1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 #include <petscblaslapack.h> 4 #include <petscsf.h> 5 6 extern PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 7 extern PetscErrorCode MatDisAssemble_MPIBAIJ(Mat); 8 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 9 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 10 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 11 extern PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 12 extern PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 13 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec); 14 15 #undef __FUNCT__ 16 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 17 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 18 { 19 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 20 PetscErrorCode ierr; 21 PetscInt i,*idxb = 0; 22 PetscScalar *va,*vb; 23 Vec vtmp; 24 25 PetscFunctionBegin; 26 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 27 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 28 if (idx) { 29 for (i=0; i<A->rmap->n; i++) { 30 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 31 } 32 } 33 34 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 35 if (idx) {ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr);} 36 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 37 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 38 39 for (i=0; i<A->rmap->n; i++) { 40 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 41 va[i] = vb[i]; 42 if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs); 43 } 44 } 45 46 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 47 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 48 ierr = PetscFree(idxb);CHKERRQ(ierr); 49 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 50 PetscFunctionReturn(0); 51 } 52 53 #undef __FUNCT__ 54 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 55 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 56 { 57 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 58 PetscErrorCode ierr; 59 60 PetscFunctionBegin; 61 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 62 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 63 PetscFunctionReturn(0); 64 } 65 66 #undef __FUNCT__ 67 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 68 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 69 { 70 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 71 PetscErrorCode ierr; 72 73 PetscFunctionBegin; 74 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 75 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 76 PetscFunctionReturn(0); 77 } 78 79 /* 80 Local utility routine that creates a mapping from the global column 81 number to the local number in the off-diagonal part of the local 82 storage of the matrix. This is done in a non scalable way since the 83 length of colmap equals the global matrix length. 84 */ 85 #undef __FUNCT__ 86 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 87 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 88 { 89 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 90 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 91 PetscErrorCode ierr; 92 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 93 94 PetscFunctionBegin; 95 #if defined(PETSC_USE_CTABLE) 96 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 97 for (i=0; i<nbs; i++) { 98 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 99 } 100 #else 101 ierr = PetscMalloc1((baij->Nbs+1),&baij->colmap);CHKERRQ(ierr); 102 ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 103 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 104 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 105 #endif 106 PetscFunctionReturn(0); 107 } 108 109 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 110 { \ 111 \ 112 brow = row/bs; \ 113 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 114 rmax = aimax[brow]; nrow = ailen[brow]; \ 115 bcol = col/bs; \ 116 ridx = row % bs; cidx = col % bs; \ 117 low = 0; high = nrow; \ 118 while (high-low > 3) { \ 119 t = (low+high)/2; \ 120 if (rp[t] > bcol) high = t; \ 121 else low = t; \ 122 } \ 123 for (_i=low; _i<high; _i++) { \ 124 if (rp[_i] > bcol) break; \ 125 if (rp[_i] == bcol) { \ 126 bap = ap + bs2*_i + bs*cidx + ridx; \ 127 if (addv == ADD_VALUES) *bap += value; \ 128 else *bap = value; \ 129 goto a_noinsert; \ 130 } \ 131 } \ 132 if (a->nonew == 1) goto a_noinsert; \ 133 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 134 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 135 N = nrow++ - 1; \ 136 /* shift up all the later entries in this row */ \ 137 for (ii=N; ii>=_i; ii--) { \ 138 rp[ii+1] = rp[ii]; \ 139 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 140 } \ 141 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 142 rp[_i] = bcol; \ 143 ap[bs2*_i + bs*cidx + ridx] = value; \ 144 a_noinsert:; \ 145 ailen[brow] = nrow; \ 146 } 147 148 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 149 { \ 150 brow = row/bs; \ 151 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 152 rmax = bimax[brow]; nrow = bilen[brow]; \ 153 bcol = col/bs; \ 154 ridx = row % bs; cidx = col % bs; \ 155 low = 0; high = nrow; \ 156 while (high-low > 3) { \ 157 t = (low+high)/2; \ 158 if (rp[t] > bcol) high = t; \ 159 else low = t; \ 160 } \ 161 for (_i=low; _i<high; _i++) { \ 162 if (rp[_i] > bcol) break; \ 163 if (rp[_i] == bcol) { \ 164 bap = ap + bs2*_i + bs*cidx + ridx; \ 165 if (addv == ADD_VALUES) *bap += value; \ 166 else *bap = value; \ 167 goto b_noinsert; \ 168 } \ 169 } \ 170 if (b->nonew == 1) goto b_noinsert; \ 171 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 172 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 173 N = nrow++ - 1; \ 174 /* shift up all the later entries in this row */ \ 175 for (ii=N; ii>=_i; ii--) { \ 176 rp[ii+1] = rp[ii]; \ 177 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 178 } \ 179 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 180 rp[_i] = bcol; \ 181 ap[bs2*_i + bs*cidx + ridx] = value; \ 182 b_noinsert:; \ 183 bilen[brow] = nrow; \ 184 } 185 186 #undef __FUNCT__ 187 #define __FUNCT__ "MatSetValues_MPIBAIJ" 188 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 189 { 190 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 191 MatScalar value; 192 PetscBool roworiented = baij->roworiented; 193 PetscErrorCode ierr; 194 PetscInt i,j,row,col; 195 PetscInt rstart_orig=mat->rmap->rstart; 196 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 197 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 198 199 /* Some Variables required in the macro */ 200 Mat A = baij->A; 201 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 202 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 203 MatScalar *aa =a->a; 204 205 Mat B = baij->B; 206 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 207 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 208 MatScalar *ba =b->a; 209 210 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 211 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 212 MatScalar *ap,*bap; 213 214 PetscFunctionBegin; 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 = PetscMalloc1(bs2,&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 for (i=0; i<m; i++) { 398 #if defined(PETSC_USE_DEBUG) 399 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 400 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); 401 #endif 402 row = im[i]; 403 if (row >= rstart_orig && row < rend_orig) { 404 for (j=0; j<n; j++) { 405 col = in[j]; 406 if (roworiented) value = v[i*n+j]; 407 else value = v[i+j*m]; 408 /* Look up PetscInto the Hash Table */ 409 key = (row/bs)*Nbs+(col/bs)+1; 410 h1 = HASH(size,key,tmp); 411 412 413 idx = h1; 414 #if defined(PETSC_USE_DEBUG) 415 insert_ct++; 416 total_ct++; 417 if (HT[idx] != key) { 418 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 419 if (idx == size) { 420 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 421 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 422 } 423 } 424 #else 425 if (HT[idx] != key) { 426 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 427 if (idx == size) { 428 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 429 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 430 } 431 } 432 #endif 433 /* A HASH table entry is found, so insert the values at the correct address */ 434 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 435 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 436 } 437 } else if (!baij->donotstash) { 438 if (roworiented) { 439 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 440 } else { 441 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 442 } 443 } 444 } 445 #if defined(PETSC_USE_DEBUG) 446 baij->ht_total_ct = total_ct; 447 baij->ht_insert_ct = insert_ct; 448 #endif 449 PetscFunctionReturn(0); 450 } 451 452 #undef __FUNCT__ 453 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 454 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 455 { 456 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 457 PetscBool roworiented = baij->roworiented; 458 PetscErrorCode ierr; 459 PetscInt i,j,ii,jj,row,col; 460 PetscInt rstart=baij->rstartbs; 461 PetscInt rend =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 462 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 463 PetscReal tmp; 464 MatScalar **HD = baij->hd,*baij_a; 465 const PetscScalar *v_t,*value; 466 #if defined(PETSC_USE_DEBUG) 467 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 468 #endif 469 470 PetscFunctionBegin; 471 if (roworiented) stepval = (n-1)*bs; 472 else stepval = (m-1)*bs; 473 474 for (i=0; i<m; i++) { 475 #if defined(PETSC_USE_DEBUG) 476 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 477 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); 478 #endif 479 row = im[i]; 480 v_t = v + i*nbs2; 481 if (row >= rstart && row < rend) { 482 for (j=0; j<n; j++) { 483 col = in[j]; 484 485 /* Look up into the Hash Table */ 486 key = row*Nbs+col+1; 487 h1 = HASH(size,key,tmp); 488 489 idx = h1; 490 #if defined(PETSC_USE_DEBUG) 491 total_ct++; 492 insert_ct++; 493 if (HT[idx] != key) { 494 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 495 if (idx == size) { 496 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 497 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 498 } 499 } 500 #else 501 if (HT[idx] != key) { 502 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 503 if (idx == size) { 504 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 505 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 506 } 507 } 508 #endif 509 baij_a = HD[idx]; 510 if (roworiented) { 511 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 512 /* value = v + (i*(stepval+bs)+j)*bs; */ 513 value = v_t; 514 v_t += bs; 515 if (addv == ADD_VALUES) { 516 for (ii=0; ii<bs; ii++,value+=stepval) { 517 for (jj=ii; jj<bs2; jj+=bs) { 518 baij_a[jj] += *value++; 519 } 520 } 521 } else { 522 for (ii=0; ii<bs; ii++,value+=stepval) { 523 for (jj=ii; jj<bs2; jj+=bs) { 524 baij_a[jj] = *value++; 525 } 526 } 527 } 528 } else { 529 value = v + j*(stepval+bs)*bs + i*bs; 530 if (addv == ADD_VALUES) { 531 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 532 for (jj=0; jj<bs; jj++) { 533 baij_a[jj] += *value++; 534 } 535 } 536 } else { 537 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 538 for (jj=0; jj<bs; jj++) { 539 baij_a[jj] = *value++; 540 } 541 } 542 } 543 } 544 } 545 } else { 546 if (!baij->donotstash) { 547 if (roworiented) { 548 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 549 } else { 550 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 551 } 552 } 553 } 554 } 555 #if defined(PETSC_USE_DEBUG) 556 baij->ht_total_ct = total_ct; 557 baij->ht_insert_ct = insert_ct; 558 #endif 559 PetscFunctionReturn(0); 560 } 561 562 #undef __FUNCT__ 563 #define __FUNCT__ "MatGetValues_MPIBAIJ" 564 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 565 { 566 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 567 PetscErrorCode ierr; 568 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 569 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 570 571 PetscFunctionBegin; 572 for (i=0; i<m; i++) { 573 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 574 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); 575 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 576 row = idxm[i] - bsrstart; 577 for (j=0; j<n; j++) { 578 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 579 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); 580 if (idxn[j] >= bscstart && idxn[j] < bscend) { 581 col = idxn[j] - bscstart; 582 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 583 } else { 584 if (!baij->colmap) { 585 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 586 } 587 #if defined(PETSC_USE_CTABLE) 588 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 589 data--; 590 #else 591 data = baij->colmap[idxn[j]/bs]-1; 592 #endif 593 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 594 else { 595 col = data + idxn[j]%bs; 596 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 597 } 598 } 599 } 600 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 601 } 602 PetscFunctionReturn(0); 603 } 604 605 #undef __FUNCT__ 606 #define __FUNCT__ "MatNorm_MPIBAIJ" 607 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 608 { 609 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 610 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 611 PetscErrorCode ierr; 612 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 613 PetscReal sum = 0.0; 614 MatScalar *v; 615 616 PetscFunctionBegin; 617 if (baij->size == 1) { 618 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 619 } else { 620 if (type == NORM_FROBENIUS) { 621 v = amat->a; 622 nz = amat->nz*bs2; 623 for (i=0; i<nz; i++) { 624 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 625 } 626 v = bmat->a; 627 nz = bmat->nz*bs2; 628 for (i=0; i<nz; i++) { 629 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 630 } 631 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 632 *nrm = PetscSqrtReal(*nrm); 633 } else if (type == NORM_1) { /* max column sum */ 634 PetscReal *tmp,*tmp2; 635 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 636 ierr = PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);CHKERRQ(ierr); 637 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 638 v = amat->a; jj = amat->j; 639 for (i=0; i<amat->nz; i++) { 640 for (j=0; j<bs; j++) { 641 col = bs*(cstart + *jj) + j; /* column index */ 642 for (row=0; row<bs; row++) { 643 tmp[col] += PetscAbsScalar(*v); v++; 644 } 645 } 646 jj++; 647 } 648 v = bmat->a; jj = bmat->j; 649 for (i=0; i<bmat->nz; i++) { 650 for (j=0; j<bs; j++) { 651 col = bs*garray[*jj] + j; 652 for (row=0; row<bs; row++) { 653 tmp[col] += PetscAbsScalar(*v); v++; 654 } 655 } 656 jj++; 657 } 658 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 659 *nrm = 0.0; 660 for (j=0; j<mat->cmap->N; j++) { 661 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 662 } 663 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 664 } else if (type == NORM_INFINITY) { /* max row sum */ 665 PetscReal *sums; 666 ierr = PetscMalloc1(bs,&sums);CHKERRQ(ierr); 667 sum = 0.0; 668 for (j=0; j<amat->mbs; j++) { 669 for (row=0; row<bs; row++) sums[row] = 0.0; 670 v = amat->a + bs2*amat->i[j]; 671 nz = amat->i[j+1]-amat->i[j]; 672 for (i=0; i<nz; i++) { 673 for (col=0; col<bs; col++) { 674 for (row=0; row<bs; row++) { 675 sums[row] += PetscAbsScalar(*v); v++; 676 } 677 } 678 } 679 v = bmat->a + bs2*bmat->i[j]; 680 nz = bmat->i[j+1]-bmat->i[j]; 681 for (i=0; i<nz; i++) { 682 for (col=0; col<bs; col++) { 683 for (row=0; row<bs; row++) { 684 sums[row] += PetscAbsScalar(*v); v++; 685 } 686 } 687 } 688 for (row=0; row<bs; row++) { 689 if (sums[row] > sum) sum = sums[row]; 690 } 691 } 692 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 693 ierr = PetscFree(sums);CHKERRQ(ierr); 694 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet"); 695 } 696 PetscFunctionReturn(0); 697 } 698 699 /* 700 Creates the hash table, and sets the table 701 This table is created only once. 702 If new entried need to be added to the matrix 703 then the hash table has to be destroyed and 704 recreated. 705 */ 706 #undef __FUNCT__ 707 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 708 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 709 { 710 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 711 Mat A = baij->A,B=baij->B; 712 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data; 713 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 714 PetscErrorCode ierr; 715 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 716 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 717 PetscInt *HT,key; 718 MatScalar **HD; 719 PetscReal tmp; 720 #if defined(PETSC_USE_INFO) 721 PetscInt ct=0,max=0; 722 #endif 723 724 PetscFunctionBegin; 725 if (baij->ht) PetscFunctionReturn(0); 726 727 baij->ht_size = (PetscInt)(factor*nz); 728 ht_size = baij->ht_size; 729 730 /* Allocate Memory for Hash Table */ 731 ierr = PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);CHKERRQ(ierr); 732 HD = baij->hd; 733 HT = baij->ht; 734 735 /* Loop Over A */ 736 for (i=0; i<a->mbs; i++) { 737 for (j=ai[i]; j<ai[i+1]; j++) { 738 row = i+rstart; 739 col = aj[j]+cstart; 740 741 key = row*Nbs + col + 1; 742 h1 = HASH(ht_size,key,tmp); 743 for (k=0; k<ht_size; k++) { 744 if (!HT[(h1+k)%ht_size]) { 745 HT[(h1+k)%ht_size] = key; 746 HD[(h1+k)%ht_size] = a->a + j*bs2; 747 break; 748 #if defined(PETSC_USE_INFO) 749 } else { 750 ct++; 751 #endif 752 } 753 } 754 #if defined(PETSC_USE_INFO) 755 if (k> max) max = k; 756 #endif 757 } 758 } 759 /* Loop Over B */ 760 for (i=0; i<b->mbs; i++) { 761 for (j=bi[i]; j<bi[i+1]; j++) { 762 row = i+rstart; 763 col = garray[bj[j]]; 764 key = row*Nbs + col + 1; 765 h1 = HASH(ht_size,key,tmp); 766 for (k=0; k<ht_size; k++) { 767 if (!HT[(h1+k)%ht_size]) { 768 HT[(h1+k)%ht_size] = key; 769 HD[(h1+k)%ht_size] = b->a + j*bs2; 770 break; 771 #if defined(PETSC_USE_INFO) 772 } else { 773 ct++; 774 #endif 775 } 776 } 777 #if defined(PETSC_USE_INFO) 778 if (k> max) max = k; 779 #endif 780 } 781 } 782 783 /* Print Summary */ 784 #if defined(PETSC_USE_INFO) 785 for (i=0,j=0; i<ht_size; i++) { 786 if (HT[i]) j++; 787 } 788 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 789 #endif 790 PetscFunctionReturn(0); 791 } 792 793 #undef __FUNCT__ 794 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 795 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 796 { 797 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 798 PetscErrorCode ierr; 799 PetscInt nstash,reallocs; 800 InsertMode addv; 801 802 PetscFunctionBegin; 803 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 804 805 /* make sure all processors are either in INSERTMODE or ADDMODE */ 806 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 807 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 808 mat->insertmode = addv; /* in case this processor had no cache */ 809 810 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 811 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 812 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 813 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 814 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 815 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 816 PetscFunctionReturn(0); 817 } 818 819 #undef __FUNCT__ 820 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 821 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 822 { 823 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 824 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)baij->A->data; 825 PetscErrorCode ierr; 826 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 827 PetscInt *row,*col; 828 PetscBool r1,r2,r3,other_disassembled; 829 MatScalar *val; 830 InsertMode addv = mat->insertmode; 831 PetscMPIInt n; 832 833 PetscFunctionBegin; 834 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 835 if (!baij->donotstash && !mat->nooffprocentries) { 836 while (1) { 837 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 838 if (!flg) break; 839 840 for (i=0; i<n;) { 841 /* Now identify the consecutive vals belonging to the same row */ 842 for (j=i,rstart=row[j]; j<n; j++) { 843 if (row[j] != rstart) break; 844 } 845 if (j < n) ncols = j-i; 846 else ncols = n-i; 847 /* Now assemble all these values with a single function call */ 848 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 849 i = j; 850 } 851 } 852 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 853 /* Now process the block-stash. Since the values are stashed column-oriented, 854 set the roworiented flag to column oriented, and after MatSetValues() 855 restore the original flags */ 856 r1 = baij->roworiented; 857 r2 = a->roworiented; 858 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 859 860 baij->roworiented = PETSC_FALSE; 861 a->roworiented = PETSC_FALSE; 862 863 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 864 while (1) { 865 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 866 if (!flg) break; 867 868 for (i=0; i<n;) { 869 /* Now identify the consecutive vals belonging to the same row */ 870 for (j=i,rstart=row[j]; j<n; j++) { 871 if (row[j] != rstart) break; 872 } 873 if (j < n) ncols = j-i; 874 else ncols = n-i; 875 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 876 i = j; 877 } 878 } 879 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 880 881 baij->roworiented = r1; 882 a->roworiented = r2; 883 884 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 885 } 886 887 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 888 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 889 890 /* determine if any processor has disassembled, if so we must 891 also disassemble ourselfs, in order that we may reassemble. */ 892 /* 893 if nonzero structure of submatrix B cannot change then we know that 894 no processor disassembled thus we can skip this stuff 895 */ 896 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 897 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 898 if (mat->was_assembled && !other_disassembled) { 899 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 900 } 901 } 902 903 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 904 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 905 } 906 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 907 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 908 909 #if defined(PETSC_USE_INFO) 910 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 911 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 912 913 baij->ht_total_ct = 0; 914 baij->ht_insert_ct = 0; 915 } 916 #endif 917 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 918 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 919 920 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 921 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 922 } 923 924 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 925 926 baij->rowvalues = 0; 927 928 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 929 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 930 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 931 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 932 } 933 PetscFunctionReturn(0); 934 } 935 936 extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer); 937 #include <petscdraw.h> 938 #undef __FUNCT__ 939 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 940 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 941 { 942 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 943 PetscErrorCode ierr; 944 PetscMPIInt rank = baij->rank; 945 PetscInt bs = mat->rmap->bs; 946 PetscBool iascii,isdraw; 947 PetscViewer sviewer; 948 PetscViewerFormat format; 949 950 PetscFunctionBegin; 951 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 952 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 953 if (iascii) { 954 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 955 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 956 MatInfo info; 957 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 958 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 959 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 960 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 961 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 962 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 963 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 964 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 965 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 966 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 967 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 968 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 969 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 970 PetscFunctionReturn(0); 971 } else if (format == PETSC_VIEWER_ASCII_INFO) { 972 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 973 PetscFunctionReturn(0); 974 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 975 PetscFunctionReturn(0); 976 } 977 } 978 979 if (isdraw) { 980 PetscDraw draw; 981 PetscBool isnull; 982 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 983 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 984 } 985 986 { 987 /* assemble the entire matrix onto first processor. */ 988 Mat A; 989 Mat_SeqBAIJ *Aloc; 990 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 991 MatScalar *a; 992 993 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 994 /* Perhaps this should be the type of mat? */ 995 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 996 if (!rank) { 997 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 998 } else { 999 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1000 } 1001 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1002 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1003 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1004 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1005 1006 /* copy over the A part */ 1007 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1008 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1009 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1010 1011 for (i=0; i<mbs; i++) { 1012 rvals[0] = bs*(baij->rstartbs + i); 1013 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1014 for (j=ai[i]; j<ai[i+1]; j++) { 1015 col = (baij->cstartbs+aj[j])*bs; 1016 for (k=0; k<bs; k++) { 1017 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1018 col++; a += bs; 1019 } 1020 } 1021 } 1022 /* copy over the B part */ 1023 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1024 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1025 for (i=0; i<mbs; i++) { 1026 rvals[0] = bs*(baij->rstartbs + i); 1027 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1028 for (j=ai[i]; j<ai[i+1]; j++) { 1029 col = baij->garray[aj[j]]*bs; 1030 for (k=0; k<bs; k++) { 1031 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1032 col++; a += bs; 1033 } 1034 } 1035 } 1036 ierr = PetscFree(rvals);CHKERRQ(ierr); 1037 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1038 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1039 /* 1040 Everyone has to call to draw the matrix since the graphics waits are 1041 synchronized across all processors that share the PetscDraw object 1042 */ 1043 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1044 if (!rank) { 1045 ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1046 } 1047 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1048 ierr = MatDestroy(&A);CHKERRQ(ierr); 1049 } 1050 PetscFunctionReturn(0); 1051 } 1052 1053 #undef __FUNCT__ 1054 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1055 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1056 { 1057 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1058 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1059 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1060 PetscErrorCode ierr; 1061 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1062 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1063 int fd; 1064 PetscScalar *column_values; 1065 FILE *file; 1066 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1067 PetscInt message_count,flowcontrolcount; 1068 1069 PetscFunctionBegin; 1070 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1071 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1072 nz = bs2*(A->nz + B->nz); 1073 rlen = mat->rmap->n; 1074 if (!rank) { 1075 header[0] = MAT_FILE_CLASSID; 1076 header[1] = mat->rmap->N; 1077 header[2] = mat->cmap->N; 1078 1079 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1080 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1081 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1082 /* get largest number of rows any processor has */ 1083 range = mat->rmap->range; 1084 for (i=1; i<size; i++) { 1085 rlen = PetscMax(rlen,range[i+1] - range[i]); 1086 } 1087 } else { 1088 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1089 } 1090 1091 ierr = PetscMalloc1((rlen/bs),&crow_lens);CHKERRQ(ierr); 1092 /* compute lengths of each row */ 1093 for (i=0; i<a->mbs; i++) { 1094 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1095 } 1096 /* store the row lengths to the file */ 1097 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1098 if (!rank) { 1099 MPI_Status status; 1100 ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr); 1101 rlen = (range[1] - range[0])/bs; 1102 for (i=0; i<rlen; i++) { 1103 for (j=0; j<bs; j++) { 1104 row_lens[i*bs+j] = bs*crow_lens[i]; 1105 } 1106 } 1107 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1108 for (i=1; i<size; i++) { 1109 rlen = (range[i+1] - range[i])/bs; 1110 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1111 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1112 for (k=0; k<rlen; k++) { 1113 for (j=0; j<bs; j++) { 1114 row_lens[k*bs+j] = bs*crow_lens[k]; 1115 } 1116 } 1117 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1118 } 1119 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1120 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1121 } else { 1122 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1123 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1124 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1125 } 1126 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1127 1128 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1129 information needed to make it for each row from a block row. This does require more communication but still not more than 1130 the communication needed for the nonzero values */ 1131 nzmax = nz; /* space a largest processor needs */ 1132 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1133 ierr = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr); 1134 cnt = 0; 1135 for (i=0; i<a->mbs; i++) { 1136 pcnt = cnt; 1137 for (j=B->i[i]; j<B->i[i+1]; j++) { 1138 if ((col = garray[B->j[j]]) > cstart) break; 1139 for (l=0; l<bs; l++) { 1140 column_indices[cnt++] = bs*col+l; 1141 } 1142 } 1143 for (k=A->i[i]; k<A->i[i+1]; k++) { 1144 for (l=0; l<bs; l++) { 1145 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1146 } 1147 } 1148 for (; j<B->i[i+1]; j++) { 1149 for (l=0; l<bs; l++) { 1150 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1151 } 1152 } 1153 len = cnt - pcnt; 1154 for (k=1; k<bs; k++) { 1155 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1156 cnt += len; 1157 } 1158 } 1159 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1160 1161 /* store the columns to the file */ 1162 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1163 if (!rank) { 1164 MPI_Status status; 1165 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1166 for (i=1; i<size; i++) { 1167 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1168 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1169 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1170 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1171 } 1172 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1173 } else { 1174 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1175 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1176 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1177 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1178 } 1179 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1180 1181 /* load up the numerical values */ 1182 ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr); 1183 cnt = 0; 1184 for (i=0; i<a->mbs; i++) { 1185 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1186 for (j=B->i[i]; j<B->i[i+1]; j++) { 1187 if (garray[B->j[j]] > cstart) break; 1188 for (l=0; l<bs; l++) { 1189 for (ll=0; ll<bs; ll++) { 1190 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1191 } 1192 } 1193 cnt += bs; 1194 } 1195 for (k=A->i[i]; k<A->i[i+1]; k++) { 1196 for (l=0; l<bs; l++) { 1197 for (ll=0; ll<bs; ll++) { 1198 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1199 } 1200 } 1201 cnt += bs; 1202 } 1203 for (; j<B->i[i+1]; j++) { 1204 for (l=0; l<bs; l++) { 1205 for (ll=0; ll<bs; ll++) { 1206 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1207 } 1208 } 1209 cnt += bs; 1210 } 1211 cnt += (bs-1)*rlen; 1212 } 1213 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1214 1215 /* store the column values to the file */ 1216 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1217 if (!rank) { 1218 MPI_Status status; 1219 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1220 for (i=1; i<size; i++) { 1221 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1222 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1223 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1224 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1225 } 1226 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1227 } else { 1228 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1229 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1230 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1231 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1232 } 1233 ierr = PetscFree(column_values);CHKERRQ(ierr); 1234 1235 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1236 if (file) { 1237 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1238 } 1239 PetscFunctionReturn(0); 1240 } 1241 1242 #undef __FUNCT__ 1243 #define __FUNCT__ "MatView_MPIBAIJ" 1244 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1245 { 1246 PetscErrorCode ierr; 1247 PetscBool iascii,isdraw,issocket,isbinary; 1248 1249 PetscFunctionBegin; 1250 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1251 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1252 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1253 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1254 if (iascii || isdraw || issocket) { 1255 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1256 } else if (isbinary) { 1257 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1258 } 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #undef __FUNCT__ 1263 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1264 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1265 { 1266 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1267 PetscErrorCode ierr; 1268 1269 PetscFunctionBegin; 1270 #if defined(PETSC_USE_LOG) 1271 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1272 #endif 1273 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1274 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1275 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1276 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1277 #if defined(PETSC_USE_CTABLE) 1278 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1279 #else 1280 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1281 #endif 1282 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1283 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1284 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1285 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1286 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1287 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1288 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1289 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1290 1291 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1292 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1293 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1294 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1295 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1301 PetscFunctionReturn(0); 1302 } 1303 1304 #undef __FUNCT__ 1305 #define __FUNCT__ "MatMult_MPIBAIJ" 1306 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1307 { 1308 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1309 PetscErrorCode ierr; 1310 PetscInt nt; 1311 1312 PetscFunctionBegin; 1313 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1314 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1315 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1316 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1317 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1318 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1319 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1320 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1321 PetscFunctionReturn(0); 1322 } 1323 1324 #undef __FUNCT__ 1325 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1326 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1327 { 1328 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1329 PetscErrorCode ierr; 1330 1331 PetscFunctionBegin; 1332 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1333 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1334 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1335 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1336 PetscFunctionReturn(0); 1337 } 1338 1339 #undef __FUNCT__ 1340 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1341 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1342 { 1343 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1344 PetscErrorCode ierr; 1345 PetscBool merged; 1346 1347 PetscFunctionBegin; 1348 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1349 /* do nondiagonal part */ 1350 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1351 if (!merged) { 1352 /* send it on its way */ 1353 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1354 /* do local part */ 1355 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1356 /* receive remote parts: note this assumes the values are not actually */ 1357 /* inserted in yy until the next line */ 1358 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1359 } else { 1360 /* do local part */ 1361 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1362 /* send it on its way */ 1363 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1364 /* values actually were received in the Begin() but we need to call this nop */ 1365 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1366 } 1367 PetscFunctionReturn(0); 1368 } 1369 1370 #undef __FUNCT__ 1371 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1372 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1373 { 1374 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1375 PetscErrorCode ierr; 1376 1377 PetscFunctionBegin; 1378 /* do nondiagonal part */ 1379 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1380 /* send it on its way */ 1381 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1382 /* do local part */ 1383 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1384 /* receive remote parts: note this assumes the values are not actually */ 1385 /* inserted in yy until the next line, which is true for my implementation*/ 1386 /* but is not perhaps always true. */ 1387 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1388 PetscFunctionReturn(0); 1389 } 1390 1391 /* 1392 This only works correctly for square matrices where the subblock A->A is the 1393 diagonal block 1394 */ 1395 #undef __FUNCT__ 1396 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1397 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1398 { 1399 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1400 PetscErrorCode ierr; 1401 1402 PetscFunctionBegin; 1403 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1404 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1405 PetscFunctionReturn(0); 1406 } 1407 1408 #undef __FUNCT__ 1409 #define __FUNCT__ "MatScale_MPIBAIJ" 1410 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1411 { 1412 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1413 PetscErrorCode ierr; 1414 1415 PetscFunctionBegin; 1416 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1417 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1418 PetscFunctionReturn(0); 1419 } 1420 1421 #undef __FUNCT__ 1422 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1423 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1424 { 1425 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1426 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1427 PetscErrorCode ierr; 1428 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1429 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1430 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1431 1432 PetscFunctionBegin; 1433 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1434 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1435 mat->getrowactive = PETSC_TRUE; 1436 1437 if (!mat->rowvalues && (idx || v)) { 1438 /* 1439 allocate enough space to hold information from the longest row. 1440 */ 1441 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1442 PetscInt max = 1,mbs = mat->mbs,tmp; 1443 for (i=0; i<mbs; i++) { 1444 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1445 if (max < tmp) max = tmp; 1446 } 1447 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1448 } 1449 lrow = row - brstart; 1450 1451 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1452 if (!v) {pvA = 0; pvB = 0;} 1453 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1454 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1455 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1456 nztot = nzA + nzB; 1457 1458 cmap = mat->garray; 1459 if (v || idx) { 1460 if (nztot) { 1461 /* Sort by increasing column numbers, assuming A and B already sorted */ 1462 PetscInt imark = -1; 1463 if (v) { 1464 *v = v_p = mat->rowvalues; 1465 for (i=0; i<nzB; i++) { 1466 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1467 else break; 1468 } 1469 imark = i; 1470 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1471 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1472 } 1473 if (idx) { 1474 *idx = idx_p = mat->rowindices; 1475 if (imark > -1) { 1476 for (i=0; i<imark; i++) { 1477 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1478 } 1479 } else { 1480 for (i=0; i<nzB; i++) { 1481 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1482 else break; 1483 } 1484 imark = i; 1485 } 1486 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1487 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1488 } 1489 } else { 1490 if (idx) *idx = 0; 1491 if (v) *v = 0; 1492 } 1493 } 1494 *nz = nztot; 1495 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1496 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1497 PetscFunctionReturn(0); 1498 } 1499 1500 #undef __FUNCT__ 1501 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1502 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1503 { 1504 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1505 1506 PetscFunctionBegin; 1507 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1508 baij->getrowactive = PETSC_FALSE; 1509 PetscFunctionReturn(0); 1510 } 1511 1512 #undef __FUNCT__ 1513 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1514 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1515 { 1516 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1517 PetscErrorCode ierr; 1518 1519 PetscFunctionBegin; 1520 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1521 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1522 PetscFunctionReturn(0); 1523 } 1524 1525 #undef __FUNCT__ 1526 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1527 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1528 { 1529 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1530 Mat A = a->A,B = a->B; 1531 PetscErrorCode ierr; 1532 PetscReal isend[5],irecv[5]; 1533 1534 PetscFunctionBegin; 1535 info->block_size = (PetscReal)matin->rmap->bs; 1536 1537 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1538 1539 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1540 isend[3] = info->memory; isend[4] = info->mallocs; 1541 1542 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1543 1544 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1545 isend[3] += info->memory; isend[4] += info->mallocs; 1546 1547 if (flag == MAT_LOCAL) { 1548 info->nz_used = isend[0]; 1549 info->nz_allocated = isend[1]; 1550 info->nz_unneeded = isend[2]; 1551 info->memory = isend[3]; 1552 info->mallocs = isend[4]; 1553 } else if (flag == MAT_GLOBAL_MAX) { 1554 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1555 1556 info->nz_used = irecv[0]; 1557 info->nz_allocated = irecv[1]; 1558 info->nz_unneeded = irecv[2]; 1559 info->memory = irecv[3]; 1560 info->mallocs = irecv[4]; 1561 } else if (flag == MAT_GLOBAL_SUM) { 1562 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1563 1564 info->nz_used = irecv[0]; 1565 info->nz_allocated = irecv[1]; 1566 info->nz_unneeded = irecv[2]; 1567 info->memory = irecv[3]; 1568 info->mallocs = irecv[4]; 1569 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1570 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1571 info->fill_ratio_needed = 0; 1572 info->factor_mallocs = 0; 1573 PetscFunctionReturn(0); 1574 } 1575 1576 #undef __FUNCT__ 1577 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1578 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1579 { 1580 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1581 PetscErrorCode ierr; 1582 1583 PetscFunctionBegin; 1584 switch (op) { 1585 case MAT_NEW_NONZERO_LOCATIONS: 1586 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1587 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1588 case MAT_KEEP_NONZERO_PATTERN: 1589 case MAT_NEW_NONZERO_LOCATION_ERR: 1590 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1591 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1592 break; 1593 case MAT_ROW_ORIENTED: 1594 a->roworiented = flg; 1595 1596 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1597 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1598 break; 1599 case MAT_NEW_DIAGONALS: 1600 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1601 break; 1602 case MAT_IGNORE_OFF_PROC_ENTRIES: 1603 a->donotstash = flg; 1604 break; 1605 case MAT_USE_HASH_TABLE: 1606 a->ht_flag = flg; 1607 break; 1608 case MAT_SYMMETRIC: 1609 case MAT_STRUCTURALLY_SYMMETRIC: 1610 case MAT_HERMITIAN: 1611 case MAT_SYMMETRY_ETERNAL: 1612 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1613 break; 1614 default: 1615 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1616 } 1617 PetscFunctionReturn(0); 1618 } 1619 1620 #undef __FUNCT__ 1621 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1622 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1623 { 1624 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1625 Mat_SeqBAIJ *Aloc; 1626 Mat B; 1627 PetscErrorCode ierr; 1628 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1629 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1630 MatScalar *a; 1631 1632 PetscFunctionBegin; 1633 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1634 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1635 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1636 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1637 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1638 /* Do not know preallocation information, but must set block size */ 1639 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1640 } else { 1641 B = *matout; 1642 } 1643 1644 /* copy over the A part */ 1645 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1646 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1647 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1648 1649 for (i=0; i<mbs; i++) { 1650 rvals[0] = bs*(baij->rstartbs + i); 1651 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1652 for (j=ai[i]; j<ai[i+1]; j++) { 1653 col = (baij->cstartbs+aj[j])*bs; 1654 for (k=0; k<bs; k++) { 1655 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1656 1657 col++; a += bs; 1658 } 1659 } 1660 } 1661 /* copy over the B part */ 1662 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1663 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1664 for (i=0; i<mbs; i++) { 1665 rvals[0] = bs*(baij->rstartbs + i); 1666 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1667 for (j=ai[i]; j<ai[i+1]; j++) { 1668 col = baij->garray[aj[j]]*bs; 1669 for (k=0; k<bs; k++) { 1670 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1671 col++; 1672 a += bs; 1673 } 1674 } 1675 } 1676 ierr = PetscFree(rvals);CHKERRQ(ierr); 1677 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1678 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1679 1680 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1681 else { 1682 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1683 } 1684 PetscFunctionReturn(0); 1685 } 1686 1687 #undef __FUNCT__ 1688 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1689 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1690 { 1691 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1692 Mat a = baij->A,b = baij->B; 1693 PetscErrorCode ierr; 1694 PetscInt s1,s2,s3; 1695 1696 PetscFunctionBegin; 1697 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1698 if (rr) { 1699 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1700 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1701 /* Overlap communication with computation. */ 1702 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1703 } 1704 if (ll) { 1705 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1706 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1707 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1708 } 1709 /* scale the diagonal block */ 1710 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1711 1712 if (rr) { 1713 /* Do a scatter end and then right scale the off-diagonal block */ 1714 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1715 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1716 } 1717 PetscFunctionReturn(0); 1718 } 1719 1720 #undef __FUNCT__ 1721 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1722 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1723 { 1724 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1725 PetscInt *owners = A->rmap->range; 1726 PetscInt n = A->rmap->n; 1727 PetscMPIInt size = l->size; 1728 PetscSF sf; 1729 PetscInt *lrows; 1730 PetscSFNode *rrows; 1731 PetscInt lastidx = -1, r, p = 0, len = 0; 1732 PetscErrorCode ierr; 1733 1734 PetscFunctionBegin; 1735 /* Create SF where leaves are input rows and roots are owned rows */ 1736 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1737 for (r = 0; r < n; ++r) lrows[r] = -1; 1738 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1739 for (r = 0; r < N; ++r) { 1740 const PetscInt idx = rows[r]; 1741 PetscBool found = PETSC_FALSE; 1742 /* Trick for efficient searching for sorted rows */ 1743 if (lastidx > idx) p = 0; 1744 lastidx = idx; 1745 for (; p < size; ++p) { 1746 if (idx >= owners[p] && idx < owners[p+1]) { 1747 rrows[r].rank = p; 1748 rrows[r].index = rows[r] - owners[p]; 1749 found = PETSC_TRUE; 1750 break; 1751 } 1752 } 1753 if (!found) SETERRQ1(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %d not found in matrix distribution", idx); 1754 } 1755 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1756 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1757 /* Collect flags for rows to be zeroed */ 1758 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1759 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1760 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1761 /* Compress and put in row numbers */ 1762 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1763 /* fix right hand side if needed */ 1764 if (x && b) { 1765 const PetscScalar *xx; 1766 PetscScalar *bb; 1767 1768 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1769 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1770 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1771 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1772 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1773 } 1774 1775 /* actually zap the local rows */ 1776 /* 1777 Zero the required rows. If the "diagonal block" of the matrix 1778 is square and the user wishes to set the diagonal we use separate 1779 code so that MatSetValues() is not called for each diagonal allocating 1780 new memory, thus calling lots of mallocs and slowing things down. 1781 1782 */ 1783 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1784 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,0,0);CHKERRQ(ierr); 1785 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1786 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,0,0);CHKERRQ(ierr); 1787 } else if (diag != 0.0) { 1788 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1789 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\ 1790 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1791 for (r = 0; r < len; ++r) { 1792 const PetscInt row = lrows[r] + A->rmap->rstart; 1793 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1794 } 1795 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1797 } else { 1798 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1799 } 1800 ierr = PetscFree(lrows);CHKERRQ(ierr); 1801 1802 /* only change matrix nonzero state if pattern was allowed to be changed */ 1803 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1804 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1805 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1806 } 1807 PetscFunctionReturn(0); 1808 } 1809 1810 #undef __FUNCT__ 1811 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1812 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1813 { 1814 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1815 PetscErrorCode ierr; 1816 PetscMPIInt size = l->size,n = A->rmap->n,lastidx = -1; 1817 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1818 PetscInt *lrows,*owners = A->rmap->range; 1819 PetscSFNode *rrows; 1820 PetscSF sf; 1821 const PetscScalar *xx; 1822 PetscScalar *bb,*mask; 1823 Vec xmask,lmask; 1824 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1825 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1826 PetscScalar *aa; 1827 #if defined(PETSC_DEBUG) 1828 PetscBool found = PETSC_FALSE; 1829 #endif 1830 1831 PetscFunctionBegin; 1832 /* Create SF where leaves are input rows and roots are owned rows */ 1833 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1834 for (r = 0; r < n; ++r) lrows[r] = -1; 1835 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1836 for (r = 0; r < N; ++r) { 1837 const PetscInt idx = rows[r]; 1838 PetscBool found = PETSC_FALSE; 1839 /* Trick for efficient searching for sorted rows */ 1840 if (lastidx > idx) p = 0; 1841 lastidx = idx; 1842 for (; p < size; ++p) { 1843 if (idx >= owners[p] && idx < owners[p+1]) { 1844 rrows[r].rank = p; 1845 rrows[r].index = rows[r] - owners[p]; 1846 found = PETSC_TRUE; 1847 break; 1848 } 1849 } 1850 if (!found) SETERRQ1(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %d not found in matrix distribution", idx); 1851 } 1852 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1853 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1854 /* Collect flags for rows to be zeroed */ 1855 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1856 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1857 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1858 /* Compress and put in row numbers */ 1859 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1860 /* zero diagonal part of matrix */ 1861 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1862 /* handle off diagonal part of matrix */ 1863 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1864 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1865 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1866 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1867 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1868 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1869 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1870 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1871 if (x) { 1872 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1873 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1874 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1875 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1876 } 1877 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1878 /* remove zeroed rows of off diagonal matrix */ 1879 for (i = 0; i < len; ++i) { 1880 row = lrows[i]; 1881 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1882 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1883 for (k = 0; k < count; ++k) { 1884 aa[0] = 0.0; 1885 aa += bs; 1886 } 1887 } 1888 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1889 for (i = 0; i < l->B->rmap->N; ++i) { 1890 row = i/bs; 1891 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1892 for (k = 0; k < bs; ++k) { 1893 col = bs*baij->j[j] + k; 1894 if (PetscAbsScalar(mask[col])) { 1895 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1896 if (b) bb[i] -= aa[0]*xx[col]; 1897 aa[0] = 0.0; 1898 } 1899 } 1900 } 1901 } 1902 if (x) { 1903 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1904 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1905 } 1906 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1907 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1908 ierr = PetscFree(lrows);CHKERRQ(ierr); 1909 1910 /* only change matrix nonzero state if pattern was allowed to be changed */ 1911 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1912 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1913 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1914 } 1915 PetscFunctionReturn(0); 1916 } 1917 1918 #undef __FUNCT__ 1919 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1920 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1921 { 1922 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1923 PetscErrorCode ierr; 1924 1925 PetscFunctionBegin; 1926 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1927 PetscFunctionReturn(0); 1928 } 1929 1930 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1931 1932 #undef __FUNCT__ 1933 #define __FUNCT__ "MatEqual_MPIBAIJ" 1934 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1935 { 1936 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1937 Mat a,b,c,d; 1938 PetscBool flg; 1939 PetscErrorCode ierr; 1940 1941 PetscFunctionBegin; 1942 a = matA->A; b = matA->B; 1943 c = matB->A; d = matB->B; 1944 1945 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1946 if (flg) { 1947 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1948 } 1949 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1950 PetscFunctionReturn(0); 1951 } 1952 1953 #undef __FUNCT__ 1954 #define __FUNCT__ "MatCopy_MPIBAIJ" 1955 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1956 { 1957 PetscErrorCode ierr; 1958 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1959 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1960 1961 PetscFunctionBegin; 1962 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1963 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1964 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1965 } else { 1966 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1967 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1968 } 1969 PetscFunctionReturn(0); 1970 } 1971 1972 #undef __FUNCT__ 1973 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1974 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1975 { 1976 PetscErrorCode ierr; 1977 1978 PetscFunctionBegin; 1979 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1980 PetscFunctionReturn(0); 1981 } 1982 1983 #undef __FUNCT__ 1984 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 1985 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 1986 { 1987 PetscErrorCode ierr; 1988 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 1989 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 1990 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 1991 1992 PetscFunctionBegin; 1993 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1999 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2000 { 2001 PetscErrorCode ierr; 2002 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 2003 PetscBLASInt bnz,one=1; 2004 Mat_SeqBAIJ *x,*y; 2005 2006 PetscFunctionBegin; 2007 if (str == SAME_NONZERO_PATTERN) { 2008 PetscScalar alpha = a; 2009 x = (Mat_SeqBAIJ*)xx->A->data; 2010 y = (Mat_SeqBAIJ*)yy->A->data; 2011 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2012 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2013 x = (Mat_SeqBAIJ*)xx->B->data; 2014 y = (Mat_SeqBAIJ*)yy->B->data; 2015 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2016 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2017 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2018 } else { 2019 Mat B; 2020 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2021 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2022 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2023 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2024 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2025 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2026 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2027 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2028 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2029 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2030 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2031 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2032 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2033 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2034 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2035 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2036 } 2037 PetscFunctionReturn(0); 2038 } 2039 2040 #undef __FUNCT__ 2041 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2042 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2043 { 2044 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2045 PetscErrorCode ierr; 2046 2047 PetscFunctionBegin; 2048 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2049 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2050 PetscFunctionReturn(0); 2051 } 2052 2053 #undef __FUNCT__ 2054 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2055 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2056 { 2057 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2058 PetscErrorCode ierr; 2059 2060 PetscFunctionBegin; 2061 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2062 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2063 PetscFunctionReturn(0); 2064 } 2065 2066 #undef __FUNCT__ 2067 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2068 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2069 { 2070 PetscErrorCode ierr; 2071 IS iscol_local; 2072 PetscInt csize; 2073 2074 PetscFunctionBegin; 2075 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2076 if (call == MAT_REUSE_MATRIX) { 2077 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2078 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2079 } else { 2080 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2081 } 2082 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2083 if (call == MAT_INITIAL_MATRIX) { 2084 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2085 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2086 } 2087 PetscFunctionReturn(0); 2088 } 2089 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2090 #undef __FUNCT__ 2091 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2092 /* 2093 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2094 in local and then by concatenating the local matrices the end result. 2095 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2096 */ 2097 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2098 { 2099 PetscErrorCode ierr; 2100 PetscMPIInt rank,size; 2101 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2102 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2103 Mat M,Mreuse; 2104 MatScalar *vwork,*aa; 2105 MPI_Comm comm; 2106 IS isrow_new, iscol_new; 2107 PetscBool idflag,allrows, allcols; 2108 Mat_SeqBAIJ *aij; 2109 2110 PetscFunctionBegin; 2111 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2112 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2113 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2114 /* The compression and expansion should be avoided. Doesn't point 2115 out errors, might change the indices, hence buggey */ 2116 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2117 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2118 2119 /* Check for special case: each processor gets entire matrix columns */ 2120 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2121 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2122 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2123 else allcols = PETSC_FALSE; 2124 2125 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2126 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2127 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2128 else allrows = PETSC_FALSE; 2129 2130 if (call == MAT_REUSE_MATRIX) { 2131 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2132 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2133 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2134 } else { 2135 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2136 } 2137 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2138 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2139 /* 2140 m - number of local rows 2141 n - number of columns (same on all processors) 2142 rstart - first row in new global matrix generated 2143 */ 2144 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2145 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2146 m = m/bs; 2147 n = n/bs; 2148 2149 if (call == MAT_INITIAL_MATRIX) { 2150 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2151 ii = aij->i; 2152 jj = aij->j; 2153 2154 /* 2155 Determine the number of non-zeros in the diagonal and off-diagonal 2156 portions of the matrix in order to do correct preallocation 2157 */ 2158 2159 /* first get start and end of "diagonal" columns */ 2160 if (csize == PETSC_DECIDE) { 2161 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2162 if (mglobal == n*bs) { /* square matrix */ 2163 nlocal = m; 2164 } else { 2165 nlocal = n/size + ((n % size) > rank); 2166 } 2167 } else { 2168 nlocal = csize/bs; 2169 } 2170 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2171 rstart = rend - nlocal; 2172 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); 2173 2174 /* next, compute all the lengths */ 2175 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2176 for (i=0; i<m; i++) { 2177 jend = ii[i+1] - ii[i]; 2178 olen = 0; 2179 dlen = 0; 2180 for (j=0; j<jend; j++) { 2181 if (*jj < rstart || *jj >= rend) olen++; 2182 else dlen++; 2183 jj++; 2184 } 2185 olens[i] = olen; 2186 dlens[i] = dlen; 2187 } 2188 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2189 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2190 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2191 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2192 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2193 } else { 2194 PetscInt ml,nl; 2195 2196 M = *newmat; 2197 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2198 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2199 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2200 /* 2201 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2202 rather than the slower MatSetValues(). 2203 */ 2204 M->was_assembled = PETSC_TRUE; 2205 M->assembled = PETSC_FALSE; 2206 } 2207 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2208 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2209 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2210 ii = aij->i; 2211 jj = aij->j; 2212 aa = aij->a; 2213 for (i=0; i<m; i++) { 2214 row = rstart/bs + i; 2215 nz = ii[i+1] - ii[i]; 2216 cwork = jj; jj += nz; 2217 vwork = aa; aa += nz*bs*bs; 2218 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2219 } 2220 2221 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2222 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2223 *newmat = M; 2224 2225 /* save submatrix used in processor for next request */ 2226 if (call == MAT_INITIAL_MATRIX) { 2227 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2228 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2229 } 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatPermute_MPIBAIJ" 2235 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2236 { 2237 MPI_Comm comm,pcomm; 2238 PetscInt clocal_size,nrows; 2239 const PetscInt *rows; 2240 PetscMPIInt size; 2241 IS crowp,lcolp; 2242 PetscErrorCode ierr; 2243 2244 PetscFunctionBegin; 2245 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2246 /* make a collective version of 'rowp' */ 2247 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2248 if (pcomm==comm) { 2249 crowp = rowp; 2250 } else { 2251 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2252 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2253 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2254 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2255 } 2256 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2257 /* make a local version of 'colp' */ 2258 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2259 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2260 if (size==1) { 2261 lcolp = colp; 2262 } else { 2263 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2264 } 2265 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2266 /* now we just get the submatrix */ 2267 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2268 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2269 /* clean up */ 2270 if (pcomm!=comm) { 2271 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2272 } 2273 if (size>1) { 2274 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2275 } 2276 PetscFunctionReturn(0); 2277 } 2278 2279 #undef __FUNCT__ 2280 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2281 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2282 { 2283 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2284 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2285 2286 PetscFunctionBegin; 2287 if (nghosts) *nghosts = B->nbs; 2288 if (ghosts) *ghosts = baij->garray; 2289 PetscFunctionReturn(0); 2290 } 2291 2292 #undef __FUNCT__ 2293 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2294 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2295 { 2296 Mat B; 2297 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2298 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2299 Mat_SeqAIJ *b; 2300 PetscErrorCode ierr; 2301 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2302 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2303 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2304 2305 PetscFunctionBegin; 2306 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2307 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2308 2309 /* ---------------------------------------------------------------- 2310 Tell every processor the number of nonzeros per row 2311 */ 2312 ierr = PetscMalloc1((A->rmap->N/bs),&lens);CHKERRQ(ierr); 2313 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2314 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]; 2315 } 2316 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2317 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2318 displs = recvcounts + size; 2319 for (i=0; i<size; i++) { 2320 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2321 displs[i] = A->rmap->range[i]/bs; 2322 } 2323 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2324 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2325 #else 2326 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2327 #endif 2328 /* --------------------------------------------------------------- 2329 Create the sequential matrix of the same type as the local block diagonal 2330 */ 2331 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2332 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2333 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2334 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2335 b = (Mat_SeqAIJ*)B->data; 2336 2337 /*-------------------------------------------------------------------- 2338 Copy my part of matrix column indices over 2339 */ 2340 sendcount = ad->nz + bd->nz; 2341 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2342 a_jsendbuf = ad->j; 2343 b_jsendbuf = bd->j; 2344 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2345 cnt = 0; 2346 for (i=0; i<n; i++) { 2347 2348 /* put in lower diagonal portion */ 2349 m = bd->i[i+1] - bd->i[i]; 2350 while (m > 0) { 2351 /* is it above diagonal (in bd (compressed) numbering) */ 2352 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2353 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2354 m--; 2355 } 2356 2357 /* put in diagonal portion */ 2358 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2359 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2360 } 2361 2362 /* put in upper diagonal portion */ 2363 while (m-- > 0) { 2364 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2365 } 2366 } 2367 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2368 2369 /*-------------------------------------------------------------------- 2370 Gather all column indices to all processors 2371 */ 2372 for (i=0; i<size; i++) { 2373 recvcounts[i] = 0; 2374 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2375 recvcounts[i] += lens[j]; 2376 } 2377 } 2378 displs[0] = 0; 2379 for (i=1; i<size; i++) { 2380 displs[i] = displs[i-1] + recvcounts[i-1]; 2381 } 2382 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2383 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2384 #else 2385 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2386 #endif 2387 /*-------------------------------------------------------------------- 2388 Assemble the matrix into useable form (note numerical values not yet set) 2389 */ 2390 /* set the b->ilen (length of each row) values */ 2391 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2392 /* set the b->i indices */ 2393 b->i[0] = 0; 2394 for (i=1; i<=A->rmap->N/bs; i++) { 2395 b->i[i] = b->i[i-1] + lens[i-1]; 2396 } 2397 ierr = PetscFree(lens);CHKERRQ(ierr); 2398 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2399 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2400 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2401 2402 if (A->symmetric) { 2403 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2404 } else if (A->hermitian) { 2405 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2406 } else if (A->structurally_symmetric) { 2407 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2408 } 2409 *newmat = B; 2410 PetscFunctionReturn(0); 2411 } 2412 2413 #undef __FUNCT__ 2414 #define __FUNCT__ "MatSOR_MPIBAIJ" 2415 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2416 { 2417 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2418 PetscErrorCode ierr; 2419 Vec bb1 = 0; 2420 2421 PetscFunctionBegin; 2422 if (flag == SOR_APPLY_UPPER) { 2423 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2424 PetscFunctionReturn(0); 2425 } 2426 2427 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2428 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2429 } 2430 2431 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2432 if (flag & SOR_ZERO_INITIAL_GUESS) { 2433 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2434 its--; 2435 } 2436 2437 while (its--) { 2438 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2439 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2440 2441 /* update rhs: bb1 = bb - B*x */ 2442 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2443 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2444 2445 /* local sweep */ 2446 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2447 } 2448 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2449 if (flag & SOR_ZERO_INITIAL_GUESS) { 2450 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2451 its--; 2452 } 2453 while (its--) { 2454 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2455 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2456 2457 /* update rhs: bb1 = bb - B*x */ 2458 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2459 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2460 2461 /* local sweep */ 2462 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2463 } 2464 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2465 if (flag & SOR_ZERO_INITIAL_GUESS) { 2466 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2467 its--; 2468 } 2469 while (its--) { 2470 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2471 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2472 2473 /* update rhs: bb1 = bb - B*x */ 2474 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2475 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2476 2477 /* local sweep */ 2478 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2479 } 2480 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2481 2482 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2483 PetscFunctionReturn(0); 2484 } 2485 2486 #undef __FUNCT__ 2487 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2488 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2489 { 2490 PetscErrorCode ierr; 2491 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2492 PetscInt N,i,*garray = aij->garray; 2493 PetscInt ib,jb,bs = A->rmap->bs; 2494 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2495 MatScalar *a_val = a_aij->a; 2496 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2497 MatScalar *b_val = b_aij->a; 2498 PetscReal *work; 2499 2500 PetscFunctionBegin; 2501 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2502 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2503 if (type == NORM_2) { 2504 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2505 for (jb=0; jb<bs; jb++) { 2506 for (ib=0; ib<bs; ib++) { 2507 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2508 a_val++; 2509 } 2510 } 2511 } 2512 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2513 for (jb=0; jb<bs; jb++) { 2514 for (ib=0; ib<bs; ib++) { 2515 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2516 b_val++; 2517 } 2518 } 2519 } 2520 } else if (type == NORM_1) { 2521 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2522 for (jb=0; jb<bs; jb++) { 2523 for (ib=0; ib<bs; ib++) { 2524 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2525 a_val++; 2526 } 2527 } 2528 } 2529 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2530 for (jb=0; jb<bs; jb++) { 2531 for (ib=0; ib<bs; ib++) { 2532 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2533 b_val++; 2534 } 2535 } 2536 } 2537 } else if (type == NORM_INFINITY) { 2538 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2539 for (jb=0; jb<bs; jb++) { 2540 for (ib=0; ib<bs; ib++) { 2541 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2542 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2543 a_val++; 2544 } 2545 } 2546 } 2547 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2548 for (jb=0; jb<bs; jb++) { 2549 for (ib=0; ib<bs; ib++) { 2550 int col = garray[b_aij->j[i]] * bs + jb; 2551 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2552 b_val++; 2553 } 2554 } 2555 } 2556 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2557 if (type == NORM_INFINITY) { 2558 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2559 } else { 2560 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2561 } 2562 ierr = PetscFree(work);CHKERRQ(ierr); 2563 if (type == NORM_2) { 2564 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2565 } 2566 PetscFunctionReturn(0); 2567 } 2568 2569 #undef __FUNCT__ 2570 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2571 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2572 { 2573 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2574 PetscErrorCode ierr; 2575 2576 PetscFunctionBegin; 2577 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2578 PetscFunctionReturn(0); 2579 } 2580 2581 2582 /* -------------------------------------------------------------------*/ 2583 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2584 MatGetRow_MPIBAIJ, 2585 MatRestoreRow_MPIBAIJ, 2586 MatMult_MPIBAIJ, 2587 /* 4*/ MatMultAdd_MPIBAIJ, 2588 MatMultTranspose_MPIBAIJ, 2589 MatMultTransposeAdd_MPIBAIJ, 2590 0, 2591 0, 2592 0, 2593 /*10*/ 0, 2594 0, 2595 0, 2596 MatSOR_MPIBAIJ, 2597 MatTranspose_MPIBAIJ, 2598 /*15*/ MatGetInfo_MPIBAIJ, 2599 MatEqual_MPIBAIJ, 2600 MatGetDiagonal_MPIBAIJ, 2601 MatDiagonalScale_MPIBAIJ, 2602 MatNorm_MPIBAIJ, 2603 /*20*/ MatAssemblyBegin_MPIBAIJ, 2604 MatAssemblyEnd_MPIBAIJ, 2605 MatSetOption_MPIBAIJ, 2606 MatZeroEntries_MPIBAIJ, 2607 /*24*/ MatZeroRows_MPIBAIJ, 2608 0, 2609 0, 2610 0, 2611 0, 2612 /*29*/ MatSetUp_MPIBAIJ, 2613 0, 2614 0, 2615 0, 2616 0, 2617 /*34*/ MatDuplicate_MPIBAIJ, 2618 0, 2619 0, 2620 0, 2621 0, 2622 /*39*/ MatAXPY_MPIBAIJ, 2623 MatGetSubMatrices_MPIBAIJ, 2624 MatIncreaseOverlap_MPIBAIJ, 2625 MatGetValues_MPIBAIJ, 2626 MatCopy_MPIBAIJ, 2627 /*44*/ 0, 2628 MatScale_MPIBAIJ, 2629 0, 2630 0, 2631 MatZeroRowsColumns_MPIBAIJ, 2632 /*49*/ 0, 2633 0, 2634 0, 2635 0, 2636 0, 2637 /*54*/ MatFDColoringCreate_MPIXAIJ, 2638 0, 2639 MatSetUnfactored_MPIBAIJ, 2640 MatPermute_MPIBAIJ, 2641 MatSetValuesBlocked_MPIBAIJ, 2642 /*59*/ MatGetSubMatrix_MPIBAIJ, 2643 MatDestroy_MPIBAIJ, 2644 MatView_MPIBAIJ, 2645 0, 2646 0, 2647 /*64*/ 0, 2648 0, 2649 0, 2650 0, 2651 0, 2652 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2653 0, 2654 0, 2655 0, 2656 0, 2657 /*74*/ 0, 2658 MatFDColoringApply_BAIJ, 2659 0, 2660 0, 2661 0, 2662 /*79*/ 0, 2663 0, 2664 0, 2665 0, 2666 MatLoad_MPIBAIJ, 2667 /*84*/ 0, 2668 0, 2669 0, 2670 0, 2671 0, 2672 /*89*/ 0, 2673 0, 2674 0, 2675 0, 2676 0, 2677 /*94*/ 0, 2678 0, 2679 0, 2680 0, 2681 0, 2682 /*99*/ 0, 2683 0, 2684 0, 2685 0, 2686 0, 2687 /*104*/0, 2688 MatRealPart_MPIBAIJ, 2689 MatImaginaryPart_MPIBAIJ, 2690 0, 2691 0, 2692 /*109*/0, 2693 0, 2694 0, 2695 0, 2696 0, 2697 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2698 0, 2699 MatGetGhosts_MPIBAIJ, 2700 0, 2701 0, 2702 /*119*/0, 2703 0, 2704 0, 2705 0, 2706 MatGetMultiProcBlock_MPIBAIJ, 2707 /*124*/0, 2708 MatGetColumnNorms_MPIBAIJ, 2709 MatInvertBlockDiagonal_MPIBAIJ, 2710 0, 2711 0, 2712 /*129*/ 0, 2713 0, 2714 0, 2715 0, 2716 0, 2717 /*134*/ 0, 2718 0, 2719 0, 2720 0, 2721 0, 2722 /*139*/ 0, 2723 0, 2724 0, 2725 MatFDColoringSetUp_MPIXAIJ 2726 }; 2727 2728 #undef __FUNCT__ 2729 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2730 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2731 { 2732 PetscFunctionBegin; 2733 *a = ((Mat_MPIBAIJ*)A->data)->A; 2734 PetscFunctionReturn(0); 2735 } 2736 2737 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2738 2739 #undef __FUNCT__ 2740 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2741 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2742 { 2743 PetscInt m,rstart,cstart,cend; 2744 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2745 const PetscInt *JJ =0; 2746 PetscScalar *values=0; 2747 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2748 PetscErrorCode ierr; 2749 2750 PetscFunctionBegin; 2751 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2752 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2753 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2754 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2755 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2756 m = B->rmap->n/bs; 2757 rstart = B->rmap->rstart/bs; 2758 cstart = B->cmap->rstart/bs; 2759 cend = B->cmap->rend/bs; 2760 2761 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2762 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2763 for (i=0; i<m; i++) { 2764 nz = ii[i+1] - ii[i]; 2765 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2766 nz_max = PetscMax(nz_max,nz); 2767 JJ = jj + ii[i]; 2768 for (j=0; j<nz; j++) { 2769 if (*JJ >= cstart) break; 2770 JJ++; 2771 } 2772 d = 0; 2773 for (; j<nz; j++) { 2774 if (*JJ++ >= cend) break; 2775 d++; 2776 } 2777 d_nnz[i] = d; 2778 o_nnz[i] = nz - d; 2779 } 2780 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2781 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2782 2783 values = (PetscScalar*)V; 2784 if (!values) { 2785 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2786 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2787 } 2788 for (i=0; i<m; i++) { 2789 PetscInt row = i + rstart; 2790 PetscInt ncols = ii[i+1] - ii[i]; 2791 const PetscInt *icols = jj + ii[i]; 2792 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2793 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2794 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2795 } else { /* block ordering does not match so we can only insert one block at a time. */ 2796 PetscInt j; 2797 for (j=0; j<ncols; j++) { 2798 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2799 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2800 } 2801 } 2802 } 2803 2804 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2805 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2806 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2807 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2808 PetscFunctionReturn(0); 2809 } 2810 2811 #undef __FUNCT__ 2812 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2813 /*@C 2814 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2815 (the default parallel PETSc format). 2816 2817 Collective on MPI_Comm 2818 2819 Input Parameters: 2820 + B - the matrix 2821 . bs - the block size 2822 . i - the indices into j for the start of each local row (starts with zero) 2823 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2824 - v - optional values in the matrix 2825 2826 Level: developer 2827 2828 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2829 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2830 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2831 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2832 block column and the second index is over columns within a block. 2833 2834 .keywords: matrix, aij, compressed row, sparse, parallel 2835 2836 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2837 @*/ 2838 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2839 { 2840 PetscErrorCode ierr; 2841 2842 PetscFunctionBegin; 2843 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2844 PetscValidType(B,1); 2845 PetscValidLogicalCollectiveInt(B,bs,2); 2846 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2847 PetscFunctionReturn(0); 2848 } 2849 2850 #undef __FUNCT__ 2851 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2852 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2853 { 2854 Mat_MPIBAIJ *b; 2855 PetscErrorCode ierr; 2856 PetscInt i; 2857 2858 PetscFunctionBegin; 2859 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2860 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2861 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2862 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2863 2864 if (d_nnz) { 2865 for (i=0; i<B->rmap->n/bs; i++) { 2866 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]); 2867 } 2868 } 2869 if (o_nnz) { 2870 for (i=0; i<B->rmap->n/bs; i++) { 2871 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]); 2872 } 2873 } 2874 2875 b = (Mat_MPIBAIJ*)B->data; 2876 b->bs2 = bs*bs; 2877 b->mbs = B->rmap->n/bs; 2878 b->nbs = B->cmap->n/bs; 2879 b->Mbs = B->rmap->N/bs; 2880 b->Nbs = B->cmap->N/bs; 2881 2882 for (i=0; i<=b->size; i++) { 2883 b->rangebs[i] = B->rmap->range[i]/bs; 2884 } 2885 b->rstartbs = B->rmap->rstart/bs; 2886 b->rendbs = B->rmap->rend/bs; 2887 b->cstartbs = B->cmap->rstart/bs; 2888 b->cendbs = B->cmap->rend/bs; 2889 2890 if (!B->preallocated) { 2891 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2892 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2893 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2894 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2895 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2896 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2897 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2898 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2899 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2900 } 2901 2902 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2903 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2904 B->preallocated = PETSC_TRUE; 2905 PetscFunctionReturn(0); 2906 } 2907 2908 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2909 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2910 2911 #undef __FUNCT__ 2912 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2913 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2914 { 2915 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2916 PetscErrorCode ierr; 2917 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2918 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2919 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2920 2921 PetscFunctionBegin; 2922 ierr = PetscMalloc1((M+1),&ii);CHKERRQ(ierr); 2923 ii[0] = 0; 2924 for (i=0; i<M; i++) { 2925 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]); 2926 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]); 2927 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2928 /* remove one from count of matrix has diagonal */ 2929 for (j=id[i]; j<id[i+1]; j++) { 2930 if (jd[j] == i) {ii[i+1]--;break;} 2931 } 2932 } 2933 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2934 cnt = 0; 2935 for (i=0; i<M; i++) { 2936 for (j=io[i]; j<io[i+1]; j++) { 2937 if (garray[jo[j]] > rstart) break; 2938 jj[cnt++] = garray[jo[j]]; 2939 } 2940 for (k=id[i]; k<id[i+1]; k++) { 2941 if (jd[k] != i) { 2942 jj[cnt++] = rstart + jd[k]; 2943 } 2944 } 2945 for (; j<io[i+1]; j++) { 2946 jj[cnt++] = garray[jo[j]]; 2947 } 2948 } 2949 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2950 PetscFunctionReturn(0); 2951 } 2952 2953 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2954 2955 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2956 2957 #undef __FUNCT__ 2958 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2959 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2960 { 2961 PetscErrorCode ierr; 2962 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2963 Mat B; 2964 Mat_MPIAIJ *b; 2965 2966 PetscFunctionBegin; 2967 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2968 2969 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2970 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2971 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2972 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2973 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2974 b = (Mat_MPIAIJ*) B->data; 2975 2976 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2977 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2978 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2979 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2980 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2981 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2982 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2983 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2984 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2985 if (reuse == MAT_REUSE_MATRIX) { 2986 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2987 } else { 2988 *newmat = B; 2989 } 2990 PetscFunctionReturn(0); 2991 } 2992 2993 #if defined(PETSC_HAVE_MUMPS) 2994 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2995 #endif 2996 2997 /*MC 2998 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2999 3000 Options Database Keys: 3001 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3002 . -mat_block_size <bs> - set the blocksize used to store the matrix 3003 - -mat_use_hash_table <fact> 3004 3005 Level: beginner 3006 3007 .seealso: MatCreateMPIBAIJ 3008 M*/ 3009 3010 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3011 3012 #undef __FUNCT__ 3013 #define __FUNCT__ "MatCreate_MPIBAIJ" 3014 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3015 { 3016 Mat_MPIBAIJ *b; 3017 PetscErrorCode ierr; 3018 PetscBool flg; 3019 3020 PetscFunctionBegin; 3021 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3022 B->data = (void*)b; 3023 3024 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3025 B->assembled = PETSC_FALSE; 3026 3027 B->insertmode = NOT_SET_VALUES; 3028 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3029 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3030 3031 /* build local table of row and column ownerships */ 3032 ierr = PetscMalloc1((b->size+1),&b->rangebs);CHKERRQ(ierr); 3033 3034 /* build cache for off array entries formed */ 3035 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3036 3037 b->donotstash = PETSC_FALSE; 3038 b->colmap = NULL; 3039 b->garray = NULL; 3040 b->roworiented = PETSC_TRUE; 3041 3042 /* stuff used in block assembly */ 3043 b->barray = 0; 3044 3045 /* stuff used for matrix vector multiply */ 3046 b->lvec = 0; 3047 b->Mvctx = 0; 3048 3049 /* stuff for MatGetRow() */ 3050 b->rowindices = 0; 3051 b->rowvalues = 0; 3052 b->getrowactive = PETSC_FALSE; 3053 3054 /* hash table stuff */ 3055 b->ht = 0; 3056 b->hd = 0; 3057 b->ht_size = 0; 3058 b->ht_flag = PETSC_FALSE; 3059 b->ht_fact = 0; 3060 b->ht_total_ct = 0; 3061 b->ht_insert_ct = 0; 3062 3063 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3064 b->ijonly = PETSC_FALSE; 3065 3066 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3067 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3068 if (flg) { 3069 PetscReal fact = 1.39; 3070 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3071 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3072 if (fact <= 1.0) fact = 1.39; 3073 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3074 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3075 } 3076 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3077 3078 #if defined(PETSC_HAVE_MUMPS) 3079 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3080 #endif 3081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3084 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3086 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3087 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3088 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3089 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3090 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3091 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3092 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3093 PetscFunctionReturn(0); 3094 } 3095 3096 /*MC 3097 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3098 3099 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3100 and MATMPIBAIJ otherwise. 3101 3102 Options Database Keys: 3103 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3104 3105 Level: beginner 3106 3107 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3108 M*/ 3109 3110 #undef __FUNCT__ 3111 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3112 /*@C 3113 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3114 (block compressed row). For good matrix assembly performance 3115 the user should preallocate the matrix storage by setting the parameters 3116 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3117 performance can be increased by more than a factor of 50. 3118 3119 Collective on Mat 3120 3121 Input Parameters: 3122 + B - the matrix 3123 . bs - size of block 3124 . d_nz - number of block nonzeros per block row in diagonal portion of local 3125 submatrix (same for all local rows) 3126 . d_nnz - array containing the number of block nonzeros in the various block rows 3127 of the in diagonal portion of the local (possibly different for each block 3128 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3129 set it even if it is zero. 3130 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3131 submatrix (same for all local rows). 3132 - o_nnz - array containing the number of nonzeros in the various block rows of the 3133 off-diagonal portion of the local submatrix (possibly different for 3134 each block row) or NULL. 3135 3136 If the *_nnz parameter is given then the *_nz parameter is ignored 3137 3138 Options Database Keys: 3139 + -mat_block_size - size of the blocks to use 3140 - -mat_use_hash_table <fact> 3141 3142 Notes: 3143 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3144 than it must be used on all processors that share the object for that argument. 3145 3146 Storage Information: 3147 For a square global matrix we define each processor's diagonal portion 3148 to be its local rows and the corresponding columns (a square submatrix); 3149 each processor's off-diagonal portion encompasses the remainder of the 3150 local matrix (a rectangular submatrix). 3151 3152 The user can specify preallocated storage for the diagonal part of 3153 the local submatrix with either d_nz or d_nnz (not both). Set 3154 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3155 memory allocation. Likewise, specify preallocated storage for the 3156 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3157 3158 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3159 the figure below we depict these three local rows and all columns (0-11). 3160 3161 .vb 3162 0 1 2 3 4 5 6 7 8 9 10 11 3163 -------------------------- 3164 row 3 |o o o d d d o o o o o o 3165 row 4 |o o o d d d o o o o o o 3166 row 5 |o o o d d d o o o o o o 3167 -------------------------- 3168 .ve 3169 3170 Thus, any entries in the d locations are stored in the d (diagonal) 3171 submatrix, and any entries in the o locations are stored in the 3172 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3173 stored simply in the MATSEQBAIJ format for compressed row storage. 3174 3175 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3176 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3177 In general, for PDE problems in which most nonzeros are near the diagonal, 3178 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3179 or you will get TERRIBLE performance; see the users' manual chapter on 3180 matrices. 3181 3182 You can call MatGetInfo() to get information on how effective the preallocation was; 3183 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3184 You can also run with the option -info and look for messages with the string 3185 malloc in them to see if additional memory allocation was needed. 3186 3187 Level: intermediate 3188 3189 .keywords: matrix, block, aij, compressed row, sparse, parallel 3190 3191 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3192 @*/ 3193 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3194 { 3195 PetscErrorCode ierr; 3196 3197 PetscFunctionBegin; 3198 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3199 PetscValidType(B,1); 3200 PetscValidLogicalCollectiveInt(B,bs,2); 3201 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); 3202 PetscFunctionReturn(0); 3203 } 3204 3205 #undef __FUNCT__ 3206 #define __FUNCT__ "MatCreateBAIJ" 3207 /*@C 3208 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3209 (block compressed row). For good matrix assembly performance 3210 the user should preallocate the matrix storage by setting the parameters 3211 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3212 performance can be increased by more than a factor of 50. 3213 3214 Collective on MPI_Comm 3215 3216 Input Parameters: 3217 + comm - MPI communicator 3218 . bs - size of blockk 3219 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3220 This value should be the same as the local size used in creating the 3221 y vector for the matrix-vector product y = Ax. 3222 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3223 This value should be the same as the local size used in creating the 3224 x vector for the matrix-vector product y = Ax. 3225 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3226 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3227 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3228 submatrix (same for all local rows) 3229 . d_nnz - array containing the number of nonzero blocks in the various block rows 3230 of the in diagonal portion of the local (possibly different for each block 3231 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3232 and set it even if it is zero. 3233 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3234 submatrix (same for all local rows). 3235 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3236 off-diagonal portion of the local submatrix (possibly different for 3237 each block row) or NULL. 3238 3239 Output Parameter: 3240 . A - the matrix 3241 3242 Options Database Keys: 3243 + -mat_block_size - size of the blocks to use 3244 - -mat_use_hash_table <fact> 3245 3246 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3247 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3248 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3249 3250 Notes: 3251 If the *_nnz parameter is given then the *_nz parameter is ignored 3252 3253 A nonzero block is any block that as 1 or more nonzeros in it 3254 3255 The user MUST specify either the local or global matrix dimensions 3256 (possibly both). 3257 3258 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3259 than it must be used on all processors that share the object for that argument. 3260 3261 Storage Information: 3262 For a square global matrix we define each processor's diagonal portion 3263 to be its local rows and the corresponding columns (a square submatrix); 3264 each processor's off-diagonal portion encompasses the remainder of the 3265 local matrix (a rectangular submatrix). 3266 3267 The user can specify preallocated storage for the diagonal part of 3268 the local submatrix with either d_nz or d_nnz (not both). Set 3269 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3270 memory allocation. Likewise, specify preallocated storage for the 3271 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3272 3273 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3274 the figure below we depict these three local rows and all columns (0-11). 3275 3276 .vb 3277 0 1 2 3 4 5 6 7 8 9 10 11 3278 -------------------------- 3279 row 3 |o o o d d d o o o o o o 3280 row 4 |o o o d d d o o o o o o 3281 row 5 |o o o d d d o o o o o o 3282 -------------------------- 3283 .ve 3284 3285 Thus, any entries in the d locations are stored in the d (diagonal) 3286 submatrix, and any entries in the o locations are stored in the 3287 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3288 stored simply in the MATSEQBAIJ format for compressed row storage. 3289 3290 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3291 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3292 In general, for PDE problems in which most nonzeros are near the diagonal, 3293 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3294 or you will get TERRIBLE performance; see the users' manual chapter on 3295 matrices. 3296 3297 Level: intermediate 3298 3299 .keywords: matrix, block, aij, compressed row, sparse, parallel 3300 3301 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3302 @*/ 3303 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) 3304 { 3305 PetscErrorCode ierr; 3306 PetscMPIInt size; 3307 3308 PetscFunctionBegin; 3309 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3310 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3311 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3312 if (size > 1) { 3313 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3314 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3315 } else { 3316 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3317 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3318 } 3319 PetscFunctionReturn(0); 3320 } 3321 3322 #undef __FUNCT__ 3323 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3324 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3325 { 3326 Mat mat; 3327 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3328 PetscErrorCode ierr; 3329 PetscInt len=0; 3330 3331 PetscFunctionBegin; 3332 *newmat = 0; 3333 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3334 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3335 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3336 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3337 3338 mat->factortype = matin->factortype; 3339 mat->preallocated = PETSC_TRUE; 3340 mat->assembled = PETSC_TRUE; 3341 mat->insertmode = NOT_SET_VALUES; 3342 3343 a = (Mat_MPIBAIJ*)mat->data; 3344 mat->rmap->bs = matin->rmap->bs; 3345 a->bs2 = oldmat->bs2; 3346 a->mbs = oldmat->mbs; 3347 a->nbs = oldmat->nbs; 3348 a->Mbs = oldmat->Mbs; 3349 a->Nbs = oldmat->Nbs; 3350 3351 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3352 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3353 3354 a->size = oldmat->size; 3355 a->rank = oldmat->rank; 3356 a->donotstash = oldmat->donotstash; 3357 a->roworiented = oldmat->roworiented; 3358 a->rowindices = 0; 3359 a->rowvalues = 0; 3360 a->getrowactive = PETSC_FALSE; 3361 a->barray = 0; 3362 a->rstartbs = oldmat->rstartbs; 3363 a->rendbs = oldmat->rendbs; 3364 a->cstartbs = oldmat->cstartbs; 3365 a->cendbs = oldmat->cendbs; 3366 3367 /* hash table stuff */ 3368 a->ht = 0; 3369 a->hd = 0; 3370 a->ht_size = 0; 3371 a->ht_flag = oldmat->ht_flag; 3372 a->ht_fact = oldmat->ht_fact; 3373 a->ht_total_ct = 0; 3374 a->ht_insert_ct = 0; 3375 3376 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3377 if (oldmat->colmap) { 3378 #if defined(PETSC_USE_CTABLE) 3379 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3380 #else 3381 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 3382 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3383 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3384 #endif 3385 } else a->colmap = 0; 3386 3387 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3388 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3389 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3390 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3391 } else a->garray = 0; 3392 3393 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3394 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3395 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3396 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3397 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3398 3399 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3400 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3401 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3402 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3403 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3404 *newmat = mat; 3405 PetscFunctionReturn(0); 3406 } 3407 3408 #undef __FUNCT__ 3409 #define __FUNCT__ "MatLoad_MPIBAIJ" 3410 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3411 { 3412 PetscErrorCode ierr; 3413 int fd; 3414 PetscInt i,nz,j,rstart,rend; 3415 PetscScalar *vals,*buf; 3416 MPI_Comm comm; 3417 MPI_Status status; 3418 PetscMPIInt rank,size,maxnz; 3419 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3420 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3421 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3422 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3423 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3424 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3425 3426 PetscFunctionBegin; 3427 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3428 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3429 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3430 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3431 3432 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3433 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3434 if (!rank) { 3435 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3436 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3437 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3438 } 3439 3440 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3441 3442 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3443 M = header[1]; N = header[2]; 3444 3445 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3446 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3447 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3448 3449 /* If global sizes are set, check if they are consistent with that given in the file */ 3450 if (sizesset) { 3451 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3452 } 3453 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); 3454 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); 3455 3456 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3457 3458 /* 3459 This code adds extra rows to make sure the number of rows is 3460 divisible by the blocksize 3461 */ 3462 Mbs = M/bs; 3463 extra_rows = bs - M + bs*Mbs; 3464 if (extra_rows == bs) extra_rows = 0; 3465 else Mbs++; 3466 if (extra_rows && !rank) { 3467 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3468 } 3469 3470 /* determine ownership of all rows */ 3471 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3472 mbs = Mbs/size + ((Mbs % size) > rank); 3473 m = mbs*bs; 3474 } else { /* User set */ 3475 m = newmat->rmap->n; 3476 mbs = m/bs; 3477 } 3478 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3479 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3480 3481 /* process 0 needs enough room for process with most rows */ 3482 if (!rank) { 3483 mmax = rowners[1]; 3484 for (i=2; i<=size; i++) { 3485 mmax = PetscMax(mmax,rowners[i]); 3486 } 3487 mmax*=bs; 3488 } else mmax = -1; /* unused, but compiler warns anyway */ 3489 3490 rowners[0] = 0; 3491 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3492 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3493 rstart = rowners[rank]; 3494 rend = rowners[rank+1]; 3495 3496 /* distribute row lengths to all processors */ 3497 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3498 if (!rank) { 3499 mend = m; 3500 if (size == 1) mend = mend - extra_rows; 3501 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3502 for (j=mend; j<m; j++) locrowlens[j] = 1; 3503 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3504 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3505 for (j=0; j<m; j++) { 3506 procsnz[0] += locrowlens[j]; 3507 } 3508 for (i=1; i<size; i++) { 3509 mend = browners[i+1] - browners[i]; 3510 if (i == size-1) mend = mend - extra_rows; 3511 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3512 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3513 /* calculate the number of nonzeros on each processor */ 3514 for (j=0; j<browners[i+1]-browners[i]; j++) { 3515 procsnz[i] += rowlengths[j]; 3516 } 3517 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3518 } 3519 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3520 } else { 3521 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3522 } 3523 3524 if (!rank) { 3525 /* determine max buffer needed and allocate it */ 3526 maxnz = procsnz[0]; 3527 for (i=1; i<size; i++) { 3528 maxnz = PetscMax(maxnz,procsnz[i]); 3529 } 3530 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3531 3532 /* read in my part of the matrix column indices */ 3533 nz = procsnz[0]; 3534 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3535 mycols = ibuf; 3536 if (size == 1) nz -= extra_rows; 3537 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3538 if (size == 1) { 3539 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3540 } 3541 3542 /* read in every ones (except the last) and ship off */ 3543 for (i=1; i<size-1; i++) { 3544 nz = procsnz[i]; 3545 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3546 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3547 } 3548 /* read in the stuff for the last proc */ 3549 if (size != 1) { 3550 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3551 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3552 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3553 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3554 } 3555 ierr = PetscFree(cols);CHKERRQ(ierr); 3556 } else { 3557 /* determine buffer space needed for message */ 3558 nz = 0; 3559 for (i=0; i<m; i++) { 3560 nz += locrowlens[i]; 3561 } 3562 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3563 mycols = ibuf; 3564 /* receive message of column indices*/ 3565 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3566 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3567 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3568 } 3569 3570 /* loop over local rows, determining number of off diagonal entries */ 3571 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3572 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3573 rowcount = 0; nzcount = 0; 3574 for (i=0; i<mbs; i++) { 3575 dcount = 0; 3576 odcount = 0; 3577 for (j=0; j<bs; j++) { 3578 kmax = locrowlens[rowcount]; 3579 for (k=0; k<kmax; k++) { 3580 tmp = mycols[nzcount++]/bs; 3581 if (!mask[tmp]) { 3582 mask[tmp] = 1; 3583 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3584 else masked1[dcount++] = tmp; 3585 } 3586 } 3587 rowcount++; 3588 } 3589 3590 dlens[i] = dcount; 3591 odlens[i] = odcount; 3592 3593 /* zero out the mask elements we set */ 3594 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3595 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3596 } 3597 3598 3599 if (!sizesset) { 3600 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3601 } 3602 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3603 3604 if (!rank) { 3605 ierr = PetscMalloc1((maxnz+1),&buf);CHKERRQ(ierr); 3606 /* read in my part of the matrix numerical values */ 3607 nz = procsnz[0]; 3608 vals = buf; 3609 mycols = ibuf; 3610 if (size == 1) nz -= extra_rows; 3611 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3612 if (size == 1) { 3613 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3614 } 3615 3616 /* insert into matrix */ 3617 jj = rstart*bs; 3618 for (i=0; i<m; i++) { 3619 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3620 mycols += locrowlens[i]; 3621 vals += locrowlens[i]; 3622 jj++; 3623 } 3624 /* read in other processors (except the last one) and ship out */ 3625 for (i=1; i<size-1; i++) { 3626 nz = procsnz[i]; 3627 vals = buf; 3628 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3629 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3630 } 3631 /* the last proc */ 3632 if (size != 1) { 3633 nz = procsnz[i] - extra_rows; 3634 vals = buf; 3635 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3636 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3637 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3638 } 3639 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3640 } else { 3641 /* receive numeric values */ 3642 ierr = PetscMalloc1((nz+1),&buf);CHKERRQ(ierr); 3643 3644 /* receive message of values*/ 3645 vals = buf; 3646 mycols = ibuf; 3647 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3648 3649 /* insert into matrix */ 3650 jj = rstart*bs; 3651 for (i=0; i<m; i++) { 3652 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3653 mycols += locrowlens[i]; 3654 vals += locrowlens[i]; 3655 jj++; 3656 } 3657 } 3658 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3659 ierr = PetscFree(buf);CHKERRQ(ierr); 3660 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3661 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3662 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3663 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3664 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3665 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3666 PetscFunctionReturn(0); 3667 } 3668 3669 #undef __FUNCT__ 3670 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3671 /*@ 3672 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3673 3674 Input Parameters: 3675 . mat - the matrix 3676 . fact - factor 3677 3678 Not Collective, each process can use a different factor 3679 3680 Level: advanced 3681 3682 Notes: 3683 This can also be set by the command line option: -mat_use_hash_table <fact> 3684 3685 .keywords: matrix, hashtable, factor, HT 3686 3687 .seealso: MatSetOption() 3688 @*/ 3689 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3690 { 3691 PetscErrorCode ierr; 3692 3693 PetscFunctionBegin; 3694 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3695 PetscFunctionReturn(0); 3696 } 3697 3698 #undef __FUNCT__ 3699 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3700 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3701 { 3702 Mat_MPIBAIJ *baij; 3703 3704 PetscFunctionBegin; 3705 baij = (Mat_MPIBAIJ*)mat->data; 3706 baij->ht_fact = fact; 3707 PetscFunctionReturn(0); 3708 } 3709 3710 #undef __FUNCT__ 3711 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3712 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3713 { 3714 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3715 3716 PetscFunctionBegin; 3717 if (Ad) *Ad = a->A; 3718 if (Ao) *Ao = a->B; 3719 if (colmap) *colmap = a->garray; 3720 PetscFunctionReturn(0); 3721 } 3722 3723 /* 3724 Special version for direct calls from Fortran (to eliminate two function call overheads 3725 */ 3726 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3727 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3728 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3729 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3730 #endif 3731 3732 #undef __FUNCT__ 3733 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3734 /*@C 3735 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3736 3737 Collective on Mat 3738 3739 Input Parameters: 3740 + mat - the matrix 3741 . min - number of input rows 3742 . im - input rows 3743 . nin - number of input columns 3744 . in - input columns 3745 . v - numerical values input 3746 - addvin - INSERT_VALUES or ADD_VALUES 3747 3748 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3749 3750 Level: advanced 3751 3752 .seealso: MatSetValuesBlocked() 3753 @*/ 3754 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3755 { 3756 /* convert input arguments to C version */ 3757 Mat mat = *matin; 3758 PetscInt m = *min, n = *nin; 3759 InsertMode addv = *addvin; 3760 3761 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3762 const MatScalar *value; 3763 MatScalar *barray = baij->barray; 3764 PetscBool roworiented = baij->roworiented; 3765 PetscErrorCode ierr; 3766 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3767 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3768 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3769 3770 PetscFunctionBegin; 3771 /* tasks normally handled by MatSetValuesBlocked() */ 3772 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3773 #if defined(PETSC_USE_DEBUG) 3774 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3775 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3776 #endif 3777 if (mat->assembled) { 3778 mat->was_assembled = PETSC_TRUE; 3779 mat->assembled = PETSC_FALSE; 3780 } 3781 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3782 3783 3784 if (!barray) { 3785 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3786 baij->barray = barray; 3787 } 3788 3789 if (roworiented) stepval = (n-1)*bs; 3790 else stepval = (m-1)*bs; 3791 3792 for (i=0; i<m; i++) { 3793 if (im[i] < 0) continue; 3794 #if defined(PETSC_USE_DEBUG) 3795 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); 3796 #endif 3797 if (im[i] >= rstart && im[i] < rend) { 3798 row = im[i] - rstart; 3799 for (j=0; j<n; j++) { 3800 /* If NumCol = 1 then a copy is not required */ 3801 if ((roworiented) && (n == 1)) { 3802 barray = (MatScalar*)v + i*bs2; 3803 } else if ((!roworiented) && (m == 1)) { 3804 barray = (MatScalar*)v + j*bs2; 3805 } else { /* Here a copy is required */ 3806 if (roworiented) { 3807 value = v + i*(stepval+bs)*bs + j*bs; 3808 } else { 3809 value = v + j*(stepval+bs)*bs + i*bs; 3810 } 3811 for (ii=0; ii<bs; ii++,value+=stepval) { 3812 for (jj=0; jj<bs; jj++) { 3813 *barray++ = *value++; 3814 } 3815 } 3816 barray -=bs2; 3817 } 3818 3819 if (in[j] >= cstart && in[j] < cend) { 3820 col = in[j] - cstart; 3821 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3822 } else if (in[j] < 0) continue; 3823 #if defined(PETSC_USE_DEBUG) 3824 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); 3825 #endif 3826 else { 3827 if (mat->was_assembled) { 3828 if (!baij->colmap) { 3829 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3830 } 3831 3832 #if defined(PETSC_USE_DEBUG) 3833 #if defined(PETSC_USE_CTABLE) 3834 { PetscInt data; 3835 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3836 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3837 } 3838 #else 3839 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3840 #endif 3841 #endif 3842 #if defined(PETSC_USE_CTABLE) 3843 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3844 col = (col - 1)/bs; 3845 #else 3846 col = (baij->colmap[in[j]] - 1)/bs; 3847 #endif 3848 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3849 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3850 col = in[j]; 3851 } 3852 } else col = in[j]; 3853 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3854 } 3855 } 3856 } else { 3857 if (!baij->donotstash) { 3858 if (roworiented) { 3859 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3860 } else { 3861 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3862 } 3863 } 3864 } 3865 } 3866 3867 /* task normally handled by MatSetValuesBlocked() */ 3868 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3869 PetscFunctionReturn(0); 3870 } 3871 3872 #undef __FUNCT__ 3873 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3874 /*@ 3875 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3876 CSR format the local rows. 3877 3878 Collective on MPI_Comm 3879 3880 Input Parameters: 3881 + comm - MPI communicator 3882 . bs - the block size, only a block size of 1 is supported 3883 . m - number of local rows (Cannot be PETSC_DECIDE) 3884 . n - This value should be the same as the local size used in creating the 3885 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3886 calculated if N is given) For square matrices n is almost always m. 3887 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3888 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3889 . i - row indices 3890 . j - column indices 3891 - a - matrix values 3892 3893 Output Parameter: 3894 . mat - the matrix 3895 3896 Level: intermediate 3897 3898 Notes: 3899 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3900 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3901 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3902 3903 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3904 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3905 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3906 with column-major ordering within blocks. 3907 3908 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3909 3910 .keywords: matrix, aij, compressed row, sparse, parallel 3911 3912 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3913 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3914 @*/ 3915 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) 3916 { 3917 PetscErrorCode ierr; 3918 3919 PetscFunctionBegin; 3920 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3921 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3922 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3923 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3924 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3925 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3926 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3927 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3928 PetscFunctionReturn(0); 3929 } 3930