1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 #include <petscblaslapack.h> 4 5 extern PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 extern PetscErrorCode MatDisAssemble_MPIBAIJ(Mat); 7 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 8 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 9 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 10 extern PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 11 extern PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 12 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec); 13 14 #undef __FUNCT__ 15 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 16 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 17 { 18 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 19 PetscErrorCode ierr; 20 PetscInt i,*idxb = 0; 21 PetscScalar *va,*vb; 22 Vec vtmp; 23 24 PetscFunctionBegin; 25 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 26 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 27 if (idx) { 28 for (i=0; i<A->rmap->n; i++) { 29 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 30 } 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])) { 40 va[i] = vb[i]; 41 if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs); 42 } 43 } 44 45 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 46 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 47 ierr = PetscFree(idxb);CHKERRQ(ierr); 48 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 49 PetscFunctionReturn(0); 50 } 51 52 #undef __FUNCT__ 53 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 54 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 55 { 56 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 57 PetscErrorCode ierr; 58 59 PetscFunctionBegin; 60 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 61 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 62 PetscFunctionReturn(0); 63 } 64 65 #undef __FUNCT__ 66 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 67 PetscErrorCode 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 78 /* 79 Local utility routine that creates a mapping from the global column 80 number to the local number in the off-diagonal part of the local 81 storage of the matrix. This is done in a non scalable way since the 82 length of colmap equals the global matrix length. 83 */ 84 #undef __FUNCT__ 85 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 86 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 87 { 88 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 89 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 90 PetscErrorCode ierr; 91 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 92 93 PetscFunctionBegin; 94 #if defined(PETSC_USE_CTABLE) 95 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 96 for (i=0; i<nbs; i++) { 97 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 98 } 99 #else 100 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 101 ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 102 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 103 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 104 #endif 105 PetscFunctionReturn(0); 106 } 107 108 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 109 { \ 110 \ 111 brow = row/bs; \ 112 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 113 rmax = aimax[brow]; nrow = ailen[brow]; \ 114 bcol = col/bs; \ 115 ridx = row % bs; cidx = col % bs; \ 116 low = 0; high = nrow; \ 117 while (high-low > 3) { \ 118 t = (low+high)/2; \ 119 if (rp[t] > bcol) high = t; \ 120 else low = t; \ 121 } \ 122 for (_i=low; _i<high; _i++) { \ 123 if (rp[_i] > bcol) break; \ 124 if (rp[_i] == bcol) { \ 125 bap = ap + bs2*_i + bs*cidx + ridx; \ 126 if (addv == ADD_VALUES) *bap += value; \ 127 else *bap = value; \ 128 goto a_noinsert; \ 129 } \ 130 } \ 131 if (a->nonew == 1) goto a_noinsert; \ 132 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 133 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 134 N = nrow++ - 1; \ 135 /* shift up all the later entries in this row */ \ 136 for (ii=N; ii>=_i; ii--) { \ 137 rp[ii+1] = rp[ii]; \ 138 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 139 } \ 140 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 141 rp[_i] = bcol; \ 142 ap[bs2*_i + bs*cidx + ridx] = value; \ 143 a_noinsert:; \ 144 ailen[brow] = nrow; \ 145 } 146 147 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 148 { \ 149 brow = row/bs; \ 150 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 151 rmax = bimax[brow]; nrow = bilen[brow]; \ 152 bcol = col/bs; \ 153 ridx = row % bs; cidx = col % bs; \ 154 low = 0; high = nrow; \ 155 while (high-low > 3) { \ 156 t = (low+high)/2; \ 157 if (rp[t] > bcol) high = t; \ 158 else low = t; \ 159 } \ 160 for (_i=low; _i<high; _i++) { \ 161 if (rp[_i] > bcol) break; \ 162 if (rp[_i] == bcol) { \ 163 bap = ap + bs2*_i + bs*cidx + ridx; \ 164 if (addv == ADD_VALUES) *bap += value; \ 165 else *bap = value; \ 166 goto b_noinsert; \ 167 } \ 168 } \ 169 if (b->nonew == 1) goto b_noinsert; \ 170 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 171 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 172 N = nrow++ - 1; \ 173 /* shift up all the later entries in this row */ \ 174 for (ii=N; ii>=_i; ii--) { \ 175 rp[ii+1] = rp[ii]; \ 176 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 177 } \ 178 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 179 rp[_i] = bcol; \ 180 ap[bs2*_i + bs*cidx + ridx] = value; \ 181 b_noinsert:; \ 182 bilen[brow] = nrow; \ 183 } 184 185 #undef __FUNCT__ 186 #define __FUNCT__ "MatSetValues_MPIBAIJ" 187 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 188 { 189 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 190 MatScalar value; 191 PetscBool roworiented = baij->roworiented; 192 PetscErrorCode ierr; 193 PetscInt i,j,row,col; 194 PetscInt rstart_orig=mat->rmap->rstart; 195 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 196 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 197 198 /* Some Variables required in the macro */ 199 Mat A = baij->A; 200 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 201 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 202 MatScalar *aa =a->a; 203 204 Mat B = baij->B; 205 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 206 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 207 MatScalar *ba =b->a; 208 209 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 210 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 211 MatScalar *ap,*bap; 212 213 PetscFunctionBegin; 214 if (v) PetscValidScalarPointer(v,6); 215 for (i=0; i<m; i++) { 216 if (im[i] < 0) continue; 217 #if defined(PETSC_USE_DEBUG) 218 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 219 #endif 220 if (im[i] >= rstart_orig && im[i] < rend_orig) { 221 row = im[i] - rstart_orig; 222 for (j=0; j<n; j++) { 223 if (in[j] >= cstart_orig && in[j] < cend_orig) { 224 col = in[j] - cstart_orig; 225 if (roworiented) value = v[i*n+j]; 226 else value = v[i+j*m]; 227 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 228 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 229 } else if (in[j] < 0) continue; 230 #if defined(PETSC_USE_DEBUG) 231 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 232 #endif 233 else { 234 if (mat->was_assembled) { 235 if (!baij->colmap) { 236 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 237 } 238 #if defined(PETSC_USE_CTABLE) 239 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 240 col = col - 1; 241 #else 242 col = baij->colmap[in[j]/bs] - 1; 243 #endif 244 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 245 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 246 col = in[j]; 247 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 248 B = baij->B; 249 b = (Mat_SeqBAIJ*)(B)->data; 250 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 251 ba =b->a; 252 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 253 else col += in[j]%bs; 254 } else col = in[j]; 255 if (roworiented) value = v[i*n+j]; 256 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 (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 263 if (!baij->donotstash) { 264 mat->assembled = PETSC_FALSE; 265 if (roworiented) { 266 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 267 } else { 268 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 269 } 270 } 271 } 272 } 273 PetscFunctionReturn(0); 274 } 275 276 #undef __FUNCT__ 277 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 278 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 279 { 280 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 281 const PetscScalar *value; 282 MatScalar *barray = baij->barray; 283 PetscBool roworiented = baij->roworiented; 284 PetscErrorCode ierr; 285 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 286 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 287 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 288 289 PetscFunctionBegin; 290 if (!barray) { 291 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 292 baij->barray = barray; 293 } 294 295 if (roworiented) stepval = (n-1)*bs; 296 else 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_COMM_SELF,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) + j)*bs; 314 } else { 315 value = v + (j*(stepval+bs) + i)*bs; 316 } 317 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 318 for (jj=0; jj<bs; jj++) barray[jj] = value[jj]; 319 barray += bs; 320 } 321 barray -= bs2; 322 } 323 324 if (in[j] >= cstart && in[j] < cend) { 325 col = in[j] - cstart; 326 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 327 } else if (in[j] < 0) continue; 328 #if defined(PETSC_USE_DEBUG) 329 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1); 330 #endif 331 else { 332 if (mat->was_assembled) { 333 if (!baij->colmap) { 334 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 335 } 336 337 #if defined(PETSC_USE_DEBUG) 338 #if defined(PETSC_USE_CTABLE) 339 { PetscInt data; 340 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 341 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 342 } 343 #else 344 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 345 #endif 346 #endif 347 #if defined(PETSC_USE_CTABLE) 348 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 349 col = (col - 1)/bs; 350 #else 351 col = (baij->colmap[in[j]] - 1)/bs; 352 #endif 353 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 354 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 355 col = in[j]; 356 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", bs*im[i], bs*in[j]); 357 } else col = in[j]; 358 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 359 } 360 } 361 } else { 362 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 363 if (!baij->donotstash) { 364 if (roworiented) { 365 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 366 } else { 367 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 368 } 369 } 370 } 371 } 372 PetscFunctionReturn(0); 373 } 374 375 #define HASH_KEY 0.6180339887 376 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 377 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 378 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 379 #undef __FUNCT__ 380 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 381 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 382 { 383 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 384 PetscBool roworiented = baij->roworiented; 385 PetscErrorCode ierr; 386 PetscInt i,j,row,col; 387 PetscInt rstart_orig=mat->rmap->rstart; 388 PetscInt rend_orig =mat->rmap->rend,Nbs=baij->Nbs; 389 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 390 PetscReal tmp; 391 MatScalar **HD = baij->hd,value; 392 #if defined(PETSC_USE_DEBUG) 393 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 394 #endif 395 396 PetscFunctionBegin; 397 if (v) PetscValidScalarPointer(v,6); 398 for (i=0; i<m; i++) { 399 #if defined(PETSC_USE_DEBUG) 400 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 401 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 402 #endif 403 row = im[i]; 404 if (row >= rstart_orig && row < rend_orig) { 405 for (j=0; j<n; j++) { 406 col = in[j]; 407 if (roworiented) value = v[i*n+j]; 408 else value = v[i+j*m]; 409 /* Look up PetscInto the Hash Table */ 410 key = (row/bs)*Nbs+(col/bs)+1; 411 h1 = HASH(size,key,tmp); 412 413 414 idx = h1; 415 #if defined(PETSC_USE_DEBUG) 416 insert_ct++; 417 total_ct++; 418 if (HT[idx] != key) { 419 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 420 if (idx == size) { 421 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 422 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 423 } 424 } 425 #else 426 if (HT[idx] != key) { 427 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 428 if (idx == size) { 429 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 430 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 431 } 432 } 433 #endif 434 /* A HASH table entry is found, so insert the values at the correct address */ 435 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 436 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 437 } 438 } else if (!baij->donotstash) { 439 if (roworiented) { 440 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 441 } else { 442 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 443 } 444 } 445 } 446 #if defined(PETSC_USE_DEBUG) 447 baij->ht_total_ct = total_ct; 448 baij->ht_insert_ct = insert_ct; 449 #endif 450 PetscFunctionReturn(0); 451 } 452 453 #undef __FUNCT__ 454 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 455 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 456 { 457 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 458 PetscBool roworiented = baij->roworiented; 459 PetscErrorCode ierr; 460 PetscInt i,j,ii,jj,row,col; 461 PetscInt rstart=baij->rstartbs; 462 PetscInt rend =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 463 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 464 PetscReal tmp; 465 MatScalar **HD = baij->hd,*baij_a; 466 const PetscScalar *v_t,*value; 467 #if defined(PETSC_USE_DEBUG) 468 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 469 #endif 470 471 PetscFunctionBegin; 472 if (roworiented) stepval = (n-1)*bs; 473 else stepval = (m-1)*bs; 474 475 for (i=0; i<m; i++) { 476 #if defined(PETSC_USE_DEBUG) 477 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 478 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 479 #endif 480 row = im[i]; 481 v_t = v + i*nbs2; 482 if (row >= rstart && row < rend) { 483 for (j=0; j<n; j++) { 484 col = in[j]; 485 486 /* Look up into the Hash Table */ 487 key = row*Nbs+col+1; 488 h1 = HASH(size,key,tmp); 489 490 idx = h1; 491 #if defined(PETSC_USE_DEBUG) 492 total_ct++; 493 insert_ct++; 494 if (HT[idx] != key) { 495 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 496 if (idx == size) { 497 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 498 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 499 } 500 } 501 #else 502 if (HT[idx] != key) { 503 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 504 if (idx == size) { 505 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 506 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 507 } 508 } 509 #endif 510 baij_a = HD[idx]; 511 if (roworiented) { 512 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 513 /* value = v + (i*(stepval+bs)+j)*bs; */ 514 value = v_t; 515 v_t += bs; 516 if (addv == ADD_VALUES) { 517 for (ii=0; ii<bs; ii++,value+=stepval) { 518 for (jj=ii; jj<bs2; jj+=bs) { 519 baij_a[jj] += *value++; 520 } 521 } 522 } else { 523 for (ii=0; ii<bs; ii++,value+=stepval) { 524 for (jj=ii; jj<bs2; jj+=bs) { 525 baij_a[jj] = *value++; 526 } 527 } 528 } 529 } else { 530 value = v + j*(stepval+bs)*bs + i*bs; 531 if (addv == ADD_VALUES) { 532 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 533 for (jj=0; jj<bs; jj++) { 534 baij_a[jj] += *value++; 535 } 536 } 537 } else { 538 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 539 for (jj=0; jj<bs; jj++) { 540 baij_a[jj] = *value++; 541 } 542 } 543 } 544 } 545 } 546 } else { 547 if (!baij->donotstash) { 548 if (roworiented) { 549 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 550 } else { 551 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 552 } 553 } 554 } 555 } 556 #if defined(PETSC_USE_DEBUG) 557 baij->ht_total_ct = total_ct; 558 baij->ht_insert_ct = insert_ct; 559 #endif 560 PetscFunctionReturn(0); 561 } 562 563 #undef __FUNCT__ 564 #define __FUNCT__ "MatGetValues_MPIBAIJ" 565 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 566 { 567 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 568 PetscErrorCode ierr; 569 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 570 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 571 572 PetscFunctionBegin; 573 for (i=0; i<m; i++) { 574 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 575 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 576 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 577 row = idxm[i] - bsrstart; 578 for (j=0; j<n; j++) { 579 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 580 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 581 if (idxn[j] >= bscstart && idxn[j] < bscend) { 582 col = idxn[j] - bscstart; 583 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 584 } else { 585 if (!baij->colmap) { 586 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 587 } 588 #if defined(PETSC_USE_CTABLE) 589 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 590 data--; 591 #else 592 data = baij->colmap[idxn[j]/bs]-1; 593 #endif 594 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 595 else { 596 col = data + idxn[j]%bs; 597 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 598 } 599 } 600 } 601 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 602 } 603 PetscFunctionReturn(0); 604 } 605 606 #undef __FUNCT__ 607 #define __FUNCT__ "MatNorm_MPIBAIJ" 608 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 609 { 610 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 611 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 612 PetscErrorCode ierr; 613 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 614 PetscReal sum = 0.0; 615 MatScalar *v; 616 617 PetscFunctionBegin; 618 if (baij->size == 1) { 619 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 620 } else { 621 if (type == NORM_FROBENIUS) { 622 v = amat->a; 623 nz = amat->nz*bs2; 624 for (i=0; i<nz; i++) { 625 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 626 } 627 v = bmat->a; 628 nz = bmat->nz*bs2; 629 for (i=0; i<nz; i++) { 630 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 631 } 632 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 633 *nrm = PetscSqrtReal(*nrm); 634 } else if (type == NORM_1) { /* max column sum */ 635 PetscReal *tmp,*tmp2; 636 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 637 ierr = PetscMalloc2(mat->cmap->N,PetscReal,&tmp,mat->cmap->N,PetscReal,&tmp2);CHKERRQ(ierr); 638 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 639 v = amat->a; jj = amat->j; 640 for (i=0; i<amat->nz; i++) { 641 for (j=0; j<bs; j++) { 642 col = bs*(cstart + *jj) + j; /* column index */ 643 for (row=0; row<bs; row++) { 644 tmp[col] += PetscAbsScalar(*v); v++; 645 } 646 } 647 jj++; 648 } 649 v = bmat->a; jj = bmat->j; 650 for (i=0; i<bmat->nz; i++) { 651 for (j=0; j<bs; j++) { 652 col = bs*garray[*jj] + j; 653 for (row=0; row<bs; row++) { 654 tmp[col] += PetscAbsScalar(*v); v++; 655 } 656 } 657 jj++; 658 } 659 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 660 *nrm = 0.0; 661 for (j=0; j<mat->cmap->N; j++) { 662 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 663 } 664 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 665 } else if (type == NORM_INFINITY) { /* max row sum */ 666 PetscReal *sums; 667 ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr); 668 sum = 0.0; 669 for (j=0; j<amat->mbs; j++) { 670 for (row=0; row<bs; row++) sums[row] = 0.0; 671 v = amat->a + bs2*amat->i[j]; 672 nz = amat->i[j+1]-amat->i[j]; 673 for (i=0; i<nz; i++) { 674 for (col=0; col<bs; col++) { 675 for (row=0; row<bs; row++) { 676 sums[row] += PetscAbsScalar(*v); v++; 677 } 678 } 679 } 680 v = bmat->a + bs2*bmat->i[j]; 681 nz = bmat->i[j+1]-bmat->i[j]; 682 for (i=0; i<nz; i++) { 683 for (col=0; col<bs; col++) { 684 for (row=0; row<bs; row++) { 685 sums[row] += PetscAbsScalar(*v); v++; 686 } 687 } 688 } 689 for (row=0; row<bs; row++) { 690 if (sums[row] > sum) sum = sums[row]; 691 } 692 } 693 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 694 ierr = PetscFree(sums);CHKERRQ(ierr); 695 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet"); 696 } 697 PetscFunctionReturn(0); 698 } 699 700 /* 701 Creates the hash table, and sets the table 702 This table is created only once. 703 If new entried need to be added to the matrix 704 then the hash table has to be destroyed and 705 recreated. 706 */ 707 #undef __FUNCT__ 708 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 709 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 710 { 711 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 712 Mat A = baij->A,B=baij->B; 713 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data; 714 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 715 PetscErrorCode ierr; 716 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 717 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 718 PetscInt *HT,key; 719 MatScalar **HD; 720 PetscReal tmp; 721 #if defined(PETSC_USE_INFO) 722 PetscInt ct=0,max=0; 723 #endif 724 725 PetscFunctionBegin; 726 if (baij->ht) PetscFunctionReturn(0); 727 728 baij->ht_size = (PetscInt)(factor*nz); 729 ht_size = baij->ht_size; 730 731 /* Allocate Memory for Hash Table */ 732 ierr = PetscMalloc2(ht_size,MatScalar*,&baij->hd,ht_size,PetscInt,&baij->ht);CHKERRQ(ierr); 733 ierr = PetscMemzero(baij->hd,ht_size*sizeof(MatScalar*));CHKERRQ(ierr); 734 ierr = PetscMemzero(baij->ht,ht_size*sizeof(PetscInt));CHKERRQ(ierr); 735 HD = baij->hd; 736 HT = baij->ht; 737 738 /* Loop Over A */ 739 for (i=0; i<a->mbs; i++) { 740 for (j=ai[i]; j<ai[i+1]; j++) { 741 row = i+rstart; 742 col = aj[j]+cstart; 743 744 key = row*Nbs + col + 1; 745 h1 = HASH(ht_size,key,tmp); 746 for (k=0; k<ht_size; k++) { 747 if (!HT[(h1+k)%ht_size]) { 748 HT[(h1+k)%ht_size] = key; 749 HD[(h1+k)%ht_size] = a->a + j*bs2; 750 break; 751 #if defined(PETSC_USE_INFO) 752 } else { 753 ct++; 754 #endif 755 } 756 } 757 #if defined(PETSC_USE_INFO) 758 if (k> max) max = k; 759 #endif 760 } 761 } 762 /* Loop Over B */ 763 for (i=0; i<b->mbs; i++) { 764 for (j=bi[i]; j<bi[i+1]; j++) { 765 row = i+rstart; 766 col = garray[bj[j]]; 767 key = row*Nbs + col + 1; 768 h1 = HASH(ht_size,key,tmp); 769 for (k=0; k<ht_size; k++) { 770 if (!HT[(h1+k)%ht_size]) { 771 HT[(h1+k)%ht_size] = key; 772 HD[(h1+k)%ht_size] = b->a + j*bs2; 773 break; 774 #if defined(PETSC_USE_INFO) 775 } else { 776 ct++; 777 #endif 778 } 779 } 780 #if defined(PETSC_USE_INFO) 781 if (k> max) max = k; 782 #endif 783 } 784 } 785 786 /* Print Summary */ 787 #if defined(PETSC_USE_INFO) 788 for (i=0,j=0; i<ht_size; i++) { 789 if (HT[i]) j++; 790 } 791 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 792 #endif 793 PetscFunctionReturn(0); 794 } 795 796 #undef __FUNCT__ 797 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 798 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 799 { 800 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 801 PetscErrorCode ierr; 802 PetscInt nstash,reallocs; 803 InsertMode addv; 804 805 PetscFunctionBegin; 806 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 807 808 /* make sure all processors are either in INSERTMODE or ADDMODE */ 809 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 810 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 811 mat->insertmode = addv; /* in case this processor had no cache */ 812 813 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 814 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 815 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 816 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 817 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 818 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 819 PetscFunctionReturn(0); 820 } 821 822 #undef __FUNCT__ 823 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 824 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 825 { 826 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 827 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)baij->A->data; 828 PetscErrorCode ierr; 829 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 830 PetscInt *row,*col; 831 PetscBool r1,r2,r3,other_disassembled; 832 MatScalar *val; 833 InsertMode addv = mat->insertmode; 834 PetscMPIInt n; 835 836 PetscFunctionBegin; 837 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 838 if (!baij->donotstash && !mat->nooffprocentries) { 839 while (1) { 840 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 841 if (!flg) break; 842 843 for (i=0; i<n;) { 844 /* Now identify the consecutive vals belonging to the same row */ 845 for (j=i,rstart=row[j]; j<n; j++) { 846 if (row[j] != rstart) break; 847 } 848 if (j < n) ncols = j-i; 849 else ncols = n-i; 850 /* Now assemble all these values with a single function call */ 851 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 852 i = j; 853 } 854 } 855 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 856 /* Now process the block-stash. Since the values are stashed column-oriented, 857 set the roworiented flag to column oriented, and after MatSetValues() 858 restore the original flags */ 859 r1 = baij->roworiented; 860 r2 = a->roworiented; 861 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 862 863 baij->roworiented = PETSC_FALSE; 864 a->roworiented = PETSC_FALSE; 865 866 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 867 while (1) { 868 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 869 if (!flg) break; 870 871 for (i=0; i<n;) { 872 /* Now identify the consecutive vals belonging to the same row */ 873 for (j=i,rstart=row[j]; j<n; j++) { 874 if (row[j] != rstart) break; 875 } 876 if (j < n) ncols = j-i; 877 else ncols = n-i; 878 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 879 i = j; 880 } 881 } 882 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 883 884 baij->roworiented = r1; 885 a->roworiented = r2; 886 887 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 888 } 889 890 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 891 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 892 893 /* determine if any processor has disassembled, if so we must 894 also disassemble ourselfs, in order that we may reassemble. */ 895 /* 896 if nonzero structure of submatrix B cannot change then we know that 897 no processor disassembled thus we can skip this stuff 898 */ 899 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 900 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 901 if (mat->was_assembled && !other_disassembled) { 902 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 903 } 904 } 905 906 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 907 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 908 } 909 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 910 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 911 912 #if defined(PETSC_USE_INFO) 913 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 914 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 915 916 baij->ht_total_ct = 0; 917 baij->ht_insert_ct = 0; 918 } 919 #endif 920 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 921 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 922 923 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 924 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 925 } 926 927 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 928 929 baij->rowvalues = 0; 930 PetscFunctionReturn(0); 931 } 932 933 #include <petscdraw.h> 934 #undef __FUNCT__ 935 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 936 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 937 { 938 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 939 PetscErrorCode ierr; 940 PetscMPIInt size = baij->size,rank = baij->rank; 941 PetscInt bs = mat->rmap->bs; 942 PetscBool iascii,isdraw; 943 PetscViewer sviewer; 944 PetscViewerFormat format; 945 946 PetscFunctionBegin; 947 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 948 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 949 if (iascii) { 950 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 951 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 952 MatInfo info; 953 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 954 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 955 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 956 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 957 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 958 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 959 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 960 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 961 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 962 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 963 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 964 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 965 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 966 PetscFunctionReturn(0); 967 } else if (format == PETSC_VIEWER_ASCII_INFO) { 968 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 969 PetscFunctionReturn(0); 970 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 971 PetscFunctionReturn(0); 972 } 973 } 974 975 if (isdraw) { 976 PetscDraw draw; 977 PetscBool isnull; 978 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 979 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 980 } 981 982 if (size == 1) { 983 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 984 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 985 } else { 986 /* assemble the entire matrix onto first processor. */ 987 Mat A; 988 Mat_SeqBAIJ *Aloc; 989 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 990 MatScalar *a; 991 992 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 993 /* Perhaps this should be the type of mat? */ 994 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 995 if (!rank) { 996 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 997 } else { 998 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 999 } 1000 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1001 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1002 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1003 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1004 1005 /* copy over the A part */ 1006 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1007 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1008 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1009 1010 for (i=0; i<mbs; i++) { 1011 rvals[0] = bs*(baij->rstartbs + i); 1012 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1013 for (j=ai[i]; j<ai[i+1]; j++) { 1014 col = (baij->cstartbs+aj[j])*bs; 1015 for (k=0; k<bs; k++) { 1016 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1017 col++; a += bs; 1018 } 1019 } 1020 } 1021 /* copy over the B part */ 1022 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1023 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1024 for (i=0; i<mbs; i++) { 1025 rvals[0] = bs*(baij->rstartbs + i); 1026 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1027 for (j=ai[i]; j<ai[i+1]; j++) { 1028 col = baij->garray[aj[j]]*bs; 1029 for (k=0; k<bs; k++) { 1030 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1031 col++; a += bs; 1032 } 1033 } 1034 } 1035 ierr = PetscFree(rvals);CHKERRQ(ierr); 1036 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1037 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1038 /* 1039 Everyone has to call to draw the matrix since the graphics waits are 1040 synchronized across all processors that share the PetscDraw object 1041 */ 1042 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1043 if (!rank) { 1044 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1045 /* Set the type name to MATMPIBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqBAIJ_ASCII()*/ 1046 PetscStrcpy(((PetscObject)((Mat_MPIBAIJ*)(A->data))->A)->type_name,MATMPIBAIJ); 1047 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1048 } 1049 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1050 ierr = MatDestroy(&A);CHKERRQ(ierr); 1051 } 1052 PetscFunctionReturn(0); 1053 } 1054 1055 #undef __FUNCT__ 1056 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1057 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1058 { 1059 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1060 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1061 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1062 PetscErrorCode ierr; 1063 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1064 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1065 int fd; 1066 PetscScalar *column_values; 1067 FILE *file; 1068 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1069 PetscInt message_count,flowcontrolcount; 1070 1071 PetscFunctionBegin; 1072 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1073 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1074 nz = bs2*(A->nz + B->nz); 1075 rlen = mat->rmap->n; 1076 if (!rank) { 1077 header[0] = MAT_FILE_CLASSID; 1078 header[1] = mat->rmap->N; 1079 header[2] = mat->cmap->N; 1080 1081 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1082 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1083 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1084 /* get largest number of rows any processor has */ 1085 range = mat->rmap->range; 1086 for (i=1; i<size; i++) { 1087 rlen = PetscMax(rlen,range[i+1] - range[i]); 1088 } 1089 } else { 1090 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1091 } 1092 1093 ierr = PetscMalloc((rlen/bs)*sizeof(PetscInt),&crow_lens);CHKERRQ(ierr); 1094 /* compute lengths of each row */ 1095 for (i=0; i<a->mbs; i++) { 1096 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1097 } 1098 /* store the row lengths to the file */ 1099 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1100 if (!rank) { 1101 MPI_Status status; 1102 ierr = PetscMalloc(rlen*sizeof(PetscInt),&row_lens);CHKERRQ(ierr); 1103 rlen = (range[1] - range[0])/bs; 1104 for (i=0; i<rlen; i++) { 1105 for (j=0; j<bs; j++) { 1106 row_lens[i*bs+j] = bs*crow_lens[i]; 1107 } 1108 } 1109 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1110 for (i=1; i<size; i++) { 1111 rlen = (range[i+1] - range[i])/bs; 1112 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1113 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1114 for (k=0; k<rlen; k++) { 1115 for (j=0; j<bs; j++) { 1116 row_lens[k*bs+j] = bs*crow_lens[k]; 1117 } 1118 } 1119 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1120 } 1121 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1122 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1123 } else { 1124 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1125 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1126 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1127 } 1128 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1129 1130 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1131 information needed to make it for each row from a block row. This does require more communication but still not more than 1132 the communication needed for the nonzero values */ 1133 nzmax = nz; /* space a largest processor needs */ 1134 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1135 ierr = PetscMalloc(nzmax*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1136 cnt = 0; 1137 for (i=0; i<a->mbs; i++) { 1138 pcnt = cnt; 1139 for (j=B->i[i]; j<B->i[i+1]; j++) { 1140 if ((col = garray[B->j[j]]) > cstart) break; 1141 for (l=0; l<bs; l++) { 1142 column_indices[cnt++] = bs*col+l; 1143 } 1144 } 1145 for (k=A->i[i]; k<A->i[i+1]; k++) { 1146 for (l=0; l<bs; l++) { 1147 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1148 } 1149 } 1150 for (; j<B->i[i+1]; j++) { 1151 for (l=0; l<bs; l++) { 1152 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1153 } 1154 } 1155 len = cnt - pcnt; 1156 for (k=1; k<bs; k++) { 1157 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1158 cnt += len; 1159 } 1160 } 1161 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1162 1163 /* store the columns to the file */ 1164 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1165 if (!rank) { 1166 MPI_Status status; 1167 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1168 for (i=1; i<size; i++) { 1169 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1170 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1171 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1172 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1173 } 1174 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1175 } else { 1176 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1177 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1178 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1179 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1180 } 1181 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1182 1183 /* load up the numerical values */ 1184 ierr = PetscMalloc(nzmax*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1185 cnt = 0; 1186 for (i=0; i<a->mbs; i++) { 1187 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1188 for (j=B->i[i]; j<B->i[i+1]; j++) { 1189 if (garray[B->j[j]] > cstart) break; 1190 for (l=0; l<bs; l++) { 1191 for (ll=0; ll<bs; ll++) { 1192 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1193 } 1194 } 1195 cnt += bs; 1196 } 1197 for (k=A->i[i]; k<A->i[i+1]; k++) { 1198 for (l=0; l<bs; l++) { 1199 for (ll=0; ll<bs; ll++) { 1200 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1201 } 1202 } 1203 cnt += bs; 1204 } 1205 for (; j<B->i[i+1]; j++) { 1206 for (l=0; l<bs; l++) { 1207 for (ll=0; ll<bs; ll++) { 1208 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1209 } 1210 } 1211 cnt += bs; 1212 } 1213 cnt += (bs-1)*rlen; 1214 } 1215 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1216 1217 /* store the column values to the file */ 1218 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1219 if (!rank) { 1220 MPI_Status status; 1221 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1222 for (i=1; i<size; i++) { 1223 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1224 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1225 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1226 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1227 } 1228 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1229 } else { 1230 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1231 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1232 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1233 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1234 } 1235 ierr = PetscFree(column_values);CHKERRQ(ierr); 1236 1237 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1238 if (file) { 1239 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1240 } 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatView_MPIBAIJ" 1246 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1247 { 1248 PetscErrorCode ierr; 1249 PetscBool iascii,isdraw,issocket,isbinary; 1250 1251 PetscFunctionBegin; 1252 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1253 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1254 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1255 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1256 if (iascii || isdraw || issocket) { 1257 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1258 } else if (isbinary) { 1259 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1260 } 1261 PetscFunctionReturn(0); 1262 } 1263 1264 #undef __FUNCT__ 1265 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1266 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1267 { 1268 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1269 PetscErrorCode ierr; 1270 1271 PetscFunctionBegin; 1272 #if defined(PETSC_USE_LOG) 1273 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1274 #endif 1275 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1276 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1277 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1278 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1279 #if defined(PETSC_USE_CTABLE) 1280 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1281 #else 1282 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1283 #endif 1284 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1285 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1286 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1287 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1288 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1289 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1290 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1291 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1292 1293 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1294 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1295 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1303 PetscFunctionReturn(0); 1304 } 1305 1306 #undef __FUNCT__ 1307 #define __FUNCT__ "MatMult_MPIBAIJ" 1308 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1309 { 1310 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1311 PetscErrorCode ierr; 1312 PetscInt nt; 1313 1314 PetscFunctionBegin; 1315 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1316 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1317 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1318 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1319 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1320 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1321 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1322 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1323 PetscFunctionReturn(0); 1324 } 1325 1326 #undef __FUNCT__ 1327 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1328 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1329 { 1330 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1331 PetscErrorCode ierr; 1332 1333 PetscFunctionBegin; 1334 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1335 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1336 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1337 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1338 PetscFunctionReturn(0); 1339 } 1340 1341 #undef __FUNCT__ 1342 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1343 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1344 { 1345 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1346 PetscErrorCode ierr; 1347 PetscBool merged; 1348 1349 PetscFunctionBegin; 1350 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1351 /* do nondiagonal part */ 1352 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1353 if (!merged) { 1354 /* send it on its way */ 1355 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1356 /* do local part */ 1357 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1358 /* receive remote parts: note this assumes the values are not actually */ 1359 /* inserted in yy until the next line */ 1360 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1361 } else { 1362 /* do local part */ 1363 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1364 /* send it on its way */ 1365 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1366 /* values actually were received in the Begin() but we need to call this nop */ 1367 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1368 } 1369 PetscFunctionReturn(0); 1370 } 1371 1372 #undef __FUNCT__ 1373 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1374 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1375 { 1376 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1377 PetscErrorCode ierr; 1378 1379 PetscFunctionBegin; 1380 /* do nondiagonal part */ 1381 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1382 /* send it on its way */ 1383 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1384 /* do local part */ 1385 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1386 /* receive remote parts: note this assumes the values are not actually */ 1387 /* inserted in yy until the next line, which is true for my implementation*/ 1388 /* but is not perhaps always true. */ 1389 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1390 PetscFunctionReturn(0); 1391 } 1392 1393 /* 1394 This only works correctly for square matrices where the subblock A->A is the 1395 diagonal block 1396 */ 1397 #undef __FUNCT__ 1398 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1399 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1400 { 1401 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1402 PetscErrorCode ierr; 1403 1404 PetscFunctionBegin; 1405 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1406 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1407 PetscFunctionReturn(0); 1408 } 1409 1410 #undef __FUNCT__ 1411 #define __FUNCT__ "MatScale_MPIBAIJ" 1412 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1413 { 1414 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1415 PetscErrorCode ierr; 1416 1417 PetscFunctionBegin; 1418 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1419 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1420 PetscFunctionReturn(0); 1421 } 1422 1423 #undef __FUNCT__ 1424 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1425 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1426 { 1427 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1428 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1429 PetscErrorCode ierr; 1430 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1431 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1432 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1433 1434 PetscFunctionBegin; 1435 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1436 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1437 mat->getrowactive = PETSC_TRUE; 1438 1439 if (!mat->rowvalues && (idx || v)) { 1440 /* 1441 allocate enough space to hold information from the longest row. 1442 */ 1443 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1444 PetscInt max = 1,mbs = mat->mbs,tmp; 1445 for (i=0; i<mbs; i++) { 1446 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1447 if (max < tmp) max = tmp; 1448 } 1449 ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1450 } 1451 lrow = row - brstart; 1452 1453 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1454 if (!v) {pvA = 0; pvB = 0;} 1455 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1456 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1457 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1458 nztot = nzA + nzB; 1459 1460 cmap = mat->garray; 1461 if (v || idx) { 1462 if (nztot) { 1463 /* Sort by increasing column numbers, assuming A and B already sorted */ 1464 PetscInt imark = -1; 1465 if (v) { 1466 *v = v_p = mat->rowvalues; 1467 for (i=0; i<nzB; i++) { 1468 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1469 else break; 1470 } 1471 imark = i; 1472 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1473 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1474 } 1475 if (idx) { 1476 *idx = idx_p = mat->rowindices; 1477 if (imark > -1) { 1478 for (i=0; i<imark; i++) { 1479 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1480 } 1481 } else { 1482 for (i=0; i<nzB; i++) { 1483 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1484 else break; 1485 } 1486 imark = i; 1487 } 1488 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1489 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1490 } 1491 } else { 1492 if (idx) *idx = 0; 1493 if (v) *v = 0; 1494 } 1495 } 1496 *nz = nztot; 1497 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1498 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1499 PetscFunctionReturn(0); 1500 } 1501 1502 #undef __FUNCT__ 1503 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1504 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1505 { 1506 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1507 1508 PetscFunctionBegin; 1509 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1510 baij->getrowactive = PETSC_FALSE; 1511 PetscFunctionReturn(0); 1512 } 1513 1514 #undef __FUNCT__ 1515 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1516 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1517 { 1518 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1519 PetscErrorCode ierr; 1520 1521 PetscFunctionBegin; 1522 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1523 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1524 PetscFunctionReturn(0); 1525 } 1526 1527 #undef __FUNCT__ 1528 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1529 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1530 { 1531 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1532 Mat A = a->A,B = a->B; 1533 PetscErrorCode ierr; 1534 PetscReal isend[5],irecv[5]; 1535 1536 PetscFunctionBegin; 1537 info->block_size = (PetscReal)matin->rmap->bs; 1538 1539 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1540 1541 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1542 isend[3] = info->memory; isend[4] = info->mallocs; 1543 1544 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1545 1546 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1547 isend[3] += info->memory; isend[4] += info->mallocs; 1548 1549 if (flag == MAT_LOCAL) { 1550 info->nz_used = isend[0]; 1551 info->nz_allocated = isend[1]; 1552 info->nz_unneeded = isend[2]; 1553 info->memory = isend[3]; 1554 info->mallocs = isend[4]; 1555 } else if (flag == MAT_GLOBAL_MAX) { 1556 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1557 1558 info->nz_used = irecv[0]; 1559 info->nz_allocated = irecv[1]; 1560 info->nz_unneeded = irecv[2]; 1561 info->memory = irecv[3]; 1562 info->mallocs = irecv[4]; 1563 } else if (flag == MAT_GLOBAL_SUM) { 1564 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1565 1566 info->nz_used = irecv[0]; 1567 info->nz_allocated = irecv[1]; 1568 info->nz_unneeded = irecv[2]; 1569 info->memory = irecv[3]; 1570 info->mallocs = irecv[4]; 1571 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1572 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1573 info->fill_ratio_needed = 0; 1574 info->factor_mallocs = 0; 1575 PetscFunctionReturn(0); 1576 } 1577 1578 #undef __FUNCT__ 1579 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1580 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1581 { 1582 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1583 PetscErrorCode ierr; 1584 1585 PetscFunctionBegin; 1586 switch (op) { 1587 case MAT_NEW_NONZERO_LOCATIONS: 1588 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1589 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1590 case MAT_KEEP_NONZERO_PATTERN: 1591 case MAT_NEW_NONZERO_LOCATION_ERR: 1592 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1593 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1594 break; 1595 case MAT_ROW_ORIENTED: 1596 a->roworiented = flg; 1597 1598 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1599 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1600 break; 1601 case MAT_NEW_DIAGONALS: 1602 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1603 break; 1604 case MAT_IGNORE_OFF_PROC_ENTRIES: 1605 a->donotstash = flg; 1606 break; 1607 case MAT_USE_HASH_TABLE: 1608 a->ht_flag = flg; 1609 break; 1610 case MAT_SYMMETRIC: 1611 case MAT_STRUCTURALLY_SYMMETRIC: 1612 case MAT_HERMITIAN: 1613 case MAT_SYMMETRY_ETERNAL: 1614 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1615 break; 1616 default: 1617 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1618 } 1619 PetscFunctionReturn(0); 1620 } 1621 1622 #undef __FUNCT__ 1623 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1624 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1625 { 1626 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1627 Mat_SeqBAIJ *Aloc; 1628 Mat B; 1629 PetscErrorCode ierr; 1630 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1631 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1632 MatScalar *a; 1633 1634 PetscFunctionBegin; 1635 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1636 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1637 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1638 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1639 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1640 /* Do not know preallocation information, but must set block size */ 1641 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1642 } else { 1643 B = *matout; 1644 } 1645 1646 /* copy over the A part */ 1647 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1648 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1649 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1650 1651 for (i=0; i<mbs; i++) { 1652 rvals[0] = bs*(baij->rstartbs + i); 1653 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1654 for (j=ai[i]; j<ai[i+1]; j++) { 1655 col = (baij->cstartbs+aj[j])*bs; 1656 for (k=0; k<bs; k++) { 1657 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1658 1659 col++; a += bs; 1660 } 1661 } 1662 } 1663 /* copy over the B part */ 1664 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1665 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1666 for (i=0; i<mbs; i++) { 1667 rvals[0] = bs*(baij->rstartbs + i); 1668 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1669 for (j=ai[i]; j<ai[i+1]; j++) { 1670 col = baij->garray[aj[j]]*bs; 1671 for (k=0; k<bs; k++) { 1672 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1673 col++; 1674 a += bs; 1675 } 1676 } 1677 } 1678 ierr = PetscFree(rvals);CHKERRQ(ierr); 1679 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1680 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1681 1682 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1683 else { 1684 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1685 } 1686 PetscFunctionReturn(0); 1687 } 1688 1689 #undef __FUNCT__ 1690 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1691 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1692 { 1693 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1694 Mat a = baij->A,b = baij->B; 1695 PetscErrorCode ierr; 1696 PetscInt s1,s2,s3; 1697 1698 PetscFunctionBegin; 1699 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1700 if (rr) { 1701 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1702 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1703 /* Overlap communication with computation. */ 1704 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1705 } 1706 if (ll) { 1707 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1708 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1709 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1710 } 1711 /* scale the diagonal block */ 1712 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1713 1714 if (rr) { 1715 /* Do a scatter end and then right scale the off-diagonal block */ 1716 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1717 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1718 } 1719 PetscFunctionReturn(0); 1720 } 1721 1722 #undef __FUNCT__ 1723 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1724 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1725 { 1726 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1727 PetscErrorCode ierr; 1728 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1729 PetscInt i,*owners = A->rmap->range; 1730 PetscInt *nprocs,j,idx,nsends,row; 1731 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1732 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1733 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1734 MPI_Comm comm; 1735 MPI_Request *send_waits,*recv_waits; 1736 MPI_Status recv_status,*send_status; 1737 const PetscScalar *xx; 1738 PetscScalar *bb; 1739 #if defined(PETSC_DEBUG) 1740 PetscBool found = PETSC_FALSE; 1741 #endif 1742 1743 PetscFunctionBegin; 1744 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1745 /* first count number of contributors to each processor */ 1746 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1747 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1748 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1749 j = 0; 1750 for (i=0; i<N; i++) { 1751 if (lastidx > (idx = rows[i])) j = 0; 1752 lastidx = idx; 1753 for (; j<size; j++) { 1754 if (idx >= owners[j] && idx < owners[j+1]) { 1755 nprocs[2*j]++; 1756 nprocs[2*j+1] = 1; 1757 owner[i] = j; 1758 #if defined(PETSC_DEBUG) 1759 found = PETSC_TRUE; 1760 #endif 1761 break; 1762 } 1763 } 1764 #if defined(PETSC_DEBUG) 1765 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1766 found = PETSC_FALSE; 1767 #endif 1768 } 1769 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 1770 1771 if (A->nooffproczerorows) { 1772 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 1773 nrecvs = nsends; 1774 nmax = N; 1775 } else { 1776 /* inform other processors of number of messages and max length*/ 1777 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1778 } 1779 1780 /* post receives: */ 1781 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1782 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1783 for (i=0; i<nrecvs; i++) { 1784 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1785 } 1786 1787 /* do sends: 1788 1) starts[i] gives the starting index in svalues for stuff going to 1789 the ith processor 1790 */ 1791 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1792 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1793 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1794 starts[0] = 0; 1795 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 1796 for (i=0; i<N; i++) { 1797 svalues[starts[owner[i]]++] = rows[i]; 1798 } 1799 1800 starts[0] = 0; 1801 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 1802 count = 0; 1803 for (i=0; i<size; i++) { 1804 if (nprocs[2*i+1]) { 1805 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1806 } 1807 } 1808 ierr = PetscFree(starts);CHKERRQ(ierr); 1809 1810 base = owners[rank]; 1811 1812 /* wait on receives */ 1813 ierr = PetscMalloc2(nrecvs+1,PetscInt,&lens,nrecvs+1,PetscInt,&source);CHKERRQ(ierr); 1814 count = nrecvs; 1815 slen = 0; 1816 while (count) { 1817 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1818 /* unpack receives into our local space */ 1819 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1820 1821 source[imdex] = recv_status.MPI_SOURCE; 1822 lens[imdex] = n; 1823 slen += n; 1824 count--; 1825 } 1826 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1827 1828 /* move the data into the send scatter */ 1829 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1830 count = 0; 1831 for (i=0; i<nrecvs; i++) { 1832 values = rvalues + i*nmax; 1833 for (j=0; j<lens[i]; j++) { 1834 lrows[count++] = values[j] - base; 1835 } 1836 } 1837 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1838 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1839 ierr = PetscFree(owner);CHKERRQ(ierr); 1840 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1841 1842 /* fix right hand side if needed */ 1843 if (x && b) { 1844 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1845 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1846 for (i=0; i<slen; i++) { 1847 bb[lrows[i]] = diag*xx[lrows[i]]; 1848 } 1849 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1850 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1851 } 1852 1853 /* actually zap the local rows */ 1854 /* 1855 Zero the required rows. If the "diagonal block" of the matrix 1856 is square and the user wishes to set the diagonal we use separate 1857 code so that MatSetValues() is not called for each diagonal allocating 1858 new memory, thus calling lots of mallocs and slowing things down. 1859 1860 */ 1861 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1862 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1863 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1864 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 1865 } else if (diag != 0.0) { 1866 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1867 if (((Mat_SeqBAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1868 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1869 for (i=0; i<slen; i++) { 1870 row = lrows[i] + rstart_bs; 1871 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1872 } 1873 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1874 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1875 } else { 1876 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1877 } 1878 1879 ierr = PetscFree(lrows);CHKERRQ(ierr); 1880 1881 /* wait on sends */ 1882 if (nsends) { 1883 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1884 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1885 ierr = PetscFree(send_status);CHKERRQ(ierr); 1886 } 1887 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1888 ierr = PetscFree(svalues);CHKERRQ(ierr); 1889 PetscFunctionReturn(0); 1890 } 1891 1892 #undef __FUNCT__ 1893 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1894 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1895 { 1896 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1897 PetscErrorCode ierr; 1898 1899 PetscFunctionBegin; 1900 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1901 PetscFunctionReturn(0); 1902 } 1903 1904 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1905 1906 #undef __FUNCT__ 1907 #define __FUNCT__ "MatEqual_MPIBAIJ" 1908 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1909 { 1910 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1911 Mat a,b,c,d; 1912 PetscBool flg; 1913 PetscErrorCode ierr; 1914 1915 PetscFunctionBegin; 1916 a = matA->A; b = matA->B; 1917 c = matB->A; d = matB->B; 1918 1919 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1920 if (flg) { 1921 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1922 } 1923 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1924 PetscFunctionReturn(0); 1925 } 1926 1927 #undef __FUNCT__ 1928 #define __FUNCT__ "MatCopy_MPIBAIJ" 1929 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1930 { 1931 PetscErrorCode ierr; 1932 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1933 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1934 1935 PetscFunctionBegin; 1936 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1937 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1938 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1939 } else { 1940 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1941 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1942 } 1943 PetscFunctionReturn(0); 1944 } 1945 1946 #undef __FUNCT__ 1947 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1948 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1949 { 1950 PetscErrorCode ierr; 1951 1952 PetscFunctionBegin; 1953 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1954 PetscFunctionReturn(0); 1955 } 1956 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1959 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1960 { 1961 PetscErrorCode ierr; 1962 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 1963 PetscBLASInt bnz,one=1; 1964 Mat_SeqBAIJ *x,*y; 1965 1966 PetscFunctionBegin; 1967 if (str == SAME_NONZERO_PATTERN) { 1968 PetscScalar alpha = a; 1969 x = (Mat_SeqBAIJ*)xx->A->data; 1970 y = (Mat_SeqBAIJ*)yy->A->data; 1971 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 1972 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1973 x = (Mat_SeqBAIJ*)xx->B->data; 1974 y = (Mat_SeqBAIJ*)yy->B->data; 1975 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 1976 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1977 } else { 1978 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1979 } 1980 PetscFunctionReturn(0); 1981 } 1982 1983 #undef __FUNCT__ 1984 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1985 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1986 { 1987 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1988 PetscErrorCode ierr; 1989 1990 PetscFunctionBegin; 1991 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1992 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1993 PetscFunctionReturn(0); 1994 } 1995 1996 #undef __FUNCT__ 1997 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 1998 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 1999 { 2000 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2001 PetscErrorCode ierr; 2002 2003 PetscFunctionBegin; 2004 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2005 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2011 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2012 { 2013 PetscErrorCode ierr; 2014 IS iscol_local; 2015 PetscInt csize; 2016 2017 PetscFunctionBegin; 2018 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2019 if (call == MAT_REUSE_MATRIX) { 2020 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2021 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2022 } else { 2023 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2024 } 2025 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2026 if (call == MAT_INITIAL_MATRIX) { 2027 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2028 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2029 } 2030 PetscFunctionReturn(0); 2031 } 2032 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2033 #undef __FUNCT__ 2034 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2035 /* 2036 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2037 in local and then by concatenating the local matrices the end result. 2038 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2039 */ 2040 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2041 { 2042 PetscErrorCode ierr; 2043 PetscMPIInt rank,size; 2044 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2045 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2046 Mat M,Mreuse; 2047 MatScalar *vwork,*aa; 2048 MPI_Comm comm; 2049 IS isrow_new, iscol_new; 2050 PetscBool idflag,allrows, allcols; 2051 Mat_SeqBAIJ *aij; 2052 2053 PetscFunctionBegin; 2054 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2055 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2056 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2057 /* The compression and expansion should be avoided. Doesn't point 2058 out errors, might change the indices, hence buggey */ 2059 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2060 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2061 2062 /* Check for special case: each processor gets entire matrix columns */ 2063 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2064 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2065 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2066 else allcols = PETSC_FALSE; 2067 2068 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2069 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2070 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2071 else allrows = PETSC_FALSE; 2072 2073 if (call == MAT_REUSE_MATRIX) { 2074 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2075 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2076 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2077 } else { 2078 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2079 } 2080 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2081 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2082 /* 2083 m - number of local rows 2084 n - number of columns (same on all processors) 2085 rstart - first row in new global matrix generated 2086 */ 2087 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2088 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2089 m = m/bs; 2090 n = n/bs; 2091 2092 if (call == MAT_INITIAL_MATRIX) { 2093 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2094 ii = aij->i; 2095 jj = aij->j; 2096 2097 /* 2098 Determine the number of non-zeros in the diagonal and off-diagonal 2099 portions of the matrix in order to do correct preallocation 2100 */ 2101 2102 /* first get start and end of "diagonal" columns */ 2103 if (csize == PETSC_DECIDE) { 2104 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2105 if (mglobal == n*bs) { /* square matrix */ 2106 nlocal = m; 2107 } else { 2108 nlocal = n/size + ((n % size) > rank); 2109 } 2110 } else { 2111 nlocal = csize/bs; 2112 } 2113 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2114 rstart = rend - nlocal; 2115 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2116 2117 /* next, compute all the lengths */ 2118 ierr = PetscMalloc2(m+1,PetscInt,&dlens,m+1,PetscInt,&olens);CHKERRQ(ierr); 2119 for (i=0; i<m; i++) { 2120 jend = ii[i+1] - ii[i]; 2121 olen = 0; 2122 dlen = 0; 2123 for (j=0; j<jend; j++) { 2124 if (*jj < rstart || *jj >= rend) olen++; 2125 else dlen++; 2126 jj++; 2127 } 2128 olens[i] = olen; 2129 dlens[i] = dlen; 2130 } 2131 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2132 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2133 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2134 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2135 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2136 } else { 2137 PetscInt ml,nl; 2138 2139 M = *newmat; 2140 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2141 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2142 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2143 /* 2144 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2145 rather than the slower MatSetValues(). 2146 */ 2147 M->was_assembled = PETSC_TRUE; 2148 M->assembled = PETSC_FALSE; 2149 } 2150 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2151 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2152 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2153 ii = aij->i; 2154 jj = aij->j; 2155 aa = aij->a; 2156 for (i=0; i<m; i++) { 2157 row = rstart/bs + i; 2158 nz = ii[i+1] - ii[i]; 2159 cwork = jj; jj += nz; 2160 vwork = aa; aa += nz*bs*bs; 2161 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2162 } 2163 2164 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2165 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2166 *newmat = M; 2167 2168 /* save submatrix used in processor for next request */ 2169 if (call == MAT_INITIAL_MATRIX) { 2170 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2171 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2172 } 2173 PetscFunctionReturn(0); 2174 } 2175 2176 #undef __FUNCT__ 2177 #define __FUNCT__ "MatPermute_MPIBAIJ" 2178 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2179 { 2180 MPI_Comm comm,pcomm; 2181 PetscInt clocal_size,nrows; 2182 const PetscInt *rows; 2183 PetscMPIInt size; 2184 IS crowp,lcolp; 2185 PetscErrorCode ierr; 2186 2187 PetscFunctionBegin; 2188 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2189 /* make a collective version of 'rowp' */ 2190 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2191 if (pcomm==comm) { 2192 crowp = rowp; 2193 } else { 2194 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2195 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2196 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2197 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2198 } 2199 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2200 /* make a local version of 'colp' */ 2201 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2202 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2203 if (size==1) { 2204 lcolp = colp; 2205 } else { 2206 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2207 } 2208 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2209 /* now we just get the submatrix */ 2210 ierr = MatGetLocalSize(A,PETSC_NULL,&clocal_size);CHKERRQ(ierr); 2211 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2212 /* clean up */ 2213 if (pcomm!=comm) { 2214 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2215 } 2216 if (size>1) { 2217 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2218 } 2219 PetscFunctionReturn(0); 2220 } 2221 2222 #undef __FUNCT__ 2223 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2224 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2225 { 2226 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2227 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2228 2229 PetscFunctionBegin; 2230 if (nghosts) *nghosts = B->nbs; 2231 if (ghosts) *ghosts = baij->garray; 2232 PetscFunctionReturn(0); 2233 } 2234 2235 #undef __FUNCT__ 2236 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2237 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2238 { 2239 Mat B; 2240 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2241 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2242 Mat_SeqAIJ *b; 2243 PetscErrorCode ierr; 2244 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2245 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2246 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2247 2248 PetscFunctionBegin; 2249 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2250 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2251 2252 /* ---------------------------------------------------------------- 2253 Tell every processor the number of nonzeros per row 2254 */ 2255 ierr = PetscMalloc((A->rmap->N/bs)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2256 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2257 lens[i] = ad->i[i-A->rmap->rstart/bs+1] - ad->i[i-A->rmap->rstart/bs] + bd->i[i-A->rmap->rstart/bs+1] - bd->i[i-A->rmap->rstart/bs]; 2258 } 2259 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2260 ierr = PetscMalloc(2*size*sizeof(PetscMPIInt),&recvcounts);CHKERRQ(ierr); 2261 displs = recvcounts + size; 2262 for (i=0; i<size; i++) { 2263 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2264 displs[i] = A->rmap->range[i]/bs; 2265 } 2266 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2267 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2268 #else 2269 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2270 #endif 2271 /* --------------------------------------------------------------- 2272 Create the sequential matrix of the same type as the local block diagonal 2273 */ 2274 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2275 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2276 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2277 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2278 b = (Mat_SeqAIJ*)B->data; 2279 2280 /*-------------------------------------------------------------------- 2281 Copy my part of matrix column indices over 2282 */ 2283 sendcount = ad->nz + bd->nz; 2284 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2285 a_jsendbuf = ad->j; 2286 b_jsendbuf = bd->j; 2287 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2288 cnt = 0; 2289 for (i=0; i<n; i++) { 2290 2291 /* put in lower diagonal portion */ 2292 m = bd->i[i+1] - bd->i[i]; 2293 while (m > 0) { 2294 /* is it above diagonal (in bd (compressed) numbering) */ 2295 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2296 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2297 m--; 2298 } 2299 2300 /* put in diagonal portion */ 2301 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2302 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2303 } 2304 2305 /* put in upper diagonal portion */ 2306 while (m-- > 0) { 2307 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2308 } 2309 } 2310 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2311 2312 /*-------------------------------------------------------------------- 2313 Gather all column indices to all processors 2314 */ 2315 for (i=0; i<size; i++) { 2316 recvcounts[i] = 0; 2317 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2318 recvcounts[i] += lens[j]; 2319 } 2320 } 2321 displs[0] = 0; 2322 for (i=1; i<size; i++) { 2323 displs[i] = displs[i-1] + recvcounts[i-1]; 2324 } 2325 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2326 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2327 #else 2328 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2329 #endif 2330 /*-------------------------------------------------------------------- 2331 Assemble the matrix into useable form (note numerical values not yet set) 2332 */ 2333 /* set the b->ilen (length of each row) values */ 2334 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2335 /* set the b->i indices */ 2336 b->i[0] = 0; 2337 for (i=1; i<=A->rmap->N/bs; i++) { 2338 b->i[i] = b->i[i-1] + lens[i-1]; 2339 } 2340 ierr = PetscFree(lens);CHKERRQ(ierr); 2341 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2342 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2343 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2344 2345 if (A->symmetric) { 2346 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2347 } else if (A->hermitian) { 2348 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2349 } else if (A->structurally_symmetric) { 2350 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2351 } 2352 *newmat = B; 2353 PetscFunctionReturn(0); 2354 } 2355 2356 #undef __FUNCT__ 2357 #define __FUNCT__ "MatSOR_MPIBAIJ" 2358 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2359 { 2360 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2361 PetscErrorCode ierr; 2362 Vec bb1 = 0; 2363 2364 PetscFunctionBegin; 2365 if (flag == SOR_APPLY_UPPER) { 2366 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2367 PetscFunctionReturn(0); 2368 } 2369 2370 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2371 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2372 } 2373 2374 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2375 if (flag & SOR_ZERO_INITIAL_GUESS) { 2376 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2377 its--; 2378 } 2379 2380 while (its--) { 2381 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2382 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2383 2384 /* update rhs: bb1 = bb - B*x */ 2385 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2386 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2387 2388 /* local sweep */ 2389 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2390 } 2391 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2392 if (flag & SOR_ZERO_INITIAL_GUESS) { 2393 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2394 its--; 2395 } 2396 while (its--) { 2397 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2398 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2399 2400 /* update rhs: bb1 = bb - B*x */ 2401 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2402 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2403 2404 /* local sweep */ 2405 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2406 } 2407 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2408 if (flag & SOR_ZERO_INITIAL_GUESS) { 2409 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2410 its--; 2411 } 2412 while (its--) { 2413 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2414 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2415 2416 /* update rhs: bb1 = bb - B*x */ 2417 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2418 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2419 2420 /* local sweep */ 2421 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2422 } 2423 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2424 2425 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2426 PetscFunctionReturn(0); 2427 } 2428 2429 #undef __FUNCT__ 2430 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2431 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2432 { 2433 PetscErrorCode ierr; 2434 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2435 PetscInt N,i,*garray = aij->garray; 2436 PetscInt ib,jb,bs = A->rmap->bs; 2437 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2438 MatScalar *a_val = a_aij->a; 2439 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2440 MatScalar *b_val = b_aij->a; 2441 PetscReal *work; 2442 2443 PetscFunctionBegin; 2444 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2445 ierr = PetscMalloc(N*sizeof(PetscReal),&work);CHKERRQ(ierr); 2446 ierr = PetscMemzero(work,N*sizeof(PetscReal));CHKERRQ(ierr); 2447 if (type == NORM_2) { 2448 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2449 for (jb=0; jb<bs; jb++) { 2450 for (ib=0; ib<bs; ib++) { 2451 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2452 a_val++; 2453 } 2454 } 2455 } 2456 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2457 for (jb=0; jb<bs; jb++) { 2458 for (ib=0; ib<bs; ib++) { 2459 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2460 b_val++; 2461 } 2462 } 2463 } 2464 } else if (type == NORM_1) { 2465 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2466 for (jb=0; jb<bs; jb++) { 2467 for (ib=0; ib<bs; ib++) { 2468 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2469 a_val++; 2470 } 2471 } 2472 } 2473 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2474 for (jb=0; jb<bs; jb++) { 2475 for (ib=0; ib<bs; ib++) { 2476 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2477 b_val++; 2478 } 2479 } 2480 } 2481 } else if (type == NORM_INFINITY) { 2482 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2483 for (jb=0; jb<bs; jb++) { 2484 for (ib=0; ib<bs; ib++) { 2485 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2486 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2487 a_val++; 2488 } 2489 } 2490 } 2491 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2492 for (jb=0; jb<bs; jb++) { 2493 for (ib=0; ib<bs; ib++) { 2494 int col = garray[b_aij->j[i]] * bs + jb; 2495 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2496 b_val++; 2497 } 2498 } 2499 } 2500 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2501 if (type == NORM_INFINITY) { 2502 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2503 } else { 2504 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2505 } 2506 ierr = PetscFree(work);CHKERRQ(ierr); 2507 if (type == NORM_2) { 2508 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2509 } 2510 PetscFunctionReturn(0); 2511 } 2512 2513 #undef __FUNCT__ 2514 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2515 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2516 { 2517 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2518 PetscErrorCode ierr; 2519 2520 PetscFunctionBegin; 2521 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2522 PetscFunctionReturn(0); 2523 } 2524 2525 2526 /* -------------------------------------------------------------------*/ 2527 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2528 MatGetRow_MPIBAIJ, 2529 MatRestoreRow_MPIBAIJ, 2530 MatMult_MPIBAIJ, 2531 /* 4*/ MatMultAdd_MPIBAIJ, 2532 MatMultTranspose_MPIBAIJ, 2533 MatMultTransposeAdd_MPIBAIJ, 2534 0, 2535 0, 2536 0, 2537 /*10*/ 0, 2538 0, 2539 0, 2540 MatSOR_MPIBAIJ, 2541 MatTranspose_MPIBAIJ, 2542 /*15*/ MatGetInfo_MPIBAIJ, 2543 MatEqual_MPIBAIJ, 2544 MatGetDiagonal_MPIBAIJ, 2545 MatDiagonalScale_MPIBAIJ, 2546 MatNorm_MPIBAIJ, 2547 /*20*/ MatAssemblyBegin_MPIBAIJ, 2548 MatAssemblyEnd_MPIBAIJ, 2549 MatSetOption_MPIBAIJ, 2550 MatZeroEntries_MPIBAIJ, 2551 /*24*/ MatZeroRows_MPIBAIJ, 2552 0, 2553 0, 2554 0, 2555 0, 2556 /*29*/ MatSetUp_MPIBAIJ, 2557 0, 2558 0, 2559 0, 2560 0, 2561 /*34*/ MatDuplicate_MPIBAIJ, 2562 0, 2563 0, 2564 0, 2565 0, 2566 /*39*/ MatAXPY_MPIBAIJ, 2567 MatGetSubMatrices_MPIBAIJ, 2568 MatIncreaseOverlap_MPIBAIJ, 2569 MatGetValues_MPIBAIJ, 2570 MatCopy_MPIBAIJ, 2571 /*44*/ 0, 2572 MatScale_MPIBAIJ, 2573 0, 2574 0, 2575 0, 2576 /*49*/ 0, 2577 0, 2578 0, 2579 0, 2580 0, 2581 /*54*/ MatFDColoringCreate_MPIXAIJ, 2582 0, 2583 MatSetUnfactored_MPIBAIJ, 2584 MatPermute_MPIBAIJ, 2585 MatSetValuesBlocked_MPIBAIJ, 2586 /*59*/ MatGetSubMatrix_MPIBAIJ, 2587 MatDestroy_MPIBAIJ, 2588 MatView_MPIBAIJ, 2589 0, 2590 0, 2591 /*64*/ 0, 2592 0, 2593 0, 2594 0, 2595 0, 2596 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2597 0, 2598 0, 2599 0, 2600 0, 2601 /*74*/ 0, 2602 MatFDColoringApply_BAIJ, 2603 0, 2604 0, 2605 0, 2606 /*79*/ 0, 2607 0, 2608 0, 2609 0, 2610 MatLoad_MPIBAIJ, 2611 /*84*/ 0, 2612 0, 2613 0, 2614 0, 2615 0, 2616 /*89*/ 0, 2617 0, 2618 0, 2619 0, 2620 0, 2621 /*94*/ 0, 2622 0, 2623 0, 2624 0, 2625 0, 2626 /*99*/ 0, 2627 0, 2628 0, 2629 0, 2630 0, 2631 /*104*/0, 2632 MatRealPart_MPIBAIJ, 2633 MatImaginaryPart_MPIBAIJ, 2634 0, 2635 0, 2636 /*109*/0, 2637 0, 2638 0, 2639 0, 2640 0, 2641 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2642 0, 2643 MatGetGhosts_MPIBAIJ, 2644 0, 2645 0, 2646 /*119*/0, 2647 0, 2648 0, 2649 0, 2650 MatGetMultiProcBlock_MPIBAIJ, 2651 /*124*/0, 2652 MatGetColumnNorms_MPIBAIJ, 2653 MatInvertBlockDiagonal_MPIBAIJ, 2654 0, 2655 0, 2656 /*129*/ 0, 2657 0, 2658 0, 2659 0, 2660 0, 2661 /*134*/ 0, 2662 0, 2663 0, 2664 0, 2665 0, 2666 /*139*/ 0, 2667 0, 2668 0, 2669 MatFDColoringSetUp_MPIXAIJ 2670 }; 2671 2672 #undef __FUNCT__ 2673 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2674 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2675 { 2676 PetscFunctionBegin; 2677 *a = ((Mat_MPIBAIJ*)A->data)->A; 2678 PetscFunctionReturn(0); 2679 } 2680 2681 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2682 2683 #undef __FUNCT__ 2684 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2685 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2686 { 2687 PetscInt m,rstart,cstart,cend; 2688 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2689 const PetscInt *JJ =0; 2690 PetscScalar *values=0; 2691 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2692 PetscErrorCode ierr; 2693 2694 PetscFunctionBegin; 2695 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2696 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2697 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2698 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2699 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2700 m = B->rmap->n/bs; 2701 rstart = B->rmap->rstart/bs; 2702 cstart = B->cmap->rstart/bs; 2703 cend = B->cmap->rend/bs; 2704 2705 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2706 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 2707 for (i=0; i<m; i++) { 2708 nz = ii[i+1] - ii[i]; 2709 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2710 nz_max = PetscMax(nz_max,nz); 2711 JJ = jj + ii[i]; 2712 for (j=0; j<nz; j++) { 2713 if (*JJ >= cstart) break; 2714 JJ++; 2715 } 2716 d = 0; 2717 for (; j<nz; j++) { 2718 if (*JJ++ >= cend) break; 2719 d++; 2720 } 2721 d_nnz[i] = d; 2722 o_nnz[i] = nz - d; 2723 } 2724 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2725 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2726 2727 values = (PetscScalar*)V; 2728 if (!values) { 2729 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2730 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2731 } 2732 for (i=0; i<m; i++) { 2733 PetscInt row = i + rstart; 2734 PetscInt ncols = ii[i+1] - ii[i]; 2735 const PetscInt *icols = jj + ii[i]; 2736 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2737 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2738 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2739 } else { /* block ordering does not match so we can only insert one block at a time. */ 2740 PetscInt j; 2741 for (j=0; j<ncols; j++) { 2742 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2743 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2744 } 2745 } 2746 } 2747 2748 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2749 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2750 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2751 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2752 PetscFunctionReturn(0); 2753 } 2754 2755 #undef __FUNCT__ 2756 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2757 /*@C 2758 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2759 (the default parallel PETSc format). 2760 2761 Collective on MPI_Comm 2762 2763 Input Parameters: 2764 + A - the matrix 2765 . bs - the block size 2766 . i - the indices into j for the start of each local row (starts with zero) 2767 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2768 - v - optional values in the matrix 2769 2770 Level: developer 2771 2772 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2773 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2774 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2775 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2776 block column and the second index is over columns within a block. 2777 2778 .keywords: matrix, aij, compressed row, sparse, parallel 2779 2780 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2781 @*/ 2782 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2783 { 2784 PetscErrorCode ierr; 2785 2786 PetscFunctionBegin; 2787 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2788 PetscValidType(B,1); 2789 PetscValidLogicalCollectiveInt(B,bs,2); 2790 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2791 PetscFunctionReturn(0); 2792 } 2793 2794 #undef __FUNCT__ 2795 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2796 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2797 { 2798 Mat_MPIBAIJ *b; 2799 PetscErrorCode ierr; 2800 PetscInt i; 2801 2802 PetscFunctionBegin; 2803 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2804 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2805 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2806 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2807 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2808 2809 if (d_nnz) { 2810 for (i=0; i<B->rmap->n/bs; i++) { 2811 if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2812 } 2813 } 2814 if (o_nnz) { 2815 for (i=0; i<B->rmap->n/bs; i++) { 2816 if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2817 } 2818 } 2819 2820 b = (Mat_MPIBAIJ*)B->data; 2821 b->bs2 = bs*bs; 2822 b->mbs = B->rmap->n/bs; 2823 b->nbs = B->cmap->n/bs; 2824 b->Mbs = B->rmap->N/bs; 2825 b->Nbs = B->cmap->N/bs; 2826 2827 for (i=0; i<=b->size; i++) { 2828 b->rangebs[i] = B->rmap->range[i]/bs; 2829 } 2830 b->rstartbs = B->rmap->rstart/bs; 2831 b->rendbs = B->rmap->rend/bs; 2832 b->cstartbs = B->cmap->rstart/bs; 2833 b->cendbs = B->cmap->rend/bs; 2834 2835 if (!B->preallocated) { 2836 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2837 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2838 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2839 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2840 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2841 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2842 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2843 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2844 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2845 } 2846 2847 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2848 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2849 B->preallocated = PETSC_TRUE; 2850 PetscFunctionReturn(0); 2851 } 2852 2853 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2854 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2855 2856 #undef __FUNCT__ 2857 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2858 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2859 { 2860 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2861 PetscErrorCode ierr; 2862 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2863 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2864 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2865 2866 PetscFunctionBegin; 2867 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr); 2868 ii[0] = 0; 2869 for (i=0; i<M; i++) { 2870 if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]); 2871 if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]); 2872 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2873 /* remove one from count of matrix has diagonal */ 2874 for (j=id[i]; j<id[i+1]; j++) { 2875 if (jd[j] == i) {ii[i+1]--;break;} 2876 } 2877 } 2878 ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr); 2879 cnt = 0; 2880 for (i=0; i<M; i++) { 2881 for (j=io[i]; j<io[i+1]; j++) { 2882 if (garray[jo[j]] > rstart) break; 2883 jj[cnt++] = garray[jo[j]]; 2884 } 2885 for (k=id[i]; k<id[i+1]; k++) { 2886 if (jd[k] != i) { 2887 jj[cnt++] = rstart + jd[k]; 2888 } 2889 } 2890 for (; j<io[i+1]; j++) { 2891 jj[cnt++] = garray[jo[j]]; 2892 } 2893 } 2894 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2895 PetscFunctionReturn(0); 2896 } 2897 2898 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2899 2900 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2901 2902 #undef __FUNCT__ 2903 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2904 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2905 { 2906 PetscErrorCode ierr; 2907 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2908 Mat B; 2909 Mat_MPIAIJ *b; 2910 2911 PetscFunctionBegin; 2912 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2913 2914 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2915 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2916 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2917 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2918 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2919 b = (Mat_MPIAIJ*) B->data; 2920 2921 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2922 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2923 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2924 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2925 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2926 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2927 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2928 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2929 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2930 if (reuse == MAT_REUSE_MATRIX) { 2931 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2932 } else { 2933 *newmat = B; 2934 } 2935 PetscFunctionReturn(0); 2936 } 2937 2938 #if defined(PETSC_HAVE_MUMPS) 2939 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2940 #endif 2941 2942 /*MC 2943 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2944 2945 Options Database Keys: 2946 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2947 . -mat_block_size <bs> - set the blocksize used to store the matrix 2948 - -mat_use_hash_table <fact> 2949 2950 Level: beginner 2951 2952 .seealso: MatCreateMPIBAIJ 2953 M*/ 2954 2955 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 2956 2957 #undef __FUNCT__ 2958 #define __FUNCT__ "MatCreate_MPIBAIJ" 2959 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 2960 { 2961 Mat_MPIBAIJ *b; 2962 PetscErrorCode ierr; 2963 PetscBool flg; 2964 2965 PetscFunctionBegin; 2966 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2967 B->data = (void*)b; 2968 2969 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2970 B->assembled = PETSC_FALSE; 2971 2972 B->insertmode = NOT_SET_VALUES; 2973 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 2974 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 2975 2976 /* build local table of row and column ownerships */ 2977 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 2978 2979 /* build cache for off array entries formed */ 2980 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 2981 2982 b->donotstash = PETSC_FALSE; 2983 b->colmap = NULL; 2984 b->garray = NULL; 2985 b->roworiented = PETSC_TRUE; 2986 2987 /* stuff used in block assembly */ 2988 b->barray = 0; 2989 2990 /* stuff used for matrix vector multiply */ 2991 b->lvec = 0; 2992 b->Mvctx = 0; 2993 2994 /* stuff for MatGetRow() */ 2995 b->rowindices = 0; 2996 b->rowvalues = 0; 2997 b->getrowactive = PETSC_FALSE; 2998 2999 /* hash table stuff */ 3000 b->ht = 0; 3001 b->hd = 0; 3002 b->ht_size = 0; 3003 b->ht_flag = PETSC_FALSE; 3004 b->ht_fact = 0; 3005 b->ht_total_ct = 0; 3006 b->ht_insert_ct = 0; 3007 3008 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3009 b->ijonly = PETSC_FALSE; 3010 3011 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3012 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3013 if (flg) { 3014 PetscReal fact = 1.39; 3015 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3016 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3017 if (fact <= 1.0) fact = 1.39; 3018 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3019 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3020 } 3021 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3022 3023 #if defined(PETSC_HAVE_MUMPS) 3024 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3025 #endif 3026 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3027 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3028 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3029 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3030 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3031 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3032 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3033 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3034 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3035 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3036 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3037 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3038 PetscFunctionReturn(0); 3039 } 3040 3041 /*MC 3042 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3043 3044 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3045 and MATMPIBAIJ otherwise. 3046 3047 Options Database Keys: 3048 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3049 3050 Level: beginner 3051 3052 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3053 M*/ 3054 3055 #undef __FUNCT__ 3056 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3057 /*@C 3058 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3059 (block compressed row). For good matrix assembly performance 3060 the user should preallocate the matrix storage by setting the parameters 3061 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3062 performance can be increased by more than a factor of 50. 3063 3064 Collective on Mat 3065 3066 Input Parameters: 3067 + A - the matrix 3068 . bs - size of block 3069 . d_nz - number of block nonzeros per block row in diagonal portion of local 3070 submatrix (same for all local rows) 3071 . d_nnz - array containing the number of block nonzeros in the various block rows 3072 of the in diagonal portion of the local (possibly different for each block 3073 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3074 set it even if it is zero. 3075 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3076 submatrix (same for all local rows). 3077 - o_nnz - array containing the number of nonzeros in the various block rows of the 3078 off-diagonal portion of the local submatrix (possibly different for 3079 each block row) or NULL. 3080 3081 If the *_nnz parameter is given then the *_nz parameter is ignored 3082 3083 Options Database Keys: 3084 + -mat_block_size - size of the blocks to use 3085 - -mat_use_hash_table <fact> 3086 3087 Notes: 3088 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3089 than it must be used on all processors that share the object for that argument. 3090 3091 Storage Information: 3092 For a square global matrix we define each processor's diagonal portion 3093 to be its local rows and the corresponding columns (a square submatrix); 3094 each processor's off-diagonal portion encompasses the remainder of the 3095 local matrix (a rectangular submatrix). 3096 3097 The user can specify preallocated storage for the diagonal part of 3098 the local submatrix with either d_nz or d_nnz (not both). Set 3099 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3100 memory allocation. Likewise, specify preallocated storage for the 3101 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3102 3103 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3104 the figure below we depict these three local rows and all columns (0-11). 3105 3106 .vb 3107 0 1 2 3 4 5 6 7 8 9 10 11 3108 -------------------------- 3109 row 3 |o o o d d d o o o o o o 3110 row 4 |o o o d d d o o o o o o 3111 row 5 |o o o d d d o o o o o o 3112 -------------------------- 3113 .ve 3114 3115 Thus, any entries in the d locations are stored in the d (diagonal) 3116 submatrix, and any entries in the o locations are stored in the 3117 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3118 stored simply in the MATSEQBAIJ format for compressed row storage. 3119 3120 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3121 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3122 In general, for PDE problems in which most nonzeros are near the diagonal, 3123 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3124 or you will get TERRIBLE performance; see the users' manual chapter on 3125 matrices. 3126 3127 You can call MatGetInfo() to get information on how effective the preallocation was; 3128 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3129 You can also run with the option -info and look for messages with the string 3130 malloc in them to see if additional memory allocation was needed. 3131 3132 Level: intermediate 3133 3134 .keywords: matrix, block, aij, compressed row, sparse, parallel 3135 3136 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3137 @*/ 3138 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3139 { 3140 PetscErrorCode ierr; 3141 3142 PetscFunctionBegin; 3143 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3144 PetscValidType(B,1); 3145 PetscValidLogicalCollectiveInt(B,bs,2); 3146 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3147 PetscFunctionReturn(0); 3148 } 3149 3150 #undef __FUNCT__ 3151 #define __FUNCT__ "MatCreateBAIJ" 3152 /*@C 3153 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3154 (block compressed row). For good matrix assembly performance 3155 the user should preallocate the matrix storage by setting the parameters 3156 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3157 performance can be increased by more than a factor of 50. 3158 3159 Collective on MPI_Comm 3160 3161 Input Parameters: 3162 + comm - MPI communicator 3163 . bs - size of blockk 3164 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3165 This value should be the same as the local size used in creating the 3166 y vector for the matrix-vector product y = Ax. 3167 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3168 This value should be the same as the local size used in creating the 3169 x vector for the matrix-vector product y = Ax. 3170 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3171 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3172 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3173 submatrix (same for all local rows) 3174 . d_nnz - array containing the number of nonzero blocks in the various block rows 3175 of the in diagonal portion of the local (possibly different for each block 3176 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3177 and set it even if it is zero. 3178 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3179 submatrix (same for all local rows). 3180 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3181 off-diagonal portion of the local submatrix (possibly different for 3182 each block row) or NULL. 3183 3184 Output Parameter: 3185 . A - the matrix 3186 3187 Options Database Keys: 3188 + -mat_block_size - size of the blocks to use 3189 - -mat_use_hash_table <fact> 3190 3191 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3192 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3193 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3194 3195 Notes: 3196 If the *_nnz parameter is given then the *_nz parameter is ignored 3197 3198 A nonzero block is any block that as 1 or more nonzeros in it 3199 3200 The user MUST specify either the local or global matrix dimensions 3201 (possibly both). 3202 3203 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3204 than it must be used on all processors that share the object for that argument. 3205 3206 Storage Information: 3207 For a square global matrix we define each processor's diagonal portion 3208 to be its local rows and the corresponding columns (a square submatrix); 3209 each processor's off-diagonal portion encompasses the remainder of the 3210 local matrix (a rectangular submatrix). 3211 3212 The user can specify preallocated storage for the diagonal part of 3213 the local submatrix with either d_nz or d_nnz (not both). Set 3214 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3215 memory allocation. Likewise, specify preallocated storage for the 3216 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3217 3218 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3219 the figure below we depict these three local rows and all columns (0-11). 3220 3221 .vb 3222 0 1 2 3 4 5 6 7 8 9 10 11 3223 -------------------------- 3224 row 3 |o o o d d d o o o o o o 3225 row 4 |o o o d d d o o o o o o 3226 row 5 |o o o d d d o o o o o o 3227 -------------------------- 3228 .ve 3229 3230 Thus, any entries in the d locations are stored in the d (diagonal) 3231 submatrix, and any entries in the o locations are stored in the 3232 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3233 stored simply in the MATSEQBAIJ format for compressed row storage. 3234 3235 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3236 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3237 In general, for PDE problems in which most nonzeros are near the diagonal, 3238 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3239 or you will get TERRIBLE performance; see the users' manual chapter on 3240 matrices. 3241 3242 Level: intermediate 3243 3244 .keywords: matrix, block, aij, compressed row, sparse, parallel 3245 3246 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3247 @*/ 3248 PetscErrorCode MatCreateBAIJ(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) 3249 { 3250 PetscErrorCode ierr; 3251 PetscMPIInt size; 3252 3253 PetscFunctionBegin; 3254 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3255 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3256 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3257 if (size > 1) { 3258 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3259 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3260 } else { 3261 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3262 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3263 } 3264 PetscFunctionReturn(0); 3265 } 3266 3267 #undef __FUNCT__ 3268 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3269 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3270 { 3271 Mat mat; 3272 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3273 PetscErrorCode ierr; 3274 PetscInt len=0; 3275 3276 PetscFunctionBegin; 3277 *newmat = 0; 3278 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3279 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3280 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3281 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3282 3283 mat->factortype = matin->factortype; 3284 mat->preallocated = PETSC_TRUE; 3285 mat->assembled = PETSC_TRUE; 3286 mat->insertmode = NOT_SET_VALUES; 3287 3288 a = (Mat_MPIBAIJ*)mat->data; 3289 mat->rmap->bs = matin->rmap->bs; 3290 a->bs2 = oldmat->bs2; 3291 a->mbs = oldmat->mbs; 3292 a->nbs = oldmat->nbs; 3293 a->Mbs = oldmat->Mbs; 3294 a->Nbs = oldmat->Nbs; 3295 3296 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3297 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3298 3299 a->size = oldmat->size; 3300 a->rank = oldmat->rank; 3301 a->donotstash = oldmat->donotstash; 3302 a->roworiented = oldmat->roworiented; 3303 a->rowindices = 0; 3304 a->rowvalues = 0; 3305 a->getrowactive = PETSC_FALSE; 3306 a->barray = 0; 3307 a->rstartbs = oldmat->rstartbs; 3308 a->rendbs = oldmat->rendbs; 3309 a->cstartbs = oldmat->cstartbs; 3310 a->cendbs = oldmat->cendbs; 3311 3312 /* hash table stuff */ 3313 a->ht = 0; 3314 a->hd = 0; 3315 a->ht_size = 0; 3316 a->ht_flag = oldmat->ht_flag; 3317 a->ht_fact = oldmat->ht_fact; 3318 a->ht_total_ct = 0; 3319 a->ht_insert_ct = 0; 3320 3321 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3322 if (oldmat->colmap) { 3323 #if defined(PETSC_USE_CTABLE) 3324 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3325 #else 3326 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3327 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3328 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3329 #endif 3330 } else a->colmap = 0; 3331 3332 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3333 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3334 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3335 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3336 } else a->garray = 0; 3337 3338 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3339 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3340 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3341 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3342 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3343 3344 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3345 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3346 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3347 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3348 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3349 *newmat = mat; 3350 PetscFunctionReturn(0); 3351 } 3352 3353 #undef __FUNCT__ 3354 #define __FUNCT__ "MatLoad_MPIBAIJ" 3355 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3356 { 3357 PetscErrorCode ierr; 3358 int fd; 3359 PetscInt i,nz,j,rstart,rend; 3360 PetscScalar *vals,*buf; 3361 MPI_Comm comm; 3362 MPI_Status status; 3363 PetscMPIInt rank,size,maxnz; 3364 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3365 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3366 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3367 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3368 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3369 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3370 3371 PetscFunctionBegin; 3372 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3373 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3374 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3375 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3376 3377 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3378 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3379 if (!rank) { 3380 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3381 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3382 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3383 } 3384 3385 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3386 3387 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3388 M = header[1]; N = header[2]; 3389 3390 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3391 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3392 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3393 3394 /* If global sizes are set, check if they are consistent with that given in the file */ 3395 if (sizesset) { 3396 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3397 } 3398 if (sizesset && newmat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows); 3399 if (sizesset && newmat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols); 3400 3401 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3402 3403 /* 3404 This code adds extra rows to make sure the number of rows is 3405 divisible by the blocksize 3406 */ 3407 Mbs = M/bs; 3408 extra_rows = bs - M + bs*Mbs; 3409 if (extra_rows == bs) extra_rows = 0; 3410 else Mbs++; 3411 if (extra_rows && !rank) { 3412 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3413 } 3414 3415 /* determine ownership of all rows */ 3416 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3417 mbs = Mbs/size + ((Mbs % size) > rank); 3418 m = mbs*bs; 3419 } else { /* User set */ 3420 m = newmat->rmap->n; 3421 mbs = m/bs; 3422 } 3423 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 3424 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3425 3426 /* process 0 needs enough room for process with most rows */ 3427 if (!rank) { 3428 mmax = rowners[1]; 3429 for (i=2; i<=size; i++) { 3430 mmax = PetscMax(mmax,rowners[i]); 3431 } 3432 mmax*=bs; 3433 } else mmax = -1; /* unused, but compiler warns anyway */ 3434 3435 rowners[0] = 0; 3436 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3437 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3438 rstart = rowners[rank]; 3439 rend = rowners[rank+1]; 3440 3441 /* distribute row lengths to all processors */ 3442 ierr = PetscMalloc(m*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 3443 if (!rank) { 3444 mend = m; 3445 if (size == 1) mend = mend - extra_rows; 3446 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3447 for (j=mend; j<m; j++) locrowlens[j] = 1; 3448 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3449 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3450 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3451 for (j=0; j<m; j++) { 3452 procsnz[0] += locrowlens[j]; 3453 } 3454 for (i=1; i<size; i++) { 3455 mend = browners[i+1] - browners[i]; 3456 if (i == size-1) mend = mend - extra_rows; 3457 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3458 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3459 /* calculate the number of nonzeros on each processor */ 3460 for (j=0; j<browners[i+1]-browners[i]; j++) { 3461 procsnz[i] += rowlengths[j]; 3462 } 3463 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3464 } 3465 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3466 } else { 3467 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3468 } 3469 3470 if (!rank) { 3471 /* determine max buffer needed and allocate it */ 3472 maxnz = procsnz[0]; 3473 for (i=1; i<size; i++) { 3474 maxnz = PetscMax(maxnz,procsnz[i]); 3475 } 3476 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3477 3478 /* read in my part of the matrix column indices */ 3479 nz = procsnz[0]; 3480 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3481 mycols = ibuf; 3482 if (size == 1) nz -= extra_rows; 3483 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3484 if (size == 1) { 3485 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3486 } 3487 3488 /* read in every ones (except the last) and ship off */ 3489 for (i=1; i<size-1; i++) { 3490 nz = procsnz[i]; 3491 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3492 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3493 } 3494 /* read in the stuff for the last proc */ 3495 if (size != 1) { 3496 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3497 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3498 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3499 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3500 } 3501 ierr = PetscFree(cols);CHKERRQ(ierr); 3502 } else { 3503 /* determine buffer space needed for message */ 3504 nz = 0; 3505 for (i=0; i<m; i++) { 3506 nz += locrowlens[i]; 3507 } 3508 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3509 mycols = ibuf; 3510 /* receive message of column indices*/ 3511 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3512 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3513 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3514 } 3515 3516 /* loop over local rows, determining number of off diagonal entries */ 3517 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 3518 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 3519 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3520 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3521 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3522 rowcount = 0; nzcount = 0; 3523 for (i=0; i<mbs; i++) { 3524 dcount = 0; 3525 odcount = 0; 3526 for (j=0; j<bs; j++) { 3527 kmax = locrowlens[rowcount]; 3528 for (k=0; k<kmax; k++) { 3529 tmp = mycols[nzcount++]/bs; 3530 if (!mask[tmp]) { 3531 mask[tmp] = 1; 3532 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3533 else masked1[dcount++] = tmp; 3534 } 3535 } 3536 rowcount++; 3537 } 3538 3539 dlens[i] = dcount; 3540 odlens[i] = odcount; 3541 3542 /* zero out the mask elements we set */ 3543 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3544 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3545 } 3546 3547 3548 if (!sizesset) { 3549 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3550 } 3551 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3552 3553 if (!rank) { 3554 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3555 /* read in my part of the matrix numerical values */ 3556 nz = procsnz[0]; 3557 vals = buf; 3558 mycols = ibuf; 3559 if (size == 1) nz -= extra_rows; 3560 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3561 if (size == 1) { 3562 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3563 } 3564 3565 /* insert into matrix */ 3566 jj = rstart*bs; 3567 for (i=0; i<m; i++) { 3568 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3569 mycols += locrowlens[i]; 3570 vals += locrowlens[i]; 3571 jj++; 3572 } 3573 /* read in other processors (except the last one) and ship out */ 3574 for (i=1; i<size-1; i++) { 3575 nz = procsnz[i]; 3576 vals = buf; 3577 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3578 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3579 } 3580 /* the last proc */ 3581 if (size != 1) { 3582 nz = procsnz[i] - extra_rows; 3583 vals = buf; 3584 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3585 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3586 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3587 } 3588 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3589 } else { 3590 /* receive numeric values */ 3591 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3592 3593 /* receive message of values*/ 3594 vals = buf; 3595 mycols = ibuf; 3596 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3597 3598 /* insert into matrix */ 3599 jj = rstart*bs; 3600 for (i=0; i<m; i++) { 3601 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3602 mycols += locrowlens[i]; 3603 vals += locrowlens[i]; 3604 jj++; 3605 } 3606 } 3607 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3608 ierr = PetscFree(buf);CHKERRQ(ierr); 3609 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3610 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3611 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3612 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3613 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3614 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3615 PetscFunctionReturn(0); 3616 } 3617 3618 #undef __FUNCT__ 3619 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3620 /*@ 3621 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3622 3623 Input Parameters: 3624 . mat - the matrix 3625 . fact - factor 3626 3627 Not Collective, each process can use a different factor 3628 3629 Level: advanced 3630 3631 Notes: 3632 This can also be set by the command line option: -mat_use_hash_table <fact> 3633 3634 .keywords: matrix, hashtable, factor, HT 3635 3636 .seealso: MatSetOption() 3637 @*/ 3638 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3639 { 3640 PetscErrorCode ierr; 3641 3642 PetscFunctionBegin; 3643 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3644 PetscFunctionReturn(0); 3645 } 3646 3647 #undef __FUNCT__ 3648 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3649 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3650 { 3651 Mat_MPIBAIJ *baij; 3652 3653 PetscFunctionBegin; 3654 baij = (Mat_MPIBAIJ*)mat->data; 3655 baij->ht_fact = fact; 3656 PetscFunctionReturn(0); 3657 } 3658 3659 #undef __FUNCT__ 3660 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3661 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3662 { 3663 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3664 3665 PetscFunctionBegin; 3666 *Ad = a->A; 3667 *Ao = a->B; 3668 *colmap = a->garray; 3669 PetscFunctionReturn(0); 3670 } 3671 3672 /* 3673 Special version for direct calls from Fortran (to eliminate two function call overheads 3674 */ 3675 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3676 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3677 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3678 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3679 #endif 3680 3681 #undef __FUNCT__ 3682 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3683 /*@C 3684 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3685 3686 Collective on Mat 3687 3688 Input Parameters: 3689 + mat - the matrix 3690 . min - number of input rows 3691 . im - input rows 3692 . nin - number of input columns 3693 . in - input columns 3694 . v - numerical values input 3695 - addvin - INSERT_VALUES or ADD_VALUES 3696 3697 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3698 3699 Level: advanced 3700 3701 .seealso: MatSetValuesBlocked() 3702 @*/ 3703 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3704 { 3705 /* convert input arguments to C version */ 3706 Mat mat = *matin; 3707 PetscInt m = *min, n = *nin; 3708 InsertMode addv = *addvin; 3709 3710 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3711 const MatScalar *value; 3712 MatScalar *barray = baij->barray; 3713 PetscBool roworiented = baij->roworiented; 3714 PetscErrorCode ierr; 3715 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3716 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3717 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3718 3719 PetscFunctionBegin; 3720 /* tasks normally handled by MatSetValuesBlocked() */ 3721 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3722 #if defined(PETSC_USE_DEBUG) 3723 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3724 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3725 #endif 3726 if (mat->assembled) { 3727 mat->was_assembled = PETSC_TRUE; 3728 mat->assembled = PETSC_FALSE; 3729 } 3730 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3731 3732 3733 if (!barray) { 3734 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 3735 baij->barray = barray; 3736 } 3737 3738 if (roworiented) stepval = (n-1)*bs; 3739 else stepval = (m-1)*bs; 3740 3741 for (i=0; i<m; i++) { 3742 if (im[i] < 0) continue; 3743 #if defined(PETSC_USE_DEBUG) 3744 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 3745 #endif 3746 if (im[i] >= rstart && im[i] < rend) { 3747 row = im[i] - rstart; 3748 for (j=0; j<n; j++) { 3749 /* If NumCol = 1 then a copy is not required */ 3750 if ((roworiented) && (n == 1)) { 3751 barray = (MatScalar*)v + i*bs2; 3752 } else if ((!roworiented) && (m == 1)) { 3753 barray = (MatScalar*)v + j*bs2; 3754 } else { /* Here a copy is required */ 3755 if (roworiented) { 3756 value = v + i*(stepval+bs)*bs + j*bs; 3757 } else { 3758 value = v + j*(stepval+bs)*bs + i*bs; 3759 } 3760 for (ii=0; ii<bs; ii++,value+=stepval) { 3761 for (jj=0; jj<bs; jj++) { 3762 *barray++ = *value++; 3763 } 3764 } 3765 barray -=bs2; 3766 } 3767 3768 if (in[j] >= cstart && in[j] < cend) { 3769 col = in[j] - cstart; 3770 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3771 } else if (in[j] < 0) continue; 3772 #if defined(PETSC_USE_DEBUG) 3773 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1); 3774 #endif 3775 else { 3776 if (mat->was_assembled) { 3777 if (!baij->colmap) { 3778 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3779 } 3780 3781 #if defined(PETSC_USE_DEBUG) 3782 #if defined(PETSC_USE_CTABLE) 3783 { PetscInt data; 3784 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3785 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3786 } 3787 #else 3788 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3789 #endif 3790 #endif 3791 #if defined(PETSC_USE_CTABLE) 3792 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3793 col = (col - 1)/bs; 3794 #else 3795 col = (baij->colmap[in[j]] - 1)/bs; 3796 #endif 3797 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3798 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3799 col = in[j]; 3800 } 3801 } else col = in[j]; 3802 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3803 } 3804 } 3805 } else { 3806 if (!baij->donotstash) { 3807 if (roworiented) { 3808 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3809 } else { 3810 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3811 } 3812 } 3813 } 3814 } 3815 3816 /* task normally handled by MatSetValuesBlocked() */ 3817 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3818 PetscFunctionReturn(0); 3819 } 3820 3821 #undef __FUNCT__ 3822 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3823 /*@ 3824 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3825 CSR format the local rows. 3826 3827 Collective on MPI_Comm 3828 3829 Input Parameters: 3830 + comm - MPI communicator 3831 . bs - the block size, only a block size of 1 is supported 3832 . m - number of local rows (Cannot be PETSC_DECIDE) 3833 . n - This value should be the same as the local size used in creating the 3834 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3835 calculated if N is given) For square matrices n is almost always m. 3836 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3837 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3838 . i - row indices 3839 . j - column indices 3840 - a - matrix values 3841 3842 Output Parameter: 3843 . mat - the matrix 3844 3845 Level: intermediate 3846 3847 Notes: 3848 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3849 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3850 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3851 3852 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3853 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3854 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3855 with column-major ordering within blocks. 3856 3857 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3858 3859 .keywords: matrix, aij, compressed row, sparse, parallel 3860 3861 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3862 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3863 @*/ 3864 PetscErrorCode MatCreateMPIBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3865 { 3866 PetscErrorCode ierr; 3867 3868 PetscFunctionBegin; 3869 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3870 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3871 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3872 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3873 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3874 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3875 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3876 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3877 PetscFunctionReturn(0); 3878 } 3879