1 #define PETSCMAT_DLL 2 3 #include "../src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 5 EXTERN PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 EXTERN PetscErrorCode DisAssemble_MPIBAIJ(Mat); 7 EXTERN PetscErrorCode MatIncreaseOverlap_MPIBAIJ(Mat,PetscInt,IS[],PetscInt); 8 EXTERN PetscErrorCode MatGetSubMatrices_MPIBAIJ(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]); 9 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 10 EXTERN PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 11 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 12 EXTERN PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 13 EXTERN PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 14 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar); 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 18 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 19 { 20 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 21 PetscErrorCode ierr; 22 PetscInt i,*idxb = 0; 23 PetscScalar *va,*vb; 24 Vec vtmp; 25 26 PetscFunctionBegin; 27 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 28 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 29 if (idx) { 30 for (i=0; i<A->rmap->n; i++) {if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;} 31 } 32 33 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 34 if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);} 35 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 36 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 37 38 for (i=0; i<A->rmap->n; i++){ 39 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {va[i] = vb[i]; if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);} 40 } 41 42 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 43 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 44 if (idxb) {ierr = PetscFree(idxb);CHKERRQ(ierr);} 45 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 46 PetscFunctionReturn(0); 47 } 48 49 EXTERN_C_BEGIN 50 #undef __FUNCT__ 51 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 52 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIBAIJ(Mat mat) 53 { 54 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 55 PetscErrorCode ierr; 56 57 PetscFunctionBegin; 58 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 59 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 60 PetscFunctionReturn(0); 61 } 62 EXTERN_C_END 63 64 EXTERN_C_BEGIN 65 #undef __FUNCT__ 66 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 67 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIBAIJ(Mat mat) 68 { 69 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 70 PetscErrorCode ierr; 71 72 PetscFunctionBegin; 73 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 74 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 75 PetscFunctionReturn(0); 76 } 77 EXTERN_C_END 78 79 /* 80 Local utility routine that creates a mapping from the global column 81 number to the local number in the off-diagonal part of the local 82 storage of the matrix. This is done in a non scable way since the 83 length of colmap equals the global matrix length. 84 */ 85 #undef __FUNCT__ 86 #define __FUNCT__ "CreateColmap_MPIBAIJ_Private" 87 PetscErrorCode CreateColmap_MPIBAIJ_Private(Mat mat) 88 { 89 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 90 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 91 PetscErrorCode ierr; 92 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 93 94 PetscFunctionBegin; 95 #if defined (PETSC_USE_CTABLE) 96 ierr = PetscTableCreate(baij->nbs,&baij->colmap);CHKERRQ(ierr); 97 for (i=0; i<nbs; i++){ 98 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1);CHKERRQ(ierr); 99 } 100 #else 101 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 102 ierr = PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 103 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 104 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 105 #endif 106 PetscFunctionReturn(0); 107 } 108 109 #define CHUNKSIZE 10 110 111 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 112 { \ 113 \ 114 brow = row/bs; \ 115 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 116 rmax = aimax[brow]; nrow = ailen[brow]; \ 117 bcol = col/bs; \ 118 ridx = row % bs; cidx = col % bs; \ 119 low = 0; high = nrow; \ 120 while (high-low > 3) { \ 121 t = (low+high)/2; \ 122 if (rp[t] > bcol) high = t; \ 123 else low = t; \ 124 } \ 125 for (_i=low; _i<high; _i++) { \ 126 if (rp[_i] > bcol) break; \ 127 if (rp[_i] == bcol) { \ 128 bap = ap + bs2*_i + bs*cidx + ridx; \ 129 if (addv == ADD_VALUES) *bap += value; \ 130 else *bap = value; \ 131 goto a_noinsert; \ 132 } \ 133 } \ 134 if (a->nonew == 1) goto a_noinsert; \ 135 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 136 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 137 N = nrow++ - 1; \ 138 /* shift up all the later entries in this row */ \ 139 for (ii=N; ii>=_i; ii--) { \ 140 rp[ii+1] = rp[ii]; \ 141 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 142 } \ 143 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 144 rp[_i] = bcol; \ 145 ap[bs2*_i + bs*cidx + ridx] = value; \ 146 a_noinsert:; \ 147 ailen[brow] = nrow; \ 148 } 149 150 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 151 { \ 152 brow = row/bs; \ 153 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 154 rmax = bimax[brow]; nrow = bilen[brow]; \ 155 bcol = col/bs; \ 156 ridx = row % bs; cidx = col % bs; \ 157 low = 0; high = nrow; \ 158 while (high-low > 3) { \ 159 t = (low+high)/2; \ 160 if (rp[t] > bcol) high = t; \ 161 else low = t; \ 162 } \ 163 for (_i=low; _i<high; _i++) { \ 164 if (rp[_i] > bcol) break; \ 165 if (rp[_i] == bcol) { \ 166 bap = ap + bs2*_i + bs*cidx + ridx; \ 167 if (addv == ADD_VALUES) *bap += value; \ 168 else *bap = value; \ 169 goto b_noinsert; \ 170 } \ 171 } \ 172 if (b->nonew == 1) goto b_noinsert; \ 173 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 174 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 175 CHKMEMQ;\ 176 N = nrow++ - 1; \ 177 /* shift up all the later entries in this row */ \ 178 for (ii=N; ii>=_i; ii--) { \ 179 rp[ii+1] = rp[ii]; \ 180 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 181 } \ 182 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 183 rp[_i] = bcol; \ 184 ap[bs2*_i + bs*cidx + ridx] = value; \ 185 b_noinsert:; \ 186 bilen[brow] = nrow; \ 187 } 188 189 #undef __FUNCT__ 190 #define __FUNCT__ "MatSetValues_MPIBAIJ" 191 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 192 { 193 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 194 MatScalar value; 195 PetscTruth roworiented = baij->roworiented; 196 PetscErrorCode ierr; 197 PetscInt i,j,row,col; 198 PetscInt rstart_orig=mat->rmap->rstart; 199 PetscInt rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart; 200 PetscInt cend_orig=mat->cmap->rend,bs=mat->rmap->bs; 201 202 /* Some Variables required in the macro */ 203 Mat A = baij->A; 204 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 205 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 206 MatScalar *aa=a->a; 207 208 Mat B = baij->B; 209 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 210 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 211 MatScalar *ba=b->a; 212 213 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 214 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 215 MatScalar *ap,*bap; 216 217 PetscFunctionBegin; 218 for (i=0; i<m; i++) { 219 if (im[i] < 0) continue; 220 #if defined(PETSC_USE_DEBUG) 221 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 222 #endif 223 if (im[i] >= rstart_orig && im[i] < rend_orig) { 224 row = im[i] - rstart_orig; 225 for (j=0; j<n; j++) { 226 if (in[j] >= cstart_orig && in[j] < cend_orig){ 227 col = in[j] - cstart_orig; 228 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 229 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 230 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 231 } else if (in[j] < 0) continue; 232 #if defined(PETSC_USE_DEBUG) 233 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[i],mat->cmap->N-1);} 234 #endif 235 else { 236 if (mat->was_assembled) { 237 if (!baij->colmap) { 238 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 239 } 240 #if defined (PETSC_USE_CTABLE) 241 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 242 col = col - 1; 243 #else 244 col = baij->colmap[in[j]/bs] - 1; 245 #endif 246 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 247 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 248 col = in[j]; 249 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 250 B = baij->B; 251 b = (Mat_SeqBAIJ*)(B)->data; 252 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 253 ba=b->a; 254 } else col += in[j]%bs; 255 } else col = in[j]; 256 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 257 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 258 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 259 } 260 } 261 } else { 262 if (!baij->donotstash) { 263 if (roworiented) { 264 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 265 } else { 266 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 267 } 268 } 269 } 270 } 271 PetscFunctionReturn(0); 272 } 273 274 #undef __FUNCT__ 275 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 276 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 277 { 278 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 279 const PetscScalar *value; 280 MatScalar *barray=baij->barray; 281 PetscTruth roworiented = baij->roworiented; 282 PetscErrorCode ierr; 283 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 284 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 285 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 286 287 PetscFunctionBegin; 288 if(!barray) { 289 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 290 baij->barray = barray; 291 } 292 293 if (roworiented) { 294 stepval = (n-1)*bs; 295 } else { 296 stepval = (m-1)*bs; 297 } 298 for (i=0; i<m; i++) { 299 if (im[i] < 0) continue; 300 #if defined(PETSC_USE_DEBUG) 301 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 302 #endif 303 if (im[i] >= rstart && im[i] < rend) { 304 row = im[i] - rstart; 305 for (j=0; j<n; j++) { 306 /* If NumCol = 1 then a copy is not required */ 307 if ((roworiented) && (n == 1)) { 308 barray = (MatScalar*)v + i*bs2; 309 } else if((!roworiented) && (m == 1)) { 310 barray = (MatScalar*)v + j*bs2; 311 } else { /* Here a copy is required */ 312 if (roworiented) { 313 value = v + i*(stepval+bs)*bs + j*bs; 314 } else { 315 value = v + j*(stepval+bs)*bs + i*bs; 316 } 317 for (ii=0; ii<bs; ii++,value+=stepval) { 318 for (jj=0; jj<bs; jj++) { 319 *barray++ = *value++; 320 } 321 } 322 barray -=bs2; 323 } 324 325 if (in[j] >= cstart && in[j] < cend){ 326 col = in[j] - cstart; 327 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 328 } 329 else if (in[j] < 0) continue; 330 #if defined(PETSC_USE_DEBUG) 331 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 332 #endif 333 else { 334 if (mat->was_assembled) { 335 if (!baij->colmap) { 336 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 337 } 338 339 #if defined(PETSC_USE_DEBUG) 340 #if defined (PETSC_USE_CTABLE) 341 { PetscInt data; 342 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 343 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 344 } 345 #else 346 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 347 #endif 348 #endif 349 #if defined (PETSC_USE_CTABLE) 350 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 351 col = (col - 1)/bs; 352 #else 353 col = (baij->colmap[in[j]] - 1)/bs; 354 #endif 355 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 356 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 357 col = in[j]; 358 } 359 } 360 else col = in[j]; 361 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 362 } 363 } 364 } else { 365 if (!baij->donotstash) { 366 if (roworiented) { 367 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 368 } else { 369 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 370 } 371 } 372 } 373 } 374 PetscFunctionReturn(0); 375 } 376 377 #define HASH_KEY 0.6180339887 378 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 379 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 380 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 381 #undef __FUNCT__ 382 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 383 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 384 { 385 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 386 PetscTruth roworiented = baij->roworiented; 387 PetscErrorCode ierr; 388 PetscInt i,j,row,col; 389 PetscInt rstart_orig=mat->rmap->rstart; 390 PetscInt rend_orig=mat->rmap->rend,Nbs=baij->Nbs; 391 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 392 PetscReal tmp; 393 MatScalar **HD = baij->hd,value; 394 #if defined(PETSC_USE_DEBUG) 395 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 396 #endif 397 398 PetscFunctionBegin; 399 400 for (i=0; i<m; i++) { 401 #if defined(PETSC_USE_DEBUG) 402 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 403 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 404 #endif 405 row = im[i]; 406 if (row >= rstart_orig && row < rend_orig) { 407 for (j=0; j<n; j++) { 408 col = in[j]; 409 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 410 /* Look up PetscInto the Hash Table */ 411 key = (row/bs)*Nbs+(col/bs)+1; 412 h1 = HASH(size,key,tmp); 413 414 415 idx = h1; 416 #if defined(PETSC_USE_DEBUG) 417 insert_ct++; 418 total_ct++; 419 if (HT[idx] != key) { 420 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 421 if (idx == size) { 422 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 423 if (idx == h1) { 424 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 425 } 426 } 427 } 428 #else 429 if (HT[idx] != key) { 430 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 431 if (idx == size) { 432 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 433 if (idx == h1) { 434 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 435 } 436 } 437 } 438 #endif 439 /* A HASH table entry is found, so insert the values at the correct address */ 440 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 441 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 442 } 443 } else { 444 if (!baij->donotstash) { 445 if (roworiented) { 446 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 447 } else { 448 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 449 } 450 } 451 } 452 } 453 #if defined(PETSC_USE_DEBUG) 454 baij->ht_total_ct = total_ct; 455 baij->ht_insert_ct = insert_ct; 456 #endif 457 PetscFunctionReturn(0); 458 } 459 460 #undef __FUNCT__ 461 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 462 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 463 { 464 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 465 PetscTruth roworiented = baij->roworiented; 466 PetscErrorCode ierr; 467 PetscInt i,j,ii,jj,row,col; 468 PetscInt rstart=baij->rstartbs; 469 PetscInt rend=mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 470 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 471 PetscReal tmp; 472 MatScalar **HD = baij->hd,*baij_a; 473 const PetscScalar *v_t,*value; 474 #if defined(PETSC_USE_DEBUG) 475 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 476 #endif 477 478 PetscFunctionBegin; 479 480 if (roworiented) { 481 stepval = (n-1)*bs; 482 } else { 483 stepval = (m-1)*bs; 484 } 485 for (i=0; i<m; i++) { 486 #if defined(PETSC_USE_DEBUG) 487 if (im[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 488 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 489 #endif 490 row = im[i]; 491 v_t = v + i*nbs2; 492 if (row >= rstart && row < rend) { 493 for (j=0; j<n; j++) { 494 col = in[j]; 495 496 /* Look up into the Hash Table */ 497 key = row*Nbs+col+1; 498 h1 = HASH(size,key,tmp); 499 500 idx = h1; 501 #if defined(PETSC_USE_DEBUG) 502 total_ct++; 503 insert_ct++; 504 if (HT[idx] != key) { 505 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 506 if (idx == size) { 507 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 508 if (idx == h1) { 509 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 510 } 511 } 512 } 513 #else 514 if (HT[idx] != key) { 515 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 516 if (idx == size) { 517 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 518 if (idx == h1) { 519 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 520 } 521 } 522 } 523 #endif 524 baij_a = HD[idx]; 525 if (roworiented) { 526 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 527 /* value = v + (i*(stepval+bs)+j)*bs; */ 528 value = v_t; 529 v_t += bs; 530 if (addv == ADD_VALUES) { 531 for (ii=0; ii<bs; ii++,value+=stepval) { 532 for (jj=ii; jj<bs2; jj+=bs) { 533 baij_a[jj] += *value++; 534 } 535 } 536 } else { 537 for (ii=0; ii<bs; ii++,value+=stepval) { 538 for (jj=ii; jj<bs2; jj+=bs) { 539 baij_a[jj] = *value++; 540 } 541 } 542 } 543 } else { 544 value = v + j*(stepval+bs)*bs + i*bs; 545 if (addv == ADD_VALUES) { 546 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 547 for (jj=0; jj<bs; jj++) { 548 baij_a[jj] += *value++; 549 } 550 } 551 } else { 552 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 553 for (jj=0; jj<bs; jj++) { 554 baij_a[jj] = *value++; 555 } 556 } 557 } 558 } 559 } 560 } else { 561 if (!baij->donotstash) { 562 if (roworiented) { 563 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 564 } else { 565 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 566 } 567 } 568 } 569 } 570 #if defined(PETSC_USE_DEBUG) 571 baij->ht_total_ct = total_ct; 572 baij->ht_insert_ct = insert_ct; 573 #endif 574 PetscFunctionReturn(0); 575 } 576 577 #undef __FUNCT__ 578 #define __FUNCT__ "MatGetValues_MPIBAIJ" 579 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 580 { 581 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 582 PetscErrorCode ierr; 583 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 584 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 585 586 PetscFunctionBegin; 587 for (i=0; i<m; i++) { 588 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 589 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 590 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 591 row = idxm[i] - bsrstart; 592 for (j=0; j<n; j++) { 593 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 594 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 595 if (idxn[j] >= bscstart && idxn[j] < bscend){ 596 col = idxn[j] - bscstart; 597 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 598 } else { 599 if (!baij->colmap) { 600 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 601 } 602 #if defined (PETSC_USE_CTABLE) 603 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 604 data --; 605 #else 606 data = baij->colmap[idxn[j]/bs]-1; 607 #endif 608 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 609 else { 610 col = data + idxn[j]%bs; 611 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 612 } 613 } 614 } 615 } else { 616 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 617 } 618 } 619 PetscFunctionReturn(0); 620 } 621 622 #undef __FUNCT__ 623 #define __FUNCT__ "MatNorm_MPIBAIJ" 624 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 625 { 626 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 627 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 628 PetscErrorCode ierr; 629 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 630 PetscReal sum = 0.0; 631 MatScalar *v; 632 633 PetscFunctionBegin; 634 if (baij->size == 1) { 635 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 636 } else { 637 if (type == NORM_FROBENIUS) { 638 v = amat->a; 639 nz = amat->nz*bs2; 640 for (i=0; i<nz; i++) { 641 #if defined(PETSC_USE_COMPLEX) 642 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 643 #else 644 sum += (*v)*(*v); v++; 645 #endif 646 } 647 v = bmat->a; 648 nz = bmat->nz*bs2; 649 for (i=0; i<nz; i++) { 650 #if defined(PETSC_USE_COMPLEX) 651 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 652 #else 653 sum += (*v)*(*v); v++; 654 #endif 655 } 656 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 657 *nrm = sqrt(*nrm); 658 } else if (type == NORM_1) { /* max column sum */ 659 PetscReal *tmp,*tmp2; 660 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 661 ierr = PetscMalloc((2*mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 662 tmp2 = tmp + mat->cmap->N; 663 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 664 v = amat->a; jj = amat->j; 665 for (i=0; i<amat->nz; i++) { 666 for (j=0; j<bs; j++){ 667 col = bs*(cstart + *jj) + j; /* column index */ 668 for (row=0; row<bs; row++){ 669 tmp[col] += PetscAbsScalar(*v); v++; 670 } 671 } 672 jj++; 673 } 674 v = bmat->a; jj = bmat->j; 675 for (i=0; i<bmat->nz; i++) { 676 for (j=0; j<bs; j++){ 677 col = bs*garray[*jj] + j; 678 for (row=0; row<bs; row++){ 679 tmp[col] += PetscAbsScalar(*v); v++; 680 } 681 } 682 jj++; 683 } 684 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 685 *nrm = 0.0; 686 for (j=0; j<mat->cmap->N; j++) { 687 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 688 } 689 ierr = PetscFree(tmp);CHKERRQ(ierr); 690 } else if (type == NORM_INFINITY) { /* max row sum */ 691 PetscReal *sums; 692 ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr) 693 sum = 0.0; 694 for (j=0; j<amat->mbs; j++) { 695 for (row=0; row<bs; row++) sums[row] = 0.0; 696 v = amat->a + bs2*amat->i[j]; 697 nz = amat->i[j+1]-amat->i[j]; 698 for (i=0; i<nz; i++) { 699 for (col=0; col<bs; col++){ 700 for (row=0; row<bs; row++){ 701 sums[row] += PetscAbsScalar(*v); v++; 702 } 703 } 704 } 705 v = bmat->a + bs2*bmat->i[j]; 706 nz = bmat->i[j+1]-bmat->i[j]; 707 for (i=0; i<nz; i++) { 708 for (col=0; col<bs; col++){ 709 for (row=0; row<bs; row++){ 710 sums[row] += PetscAbsScalar(*v); v++; 711 } 712 } 713 } 714 for (row=0; row<bs; row++){ 715 if (sums[row] > sum) sum = sums[row]; 716 } 717 } 718 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 719 ierr = PetscFree(sums);CHKERRQ(ierr); 720 } else { 721 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 722 } 723 } 724 PetscFunctionReturn(0); 725 } 726 727 /* 728 Creates the hash table, and sets the table 729 This table is created only once. 730 If new entried need to be added to the matrix 731 then the hash table has to be destroyed and 732 recreated. 733 */ 734 #undef __FUNCT__ 735 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 736 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 737 { 738 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 739 Mat A = baij->A,B=baij->B; 740 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 741 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 742 PetscErrorCode ierr; 743 PetscInt size,bs2=baij->bs2,rstart=baij->rstartbs; 744 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 745 PetscInt *HT,key; 746 MatScalar **HD; 747 PetscReal tmp; 748 #if defined(PETSC_USE_INFO) 749 PetscInt ct=0,max=0; 750 #endif 751 752 PetscFunctionBegin; 753 baij->ht_size=(PetscInt)(factor*nz); 754 size = baij->ht_size; 755 756 if (baij->ht) { 757 PetscFunctionReturn(0); 758 } 759 760 /* Allocate Memory for Hash Table */ 761 ierr = PetscMalloc((size)*(sizeof(PetscInt)+sizeof(MatScalar*))+1,&baij->hd);CHKERRQ(ierr); 762 baij->ht = (PetscInt*)(baij->hd + size); 763 HD = baij->hd; 764 HT = baij->ht; 765 766 767 ierr = PetscMemzero(HD,size*(sizeof(PetscInt)+sizeof(PetscScalar*)));CHKERRQ(ierr); 768 769 770 /* Loop Over A */ 771 for (i=0; i<a->mbs; i++) { 772 for (j=ai[i]; j<ai[i+1]; j++) { 773 row = i+rstart; 774 col = aj[j]+cstart; 775 776 key = row*Nbs + col + 1; 777 h1 = HASH(size,key,tmp); 778 for (k=0; k<size; k++){ 779 if (!HT[(h1+k)%size]) { 780 HT[(h1+k)%size] = key; 781 HD[(h1+k)%size] = a->a + j*bs2; 782 break; 783 #if defined(PETSC_USE_INFO) 784 } else { 785 ct++; 786 #endif 787 } 788 } 789 #if defined(PETSC_USE_INFO) 790 if (k> max) max = k; 791 #endif 792 } 793 } 794 /* Loop Over B */ 795 for (i=0; i<b->mbs; i++) { 796 for (j=bi[i]; j<bi[i+1]; j++) { 797 row = i+rstart; 798 col = garray[bj[j]]; 799 key = row*Nbs + col + 1; 800 h1 = HASH(size,key,tmp); 801 for (k=0; k<size; k++){ 802 if (!HT[(h1+k)%size]) { 803 HT[(h1+k)%size] = key; 804 HD[(h1+k)%size] = b->a + j*bs2; 805 break; 806 #if defined(PETSC_USE_INFO) 807 } else { 808 ct++; 809 #endif 810 } 811 } 812 #if defined(PETSC_USE_INFO) 813 if (k> max) max = k; 814 #endif 815 } 816 } 817 818 /* Print Summary */ 819 #if defined(PETSC_USE_INFO) 820 for (i=0,j=0; i<size; i++) { 821 if (HT[i]) {j++;} 822 } 823 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 824 #endif 825 PetscFunctionReturn(0); 826 } 827 828 #undef __FUNCT__ 829 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 830 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 831 { 832 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 833 PetscErrorCode ierr; 834 PetscInt nstash,reallocs; 835 InsertMode addv; 836 837 PetscFunctionBegin; 838 if (baij->donotstash) { 839 PetscFunctionReturn(0); 840 } 841 842 /* make sure all processors are either in INSERTMODE or ADDMODE */ 843 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 844 if (addv == (ADD_VALUES|INSERT_VALUES)) { 845 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 846 } 847 mat->insertmode = addv; /* in case this processor had no cache */ 848 849 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 850 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 851 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 852 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 853 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 854 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 855 PetscFunctionReturn(0); 856 } 857 858 #undef __FUNCT__ 859 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 860 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 861 { 862 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 863 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data; 864 PetscErrorCode ierr; 865 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 866 PetscInt *row,*col; 867 PetscTruth r1,r2,r3,other_disassembled; 868 MatScalar *val; 869 InsertMode addv = mat->insertmode; 870 PetscMPIInt n; 871 872 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 873 PetscFunctionBegin; 874 if (!baij->donotstash) { 875 while (1) { 876 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 877 if (!flg) break; 878 879 for (i=0; i<n;) { 880 /* Now identify the consecutive vals belonging to the same row */ 881 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 882 if (j < n) ncols = j-i; 883 else ncols = n-i; 884 /* Now assemble all these values with a single function call */ 885 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 886 i = j; 887 } 888 } 889 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 890 /* Now process the block-stash. Since the values are stashed column-oriented, 891 set the roworiented flag to column oriented, and after MatSetValues() 892 restore the original flags */ 893 r1 = baij->roworiented; 894 r2 = a->roworiented; 895 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 896 baij->roworiented = PETSC_FALSE; 897 a->roworiented = PETSC_FALSE; 898 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 899 while (1) { 900 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 901 if (!flg) break; 902 903 for (i=0; i<n;) { 904 /* Now identify the consecutive vals belonging to the same row */ 905 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 906 if (j < n) ncols = j-i; 907 else ncols = n-i; 908 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 909 i = j; 910 } 911 } 912 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 913 baij->roworiented = r1; 914 a->roworiented = r2; 915 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 916 } 917 918 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 919 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 920 921 /* determine if any processor has disassembled, if so we must 922 also disassemble ourselfs, in order that we may reassemble. */ 923 /* 924 if nonzero structure of submatrix B cannot change then we know that 925 no processor disassembled thus we can skip this stuff 926 */ 927 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 928 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 929 if (mat->was_assembled && !other_disassembled) { 930 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 931 } 932 } 933 934 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 935 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 936 } 937 ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 938 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 939 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 940 941 #if defined(PETSC_USE_INFO) 942 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 943 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 944 baij->ht_total_ct = 0; 945 baij->ht_insert_ct = 0; 946 } 947 #endif 948 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 949 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 950 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 951 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 952 } 953 954 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 955 baij->rowvalues = 0; 956 PetscFunctionReturn(0); 957 } 958 959 #undef __FUNCT__ 960 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 961 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 962 { 963 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 964 PetscErrorCode ierr; 965 PetscMPIInt size = baij->size,rank = baij->rank; 966 PetscInt bs = mat->rmap->bs; 967 PetscTruth iascii,isdraw; 968 PetscViewer sviewer; 969 PetscViewerFormat format; 970 971 PetscFunctionBegin; 972 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 973 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 974 if (iascii) { 975 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 976 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 977 MatInfo info; 978 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 979 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 980 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 981 rank,mat->rmap->N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 982 mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 983 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 984 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 985 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 986 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 987 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 988 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 989 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 990 PetscFunctionReturn(0); 991 } else if (format == PETSC_VIEWER_ASCII_INFO) { 992 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 993 PetscFunctionReturn(0); 994 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 995 PetscFunctionReturn(0); 996 } 997 } 998 999 if (isdraw) { 1000 PetscDraw draw; 1001 PetscTruth isnull; 1002 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1003 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1004 } 1005 1006 if (size == 1) { 1007 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1008 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1009 } else { 1010 /* assemble the entire matrix onto first processor. */ 1011 Mat A; 1012 Mat_SeqBAIJ *Aloc; 1013 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1014 MatScalar *a; 1015 1016 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1017 /* Perhaps this should be the type of mat? */ 1018 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1019 if (!rank) { 1020 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1021 } else { 1022 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1023 } 1024 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1025 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1026 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1027 1028 /* copy over the A part */ 1029 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1030 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1031 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1032 1033 for (i=0; i<mbs; i++) { 1034 rvals[0] = bs*(baij->rstartbs + i); 1035 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1036 for (j=ai[i]; j<ai[i+1]; j++) { 1037 col = (baij->cstartbs+aj[j])*bs; 1038 for (k=0; k<bs; k++) { 1039 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1040 col++; a += bs; 1041 } 1042 } 1043 } 1044 /* copy over the B part */ 1045 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1046 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1047 for (i=0; i<mbs; i++) { 1048 rvals[0] = bs*(baij->rstartbs + i); 1049 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1050 for (j=ai[i]; j<ai[i+1]; j++) { 1051 col = baij->garray[aj[j]]*bs; 1052 for (k=0; k<bs; k++) { 1053 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1054 col++; a += bs; 1055 } 1056 } 1057 } 1058 ierr = PetscFree(rvals);CHKERRQ(ierr); 1059 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1060 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1061 /* 1062 Everyone has to call to draw the matrix since the graphics waits are 1063 synchronized across all processors that share the PetscDraw object 1064 */ 1065 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1066 if (!rank) { 1067 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1068 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1069 } 1070 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1071 ierr = MatDestroy(A);CHKERRQ(ierr); 1072 } 1073 PetscFunctionReturn(0); 1074 } 1075 1076 #undef __FUNCT__ 1077 #define __FUNCT__ "MatView_MPIBAIJ" 1078 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1079 { 1080 PetscErrorCode ierr; 1081 PetscTruth iascii,isdraw,issocket,isbinary; 1082 1083 PetscFunctionBegin; 1084 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1085 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1086 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1087 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1088 if (iascii || isdraw || issocket || isbinary) { 1089 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1090 } else { 1091 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1092 } 1093 PetscFunctionReturn(0); 1094 } 1095 1096 #undef __FUNCT__ 1097 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1098 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1099 { 1100 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1101 PetscErrorCode ierr; 1102 1103 PetscFunctionBegin; 1104 #if defined(PETSC_USE_LOG) 1105 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1106 #endif 1107 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1108 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1109 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1110 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1111 #if defined (PETSC_USE_CTABLE) 1112 if (baij->colmap) {ierr = PetscTableDestroy(baij->colmap);CHKERRQ(ierr);} 1113 #else 1114 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1115 #endif 1116 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1117 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1118 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1119 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 1120 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1121 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 1122 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1123 ierr = PetscFree(baij);CHKERRQ(ierr); 1124 1125 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1127 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1128 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1129 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1130 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1131 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1132 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "MatMult_MPIBAIJ" 1138 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1139 { 1140 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1141 PetscErrorCode ierr; 1142 PetscInt nt; 1143 1144 PetscFunctionBegin; 1145 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1146 if (nt != A->cmap->n) { 1147 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1148 } 1149 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1150 if (nt != A->rmap->n) { 1151 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1152 } 1153 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1154 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1155 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1156 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1157 PetscFunctionReturn(0); 1158 } 1159 1160 #undef __FUNCT__ 1161 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1162 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1163 { 1164 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1165 PetscErrorCode ierr; 1166 1167 PetscFunctionBegin; 1168 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1169 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1170 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1171 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1172 PetscFunctionReturn(0); 1173 } 1174 1175 #undef __FUNCT__ 1176 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1177 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1178 { 1179 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1180 PetscErrorCode ierr; 1181 PetscTruth merged; 1182 1183 PetscFunctionBegin; 1184 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1185 /* do nondiagonal part */ 1186 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1187 if (!merged) { 1188 /* send it on its way */ 1189 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1190 /* do local part */ 1191 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1192 /* receive remote parts: note this assumes the values are not actually */ 1193 /* inserted in yy until the next line */ 1194 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1195 } else { 1196 /* do local part */ 1197 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1198 /* send it on its way */ 1199 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1200 /* values actually were received in the Begin() but we need to call this nop */ 1201 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1202 } 1203 PetscFunctionReturn(0); 1204 } 1205 1206 #undef __FUNCT__ 1207 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1208 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1209 { 1210 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1211 PetscErrorCode ierr; 1212 1213 PetscFunctionBegin; 1214 /* do nondiagonal part */ 1215 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1216 /* send it on its way */ 1217 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1218 /* do local part */ 1219 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1220 /* receive remote parts: note this assumes the values are not actually */ 1221 /* inserted in yy until the next line, which is true for my implementation*/ 1222 /* but is not perhaps always true. */ 1223 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1224 PetscFunctionReturn(0); 1225 } 1226 1227 /* 1228 This only works correctly for square matrices where the subblock A->A is the 1229 diagonal block 1230 */ 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1233 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1234 { 1235 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1236 PetscErrorCode ierr; 1237 1238 PetscFunctionBegin; 1239 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1240 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatScale_MPIBAIJ" 1246 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1247 { 1248 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1249 PetscErrorCode ierr; 1250 1251 PetscFunctionBegin; 1252 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1253 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1254 PetscFunctionReturn(0); 1255 } 1256 1257 #undef __FUNCT__ 1258 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1259 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1260 { 1261 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1262 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1263 PetscErrorCode ierr; 1264 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1265 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1266 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1267 1268 PetscFunctionBegin; 1269 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1270 mat->getrowactive = PETSC_TRUE; 1271 1272 if (!mat->rowvalues && (idx || v)) { 1273 /* 1274 allocate enough space to hold information from the longest row. 1275 */ 1276 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1277 PetscInt max = 1,mbs = mat->mbs,tmp; 1278 for (i=0; i<mbs; i++) { 1279 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1280 if (max < tmp) { max = tmp; } 1281 } 1282 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1283 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1284 } 1285 1286 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1287 lrow = row - brstart; 1288 1289 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1290 if (!v) {pvA = 0; pvB = 0;} 1291 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1292 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1293 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1294 nztot = nzA + nzB; 1295 1296 cmap = mat->garray; 1297 if (v || idx) { 1298 if (nztot) { 1299 /* Sort by increasing column numbers, assuming A and B already sorted */ 1300 PetscInt imark = -1; 1301 if (v) { 1302 *v = v_p = mat->rowvalues; 1303 for (i=0; i<nzB; i++) { 1304 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1305 else break; 1306 } 1307 imark = i; 1308 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1309 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1310 } 1311 if (idx) { 1312 *idx = idx_p = mat->rowindices; 1313 if (imark > -1) { 1314 for (i=0; i<imark; i++) { 1315 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1316 } 1317 } else { 1318 for (i=0; i<nzB; i++) { 1319 if (cmap[cworkB[i]/bs] < cstart) 1320 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1321 else break; 1322 } 1323 imark = i; 1324 } 1325 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1326 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1327 } 1328 } else { 1329 if (idx) *idx = 0; 1330 if (v) *v = 0; 1331 } 1332 } 1333 *nz = nztot; 1334 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1335 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1336 PetscFunctionReturn(0); 1337 } 1338 1339 #undef __FUNCT__ 1340 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1341 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1342 { 1343 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1344 1345 PetscFunctionBegin; 1346 if (!baij->getrowactive) { 1347 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1348 } 1349 baij->getrowactive = PETSC_FALSE; 1350 PetscFunctionReturn(0); 1351 } 1352 1353 #undef __FUNCT__ 1354 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1355 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1356 { 1357 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1358 PetscErrorCode ierr; 1359 1360 PetscFunctionBegin; 1361 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1362 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1363 PetscFunctionReturn(0); 1364 } 1365 1366 #undef __FUNCT__ 1367 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1368 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1369 { 1370 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1371 Mat A = a->A,B = a->B; 1372 PetscErrorCode ierr; 1373 PetscReal isend[5],irecv[5]; 1374 1375 PetscFunctionBegin; 1376 info->block_size = (PetscReal)matin->rmap->bs; 1377 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1378 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1379 isend[3] = info->memory; isend[4] = info->mallocs; 1380 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1381 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1382 isend[3] += info->memory; isend[4] += info->mallocs; 1383 if (flag == MAT_LOCAL) { 1384 info->nz_used = isend[0]; 1385 info->nz_allocated = isend[1]; 1386 info->nz_unneeded = isend[2]; 1387 info->memory = isend[3]; 1388 info->mallocs = isend[4]; 1389 } else if (flag == MAT_GLOBAL_MAX) { 1390 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1391 info->nz_used = irecv[0]; 1392 info->nz_allocated = irecv[1]; 1393 info->nz_unneeded = irecv[2]; 1394 info->memory = irecv[3]; 1395 info->mallocs = irecv[4]; 1396 } else if (flag == MAT_GLOBAL_SUM) { 1397 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1398 info->nz_used = irecv[0]; 1399 info->nz_allocated = irecv[1]; 1400 info->nz_unneeded = irecv[2]; 1401 info->memory = irecv[3]; 1402 info->mallocs = irecv[4]; 1403 } else { 1404 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1405 } 1406 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1407 info->fill_ratio_needed = 0; 1408 info->factor_mallocs = 0; 1409 PetscFunctionReturn(0); 1410 } 1411 1412 #undef __FUNCT__ 1413 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1414 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscTruth flg) 1415 { 1416 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1417 PetscErrorCode ierr; 1418 1419 PetscFunctionBegin; 1420 switch (op) { 1421 case MAT_NEW_NONZERO_LOCATIONS: 1422 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1423 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1424 case MAT_KEEP_ZEROED_ROWS: 1425 case MAT_NEW_NONZERO_LOCATION_ERR: 1426 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1427 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1428 break; 1429 case MAT_ROW_ORIENTED: 1430 a->roworiented = flg; 1431 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1432 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1433 break; 1434 case MAT_NEW_DIAGONALS: 1435 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1436 break; 1437 case MAT_IGNORE_OFF_PROC_ENTRIES: 1438 a->donotstash = flg; 1439 break; 1440 case MAT_USE_HASH_TABLE: 1441 a->ht_flag = flg; 1442 break; 1443 case MAT_SYMMETRIC: 1444 case MAT_STRUCTURALLY_SYMMETRIC: 1445 case MAT_HERMITIAN: 1446 case MAT_SYMMETRY_ETERNAL: 1447 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1448 break; 1449 default: 1450 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1451 } 1452 PetscFunctionReturn(0); 1453 } 1454 1455 #undef __FUNCT__ 1456 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1457 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1458 { 1459 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1460 Mat_SeqBAIJ *Aloc; 1461 Mat B; 1462 PetscErrorCode ierr; 1463 PetscInt M=A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1464 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1465 MatScalar *a; 1466 1467 PetscFunctionBegin; 1468 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1469 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1470 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1471 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1472 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1473 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1474 } else { 1475 B = *matout; 1476 } 1477 1478 /* copy over the A part */ 1479 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1480 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1481 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1482 1483 for (i=0; i<mbs; i++) { 1484 rvals[0] = bs*(baij->rstartbs + i); 1485 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1486 for (j=ai[i]; j<ai[i+1]; j++) { 1487 col = (baij->cstartbs+aj[j])*bs; 1488 for (k=0; k<bs; k++) { 1489 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1490 col++; a += bs; 1491 } 1492 } 1493 } 1494 /* copy over the B part */ 1495 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1496 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1497 for (i=0; i<mbs; i++) { 1498 rvals[0] = bs*(baij->rstartbs + i); 1499 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1500 for (j=ai[i]; j<ai[i+1]; j++) { 1501 col = baij->garray[aj[j]]*bs; 1502 for (k=0; k<bs; k++) { 1503 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1504 col++; a += bs; 1505 } 1506 } 1507 } 1508 ierr = PetscFree(rvals);CHKERRQ(ierr); 1509 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1510 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1511 1512 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1513 *matout = B; 1514 } else { 1515 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1516 } 1517 PetscFunctionReturn(0); 1518 } 1519 1520 #undef __FUNCT__ 1521 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1522 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1523 { 1524 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1525 Mat a = baij->A,b = baij->B; 1526 PetscErrorCode ierr; 1527 PetscInt s1,s2,s3; 1528 1529 PetscFunctionBegin; 1530 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1531 if (rr) { 1532 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1533 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1534 /* Overlap communication with computation. */ 1535 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1536 } 1537 if (ll) { 1538 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1539 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1540 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1541 } 1542 /* scale the diagonal block */ 1543 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1544 1545 if (rr) { 1546 /* Do a scatter end and then right scale the off-diagonal block */ 1547 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1548 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1549 } 1550 1551 PetscFunctionReturn(0); 1552 } 1553 1554 #undef __FUNCT__ 1555 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1556 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 1557 { 1558 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1559 PetscErrorCode ierr; 1560 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1561 PetscInt i,*owners = A->rmap->range; 1562 PetscInt *nprocs,j,idx,nsends,row; 1563 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1564 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1565 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1566 MPI_Comm comm = ((PetscObject)A)->comm; 1567 MPI_Request *send_waits,*recv_waits; 1568 MPI_Status recv_status,*send_status; 1569 #if defined(PETSC_DEBUG) 1570 PetscTruth found = PETSC_FALSE; 1571 #endif 1572 1573 PetscFunctionBegin; 1574 /* first count number of contributors to each processor */ 1575 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1576 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1577 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1578 j = 0; 1579 for (i=0; i<N; i++) { 1580 if (lastidx > (idx = rows[i])) j = 0; 1581 lastidx = idx; 1582 for (; j<size; j++) { 1583 if (idx >= owners[j] && idx < owners[j+1]) { 1584 nprocs[2*j]++; 1585 nprocs[2*j+1] = 1; 1586 owner[i] = j; 1587 #if defined(PETSC_DEBUG) 1588 found = PETSC_TRUE; 1589 #endif 1590 break; 1591 } 1592 } 1593 #if defined(PETSC_DEBUG) 1594 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1595 found = PETSC_FALSE; 1596 #endif 1597 } 1598 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1599 1600 /* inform other processors of number of messages and max length*/ 1601 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1602 1603 /* post receives: */ 1604 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1605 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1606 for (i=0; i<nrecvs; i++) { 1607 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1608 } 1609 1610 /* do sends: 1611 1) starts[i] gives the starting index in svalues for stuff going to 1612 the ith processor 1613 */ 1614 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1615 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1616 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1617 starts[0] = 0; 1618 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1619 for (i=0; i<N; i++) { 1620 svalues[starts[owner[i]]++] = rows[i]; 1621 } 1622 1623 starts[0] = 0; 1624 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1625 count = 0; 1626 for (i=0; i<size; i++) { 1627 if (nprocs[2*i+1]) { 1628 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1629 } 1630 } 1631 ierr = PetscFree(starts);CHKERRQ(ierr); 1632 1633 base = owners[rank]; 1634 1635 /* wait on receives */ 1636 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1637 source = lens + nrecvs; 1638 count = nrecvs; slen = 0; 1639 while (count) { 1640 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1641 /* unpack receives into our local space */ 1642 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1643 source[imdex] = recv_status.MPI_SOURCE; 1644 lens[imdex] = n; 1645 slen += n; 1646 count--; 1647 } 1648 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1649 1650 /* move the data into the send scatter */ 1651 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1652 count = 0; 1653 for (i=0; i<nrecvs; i++) { 1654 values = rvalues + i*nmax; 1655 for (j=0; j<lens[i]; j++) { 1656 lrows[count++] = values[j] - base; 1657 } 1658 } 1659 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1660 ierr = PetscFree(lens);CHKERRQ(ierr); 1661 ierr = PetscFree(owner);CHKERRQ(ierr); 1662 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1663 1664 /* actually zap the local rows */ 1665 /* 1666 Zero the required rows. If the "diagonal block" of the matrix 1667 is square and the user wishes to set the diagonal we use separate 1668 code so that MatSetValues() is not called for each diagonal allocating 1669 new memory, thus calling lots of mallocs and slowing things down. 1670 1671 Contributed by: Matthew Knepley 1672 */ 1673 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1674 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0);CHKERRQ(ierr); 1675 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1676 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag);CHKERRQ(ierr); 1677 } else if (diag != 0.0) { 1678 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1679 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1680 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1681 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1682 } 1683 for (i=0; i<slen; i++) { 1684 row = lrows[i] + rstart_bs; 1685 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1686 } 1687 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1688 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1689 } else { 1690 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1691 } 1692 1693 ierr = PetscFree(lrows);CHKERRQ(ierr); 1694 1695 /* wait on sends */ 1696 if (nsends) { 1697 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1698 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1699 ierr = PetscFree(send_status);CHKERRQ(ierr); 1700 } 1701 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1702 ierr = PetscFree(svalues);CHKERRQ(ierr); 1703 1704 PetscFunctionReturn(0); 1705 } 1706 1707 #undef __FUNCT__ 1708 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1709 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1710 { 1711 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1712 PetscErrorCode ierr; 1713 1714 PetscFunctionBegin; 1715 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1716 PetscFunctionReturn(0); 1717 } 1718 1719 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1720 1721 #undef __FUNCT__ 1722 #define __FUNCT__ "MatEqual_MPIBAIJ" 1723 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1724 { 1725 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1726 Mat a,b,c,d; 1727 PetscTruth flg; 1728 PetscErrorCode ierr; 1729 1730 PetscFunctionBegin; 1731 a = matA->A; b = matA->B; 1732 c = matB->A; d = matB->B; 1733 1734 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1735 if (flg) { 1736 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1737 } 1738 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1739 PetscFunctionReturn(0); 1740 } 1741 1742 #undef __FUNCT__ 1743 #define __FUNCT__ "MatCopy_MPIBAIJ" 1744 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1745 { 1746 PetscErrorCode ierr; 1747 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 1748 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 1749 1750 PetscFunctionBegin; 1751 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1752 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1753 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1754 } else { 1755 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1756 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1757 } 1758 PetscFunctionReturn(0); 1759 } 1760 1761 #undef __FUNCT__ 1762 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1763 PetscErrorCode MatSetUpPreallocation_MPIBAIJ(Mat A) 1764 { 1765 PetscErrorCode ierr; 1766 1767 PetscFunctionBegin; 1768 ierr = MatMPIBAIJSetPreallocation(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1769 PetscFunctionReturn(0); 1770 } 1771 1772 #include "petscblaslapack.h" 1773 #undef __FUNCT__ 1774 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1775 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1776 { 1777 PetscErrorCode ierr; 1778 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ *)X->data,*yy=(Mat_MPIBAIJ *)Y->data; 1779 PetscBLASInt bnz,one=1; 1780 Mat_SeqBAIJ *x,*y; 1781 1782 PetscFunctionBegin; 1783 if (str == SAME_NONZERO_PATTERN) { 1784 PetscScalar alpha = a; 1785 x = (Mat_SeqBAIJ *)xx->A->data; 1786 y = (Mat_SeqBAIJ *)yy->A->data; 1787 bnz = PetscBLASIntCast(x->nz); 1788 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1789 x = (Mat_SeqBAIJ *)xx->B->data; 1790 y = (Mat_SeqBAIJ *)yy->B->data; 1791 bnz = PetscBLASIntCast(x->nz); 1792 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1793 } else { 1794 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1795 } 1796 PetscFunctionReturn(0); 1797 } 1798 1799 #undef __FUNCT__ 1800 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1801 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1802 { 1803 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1804 PetscErrorCode ierr; 1805 1806 PetscFunctionBegin; 1807 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1808 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1809 PetscFunctionReturn(0); 1810 } 1811 1812 #undef __FUNCT__ 1813 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 1814 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 1815 { 1816 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1817 PetscErrorCode ierr; 1818 1819 PetscFunctionBegin; 1820 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1821 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1822 PetscFunctionReturn(0); 1823 } 1824 1825 #undef __FUNCT__ 1826 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 1827 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 1828 { 1829 PetscErrorCode ierr; 1830 IS iscol_local; 1831 PetscInt csize; 1832 1833 PetscFunctionBegin; 1834 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 1835 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 1836 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 1837 ierr = ISDestroy(iscol_local);CHKERRQ(ierr); 1838 PetscFunctionReturn(0); 1839 } 1840 1841 #undef __FUNCT__ 1842 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 1843 /* 1844 Not great since it makes two copies of the submatrix, first an SeqBAIJ 1845 in local and then by concatenating the local matrices the end result. 1846 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 1847 */ 1848 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 1849 { 1850 PetscErrorCode ierr; 1851 PetscMPIInt rank,size; 1852 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 1853 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 1854 Mat *local,M,Mreuse; 1855 MatScalar *vwork,*aa; 1856 MPI_Comm comm = ((PetscObject)mat)->comm; 1857 Mat_SeqBAIJ *aij; 1858 1859 1860 PetscFunctionBegin; 1861 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1862 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1863 1864 if (call == MAT_REUSE_MATRIX) { 1865 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 1866 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 1867 local = &Mreuse; 1868 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 1869 } else { 1870 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 1871 Mreuse = *local; 1872 ierr = PetscFree(local);CHKERRQ(ierr); 1873 } 1874 1875 /* 1876 m - number of local rows 1877 n - number of columns (same on all processors) 1878 rstart - first row in new global matrix generated 1879 */ 1880 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 1881 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 1882 m = m/bs; 1883 n = n/bs; 1884 1885 if (call == MAT_INITIAL_MATRIX) { 1886 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 1887 ii = aij->i; 1888 jj = aij->j; 1889 1890 /* 1891 Determine the number of non-zeros in the diagonal and off-diagonal 1892 portions of the matrix in order to do correct preallocation 1893 */ 1894 1895 /* first get start and end of "diagonal" columns */ 1896 if (csize == PETSC_DECIDE) { 1897 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 1898 if (mglobal == n*bs) { /* square matrix */ 1899 nlocal = m; 1900 } else { 1901 nlocal = n/size + ((n % size) > rank); 1902 } 1903 } else { 1904 nlocal = csize/bs; 1905 } 1906 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 1907 rstart = rend - nlocal; 1908 if (rank == size - 1 && rend != n) { 1909 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 1910 } 1911 1912 /* next, compute all the lengths */ 1913 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 1914 olens = dlens + m; 1915 for (i=0; i<m; i++) { 1916 jend = ii[i+1] - ii[i]; 1917 olen = 0; 1918 dlen = 0; 1919 for (j=0; j<jend; j++) { 1920 if (*jj < rstart || *jj >= rend) olen++; 1921 else dlen++; 1922 jj++; 1923 } 1924 olens[i] = olen; 1925 dlens[i] = dlen; 1926 } 1927 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 1928 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 1929 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 1930 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 1931 ierr = PetscFree(dlens);CHKERRQ(ierr); 1932 } else { 1933 PetscInt ml,nl; 1934 1935 M = *newmat; 1936 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 1937 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 1938 ierr = MatZeroEntries(M);CHKERRQ(ierr); 1939 /* 1940 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 1941 rather than the slower MatSetValues(). 1942 */ 1943 M->was_assembled = PETSC_TRUE; 1944 M->assembled = PETSC_FALSE; 1945 } 1946 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 1947 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 1948 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 1949 ii = aij->i; 1950 jj = aij->j; 1951 aa = aij->a; 1952 for (i=0; i<m; i++) { 1953 row = rstart/bs + i; 1954 nz = ii[i+1] - ii[i]; 1955 cwork = jj; jj += nz; 1956 vwork = aa; aa += nz; 1957 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 1958 } 1959 1960 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1961 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1962 *newmat = M; 1963 1964 /* save submatrix used in processor for next request */ 1965 if (call == MAT_INITIAL_MATRIX) { 1966 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 1967 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 1968 } 1969 1970 PetscFunctionReturn(0); 1971 } 1972 1973 #undef __FUNCT__ 1974 #define __FUNCT__ "MatPermute_MPIBAIJ" 1975 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 1976 { 1977 MPI_Comm comm,pcomm; 1978 PetscInt first,local_size,nrows; 1979 const PetscInt *rows; 1980 PetscMPIInt size; 1981 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1982 PetscErrorCode ierr; 1983 1984 PetscFunctionBegin; 1985 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1986 /* make a collective version of 'rowp' */ 1987 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 1988 if (pcomm==comm) { 1989 crowp = rowp; 1990 } else { 1991 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 1992 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 1993 ierr = ISCreateGeneral(comm,nrows,rows,&crowp);CHKERRQ(ierr); 1994 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 1995 } 1996 /* collect the global row permutation and invert it */ 1997 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 1998 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 1999 if (pcomm!=comm) { 2000 ierr = ISDestroy(crowp);CHKERRQ(ierr); 2001 } 2002 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2003 /* get the local target indices */ 2004 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL);CHKERRQ(ierr); 2005 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL);CHKERRQ(ierr); 2006 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 2007 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp);CHKERRQ(ierr); 2008 ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr); 2009 ierr = ISDestroy(irowp);CHKERRQ(ierr); 2010 /* the column permutation is so much easier; 2011 make a local version of 'colp' and invert it */ 2012 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2013 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2014 if (size==1) { 2015 lcolp = colp; 2016 } else { 2017 ierr = ISGetSize(colp,&nrows);CHKERRQ(ierr); 2018 ierr = ISGetIndices(colp,&rows);CHKERRQ(ierr); 2019 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp);CHKERRQ(ierr); 2020 } 2021 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2022 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2023 ierr = ISSetPermutation(icolp);CHKERRQ(ierr); 2024 if (size>1) { 2025 ierr = ISRestoreIndices(colp,&rows);CHKERRQ(ierr); 2026 ierr = ISDestroy(lcolp);CHKERRQ(ierr); 2027 } 2028 /* now we just get the submatrix */ 2029 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2030 /* clean up */ 2031 ierr = ISDestroy(lrowp);CHKERRQ(ierr); 2032 ierr = ISDestroy(icolp);CHKERRQ(ierr); 2033 PetscFunctionReturn(0); 2034 } 2035 2036 #undef __FUNCT__ 2037 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2038 PetscErrorCode PETSCMAT_DLLEXPORT MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2039 { 2040 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2041 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2042 2043 PetscFunctionBegin; 2044 if (nghosts) { *nghosts = B->nbs;} 2045 if (ghosts) {*ghosts = baij->garray;} 2046 PetscFunctionReturn(0); 2047 } 2048 2049 2050 /* -------------------------------------------------------------------*/ 2051 static struct _MatOps MatOps_Values = { 2052 MatSetValues_MPIBAIJ, 2053 MatGetRow_MPIBAIJ, 2054 MatRestoreRow_MPIBAIJ, 2055 MatMult_MPIBAIJ, 2056 /* 4*/ MatMultAdd_MPIBAIJ, 2057 MatMultTranspose_MPIBAIJ, 2058 MatMultTransposeAdd_MPIBAIJ, 2059 0, 2060 0, 2061 0, 2062 /*10*/ 0, 2063 0, 2064 0, 2065 0, 2066 MatTranspose_MPIBAIJ, 2067 /*15*/ MatGetInfo_MPIBAIJ, 2068 MatEqual_MPIBAIJ, 2069 MatGetDiagonal_MPIBAIJ, 2070 MatDiagonalScale_MPIBAIJ, 2071 MatNorm_MPIBAIJ, 2072 /*20*/ MatAssemblyBegin_MPIBAIJ, 2073 MatAssemblyEnd_MPIBAIJ, 2074 MatSetOption_MPIBAIJ, 2075 MatZeroEntries_MPIBAIJ, 2076 /*24*/ MatZeroRows_MPIBAIJ, 2077 0, 2078 0, 2079 0, 2080 0, 2081 /*29*/ MatSetUpPreallocation_MPIBAIJ, 2082 0, 2083 0, 2084 0, 2085 0, 2086 /*34*/ MatDuplicate_MPIBAIJ, 2087 0, 2088 0, 2089 0, 2090 0, 2091 /*39*/ MatAXPY_MPIBAIJ, 2092 MatGetSubMatrices_MPIBAIJ, 2093 MatIncreaseOverlap_MPIBAIJ, 2094 MatGetValues_MPIBAIJ, 2095 MatCopy_MPIBAIJ, 2096 /*44*/ 0, 2097 MatScale_MPIBAIJ, 2098 0, 2099 0, 2100 0, 2101 /*49*/ 0, 2102 0, 2103 0, 2104 0, 2105 0, 2106 /*54*/ 0, 2107 0, 2108 MatSetUnfactored_MPIBAIJ, 2109 MatPermute_MPIBAIJ, 2110 MatSetValuesBlocked_MPIBAIJ, 2111 /*59*/ MatGetSubMatrix_MPIBAIJ, 2112 MatDestroy_MPIBAIJ, 2113 MatView_MPIBAIJ, 2114 0, 2115 0, 2116 /*64*/ 0, 2117 0, 2118 0, 2119 0, 2120 0, 2121 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2122 0, 2123 0, 2124 0, 2125 0, 2126 /*74*/ 0, 2127 0, 2128 0, 2129 0, 2130 0, 2131 /*79*/ 0, 2132 0, 2133 0, 2134 0, 2135 MatLoad_MPIBAIJ, 2136 /*84*/ 0, 2137 0, 2138 0, 2139 0, 2140 0, 2141 /*89*/ 0, 2142 0, 2143 0, 2144 0, 2145 0, 2146 /*94*/ 0, 2147 0, 2148 0, 2149 0, 2150 0, 2151 /*99*/ 0, 2152 0, 2153 0, 2154 0, 2155 0, 2156 /*104*/0, 2157 MatRealPart_MPIBAIJ, 2158 MatImaginaryPart_MPIBAIJ, 2159 0, 2160 0, 2161 /*109*/0, 2162 0, 2163 0, 2164 0, 2165 0, 2166 /*114*/0, 2167 0, 2168 MatGetGhosts_MPIBAIJ 2169 }; 2170 2171 2172 EXTERN_C_BEGIN 2173 #undef __FUNCT__ 2174 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2175 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 2176 { 2177 PetscFunctionBegin; 2178 *a = ((Mat_MPIBAIJ *)A->data)->A; 2179 *iscopy = PETSC_FALSE; 2180 PetscFunctionReturn(0); 2181 } 2182 EXTERN_C_END 2183 2184 EXTERN_C_BEGIN 2185 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2186 EXTERN_C_END 2187 2188 EXTERN_C_BEGIN 2189 #undef __FUNCT__ 2190 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2191 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2192 { 2193 PetscInt m,rstart,cstart,cend; 2194 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2195 const PetscInt *JJ=0; 2196 PetscScalar *values=0; 2197 PetscErrorCode ierr; 2198 2199 PetscFunctionBegin; 2200 2201 if (bs < 1) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 2202 ierr = PetscMapSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2203 ierr = PetscMapSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2204 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2205 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2206 m = B->rmap->n/bs; 2207 rstart = B->rmap->rstart/bs; 2208 cstart = B->cmap->rstart/bs; 2209 cend = B->cmap->rend/bs; 2210 2211 if (ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2212 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2213 o_nnz = d_nnz + m; 2214 for (i=0; i<m; i++) { 2215 nz = ii[i+1] - ii[i]; 2216 if (nz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2217 nz_max = PetscMax(nz_max,nz); 2218 JJ = jj + ii[i]; 2219 for (j=0; j<nz; j++) { 2220 if (*JJ >= cstart) break; 2221 JJ++; 2222 } 2223 d = 0; 2224 for (; j<nz; j++) { 2225 if (*JJ++ >= cend) break; 2226 d++; 2227 } 2228 d_nnz[i] = d; 2229 o_nnz[i] = nz - d; 2230 } 2231 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2232 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2233 2234 values = (PetscScalar*)V; 2235 if (!values) { 2236 ierr = PetscMalloc(bs*bs*(nz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2237 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2238 } 2239 for (i=0; i<m; i++) { 2240 PetscInt row = i + rstart; 2241 PetscInt ncols = ii[i+1] - ii[i]; 2242 const PetscInt *icols = jj + ii[i]; 2243 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2244 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2245 } 2246 2247 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2248 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2249 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2250 2251 PetscFunctionReturn(0); 2252 } 2253 EXTERN_C_END 2254 2255 #undef __FUNCT__ 2256 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2257 /*@C 2258 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2259 (the default parallel PETSc format). 2260 2261 Collective on MPI_Comm 2262 2263 Input Parameters: 2264 + A - the matrix 2265 . i - the indices into j for the start of each local row (starts with zero) 2266 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2267 - v - optional values in the matrix 2268 2269 Level: developer 2270 2271 .keywords: matrix, aij, compressed row, sparse, parallel 2272 2273 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ 2274 @*/ 2275 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2276 { 2277 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]); 2278 2279 PetscFunctionBegin; 2280 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2281 if (f) { 2282 ierr = (*f)(B,bs,i,j,v);CHKERRQ(ierr); 2283 } 2284 PetscFunctionReturn(0); 2285 } 2286 2287 EXTERN_C_BEGIN 2288 #undef __FUNCT__ 2289 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2290 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2291 { 2292 Mat_MPIBAIJ *b; 2293 PetscErrorCode ierr; 2294 PetscInt i, newbs = PetscAbs(bs); 2295 2296 PetscFunctionBegin; 2297 if (bs < 0) { 2298 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPIBAIJ matrix","Mat");CHKERRQ(ierr); 2299 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);CHKERRQ(ierr); 2300 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2301 bs = PetscAbs(bs); 2302 } 2303 if ((d_nnz || o_nnz) && newbs != bs) { 2304 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz"); 2305 } 2306 bs = newbs; 2307 2308 2309 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2310 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2311 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2312 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2313 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2314 2315 ierr = PetscMapSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2316 ierr = PetscMapSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2317 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2318 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2319 2320 if (d_nnz) { 2321 for (i=0; i<B->rmap->n/bs; i++) { 2322 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2323 } 2324 } 2325 if (o_nnz) { 2326 for (i=0; i<B->rmap->n/bs; i++) { 2327 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2328 } 2329 } 2330 2331 b = (Mat_MPIBAIJ*)B->data; 2332 b->bs2 = bs*bs; 2333 b->mbs = B->rmap->n/bs; 2334 b->nbs = B->cmap->n/bs; 2335 b->Mbs = B->rmap->N/bs; 2336 b->Nbs = B->cmap->N/bs; 2337 2338 for (i=0; i<=b->size; i++) { 2339 b->rangebs[i] = B->rmap->range[i]/bs; 2340 } 2341 b->rstartbs = B->rmap->rstart/bs; 2342 b->rendbs = B->rmap->rend/bs; 2343 b->cstartbs = B->cmap->rstart/bs; 2344 b->cendbs = B->cmap->rend/bs; 2345 2346 if (!B->preallocated) { 2347 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2348 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2349 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2350 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2351 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2352 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2353 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2354 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2355 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 2356 } 2357 2358 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2359 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2360 B->preallocated = PETSC_TRUE; 2361 PetscFunctionReturn(0); 2362 } 2363 EXTERN_C_END 2364 2365 EXTERN_C_BEGIN 2366 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2367 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2368 EXTERN_C_END 2369 2370 2371 EXTERN_C_BEGIN 2372 #undef __FUNCT__ 2373 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2374 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPIAdj(Mat B, const MatType newtype,MatReuse reuse,Mat *adj) 2375 { 2376 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2377 PetscErrorCode ierr; 2378 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2379 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2380 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2381 2382 PetscFunctionBegin; 2383 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr); 2384 ii[0] = 0; 2385 CHKMEMQ; 2386 for (i=0; i<M; i++) { 2387 if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]); 2388 if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]); 2389 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2390 /* remove one from count of matrix has diagonal */ 2391 for (j=id[i]; j<id[i+1]; j++) { 2392 if (jd[j] == i) {ii[i+1]--;break;} 2393 } 2394 CHKMEMQ; 2395 } 2396 ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr); 2397 cnt = 0; 2398 for (i=0; i<M; i++) { 2399 for (j=io[i]; j<io[i+1]; j++) { 2400 if (garray[jo[j]] > rstart) break; 2401 jj[cnt++] = garray[jo[j]]; 2402 CHKMEMQ; 2403 } 2404 for (k=id[i]; k<id[i+1]; k++) { 2405 if (jd[k] != i) { 2406 jj[cnt++] = rstart + jd[k]; 2407 CHKMEMQ; 2408 } 2409 } 2410 for (;j<io[i+1]; j++) { 2411 jj[cnt++] = garray[jo[j]]; 2412 CHKMEMQ; 2413 } 2414 } 2415 ierr = MatCreateMPIAdj(((PetscObject)B)->comm,M,B->cmap->N/B->rmap->bs,ii,jj,PETSC_NULL,adj);CHKERRQ(ierr); 2416 PetscFunctionReturn(0); 2417 } 2418 EXTERN_C_END 2419 2420 /*MC 2421 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2422 2423 Options Database Keys: 2424 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2425 . -mat_block_size <bs> - set the blocksize used to store the matrix 2426 - -mat_use_hash_table <fact> 2427 2428 Level: beginner 2429 2430 .seealso: MatCreateMPIBAIJ 2431 M*/ 2432 2433 EXTERN_C_BEGIN 2434 #undef __FUNCT__ 2435 #define __FUNCT__ "MatCreate_MPIBAIJ" 2436 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2437 { 2438 Mat_MPIBAIJ *b; 2439 PetscErrorCode ierr; 2440 PetscTruth flg; 2441 2442 PetscFunctionBegin; 2443 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2444 B->data = (void*)b; 2445 2446 2447 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2448 B->mapping = 0; 2449 B->assembled = PETSC_FALSE; 2450 2451 B->insertmode = NOT_SET_VALUES; 2452 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 2453 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 2454 2455 /* build local table of row and column ownerships */ 2456 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 2457 2458 /* build cache for off array entries formed */ 2459 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 2460 b->donotstash = PETSC_FALSE; 2461 b->colmap = PETSC_NULL; 2462 b->garray = PETSC_NULL; 2463 b->roworiented = PETSC_TRUE; 2464 2465 /* stuff used in block assembly */ 2466 b->barray = 0; 2467 2468 /* stuff used for matrix vector multiply */ 2469 b->lvec = 0; 2470 b->Mvctx = 0; 2471 2472 /* stuff for MatGetRow() */ 2473 b->rowindices = 0; 2474 b->rowvalues = 0; 2475 b->getrowactive = PETSC_FALSE; 2476 2477 /* hash table stuff */ 2478 b->ht = 0; 2479 b->hd = 0; 2480 b->ht_size = 0; 2481 b->ht_flag = PETSC_FALSE; 2482 b->ht_fact = 0; 2483 b->ht_total_ct = 0; 2484 b->ht_insert_ct = 0; 2485 2486 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 2487 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 2488 if (flg) { 2489 PetscReal fact = 1.39; 2490 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 2491 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 2492 if (fact <= 1.0) fact = 1.39; 2493 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2494 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 2495 } 2496 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2497 2498 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpiadj_C", 2499 "MatConvert_MPIBAIJ_MPIAdj", 2500 MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 2501 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2502 "MatStoreValues_MPIBAIJ", 2503 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2504 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2505 "MatRetrieveValues_MPIBAIJ", 2506 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2507 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2508 "MatGetDiagonalBlock_MPIBAIJ", 2509 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2510 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2511 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2512 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2513 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2514 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 2515 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2516 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2517 "MatDiagonalScaleLocal_MPIBAIJ", 2518 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2519 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2520 "MatSetHashTableFactor_MPIBAIJ", 2521 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2522 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 2523 PetscFunctionReturn(0); 2524 } 2525 EXTERN_C_END 2526 2527 /*MC 2528 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2529 2530 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2531 and MATMPIBAIJ otherwise. 2532 2533 Options Database Keys: 2534 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2535 2536 Level: beginner 2537 2538 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2539 M*/ 2540 2541 EXTERN_C_BEGIN 2542 #undef __FUNCT__ 2543 #define __FUNCT__ "MatCreate_BAIJ" 2544 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2545 { 2546 PetscErrorCode ierr; 2547 PetscMPIInt size; 2548 2549 PetscFunctionBegin; 2550 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2551 if (size == 1) { 2552 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2553 } else { 2554 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2555 } 2556 PetscFunctionReturn(0); 2557 } 2558 EXTERN_C_END 2559 2560 #undef __FUNCT__ 2561 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2562 /*@C 2563 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2564 (block compressed row). For good matrix assembly performance 2565 the user should preallocate the matrix storage by setting the parameters 2566 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2567 performance can be increased by more than a factor of 50. 2568 2569 Collective on Mat 2570 2571 Input Parameters: 2572 + A - the matrix 2573 . bs - size of blockk 2574 . d_nz - number of block nonzeros per block row in diagonal portion of local 2575 submatrix (same for all local rows) 2576 . d_nnz - array containing the number of block nonzeros in the various block rows 2577 of the in diagonal portion of the local (possibly different for each block 2578 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2579 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2580 submatrix (same for all local rows). 2581 - o_nnz - array containing the number of nonzeros in the various block rows of the 2582 off-diagonal portion of the local submatrix (possibly different for 2583 each block row) or PETSC_NULL. 2584 2585 If the *_nnz parameter is given then the *_nz parameter is ignored 2586 2587 Options Database Keys: 2588 + -mat_block_size - size of the blocks to use 2589 - -mat_use_hash_table <fact> 2590 2591 Notes: 2592 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2593 than it must be used on all processors that share the object for that argument. 2594 2595 Storage Information: 2596 For a square global matrix we define each processor's diagonal portion 2597 to be its local rows and the corresponding columns (a square submatrix); 2598 each processor's off-diagonal portion encompasses the remainder of the 2599 local matrix (a rectangular submatrix). 2600 2601 The user can specify preallocated storage for the diagonal part of 2602 the local submatrix with either d_nz or d_nnz (not both). Set 2603 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2604 memory allocation. Likewise, specify preallocated storage for the 2605 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2606 2607 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2608 the figure below we depict these three local rows and all columns (0-11). 2609 2610 .vb 2611 0 1 2 3 4 5 6 7 8 9 10 11 2612 ------------------- 2613 row 3 | o o o d d d o o o o o o 2614 row 4 | o o o d d d o o o o o o 2615 row 5 | o o o d d d o o o o o o 2616 ------------------- 2617 .ve 2618 2619 Thus, any entries in the d locations are stored in the d (diagonal) 2620 submatrix, and any entries in the o locations are stored in the 2621 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2622 stored simply in the MATSEQBAIJ format for compressed row storage. 2623 2624 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2625 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2626 In general, for PDE problems in which most nonzeros are near the diagonal, 2627 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2628 or you will get TERRIBLE performance; see the users' manual chapter on 2629 matrices. 2630 2631 You can call MatGetInfo() to get information on how effective the preallocation was; 2632 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2633 You can also run with the option -info and look for messages with the string 2634 malloc in them to see if additional memory allocation was needed. 2635 2636 Level: intermediate 2637 2638 .keywords: matrix, block, aij, compressed row, sparse, parallel 2639 2640 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2641 @*/ 2642 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2643 { 2644 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2645 2646 PetscFunctionBegin; 2647 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2648 if (f) { 2649 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2650 } 2651 PetscFunctionReturn(0); 2652 } 2653 2654 #undef __FUNCT__ 2655 #define __FUNCT__ "MatCreateMPIBAIJ" 2656 /*@C 2657 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2658 (block compressed row). For good matrix assembly performance 2659 the user should preallocate the matrix storage by setting the parameters 2660 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2661 performance can be increased by more than a factor of 50. 2662 2663 Collective on MPI_Comm 2664 2665 Input Parameters: 2666 + comm - MPI communicator 2667 . bs - size of blockk 2668 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2669 This value should be the same as the local size used in creating the 2670 y vector for the matrix-vector product y = Ax. 2671 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2672 This value should be the same as the local size used in creating the 2673 x vector for the matrix-vector product y = Ax. 2674 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2675 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2676 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2677 submatrix (same for all local rows) 2678 . d_nnz - array containing the number of nonzero blocks in the various block rows 2679 of the in diagonal portion of the local (possibly different for each block 2680 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2681 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2682 submatrix (same for all local rows). 2683 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2684 off-diagonal portion of the local submatrix (possibly different for 2685 each block row) or PETSC_NULL. 2686 2687 Output Parameter: 2688 . A - the matrix 2689 2690 Options Database Keys: 2691 + -mat_block_size - size of the blocks to use 2692 - -mat_use_hash_table <fact> 2693 2694 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2695 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2696 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2697 2698 Notes: 2699 If the *_nnz parameter is given then the *_nz parameter is ignored 2700 2701 A nonzero block is any block that as 1 or more nonzeros in it 2702 2703 The user MUST specify either the local or global matrix dimensions 2704 (possibly both). 2705 2706 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2707 than it must be used on all processors that share the object for that argument. 2708 2709 Storage Information: 2710 For a square global matrix we define each processor's diagonal portion 2711 to be its local rows and the corresponding columns (a square submatrix); 2712 each processor's off-diagonal portion encompasses the remainder of the 2713 local matrix (a rectangular submatrix). 2714 2715 The user can specify preallocated storage for the diagonal part of 2716 the local submatrix with either d_nz or d_nnz (not both). Set 2717 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2718 memory allocation. Likewise, specify preallocated storage for the 2719 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2720 2721 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2722 the figure below we depict these three local rows and all columns (0-11). 2723 2724 .vb 2725 0 1 2 3 4 5 6 7 8 9 10 11 2726 ------------------- 2727 row 3 | o o o d d d o o o o o o 2728 row 4 | o o o d d d o o o o o o 2729 row 5 | o o o d d d o o o o o o 2730 ------------------- 2731 .ve 2732 2733 Thus, any entries in the d locations are stored in the d (diagonal) 2734 submatrix, and any entries in the o locations are stored in the 2735 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2736 stored simply in the MATSEQBAIJ format for compressed row storage. 2737 2738 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2739 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2740 In general, for PDE problems in which most nonzeros are near the diagonal, 2741 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2742 or you will get TERRIBLE performance; see the users' manual chapter on 2743 matrices. 2744 2745 Level: intermediate 2746 2747 .keywords: matrix, block, aij, compressed row, sparse, parallel 2748 2749 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2750 @*/ 2751 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 2752 { 2753 PetscErrorCode ierr; 2754 PetscMPIInt size; 2755 2756 PetscFunctionBegin; 2757 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2758 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2759 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2760 if (size > 1) { 2761 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2762 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2763 } else { 2764 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2765 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2766 } 2767 PetscFunctionReturn(0); 2768 } 2769 2770 #undef __FUNCT__ 2771 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2772 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2773 { 2774 Mat mat; 2775 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2776 PetscErrorCode ierr; 2777 PetscInt len=0; 2778 2779 PetscFunctionBegin; 2780 *newmat = 0; 2781 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2782 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2783 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2784 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2785 2786 mat->factor = matin->factor; 2787 mat->preallocated = PETSC_TRUE; 2788 mat->assembled = PETSC_TRUE; 2789 mat->insertmode = NOT_SET_VALUES; 2790 2791 a = (Mat_MPIBAIJ*)mat->data; 2792 mat->rmap->bs = matin->rmap->bs; 2793 a->bs2 = oldmat->bs2; 2794 a->mbs = oldmat->mbs; 2795 a->nbs = oldmat->nbs; 2796 a->Mbs = oldmat->Mbs; 2797 a->Nbs = oldmat->Nbs; 2798 2799 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 2800 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 2801 2802 a->size = oldmat->size; 2803 a->rank = oldmat->rank; 2804 a->donotstash = oldmat->donotstash; 2805 a->roworiented = oldmat->roworiented; 2806 a->rowindices = 0; 2807 a->rowvalues = 0; 2808 a->getrowactive = PETSC_FALSE; 2809 a->barray = 0; 2810 a->rstartbs = oldmat->rstartbs; 2811 a->rendbs = oldmat->rendbs; 2812 a->cstartbs = oldmat->cstartbs; 2813 a->cendbs = oldmat->cendbs; 2814 2815 /* hash table stuff */ 2816 a->ht = 0; 2817 a->hd = 0; 2818 a->ht_size = 0; 2819 a->ht_flag = oldmat->ht_flag; 2820 a->ht_fact = oldmat->ht_fact; 2821 a->ht_total_ct = 0; 2822 a->ht_insert_ct = 0; 2823 2824 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 2825 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2826 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2827 if (oldmat->colmap) { 2828 #if defined (PETSC_USE_CTABLE) 2829 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2830 #else 2831 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2832 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2833 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2834 #endif 2835 } else a->colmap = 0; 2836 2837 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2838 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2839 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2840 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2841 } else a->garray = 0; 2842 2843 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2844 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2845 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2846 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2847 2848 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2849 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2850 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2851 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2852 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2853 *newmat = mat; 2854 2855 PetscFunctionReturn(0); 2856 } 2857 2858 #include "petscsys.h" 2859 2860 #undef __FUNCT__ 2861 #define __FUNCT__ "MatLoad_MPIBAIJ" 2862 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2863 { 2864 Mat A; 2865 PetscErrorCode ierr; 2866 int fd; 2867 PetscInt i,nz,j,rstart,rend; 2868 PetscScalar *vals,*buf; 2869 MPI_Comm comm = ((PetscObject)viewer)->comm; 2870 MPI_Status status; 2871 PetscMPIInt rank,size,maxnz; 2872 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2873 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 2874 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2875 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2876 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 2877 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2878 2879 PetscFunctionBegin; 2880 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 2881 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2882 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2883 2884 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2885 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2886 if (!rank) { 2887 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2888 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2889 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2890 } 2891 2892 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2893 M = header[1]; N = header[2]; 2894 2895 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2896 2897 /* 2898 This code adds extra rows to make sure the number of rows is 2899 divisible by the blocksize 2900 */ 2901 Mbs = M/bs; 2902 extra_rows = bs - M + bs*Mbs; 2903 if (extra_rows == bs) extra_rows = 0; 2904 else Mbs++; 2905 if (extra_rows && !rank) { 2906 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2907 } 2908 2909 /* determine ownership of all rows */ 2910 mbs = Mbs/size + ((Mbs % size) > rank); 2911 m = mbs*bs; 2912 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2913 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2914 2915 /* process 0 needs enough room for process with most rows */ 2916 if (!rank) { 2917 mmax = rowners[1]; 2918 for (i=2; i<size; i++) { 2919 mmax = PetscMax(mmax,rowners[i]); 2920 } 2921 mmax*=bs; 2922 } else mmax = m; 2923 2924 rowners[0] = 0; 2925 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2926 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2927 rstart = rowners[rank]; 2928 rend = rowners[rank+1]; 2929 2930 /* distribute row lengths to all processors */ 2931 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2932 if (!rank) { 2933 mend = m; 2934 if (size == 1) mend = mend - extra_rows; 2935 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2936 for (j=mend; j<m; j++) locrowlens[j] = 1; 2937 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2938 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2939 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2940 for (j=0; j<m; j++) { 2941 procsnz[0] += locrowlens[j]; 2942 } 2943 for (i=1; i<size; i++) { 2944 mend = browners[i+1] - browners[i]; 2945 if (i == size-1) mend = mend - extra_rows; 2946 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2947 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2948 /* calculate the number of nonzeros on each processor */ 2949 for (j=0; j<browners[i+1]-browners[i]; j++) { 2950 procsnz[i] += rowlengths[j]; 2951 } 2952 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2953 } 2954 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2955 } else { 2956 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2957 } 2958 2959 if (!rank) { 2960 /* determine max buffer needed and allocate it */ 2961 maxnz = procsnz[0]; 2962 for (i=1; i<size; i++) { 2963 maxnz = PetscMax(maxnz,procsnz[i]); 2964 } 2965 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2966 2967 /* read in my part of the matrix column indices */ 2968 nz = procsnz[0]; 2969 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2970 mycols = ibuf; 2971 if (size == 1) nz -= extra_rows; 2972 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2973 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2974 2975 /* read in every ones (except the last) and ship off */ 2976 for (i=1; i<size-1; i++) { 2977 nz = procsnz[i]; 2978 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2979 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2980 } 2981 /* read in the stuff for the last proc */ 2982 if (size != 1) { 2983 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2984 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2985 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2986 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2987 } 2988 ierr = PetscFree(cols);CHKERRQ(ierr); 2989 } else { 2990 /* determine buffer space needed for message */ 2991 nz = 0; 2992 for (i=0; i<m; i++) { 2993 nz += locrowlens[i]; 2994 } 2995 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2996 mycols = ibuf; 2997 /* receive message of column indices*/ 2998 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2999 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3000 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3001 } 3002 3003 /* loop over local rows, determining number of off diagonal entries */ 3004 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 3005 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 3006 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3007 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3008 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3009 rowcount = 0; nzcount = 0; 3010 for (i=0; i<mbs; i++) { 3011 dcount = 0; 3012 odcount = 0; 3013 for (j=0; j<bs; j++) { 3014 kmax = locrowlens[rowcount]; 3015 for (k=0; k<kmax; k++) { 3016 tmp = mycols[nzcount++]/bs; 3017 if (!mask[tmp]) { 3018 mask[tmp] = 1; 3019 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3020 else masked1[dcount++] = tmp; 3021 } 3022 } 3023 rowcount++; 3024 } 3025 3026 dlens[i] = dcount; 3027 odlens[i] = odcount; 3028 3029 /* zero out the mask elements we set */ 3030 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3031 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3032 } 3033 3034 /* create our matrix */ 3035 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 3036 ierr = MatSetSizes(A,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3037 ierr = MatSetType(A,type);CHKERRQ(ierr) 3038 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3039 3040 if (!rank) { 3041 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3042 /* read in my part of the matrix numerical values */ 3043 nz = procsnz[0]; 3044 vals = buf; 3045 mycols = ibuf; 3046 if (size == 1) nz -= extra_rows; 3047 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3048 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 3049 3050 /* insert into matrix */ 3051 jj = rstart*bs; 3052 for (i=0; i<m; i++) { 3053 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3054 mycols += locrowlens[i]; 3055 vals += locrowlens[i]; 3056 jj++; 3057 } 3058 /* read in other processors (except the last one) and ship out */ 3059 for (i=1; i<size-1; i++) { 3060 nz = procsnz[i]; 3061 vals = buf; 3062 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3063 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 3064 } 3065 /* the last proc */ 3066 if (size != 1){ 3067 nz = procsnz[i] - extra_rows; 3068 vals = buf; 3069 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3070 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3071 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 3072 } 3073 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3074 } else { 3075 /* receive numeric values */ 3076 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3077 3078 /* receive message of values*/ 3079 vals = buf; 3080 mycols = ibuf; 3081 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 3082 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 3083 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3084 3085 /* insert into matrix */ 3086 jj = rstart*bs; 3087 for (i=0; i<m; i++) { 3088 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3089 mycols += locrowlens[i]; 3090 vals += locrowlens[i]; 3091 jj++; 3092 } 3093 } 3094 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3095 ierr = PetscFree(buf);CHKERRQ(ierr); 3096 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3097 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3098 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3099 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3100 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3101 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3102 3103 *newmat = A; 3104 PetscFunctionReturn(0); 3105 } 3106 3107 #undef __FUNCT__ 3108 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3109 /*@ 3110 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3111 3112 Input Parameters: 3113 . mat - the matrix 3114 . fact - factor 3115 3116 Collective on Mat 3117 3118 Level: advanced 3119 3120 Notes: 3121 This can also be set by the command line option: -mat_use_hash_table <fact> 3122 3123 .keywords: matrix, hashtable, factor, HT 3124 3125 .seealso: MatSetOption() 3126 @*/ 3127 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3128 { 3129 PetscErrorCode ierr,(*f)(Mat,PetscReal); 3130 3131 PetscFunctionBegin; 3132 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 3133 if (f) { 3134 ierr = (*f)(mat,fact);CHKERRQ(ierr); 3135 } 3136 PetscFunctionReturn(0); 3137 } 3138 3139 EXTERN_C_BEGIN 3140 #undef __FUNCT__ 3141 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3142 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3143 { 3144 Mat_MPIBAIJ *baij; 3145 3146 PetscFunctionBegin; 3147 baij = (Mat_MPIBAIJ*)mat->data; 3148 baij->ht_fact = fact; 3149 PetscFunctionReturn(0); 3150 } 3151 EXTERN_C_END 3152 3153 #undef __FUNCT__ 3154 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3155 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3156 { 3157 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 3158 PetscFunctionBegin; 3159 *Ad = a->A; 3160 *Ao = a->B; 3161 *colmap = a->garray; 3162 PetscFunctionReturn(0); 3163 } 3164 3165 /* 3166 Special version for direct calls from Fortran (to eliminate two function call overheads 3167 */ 3168 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3169 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3170 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3171 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3172 #endif 3173 3174 #undef __FUNCT__ 3175 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3176 /*@C 3177 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3178 3179 Collective on Mat 3180 3181 Input Parameters: 3182 + mat - the matrix 3183 . min - number of input rows 3184 . im - input rows 3185 . nin - number of input columns 3186 . in - input columns 3187 . v - numerical values input 3188 - addvin - INSERT_VALUES or ADD_VALUES 3189 3190 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3191 3192 Level: advanced 3193 3194 .seealso: MatSetValuesBlocked() 3195 @*/ 3196 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3197 { 3198 /* convert input arguments to C version */ 3199 Mat mat = *matin; 3200 PetscInt m = *min, n = *nin; 3201 InsertMode addv = *addvin; 3202 3203 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3204 const MatScalar *value; 3205 MatScalar *barray=baij->barray; 3206 PetscTruth roworiented = baij->roworiented; 3207 PetscErrorCode ierr; 3208 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3209 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3210 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3211 3212 PetscFunctionBegin; 3213 /* tasks normally handled by MatSetValuesBlocked() */ 3214 if (mat->insertmode == NOT_SET_VALUES) { 3215 mat->insertmode = addv; 3216 } 3217 #if defined(PETSC_USE_DEBUG) 3218 else if (mat->insertmode != addv) { 3219 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3220 } 3221 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3222 #endif 3223 if (mat->assembled) { 3224 mat->was_assembled = PETSC_TRUE; 3225 mat->assembled = PETSC_FALSE; 3226 } 3227 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3228 3229 3230 if(!barray) { 3231 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 3232 baij->barray = barray; 3233 } 3234 3235 if (roworiented) { 3236 stepval = (n-1)*bs; 3237 } else { 3238 stepval = (m-1)*bs; 3239 } 3240 for (i=0; i<m; i++) { 3241 if (im[i] < 0) continue; 3242 #if defined(PETSC_USE_DEBUG) 3243 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 3244 #endif 3245 if (im[i] >= rstart && im[i] < rend) { 3246 row = im[i] - rstart; 3247 for (j=0; j<n; j++) { 3248 /* If NumCol = 1 then a copy is not required */ 3249 if ((roworiented) && (n == 1)) { 3250 barray = (MatScalar*)v + i*bs2; 3251 } else if((!roworiented) && (m == 1)) { 3252 barray = (MatScalar*)v + j*bs2; 3253 } else { /* Here a copy is required */ 3254 if (roworiented) { 3255 value = v + i*(stepval+bs)*bs + j*bs; 3256 } else { 3257 value = v + j*(stepval+bs)*bs + i*bs; 3258 } 3259 for (ii=0; ii<bs; ii++,value+=stepval) { 3260 for (jj=0; jj<bs; jj++) { 3261 *barray++ = *value++; 3262 } 3263 } 3264 barray -=bs2; 3265 } 3266 3267 if (in[j] >= cstart && in[j] < cend){ 3268 col = in[j] - cstart; 3269 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3270 } 3271 else if (in[j] < 0) continue; 3272 #if defined(PETSC_USE_DEBUG) 3273 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 3274 #endif 3275 else { 3276 if (mat->was_assembled) { 3277 if (!baij->colmap) { 3278 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3279 } 3280 3281 #if defined(PETSC_USE_DEBUG) 3282 #if defined (PETSC_USE_CTABLE) 3283 { PetscInt data; 3284 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3285 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 3286 } 3287 #else 3288 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 3289 #endif 3290 #endif 3291 #if defined (PETSC_USE_CTABLE) 3292 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3293 col = (col - 1)/bs; 3294 #else 3295 col = (baij->colmap[in[j]] - 1)/bs; 3296 #endif 3297 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3298 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3299 col = in[j]; 3300 } 3301 } 3302 else col = in[j]; 3303 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3304 } 3305 } 3306 } else { 3307 if (!baij->donotstash) { 3308 if (roworiented) { 3309 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3310 } else { 3311 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3312 } 3313 } 3314 } 3315 } 3316 3317 /* task normally handled by MatSetValuesBlocked() */ 3318 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3319 PetscFunctionReturn(0); 3320 } 3321