERN PetscLogEvent MAT_Getsymtransreduced;
1780: PETSC_EXTERN PetscLogEvent MAT_GetSequentialNonzeroStructure;
1781: PETSC_EXTERN PetscLogEvent MATMFFD_Mult;
1782: PETSC_EXTERN PetscLogEvent MAT_GetMultiProcBlock;
1783: PETSC_EXTERN PetscLogEvent MAT_CUSPARSECopyToGPU;
1784: PETSC_EXTERN PetscLogEvent MAT_CUSPARSEGenerateTranspose;
1785: PETSC_EXTERN PetscLogEvent MAT_SetValuesBatch;
1786: PETSC_EXTERN PetscLogEvent MAT_ViennaCLCopyToGPU;
1787: PETSC_EXTERN PetscLogEvent MAT_DenseCopyToGPU;
1788: PETSC_EXTERN PetscLogEvent MAT_DenseCopyFromGPU;
1789: PETSC_EXTERN PetscLogEvent MAT_Merge;
1790: PETSC_EXTERN PetscLogEvent MAT_Residual;
1791: PETSC_EXTERN PetscLogEvent MAT_SetRandom;
1792: PETSC_EXTERN PetscLogEvent MAT_FactorFactS;
1793: PETSC_EXTERN PetscLogEvent MAT_FactorInvS;
1794: PETSC_EXTERN PetscLogEvent MATCOLORING_Apply;
1795: PETSC_EXTERN PetscLogEvent MATCOLORING_Comm;
1796: PETSC_EXTERN PetscLogEvent MATCOLORING_Local;
1797: PETSC_EXTERN PetscLogEvent MATCOLORING_ISCreate;
1798: PETSC_EXTERN PetscLogEvent MATCOLORING_SetUp;
1799: PETSC_EXTERN PetscLogEvent MATCOLORING_Weights;
1801: #endif