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