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 const char *matname; 993 994 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 995 /* Perhaps this should be the type of mat? */ 996 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 997 if (!rank) { 998 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 999 } else { 1000 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1001 } 1002 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1003 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1004 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1005 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1006 1007 /* copy over the A part */ 1008 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1009 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1010 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1011 1012 for (i=0; i<mbs; i++) { 1013 rvals[0] = bs*(baij->rstartbs + i); 1014 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1015 for (j=ai[i]; j<ai[i+1]; j++) { 1016 col = (baij->cstartbs+aj[j])*bs; 1017 for (k=0; k<bs; k++) { 1018 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1019 col++; a += bs; 1020 } 1021 } 1022 } 1023 /* copy over the B part */ 1024 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1025 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1026 for (i=0; i<mbs; i++) { 1027 rvals[0] = bs*(baij->rstartbs + i); 1028 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1029 for (j=ai[i]; j<ai[i+1]; j++) { 1030 col = baij->garray[aj[j]]*bs; 1031 for (k=0; k<bs; k++) { 1032 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1033 col++; a += bs; 1034 } 1035 } 1036 } 1037 ierr = PetscFree(rvals);CHKERRQ(ierr); 1038 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1039 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1040 /* 1041 Everyone has to call to draw the matrix since the graphics waits are 1042 synchronized across all processors that share the PetscDraw object 1043 */ 1044 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1045 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 1046 if (!rank) { 1047 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 1048 ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1049 } 1050 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1051 ierr = MatDestroy(&A);CHKERRQ(ierr); 1052 } 1053 PetscFunctionReturn(0); 1054 } 1055 1056 #undef __FUNCT__ 1057 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1058 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1059 { 1060 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1061 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1062 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1063 PetscErrorCode ierr; 1064 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1065 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1066 int fd; 1067 PetscScalar *column_values; 1068 FILE *file; 1069 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1070 PetscInt message_count,flowcontrolcount; 1071 1072 PetscFunctionBegin; 1073 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1074 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1075 nz = bs2*(A->nz + B->nz); 1076 rlen = mat->rmap->n; 1077 if (!rank) { 1078 header[0] = MAT_FILE_CLASSID; 1079 header[1] = mat->rmap->N; 1080 header[2] = mat->cmap->N; 1081 1082 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1083 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1084 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1085 /* get largest number of rows any processor has */ 1086 range = mat->rmap->range; 1087 for (i=1; i<size; i++) { 1088 rlen = PetscMax(rlen,range[i+1] - range[i]); 1089 } 1090 } else { 1091 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1092 } 1093 1094 ierr = PetscMalloc1(rlen/bs,&crow_lens);CHKERRQ(ierr); 1095 /* compute lengths of each row */ 1096 for (i=0; i<a->mbs; i++) { 1097 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1098 } 1099 /* store the row lengths to the file */ 1100 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1101 if (!rank) { 1102 MPI_Status status; 1103 ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr); 1104 rlen = (range[1] - range[0])/bs; 1105 for (i=0; i<rlen; i++) { 1106 for (j=0; j<bs; j++) { 1107 row_lens[i*bs+j] = bs*crow_lens[i]; 1108 } 1109 } 1110 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1111 for (i=1; i<size; i++) { 1112 rlen = (range[i+1] - range[i])/bs; 1113 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1114 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1115 for (k=0; k<rlen; k++) { 1116 for (j=0; j<bs; j++) { 1117 row_lens[k*bs+j] = bs*crow_lens[k]; 1118 } 1119 } 1120 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1121 } 1122 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1123 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1124 } else { 1125 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1126 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1127 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1128 } 1129 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1130 1131 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1132 information needed to make it for each row from a block row. This does require more communication but still not more than 1133 the communication needed for the nonzero values */ 1134 nzmax = nz; /* space a largest processor needs */ 1135 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1136 ierr = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr); 1137 cnt = 0; 1138 for (i=0; i<a->mbs; i++) { 1139 pcnt = cnt; 1140 for (j=B->i[i]; j<B->i[i+1]; j++) { 1141 if ((col = garray[B->j[j]]) > cstart) break; 1142 for (l=0; l<bs; l++) { 1143 column_indices[cnt++] = bs*col+l; 1144 } 1145 } 1146 for (k=A->i[i]; k<A->i[i+1]; k++) { 1147 for (l=0; l<bs; l++) { 1148 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1149 } 1150 } 1151 for (; j<B->i[i+1]; j++) { 1152 for (l=0; l<bs; l++) { 1153 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1154 } 1155 } 1156 len = cnt - pcnt; 1157 for (k=1; k<bs; k++) { 1158 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1159 cnt += len; 1160 } 1161 } 1162 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1163 1164 /* store the columns to the file */ 1165 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1166 if (!rank) { 1167 MPI_Status status; 1168 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1169 for (i=1; i<size; i++) { 1170 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1171 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1172 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1173 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1174 } 1175 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1176 } else { 1177 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1178 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1179 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1180 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1181 } 1182 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1183 1184 /* load up the numerical values */ 1185 ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr); 1186 cnt = 0; 1187 for (i=0; i<a->mbs; i++) { 1188 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1189 for (j=B->i[i]; j<B->i[i+1]; j++) { 1190 if (garray[B->j[j]] > cstart) break; 1191 for (l=0; l<bs; l++) { 1192 for (ll=0; ll<bs; ll++) { 1193 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1194 } 1195 } 1196 cnt += bs; 1197 } 1198 for (k=A->i[i]; k<A->i[i+1]; k++) { 1199 for (l=0; l<bs; l++) { 1200 for (ll=0; ll<bs; ll++) { 1201 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1202 } 1203 } 1204 cnt += bs; 1205 } 1206 for (; j<B->i[i+1]; j++) { 1207 for (l=0; l<bs; l++) { 1208 for (ll=0; ll<bs; ll++) { 1209 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1210 } 1211 } 1212 cnt += bs; 1213 } 1214 cnt += (bs-1)*rlen; 1215 } 1216 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1217 1218 /* store the column values to the file */ 1219 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1220 if (!rank) { 1221 MPI_Status status; 1222 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1223 for (i=1; i<size; i++) { 1224 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1225 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1226 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1227 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1228 } 1229 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1230 } else { 1231 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1232 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1233 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1234 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1235 } 1236 ierr = PetscFree(column_values);CHKERRQ(ierr); 1237 1238 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1239 if (file) { 1240 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1241 } 1242 PetscFunctionReturn(0); 1243 } 1244 1245 #undef __FUNCT__ 1246 #define __FUNCT__ "MatView_MPIBAIJ" 1247 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1248 { 1249 PetscErrorCode ierr; 1250 PetscBool iascii,isdraw,issocket,isbinary; 1251 1252 PetscFunctionBegin; 1253 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1254 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1255 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1256 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1257 if (iascii || isdraw || issocket) { 1258 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1259 } else if (isbinary) { 1260 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1261 } 1262 PetscFunctionReturn(0); 1263 } 1264 1265 #undef __FUNCT__ 1266 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1267 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1268 { 1269 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1270 PetscErrorCode ierr; 1271 1272 PetscFunctionBegin; 1273 #if defined(PETSC_USE_LOG) 1274 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1275 #endif 1276 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1277 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1278 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1279 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1280 #if defined(PETSC_USE_CTABLE) 1281 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1282 #else 1283 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1284 #endif 1285 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1286 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1287 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1288 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1289 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1290 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1291 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1292 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1293 1294 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1295 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatMult_MPIBAIJ" 1309 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1310 { 1311 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1312 PetscErrorCode ierr; 1313 PetscInt nt; 1314 1315 PetscFunctionBegin; 1316 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1317 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1318 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1319 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1320 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1321 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1322 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1323 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1324 PetscFunctionReturn(0); 1325 } 1326 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1329 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1330 { 1331 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1332 PetscErrorCode ierr; 1333 1334 PetscFunctionBegin; 1335 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1336 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1337 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1338 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1339 PetscFunctionReturn(0); 1340 } 1341 1342 #undef __FUNCT__ 1343 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1344 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1345 { 1346 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1347 PetscErrorCode ierr; 1348 PetscBool merged; 1349 1350 PetscFunctionBegin; 1351 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1352 /* do nondiagonal part */ 1353 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1354 if (!merged) { 1355 /* send it on its way */ 1356 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1357 /* do local part */ 1358 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1359 /* receive remote parts: note this assumes the values are not actually */ 1360 /* inserted in yy until the next line */ 1361 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1362 } else { 1363 /* do local part */ 1364 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1365 /* send it on its way */ 1366 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1367 /* values actually were received in the Begin() but we need to call this nop */ 1368 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1369 } 1370 PetscFunctionReturn(0); 1371 } 1372 1373 #undef __FUNCT__ 1374 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1375 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1376 { 1377 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1378 PetscErrorCode ierr; 1379 1380 PetscFunctionBegin; 1381 /* do nondiagonal part */ 1382 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1383 /* send it on its way */ 1384 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1385 /* do local part */ 1386 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1387 /* receive remote parts: note this assumes the values are not actually */ 1388 /* inserted in yy until the next line, which is true for my implementation*/ 1389 /* but is not perhaps always true. */ 1390 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1391 PetscFunctionReturn(0); 1392 } 1393 1394 /* 1395 This only works correctly for square matrices where the subblock A->A is the 1396 diagonal block 1397 */ 1398 #undef __FUNCT__ 1399 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1400 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1401 { 1402 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1403 PetscErrorCode ierr; 1404 1405 PetscFunctionBegin; 1406 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1407 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1408 PetscFunctionReturn(0); 1409 } 1410 1411 #undef __FUNCT__ 1412 #define __FUNCT__ "MatScale_MPIBAIJ" 1413 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1414 { 1415 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1416 PetscErrorCode ierr; 1417 1418 PetscFunctionBegin; 1419 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1420 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1421 PetscFunctionReturn(0); 1422 } 1423 1424 #undef __FUNCT__ 1425 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1426 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1427 { 1428 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1429 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1430 PetscErrorCode ierr; 1431 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1432 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1433 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1434 1435 PetscFunctionBegin; 1436 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1437 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1438 mat->getrowactive = PETSC_TRUE; 1439 1440 if (!mat->rowvalues && (idx || v)) { 1441 /* 1442 allocate enough space to hold information from the longest row. 1443 */ 1444 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1445 PetscInt max = 1,mbs = mat->mbs,tmp; 1446 for (i=0; i<mbs; i++) { 1447 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1448 if (max < tmp) max = tmp; 1449 } 1450 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1451 } 1452 lrow = row - brstart; 1453 1454 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1455 if (!v) {pvA = 0; pvB = 0;} 1456 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1457 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1458 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1459 nztot = nzA + nzB; 1460 1461 cmap = mat->garray; 1462 if (v || idx) { 1463 if (nztot) { 1464 /* Sort by increasing column numbers, assuming A and B already sorted */ 1465 PetscInt imark = -1; 1466 if (v) { 1467 *v = v_p = mat->rowvalues; 1468 for (i=0; i<nzB; i++) { 1469 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1470 else break; 1471 } 1472 imark = i; 1473 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1474 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1475 } 1476 if (idx) { 1477 *idx = idx_p = mat->rowindices; 1478 if (imark > -1) { 1479 for (i=0; i<imark; i++) { 1480 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1481 } 1482 } else { 1483 for (i=0; i<nzB; i++) { 1484 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1485 else break; 1486 } 1487 imark = i; 1488 } 1489 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1490 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1491 } 1492 } else { 1493 if (idx) *idx = 0; 1494 if (v) *v = 0; 1495 } 1496 } 1497 *nz = nztot; 1498 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1499 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1500 PetscFunctionReturn(0); 1501 } 1502 1503 #undef __FUNCT__ 1504 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1505 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1506 { 1507 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1508 1509 PetscFunctionBegin; 1510 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1511 baij->getrowactive = PETSC_FALSE; 1512 PetscFunctionReturn(0); 1513 } 1514 1515 #undef __FUNCT__ 1516 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1517 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1518 { 1519 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1520 PetscErrorCode ierr; 1521 1522 PetscFunctionBegin; 1523 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1524 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1525 PetscFunctionReturn(0); 1526 } 1527 1528 #undef __FUNCT__ 1529 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1530 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1531 { 1532 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1533 Mat A = a->A,B = a->B; 1534 PetscErrorCode ierr; 1535 PetscReal isend[5],irecv[5]; 1536 1537 PetscFunctionBegin; 1538 info->block_size = (PetscReal)matin->rmap->bs; 1539 1540 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1541 1542 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1543 isend[3] = info->memory; isend[4] = info->mallocs; 1544 1545 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1546 1547 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1548 isend[3] += info->memory; isend[4] += info->mallocs; 1549 1550 if (flag == MAT_LOCAL) { 1551 info->nz_used = isend[0]; 1552 info->nz_allocated = isend[1]; 1553 info->nz_unneeded = isend[2]; 1554 info->memory = isend[3]; 1555 info->mallocs = isend[4]; 1556 } else if (flag == MAT_GLOBAL_MAX) { 1557 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1558 1559 info->nz_used = irecv[0]; 1560 info->nz_allocated = irecv[1]; 1561 info->nz_unneeded = irecv[2]; 1562 info->memory = irecv[3]; 1563 info->mallocs = irecv[4]; 1564 } else if (flag == MAT_GLOBAL_SUM) { 1565 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1566 1567 info->nz_used = irecv[0]; 1568 info->nz_allocated = irecv[1]; 1569 info->nz_unneeded = irecv[2]; 1570 info->memory = irecv[3]; 1571 info->mallocs = irecv[4]; 1572 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1573 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1574 info->fill_ratio_needed = 0; 1575 info->factor_mallocs = 0; 1576 PetscFunctionReturn(0); 1577 } 1578 1579 #undef __FUNCT__ 1580 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1581 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1582 { 1583 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1584 PetscErrorCode ierr; 1585 1586 PetscFunctionBegin; 1587 switch (op) { 1588 case MAT_NEW_NONZERO_LOCATIONS: 1589 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1590 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1591 case MAT_KEEP_NONZERO_PATTERN: 1592 case MAT_NEW_NONZERO_LOCATION_ERR: 1593 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1594 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1595 break; 1596 case MAT_ROW_ORIENTED: 1597 a->roworiented = flg; 1598 1599 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1600 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1601 break; 1602 case MAT_NEW_DIAGONALS: 1603 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1604 break; 1605 case MAT_IGNORE_OFF_PROC_ENTRIES: 1606 a->donotstash = flg; 1607 break; 1608 case MAT_USE_HASH_TABLE: 1609 a->ht_flag = flg; 1610 break; 1611 case MAT_SYMMETRIC: 1612 case MAT_STRUCTURALLY_SYMMETRIC: 1613 case MAT_HERMITIAN: 1614 case MAT_SYMMETRY_ETERNAL: 1615 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1616 break; 1617 default: 1618 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1619 } 1620 PetscFunctionReturn(0); 1621 } 1622 1623 #undef __FUNCT__ 1624 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1625 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1626 { 1627 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1628 Mat_SeqBAIJ *Aloc; 1629 Mat B; 1630 PetscErrorCode ierr; 1631 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1632 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1633 MatScalar *a; 1634 1635 PetscFunctionBegin; 1636 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1637 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1638 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1639 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1640 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1641 /* Do not know preallocation information, but must set block size */ 1642 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1643 } else { 1644 B = *matout; 1645 } 1646 1647 /* copy over the A part */ 1648 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1649 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1650 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1651 1652 for (i=0; i<mbs; i++) { 1653 rvals[0] = bs*(baij->rstartbs + i); 1654 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1655 for (j=ai[i]; j<ai[i+1]; j++) { 1656 col = (baij->cstartbs+aj[j])*bs; 1657 for (k=0; k<bs; k++) { 1658 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1659 1660 col++; a += bs; 1661 } 1662 } 1663 } 1664 /* copy over the B part */ 1665 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1666 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1667 for (i=0; i<mbs; i++) { 1668 rvals[0] = bs*(baij->rstartbs + i); 1669 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1670 for (j=ai[i]; j<ai[i+1]; j++) { 1671 col = baij->garray[aj[j]]*bs; 1672 for (k=0; k<bs; k++) { 1673 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1674 col++; 1675 a += bs; 1676 } 1677 } 1678 } 1679 ierr = PetscFree(rvals);CHKERRQ(ierr); 1680 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1681 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1682 1683 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1684 else { 1685 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1686 } 1687 PetscFunctionReturn(0); 1688 } 1689 1690 #undef __FUNCT__ 1691 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1692 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1693 { 1694 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1695 Mat a = baij->A,b = baij->B; 1696 PetscErrorCode ierr; 1697 PetscInt s1,s2,s3; 1698 1699 PetscFunctionBegin; 1700 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1701 if (rr) { 1702 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1703 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1704 /* Overlap communication with computation. */ 1705 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1706 } 1707 if (ll) { 1708 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1709 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1710 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1711 } 1712 /* scale the diagonal block */ 1713 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1714 1715 if (rr) { 1716 /* Do a scatter end and then right scale the off-diagonal block */ 1717 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1718 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1719 } 1720 PetscFunctionReturn(0); 1721 } 1722 1723 #undef __FUNCT__ 1724 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1725 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1726 { 1727 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1728 PetscInt *owners = A->rmap->range; 1729 PetscInt n = A->rmap->n; 1730 PetscSF sf; 1731 PetscInt *lrows; 1732 PetscSFNode *rrows; 1733 PetscInt r, p = 0, len = 0; 1734 PetscErrorCode ierr; 1735 1736 PetscFunctionBegin; 1737 /* Create SF where leaves are input rows and roots are owned rows */ 1738 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1739 for (r = 0; r < n; ++r) lrows[r] = -1; 1740 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 1741 for (r = 0; r < N; ++r) { 1742 const PetscInt idx = rows[r]; 1743 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 1744 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1745 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1746 } 1747 if (A->nooffproczerorows) { 1748 if (p != l->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,l->rank); 1749 lrows[len++] = idx - owners[p]; 1750 } else { 1751 rrows[r].rank = p; 1752 rrows[r].index = rows[r] - owners[p]; 1753 } 1754 } 1755 if (!A->nooffproczerorows) { 1756 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1757 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1758 /* Collect flags for rows to be zeroed */ 1759 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1760 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1761 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1762 /* Compress and put in row numbers */ 1763 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1764 } 1765 /* fix right hand side if needed */ 1766 if (x && b) { 1767 const PetscScalar *xx; 1768 PetscScalar *bb; 1769 1770 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1771 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1772 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1773 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1774 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1775 } 1776 1777 /* actually zap the local rows */ 1778 /* 1779 Zero the required rows. If the "diagonal block" of the matrix 1780 is square and the user wishes to set the diagonal we use separate 1781 code so that MatSetValues() is not called for each diagonal allocating 1782 new memory, thus calling lots of mallocs and slowing things down. 1783 1784 */ 1785 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1786 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1787 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1788 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1789 } else if (diag != 0.0) { 1790 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1791 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\ 1792 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1793 for (r = 0; r < len; ++r) { 1794 const PetscInt row = lrows[r] + A->rmap->rstart; 1795 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1796 } 1797 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1798 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1799 } else { 1800 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1801 } 1802 ierr = PetscFree(lrows);CHKERRQ(ierr); 1803 1804 /* only change matrix nonzero state if pattern was allowed to be changed */ 1805 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1806 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1807 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1808 } 1809 PetscFunctionReturn(0); 1810 } 1811 1812 #undef __FUNCT__ 1813 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1814 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1815 { 1816 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1817 PetscErrorCode ierr; 1818 PetscMPIInt n = A->rmap->n; 1819 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1820 PetscInt *lrows,*owners = A->rmap->range; 1821 PetscSFNode *rrows; 1822 PetscSF sf; 1823 const PetscScalar *xx; 1824 PetscScalar *bb,*mask; 1825 Vec xmask,lmask; 1826 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1827 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1828 PetscScalar *aa; 1829 1830 PetscFunctionBegin; 1831 /* Create SF where leaves are input rows and roots are owned rows */ 1832 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1833 for (r = 0; r < n; ++r) lrows[r] = -1; 1834 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1835 for (r = 0; r < N; ++r) { 1836 const PetscInt idx = rows[r]; 1837 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 1838 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1839 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1840 } 1841 rrows[r].rank = p; 1842 rrows[r].index = rows[r] - owners[p]; 1843 } 1844 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1845 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1846 /* Collect flags for rows to be zeroed */ 1847 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1848 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1849 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1850 /* Compress and put in row numbers */ 1851 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1852 /* zero diagonal part of matrix */ 1853 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1854 /* handle off diagonal part of matrix */ 1855 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 1856 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1857 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1858 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1859 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1860 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1861 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1862 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1863 if (x) { 1864 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1865 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1866 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1867 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1868 } 1869 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1870 /* remove zeroed rows of off diagonal matrix */ 1871 for (i = 0; i < len; ++i) { 1872 row = lrows[i]; 1873 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1874 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1875 for (k = 0; k < count; ++k) { 1876 aa[0] = 0.0; 1877 aa += bs; 1878 } 1879 } 1880 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1881 for (i = 0; i < l->B->rmap->N; ++i) { 1882 row = i/bs; 1883 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1884 for (k = 0; k < bs; ++k) { 1885 col = bs*baij->j[j] + k; 1886 if (PetscAbsScalar(mask[col])) { 1887 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1888 if (b) bb[i] -= aa[0]*xx[col]; 1889 aa[0] = 0.0; 1890 } 1891 } 1892 } 1893 } 1894 if (x) { 1895 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1896 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1897 } 1898 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1899 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1900 ierr = PetscFree(lrows);CHKERRQ(ierr); 1901 1902 /* only change matrix nonzero state if pattern was allowed to be changed */ 1903 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1904 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1905 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1906 } 1907 PetscFunctionReturn(0); 1908 } 1909 1910 #undef __FUNCT__ 1911 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1912 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1913 { 1914 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1915 PetscErrorCode ierr; 1916 1917 PetscFunctionBegin; 1918 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1919 PetscFunctionReturn(0); 1920 } 1921 1922 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1923 1924 #undef __FUNCT__ 1925 #define __FUNCT__ "MatEqual_MPIBAIJ" 1926 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1927 { 1928 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1929 Mat a,b,c,d; 1930 PetscBool flg; 1931 PetscErrorCode ierr; 1932 1933 PetscFunctionBegin; 1934 a = matA->A; b = matA->B; 1935 c = matB->A; d = matB->B; 1936 1937 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1938 if (flg) { 1939 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1940 } 1941 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1942 PetscFunctionReturn(0); 1943 } 1944 1945 #undef __FUNCT__ 1946 #define __FUNCT__ "MatCopy_MPIBAIJ" 1947 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1948 { 1949 PetscErrorCode ierr; 1950 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1951 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1952 1953 PetscFunctionBegin; 1954 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1955 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1956 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1957 } else { 1958 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1959 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1960 } 1961 PetscFunctionReturn(0); 1962 } 1963 1964 #undef __FUNCT__ 1965 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1966 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1967 { 1968 PetscErrorCode ierr; 1969 1970 PetscFunctionBegin; 1971 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1972 PetscFunctionReturn(0); 1973 } 1974 1975 #undef __FUNCT__ 1976 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 1977 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 1978 { 1979 PetscErrorCode ierr; 1980 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 1981 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 1982 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 1983 1984 PetscFunctionBegin; 1985 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 1986 PetscFunctionReturn(0); 1987 } 1988 1989 #undef __FUNCT__ 1990 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1991 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1992 { 1993 PetscErrorCode ierr; 1994 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 1995 PetscBLASInt bnz,one=1; 1996 Mat_SeqBAIJ *x,*y; 1997 1998 PetscFunctionBegin; 1999 if (str == SAME_NONZERO_PATTERN) { 2000 PetscScalar alpha = a; 2001 x = (Mat_SeqBAIJ*)xx->A->data; 2002 y = (Mat_SeqBAIJ*)yy->A->data; 2003 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2004 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2005 x = (Mat_SeqBAIJ*)xx->B->data; 2006 y = (Mat_SeqBAIJ*)yy->B->data; 2007 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2008 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2009 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2010 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2011 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2012 } else { 2013 Mat B; 2014 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2015 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2016 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2017 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2018 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2019 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2020 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2021 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2022 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2023 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2024 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2025 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2026 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2027 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2028 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2029 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2030 } 2031 PetscFunctionReturn(0); 2032 } 2033 2034 #undef __FUNCT__ 2035 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2036 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2037 { 2038 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2039 PetscErrorCode ierr; 2040 2041 PetscFunctionBegin; 2042 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2043 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2044 PetscFunctionReturn(0); 2045 } 2046 2047 #undef __FUNCT__ 2048 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2049 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2050 { 2051 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2052 PetscErrorCode ierr; 2053 2054 PetscFunctionBegin; 2055 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2056 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2057 PetscFunctionReturn(0); 2058 } 2059 2060 #undef __FUNCT__ 2061 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2062 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2063 { 2064 PetscErrorCode ierr; 2065 IS iscol_local; 2066 PetscInt csize; 2067 2068 PetscFunctionBegin; 2069 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2070 if (call == MAT_REUSE_MATRIX) { 2071 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2072 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2073 } else { 2074 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2075 } 2076 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2077 if (call == MAT_INITIAL_MATRIX) { 2078 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2079 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2080 } 2081 PetscFunctionReturn(0); 2082 } 2083 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2084 #undef __FUNCT__ 2085 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2086 /* 2087 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2088 in local and then by concatenating the local matrices the end result. 2089 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2090 */ 2091 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2092 { 2093 PetscErrorCode ierr; 2094 PetscMPIInt rank,size; 2095 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2096 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2097 Mat M,Mreuse; 2098 MatScalar *vwork,*aa; 2099 MPI_Comm comm; 2100 IS isrow_new, iscol_new; 2101 PetscBool idflag,allrows, allcols; 2102 Mat_SeqBAIJ *aij; 2103 2104 PetscFunctionBegin; 2105 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2106 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2107 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2108 /* The compression and expansion should be avoided. Doesn't point 2109 out errors, might change the indices, hence buggey */ 2110 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2111 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2112 2113 /* Check for special case: each processor gets entire matrix columns */ 2114 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2115 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2116 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2117 else allcols = PETSC_FALSE; 2118 2119 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2120 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2121 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2122 else allrows = PETSC_FALSE; 2123 2124 if (call == MAT_REUSE_MATRIX) { 2125 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2126 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2127 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2128 } else { 2129 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2130 } 2131 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2132 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2133 /* 2134 m - number of local rows 2135 n - number of columns (same on all processors) 2136 rstart - first row in new global matrix generated 2137 */ 2138 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2139 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2140 m = m/bs; 2141 n = n/bs; 2142 2143 if (call == MAT_INITIAL_MATRIX) { 2144 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2145 ii = aij->i; 2146 jj = aij->j; 2147 2148 /* 2149 Determine the number of non-zeros in the diagonal and off-diagonal 2150 portions of the matrix in order to do correct preallocation 2151 */ 2152 2153 /* first get start and end of "diagonal" columns */ 2154 if (csize == PETSC_DECIDE) { 2155 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2156 if (mglobal == n*bs) { /* square matrix */ 2157 nlocal = m; 2158 } else { 2159 nlocal = n/size + ((n % size) > rank); 2160 } 2161 } else { 2162 nlocal = csize/bs; 2163 } 2164 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2165 rstart = rend - nlocal; 2166 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); 2167 2168 /* next, compute all the lengths */ 2169 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2170 for (i=0; i<m; i++) { 2171 jend = ii[i+1] - ii[i]; 2172 olen = 0; 2173 dlen = 0; 2174 for (j=0; j<jend; j++) { 2175 if (*jj < rstart || *jj >= rend) olen++; 2176 else dlen++; 2177 jj++; 2178 } 2179 olens[i] = olen; 2180 dlens[i] = dlen; 2181 } 2182 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2183 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2184 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2185 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2186 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2187 } else { 2188 PetscInt ml,nl; 2189 2190 M = *newmat; 2191 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2192 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2193 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2194 /* 2195 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2196 rather than the slower MatSetValues(). 2197 */ 2198 M->was_assembled = PETSC_TRUE; 2199 M->assembled = PETSC_FALSE; 2200 } 2201 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2202 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2203 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2204 ii = aij->i; 2205 jj = aij->j; 2206 aa = aij->a; 2207 for (i=0; i<m; i++) { 2208 row = rstart/bs + i; 2209 nz = ii[i+1] - ii[i]; 2210 cwork = jj; jj += nz; 2211 vwork = aa; aa += nz*bs*bs; 2212 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2213 } 2214 2215 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2216 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2217 *newmat = M; 2218 2219 /* save submatrix used in processor for next request */ 2220 if (call == MAT_INITIAL_MATRIX) { 2221 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2222 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2223 } 2224 PetscFunctionReturn(0); 2225 } 2226 2227 #undef __FUNCT__ 2228 #define __FUNCT__ "MatPermute_MPIBAIJ" 2229 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2230 { 2231 MPI_Comm comm,pcomm; 2232 PetscInt clocal_size,nrows; 2233 const PetscInt *rows; 2234 PetscMPIInt size; 2235 IS crowp,lcolp; 2236 PetscErrorCode ierr; 2237 2238 PetscFunctionBegin; 2239 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2240 /* make a collective version of 'rowp' */ 2241 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2242 if (pcomm==comm) { 2243 crowp = rowp; 2244 } else { 2245 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2246 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2247 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2248 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2249 } 2250 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2251 /* make a local version of 'colp' */ 2252 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2253 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2254 if (size==1) { 2255 lcolp = colp; 2256 } else { 2257 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2258 } 2259 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2260 /* now we just get the submatrix */ 2261 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2262 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2263 /* clean up */ 2264 if (pcomm!=comm) { 2265 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2266 } 2267 if (size>1) { 2268 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2269 } 2270 PetscFunctionReturn(0); 2271 } 2272 2273 #undef __FUNCT__ 2274 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2275 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2276 { 2277 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2278 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2279 2280 PetscFunctionBegin; 2281 if (nghosts) *nghosts = B->nbs; 2282 if (ghosts) *ghosts = baij->garray; 2283 PetscFunctionReturn(0); 2284 } 2285 2286 #undef __FUNCT__ 2287 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2288 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2289 { 2290 Mat B; 2291 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2292 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2293 Mat_SeqAIJ *b; 2294 PetscErrorCode ierr; 2295 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2296 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2297 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2298 2299 PetscFunctionBegin; 2300 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2301 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2302 2303 /* ---------------------------------------------------------------- 2304 Tell every processor the number of nonzeros per row 2305 */ 2306 ierr = PetscMalloc1(A->rmap->N/bs,&lens);CHKERRQ(ierr); 2307 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2308 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]; 2309 } 2310 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2311 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2312 displs = recvcounts + size; 2313 for (i=0; i<size; i++) { 2314 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2315 displs[i] = A->rmap->range[i]/bs; 2316 } 2317 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2318 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2319 #else 2320 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2321 #endif 2322 /* --------------------------------------------------------------- 2323 Create the sequential matrix of the same type as the local block diagonal 2324 */ 2325 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2326 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2327 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2328 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2329 b = (Mat_SeqAIJ*)B->data; 2330 2331 /*-------------------------------------------------------------------- 2332 Copy my part of matrix column indices over 2333 */ 2334 sendcount = ad->nz + bd->nz; 2335 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2336 a_jsendbuf = ad->j; 2337 b_jsendbuf = bd->j; 2338 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2339 cnt = 0; 2340 for (i=0; i<n; i++) { 2341 2342 /* put in lower diagonal portion */ 2343 m = bd->i[i+1] - bd->i[i]; 2344 while (m > 0) { 2345 /* is it above diagonal (in bd (compressed) numbering) */ 2346 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2347 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2348 m--; 2349 } 2350 2351 /* put in diagonal portion */ 2352 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2353 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2354 } 2355 2356 /* put in upper diagonal portion */ 2357 while (m-- > 0) { 2358 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2359 } 2360 } 2361 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2362 2363 /*-------------------------------------------------------------------- 2364 Gather all column indices to all processors 2365 */ 2366 for (i=0; i<size; i++) { 2367 recvcounts[i] = 0; 2368 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2369 recvcounts[i] += lens[j]; 2370 } 2371 } 2372 displs[0] = 0; 2373 for (i=1; i<size; i++) { 2374 displs[i] = displs[i-1] + recvcounts[i-1]; 2375 } 2376 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2377 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2378 #else 2379 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2380 #endif 2381 /*-------------------------------------------------------------------- 2382 Assemble the matrix into useable form (note numerical values not yet set) 2383 */ 2384 /* set the b->ilen (length of each row) values */ 2385 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2386 /* set the b->i indices */ 2387 b->i[0] = 0; 2388 for (i=1; i<=A->rmap->N/bs; i++) { 2389 b->i[i] = b->i[i-1] + lens[i-1]; 2390 } 2391 ierr = PetscFree(lens);CHKERRQ(ierr); 2392 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2393 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2394 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2395 2396 if (A->symmetric) { 2397 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2398 } else if (A->hermitian) { 2399 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2400 } else if (A->structurally_symmetric) { 2401 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2402 } 2403 *newmat = B; 2404 PetscFunctionReturn(0); 2405 } 2406 2407 #undef __FUNCT__ 2408 #define __FUNCT__ "MatSOR_MPIBAIJ" 2409 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2410 { 2411 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2412 PetscErrorCode ierr; 2413 Vec bb1 = 0; 2414 2415 PetscFunctionBegin; 2416 if (flag == SOR_APPLY_UPPER) { 2417 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2418 PetscFunctionReturn(0); 2419 } 2420 2421 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2422 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2423 } 2424 2425 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2426 if (flag & SOR_ZERO_INITIAL_GUESS) { 2427 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2428 its--; 2429 } 2430 2431 while (its--) { 2432 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2433 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2434 2435 /* update rhs: bb1 = bb - B*x */ 2436 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2437 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2438 2439 /* local sweep */ 2440 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2441 } 2442 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2443 if (flag & SOR_ZERO_INITIAL_GUESS) { 2444 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2445 its--; 2446 } 2447 while (its--) { 2448 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2449 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2450 2451 /* update rhs: bb1 = bb - B*x */ 2452 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2453 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2454 2455 /* local sweep */ 2456 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2457 } 2458 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2459 if (flag & SOR_ZERO_INITIAL_GUESS) { 2460 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2461 its--; 2462 } 2463 while (its--) { 2464 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2465 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2466 2467 /* update rhs: bb1 = bb - B*x */ 2468 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2469 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2470 2471 /* local sweep */ 2472 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2473 } 2474 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2475 2476 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2477 PetscFunctionReturn(0); 2478 } 2479 2480 #undef __FUNCT__ 2481 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2482 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2483 { 2484 PetscErrorCode ierr; 2485 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2486 PetscInt N,i,*garray = aij->garray; 2487 PetscInt ib,jb,bs = A->rmap->bs; 2488 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2489 MatScalar *a_val = a_aij->a; 2490 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2491 MatScalar *b_val = b_aij->a; 2492 PetscReal *work; 2493 2494 PetscFunctionBegin; 2495 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2496 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2497 if (type == NORM_2) { 2498 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2499 for (jb=0; jb<bs; jb++) { 2500 for (ib=0; ib<bs; ib++) { 2501 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2502 a_val++; 2503 } 2504 } 2505 } 2506 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2507 for (jb=0; jb<bs; jb++) { 2508 for (ib=0; ib<bs; ib++) { 2509 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2510 b_val++; 2511 } 2512 } 2513 } 2514 } else if (type == NORM_1) { 2515 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2516 for (jb=0; jb<bs; jb++) { 2517 for (ib=0; ib<bs; ib++) { 2518 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2519 a_val++; 2520 } 2521 } 2522 } 2523 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2524 for (jb=0; jb<bs; jb++) { 2525 for (ib=0; ib<bs; ib++) { 2526 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2527 b_val++; 2528 } 2529 } 2530 } 2531 } else if (type == NORM_INFINITY) { 2532 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2533 for (jb=0; jb<bs; jb++) { 2534 for (ib=0; ib<bs; ib++) { 2535 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2536 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2537 a_val++; 2538 } 2539 } 2540 } 2541 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2542 for (jb=0; jb<bs; jb++) { 2543 for (ib=0; ib<bs; ib++) { 2544 int col = garray[b_aij->j[i]] * bs + jb; 2545 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2546 b_val++; 2547 } 2548 } 2549 } 2550 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2551 if (type == NORM_INFINITY) { 2552 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2553 } else { 2554 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2555 } 2556 ierr = PetscFree(work);CHKERRQ(ierr); 2557 if (type == NORM_2) { 2558 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2559 } 2560 PetscFunctionReturn(0); 2561 } 2562 2563 #undef __FUNCT__ 2564 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2565 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2566 { 2567 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2568 PetscErrorCode ierr; 2569 2570 PetscFunctionBegin; 2571 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2572 PetscFunctionReturn(0); 2573 } 2574 2575 2576 /* -------------------------------------------------------------------*/ 2577 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2578 MatGetRow_MPIBAIJ, 2579 MatRestoreRow_MPIBAIJ, 2580 MatMult_MPIBAIJ, 2581 /* 4*/ MatMultAdd_MPIBAIJ, 2582 MatMultTranspose_MPIBAIJ, 2583 MatMultTransposeAdd_MPIBAIJ, 2584 0, 2585 0, 2586 0, 2587 /*10*/ 0, 2588 0, 2589 0, 2590 MatSOR_MPIBAIJ, 2591 MatTranspose_MPIBAIJ, 2592 /*15*/ MatGetInfo_MPIBAIJ, 2593 MatEqual_MPIBAIJ, 2594 MatGetDiagonal_MPIBAIJ, 2595 MatDiagonalScale_MPIBAIJ, 2596 MatNorm_MPIBAIJ, 2597 /*20*/ MatAssemblyBegin_MPIBAIJ, 2598 MatAssemblyEnd_MPIBAIJ, 2599 MatSetOption_MPIBAIJ, 2600 MatZeroEntries_MPIBAIJ, 2601 /*24*/ MatZeroRows_MPIBAIJ, 2602 0, 2603 0, 2604 0, 2605 0, 2606 /*29*/ MatSetUp_MPIBAIJ, 2607 0, 2608 0, 2609 0, 2610 0, 2611 /*34*/ MatDuplicate_MPIBAIJ, 2612 0, 2613 0, 2614 0, 2615 0, 2616 /*39*/ MatAXPY_MPIBAIJ, 2617 MatGetSubMatrices_MPIBAIJ, 2618 MatIncreaseOverlap_MPIBAIJ, 2619 MatGetValues_MPIBAIJ, 2620 MatCopy_MPIBAIJ, 2621 /*44*/ 0, 2622 MatScale_MPIBAIJ, 2623 0, 2624 0, 2625 MatZeroRowsColumns_MPIBAIJ, 2626 /*49*/ 0, 2627 0, 2628 0, 2629 0, 2630 0, 2631 /*54*/ MatFDColoringCreate_MPIXAIJ, 2632 0, 2633 MatSetUnfactored_MPIBAIJ, 2634 MatPermute_MPIBAIJ, 2635 MatSetValuesBlocked_MPIBAIJ, 2636 /*59*/ MatGetSubMatrix_MPIBAIJ, 2637 MatDestroy_MPIBAIJ, 2638 MatView_MPIBAIJ, 2639 0, 2640 0, 2641 /*64*/ 0, 2642 0, 2643 0, 2644 0, 2645 0, 2646 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2647 0, 2648 0, 2649 0, 2650 0, 2651 /*74*/ 0, 2652 MatFDColoringApply_BAIJ, 2653 0, 2654 0, 2655 0, 2656 /*79*/ 0, 2657 0, 2658 0, 2659 0, 2660 MatLoad_MPIBAIJ, 2661 /*84*/ 0, 2662 0, 2663 0, 2664 0, 2665 0, 2666 /*89*/ 0, 2667 0, 2668 0, 2669 0, 2670 0, 2671 /*94*/ 0, 2672 0, 2673 0, 2674 0, 2675 0, 2676 /*99*/ 0, 2677 0, 2678 0, 2679 0, 2680 0, 2681 /*104*/0, 2682 MatRealPart_MPIBAIJ, 2683 MatImaginaryPart_MPIBAIJ, 2684 0, 2685 0, 2686 /*109*/0, 2687 0, 2688 0, 2689 0, 2690 0, 2691 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2692 0, 2693 MatGetGhosts_MPIBAIJ, 2694 0, 2695 0, 2696 /*119*/0, 2697 0, 2698 0, 2699 0, 2700 MatGetMultiProcBlock_MPIBAIJ, 2701 /*124*/0, 2702 MatGetColumnNorms_MPIBAIJ, 2703 MatInvertBlockDiagonal_MPIBAIJ, 2704 0, 2705 0, 2706 /*129*/ 0, 2707 0, 2708 0, 2709 0, 2710 0, 2711 /*134*/ 0, 2712 0, 2713 0, 2714 0, 2715 0, 2716 /*139*/ 0, 2717 0, 2718 0, 2719 MatFDColoringSetUp_MPIXAIJ, 2720 0, 2721 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ 2722 }; 2723 2724 #undef __FUNCT__ 2725 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2726 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2727 { 2728 PetscFunctionBegin; 2729 *a = ((Mat_MPIBAIJ*)A->data)->A; 2730 PetscFunctionReturn(0); 2731 } 2732 2733 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2734 2735 #undef __FUNCT__ 2736 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2737 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2738 { 2739 PetscInt m,rstart,cstart,cend; 2740 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2741 const PetscInt *JJ =0; 2742 PetscScalar *values=0; 2743 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2744 PetscErrorCode ierr; 2745 2746 PetscFunctionBegin; 2747 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2748 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2749 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2750 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2751 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2752 m = B->rmap->n/bs; 2753 rstart = B->rmap->rstart/bs; 2754 cstart = B->cmap->rstart/bs; 2755 cend = B->cmap->rend/bs; 2756 2757 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2758 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2759 for (i=0; i<m; i++) { 2760 nz = ii[i+1] - ii[i]; 2761 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2762 nz_max = PetscMax(nz_max,nz); 2763 JJ = jj + ii[i]; 2764 for (j=0; j<nz; j++) { 2765 if (*JJ >= cstart) break; 2766 JJ++; 2767 } 2768 d = 0; 2769 for (; j<nz; j++) { 2770 if (*JJ++ >= cend) break; 2771 d++; 2772 } 2773 d_nnz[i] = d; 2774 o_nnz[i] = nz - d; 2775 } 2776 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2777 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2778 2779 values = (PetscScalar*)V; 2780 if (!values) { 2781 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2782 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2783 } 2784 for (i=0; i<m; i++) { 2785 PetscInt row = i + rstart; 2786 PetscInt ncols = ii[i+1] - ii[i]; 2787 const PetscInt *icols = jj + ii[i]; 2788 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2789 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2790 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2791 } else { /* block ordering does not match so we can only insert one block at a time. */ 2792 PetscInt j; 2793 for (j=0; j<ncols; j++) { 2794 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2795 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2796 } 2797 } 2798 } 2799 2800 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2801 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2802 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2803 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2804 PetscFunctionReturn(0); 2805 } 2806 2807 #undef __FUNCT__ 2808 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2809 /*@C 2810 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2811 (the default parallel PETSc format). 2812 2813 Collective on MPI_Comm 2814 2815 Input Parameters: 2816 + B - the matrix 2817 . bs - the block size 2818 . i - the indices into j for the start of each local row (starts with zero) 2819 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2820 - v - optional values in the matrix 2821 2822 Level: developer 2823 2824 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2825 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2826 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2827 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2828 block column and the second index is over columns within a block. 2829 2830 .keywords: matrix, aij, compressed row, sparse, parallel 2831 2832 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2833 @*/ 2834 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2835 { 2836 PetscErrorCode ierr; 2837 2838 PetscFunctionBegin; 2839 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2840 PetscValidType(B,1); 2841 PetscValidLogicalCollectiveInt(B,bs,2); 2842 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2843 PetscFunctionReturn(0); 2844 } 2845 2846 #undef __FUNCT__ 2847 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2848 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2849 { 2850 Mat_MPIBAIJ *b; 2851 PetscErrorCode ierr; 2852 PetscInt i; 2853 2854 PetscFunctionBegin; 2855 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2856 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2857 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2858 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2859 2860 if (d_nnz) { 2861 for (i=0; i<B->rmap->n/bs; i++) { 2862 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]); 2863 } 2864 } 2865 if (o_nnz) { 2866 for (i=0; i<B->rmap->n/bs; i++) { 2867 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]); 2868 } 2869 } 2870 2871 b = (Mat_MPIBAIJ*)B->data; 2872 b->bs2 = bs*bs; 2873 b->mbs = B->rmap->n/bs; 2874 b->nbs = B->cmap->n/bs; 2875 b->Mbs = B->rmap->N/bs; 2876 b->Nbs = B->cmap->N/bs; 2877 2878 for (i=0; i<=b->size; i++) { 2879 b->rangebs[i] = B->rmap->range[i]/bs; 2880 } 2881 b->rstartbs = B->rmap->rstart/bs; 2882 b->rendbs = B->rmap->rend/bs; 2883 b->cstartbs = B->cmap->rstart/bs; 2884 b->cendbs = B->cmap->rend/bs; 2885 2886 if (!B->preallocated) { 2887 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2888 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2889 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2890 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2891 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2892 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2893 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2894 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2895 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2896 } 2897 2898 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2899 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2900 B->preallocated = PETSC_TRUE; 2901 PetscFunctionReturn(0); 2902 } 2903 2904 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2905 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2906 2907 #undef __FUNCT__ 2908 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2909 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2910 { 2911 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2912 PetscErrorCode ierr; 2913 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2914 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2915 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2916 2917 PetscFunctionBegin; 2918 ierr = PetscMalloc1(M+1,&ii);CHKERRQ(ierr); 2919 ii[0] = 0; 2920 for (i=0; i<M; i++) { 2921 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]); 2922 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]); 2923 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2924 /* remove one from count of matrix has diagonal */ 2925 for (j=id[i]; j<id[i+1]; j++) { 2926 if (jd[j] == i) {ii[i+1]--;break;} 2927 } 2928 } 2929 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2930 cnt = 0; 2931 for (i=0; i<M; i++) { 2932 for (j=io[i]; j<io[i+1]; j++) { 2933 if (garray[jo[j]] > rstart) break; 2934 jj[cnt++] = garray[jo[j]]; 2935 } 2936 for (k=id[i]; k<id[i+1]; k++) { 2937 if (jd[k] != i) { 2938 jj[cnt++] = rstart + jd[k]; 2939 } 2940 } 2941 for (; j<io[i+1]; j++) { 2942 jj[cnt++] = garray[jo[j]]; 2943 } 2944 } 2945 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2946 PetscFunctionReturn(0); 2947 } 2948 2949 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2950 2951 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2952 2953 #undef __FUNCT__ 2954 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2955 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2956 { 2957 PetscErrorCode ierr; 2958 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2959 Mat B; 2960 Mat_MPIAIJ *b; 2961 2962 PetscFunctionBegin; 2963 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2964 2965 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2966 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2967 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2968 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2969 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2970 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2971 b = (Mat_MPIAIJ*) B->data; 2972 2973 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2974 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2975 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2976 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2977 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2978 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2979 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2980 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2981 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2982 if (reuse == MAT_REUSE_MATRIX) { 2983 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2984 } else { 2985 *newmat = B; 2986 } 2987 PetscFunctionReturn(0); 2988 } 2989 2990 /*MC 2991 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2992 2993 Options Database Keys: 2994 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2995 . -mat_block_size <bs> - set the blocksize used to store the matrix 2996 - -mat_use_hash_table <fact> 2997 2998 Level: beginner 2999 3000 .seealso: MatCreateMPIBAIJ 3001 M*/ 3002 3003 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3004 3005 #undef __FUNCT__ 3006 #define __FUNCT__ "MatCreate_MPIBAIJ" 3007 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3008 { 3009 Mat_MPIBAIJ *b; 3010 PetscErrorCode ierr; 3011 PetscBool flg = PETSC_FALSE; 3012 3013 PetscFunctionBegin; 3014 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3015 B->data = (void*)b; 3016 3017 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3018 B->assembled = PETSC_FALSE; 3019 3020 B->insertmode = NOT_SET_VALUES; 3021 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3022 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3023 3024 /* build local table of row and column ownerships */ 3025 ierr = PetscMalloc1(b->size+1,&b->rangebs);CHKERRQ(ierr); 3026 3027 /* build cache for off array entries formed */ 3028 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3029 3030 b->donotstash = PETSC_FALSE; 3031 b->colmap = NULL; 3032 b->garray = NULL; 3033 b->roworiented = PETSC_TRUE; 3034 3035 /* stuff used in block assembly */ 3036 b->barray = 0; 3037 3038 /* stuff used for matrix vector multiply */ 3039 b->lvec = 0; 3040 b->Mvctx = 0; 3041 3042 /* stuff for MatGetRow() */ 3043 b->rowindices = 0; 3044 b->rowvalues = 0; 3045 b->getrowactive = PETSC_FALSE; 3046 3047 /* hash table stuff */ 3048 b->ht = 0; 3049 b->hd = 0; 3050 b->ht_size = 0; 3051 b->ht_flag = PETSC_FALSE; 3052 b->ht_fact = 0; 3053 b->ht_total_ct = 0; 3054 b->ht_insert_ct = 0; 3055 3056 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3057 b->ijonly = PETSC_FALSE; 3058 3059 3060 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3061 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3062 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3063 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3064 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3065 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3066 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3067 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3068 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3069 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3070 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3071 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3072 3073 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3074 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);CHKERRQ(ierr); 3075 if (flg) { 3076 PetscReal fact = 1.39; 3077 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3078 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3079 if (fact <= 1.0) fact = 1.39; 3080 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3081 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3082 } 3083 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3084 PetscFunctionReturn(0); 3085 } 3086 3087 /*MC 3088 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3089 3090 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3091 and MATMPIBAIJ otherwise. 3092 3093 Options Database Keys: 3094 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3095 3096 Level: beginner 3097 3098 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3099 M*/ 3100 3101 #undef __FUNCT__ 3102 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3103 /*@C 3104 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3105 (block compressed row). For good matrix assembly performance 3106 the user should preallocate the matrix storage by setting the parameters 3107 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3108 performance can be increased by more than a factor of 50. 3109 3110 Collective on Mat 3111 3112 Input Parameters: 3113 + B - the matrix 3114 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3115 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3116 . d_nz - number of block nonzeros per block row in diagonal portion of local 3117 submatrix (same for all local rows) 3118 . d_nnz - array containing the number of block nonzeros in the various block rows 3119 of the in diagonal portion of the local (possibly different for each block 3120 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3121 set it even if it is zero. 3122 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3123 submatrix (same for all local rows). 3124 - o_nnz - array containing the number of nonzeros in the various block rows of the 3125 off-diagonal portion of the local submatrix (possibly different for 3126 each block row) or NULL. 3127 3128 If the *_nnz parameter is given then the *_nz parameter is ignored 3129 3130 Options Database Keys: 3131 + -mat_block_size - size of the blocks to use 3132 - -mat_use_hash_table <fact> 3133 3134 Notes: 3135 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3136 than it must be used on all processors that share the object for that argument. 3137 3138 Storage Information: 3139 For a square global matrix we define each processor's diagonal portion 3140 to be its local rows and the corresponding columns (a square submatrix); 3141 each processor's off-diagonal portion encompasses the remainder of the 3142 local matrix (a rectangular submatrix). 3143 3144 The user can specify preallocated storage for the diagonal part of 3145 the local submatrix with either d_nz or d_nnz (not both). Set 3146 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3147 memory allocation. Likewise, specify preallocated storage for the 3148 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3149 3150 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3151 the figure below we depict these three local rows and all columns (0-11). 3152 3153 .vb 3154 0 1 2 3 4 5 6 7 8 9 10 11 3155 -------------------------- 3156 row 3 |o o o d d d o o o o o o 3157 row 4 |o o o d d d o o o o o o 3158 row 5 |o o o d d d o o o o o o 3159 -------------------------- 3160 .ve 3161 3162 Thus, any entries in the d locations are stored in the d (diagonal) 3163 submatrix, and any entries in the o locations are stored in the 3164 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3165 stored simply in the MATSEQBAIJ format for compressed row storage. 3166 3167 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3168 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3169 In general, for PDE problems in which most nonzeros are near the diagonal, 3170 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3171 or you will get TERRIBLE performance; see the users' manual chapter on 3172 matrices. 3173 3174 You can call MatGetInfo() to get information on how effective the preallocation was; 3175 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3176 You can also run with the option -info and look for messages with the string 3177 malloc in them to see if additional memory allocation was needed. 3178 3179 Level: intermediate 3180 3181 .keywords: matrix, block, aij, compressed row, sparse, parallel 3182 3183 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3184 @*/ 3185 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3186 { 3187 PetscErrorCode ierr; 3188 3189 PetscFunctionBegin; 3190 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3191 PetscValidType(B,1); 3192 PetscValidLogicalCollectiveInt(B,bs,2); 3193 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); 3194 PetscFunctionReturn(0); 3195 } 3196 3197 #undef __FUNCT__ 3198 #define __FUNCT__ "MatCreateBAIJ" 3199 /*@C 3200 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3201 (block compressed row). For good matrix assembly performance 3202 the user should preallocate the matrix storage by setting the parameters 3203 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3204 performance can be increased by more than a factor of 50. 3205 3206 Collective on MPI_Comm 3207 3208 Input Parameters: 3209 + comm - MPI communicator 3210 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3211 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3212 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3213 This value should be the same as the local size used in creating the 3214 y vector for the matrix-vector product y = Ax. 3215 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3216 This value should be the same as the local size used in creating the 3217 x vector for the matrix-vector product y = Ax. 3218 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3219 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3220 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3221 submatrix (same for all local rows) 3222 . d_nnz - array containing the number of nonzero blocks in the various block rows 3223 of the in diagonal portion of the local (possibly different for each block 3224 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3225 and set it even if it is zero. 3226 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3227 submatrix (same for all local rows). 3228 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3229 off-diagonal portion of the local submatrix (possibly different for 3230 each block row) or NULL. 3231 3232 Output Parameter: 3233 . A - the matrix 3234 3235 Options Database Keys: 3236 + -mat_block_size - size of the blocks to use 3237 - -mat_use_hash_table <fact> 3238 3239 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3240 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3241 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3242 3243 Notes: 3244 If the *_nnz parameter is given then the *_nz parameter is ignored 3245 3246 A nonzero block is any block that as 1 or more nonzeros in it 3247 3248 The user MUST specify either the local or global matrix dimensions 3249 (possibly both). 3250 3251 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3252 than it must be used on all processors that share the object for that argument. 3253 3254 Storage Information: 3255 For a square global matrix we define each processor's diagonal portion 3256 to be its local rows and the corresponding columns (a square submatrix); 3257 each processor's off-diagonal portion encompasses the remainder of the 3258 local matrix (a rectangular submatrix). 3259 3260 The user can specify preallocated storage for the diagonal part of 3261 the local submatrix with either d_nz or d_nnz (not both). Set 3262 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3263 memory allocation. Likewise, specify preallocated storage for the 3264 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3265 3266 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3267 the figure below we depict these three local rows and all columns (0-11). 3268 3269 .vb 3270 0 1 2 3 4 5 6 7 8 9 10 11 3271 -------------------------- 3272 row 3 |o o o d d d o o o o o o 3273 row 4 |o o o d d d o o o o o o 3274 row 5 |o o o d d d o o o o o o 3275 -------------------------- 3276 .ve 3277 3278 Thus, any entries in the d locations are stored in the d (diagonal) 3279 submatrix, and any entries in the o locations are stored in the 3280 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3281 stored simply in the MATSEQBAIJ format for compressed row storage. 3282 3283 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3284 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3285 In general, for PDE problems in which most nonzeros are near the diagonal, 3286 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3287 or you will get TERRIBLE performance; see the users' manual chapter on 3288 matrices. 3289 3290 Level: intermediate 3291 3292 .keywords: matrix, block, aij, compressed row, sparse, parallel 3293 3294 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3295 @*/ 3296 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) 3297 { 3298 PetscErrorCode ierr; 3299 PetscMPIInt size; 3300 3301 PetscFunctionBegin; 3302 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3303 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3304 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3305 if (size > 1) { 3306 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3307 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3308 } else { 3309 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3310 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3311 } 3312 PetscFunctionReturn(0); 3313 } 3314 3315 #undef __FUNCT__ 3316 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3317 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3318 { 3319 Mat mat; 3320 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3321 PetscErrorCode ierr; 3322 PetscInt len=0; 3323 3324 PetscFunctionBegin; 3325 *newmat = 0; 3326 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3327 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3328 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3329 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3330 3331 mat->factortype = matin->factortype; 3332 mat->preallocated = PETSC_TRUE; 3333 mat->assembled = PETSC_TRUE; 3334 mat->insertmode = NOT_SET_VALUES; 3335 3336 a = (Mat_MPIBAIJ*)mat->data; 3337 mat->rmap->bs = matin->rmap->bs; 3338 a->bs2 = oldmat->bs2; 3339 a->mbs = oldmat->mbs; 3340 a->nbs = oldmat->nbs; 3341 a->Mbs = oldmat->Mbs; 3342 a->Nbs = oldmat->Nbs; 3343 3344 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3345 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3346 3347 a->size = oldmat->size; 3348 a->rank = oldmat->rank; 3349 a->donotstash = oldmat->donotstash; 3350 a->roworiented = oldmat->roworiented; 3351 a->rowindices = 0; 3352 a->rowvalues = 0; 3353 a->getrowactive = PETSC_FALSE; 3354 a->barray = 0; 3355 a->rstartbs = oldmat->rstartbs; 3356 a->rendbs = oldmat->rendbs; 3357 a->cstartbs = oldmat->cstartbs; 3358 a->cendbs = oldmat->cendbs; 3359 3360 /* hash table stuff */ 3361 a->ht = 0; 3362 a->hd = 0; 3363 a->ht_size = 0; 3364 a->ht_flag = oldmat->ht_flag; 3365 a->ht_fact = oldmat->ht_fact; 3366 a->ht_total_ct = 0; 3367 a->ht_insert_ct = 0; 3368 3369 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3370 if (oldmat->colmap) { 3371 #if defined(PETSC_USE_CTABLE) 3372 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3373 #else 3374 ierr = PetscMalloc1(a->Nbs,&a->colmap);CHKERRQ(ierr); 3375 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3376 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3377 #endif 3378 } else a->colmap = 0; 3379 3380 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3381 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3382 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3383 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3384 } else a->garray = 0; 3385 3386 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3387 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3388 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3389 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3390 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3391 3392 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3393 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3394 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3395 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3396 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3397 *newmat = mat; 3398 PetscFunctionReturn(0); 3399 } 3400 3401 #undef __FUNCT__ 3402 #define __FUNCT__ "MatLoad_MPIBAIJ" 3403 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3404 { 3405 PetscErrorCode ierr; 3406 int fd; 3407 PetscInt i,nz,j,rstart,rend; 3408 PetscScalar *vals,*buf; 3409 MPI_Comm comm; 3410 MPI_Status status; 3411 PetscMPIInt rank,size,maxnz; 3412 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3413 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3414 PetscInt jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax; 3415 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3416 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3417 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3418 3419 PetscFunctionBegin; 3420 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3421 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3422 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3423 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3424 if (bs < 0) bs = 1; 3425 3426 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3427 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3428 if (!rank) { 3429 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3430 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3431 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3432 } 3433 3434 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3435 3436 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3437 M = header[1]; N = header[2]; 3438 3439 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3440 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3441 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3442 3443 /* If global sizes are set, check if they are consistent with that given in the file */ 3444 if (sizesset) { 3445 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3446 } 3447 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); 3448 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); 3449 3450 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3451 3452 /* 3453 This code adds extra rows to make sure the number of rows is 3454 divisible by the blocksize 3455 */ 3456 Mbs = M/bs; 3457 extra_rows = bs - M + bs*Mbs; 3458 if (extra_rows == bs) extra_rows = 0; 3459 else Mbs++; 3460 if (extra_rows && !rank) { 3461 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3462 } 3463 3464 /* determine ownership of all rows */ 3465 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3466 mbs = Mbs/size + ((Mbs % size) > rank); 3467 m = mbs*bs; 3468 } else { /* User set */ 3469 m = newmat->rmap->n; 3470 mbs = m/bs; 3471 } 3472 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3473 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3474 3475 /* process 0 needs enough room for process with most rows */ 3476 if (!rank) { 3477 mmax = rowners[1]; 3478 for (i=2; i<=size; i++) { 3479 mmax = PetscMax(mmax,rowners[i]); 3480 } 3481 mmax*=bs; 3482 } else mmax = -1; /* unused, but compiler warns anyway */ 3483 3484 rowners[0] = 0; 3485 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3486 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3487 rstart = rowners[rank]; 3488 rend = rowners[rank+1]; 3489 3490 /* distribute row lengths to all processors */ 3491 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3492 if (!rank) { 3493 mend = m; 3494 if (size == 1) mend = mend - extra_rows; 3495 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3496 for (j=mend; j<m; j++) locrowlens[j] = 1; 3497 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3498 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3499 for (j=0; j<m; j++) { 3500 procsnz[0] += locrowlens[j]; 3501 } 3502 for (i=1; i<size; i++) { 3503 mend = browners[i+1] - browners[i]; 3504 if (i == size-1) mend = mend - extra_rows; 3505 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3506 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3507 /* calculate the number of nonzeros on each processor */ 3508 for (j=0; j<browners[i+1]-browners[i]; j++) { 3509 procsnz[i] += rowlengths[j]; 3510 } 3511 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3512 } 3513 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3514 } else { 3515 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3516 } 3517 3518 if (!rank) { 3519 /* determine max buffer needed and allocate it */ 3520 maxnz = procsnz[0]; 3521 for (i=1; i<size; i++) { 3522 maxnz = PetscMax(maxnz,procsnz[i]); 3523 } 3524 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3525 3526 /* read in my part of the matrix column indices */ 3527 nz = procsnz[0]; 3528 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3529 mycols = ibuf; 3530 if (size == 1) nz -= extra_rows; 3531 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3532 if (size == 1) { 3533 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3534 } 3535 3536 /* read in every ones (except the last) and ship off */ 3537 for (i=1; i<size-1; i++) { 3538 nz = procsnz[i]; 3539 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3540 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3541 } 3542 /* read in the stuff for the last proc */ 3543 if (size != 1) { 3544 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3545 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3546 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3547 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3548 } 3549 ierr = PetscFree(cols);CHKERRQ(ierr); 3550 } else { 3551 /* determine buffer space needed for message */ 3552 nz = 0; 3553 for (i=0; i<m; i++) { 3554 nz += locrowlens[i]; 3555 } 3556 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3557 mycols = ibuf; 3558 /* receive message of column indices*/ 3559 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3560 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3561 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3562 } 3563 3564 /* loop over local rows, determining number of off diagonal entries */ 3565 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3566 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3567 rowcount = 0; nzcount = 0; 3568 for (i=0; i<mbs; i++) { 3569 dcount = 0; 3570 odcount = 0; 3571 for (j=0; j<bs; j++) { 3572 kmax = locrowlens[rowcount]; 3573 for (k=0; k<kmax; k++) { 3574 tmp = mycols[nzcount++]/bs; 3575 if (!mask[tmp]) { 3576 mask[tmp] = 1; 3577 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3578 else masked1[dcount++] = tmp; 3579 } 3580 } 3581 rowcount++; 3582 } 3583 3584 dlens[i] = dcount; 3585 odlens[i] = odcount; 3586 3587 /* zero out the mask elements we set */ 3588 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3589 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3590 } 3591 3592 3593 if (!sizesset) { 3594 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3595 } 3596 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3597 3598 if (!rank) { 3599 ierr = PetscMalloc1(maxnz+1,&buf);CHKERRQ(ierr); 3600 /* read in my part of the matrix numerical values */ 3601 nz = procsnz[0]; 3602 vals = buf; 3603 mycols = ibuf; 3604 if (size == 1) nz -= extra_rows; 3605 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3606 if (size == 1) { 3607 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3608 } 3609 3610 /* insert into matrix */ 3611 jj = rstart*bs; 3612 for (i=0; i<m; i++) { 3613 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3614 mycols += locrowlens[i]; 3615 vals += locrowlens[i]; 3616 jj++; 3617 } 3618 /* read in other processors (except the last one) and ship out */ 3619 for (i=1; i<size-1; i++) { 3620 nz = procsnz[i]; 3621 vals = buf; 3622 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3623 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3624 } 3625 /* the last proc */ 3626 if (size != 1) { 3627 nz = procsnz[i] - extra_rows; 3628 vals = buf; 3629 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3630 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3631 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3632 } 3633 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3634 } else { 3635 /* receive numeric values */ 3636 ierr = PetscMalloc1(nz+1,&buf);CHKERRQ(ierr); 3637 3638 /* receive message of values*/ 3639 vals = buf; 3640 mycols = ibuf; 3641 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3642 3643 /* insert into matrix */ 3644 jj = rstart*bs; 3645 for (i=0; i<m; i++) { 3646 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3647 mycols += locrowlens[i]; 3648 vals += locrowlens[i]; 3649 jj++; 3650 } 3651 } 3652 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3653 ierr = PetscFree(buf);CHKERRQ(ierr); 3654 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3655 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3656 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3657 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3658 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3659 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3660 PetscFunctionReturn(0); 3661 } 3662 3663 #undef __FUNCT__ 3664 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3665 /*@ 3666 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3667 3668 Input Parameters: 3669 . mat - the matrix 3670 . fact - factor 3671 3672 Not Collective, each process can use a different factor 3673 3674 Level: advanced 3675 3676 Notes: 3677 This can also be set by the command line option: -mat_use_hash_table <fact> 3678 3679 .keywords: matrix, hashtable, factor, HT 3680 3681 .seealso: MatSetOption() 3682 @*/ 3683 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3684 { 3685 PetscErrorCode ierr; 3686 3687 PetscFunctionBegin; 3688 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3689 PetscFunctionReturn(0); 3690 } 3691 3692 #undef __FUNCT__ 3693 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3694 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3695 { 3696 Mat_MPIBAIJ *baij; 3697 3698 PetscFunctionBegin; 3699 baij = (Mat_MPIBAIJ*)mat->data; 3700 baij->ht_fact = fact; 3701 PetscFunctionReturn(0); 3702 } 3703 3704 #undef __FUNCT__ 3705 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3706 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3707 { 3708 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3709 3710 PetscFunctionBegin; 3711 if (Ad) *Ad = a->A; 3712 if (Ao) *Ao = a->B; 3713 if (colmap) *colmap = a->garray; 3714 PetscFunctionReturn(0); 3715 } 3716 3717 /* 3718 Special version for direct calls from Fortran (to eliminate two function call overheads 3719 */ 3720 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3721 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3722 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3723 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3724 #endif 3725 3726 #undef __FUNCT__ 3727 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3728 /*@C 3729 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3730 3731 Collective on Mat 3732 3733 Input Parameters: 3734 + mat - the matrix 3735 . min - number of input rows 3736 . im - input rows 3737 . nin - number of input columns 3738 . in - input columns 3739 . v - numerical values input 3740 - addvin - INSERT_VALUES or ADD_VALUES 3741 3742 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3743 3744 Level: advanced 3745 3746 .seealso: MatSetValuesBlocked() 3747 @*/ 3748 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3749 { 3750 /* convert input arguments to C version */ 3751 Mat mat = *matin; 3752 PetscInt m = *min, n = *nin; 3753 InsertMode addv = *addvin; 3754 3755 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3756 const MatScalar *value; 3757 MatScalar *barray = baij->barray; 3758 PetscBool roworiented = baij->roworiented; 3759 PetscErrorCode ierr; 3760 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3761 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3762 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3763 3764 PetscFunctionBegin; 3765 /* tasks normally handled by MatSetValuesBlocked() */ 3766 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3767 #if defined(PETSC_USE_DEBUG) 3768 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3769 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3770 #endif 3771 if (mat->assembled) { 3772 mat->was_assembled = PETSC_TRUE; 3773 mat->assembled = PETSC_FALSE; 3774 } 3775 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3776 3777 3778 if (!barray) { 3779 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3780 baij->barray = barray; 3781 } 3782 3783 if (roworiented) stepval = (n-1)*bs; 3784 else stepval = (m-1)*bs; 3785 3786 for (i=0; i<m; i++) { 3787 if (im[i] < 0) continue; 3788 #if defined(PETSC_USE_DEBUG) 3789 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); 3790 #endif 3791 if (im[i] >= rstart && im[i] < rend) { 3792 row = im[i] - rstart; 3793 for (j=0; j<n; j++) { 3794 /* If NumCol = 1 then a copy is not required */ 3795 if ((roworiented) && (n == 1)) { 3796 barray = (MatScalar*)v + i*bs2; 3797 } else if ((!roworiented) && (m == 1)) { 3798 barray = (MatScalar*)v + j*bs2; 3799 } else { /* Here a copy is required */ 3800 if (roworiented) { 3801 value = v + i*(stepval+bs)*bs + j*bs; 3802 } else { 3803 value = v + j*(stepval+bs)*bs + i*bs; 3804 } 3805 for (ii=0; ii<bs; ii++,value+=stepval) { 3806 for (jj=0; jj<bs; jj++) { 3807 *barray++ = *value++; 3808 } 3809 } 3810 barray -=bs2; 3811 } 3812 3813 if (in[j] >= cstart && in[j] < cend) { 3814 col = in[j] - cstart; 3815 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3816 } else if (in[j] < 0) continue; 3817 #if defined(PETSC_USE_DEBUG) 3818 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); 3819 #endif 3820 else { 3821 if (mat->was_assembled) { 3822 if (!baij->colmap) { 3823 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3824 } 3825 3826 #if defined(PETSC_USE_DEBUG) 3827 #if defined(PETSC_USE_CTABLE) 3828 { PetscInt data; 3829 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3830 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3831 } 3832 #else 3833 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3834 #endif 3835 #endif 3836 #if defined(PETSC_USE_CTABLE) 3837 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3838 col = (col - 1)/bs; 3839 #else 3840 col = (baij->colmap[in[j]] - 1)/bs; 3841 #endif 3842 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3843 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3844 col = in[j]; 3845 } 3846 } else col = in[j]; 3847 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3848 } 3849 } 3850 } else { 3851 if (!baij->donotstash) { 3852 if (roworiented) { 3853 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3854 } else { 3855 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3856 } 3857 } 3858 } 3859 } 3860 3861 /* task normally handled by MatSetValuesBlocked() */ 3862 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3863 PetscFunctionReturn(0); 3864 } 3865 3866 #undef __FUNCT__ 3867 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3868 /*@ 3869 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3870 CSR format the local rows. 3871 3872 Collective on MPI_Comm 3873 3874 Input Parameters: 3875 + comm - MPI communicator 3876 . bs - the block size, only a block size of 1 is supported 3877 . m - number of local rows (Cannot be PETSC_DECIDE) 3878 . n - This value should be the same as the local size used in creating the 3879 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3880 calculated if N is given) For square matrices n is almost always m. 3881 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3882 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3883 . i - row indices 3884 . j - column indices 3885 - a - matrix values 3886 3887 Output Parameter: 3888 . mat - the matrix 3889 3890 Level: intermediate 3891 3892 Notes: 3893 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3894 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3895 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3896 3897 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3898 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3899 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3900 with column-major ordering within blocks. 3901 3902 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3903 3904 .keywords: matrix, aij, compressed row, sparse, parallel 3905 3906 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3907 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3908 @*/ 3909 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) 3910 { 3911 PetscErrorCode ierr; 3912 3913 PetscFunctionBegin; 3914 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3915 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3916 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3917 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3918 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3919 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3920 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3921 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3922 PetscFunctionReturn(0); 3923 } 3924 3925 #undef __FUNCT__ 3926 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIBAIJ" 3927 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3928 { 3929 PetscErrorCode ierr; 3930 PetscInt m,N,i,rstart,nnz,Ii,bs,cbs; 3931 PetscInt *indx; 3932 PetscScalar *values; 3933 3934 PetscFunctionBegin; 3935 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3936 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3937 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inmat->data; 3938 PetscInt *dnz,*onz,sum,mbs,Nbs; 3939 PetscInt *bindx,rmax=a->rmax,j; 3940 3941 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3942 mbs = m/bs; Nbs = N/cbs; 3943 if (n == PETSC_DECIDE) { 3944 ierr = PetscSplitOwnership(comm,&n,&Nbs);CHKERRQ(ierr); 3945 } 3946 /* Check sum(n) = Nbs */ 3947 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3948 if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs); 3949 3950 ierr = MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3951 rstart -= mbs; 3952 3953 ierr = PetscMalloc1(rmax,&bindx);CHKERRQ(ierr); 3954 ierr = MatPreallocateInitialize(comm,mbs,n,dnz,onz);CHKERRQ(ierr); 3955 for (i=0; i<mbs; i++) { 3956 ierr = MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); /* non-blocked nnz and indx */ 3957 nnz = nnz/bs; 3958 for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs; 3959 ierr = MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);CHKERRQ(ierr); 3960 ierr = MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); 3961 } 3962 ierr = PetscFree(bindx);CHKERRQ(ierr); 3963 3964 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3965 ierr = MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3966 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3967 ierr = MatSetType(*outmat,MATMPIBAIJ);CHKERRQ(ierr); 3968 ierr = MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);CHKERRQ(ierr); 3969 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3970 } 3971 3972 /* numeric phase */ 3973 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3974 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3975 3976 for (i=0; i<m; i++) { 3977 ierr = MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3978 Ii = i + rstart; 3979 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3980 ierr = MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3981 } 3982 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3983 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3984 PetscFunctionReturn(0); 3985 } 3986