1 2 /* 3 Defines matrix-matrix product routines for pairs of MPIAIJ matrices 4 C = A * B 5 */ 6 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 7 #include <../src/mat/utils/freespace.h> 8 #include <../src/mat/impls/aij/mpi/mpiaij.h> 9 #include <petscbt.h> 10 #include <../src/mat/impls/dense/mpi/mpidense.h> 11 #include <petsc/private/vecimpl.h> 12 #include <petsc/private/vecscatterimpl.h> 13 14 #if defined(PETSC_HAVE_HYPRE) 15 PETSC_INTERN PetscErrorCode MatMatMultSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat); 16 #endif 17 18 PETSC_INTERN PetscErrorCode MatProductSymbolic_AB_MPIAIJ_MPIAIJ(Mat C) 19 { 20 PetscErrorCode ierr; 21 Mat_Product *product = C->product; 22 Mat A=product->A,B=product->B; 23 MatProductAlgorithm alg=product->alg; 24 PetscReal fill=product->fill; 25 PetscBool flg; 26 27 PetscFunctionBegin; 28 /* scalable */ 29 ierr = PetscStrcmp(alg,"scalable",&flg);CHKERRQ(ierr); 30 if (flg) { 31 ierr = MatMatMultSymbolic_MPIAIJ_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 32 goto next; 33 } 34 35 /* nonscalable */ 36 ierr = PetscStrcmp(alg,"nonscalable",&flg);CHKERRQ(ierr); 37 if (flg) { 38 ierr = MatMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(A,B,fill,C);CHKERRQ(ierr); 39 goto next; 40 } 41 42 /* seqmpi */ 43 ierr = PetscStrcmp(alg,"seqmpi",&flg);CHKERRQ(ierr); 44 if (flg) { 45 ierr = MatMatMultSymbolic_MPIAIJ_MPIAIJ_seqMPI(A,B,fill,C);CHKERRQ(ierr); 46 goto next; 47 } 48 49 #if defined(PETSC_HAVE_HYPRE) 50 ierr = PetscStrcmp(alg,"hypre",&flg);CHKERRQ(ierr); 51 if (flg) { 52 ierr = MatMatMultSymbolic_AIJ_AIJ_wHYPRE(A,B,fill,C);CHKERRQ(ierr); 53 PetscFunctionReturn(0); 54 } 55 #endif 56 SETERRQ(PetscObjectComm((PetscObject)C),PETSC_ERR_SUP,"Mat Product Algorithm is not supported"); 57 58 next: 59 { 60 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 61 Mat_APMPI *ap = c->ap; 62 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatFreeIntermediateDataStructures","Mat");CHKERRQ(ierr); 63 ap->freestruct = PETSC_FALSE; 64 ierr = PetscOptionsBool("-mat_freeintermediatedatastructures","Free intermediate data structures", "MatFreeIntermediateDataStructures",ap->freestruct,&ap->freestruct, NULL);CHKERRQ(ierr); 65 ierr = PetscOptionsEnd();CHKERRQ(ierr); 66 } 67 PetscFunctionReturn(0); 68 } 69 70 PetscErrorCode MatDestroy_MPIAIJ_MatMatMult(Mat A) 71 { 72 PetscErrorCode ierr; 73 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 74 Mat_APMPI *ptap = a->ap; 75 76 PetscFunctionBegin; 77 ierr = PetscFree2(ptap->startsj_s,ptap->startsj_r);CHKERRQ(ierr); 78 ierr = PetscFree(ptap->bufa);CHKERRQ(ierr); 79 ierr = MatDestroy(&ptap->P_loc);CHKERRQ(ierr); 80 ierr = MatDestroy(&ptap->P_oth);CHKERRQ(ierr); 81 ierr = MatDestroy(&ptap->Pt);CHKERRQ(ierr); 82 ierr = PetscFree(ptap->api);CHKERRQ(ierr); 83 ierr = PetscFree(ptap->apj);CHKERRQ(ierr); 84 ierr = PetscFree(ptap->apa);CHKERRQ(ierr); 85 ierr = ptap->destroy(A);CHKERRQ(ierr); 86 ierr = PetscFree(ptap);CHKERRQ(ierr); 87 PetscFunctionReturn(0); 88 } 89 90 PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat A,Mat P,Mat C) 91 { 92 PetscErrorCode ierr; 93 Mat_MPIAIJ *a =(Mat_MPIAIJ*)A->data,*c=(Mat_MPIAIJ*)C->data; 94 Mat_SeqAIJ *ad =(Mat_SeqAIJ*)(a->A)->data,*ao=(Mat_SeqAIJ*)(a->B)->data; 95 Mat_SeqAIJ *cd =(Mat_SeqAIJ*)(c->A)->data,*co=(Mat_SeqAIJ*)(c->B)->data; 96 PetscScalar *cda=cd->a,*coa=co->a; 97 Mat_SeqAIJ *p_loc,*p_oth; 98 PetscScalar *apa,*ca; 99 PetscInt cm =C->rmap->n; 100 Mat_APMPI *ptap=c->ap; 101 PetscInt *api,*apj,*apJ,i,k; 102 PetscInt cstart=C->cmap->rstart; 103 PetscInt cdnz,conz,k0,k1; 104 MPI_Comm comm; 105 PetscMPIInt size; 106 107 PetscFunctionBegin; 108 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 109 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 110 111 if (!ptap->P_oth && size>1) SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"AP cannot be reused. Do not call MatFreeIntermediateDataStructures() or use '-mat_freeintermediatedatastructures'"); 112 113 /* 1) get P_oth = ptap->P_oth and P_loc = ptap->P_loc */ 114 /*-----------------------------------------------------*/ 115 /* update numerical values of P_oth and P_loc */ 116 ierr = MatGetBrowsOfAoCols_MPIAIJ(A,P,MAT_REUSE_MATRIX,&ptap->startsj_s,&ptap->startsj_r,&ptap->bufa,&ptap->P_oth);CHKERRQ(ierr); 117 ierr = MatMPIAIJGetLocalMat(P,MAT_REUSE_MATRIX,&ptap->P_loc);CHKERRQ(ierr); 118 119 /* 2) compute numeric C_loc = A_loc*P = Ad*P_loc + Ao*P_oth */ 120 /*----------------------------------------------------------*/ 121 /* get data from symbolic products */ 122 p_loc = (Mat_SeqAIJ*)(ptap->P_loc)->data; 123 p_oth = NULL; 124 if (size >1) { 125 p_oth = (Mat_SeqAIJ*)(ptap->P_oth)->data; 126 } 127 128 /* get apa for storing dense row A[i,:]*P */ 129 apa = ptap->apa; 130 131 api = ptap->api; 132 apj = ptap->apj; 133 for (i=0; i<cm; i++) { 134 /* compute apa = A[i,:]*P */ 135 AProw_nonscalable(i,ad,ao,p_loc,p_oth,apa); 136 137 /* set values in C */ 138 apJ = apj + api[i]; 139 cdnz = cd->i[i+1] - cd->i[i]; 140 conz = co->i[i+1] - co->i[i]; 141 142 /* 1st off-diagonal part of C */ 143 ca = coa + co->i[i]; 144 k = 0; 145 for (k0=0; k0<conz; k0++) { 146 if (apJ[k] >= cstart) break; 147 ca[k0] = apa[apJ[k]]; 148 apa[apJ[k++]] = 0.0; 149 } 150 151 /* diagonal part of C */ 152 ca = cda + cd->i[i]; 153 for (k1=0; k1<cdnz; k1++) { 154 ca[k1] = apa[apJ[k]]; 155 apa[apJ[k++]] = 0.0; 156 } 157 158 /* 2nd off-diagonal part of C */ 159 ca = coa + co->i[i]; 160 for (; k0<conz; k0++) { 161 ca[k0] = apa[apJ[k]]; 162 apa[apJ[k++]] = 0.0; 163 } 164 } 165 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 166 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 167 168 if (ptap->freestruct) { 169 ierr = MatFreeIntermediateDataStructures(C);CHKERRQ(ierr); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat A,Mat P,PetscReal fill,Mat C) 175 { 176 PetscErrorCode ierr; 177 MPI_Comm comm; 178 PetscMPIInt size; 179 Mat_APMPI *ptap; 180 PetscFreeSpaceList free_space=NULL,current_space=NULL; 181 Mat_MPIAIJ *a =(Mat_MPIAIJ*)A->data,*c; 182 Mat_SeqAIJ *ad =(Mat_SeqAIJ*)(a->A)->data,*ao=(Mat_SeqAIJ*)(a->B)->data,*p_loc,*p_oth; 183 PetscInt *pi_loc,*pj_loc,*pi_oth,*pj_oth,*dnz,*onz; 184 PetscInt *adi=ad->i,*adj=ad->j,*aoi=ao->i,*aoj=ao->j,rstart=A->rmap->rstart; 185 PetscInt *lnk,i,pnz,row,*api,*apj,*Jptr,apnz,nspacedouble=0,j,nzi; 186 PetscInt am=A->rmap->n,pN=P->cmap->N,pn=P->cmap->n,pm=P->rmap->n; 187 PetscBT lnkbt; 188 PetscReal afill; 189 MatType mtype; 190 191 PetscFunctionBegin; 192 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 193 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 194 195 /* create struct Mat_APMPI and attached it to C later */ 196 ierr = PetscNew(&ptap);CHKERRQ(ierr); 197 198 /* get P_oth by taking rows of P (= non-zero cols of local A) from other processors */ 199 ierr = MatGetBrowsOfAoCols_MPIAIJ(A,P,MAT_INITIAL_MATRIX,&ptap->startsj_s,&ptap->startsj_r,&ptap->bufa,&ptap->P_oth);CHKERRQ(ierr); 200 201 /* get P_loc by taking all local rows of P */ 202 ierr = MatMPIAIJGetLocalMat(P,MAT_INITIAL_MATRIX,&ptap->P_loc);CHKERRQ(ierr); 203 204 p_loc = (Mat_SeqAIJ*)(ptap->P_loc)->data; 205 pi_loc = p_loc->i; pj_loc = p_loc->j; 206 if (size > 1) { 207 p_oth = (Mat_SeqAIJ*)(ptap->P_oth)->data; 208 pi_oth = p_oth->i; pj_oth = p_oth->j; 209 } else { 210 p_oth = NULL; 211 pi_oth = NULL; pj_oth = NULL; 212 } 213 214 /* first, compute symbolic AP = A_loc*P = A_diag*P_loc + A_off*P_oth */ 215 /*-------------------------------------------------------------------*/ 216 ierr = PetscMalloc1(am+2,&api);CHKERRQ(ierr); 217 ptap->api = api; 218 api[0] = 0; 219 220 /* create and initialize a linked list */ 221 ierr = PetscLLCondensedCreate(pN,pN,&lnk,&lnkbt);CHKERRQ(ierr); 222 223 /* Initial FreeSpace size is fill*(nnz(A)+nnz(P)) */ 224 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,PetscIntSumTruncate(adi[am],PetscIntSumTruncate(aoi[am],pi_loc[pm]))),&free_space);CHKERRQ(ierr); 225 current_space = free_space; 226 227 ierr = MatPreallocateInitialize(comm,am,pn,dnz,onz);CHKERRQ(ierr); 228 for (i=0; i<am; i++) { 229 /* diagonal portion of A */ 230 nzi = adi[i+1] - adi[i]; 231 for (j=0; j<nzi; j++) { 232 row = *adj++; 233 pnz = pi_loc[row+1] - pi_loc[row]; 234 Jptr = pj_loc + pi_loc[row]; 235 /* add non-zero cols of P into the sorted linked list lnk */ 236 ierr = PetscLLCondensedAddSorted(pnz,Jptr,lnk,lnkbt);CHKERRQ(ierr); 237 } 238 /* off-diagonal portion of A */ 239 nzi = aoi[i+1] - aoi[i]; 240 for (j=0; j<nzi; j++) { 241 row = *aoj++; 242 pnz = pi_oth[row+1] - pi_oth[row]; 243 Jptr = pj_oth + pi_oth[row]; 244 ierr = PetscLLCondensedAddSorted(pnz,Jptr,lnk,lnkbt);CHKERRQ(ierr); 245 } 246 247 apnz = lnk[0]; 248 api[i+1] = api[i] + apnz; 249 250 /* if free space is not available, double the total space in the list */ 251 if (current_space->local_remaining<apnz) { 252 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(apnz,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 253 nspacedouble++; 254 } 255 256 /* Copy data into free space, then initialize lnk */ 257 ierr = PetscLLCondensedClean(pN,apnz,current_space->array,lnk,lnkbt);CHKERRQ(ierr); 258 ierr = MatPreallocateSet(i+rstart,apnz,current_space->array,dnz,onz);CHKERRQ(ierr); 259 260 current_space->array += apnz; 261 current_space->local_used += apnz; 262 current_space->local_remaining -= apnz; 263 } 264 265 /* Allocate space for apj, initialize apj, and */ 266 /* destroy list of free space and other temporary array(s) */ 267 ierr = PetscMalloc1(api[am]+1,&ptap->apj);CHKERRQ(ierr); 268 apj = ptap->apj; 269 ierr = PetscFreeSpaceContiguous(&free_space,ptap->apj);CHKERRQ(ierr); 270 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 271 272 /* malloc apa to store dense row A[i,:]*P */ 273 ierr = PetscCalloc1(pN,&ptap->apa);CHKERRQ(ierr); 274 275 /* set and assemble symbolic parallel matrix C */ 276 /*---------------------------------------------*/ 277 ierr = MatSetSizes(C,am,pn,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 278 ierr = MatSetBlockSizesFromMats(C,A,P);CHKERRQ(ierr); 279 280 ierr = MatGetType(A,&mtype);CHKERRQ(ierr); 281 ierr = MatSetType(C,mtype);CHKERRQ(ierr); 282 ierr = MatMPIAIJSetPreallocation(C,0,dnz,0,onz);CHKERRQ(ierr); 283 284 ierr = MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(C, apj, api);CHKERRQ(ierr); 285 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 286 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 287 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 288 289 ptap->destroy = C->ops->destroy; 290 ptap->duplicate = C->ops->duplicate; 291 C->ops->matmultnumeric = MatMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable; 292 C->ops->productnumeric = MatProductNumeric_AB; 293 C->ops->destroy = MatDestroy_MPIAIJ_MatMatMult; 294 C->ops->freeintermediatedatastructures = MatFreeIntermediateDataStructures_MPIAIJ_AP; 295 296 /* attach the supporting struct to C for reuse */ 297 c = (Mat_MPIAIJ*)C->data; 298 c->ap = ptap; 299 300 /* set MatInfo */ 301 afill = (PetscReal)api[am]/(adi[am]+aoi[am]+pi_loc[pm]+1) + 1.e-5; 302 if (afill < 1.0) afill = 1.0; 303 C->info.mallocs = nspacedouble; 304 C->info.fill_ratio_given = fill; 305 C->info.fill_ratio_needed = afill; 306 307 #if defined(PETSC_USE_INFO) 308 if (api[am]) { 309 ierr = PetscInfo3(C,"Reallocs %D; Fill ratio: given %g needed %g.\n",nspacedouble,(double)fill,(double)afill);CHKERRQ(ierr); 310 ierr = PetscInfo1(C,"Use MatMatMult(A,B,MatReuse,%g,&C) for best performance.;\n",(double)afill);CHKERRQ(ierr); 311 } else { 312 ierr = PetscInfo(C,"Empty matrix product\n");CHKERRQ(ierr); 313 } 314 #endif 315 PetscFunctionReturn(0); 316 } 317 318 /* ------------------------------------------------------- */ 319 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_MPIDense_AB(Mat C) 320 { 321 Mat_Product *product = C->product; 322 Mat A = product->A,B=product->B; 323 324 PetscFunctionBegin; 325 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) 326 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 327 328 C->ops->matmultsymbolic = MatMatMultSymbolic_MPIAIJ_MPIDense; 329 C->ops->productsymbolic = MatProductSymbolic_AB; 330 C->ops->productnumeric = MatProductNumeric_AB; 331 PetscFunctionReturn(0); 332 } 333 /* -------------------------------------------------------------------- */ 334 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_MPIDense_AtB(Mat C) 335 { 336 Mat_Product *product = C->product; 337 Mat A = product->A,B=product->B; 338 339 PetscFunctionBegin; 340 if (A->rmap->rstart != B->rmap->rstart || A->rmap->rend != B->rmap->rend) 341 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->rmap->rstart,A->rmap->rend,B->rmap->rstart,B->rmap->rend); 342 343 C->ops->transposematmultsymbolic = MatTransposeMatMultSymbolic_MPIAIJ_MPIDense; 344 C->ops->productsymbolic = MatProductSymbolic_AtB; 345 PetscFunctionReturn(0); 346 } 347 348 /* --------------------------------------------------------------------- */ 349 PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIAIJ_MPIDense(Mat C) 350 { 351 PetscErrorCode ierr; 352 Mat_Product *product = C->product; 353 354 PetscFunctionBegin; 355 switch (product->type) { 356 case MATPRODUCT_AB: 357 ierr = MatProductSetFromOptions_MPIAIJ_MPIDense_AB(C);CHKERRQ(ierr); 358 break; 359 case MATPRODUCT_AtB: 360 ierr = MatProductSetFromOptions_MPIAIJ_MPIDense_AtB(C);CHKERRQ(ierr); 361 break; 362 default: 363 /* Use MatProduct_Basic() if there is no specific implementation */ 364 C->ops->productsymbolic = MatProductSymbolic_Basic; 365 } 366 PetscFunctionReturn(0); 367 } 368 /* ------------------------------------------------------- */ 369 370 typedef struct { 371 Mat workB,Bb,Cb,workB1,Bb1,Cb1; 372 MPI_Request *rwaits,*swaits; 373 PetscInt numBb; /* num of Bb matrices */ 374 PetscInt nsends,nrecvs; 375 MPI_Datatype *stype,*rtype; 376 } MPIAIJ_MPIDense; 377 378 PetscErrorCode MatMPIAIJ_MPIDenseDestroy(void *ctx) 379 { 380 MPIAIJ_MPIDense *contents = (MPIAIJ_MPIDense*)ctx; 381 PetscErrorCode ierr; 382 PetscInt i; 383 384 PetscFunctionBegin; 385 ierr = MatDestroy(&contents->workB);CHKERRQ(ierr); 386 387 if (contents->numBb) { 388 ierr = MatDestroy(&contents->Bb);CHKERRQ(ierr); 389 ierr = MatDestroy(&contents->Cb);CHKERRQ(ierr); 390 391 ierr = MatDestroy(&contents->workB1);CHKERRQ(ierr); 392 ierr = MatDestroy(&contents->Bb1);CHKERRQ(ierr); 393 ierr = MatDestroy(&contents->Cb1);CHKERRQ(ierr); 394 } 395 for (i=0; i<contents->nsends; i++) { 396 ierr = MPI_Type_free(&contents->stype[i]);CHKERRQ(ierr); 397 } 398 for (i=0; i<contents->nrecvs; i++) { 399 ierr = MPI_Type_free(&contents->rtype[i]);CHKERRQ(ierr); 400 } 401 ierr = PetscFree4(contents->stype,contents->rtype,contents->rwaits,contents->swaits);CHKERRQ(ierr); 402 ierr = PetscFree(contents);CHKERRQ(ierr); 403 PetscFunctionReturn(0); 404 } 405 406 /* 407 This is a "dummy function" that handles the case where matrix C was created as a dense matrix 408 directly by the user and passed to MatMatMult() with the MAT_REUSE_MATRIX option 409 410 It is the same as MatMatMultSymbolic_MPIAIJ_MPIDense() except does not create C 411 */ 412 PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIDense(Mat A,Mat B,Mat C) 413 { 414 PetscBool flg; 415 PetscErrorCode ierr; 416 417 PetscFunctionBegin; 418 ierr = PetscObjectTypeCompare((PetscObject)A,MATNEST,&flg);CHKERRQ(ierr); 419 if (flg) { 420 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 421 ierr = MatMatMultSymbolic_Nest_Dense(A,B,PETSC_DEFAULT,&C);CHKERRQ(ierr); 422 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 423 C->ops->matmultnumeric = MatMatMultNumeric_Nest_Dense; 424 } else { 425 ierr = MatMatMultSymbolic_MPIAIJ_MPIDense(A,B,PETSC_DEFAULT,C);CHKERRQ(ierr); 426 } 427 ierr = (*C->ops->matmultnumeric)(A,B,C);CHKERRQ(ierr); 428 PetscFunctionReturn(0); 429 } 430 431 /* 432 Create Bb, Cb, Bb1 and Cb1 matrices to be used by MatMatMultSymbolic_MPIAIJ_MPIDense(). 433 These matrices are used as wrappers for sub-columns of B and C, thus their own matrix operations are not used. 434 Modified from MatCreateDense(). 435 */ 436 PETSC_STATIC_INLINE PetscErrorCode MatCreateSubMPIDense_private(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt rbs,PetscInt cbs,PetscScalar *data,Mat *A) 437 { 438 PetscErrorCode ierr; 439 440 PetscFunctionBegin; 441 ierr = MatCreate(comm,A);CHKERRQ(ierr); 442 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 443 ierr = MatSetBlockSizes(*A,rbs,cbs);CHKERRQ(ierr); 444 ierr = MatSetType(*A,MATMPIDENSE);CHKERRQ(ierr); 445 ierr = MatMPIDenseSetPreallocation(*A,data);CHKERRQ(ierr); 446 (*A)->assembled = PETSC_TRUE; 447 PetscFunctionReturn(0); 448 } 449 450 PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIDense(Mat A,Mat B,PetscReal fill,Mat C) 451 { 452 PetscErrorCode ierr; 453 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)A->data; 454 Mat_MPIDense *b=(Mat_MPIDense*)B->data; 455 Mat_SeqDense *bseq=(Mat_SeqDense*)(b->A)->data; 456 PetscInt nz=aij->B->cmap->n,nsends,nrecvs,i,nrows_to,j,lda=bseq->lda; 457 PetscContainer container; 458 MPIAIJ_MPIDense *contents; 459 VecScatter ctx=aij->Mvctx; 460 PetscInt Am=A->rmap->n,Bm=B->rmap->n,BN=B->cmap->N,Bbn,Bbn1,bs,nrows_from; 461 MPI_Comm comm; 462 MPI_Datatype type1,*stype,*rtype; 463 const PetscInt *sindices,*sstarts,*rstarts; 464 PetscMPIInt *disp; 465 466 PetscFunctionBegin; 467 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 468 if (!C->preallocated) { 469 ierr = MatSetSizes(C,Am,B->cmap->n,A->rmap->N,BN);CHKERRQ(ierr); 470 ierr = MatSetBlockSizesFromMats(C,A,B);CHKERRQ(ierr); 471 ierr = MatSetType(C,MATMPIDENSE);CHKERRQ(ierr); 472 ierr = MatMPIDenseSetPreallocation(C,NULL);CHKERRQ(ierr); 473 } 474 475 ierr = PetscNew(&contents);CHKERRQ(ierr); 476 contents->numBb = 0; 477 478 ierr = VecScatterGetRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&sindices,NULL,NULL);CHKERRQ(ierr); 479 ierr = VecScatterGetRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL,NULL,NULL);CHKERRQ(ierr); 480 481 /* Create column block of B and C for memory scalability when BN is too large */ 482 /* Estimate Bbn, column size of Bb */ 483 if (nz) { 484 Bbn1 = 2*Am*BN/nz; 485 } else Bbn1 = BN; 486 487 bs = PetscAbs(B->cmap->bs); 488 Bbn1 = Bbn1/bs *bs; /* Bbn1 is a multiple of bs */ 489 if (Bbn1 > BN) Bbn1 = BN; 490 ierr = MPI_Allreduce(&Bbn1,&Bbn,1,MPIU_INT,MPI_MAX,comm);CHKERRQ(ierr); 491 492 /* Enable runtime option for Bbn */ 493 ierr = PetscOptionsBegin(comm,((PetscObject)C)->prefix,"MatMatMult","Mat");CHKERRQ(ierr); 494 ierr = PetscOptionsInt("-matmatmult_Bbn","Number of columns in Bb","MatMatMult",Bbn,&Bbn,NULL);CHKERRQ(ierr); 495 if (Bbn > BN) SETERRQ2(comm,PETSC_ERR_ARG_SIZ,"Bbn=%D cannot be larger than %D, column size of B",Bbn,BN); 496 ierr = PetscOptionsEnd();CHKERRQ(ierr); 497 498 if (Bbn < BN) { 499 contents->numBb = BN/Bbn; 500 Bbn1 = BN - contents->numBb*Bbn; 501 } 502 503 if (contents->numBb) { 504 PetscScalar data[1]; /* fake array for Bb and Cb */ 505 ierr = PetscInfo3(C,"use Bb, BN=%D, Bbn=%D; numBb=%D\n",BN,Bbn,contents->numBb);CHKERRQ(ierr); 506 ierr = MatCreateSubMPIDense_private(comm,B->rmap->n,PETSC_DECIDE,A->rmap->N,Bbn,B->rmap->bs,B->cmap->bs,data,&contents->Bb);CHKERRQ(ierr); 507 ierr = MatCreateSubMPIDense_private(comm,Am,PETSC_DECIDE,A->rmap->N,Bbn,C->rmap->bs,C->cmap->bs,data,&contents->Cb);CHKERRQ(ierr); 508 509 if (Bbn1) { /* Create Bb1 and Cb1 for the remaining columns */ 510 ierr = PetscInfo2(C,"use Bb1, BN=%D, Bbn1=%D\n",BN,Bbn1);CHKERRQ(ierr); 511 ierr = MatCreateSubMPIDense_private(comm,B->rmap->n,PETSC_DECIDE,A->rmap->N,Bbn1,B->rmap->bs,B->cmap->bs,data,&contents->Bb1);CHKERRQ(ierr); 512 ierr = MatCreateSubMPIDense_private(comm,Am,PETSC_DECIDE,A->rmap->N,Bbn1,C->rmap->bs,C->cmap->bs,data,&contents->Cb1);CHKERRQ(ierr); 513 514 /* Create work matrix used to store off processor rows of B needed for local product */ 515 ierr = MatCreateSeqDense(PETSC_COMM_SELF,nz,Bbn1,NULL,&contents->workB1);CHKERRQ(ierr); 516 } 517 } 518 519 /* Create work matrix used to store off processor rows of B needed for local product */ 520 ierr = MatCreateSeqDense(PETSC_COMM_SELF,nz,Bbn,NULL,&contents->workB);CHKERRQ(ierr); 521 522 /* Use MPI derived data type to reduce memory required by the send/recv buffers */ 523 ierr = PetscMalloc4(nsends,&stype,nrecvs,&rtype,nrecvs,&contents->rwaits,nsends,&contents->swaits);CHKERRQ(ierr); 524 contents->stype = stype; 525 contents->nsends = nsends; 526 527 contents->rtype = rtype; 528 contents->nrecvs = nrecvs; 529 530 ierr = PetscMalloc1(Bm+1,&disp);CHKERRQ(ierr); 531 for (i=0; i<nsends; i++) { 532 nrows_to = sstarts[i+1]-sstarts[i]; 533 for (j=0; j<nrows_to; j++){ 534 disp[j] = sindices[sstarts[i]+j]; /* rowB to be sent */ 535 } 536 ierr = MPI_Type_create_indexed_block(nrows_to,1,(const PetscMPIInt *)disp,MPIU_SCALAR,&type1);CHKERRQ(ierr); 537 538 ierr = MPI_Type_create_resized(type1,0,lda*sizeof(PetscScalar),&stype[i]);CHKERRQ(ierr); 539 ierr = MPI_Type_commit(&stype[i]);CHKERRQ(ierr); 540 ierr = MPI_Type_free(&type1);CHKERRQ(ierr); 541 } 542 543 for (i=0; i<nrecvs; i++) { 544 /* received values from a process form a (nrows_from x Bbn) row block in workB (column-wise) */ 545 nrows_from = rstarts[i+1]-rstarts[i]; 546 disp[0] = 0; 547 ierr = MPI_Type_create_indexed_block(1, nrows_from, (const PetscMPIInt *)disp, MPIU_SCALAR, &type1);CHKERRQ(ierr); 548 ierr = MPI_Type_create_resized(type1, 0, nz*sizeof(PetscScalar), &rtype[i]);CHKERRQ(ierr); 549 ierr = MPI_Type_commit(&rtype[i]);CHKERRQ(ierr); 550 ierr = MPI_Type_free(&type1);CHKERRQ(ierr); 551 } 552 553 ierr = PetscFree(disp);CHKERRQ(ierr); 554 ierr = VecScatterRestoreRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&sindices,NULL,NULL);CHKERRQ(ierr); 555 ierr = VecScatterRestoreRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL,NULL,NULL);CHKERRQ(ierr); 556 557 ierr = PetscContainerCreate(comm,&container);CHKERRQ(ierr); 558 ierr = PetscContainerSetPointer(container,contents);CHKERRQ(ierr); 559 ierr = PetscContainerSetUserDestroy(container,MatMPIAIJ_MPIDenseDestroy);CHKERRQ(ierr); 560 ierr = PetscObjectCompose((PetscObject)C,"workB",(PetscObject)container);CHKERRQ(ierr); 561 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 562 ierr = MatSetOption(C,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 563 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 564 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 565 C->ops->matmultnumeric = MatMatMultNumeric_MPIAIJ_MPIDense; 566 PetscFunctionReturn(0); 567 } 568 569 extern PetscErrorCode MatMatMultNumericAdd_SeqAIJ_SeqDense(Mat,Mat,Mat); 570 /* 571 Performs an efficient scatter on the rows of B needed by this process; this is 572 a modification of the VecScatterBegin_() routines. 573 574 Input: Bbidx = 0: B = Bb 575 = 1: B = Bb1, see MatMatMultSymbolic_MPIAIJ_MPIDense() 576 */ 577 PetscErrorCode MatMPIDenseScatter(Mat A,Mat B,PetscInt Bbidx,Mat C,Mat *outworkB) 578 { 579 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 580 PetscErrorCode ierr; 581 const PetscScalar *b; 582 PetscScalar *rvalues; 583 VecScatter ctx = aij->Mvctx; 584 const PetscInt *sindices,*sstarts,*rstarts; 585 const PetscMPIInt *sprocs,*rprocs; 586 PetscInt i,nsends,nrecvs,nrecvs2; 587 MPI_Request *swaits,*rwaits; 588 MPI_Comm comm; 589 PetscMPIInt tag=((PetscObject)ctx)->tag,ncols=B->cmap->N,nrows=aij->B->cmap->n,imdex,nsends_mpi,nrecvs_mpi; 590 MPI_Status status; 591 MPIAIJ_MPIDense *contents; 592 PetscContainer container; 593 Mat workB; 594 MPI_Datatype *stype,*rtype; 595 596 PetscFunctionBegin; 597 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 598 ierr = PetscObjectQuery((PetscObject)C,"workB",(PetscObject*)&container);CHKERRQ(ierr); 599 if (!container) SETERRQ(comm,PETSC_ERR_PLIB,"Container does not exist"); 600 ierr = PetscContainerGetPointer(container,(void**)&contents);CHKERRQ(ierr); 601 602 ierr = VecScatterGetRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&sindices,&sprocs,NULL/*bs*/);CHKERRQ(ierr); 603 ierr = VecScatterGetRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL,&rprocs,NULL/*bs*/);CHKERRQ(ierr); 604 ierr = PetscMPIIntCast(nsends,&nsends_mpi);CHKERRQ(ierr); 605 ierr = PetscMPIIntCast(nrecvs,&nrecvs_mpi);CHKERRQ(ierr); 606 if (Bbidx == 0) { 607 workB = *outworkB = contents->workB; 608 } else { 609 workB = *outworkB = contents->workB1; 610 } 611 if (nrows != workB->rmap->n) SETERRQ2(comm,PETSC_ERR_PLIB,"Number of rows of workB %D not equal to columns of aij->B %D",workB->cmap->n,nrows); 612 swaits = contents->swaits; 613 rwaits = contents->rwaits; 614 615 ierr = MatDenseGetArrayRead(B,&b);CHKERRQ(ierr); 616 ierr = MatDenseGetArray(workB,&rvalues);CHKERRQ(ierr); 617 618 /* Post recv, use MPI derived data type to save memory */ 619 rtype = contents->rtype; 620 for (i=0; i<nrecvs; i++) { 621 ierr = MPI_Irecv(rvalues+(rstarts[i]-rstarts[0]),ncols,rtype[i],rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 622 } 623 624 stype = contents->stype; 625 for (i=0; i<nsends; i++) { 626 ierr = MPI_Isend(b,ncols,stype[i],sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 627 } 628 629 nrecvs2 = nrecvs; 630 while (nrecvs2) { 631 ierr = MPI_Waitany(nrecvs_mpi,rwaits,&imdex,&status);CHKERRQ(ierr); 632 nrecvs2--; 633 } 634 if (nsends) {ierr = MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);CHKERRQ(ierr);} 635 636 ierr = VecScatterRestoreRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&sindices,&sprocs,NULL);CHKERRQ(ierr); 637 ierr = VecScatterRestoreRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL,&rprocs,NULL);CHKERRQ(ierr); 638 ierr = MatDenseRestoreArrayRead(B,&b);CHKERRQ(ierr); 639 ierr = MatDenseRestoreArray(workB,&rvalues);CHKERRQ(ierr); 640 ierr = MatAssemblyBegin(workB,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 641 ierr = MatAssemblyEnd(workB,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 642 PetscFunctionReturn(0); 643 } 644 645 /* 646 Compute Cb = A*Bb 647 */ 648 PETSC_STATIC_INLINE PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIDense_private(Mat A,Mat Bb,PetscInt Bbidx,PetscInt start,Mat C,const PetscScalar *barray,PetscScalar *carray,Mat Cb) 649 { 650 PetscErrorCode ierr; 651 PetscInt start1; 652 Mat workB; 653 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 654 Mat_MPIDense *cbdense = (Mat_MPIDense*)Cb->data; 655 656 PetscFunctionBegin; 657 /* Place barray to Bb */ 658 start1 = start*Bb->rmap->n; 659 ierr = MatDensePlaceArray(Bb,barray+start1);CHKERRQ(ierr); 660 661 /* get off processor parts of Bb needed to complete Cb=A*Bb */ 662 ierr = MatMPIDenseScatter(A,Bb,Bbidx,C,&workB);CHKERRQ(ierr); 663 ierr = MatDenseResetArray(Bb);CHKERRQ(ierr); 664 665 /* off-diagonal block of A times nonlocal rows of Bb */ 666 /* Place carray to Cb */ 667 start1 = start*Cb->rmap->n; 668 ierr = MatDensePlaceArray(Cb,carray+start1);CHKERRQ(ierr); 669 ierr = MatMatMultNumericAdd_SeqAIJ_SeqDense(aij->B,workB,cbdense->A);CHKERRQ(ierr); 670 ierr = MatDenseResetArray(Cb);CHKERRQ(ierr); 671 PetscFunctionReturn(0); 672 } 673 674 PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIDense(Mat A,Mat B,Mat C) 675 { 676 PetscErrorCode ierr; 677 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 678 Mat_MPIDense *bdense = (Mat_MPIDense*)B->data; 679 Mat_MPIDense *cdense = (Mat_MPIDense*)C->data; 680 Mat workB; 681 MPIAIJ_MPIDense *contents; 682 PetscContainer container; 683 MPI_Comm comm; 684 PetscInt numBb; 685 686 PetscFunctionBegin; 687 /* diagonal block of A times all local rows of B*/ 688 ierr = MatMatMultNumeric_SeqAIJ_SeqDense(aij->A,bdense->A,cdense->A);CHKERRQ(ierr); 689 690 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 691 ierr = PetscObjectQuery((PetscObject)C,"workB",(PetscObject*)&container);CHKERRQ(ierr); 692 if (!container) SETERRQ(comm,PETSC_ERR_PLIB,"Container does not exist"); 693 ierr = PetscContainerGetPointer(container,(void**)&contents);CHKERRQ(ierr); 694 numBb = contents->numBb; 695 696 if (!numBb) { 697 /* get off processor parts of B needed to complete C=A*B */ 698 ierr = MatMPIDenseScatter(A,B,0,C,&workB);CHKERRQ(ierr); 699 700 /* off-diagonal block of A times nonlocal rows of B */ 701 ierr = MatMatMultNumericAdd_SeqAIJ_SeqDense(aij->B,workB,cdense->A);CHKERRQ(ierr); 702 703 } else { 704 const PetscScalar *barray; 705 PetscScalar *carray; 706 Mat Bb=contents->Bb,Cb=contents->Cb; 707 PetscInt BbN=Bb->cmap->N,start,i; 708 709 ierr = MatDenseGetArrayRead(B,&barray);CHKERRQ(ierr); 710 ierr = MatDenseGetArray(C,&carray);CHKERRQ(ierr); 711 for (i=0; i<numBb; i++) { 712 start = i*BbN; 713 ierr = MatMatMultNumeric_MPIAIJ_MPIDense_private(A,Bb,0,start,C,barray,carray,Cb);CHKERRQ(ierr); 714 } 715 716 if (contents->Bb1) { 717 Bb = contents->Bb1; Cb = contents->Cb1; 718 start = i*BbN; 719 ierr = MatMatMultNumeric_MPIAIJ_MPIDense_private(A,Bb,1,start,C,barray,carray,Cb);CHKERRQ(ierr); 720 } 721 ierr = MatDenseRestoreArrayRead(B,&barray);CHKERRQ(ierr); 722 ierr = MatDenseRestoreArray(C,&carray);CHKERRQ(ierr); 723 } 724 PetscFunctionReturn(0); 725 } 726 727 PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ(Mat A,Mat P,Mat C) 728 { 729 PetscErrorCode ierr; 730 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data,*c=(Mat_MPIAIJ*)C->data; 731 Mat_SeqAIJ *ad = (Mat_SeqAIJ*)(a->A)->data,*ao=(Mat_SeqAIJ*)(a->B)->data; 732 Mat_SeqAIJ *cd = (Mat_SeqAIJ*)(c->A)->data,*co=(Mat_SeqAIJ*)(c->B)->data; 733 PetscInt *adi = ad->i,*adj,*aoi=ao->i,*aoj; 734 PetscScalar *ada,*aoa,*cda=cd->a,*coa=co->a; 735 Mat_SeqAIJ *p_loc,*p_oth; 736 PetscInt *pi_loc,*pj_loc,*pi_oth,*pj_oth,*pj; 737 PetscScalar *pa_loc,*pa_oth,*pa,valtmp,*ca; 738 PetscInt cm = C->rmap->n,anz,pnz; 739 Mat_APMPI *ptap = c->ap; 740 PetscScalar *apa_sparse; 741 PetscInt *api,*apj,*apJ,i,j,k,row; 742 PetscInt cstart = C->cmap->rstart; 743 PetscInt cdnz,conz,k0,k1,nextp; 744 MPI_Comm comm; 745 PetscMPIInt size; 746 747 PetscFunctionBegin; 748 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 749 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 750 751 if (!ptap->P_oth && size>1) { 752 SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"AP cannot be reused. Do not call MatFreeIntermediateDataStructures() or use '-mat_freeintermediatedatastructures'"); 753 } 754 apa_sparse = ptap->apa; 755 756 /* 1) get P_oth = ptap->P_oth and P_loc = ptap->P_loc */ 757 /*-----------------------------------------------------*/ 758 /* update numerical values of P_oth and P_loc */ 759 ierr = MatGetBrowsOfAoCols_MPIAIJ(A,P,MAT_REUSE_MATRIX,&ptap->startsj_s,&ptap->startsj_r,&ptap->bufa,&ptap->P_oth);CHKERRQ(ierr); 760 ierr = MatMPIAIJGetLocalMat(P,MAT_REUSE_MATRIX,&ptap->P_loc);CHKERRQ(ierr); 761 762 /* 2) compute numeric C_loc = A_loc*P = Ad*P_loc + Ao*P_oth */ 763 /*----------------------------------------------------------*/ 764 /* get data from symbolic products */ 765 p_loc = (Mat_SeqAIJ*)(ptap->P_loc)->data; 766 pi_loc = p_loc->i; pj_loc = p_loc->j; pa_loc = p_loc->a; 767 if (size >1) { 768 p_oth = (Mat_SeqAIJ*)(ptap->P_oth)->data; 769 pi_oth = p_oth->i; pj_oth = p_oth->j; pa_oth = p_oth->a; 770 } else { 771 p_oth = NULL; pi_oth = NULL; pj_oth = NULL; pa_oth = NULL; 772 } 773 774 api = ptap->api; 775 apj = ptap->apj; 776 for (i=0; i<cm; i++) { 777 apJ = apj + api[i]; 778 779 /* diagonal portion of A */ 780 anz = adi[i+1] - adi[i]; 781 adj = ad->j + adi[i]; 782 ada = ad->a + adi[i]; 783 for (j=0; j<anz; j++) { 784 row = adj[j]; 785 pnz = pi_loc[row+1] - pi_loc[row]; 786 pj = pj_loc + pi_loc[row]; 787 pa = pa_loc + pi_loc[row]; 788 /* perform sparse axpy */ 789 valtmp = ada[j]; 790 nextp = 0; 791 for (k=0; nextp<pnz; k++) { 792 if (apJ[k] == pj[nextp]) { /* column of AP == column of P */ 793 apa_sparse[k] += valtmp*pa[nextp++]; 794 } 795 } 796 ierr = PetscLogFlops(2.0*pnz);CHKERRQ(ierr); 797 } 798 799 /* off-diagonal portion of A */ 800 anz = aoi[i+1] - aoi[i]; 801 aoj = ao->j + aoi[i]; 802 aoa = ao->a + aoi[i]; 803 for (j=0; j<anz; j++) { 804 row = aoj[j]; 805 pnz = pi_oth[row+1] - pi_oth[row]; 806 pj = pj_oth + pi_oth[row]; 807 pa = pa_oth + pi_oth[row]; 808 /* perform sparse axpy */ 809 valtmp = aoa[j]; 810 nextp = 0; 811 for (k=0; nextp<pnz; k++) { 812 if (apJ[k] == pj[nextp]) { /* column of AP == column of P */ 813 apa_sparse[k] += valtmp*pa[nextp++]; 814 } 815 } 816 ierr = PetscLogFlops(2.0*pnz);CHKERRQ(ierr); 817 } 818 819 /* set values in C */ 820 cdnz = cd->i[i+1] - cd->i[i]; 821 conz = co->i[i+1] - co->i[i]; 822 823 /* 1st off-diagonal part of C */ 824 ca = coa + co->i[i]; 825 k = 0; 826 for (k0=0; k0<conz; k0++) { 827 if (apJ[k] >= cstart) break; 828 ca[k0] = apa_sparse[k]; 829 apa_sparse[k] = 0.0; 830 k++; 831 } 832 833 /* diagonal part of C */ 834 ca = cda + cd->i[i]; 835 for (k1=0; k1<cdnz; k1++) { 836 ca[k1] = apa_sparse[k]; 837 apa_sparse[k] = 0.0; 838 k++; 839 } 840 841 /* 2nd off-diagonal part of C */ 842 ca = coa + co->i[i]; 843 for (; k0<conz; k0++) { 844 ca[k0] = apa_sparse[k]; 845 apa_sparse[k] = 0.0; 846 k++; 847 } 848 } 849 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 850 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 851 852 if (ptap->freestruct) { 853 ierr = MatFreeIntermediateDataStructures(C);CHKERRQ(ierr); 854 } 855 PetscFunctionReturn(0); 856 } 857 858 /* same as MatMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(), except using LLCondensed to avoid O(BN) memory requirement */ 859 PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ(Mat A,Mat P,PetscReal fill,Mat C) 860 { 861 PetscErrorCode ierr; 862 MPI_Comm comm; 863 PetscMPIInt size; 864 Mat_APMPI *ptap; 865 PetscFreeSpaceList free_space = NULL,current_space=NULL; 866 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data,*c; 867 Mat_SeqAIJ *ad = (Mat_SeqAIJ*)(a->A)->data,*ao=(Mat_SeqAIJ*)(a->B)->data,*p_loc,*p_oth; 868 PetscInt *pi_loc,*pj_loc,*pi_oth,*pj_oth,*dnz,*onz; 869 PetscInt *adi=ad->i,*adj=ad->j,*aoi=ao->i,*aoj=ao->j,rstart=A->rmap->rstart; 870 PetscInt i,pnz,row,*api,*apj,*Jptr,apnz,nspacedouble=0,j,nzi,*lnk,apnz_max=0; 871 PetscInt am=A->rmap->n,pn=P->cmap->n,pm=P->rmap->n,lsize=pn+20; 872 PetscReal afill; 873 MatType mtype; 874 875 PetscFunctionBegin; 876 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 877 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 878 879 /* create struct Mat_APMPI and attached it to C later */ 880 ierr = PetscNew(&ptap);CHKERRQ(ierr); 881 882 /* get P_oth by taking rows of P (= non-zero cols of local A) from other processors */ 883 ierr = MatGetBrowsOfAoCols_MPIAIJ(A,P,MAT_INITIAL_MATRIX,&ptap->startsj_s,&ptap->startsj_r,&ptap->bufa,&ptap->P_oth);CHKERRQ(ierr); 884 885 /* get P_loc by taking all local rows of P */ 886 ierr = MatMPIAIJGetLocalMat(P,MAT_INITIAL_MATRIX,&ptap->P_loc);CHKERRQ(ierr); 887 888 p_loc = (Mat_SeqAIJ*)(ptap->P_loc)->data; 889 pi_loc = p_loc->i; pj_loc = p_loc->j; 890 if (size > 1) { 891 p_oth = (Mat_SeqAIJ*)(ptap->P_oth)->data; 892 pi_oth = p_oth->i; pj_oth = p_oth->j; 893 } else { 894 p_oth = NULL; 895 pi_oth = NULL; pj_oth = NULL; 896 } 897 898 /* first, compute symbolic AP = A_loc*P = A_diag*P_loc + A_off*P_oth */ 899 /*-------------------------------------------------------------------*/ 900 ierr = PetscMalloc1(am+2,&api);CHKERRQ(ierr); 901 ptap->api = api; 902 api[0] = 0; 903 904 ierr = PetscLLCondensedCreate_Scalable(lsize,&lnk);CHKERRQ(ierr); 905 906 /* Initial FreeSpace size is fill*(nnz(A)+nnz(P)) */ 907 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,PetscIntSumTruncate(adi[am],PetscIntSumTruncate(aoi[am],pi_loc[pm]))),&free_space);CHKERRQ(ierr); 908 current_space = free_space; 909 ierr = MatPreallocateInitialize(comm,am,pn,dnz,onz);CHKERRQ(ierr); 910 for (i=0; i<am; i++) { 911 /* diagonal portion of A */ 912 nzi = adi[i+1] - adi[i]; 913 for (j=0; j<nzi; j++) { 914 row = *adj++; 915 pnz = pi_loc[row+1] - pi_loc[row]; 916 Jptr = pj_loc + pi_loc[row]; 917 /* Expand list if it is not long enough */ 918 if (pnz+apnz_max > lsize) { 919 lsize = pnz+apnz_max; 920 ierr = PetscLLCondensedExpand_Scalable(lsize, &lnk);CHKERRQ(ierr); 921 } 922 /* add non-zero cols of P into the sorted linked list lnk */ 923 ierr = PetscLLCondensedAddSorted_Scalable(pnz,Jptr,lnk);CHKERRQ(ierr); 924 apnz = *lnk; /* The first element in the list is the number of items in the list */ 925 api[i+1] = api[i] + apnz; 926 if (apnz > apnz_max) apnz_max = apnz; 927 } 928 /* off-diagonal portion of A */ 929 nzi = aoi[i+1] - aoi[i]; 930 for (j=0; j<nzi; j++) { 931 row = *aoj++; 932 pnz = pi_oth[row+1] - pi_oth[row]; 933 Jptr = pj_oth + pi_oth[row]; 934 /* Expand list if it is not long enough */ 935 if (pnz+apnz_max > lsize) { 936 lsize = pnz + apnz_max; 937 ierr = PetscLLCondensedExpand_Scalable(lsize, &lnk);CHKERRQ(ierr); 938 } 939 /* add non-zero cols of P into the sorted linked list lnk */ 940 ierr = PetscLLCondensedAddSorted_Scalable(pnz,Jptr,lnk);CHKERRQ(ierr); 941 apnz = *lnk; /* The first element in the list is the number of items in the list */ 942 api[i+1] = api[i] + apnz; 943 if (apnz > apnz_max) apnz_max = apnz; 944 } 945 apnz = *lnk; 946 api[i+1] = api[i] + apnz; 947 if (apnz > apnz_max) apnz_max = apnz; 948 949 /* if free space is not available, double the total space in the list */ 950 if (current_space->local_remaining<apnz) { 951 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(apnz,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 952 nspacedouble++; 953 } 954 955 /* Copy data into free space, then initialize lnk */ 956 ierr = PetscLLCondensedClean_Scalable(apnz,current_space->array,lnk);CHKERRQ(ierr); 957 ierr = MatPreallocateSet(i+rstart,apnz,current_space->array,dnz,onz);CHKERRQ(ierr); 958 959 current_space->array += apnz; 960 current_space->local_used += apnz; 961 current_space->local_remaining -= apnz; 962 } 963 964 /* Allocate space for apj, initialize apj, and */ 965 /* destroy list of free space and other temporary array(s) */ 966 ierr = PetscMalloc1(api[am]+1,&ptap->apj);CHKERRQ(ierr); 967 apj = ptap->apj; 968 ierr = PetscFreeSpaceContiguous(&free_space,ptap->apj);CHKERRQ(ierr); 969 ierr = PetscLLCondensedDestroy_Scalable(lnk);CHKERRQ(ierr); 970 971 /* create and assemble symbolic parallel matrix C */ 972 /*----------------------------------------------------*/ 973 ierr = MatSetSizes(C,am,pn,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 974 ierr = MatSetBlockSizesFromMats(C,A,P);CHKERRQ(ierr); 975 ierr = MatGetType(A,&mtype);CHKERRQ(ierr); 976 ierr = MatSetType(C,mtype);CHKERRQ(ierr); 977 ierr = MatMPIAIJSetPreallocation(C,0,dnz,0,onz);CHKERRQ(ierr); 978 979 /* malloc apa for assembly C */ 980 ierr = PetscCalloc1(apnz_max,&ptap->apa);CHKERRQ(ierr); 981 982 ierr = MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(C, apj, api);CHKERRQ(ierr); 983 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 984 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 985 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 986 987 ptap->destroy = C->ops->destroy; 988 ptap->duplicate = C->ops->duplicate; 989 C->ops->matmultnumeric = MatMatMultNumeric_MPIAIJ_MPIAIJ; 990 C->ops->productnumeric = MatProductNumeric_AB; 991 C->ops->destroy = MatDestroy_MPIAIJ_MatMatMult; 992 C->ops->freeintermediatedatastructures = MatFreeIntermediateDataStructures_MPIAIJ_AP; 993 994 /* attach the supporting struct to C for reuse */ 995 c = (Mat_MPIAIJ*)C->data; 996 c->ap = ptap; 997 998 /* set MatInfo */ 999 afill = (PetscReal)api[am]/(adi[am]+aoi[am]+pi_loc[pm]+1) + 1.e-5; 1000 if (afill < 1.0) afill = 1.0; 1001 C->info.mallocs = nspacedouble; 1002 C->info.fill_ratio_given = fill; 1003 C->info.fill_ratio_needed = afill; 1004 1005 #if defined(PETSC_USE_INFO) 1006 if (api[am]) { 1007 ierr = PetscInfo3(C,"Reallocs %D; Fill ratio: given %g needed %g.\n",nspacedouble,(double)fill,(double)afill);CHKERRQ(ierr); 1008 ierr = PetscInfo1(C,"Use MatMatMult(A,B,MatReuse,%g,&C) for best performance.;\n",(double)afill);CHKERRQ(ierr); 1009 } else { 1010 ierr = PetscInfo(C,"Empty matrix product\n");CHKERRQ(ierr); 1011 } 1012 #endif 1013 PetscFunctionReturn(0); 1014 } 1015 1016 /* This function is needed for the seqMPI matrix-matrix multiplication. */ 1017 /* Three input arrays are merged to one output array. The size of the */ 1018 /* output array is also output. Duplicate entries only show up once. */ 1019 static void Merge3SortedArrays(PetscInt size1, PetscInt *in1, 1020 PetscInt size2, PetscInt *in2, 1021 PetscInt size3, PetscInt *in3, 1022 PetscInt *size4, PetscInt *out) 1023 { 1024 int i = 0, j = 0, k = 0, l = 0; 1025 1026 /* Traverse all three arrays */ 1027 while (i<size1 && j<size2 && k<size3) { 1028 if (in1[i] < in2[j] && in1[i] < in3[k]) { 1029 out[l++] = in1[i++]; 1030 } 1031 else if(in2[j] < in1[i] && in2[j] < in3[k]) { 1032 out[l++] = in2[j++]; 1033 } 1034 else if(in3[k] < in1[i] && in3[k] < in2[j]) { 1035 out[l++] = in3[k++]; 1036 } 1037 else if(in1[i] == in2[j] && in1[i] < in3[k]) { 1038 out[l++] = in1[i]; 1039 i++, j++; 1040 } 1041 else if(in1[i] == in3[k] && in1[i] < in2[j]) { 1042 out[l++] = in1[i]; 1043 i++, k++; 1044 } 1045 else if(in3[k] == in2[j] && in2[j] < in1[i]) { 1046 out[l++] = in2[j]; 1047 k++, j++; 1048 } 1049 else if(in1[i] == in2[j] && in1[i] == in3[k]) { 1050 out[l++] = in1[i]; 1051 i++, j++, k++; 1052 } 1053 } 1054 1055 /* Traverse two remaining arrays */ 1056 while (i<size1 && j<size2) { 1057 if (in1[i] < in2[j]) { 1058 out[l++] = in1[i++]; 1059 } 1060 else if(in1[i] > in2[j]) { 1061 out[l++] = in2[j++]; 1062 } 1063 else { 1064 out[l++] = in1[i]; 1065 i++, j++; 1066 } 1067 } 1068 1069 while (i<size1 && k<size3) { 1070 if (in1[i] < in3[k]) { 1071 out[l++] = in1[i++]; 1072 } 1073 else if(in1[i] > in3[k]) { 1074 out[l++] = in3[k++]; 1075 } 1076 else { 1077 out[l++] = in1[i]; 1078 i++, k++; 1079 } 1080 } 1081 1082 while (k<size3 && j<size2) { 1083 if (in3[k] < in2[j]) { 1084 out[l++] = in3[k++]; 1085 } 1086 else if(in3[k] > in2[j]) { 1087 out[l++] = in2[j++]; 1088 } 1089 else { 1090 out[l++] = in3[k]; 1091 k++, j++; 1092 } 1093 } 1094 1095 /* Traverse one remaining array */ 1096 while (i<size1) out[l++] = in1[i++]; 1097 while (j<size2) out[l++] = in2[j++]; 1098 while (k<size3) out[l++] = in3[k++]; 1099 1100 *size4 = l; 1101 } 1102 1103 /* This matrix-matrix multiplication algorithm divides the multiplication into three multiplications and */ 1104 /* adds up the products. Two of these three multiplications are performed with existing (sequential) */ 1105 /* matrix-matrix multiplications. */ 1106 PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_seqMPI(Mat A, Mat P, PetscReal fill, Mat C) 1107 { 1108 PetscErrorCode ierr; 1109 MPI_Comm comm; 1110 PetscMPIInt size; 1111 Mat_APMPI *ptap; 1112 PetscFreeSpaceList free_space_diag=NULL, current_space=NULL; 1113 Mat_MPIAIJ *a =(Mat_MPIAIJ*)A->data; 1114 Mat_SeqAIJ *ad =(Mat_SeqAIJ*)(a->A)->data,*ao=(Mat_SeqAIJ*)(a->B)->data,*p_loc; 1115 Mat_MPIAIJ *p =(Mat_MPIAIJ*)P->data; 1116 Mat_MPIAIJ *c; 1117 Mat_SeqAIJ *adpd_seq, *p_off, *aopoth_seq; 1118 PetscInt adponz, adpdnz; 1119 PetscInt *pi_loc,*dnz,*onz; 1120 PetscInt *adi=ad->i,*adj=ad->j,*aoi=ao->i,rstart=A->rmap->rstart; 1121 PetscInt *lnk,i, i1=0,pnz,row,*adpoi,*adpoj, *api, *adpoJ, *aopJ, *apJ,*Jptr, aopnz, nspacedouble=0,j,nzi, 1122 *apj,apnz, *adpdi, *adpdj, *adpdJ, *poff_i, *poff_j, *j_temp, *aopothi, *aopothj; 1123 PetscInt am=A->rmap->n,pN=P->cmap->N,pn=P->cmap->n,pm=P->rmap->n, p_colstart, p_colend; 1124 PetscBT lnkbt; 1125 PetscReal afill; 1126 PetscMPIInt rank; 1127 Mat adpd, aopoth; 1128 MatType mtype; 1129 const char *prefix; 1130 1131 PetscFunctionBegin; 1132 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1133 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1134 ierr = MPI_Comm_rank(comm, &rank);CHKERRQ(ierr); 1135 ierr = MatGetOwnershipRangeColumn(P, &p_colstart, &p_colend); CHKERRQ(ierr); 1136 1137 /* create struct Mat_APMPI and attached it to C later */ 1138 ierr = PetscNew(&ptap);CHKERRQ(ierr); 1139 1140 /* get P_oth by taking rows of P (= non-zero cols of local A) from other processors */ 1141 ierr = MatGetBrowsOfAoCols_MPIAIJ(A,P,MAT_INITIAL_MATRIX,&ptap->startsj_s,&ptap->startsj_r,&ptap->bufa,&ptap->P_oth);CHKERRQ(ierr); 1142 1143 /* get P_loc by taking all local rows of P */ 1144 ierr = MatMPIAIJGetLocalMat(P,MAT_INITIAL_MATRIX,&ptap->P_loc);CHKERRQ(ierr); 1145 1146 1147 p_loc = (Mat_SeqAIJ*)(ptap->P_loc)->data; 1148 pi_loc = p_loc->i; 1149 1150 /* Allocate memory for the i arrays of the matrices A*P, A_diag*P_off and A_offd * P */ 1151 ierr = PetscMalloc1(am+2,&api);CHKERRQ(ierr); 1152 ierr = PetscMalloc1(am+2,&adpoi);CHKERRQ(ierr); 1153 1154 adpoi[0] = 0; 1155 ptap->api = api; 1156 api[0] = 0; 1157 1158 /* create and initialize a linked list, will be used for both A_diag * P_loc_off and A_offd * P_oth */ 1159 ierr = PetscLLCondensedCreate(pN,pN,&lnk,&lnkbt);CHKERRQ(ierr); 1160 ierr = MatPreallocateInitialize(comm,am,pn,dnz,onz);CHKERRQ(ierr); 1161 1162 /* Symbolic calc of A_loc_diag * P_loc_diag */ 1163 ierr = MatGetOptionsPrefix(A,&prefix);CHKERRQ(ierr); 1164 ierr = MatProductCreate(a->A,p->A,NULL,&adpd);CHKERRQ(ierr); 1165 ierr = MatGetOptionsPrefix(A,&prefix);CHKERRQ(ierr); 1166 ierr = MatSetOptionsPrefix(adpd,prefix);CHKERRQ(ierr); 1167 ierr = MatAppendOptionsPrefix(adpd,"inner_diag_");CHKERRQ(ierr); 1168 1169 ierr = MatProductSetType(adpd,MATPRODUCT_AB);CHKERRQ(ierr); 1170 ierr = MatProductSetAlgorithm(adpd,"sorted");CHKERRQ(ierr); 1171 ierr = MatProductSetFill(adpd,fill);CHKERRQ(ierr); 1172 ierr = MatProductSetFromOptions(adpd);CHKERRQ(ierr); 1173 ierr = MatProductSymbolic(adpd);CHKERRQ(ierr); 1174 1175 adpd_seq = (Mat_SeqAIJ*)((adpd)->data); 1176 adpdi = adpd_seq->i; adpdj = adpd_seq->j; 1177 p_off = (Mat_SeqAIJ*)((p->B)->data); 1178 poff_i = p_off->i; poff_j = p_off->j; 1179 1180 /* j_temp stores indices of a result row before they are added to the linked list */ 1181 ierr = PetscMalloc1(pN+2,&j_temp);CHKERRQ(ierr); 1182 1183 1184 /* Symbolic calc of the A_diag * p_loc_off */ 1185 /* Initial FreeSpace size is fill*(nnz(A)+nnz(P)) */ 1186 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,PetscIntSumTruncate(adi[am],PetscIntSumTruncate(aoi[am],pi_loc[pm]))),&free_space_diag);CHKERRQ(ierr); 1187 current_space = free_space_diag; 1188 1189 for (i=0; i<am; i++) { 1190 /* A_diag * P_loc_off */ 1191 nzi = adi[i+1] - adi[i]; 1192 for (j=0; j<nzi; j++) { 1193 row = *adj++; 1194 pnz = poff_i[row+1] - poff_i[row]; 1195 Jptr = poff_j + poff_i[row]; 1196 for(i1 = 0; i1 < pnz; i1++) { 1197 j_temp[i1] = p->garray[Jptr[i1]]; 1198 } 1199 /* add non-zero cols of P into the sorted linked list lnk */ 1200 ierr = PetscLLCondensedAddSorted(pnz,j_temp,lnk,lnkbt);CHKERRQ(ierr); 1201 } 1202 1203 adponz = lnk[0]; 1204 adpoi[i+1] = adpoi[i] + adponz; 1205 1206 /* if free space is not available, double the total space in the list */ 1207 if (current_space->local_remaining<adponz) { 1208 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(adponz,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 1209 nspacedouble++; 1210 } 1211 1212 /* Copy data into free space, then initialize lnk */ 1213 ierr = PetscLLCondensedClean(pN,adponz,current_space->array,lnk,lnkbt);CHKERRQ(ierr); 1214 1215 current_space->array += adponz; 1216 current_space->local_used += adponz; 1217 current_space->local_remaining -= adponz; 1218 } 1219 1220 /* Symbolic calc of A_off * P_oth */ 1221 ierr = MatSetOptionsPrefix(a->B,prefix);CHKERRQ(ierr); 1222 ierr = MatAppendOptionsPrefix(a->B,"inner_offdiag_");CHKERRQ(ierr); 1223 ierr = MatCreate(PETSC_COMM_SELF,&aopoth);CHKERRQ(ierr); 1224 ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(a->B, ptap->P_oth, fill, aopoth);CHKERRQ(ierr); 1225 aopoth_seq = (Mat_SeqAIJ*)((aopoth)->data); 1226 aopothi = aopoth_seq->i; aopothj = aopoth_seq->j; 1227 1228 /* Allocate space for apj, adpj, aopj, ... */ 1229 /* destroy lists of free space and other temporary array(s) */ 1230 1231 ierr = PetscMalloc1(aopothi[am] + adpoi[am] + adpdi[am]+2, &ptap->apj);CHKERRQ(ierr); 1232 ierr = PetscMalloc1(adpoi[am]+2, &adpoj);CHKERRQ(ierr); 1233 1234 /* Copy from linked list to j-array */ 1235 ierr = PetscFreeSpaceContiguous(&free_space_diag,adpoj);CHKERRQ(ierr); 1236 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 1237 1238 adpoJ = adpoj; 1239 adpdJ = adpdj; 1240 aopJ = aopothj; 1241 apj = ptap->apj; 1242 apJ = apj; /* still empty */ 1243 1244 /* Merge j-arrays of A_off * P, A_diag * P_loc_off, and */ 1245 /* A_diag * P_loc_diag to get A*P */ 1246 for (i = 0; i < am; i++) { 1247 aopnz = aopothi[i+1] - aopothi[i]; 1248 adponz = adpoi[i+1] - adpoi[i]; 1249 adpdnz = adpdi[i+1] - adpdi[i]; 1250 1251 /* Correct indices from A_diag*P_diag */ 1252 for(i1 = 0; i1 < adpdnz; i1++) { 1253 adpdJ[i1] += p_colstart; 1254 } 1255 /* Merge j-arrays of A_diag * P_loc_off and A_diag * P_loc_diag and A_off * P_oth */ 1256 Merge3SortedArrays(adponz, adpoJ, adpdnz, adpdJ, aopnz, aopJ, &apnz, apJ); 1257 ierr = MatPreallocateSet(i+rstart, apnz, apJ, dnz, onz); CHKERRQ(ierr); 1258 1259 aopJ += aopnz; 1260 adpoJ += adponz; 1261 adpdJ += adpdnz; 1262 apJ += apnz; 1263 api[i+1] = api[i] + apnz; 1264 } 1265 1266 /* malloc apa to store dense row A[i,:]*P */ 1267 ierr = PetscCalloc1(pN+2,&ptap->apa);CHKERRQ(ierr); 1268 1269 /* create and assemble symbolic parallel matrix C */ 1270 ierr = MatSetSizes(C,am,pn,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 1271 ierr = MatSetBlockSizesFromMats(C,A,P);CHKERRQ(ierr); 1272 ierr = MatGetType(A,&mtype);CHKERRQ(ierr); 1273 ierr = MatSetType(C,mtype);CHKERRQ(ierr); 1274 ierr = MatMPIAIJSetPreallocation(C,0,dnz,0,onz);CHKERRQ(ierr); 1275 1276 1277 ierr = MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(C, apj, api);CHKERRQ(ierr); 1278 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1279 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1280 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 1281 1282 1283 ptap->destroy = C->ops->destroy; 1284 ptap->duplicate = C->ops->duplicate; 1285 C->ops->matmultnumeric = MatMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable; 1286 C->ops->productnumeric = MatProductNumeric_AB; 1287 C->ops->destroy = MatDestroy_MPIAIJ_MatMatMult; 1288 1289 /* attach the supporting struct to C for reuse */ 1290 c = (Mat_MPIAIJ*)C->data; 1291 c->ap = ptap; 1292 1293 /* set MatInfo */ 1294 afill = (PetscReal)api[am]/(adi[am]+aoi[am]+pi_loc[pm]+1) + 1.e-5; 1295 if (afill < 1.0) afill = 1.0; 1296 C->info.mallocs = nspacedouble; 1297 C->info.fill_ratio_given = fill; 1298 C->info.fill_ratio_needed = afill; 1299 1300 #if defined(PETSC_USE_INFO) 1301 if (api[am]) { 1302 ierr = PetscInfo3(C,"Reallocs %D; Fill ratio: given %g needed %g.\n",nspacedouble,(double)fill,(double)afill);CHKERRQ(ierr); 1303 ierr = PetscInfo1(C,"Use MatMatMult(A,B,MatReuse,%g,&C) for best performance.;\n",(double)afill);CHKERRQ(ierr); 1304 } else { 1305 ierr = PetscInfo(C,"Empty matrix product\n");CHKERRQ(ierr); 1306 } 1307 #endif 1308 1309 ierr = MatDestroy(&aopoth);CHKERRQ(ierr); 1310 ierr = MatDestroy(&adpd);CHKERRQ(ierr); 1311 ierr = PetscFree(j_temp);CHKERRQ(ierr); 1312 ierr = PetscFree(adpoj);CHKERRQ(ierr); 1313 ierr = PetscFree(adpoi);CHKERRQ(ierr); 1314 PetscFunctionReturn(0); 1315 } 1316 1317 /*-------------------------------------------------------------------------*/ 1318 /* This routine only works when scall=MAT_REUSE_MATRIX! */ 1319 PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_matmatmult(Mat P,Mat A,Mat C) 1320 { 1321 PetscErrorCode ierr; 1322 Mat_MPIAIJ *c=(Mat_MPIAIJ*)C->data; 1323 Mat_APMPI *ptap= c->ap; 1324 Mat Pt; 1325 1326 PetscFunctionBegin; 1327 if (!ptap->Pt) { 1328 MPI_Comm comm; 1329 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 1330 SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"PtA cannot be reused. Do not call MatFreeIntermediateDataStructures() or use '-mat_freeintermediatedatastructures'"); 1331 } 1332 1333 Pt = ptap->Pt; 1334 ierr = MatTranspose(P,MAT_REUSE_MATRIX,&Pt);CHKERRQ(ierr); 1335 ierr = MatMatMultNumeric_MPIAIJ_MPIAIJ(Pt,A,C);CHKERRQ(ierr); 1336 1337 /* supporting struct ptap consumes almost same amount of memory as C=PtAP, release it if C will not be updated by A and P */ 1338 if (ptap->freestruct) { 1339 ierr = MatFreeIntermediateDataStructures(C);CHKERRQ(ierr); 1340 } 1341 PetscFunctionReturn(0); 1342 } 1343 1344 /* This routine is modified from MatPtAPSymbolic_MPIAIJ_MPIAIJ() */ 1345 PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat P,Mat A,PetscReal fill,Mat C) 1346 { 1347 PetscErrorCode ierr; 1348 Mat_APMPI *ptap; 1349 Mat_MPIAIJ *p=(Mat_MPIAIJ*)P->data,*c; 1350 MPI_Comm comm; 1351 PetscMPIInt size,rank; 1352 PetscFreeSpaceList free_space=NULL,current_space=NULL; 1353 PetscInt pn=P->cmap->n,aN=A->cmap->N,an=A->cmap->n; 1354 PetscInt *lnk,i,k,nsend; 1355 PetscBT lnkbt; 1356 PetscMPIInt tagi,tagj,*len_si,*len_s,*len_ri,icompleted=0,nrecv; 1357 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 1358 PetscInt len,proc,*dnz,*onz,*owners,nzi; 1359 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextci; 1360 MPI_Request *swaits,*rwaits; 1361 MPI_Status *sstatus,rstatus; 1362 PetscLayout rowmap; 1363 PetscInt *owners_co,*coi,*coj; /* i and j array of (p->B)^T*A*P - used in the communication */ 1364 PetscMPIInt *len_r,*id_r; /* array of length of comm->size, store send/recv matrix values */ 1365 PetscInt *Jptr,*prmap=p->garray,con,j,Crmax; 1366 Mat_SeqAIJ *a_loc,*c_loc,*c_oth; 1367 PetscTable ta; 1368 MatType mtype; 1369 const char *prefix; 1370 1371 PetscFunctionBegin; 1372 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1373 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1374 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1375 1376 /* create symbolic parallel matrix C */ 1377 ierr = MatGetType(A,&mtype);CHKERRQ(ierr); 1378 ierr = MatSetType(C,mtype);CHKERRQ(ierr); 1379 1380 C->ops->transposematmultnumeric = MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable; 1381 1382 /* create struct Mat_APMPI and attached it to C later */ 1383 ierr = PetscNew(&ptap);CHKERRQ(ierr); 1384 ptap->reuse = MAT_INITIAL_MATRIX; 1385 1386 /* (0) compute Rd = Pd^T, Ro = Po^T */ 1387 /* --------------------------------- */ 1388 ierr = MatTranspose_SeqAIJ(p->A,MAT_INITIAL_MATRIX,&ptap->Rd);CHKERRQ(ierr); 1389 ierr = MatTranspose_SeqAIJ(p->B,MAT_INITIAL_MATRIX,&ptap->Ro);CHKERRQ(ierr); 1390 1391 /* (1) compute symbolic A_loc */ 1392 /* ---------------------------*/ 1393 ierr = MatMPIAIJGetLocalMat(A,MAT_INITIAL_MATRIX,&ptap->A_loc);CHKERRQ(ierr); 1394 1395 /* (2-1) compute symbolic C_oth = Ro*A_loc */ 1396 /* ------------------------------------ */ 1397 ierr = MatGetOptionsPrefix(A,&prefix);CHKERRQ(ierr); 1398 ierr = MatSetOptionsPrefix(ptap->Ro,prefix);CHKERRQ(ierr); 1399 ierr = MatAppendOptionsPrefix(ptap->Ro,"inner_offdiag_");CHKERRQ(ierr); 1400 ierr = MatCreate(PETSC_COMM_SELF,&ptap->C_oth);CHKERRQ(ierr); 1401 ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(ptap->Ro,ptap->A_loc,fill,ptap->C_oth);CHKERRQ(ierr); 1402 1403 /* (3) send coj of C_oth to other processors */ 1404 /* ------------------------------------------ */ 1405 /* determine row ownership */ 1406 ierr = PetscLayoutCreate(comm,&rowmap);CHKERRQ(ierr); 1407 rowmap->n = pn; 1408 rowmap->bs = 1; 1409 ierr = PetscLayoutSetUp(rowmap);CHKERRQ(ierr); 1410 owners = rowmap->range; 1411 1412 /* determine the number of messages to send, their lengths */ 1413 ierr = PetscMalloc4(size,&len_s,size,&len_si,size,&sstatus,size+2,&owners_co);CHKERRQ(ierr); 1414 ierr = PetscArrayzero(len_s,size);CHKERRQ(ierr); 1415 ierr = PetscArrayzero(len_si,size);CHKERRQ(ierr); 1416 1417 c_oth = (Mat_SeqAIJ*)ptap->C_oth->data; 1418 coi = c_oth->i; coj = c_oth->j; 1419 con = ptap->C_oth->rmap->n; 1420 proc = 0; 1421 for (i=0; i<con; i++) { 1422 while (prmap[i] >= owners[proc+1]) proc++; 1423 len_si[proc]++; /* num of rows in Co(=Pt*A) to be sent to [proc] */ 1424 len_s[proc] += coi[i+1] - coi[i]; /* num of nonzeros in Co to be sent to [proc] */ 1425 } 1426 1427 len = 0; /* max length of buf_si[], see (4) */ 1428 owners_co[0] = 0; 1429 nsend = 0; 1430 for (proc=0; proc<size; proc++) { 1431 owners_co[proc+1] = owners_co[proc] + len_si[proc]; 1432 if (len_s[proc]) { 1433 nsend++; 1434 len_si[proc] = 2*(len_si[proc] + 1); /* length of buf_si to be sent to [proc] */ 1435 len += len_si[proc]; 1436 } 1437 } 1438 1439 /* determine the number and length of messages to receive for coi and coj */ 1440 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&nrecv);CHKERRQ(ierr); 1441 ierr = PetscGatherMessageLengths2(comm,nsend,nrecv,len_s,len_si,&id_r,&len_r,&len_ri);CHKERRQ(ierr); 1442 1443 /* post the Irecv and Isend of coj */ 1444 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 1445 ierr = PetscPostIrecvInt(comm,tagj,nrecv,id_r,len_r,&buf_rj,&rwaits);CHKERRQ(ierr); 1446 ierr = PetscMalloc1(nsend+1,&swaits);CHKERRQ(ierr); 1447 for (proc=0, k=0; proc<size; proc++) { 1448 if (!len_s[proc]) continue; 1449 i = owners_co[proc]; 1450 ierr = MPI_Isend(coj+coi[i],len_s[proc],MPIU_INT,proc,tagj,comm,swaits+k);CHKERRQ(ierr); 1451 k++; 1452 } 1453 1454 /* (2-2) compute symbolic C_loc = Rd*A_loc */ 1455 /* ---------------------------------------- */ 1456 ierr = MatSetOptionsPrefix(ptap->Rd,prefix);CHKERRQ(ierr); 1457 ierr = MatAppendOptionsPrefix(ptap->Rd,"inner_diag_");CHKERRQ(ierr); 1458 ierr = MatCreate(PETSC_COMM_SELF,&ptap->C_loc);CHKERRQ(ierr); 1459 ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(ptap->Rd,ptap->A_loc,fill,ptap->C_loc);CHKERRQ(ierr); 1460 c_loc = (Mat_SeqAIJ*)ptap->C_loc->data; 1461 1462 /* receives coj are complete */ 1463 for (i=0; i<nrecv; i++) { 1464 ierr = MPI_Waitany(nrecv,rwaits,&icompleted,&rstatus);CHKERRQ(ierr); 1465 } 1466 ierr = PetscFree(rwaits);CHKERRQ(ierr); 1467 if (nsend) {ierr = MPI_Waitall(nsend,swaits,sstatus);CHKERRQ(ierr);} 1468 1469 /* add received column indices into ta to update Crmax */ 1470 a_loc = (Mat_SeqAIJ*)(ptap->A_loc)->data; 1471 1472 /* create and initialize a linked list */ 1473 ierr = PetscTableCreate(an,aN,&ta);CHKERRQ(ierr); /* for compute Crmax */ 1474 MatRowMergeMax_SeqAIJ(a_loc,ptap->A_loc->rmap->N,ta); 1475 1476 for (k=0; k<nrecv; k++) {/* k-th received message */ 1477 Jptr = buf_rj[k]; 1478 for (j=0; j<len_r[k]; j++) { 1479 ierr = PetscTableAdd(ta,*(Jptr+j)+1,1,INSERT_VALUES);CHKERRQ(ierr); 1480 } 1481 } 1482 ierr = PetscTableGetCount(ta,&Crmax);CHKERRQ(ierr); 1483 ierr = PetscTableDestroy(&ta);CHKERRQ(ierr); 1484 1485 /* (4) send and recv coi */ 1486 /*-----------------------*/ 1487 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 1488 ierr = PetscPostIrecvInt(comm,tagi,nrecv,id_r,len_ri,&buf_ri,&rwaits);CHKERRQ(ierr); 1489 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 1490 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 1491 for (proc=0,k=0; proc<size; proc++) { 1492 if (!len_s[proc]) continue; 1493 /* form outgoing message for i-structure: 1494 buf_si[0]: nrows to be sent 1495 [1:nrows]: row index (global) 1496 [nrows+1:2*nrows+1]: i-structure index 1497 */ 1498 /*-------------------------------------------*/ 1499 nrows = len_si[proc]/2 - 1; /* num of rows in Co to be sent to [proc] */ 1500 buf_si_i = buf_si + nrows+1; 1501 buf_si[0] = nrows; 1502 buf_si_i[0] = 0; 1503 nrows = 0; 1504 for (i=owners_co[proc]; i<owners_co[proc+1]; i++) { 1505 nzi = coi[i+1] - coi[i]; 1506 buf_si_i[nrows+1] = buf_si_i[nrows] + nzi; /* i-structure */ 1507 buf_si[nrows+1] = prmap[i] -owners[proc]; /* local row index */ 1508 nrows++; 1509 } 1510 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,swaits+k);CHKERRQ(ierr); 1511 k++; 1512 buf_si += len_si[proc]; 1513 } 1514 for (i=0; i<nrecv; i++) { 1515 ierr = MPI_Waitany(nrecv,rwaits,&icompleted,&rstatus);CHKERRQ(ierr); 1516 } 1517 ierr = PetscFree(rwaits);CHKERRQ(ierr); 1518 if (nsend) {ierr = MPI_Waitall(nsend,swaits,sstatus);CHKERRQ(ierr);} 1519 1520 ierr = PetscFree4(len_s,len_si,sstatus,owners_co);CHKERRQ(ierr); 1521 ierr = PetscFree(len_ri);CHKERRQ(ierr); 1522 ierr = PetscFree(swaits);CHKERRQ(ierr); 1523 ierr = PetscFree(buf_s);CHKERRQ(ierr); 1524 1525 /* (5) compute the local portion of C */ 1526 /* ------------------------------------------ */ 1527 /* set initial free space to be Crmax, sufficient for holding nozeros in each row of C */ 1528 ierr = PetscFreeSpaceGet(Crmax,&free_space);CHKERRQ(ierr); 1529 current_space = free_space; 1530 1531 ierr = PetscMalloc3(nrecv,&buf_ri_k,nrecv,&nextrow,nrecv,&nextci);CHKERRQ(ierr); 1532 for (k=0; k<nrecv; k++) { 1533 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 1534 nrows = *buf_ri_k[k]; 1535 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 1536 nextci[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 1537 } 1538 1539 ierr = MatPreallocateInitialize(comm,pn,an,dnz,onz);CHKERRQ(ierr); 1540 ierr = PetscLLCondensedCreate(Crmax,aN,&lnk,&lnkbt);CHKERRQ(ierr); 1541 for (i=0; i<pn; i++) { 1542 /* add C_loc into C */ 1543 nzi = c_loc->i[i+1] - c_loc->i[i]; 1544 Jptr = c_loc->j + c_loc->i[i]; 1545 ierr = PetscLLCondensedAddSorted(nzi,Jptr,lnk,lnkbt);CHKERRQ(ierr); 1546 1547 /* add received col data into lnk */ 1548 for (k=0; k<nrecv; k++) { /* k-th received message */ 1549 if (i == *nextrow[k]) { /* i-th row */ 1550 nzi = *(nextci[k]+1) - *nextci[k]; 1551 Jptr = buf_rj[k] + *nextci[k]; 1552 ierr = PetscLLCondensedAddSorted(nzi,Jptr,lnk,lnkbt);CHKERRQ(ierr); 1553 nextrow[k]++; nextci[k]++; 1554 } 1555 } 1556 nzi = lnk[0]; 1557 1558 /* copy data into free space, then initialize lnk */ 1559 ierr = PetscLLCondensedClean(aN,nzi,current_space->array,lnk,lnkbt);CHKERRQ(ierr); 1560 ierr = MatPreallocateSet(i+owners[rank],nzi,current_space->array,dnz,onz);CHKERRQ(ierr); 1561 } 1562 ierr = PetscFree3(buf_ri_k,nextrow,nextci);CHKERRQ(ierr); 1563 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 1564 ierr = PetscFreeSpaceDestroy(free_space);CHKERRQ(ierr); 1565 1566 /* local sizes and preallocation */ 1567 ierr = MatSetSizes(C,pn,an,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 1568 if (P->cmap->bs > 0) {ierr = PetscLayoutSetBlockSize(C->rmap,P->cmap->bs);CHKERRQ(ierr);} 1569 if (A->cmap->bs > 0) {ierr = PetscLayoutSetBlockSize(C->cmap,A->cmap->bs);CHKERRQ(ierr);} 1570 ierr = MatMPIAIJSetPreallocation(C,0,dnz,0,onz);CHKERRQ(ierr); 1571 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 1572 1573 /* members in merge */ 1574 ierr = PetscFree(id_r);CHKERRQ(ierr); 1575 ierr = PetscFree(len_r);CHKERRQ(ierr); 1576 ierr = PetscFree(buf_ri[0]);CHKERRQ(ierr); 1577 ierr = PetscFree(buf_ri);CHKERRQ(ierr); 1578 ierr = PetscFree(buf_rj[0]);CHKERRQ(ierr); 1579 ierr = PetscFree(buf_rj);CHKERRQ(ierr); 1580 ierr = PetscLayoutDestroy(&rowmap);CHKERRQ(ierr); 1581 1582 /* attach the supporting struct to C for reuse */ 1583 c = (Mat_MPIAIJ*)C->data; 1584 c->ap = ptap; 1585 ptap->destroy = C->ops->destroy; 1586 1587 /* C is not ready for use - assembly will be done by MatPtAPNumeric() */ 1588 C->assembled = PETSC_FALSE; 1589 C->ops->destroy = MatDestroy_MPIAIJ_PtAP; 1590 C->ops->freeintermediatedatastructures = MatFreeIntermediateDataStructures_MPIAIJ_AP; 1591 PetscFunctionReturn(0); 1592 } 1593 1594 PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat P,Mat A,Mat C) 1595 { 1596 PetscErrorCode ierr; 1597 Mat_MPIAIJ *p=(Mat_MPIAIJ*)P->data,*c=(Mat_MPIAIJ*)C->data; 1598 Mat_SeqAIJ *c_seq; 1599 Mat_APMPI *ptap = c->ap; 1600 Mat A_loc,C_loc,C_oth; 1601 PetscInt i,rstart,rend,cm,ncols,row; 1602 const PetscInt *cols; 1603 const PetscScalar *vals; 1604 1605 PetscFunctionBegin; 1606 if (!ptap->A_loc) { 1607 MPI_Comm comm; 1608 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 1609 SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"PtA cannot be reused. Do not call MatFreeIntermediateDataStructures() or use '-mat_freeintermediatedatastructures'"); 1610 } 1611 1612 ierr = MatZeroEntries(C);CHKERRQ(ierr); 1613 1614 if (ptap->reuse == MAT_REUSE_MATRIX) { 1615 /* These matrices are obtained in MatTransposeMatMultSymbolic() */ 1616 /* 1) get R = Pd^T, Ro = Po^T */ 1617 /*----------------------------*/ 1618 ierr = MatTranspose_SeqAIJ(p->A,MAT_REUSE_MATRIX,&ptap->Rd);CHKERRQ(ierr); 1619 ierr = MatTranspose_SeqAIJ(p->B,MAT_REUSE_MATRIX,&ptap->Ro);CHKERRQ(ierr); 1620 1621 /* 2) compute numeric A_loc */ 1622 /*--------------------------*/ 1623 ierr = MatMPIAIJGetLocalMat(A,MAT_REUSE_MATRIX,&ptap->A_loc);CHKERRQ(ierr); 1624 } 1625 1626 /* 3) C_loc = Rd*A_loc, C_oth = Ro*A_loc */ 1627 A_loc = ptap->A_loc; 1628 ierr = ((ptap->C_loc)->ops->matmultnumeric)(ptap->Rd,A_loc,ptap->C_loc);CHKERRQ(ierr); 1629 ierr = ((ptap->C_oth)->ops->matmultnumeric)(ptap->Ro,A_loc,ptap->C_oth);CHKERRQ(ierr); 1630 C_loc = ptap->C_loc; 1631 C_oth = ptap->C_oth; 1632 1633 /* add C_loc and Co to to C */ 1634 ierr = MatGetOwnershipRange(C,&rstart,&rend);CHKERRQ(ierr); 1635 1636 /* C_loc -> C */ 1637 cm = C_loc->rmap->N; 1638 c_seq = (Mat_SeqAIJ*)C_loc->data; 1639 cols = c_seq->j; 1640 vals = c_seq->a; 1641 for (i=0; i<cm; i++) { 1642 ncols = c_seq->i[i+1] - c_seq->i[i]; 1643 row = rstart + i; 1644 ierr = MatSetValues(C,1,&row,ncols,cols,vals,ADD_VALUES);CHKERRQ(ierr); 1645 cols += ncols; vals += ncols; 1646 } 1647 1648 /* Co -> C, off-processor part */ 1649 cm = C_oth->rmap->N; 1650 c_seq = (Mat_SeqAIJ*)C_oth->data; 1651 cols = c_seq->j; 1652 vals = c_seq->a; 1653 for (i=0; i<cm; i++) { 1654 ncols = c_seq->i[i+1] - c_seq->i[i]; 1655 row = p->garray[i]; 1656 ierr = MatSetValues(C,1,&row,ncols,cols,vals,ADD_VALUES);CHKERRQ(ierr); 1657 cols += ncols; vals += ncols; 1658 } 1659 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1660 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1661 1662 ptap->reuse = MAT_REUSE_MATRIX; 1663 1664 /* supporting struct ptap consumes almost same amount of memory as C=PtAP, release it if C will not be updated by A and P */ 1665 if (ptap->freestruct) { 1666 ierr = MatFreeIntermediateDataStructures(C);CHKERRQ(ierr); 1667 } 1668 PetscFunctionReturn(0); 1669 } 1670 1671 PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ(Mat P,Mat A,Mat C) 1672 { 1673 PetscErrorCode ierr; 1674 Mat_Merge_SeqsToMPI *merge; 1675 Mat_MPIAIJ *p =(Mat_MPIAIJ*)P->data,*c=(Mat_MPIAIJ*)C->data; 1676 Mat_SeqAIJ *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data; 1677 Mat_APMPI *ptap; 1678 PetscInt *adj; 1679 PetscInt i,j,k,anz,pnz,row,*cj,nexta; 1680 MatScalar *ada,*ca,valtmp; 1681 PetscInt am =A->rmap->n,cm=C->rmap->n,pon=(p->B)->cmap->n; 1682 MPI_Comm comm; 1683 PetscMPIInt size,rank,taga,*len_s; 1684 PetscInt *owners,proc,nrows,**buf_ri_k,**nextrow,**nextci; 1685 PetscInt **buf_ri,**buf_rj; 1686 PetscInt cnz=0,*bj_i,*bi,*bj,bnz,nextcj; /* bi,bj,ba: local array of C(mpi mat) */ 1687 MPI_Request *s_waits,*r_waits; 1688 MPI_Status *status; 1689 MatScalar **abuf_r,*ba_i,*pA,*coa,*ba; 1690 PetscInt *ai,*aj,*coi,*coj,*poJ,*pdJ; 1691 Mat A_loc; 1692 Mat_SeqAIJ *a_loc; 1693 1694 PetscFunctionBegin; 1695 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 1696 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1697 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1698 1699 ptap = c->ap; 1700 if (!ptap->A_loc) SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"PtA cannot be reused. Do not call MatFreeIntermediateDataStructures() or use '-mat_freeintermediatedatastructures'"); 1701 merge = ptap->merge; 1702 1703 /* 2) compute numeric C_seq = P_loc^T*A_loc */ 1704 /*------------------------------------------*/ 1705 /* get data from symbolic products */ 1706 coi = merge->coi; coj = merge->coj; 1707 ierr = PetscCalloc1(coi[pon]+1,&coa);CHKERRQ(ierr); 1708 bi = merge->bi; bj = merge->bj; 1709 owners = merge->rowmap->range; 1710 ierr = PetscCalloc1(bi[cm]+1,&ba);CHKERRQ(ierr); 1711 1712 /* get A_loc by taking all local rows of A */ 1713 A_loc = ptap->A_loc; 1714 ierr = MatMPIAIJGetLocalMat(A,MAT_REUSE_MATRIX,&A_loc);CHKERRQ(ierr); 1715 a_loc = (Mat_SeqAIJ*)(A_loc)->data; 1716 ai = a_loc->i; 1717 aj = a_loc->j; 1718 1719 for (i=0; i<am; i++) { 1720 anz = ai[i+1] - ai[i]; 1721 adj = aj + ai[i]; 1722 ada = a_loc->a + ai[i]; 1723 1724 /* 2-b) Compute Cseq = P_loc[i,:]^T*A[i,:] using outer product */ 1725 /*-------------------------------------------------------------*/ 1726 /* put the value into Co=(p->B)^T*A (off-diagonal part, send to others) */ 1727 pnz = po->i[i+1] - po->i[i]; 1728 poJ = po->j + po->i[i]; 1729 pA = po->a + po->i[i]; 1730 for (j=0; j<pnz; j++) { 1731 row = poJ[j]; 1732 cj = coj + coi[row]; 1733 ca = coa + coi[row]; 1734 /* perform sparse axpy */ 1735 nexta = 0; 1736 valtmp = pA[j]; 1737 for (k=0; nexta<anz; k++) { 1738 if (cj[k] == adj[nexta]) { 1739 ca[k] += valtmp*ada[nexta]; 1740 nexta++; 1741 } 1742 } 1743 ierr = PetscLogFlops(2.0*anz);CHKERRQ(ierr); 1744 } 1745 1746 /* put the value into Cd (diagonal part) */ 1747 pnz = pd->i[i+1] - pd->i[i]; 1748 pdJ = pd->j + pd->i[i]; 1749 pA = pd->a + pd->i[i]; 1750 for (j=0; j<pnz; j++) { 1751 row = pdJ[j]; 1752 cj = bj + bi[row]; 1753 ca = ba + bi[row]; 1754 /* perform sparse axpy */ 1755 nexta = 0; 1756 valtmp = pA[j]; 1757 for (k=0; nexta<anz; k++) { 1758 if (cj[k] == adj[nexta]) { 1759 ca[k] += valtmp*ada[nexta]; 1760 nexta++; 1761 } 1762 } 1763 ierr = PetscLogFlops(2.0*anz);CHKERRQ(ierr); 1764 } 1765 } 1766 1767 /* 3) send and recv matrix values coa */ 1768 /*------------------------------------*/ 1769 buf_ri = merge->buf_ri; 1770 buf_rj = merge->buf_rj; 1771 len_s = merge->len_s; 1772 ierr = PetscCommGetNewTag(comm,&taga);CHKERRQ(ierr); 1773 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 1774 1775 ierr = PetscMalloc2(merge->nsend+1,&s_waits,size,&status);CHKERRQ(ierr); 1776 for (proc=0,k=0; proc<size; proc++) { 1777 if (!len_s[proc]) continue; 1778 i = merge->owners_co[proc]; 1779 ierr = MPI_Isend(coa+coi[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 1780 k++; 1781 } 1782 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 1783 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 1784 1785 ierr = PetscFree2(s_waits,status);CHKERRQ(ierr); 1786 ierr = PetscFree(r_waits);CHKERRQ(ierr); 1787 ierr = PetscFree(coa);CHKERRQ(ierr); 1788 1789 /* 4) insert local Cseq and received values into Cmpi */ 1790 /*----------------------------------------------------*/ 1791 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextci);CHKERRQ(ierr); 1792 for (k=0; k<merge->nrecv; k++) { 1793 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 1794 nrows = *(buf_ri_k[k]); 1795 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 1796 nextci[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 1797 } 1798 1799 for (i=0; i<cm; i++) { 1800 row = owners[rank] + i; /* global row index of C_seq */ 1801 bj_i = bj + bi[i]; /* col indices of the i-th row of C */ 1802 ba_i = ba + bi[i]; 1803 bnz = bi[i+1] - bi[i]; 1804 /* add received vals into ba */ 1805 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 1806 /* i-th row */ 1807 if (i == *nextrow[k]) { 1808 cnz = *(nextci[k]+1) - *nextci[k]; 1809 cj = buf_rj[k] + *(nextci[k]); 1810 ca = abuf_r[k] + *(nextci[k]); 1811 nextcj = 0; 1812 for (j=0; nextcj<cnz; j++) { 1813 if (bj_i[j] == cj[nextcj]) { /* bcol == ccol */ 1814 ba_i[j] += ca[nextcj++]; 1815 } 1816 } 1817 nextrow[k]++; nextci[k]++; 1818 ierr = PetscLogFlops(2.0*cnz);CHKERRQ(ierr); 1819 } 1820 } 1821 ierr = MatSetValues(C,1,&row,bnz,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 1822 } 1823 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1824 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1825 1826 ierr = PetscFree(ba);CHKERRQ(ierr); 1827 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 1828 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 1829 ierr = PetscFree3(buf_ri_k,nextrow,nextci);CHKERRQ(ierr); 1830 1831 if (ptap->freestruct) { 1832 ierr = MatFreeIntermediateDataStructures(C);CHKERRQ(ierr); 1833 } 1834 PetscFunctionReturn(0); 1835 } 1836 1837 PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ(Mat P,Mat A,PetscReal fill,Mat C) 1838 { 1839 PetscErrorCode ierr; 1840 Mat A_loc,POt,PDt; 1841 Mat_APMPI *ptap; 1842 PetscFreeSpaceList free_space=NULL,current_space=NULL; 1843 Mat_MPIAIJ *p=(Mat_MPIAIJ*)P->data,*a=(Mat_MPIAIJ*)A->data,*c; 1844 PetscInt *pdti,*pdtj,*poti,*potj,*ptJ; 1845 PetscInt nnz; 1846 PetscInt *lnk,*owners_co,*coi,*coj,i,k,pnz,row; 1847 PetscInt am =A->rmap->n,pn=P->cmap->n; 1848 MPI_Comm comm; 1849 PetscMPIInt size,rank,tagi,tagj,*len_si,*len_s,*len_ri; 1850 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 1851 PetscInt len,proc,*dnz,*onz,*owners; 1852 PetscInt nzi,*bi,*bj; 1853 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextci; 1854 MPI_Request *swaits,*rwaits; 1855 MPI_Status *sstatus,rstatus; 1856 Mat_Merge_SeqsToMPI *merge; 1857 PetscInt *ai,*aj,*Jptr,anz,*prmap=p->garray,pon,nspacedouble=0,j; 1858 PetscReal afill =1.0,afill_tmp; 1859 PetscInt rstart = P->cmap->rstart,rmax,aN=A->cmap->N,Armax; 1860 Mat_SeqAIJ *a_loc,*pdt,*pot; 1861 PetscTable ta; 1862 MatType mtype; 1863 1864 PetscFunctionBegin; 1865 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1866 /* check if matrix local sizes are compatible */ 1867 if (A->rmap->rstart != P->rmap->rstart || A->rmap->rend != P->rmap->rend) SETERRQ4(comm,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A (%D, %D) != P (%D,%D)",A->rmap->rstart,A->rmap->rend,P->rmap->rstart,P->rmap->rend); 1868 1869 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1870 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1871 1872 /* create struct Mat_APMPI and attached it to C later */ 1873 ierr = PetscNew(&ptap);CHKERRQ(ierr); 1874 1875 /* get A_loc by taking all local rows of A */ 1876 ierr = MatMPIAIJGetLocalMat(A,MAT_INITIAL_MATRIX,&A_loc);CHKERRQ(ierr); 1877 1878 ptap->A_loc = A_loc; 1879 a_loc = (Mat_SeqAIJ*)(A_loc)->data; 1880 ai = a_loc->i; 1881 aj = a_loc->j; 1882 1883 /* determine symbolic Co=(p->B)^T*A - send to others */ 1884 /*----------------------------------------------------*/ 1885 ierr = MatTransposeSymbolic_SeqAIJ(p->A,&PDt);CHKERRQ(ierr); 1886 pdt = (Mat_SeqAIJ*)PDt->data; 1887 pdti = pdt->i; pdtj = pdt->j; 1888 1889 ierr = MatTransposeSymbolic_SeqAIJ(p->B,&POt);CHKERRQ(ierr); 1890 pot = (Mat_SeqAIJ*)POt->data; 1891 poti = pot->i; potj = pot->j; 1892 1893 /* then, compute symbolic Co = (p->B)^T*A */ 1894 pon = (p->B)->cmap->n; /* total num of rows to be sent to other processors 1895 >= (num of nonzero rows of C_seq) - pn */ 1896 ierr = PetscMalloc1(pon+1,&coi);CHKERRQ(ierr); 1897 coi[0] = 0; 1898 1899 /* set initial free space to be fill*(nnz(p->B) + nnz(A)) */ 1900 nnz = PetscRealIntMultTruncate(fill,PetscIntSumTruncate(poti[pon],ai[am])); 1901 ierr = PetscFreeSpaceGet(nnz,&free_space);CHKERRQ(ierr); 1902 current_space = free_space; 1903 1904 /* create and initialize a linked list */ 1905 ierr = PetscTableCreate(A->cmap->n + a->B->cmap->N,aN,&ta);CHKERRQ(ierr); 1906 MatRowMergeMax_SeqAIJ(a_loc,am,ta); 1907 ierr = PetscTableGetCount(ta,&Armax);CHKERRQ(ierr); 1908 1909 ierr = PetscLLCondensedCreate_Scalable(Armax,&lnk);CHKERRQ(ierr); 1910 1911 for (i=0; i<pon; i++) { 1912 pnz = poti[i+1] - poti[i]; 1913 ptJ = potj + poti[i]; 1914 for (j=0; j<pnz; j++) { 1915 row = ptJ[j]; /* row of A_loc == col of Pot */ 1916 anz = ai[row+1] - ai[row]; 1917 Jptr = aj + ai[row]; 1918 /* add non-zero cols of AP into the sorted linked list lnk */ 1919 ierr = PetscLLCondensedAddSorted_Scalable(anz,Jptr,lnk);CHKERRQ(ierr); 1920 } 1921 nnz = lnk[0]; 1922 1923 /* If free space is not available, double the total space in the list */ 1924 if (current_space->local_remaining<nnz) { 1925 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(nnz,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 1926 nspacedouble++; 1927 } 1928 1929 /* Copy data into free space, and zero out denserows */ 1930 ierr = PetscLLCondensedClean_Scalable(nnz,current_space->array,lnk);CHKERRQ(ierr); 1931 1932 current_space->array += nnz; 1933 current_space->local_used += nnz; 1934 current_space->local_remaining -= nnz; 1935 1936 coi[i+1] = coi[i] + nnz; 1937 } 1938 1939 ierr = PetscMalloc1(coi[pon]+1,&coj);CHKERRQ(ierr); 1940 ierr = PetscFreeSpaceContiguous(&free_space,coj);CHKERRQ(ierr); 1941 ierr = PetscLLCondensedDestroy_Scalable(lnk);CHKERRQ(ierr); /* must destroy to get a new one for C */ 1942 1943 afill_tmp = (PetscReal)coi[pon]/(poti[pon] + ai[am]+1); 1944 if (afill_tmp > afill) afill = afill_tmp; 1945 1946 /* send j-array (coj) of Co to other processors */ 1947 /*----------------------------------------------*/ 1948 /* determine row ownership */ 1949 ierr = PetscNew(&merge);CHKERRQ(ierr); 1950 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 1951 1952 merge->rowmap->n = pn; 1953 merge->rowmap->bs = 1; 1954 1955 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 1956 owners = merge->rowmap->range; 1957 1958 /* determine the number of messages to send, their lengths */ 1959 ierr = PetscCalloc1(size,&len_si);CHKERRQ(ierr); 1960 ierr = PetscCalloc1(size,&merge->len_s);CHKERRQ(ierr); 1961 1962 len_s = merge->len_s; 1963 merge->nsend = 0; 1964 1965 ierr = PetscMalloc1(size+2,&owners_co);CHKERRQ(ierr); 1966 1967 proc = 0; 1968 for (i=0; i<pon; i++) { 1969 while (prmap[i] >= owners[proc+1]) proc++; 1970 len_si[proc]++; /* num of rows in Co to be sent to [proc] */ 1971 len_s[proc] += coi[i+1] - coi[i]; 1972 } 1973 1974 len = 0; /* max length of buf_si[] */ 1975 owners_co[0] = 0; 1976 for (proc=0; proc<size; proc++) { 1977 owners_co[proc+1] = owners_co[proc] + len_si[proc]; 1978 if (len_si[proc]) { 1979 merge->nsend++; 1980 len_si[proc] = 2*(len_si[proc] + 1); 1981 len += len_si[proc]; 1982 } 1983 } 1984 1985 /* determine the number and length of messages to receive for coi and coj */ 1986 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 1987 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 1988 1989 /* post the Irecv and Isend of coj */ 1990 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 1991 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rwaits);CHKERRQ(ierr); 1992 ierr = PetscMalloc1(merge->nsend+1,&swaits);CHKERRQ(ierr); 1993 for (proc=0, k=0; proc<size; proc++) { 1994 if (!len_s[proc]) continue; 1995 i = owners_co[proc]; 1996 ierr = MPI_Isend(coj+coi[i],len_s[proc],MPIU_INT,proc,tagj,comm,swaits+k);CHKERRQ(ierr); 1997 k++; 1998 } 1999 2000 /* receives and sends of coj are complete */ 2001 ierr = PetscMalloc1(size,&sstatus);CHKERRQ(ierr); 2002 for (i=0; i<merge->nrecv; i++) { 2003 PetscMPIInt icompleted; 2004 ierr = MPI_Waitany(merge->nrecv,rwaits,&icompleted,&rstatus);CHKERRQ(ierr); 2005 } 2006 ierr = PetscFree(rwaits);CHKERRQ(ierr); 2007 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,swaits,sstatus);CHKERRQ(ierr);} 2008 2009 /* add received column indices into table to update Armax */ 2010 /* Armax can be as large as aN if a P[row,:] is dense, see src/ksp/ksp/tutorials/ex56.c! */ 2011 for (k=0; k<merge->nrecv; k++) {/* k-th received message */ 2012 Jptr = buf_rj[k]; 2013 for (j=0; j<merge->len_r[k]; j++) { 2014 ierr = PetscTableAdd(ta,*(Jptr+j)+1,1,INSERT_VALUES);CHKERRQ(ierr); 2015 } 2016 } 2017 ierr = PetscTableGetCount(ta,&Armax);CHKERRQ(ierr); 2018 /* printf("Armax %d, an %d + Bn %d = %d, aN %d\n",Armax,A->cmap->n,a->B->cmap->N,A->cmap->n+a->B->cmap->N,aN); */ 2019 2020 /* send and recv coi */ 2021 /*-------------------*/ 2022 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 2023 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&rwaits);CHKERRQ(ierr); 2024 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 2025 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 2026 for (proc=0,k=0; proc<size; proc++) { 2027 if (!len_s[proc]) continue; 2028 /* form outgoing message for i-structure: 2029 buf_si[0]: nrows to be sent 2030 [1:nrows]: row index (global) 2031 [nrows+1:2*nrows+1]: i-structure index 2032 */ 2033 /*-------------------------------------------*/ 2034 nrows = len_si[proc]/2 - 1; 2035 buf_si_i = buf_si + nrows+1; 2036 buf_si[0] = nrows; 2037 buf_si_i[0] = 0; 2038 nrows = 0; 2039 for (i=owners_co[proc]; i<owners_co[proc+1]; i++) { 2040 nzi = coi[i+1] - coi[i]; 2041 buf_si_i[nrows+1] = buf_si_i[nrows] + nzi; /* i-structure */ 2042 buf_si[nrows+1] = prmap[i] -owners[proc]; /* local row index */ 2043 nrows++; 2044 } 2045 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,swaits+k);CHKERRQ(ierr); 2046 k++; 2047 buf_si += len_si[proc]; 2048 } 2049 i = merge->nrecv; 2050 while (i--) { 2051 PetscMPIInt icompleted; 2052 ierr = MPI_Waitany(merge->nrecv,rwaits,&icompleted,&rstatus);CHKERRQ(ierr); 2053 } 2054 ierr = PetscFree(rwaits);CHKERRQ(ierr); 2055 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,swaits,sstatus);CHKERRQ(ierr);} 2056 ierr = PetscFree(len_si);CHKERRQ(ierr); 2057 ierr = PetscFree(len_ri);CHKERRQ(ierr); 2058 ierr = PetscFree(swaits);CHKERRQ(ierr); 2059 ierr = PetscFree(sstatus);CHKERRQ(ierr); 2060 ierr = PetscFree(buf_s);CHKERRQ(ierr); 2061 2062 /* compute the local portion of C (mpi mat) */ 2063 /*------------------------------------------*/ 2064 /* allocate bi array and free space for accumulating nonzero column info */ 2065 ierr = PetscMalloc1(pn+1,&bi);CHKERRQ(ierr); 2066 bi[0] = 0; 2067 2068 /* set initial free space to be fill*(nnz(P) + nnz(AP)) */ 2069 nnz = PetscRealIntMultTruncate(fill,PetscIntSumTruncate(pdti[pn],PetscIntSumTruncate(poti[pon],ai[am]))); 2070 ierr = PetscFreeSpaceGet(nnz,&free_space);CHKERRQ(ierr); 2071 current_space = free_space; 2072 2073 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextci);CHKERRQ(ierr); 2074 for (k=0; k<merge->nrecv; k++) { 2075 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 2076 nrows = *buf_ri_k[k]; 2077 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 2078 nextci[k] = buf_ri_k[k] + (nrows + 1); /* points to the next i-structure of k-th received i-structure */ 2079 } 2080 2081 ierr = PetscLLCondensedCreate_Scalable(Armax,&lnk);CHKERRQ(ierr); 2082 ierr = MatPreallocateInitialize(comm,pn,A->cmap->n,dnz,onz);CHKERRQ(ierr); 2083 rmax = 0; 2084 for (i=0; i<pn; i++) { 2085 /* add pdt[i,:]*AP into lnk */ 2086 pnz = pdti[i+1] - pdti[i]; 2087 ptJ = pdtj + pdti[i]; 2088 for (j=0; j<pnz; j++) { 2089 row = ptJ[j]; /* row of AP == col of Pt */ 2090 anz = ai[row+1] - ai[row]; 2091 Jptr = aj + ai[row]; 2092 /* add non-zero cols of AP into the sorted linked list lnk */ 2093 ierr = PetscLLCondensedAddSorted_Scalable(anz,Jptr,lnk);CHKERRQ(ierr); 2094 } 2095 2096 /* add received col data into lnk */ 2097 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 2098 if (i == *nextrow[k]) { /* i-th row */ 2099 nzi = *(nextci[k]+1) - *nextci[k]; 2100 Jptr = buf_rj[k] + *nextci[k]; 2101 ierr = PetscLLCondensedAddSorted_Scalable(nzi,Jptr,lnk);CHKERRQ(ierr); 2102 nextrow[k]++; nextci[k]++; 2103 } 2104 } 2105 nnz = lnk[0]; 2106 2107 /* if free space is not available, make more free space */ 2108 if (current_space->local_remaining<nnz) { 2109 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(nnz,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 2110 nspacedouble++; 2111 } 2112 /* copy data into free space, then initialize lnk */ 2113 ierr = PetscLLCondensedClean_Scalable(nnz,current_space->array,lnk);CHKERRQ(ierr); 2114 ierr = MatPreallocateSet(i+owners[rank],nnz,current_space->array,dnz,onz);CHKERRQ(ierr); 2115 2116 current_space->array += nnz; 2117 current_space->local_used += nnz; 2118 current_space->local_remaining -= nnz; 2119 2120 bi[i+1] = bi[i] + nnz; 2121 if (nnz > rmax) rmax = nnz; 2122 } 2123 ierr = PetscFree3(buf_ri_k,nextrow,nextci);CHKERRQ(ierr); 2124 2125 ierr = PetscMalloc1(bi[pn]+1,&bj);CHKERRQ(ierr); 2126 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 2127 afill_tmp = (PetscReal)bi[pn]/(pdti[pn] + poti[pon] + ai[am]+1); 2128 if (afill_tmp > afill) afill = afill_tmp; 2129 ierr = PetscLLCondensedDestroy_Scalable(lnk);CHKERRQ(ierr); 2130 ierr = PetscTableDestroy(&ta);CHKERRQ(ierr); 2131 2132 ierr = MatDestroy(&POt);CHKERRQ(ierr); 2133 ierr = MatDestroy(&PDt);CHKERRQ(ierr); 2134 2135 /* create symbolic parallel matrix C - why cannot be assembled in Numeric part */ 2136 /*-------------------------------------------------------------------------------*/ 2137 ierr = MatSetSizes(C,pn,A->cmap->n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2138 ierr = MatSetBlockSizes(C,PetscAbs(P->cmap->bs),PetscAbs(A->cmap->bs));CHKERRQ(ierr); 2139 ierr = MatGetType(A,&mtype);CHKERRQ(ierr); 2140 ierr = MatSetType(C,mtype);CHKERRQ(ierr); 2141 ierr = MatMPIAIJSetPreallocation(C,0,dnz,0,onz);CHKERRQ(ierr); 2142 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 2143 ierr = MatSetBlockSize(C,1);CHKERRQ(ierr); 2144 for (i=0; i<pn; i++) { 2145 row = i + rstart; 2146 nnz = bi[i+1] - bi[i]; 2147 Jptr = bj + bi[i]; 2148 ierr = MatSetValues(C,1,&row,nnz,Jptr,NULL,INSERT_VALUES);CHKERRQ(ierr); 2149 } 2150 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2151 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2152 merge->bi = bi; 2153 merge->bj = bj; 2154 merge->coi = coi; 2155 merge->coj = coj; 2156 merge->buf_ri = buf_ri; 2157 merge->buf_rj = buf_rj; 2158 merge->owners_co = owners_co; 2159 2160 /* attach the supporting struct to C for reuse */ 2161 c = (Mat_MPIAIJ*)C->data; 2162 2163 c->ap = ptap; 2164 ptap->api = NULL; 2165 ptap->apj = NULL; 2166 ptap->merge = merge; 2167 ptap->apa = NULL; 2168 ptap->destroy = C->ops->destroy; 2169 ptap->duplicate = C->ops->duplicate; 2170 2171 C->ops->mattransposemultnumeric = MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ; 2172 C->ops->destroy = MatDestroy_MPIAIJ_PtAP; 2173 C->ops->freeintermediatedatastructures = MatFreeIntermediateDataStructures_MPIAIJ_AP; 2174 2175 #if defined(PETSC_USE_INFO) 2176 if (bi[pn] != 0) { 2177 ierr = PetscInfo3(C,"Reallocs %D; Fill ratio: given %g needed %g.\n",nspacedouble,(double)fill,(double)afill);CHKERRQ(ierr); 2178 ierr = PetscInfo1(C,"Use MatTransposeMatMult(A,B,MatReuse,%g,&C) for best performance.\n",(double)afill);CHKERRQ(ierr); 2179 } else { 2180 ierr = PetscInfo(C,"Empty matrix product\n");CHKERRQ(ierr); 2181 } 2182 #endif 2183 PetscFunctionReturn(0); 2184 } 2185 2186 /* ---------------------------------------------------------------- */ 2187 static PetscErrorCode MatProductSymbolic_AtB_MPIAIJ_MPIAIJ(Mat C) 2188 { 2189 PetscErrorCode ierr; 2190 Mat_Product *product = C->product; 2191 Mat A=product->A,B=product->B; 2192 PetscReal fill=product->fill; 2193 PetscBool flg; 2194 2195 PetscFunctionBegin; 2196 /* scalable */ 2197 ierr = PetscStrcmp(product->alg,"scalable",&flg);CHKERRQ(ierr); 2198 if (flg) { 2199 ierr = MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 2200 goto next; 2201 } 2202 2203 /* nonscalable */ 2204 ierr = PetscStrcmp(product->alg,"nonscalable",&flg);CHKERRQ(ierr); 2205 if (flg) { 2206 ierr = MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(A,B,fill,C);CHKERRQ(ierr); 2207 goto next; 2208 } 2209 2210 /* matmatmult */ 2211 ierr = PetscStrcmp(product->alg,"at*b",&flg);CHKERRQ(ierr); 2212 if (flg) { 2213 Mat At; 2214 Mat_APMPI *ptap; 2215 Mat_MPIAIJ *c; 2216 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 2217 2218 ierr = MatMatMultSymbolic_MPIAIJ_MPIAIJ(At,B,fill,C);CHKERRQ(ierr); 2219 c = (Mat_MPIAIJ*)C->data; 2220 ptap = c->ap; 2221 if (ptap) { 2222 ptap->Pt = At; 2223 C->ops->freeintermediatedatastructures = MatFreeIntermediateDataStructures_MPIAIJ_AP; 2224 } 2225 C->ops->transposematmultnumeric = MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_matmatmult; 2226 goto next; 2227 } 2228 2229 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatProduct type is not supported"); 2230 2231 next: 2232 C->ops->productnumeric = MatProductNumeric_AtB; 2233 2234 { 2235 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2236 Mat_APMPI *ap = c->ap; 2237 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatFreeIntermediateDataStructures","Mat");CHKERRQ(ierr); 2238 ap->freestruct = PETSC_FALSE; 2239 ierr = PetscOptionsBool("-mat_freeintermediatedatastructures","Free intermediate data structures", "MatFreeIntermediateDataStructures",ap->freestruct,&ap->freestruct, NULL);CHKERRQ(ierr); 2240 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2241 } 2242 PetscFunctionReturn(0); 2243 } 2244 2245 /* ---------------------------------------------------------------- */ 2246 /* Set options for MatMatMultxxx_MPIAIJ_MPIAIJ */ 2247 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_AB(Mat C) 2248 { 2249 PetscErrorCode ierr; 2250 Mat_Product *product = C->product; 2251 Mat A=product->A,B=product->B; 2252 #if defined(PETSC_HAVE_HYPRE) 2253 const char *algTypes[4] = {"scalable","nonscalable","seqmpi","hypre"}; 2254 PetscInt nalg = 4; 2255 #else 2256 const char *algTypes[3] = {"scalable","nonscalable","seqmpi"}; 2257 PetscInt nalg = 3; 2258 #endif 2259 PetscInt alg = 1; /* set nonscalable algorithm as default */ 2260 PetscBool flg; 2261 MPI_Comm comm; 2262 2263 PetscFunctionBegin; 2264 /* Check matrix local sizes */ 2265 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 2266 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 2267 2268 /* Set "nonscalable" as default algorithm */ 2269 ierr = PetscStrcmp(C->product->alg,"default",&flg);CHKERRQ(ierr); 2270 if (flg) { 2271 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2272 2273 /* Set "scalable" as default if BN and local nonzeros of A and B are large */ 2274 if (B->cmap->N > 100000) { /* may switch to scalable algorithm as default */ 2275 MatInfo Ainfo,Binfo; 2276 PetscInt nz_local; 2277 PetscBool alg_scalable_loc=PETSC_FALSE,alg_scalable; 2278 2279 ierr = MatGetInfo(A,MAT_LOCAL,&Ainfo);CHKERRQ(ierr); 2280 ierr = MatGetInfo(B,MAT_LOCAL,&Binfo);CHKERRQ(ierr); 2281 nz_local = (PetscInt)(Ainfo.nz_allocated + Binfo.nz_allocated); 2282 2283 if (B->cmap->N > product->fill*nz_local) alg_scalable_loc = PETSC_TRUE; 2284 ierr = MPIU_Allreduce(&alg_scalable_loc,&alg_scalable,1,MPIU_BOOL,MPI_LOR,comm);CHKERRQ(ierr); 2285 2286 if (alg_scalable) { 2287 alg = 0; /* scalable algorithm would 50% slower than nonscalable algorithm */ 2288 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2289 ierr = PetscInfo2(B,"Use scalable algorithm, BN %D, fill*nz_allocated %g\n",B->cmap->N,product->fill*nz_local);CHKERRQ(ierr); 2290 } 2291 } 2292 } 2293 2294 /* Get runtime option */ 2295 if (product->api_user) { 2296 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatMatMult","Mat");CHKERRQ(ierr); 2297 ierr = PetscOptionsEList("-matmatmult_via","Algorithmic approach","MatMatMult",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2298 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2299 } else { 2300 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatProduct_AB","Mat");CHKERRQ(ierr); 2301 ierr = PetscOptionsEList("-matproduct_ab_via","Algorithmic approach","MatMatMult",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2302 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2303 } 2304 if (flg) { 2305 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2306 } 2307 2308 C->ops->productsymbolic = MatProductSymbolic_AB_MPIAIJ_MPIAIJ; 2309 PetscFunctionReturn(0); 2310 } 2311 2312 /* Set options for MatTransposeMatMultXXX_MPIAIJ_MPIAIJ */ 2313 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_AtB(Mat C) 2314 { 2315 PetscErrorCode ierr; 2316 Mat_Product *product = C->product; 2317 Mat A=product->A,B=product->B; 2318 const char *algTypes[3] = {"scalable","nonscalable","at*b"}; 2319 PetscInt nalg = 3; 2320 PetscInt alg = 1; /* set default algorithm */ 2321 PetscBool flg; 2322 MPI_Comm comm; 2323 2324 PetscFunctionBegin; 2325 /* Check matrix local sizes */ 2326 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 2327 if (A->rmap->rstart != B->rmap->rstart || A->rmap->rend != B->rmap->rend) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A (%D, %D) != B (%D,%D)",A->rmap->rstart,A->rmap->rend,B->rmap->rstart,B->rmap->rend); 2328 2329 /* Set default algorithm */ 2330 ierr = PetscStrcmp(C->product->alg,"default",&flg);CHKERRQ(ierr); 2331 if (flg) { 2332 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2333 } 2334 2335 /* Set "scalable" as default if BN and local nonzeros of A and B are large */ 2336 if (alg && B->cmap->N > 100000) { /* may switch to scalable algorithm as default */ 2337 MatInfo Ainfo,Binfo; 2338 PetscInt nz_local; 2339 PetscBool alg_scalable_loc=PETSC_FALSE,alg_scalable; 2340 2341 ierr = MatGetInfo(A,MAT_LOCAL,&Ainfo);CHKERRQ(ierr); 2342 ierr = MatGetInfo(B,MAT_LOCAL,&Binfo);CHKERRQ(ierr); 2343 nz_local = (PetscInt)(Ainfo.nz_allocated + Binfo.nz_allocated); 2344 2345 if (B->cmap->N > product->fill*nz_local) alg_scalable_loc = PETSC_TRUE; 2346 ierr = MPIU_Allreduce(&alg_scalable_loc,&alg_scalable,1,MPIU_BOOL,MPI_LOR,comm);CHKERRQ(ierr); 2347 2348 if (alg_scalable) { 2349 alg = 0; /* scalable algorithm would 50% slower than nonscalable algorithm */ 2350 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2351 ierr = PetscInfo2(B,"Use scalable algorithm, BN %D, fill*nz_allocated %g\n",B->cmap->N,product->fill*nz_local);CHKERRQ(ierr); 2352 } 2353 } 2354 2355 /* Get runtime option */ 2356 if (product->api_user) { 2357 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatTransposeMatMult","Mat");CHKERRQ(ierr); 2358 ierr = PetscOptionsEList("-mattransposematmult_via","Algorithmic approach","MatTransposeMatMult",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2359 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2360 } else { 2361 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatProduct_AtB","Mat");CHKERRQ(ierr); 2362 ierr = PetscOptionsEList("-matproduct_atb_via","Algorithmic approach","MatTransposeMatMult",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2363 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2364 } 2365 if (flg) { 2366 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2367 } 2368 2369 C->ops->productsymbolic = MatProductSymbolic_AtB_MPIAIJ_MPIAIJ; 2370 PetscFunctionReturn(0); 2371 } 2372 2373 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_PtAP(Mat C) 2374 { 2375 PetscErrorCode ierr; 2376 Mat_Product *product = C->product; 2377 Mat A=product->A,P=product->B; 2378 MPI_Comm comm; 2379 PetscBool flg; 2380 PetscInt alg=1; /* set default algorithm */ 2381 #if !defined(PETSC_HAVE_HYPRE) 2382 const char *algTypes[4] = {"scalable","nonscalable","allatonce","allatonce_merged"}; 2383 PetscInt nalg=4; 2384 #else 2385 const char *algTypes[5] = {"scalable","nonscalable","allatonce","allatonce_merged","hypre"}; 2386 PetscInt nalg=5; 2387 #endif 2388 PetscInt pN=P->cmap->N; 2389 2390 PetscFunctionBegin; 2391 /* Check matrix local sizes */ 2392 ierr = PetscObjectGetComm((PetscObject)C,&comm);CHKERRQ(ierr); 2393 if (A->rmap->rstart != P->rmap->rstart || A->rmap->rend != P->rmap->rend) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, Arow (%D, %D) != Prow (%D,%D)",A->rmap->rstart,A->rmap->rend,P->rmap->rstart,P->rmap->rend); 2394 if (A->cmap->rstart != P->rmap->rstart || A->cmap->rend != P->rmap->rend) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, Acol (%D, %D) != Prow (%D,%D)",A->cmap->rstart,A->cmap->rend,P->rmap->rstart,P->rmap->rend); 2395 2396 /* Set "nonscalable" as default algorithm */ 2397 ierr = PetscStrcmp(C->product->alg,"default",&flg);CHKERRQ(ierr); 2398 if (flg) { 2399 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2400 2401 /* Set "scalable" as default if BN and local nonzeros of A and B are large */ 2402 if (pN > 100000) { 2403 MatInfo Ainfo,Pinfo; 2404 PetscInt nz_local; 2405 PetscBool alg_scalable_loc=PETSC_FALSE,alg_scalable; 2406 2407 ierr = MatGetInfo(A,MAT_LOCAL,&Ainfo);CHKERRQ(ierr); 2408 ierr = MatGetInfo(P,MAT_LOCAL,&Pinfo);CHKERRQ(ierr); 2409 nz_local = (PetscInt)(Ainfo.nz_allocated + Pinfo.nz_allocated); 2410 2411 if (pN > product->fill*nz_local) alg_scalable_loc = PETSC_TRUE; 2412 ierr = MPIU_Allreduce(&alg_scalable_loc,&alg_scalable,1,MPIU_BOOL,MPI_LOR,comm);CHKERRQ(ierr); 2413 2414 if (alg_scalable) { 2415 alg = 0; /* scalable algorithm would 50% slower than nonscalable algorithm */ 2416 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2417 } 2418 } 2419 } 2420 2421 /* Get runtime option */ 2422 if (product->api_user) { 2423 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatPtAP","Mat");CHKERRQ(ierr); 2424 ierr = PetscOptionsEList("-matptap_via","Algorithmic approach","MatPtAP",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2425 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2426 } else { 2427 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatProduct_PtAP","Mat");CHKERRQ(ierr); 2428 ierr = PetscOptionsEList("-matproduct_ptap_via","Algorithmic approach","MatPtAP",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2429 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2430 } 2431 if (flg) { 2432 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2433 } 2434 2435 C->ops->productsymbolic = MatProductSymbolic_PtAP_MPIAIJ_MPIAIJ; 2436 PetscFunctionReturn(0); 2437 } 2438 2439 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_RARt(Mat C) 2440 { 2441 Mat_Product *product = C->product; 2442 Mat A = product->A,R=product->B; 2443 2444 PetscFunctionBegin; 2445 /* Check matrix local sizes */ 2446 if (A->cmap->n != R->cmap->n || A->rmap->n != R->cmap->n) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A local (%D, %D), R local (%D,%D)",A->rmap->n,A->rmap->n,R->rmap->n,R->cmap->n); 2447 2448 C->ops->productsymbolic = MatProductSymbolic_RARt_MPIAIJ_MPIAIJ; 2449 PetscFunctionReturn(0); 2450 } 2451 2452 /* 2453 Set options for ABC = A*B*C = A*(B*C); ABC's algorithm must be chosen from AB's algorithm 2454 */ 2455 static PetscErrorCode MatProductSetFromOptions_MPIAIJ_ABC(Mat C) 2456 { 2457 PetscErrorCode ierr; 2458 Mat_Product *product = C->product; 2459 PetscBool flg = PETSC_FALSE; 2460 PetscInt alg = 1; /* default algorithm */ 2461 const char *algTypes[3] = {"scalable","nonscalable","seqmpi"}; 2462 PetscInt nalg = 3; 2463 2464 PetscFunctionBegin; 2465 /* Set default algorithm */ 2466 ierr = PetscStrcmp(C->product->alg,"default",&flg);CHKERRQ(ierr); 2467 if (flg) { 2468 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2469 } 2470 2471 /* Get runtime option */ 2472 if (product->api_user) { 2473 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatMatMatMult","Mat");CHKERRQ(ierr); 2474 ierr = PetscOptionsEList("-matmatmatmult_via","Algorithmic approach","MatMatMatMult",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2475 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2476 } else { 2477 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)C),((PetscObject)C)->prefix,"MatProduct_ABC","Mat");CHKERRQ(ierr); 2478 ierr = PetscOptionsEList("-matproduct_abc_via","Algorithmic approach","MatProduct_ABC",algTypes,nalg,algTypes[alg],&alg,&flg);CHKERRQ(ierr); 2479 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2480 } 2481 if (flg) { 2482 ierr = MatProductSetAlgorithm(C,(MatProductAlgorithm)algTypes[alg]);CHKERRQ(ierr); 2483 } 2484 2485 C->ops->matmatmultsymbolic = MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ; 2486 C->ops->productsymbolic = MatProductSymbolic_ABC; 2487 PetscFunctionReturn(0); 2488 } 2489 2490 PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIAIJ(Mat C) 2491 { 2492 PetscErrorCode ierr; 2493 Mat_Product *product = C->product; 2494 2495 PetscFunctionBegin; 2496 switch (product->type) { 2497 case MATPRODUCT_AB: 2498 ierr = MatProductSetFromOptions_MPIAIJ_AB(C);CHKERRQ(ierr); 2499 break; 2500 case MATPRODUCT_AtB: 2501 ierr = MatProductSetFromOptions_MPIAIJ_AtB(C);CHKERRQ(ierr); 2502 break; 2503 case MATPRODUCT_PtAP: 2504 ierr = MatProductSetFromOptions_MPIAIJ_PtAP(C);CHKERRQ(ierr); 2505 break; 2506 case MATPRODUCT_RARt: 2507 ierr = MatProductSetFromOptions_MPIAIJ_RARt(C);CHKERRQ(ierr); 2508 break; 2509 case MATPRODUCT_ABC: 2510 ierr = MatProductSetFromOptions_MPIAIJ_ABC(C);CHKERRQ(ierr); 2511 break; 2512 default: SETERRQ1(PetscObjectComm((PetscObject)C),PETSC_ERR_SUP,"MatProduct type %s is not supported for MPIAIJ and MPIAIJ matrices",MatProductTypes[product->type]); 2513 } 2514 PetscFunctionReturn(0); 2515 } 2516