1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 #undef __FUNCT__ 8 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 9 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 10 { 11 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 12 PetscErrorCode ierr; 13 PetscInt i,*idxb = 0; 14 PetscScalar *va,*vb; 15 Vec vtmp; 16 17 PetscFunctionBegin; 18 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 19 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 20 if (idx) { 21 for (i=0; i<A->rmap->n; i++) { 22 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 23 } 24 } 25 26 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 27 if (idx) {ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr);} 28 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 29 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 30 31 for (i=0; i<A->rmap->n; i++) { 32 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 33 va[i] = vb[i]; 34 if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs); 35 } 36 } 37 38 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 39 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 40 ierr = PetscFree(idxb);CHKERRQ(ierr); 41 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 42 PetscFunctionReturn(0); 43 } 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 47 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 48 { 49 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 50 PetscErrorCode ierr; 51 52 PetscFunctionBegin; 53 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 54 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 55 PetscFunctionReturn(0); 56 } 57 58 #undef __FUNCT__ 59 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 60 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 61 { 62 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 63 PetscErrorCode ierr; 64 65 PetscFunctionBegin; 66 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 67 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 68 PetscFunctionReturn(0); 69 } 70 71 /* 72 Local utility routine that creates a mapping from the global column 73 number to the local number in the off-diagonal part of the local 74 storage of the matrix. This is done in a non scalable way since the 75 length of colmap equals the global matrix length. 76 */ 77 #undef __FUNCT__ 78 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 79 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 80 { 81 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 82 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 83 PetscErrorCode ierr; 84 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 85 86 PetscFunctionBegin; 87 #if defined(PETSC_USE_CTABLE) 88 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 89 for (i=0; i<nbs; i++) { 90 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 91 } 92 #else 93 ierr = PetscMalloc1((baij->Nbs+1),&baij->colmap);CHKERRQ(ierr); 94 ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 95 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 96 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 97 #endif 98 PetscFunctionReturn(0); 99 } 100 101 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 102 { \ 103 \ 104 brow = row/bs; \ 105 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 106 rmax = aimax[brow]; nrow = ailen[brow]; \ 107 bcol = col/bs; \ 108 ridx = row % bs; cidx = col % bs; \ 109 low = 0; high = nrow; \ 110 while (high-low > 3) { \ 111 t = (low+high)/2; \ 112 if (rp[t] > bcol) high = t; \ 113 else low = t; \ 114 } \ 115 for (_i=low; _i<high; _i++) { \ 116 if (rp[_i] > bcol) break; \ 117 if (rp[_i] == bcol) { \ 118 bap = ap + bs2*_i + bs*cidx + ridx; \ 119 if (addv == ADD_VALUES) *bap += value; \ 120 else *bap = value; \ 121 goto a_noinsert; \ 122 } \ 123 } \ 124 if (a->nonew == 1) goto a_noinsert; \ 125 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 126 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 127 N = nrow++ - 1; \ 128 /* shift up all the later entries in this row */ \ 129 for (ii=N; ii>=_i; ii--) { \ 130 rp[ii+1] = rp[ii]; \ 131 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 132 } \ 133 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 134 rp[_i] = bcol; \ 135 ap[bs2*_i + bs*cidx + ridx] = value; \ 136 a_noinsert:; \ 137 ailen[brow] = nrow; \ 138 } 139 140 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 141 { \ 142 brow = row/bs; \ 143 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 144 rmax = bimax[brow]; nrow = bilen[brow]; \ 145 bcol = col/bs; \ 146 ridx = row % bs; cidx = col % bs; \ 147 low = 0; high = nrow; \ 148 while (high-low > 3) { \ 149 t = (low+high)/2; \ 150 if (rp[t] > bcol) high = t; \ 151 else low = t; \ 152 } \ 153 for (_i=low; _i<high; _i++) { \ 154 if (rp[_i] > bcol) break; \ 155 if (rp[_i] == bcol) { \ 156 bap = ap + bs2*_i + bs*cidx + ridx; \ 157 if (addv == ADD_VALUES) *bap += value; \ 158 else *bap = value; \ 159 goto b_noinsert; \ 160 } \ 161 } \ 162 if (b->nonew == 1) goto b_noinsert; \ 163 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 164 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 165 N = nrow++ - 1; \ 166 /* shift up all the later entries in this row */ \ 167 for (ii=N; ii>=_i; ii--) { \ 168 rp[ii+1] = rp[ii]; \ 169 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 170 } \ 171 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 172 rp[_i] = bcol; \ 173 ap[bs2*_i + bs*cidx + ridx] = value; \ 174 b_noinsert:; \ 175 bilen[brow] = nrow; \ 176 } 177 178 #undef __FUNCT__ 179 #define __FUNCT__ "MatSetValues_MPIBAIJ" 180 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 181 { 182 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 183 MatScalar value; 184 PetscBool roworiented = baij->roworiented; 185 PetscErrorCode ierr; 186 PetscInt i,j,row,col; 187 PetscInt rstart_orig=mat->rmap->rstart; 188 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 189 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 190 191 /* Some Variables required in the macro */ 192 Mat A = baij->A; 193 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 194 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 195 MatScalar *aa =a->a; 196 197 Mat B = baij->B; 198 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 199 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 200 MatScalar *ba =b->a; 201 202 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 203 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 204 MatScalar *ap,*bap; 205 206 PetscFunctionBegin; 207 for (i=0; i<m; i++) { 208 if (im[i] < 0) continue; 209 #if defined(PETSC_USE_DEBUG) 210 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); 211 #endif 212 if (im[i] >= rstart_orig && im[i] < rend_orig) { 213 row = im[i] - rstart_orig; 214 for (j=0; j<n; j++) { 215 if (in[j] >= cstart_orig && in[j] < cend_orig) { 216 col = in[j] - cstart_orig; 217 if (roworiented) value = v[i*n+j]; 218 else value = v[i+j*m]; 219 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 220 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 221 } else if (in[j] < 0) continue; 222 #if defined(PETSC_USE_DEBUG) 223 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); 224 #endif 225 else { 226 if (mat->was_assembled) { 227 if (!baij->colmap) { 228 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 229 } 230 #if defined(PETSC_USE_CTABLE) 231 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 232 col = col - 1; 233 #else 234 col = baij->colmap[in[j]/bs] - 1; 235 #endif 236 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 237 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 238 col = in[j]; 239 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 240 B = baij->B; 241 b = (Mat_SeqBAIJ*)(B)->data; 242 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 243 ba =b->a; 244 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 245 else col += in[j]%bs; 246 } else col = in[j]; 247 if (roworiented) value = v[i*n+j]; 248 else value = v[i+j*m]; 249 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 250 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 251 } 252 } 253 } else { 254 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]); 255 if (!baij->donotstash) { 256 mat->assembled = PETSC_FALSE; 257 if (roworiented) { 258 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 259 } else { 260 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 261 } 262 } 263 } 264 } 265 PetscFunctionReturn(0); 266 } 267 268 #undef __FUNCT__ 269 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 270 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 271 { 272 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 273 const PetscScalar *value; 274 MatScalar *barray = baij->barray; 275 PetscBool roworiented = baij->roworiented; 276 PetscErrorCode ierr; 277 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 278 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 279 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 280 281 PetscFunctionBegin; 282 if (!barray) { 283 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 284 baij->barray = barray; 285 } 286 287 if (roworiented) stepval = (n-1)*bs; 288 else stepval = (m-1)*bs; 289 290 for (i=0; i<m; i++) { 291 if (im[i] < 0) continue; 292 #if defined(PETSC_USE_DEBUG) 293 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); 294 #endif 295 if (im[i] >= rstart && im[i] < rend) { 296 row = im[i] - rstart; 297 for (j=0; j<n; j++) { 298 /* If NumCol = 1 then a copy is not required */ 299 if ((roworiented) && (n == 1)) { 300 barray = (MatScalar*)v + i*bs2; 301 } else if ((!roworiented) && (m == 1)) { 302 barray = (MatScalar*)v + j*bs2; 303 } else { /* Here a copy is required */ 304 if (roworiented) { 305 value = v + (i*(stepval+bs) + j)*bs; 306 } else { 307 value = v + (j*(stepval+bs) + i)*bs; 308 } 309 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 310 for (jj=0; jj<bs; jj++) barray[jj] = value[jj]; 311 barray += bs; 312 } 313 barray -= bs2; 314 } 315 316 if (in[j] >= cstart && in[j] < cend) { 317 col = in[j] - cstart; 318 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 319 } else if (in[j] < 0) continue; 320 #if defined(PETSC_USE_DEBUG) 321 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); 322 #endif 323 else { 324 if (mat->was_assembled) { 325 if (!baij->colmap) { 326 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 327 } 328 329 #if defined(PETSC_USE_DEBUG) 330 #if defined(PETSC_USE_CTABLE) 331 { PetscInt data; 332 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 333 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 334 } 335 #else 336 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 337 #endif 338 #endif 339 #if defined(PETSC_USE_CTABLE) 340 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 341 col = (col - 1)/bs; 342 #else 343 col = (baij->colmap[in[j]] - 1)/bs; 344 #endif 345 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 346 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 347 col = in[j]; 348 } 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]); 349 } else col = in[j]; 350 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 351 } 352 } 353 } else { 354 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]); 355 if (!baij->donotstash) { 356 if (roworiented) { 357 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 358 } else { 359 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 360 } 361 } 362 } 363 } 364 PetscFunctionReturn(0); 365 } 366 367 #define HASH_KEY 0.6180339887 368 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 369 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 370 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 371 #undef __FUNCT__ 372 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 373 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 374 { 375 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 376 PetscBool roworiented = baij->roworiented; 377 PetscErrorCode ierr; 378 PetscInt i,j,row,col; 379 PetscInt rstart_orig=mat->rmap->rstart; 380 PetscInt rend_orig =mat->rmap->rend,Nbs=baij->Nbs; 381 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 382 PetscReal tmp; 383 MatScalar **HD = baij->hd,value; 384 #if defined(PETSC_USE_DEBUG) 385 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 386 #endif 387 388 PetscFunctionBegin; 389 for (i=0; i<m; i++) { 390 #if defined(PETSC_USE_DEBUG) 391 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 392 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); 393 #endif 394 row = im[i]; 395 if (row >= rstart_orig && row < rend_orig) { 396 for (j=0; j<n; j++) { 397 col = in[j]; 398 if (roworiented) value = v[i*n+j]; 399 else value = v[i+j*m]; 400 /* Look up PetscInto the Hash Table */ 401 key = (row/bs)*Nbs+(col/bs)+1; 402 h1 = HASH(size,key,tmp); 403 404 405 idx = h1; 406 #if defined(PETSC_USE_DEBUG) 407 insert_ct++; 408 total_ct++; 409 if (HT[idx] != key) { 410 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 411 if (idx == size) { 412 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 413 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 414 } 415 } 416 #else 417 if (HT[idx] != key) { 418 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 419 if (idx == size) { 420 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 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 #endif 425 /* A HASH table entry is found, so insert the values at the correct address */ 426 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 427 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 428 } 429 } else if (!baij->donotstash) { 430 if (roworiented) { 431 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 432 } else { 433 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 434 } 435 } 436 } 437 #if defined(PETSC_USE_DEBUG) 438 baij->ht_total_ct = total_ct; 439 baij->ht_insert_ct = insert_ct; 440 #endif 441 PetscFunctionReturn(0); 442 } 443 444 #undef __FUNCT__ 445 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 446 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 447 { 448 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 449 PetscBool roworiented = baij->roworiented; 450 PetscErrorCode ierr; 451 PetscInt i,j,ii,jj,row,col; 452 PetscInt rstart=baij->rstartbs; 453 PetscInt rend =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 454 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 455 PetscReal tmp; 456 MatScalar **HD = baij->hd,*baij_a; 457 const PetscScalar *v_t,*value; 458 #if defined(PETSC_USE_DEBUG) 459 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 460 #endif 461 462 PetscFunctionBegin; 463 if (roworiented) stepval = (n-1)*bs; 464 else stepval = (m-1)*bs; 465 466 for (i=0; i<m; i++) { 467 #if defined(PETSC_USE_DEBUG) 468 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 469 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); 470 #endif 471 row = im[i]; 472 v_t = v + i*nbs2; 473 if (row >= rstart && row < rend) { 474 for (j=0; j<n; j++) { 475 col = in[j]; 476 477 /* Look up into the Hash Table */ 478 key = row*Nbs+col+1; 479 h1 = HASH(size,key,tmp); 480 481 idx = h1; 482 #if defined(PETSC_USE_DEBUG) 483 total_ct++; 484 insert_ct++; 485 if (HT[idx] != key) { 486 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 487 if (idx == size) { 488 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 489 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 490 } 491 } 492 #else 493 if (HT[idx] != key) { 494 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 495 if (idx == size) { 496 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 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 #endif 501 baij_a = HD[idx]; 502 if (roworiented) { 503 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 504 /* value = v + (i*(stepval+bs)+j)*bs; */ 505 value = v_t; 506 v_t += bs; 507 if (addv == ADD_VALUES) { 508 for (ii=0; ii<bs; ii++,value+=stepval) { 509 for (jj=ii; jj<bs2; jj+=bs) { 510 baij_a[jj] += *value++; 511 } 512 } 513 } else { 514 for (ii=0; ii<bs; ii++,value+=stepval) { 515 for (jj=ii; jj<bs2; jj+=bs) { 516 baij_a[jj] = *value++; 517 } 518 } 519 } 520 } else { 521 value = v + j*(stepval+bs)*bs + i*bs; 522 if (addv == ADD_VALUES) { 523 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 524 for (jj=0; jj<bs; jj++) { 525 baij_a[jj] += *value++; 526 } 527 } 528 } else { 529 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 530 for (jj=0; jj<bs; jj++) { 531 baij_a[jj] = *value++; 532 } 533 } 534 } 535 } 536 } 537 } else { 538 if (!baij->donotstash) { 539 if (roworiented) { 540 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 541 } else { 542 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 543 } 544 } 545 } 546 } 547 #if defined(PETSC_USE_DEBUG) 548 baij->ht_total_ct = total_ct; 549 baij->ht_insert_ct = insert_ct; 550 #endif 551 PetscFunctionReturn(0); 552 } 553 554 #undef __FUNCT__ 555 #define __FUNCT__ "MatGetValues_MPIBAIJ" 556 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 557 { 558 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 559 PetscErrorCode ierr; 560 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 561 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 562 563 PetscFunctionBegin; 564 for (i=0; i<m; i++) { 565 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 566 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); 567 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 568 row = idxm[i] - bsrstart; 569 for (j=0; j<n; j++) { 570 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 571 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); 572 if (idxn[j] >= bscstart && idxn[j] < bscend) { 573 col = idxn[j] - bscstart; 574 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 575 } else { 576 if (!baij->colmap) { 577 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 578 } 579 #if defined(PETSC_USE_CTABLE) 580 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 581 data--; 582 #else 583 data = baij->colmap[idxn[j]/bs]-1; 584 #endif 585 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 586 else { 587 col = data + idxn[j]%bs; 588 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 589 } 590 } 591 } 592 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 593 } 594 PetscFunctionReturn(0); 595 } 596 597 #undef __FUNCT__ 598 #define __FUNCT__ "MatNorm_MPIBAIJ" 599 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 600 { 601 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 602 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 603 PetscErrorCode ierr; 604 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 605 PetscReal sum = 0.0; 606 MatScalar *v; 607 608 PetscFunctionBegin; 609 if (baij->size == 1) { 610 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 611 } else { 612 if (type == NORM_FROBENIUS) { 613 v = amat->a; 614 nz = amat->nz*bs2; 615 for (i=0; i<nz; i++) { 616 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 617 } 618 v = bmat->a; 619 nz = bmat->nz*bs2; 620 for (i=0; i<nz; i++) { 621 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 622 } 623 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 624 *nrm = PetscSqrtReal(*nrm); 625 } else if (type == NORM_1) { /* max column sum */ 626 PetscReal *tmp,*tmp2; 627 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 628 ierr = PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);CHKERRQ(ierr); 629 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 630 v = amat->a; jj = amat->j; 631 for (i=0; i<amat->nz; i++) { 632 for (j=0; j<bs; j++) { 633 col = bs*(cstart + *jj) + j; /* column index */ 634 for (row=0; row<bs; row++) { 635 tmp[col] += PetscAbsScalar(*v); v++; 636 } 637 } 638 jj++; 639 } 640 v = bmat->a; jj = bmat->j; 641 for (i=0; i<bmat->nz; i++) { 642 for (j=0; j<bs; j++) { 643 col = bs*garray[*jj] + j; 644 for (row=0; row<bs; row++) { 645 tmp[col] += PetscAbsScalar(*v); v++; 646 } 647 } 648 jj++; 649 } 650 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 651 *nrm = 0.0; 652 for (j=0; j<mat->cmap->N; j++) { 653 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 654 } 655 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 656 } else if (type == NORM_INFINITY) { /* max row sum */ 657 PetscReal *sums; 658 ierr = PetscMalloc1(bs,&sums);CHKERRQ(ierr); 659 sum = 0.0; 660 for (j=0; j<amat->mbs; j++) { 661 for (row=0; row<bs; row++) sums[row] = 0.0; 662 v = amat->a + bs2*amat->i[j]; 663 nz = amat->i[j+1]-amat->i[j]; 664 for (i=0; i<nz; i++) { 665 for (col=0; col<bs; col++) { 666 for (row=0; row<bs; row++) { 667 sums[row] += PetscAbsScalar(*v); v++; 668 } 669 } 670 } 671 v = bmat->a + bs2*bmat->i[j]; 672 nz = bmat->i[j+1]-bmat->i[j]; 673 for (i=0; i<nz; i++) { 674 for (col=0; col<bs; col++) { 675 for (row=0; row<bs; row++) { 676 sums[row] += PetscAbsScalar(*v); v++; 677 } 678 } 679 } 680 for (row=0; row<bs; row++) { 681 if (sums[row] > sum) sum = sums[row]; 682 } 683 } 684 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 685 ierr = PetscFree(sums);CHKERRQ(ierr); 686 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet"); 687 } 688 PetscFunctionReturn(0); 689 } 690 691 /* 692 Creates the hash table, and sets the table 693 This table is created only once. 694 If new entried need to be added to the matrix 695 then the hash table has to be destroyed and 696 recreated. 697 */ 698 #undef __FUNCT__ 699 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 700 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 701 { 702 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 703 Mat A = baij->A,B=baij->B; 704 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data; 705 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 706 PetscErrorCode ierr; 707 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 708 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 709 PetscInt *HT,key; 710 MatScalar **HD; 711 PetscReal tmp; 712 #if defined(PETSC_USE_INFO) 713 PetscInt ct=0,max=0; 714 #endif 715 716 PetscFunctionBegin; 717 if (baij->ht) PetscFunctionReturn(0); 718 719 baij->ht_size = (PetscInt)(factor*nz); 720 ht_size = baij->ht_size; 721 722 /* Allocate Memory for Hash Table */ 723 ierr = PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);CHKERRQ(ierr); 724 HD = baij->hd; 725 HT = baij->ht; 726 727 /* Loop Over A */ 728 for (i=0; i<a->mbs; i++) { 729 for (j=ai[i]; j<ai[i+1]; j++) { 730 row = i+rstart; 731 col = aj[j]+cstart; 732 733 key = row*Nbs + col + 1; 734 h1 = HASH(ht_size,key,tmp); 735 for (k=0; k<ht_size; k++) { 736 if (!HT[(h1+k)%ht_size]) { 737 HT[(h1+k)%ht_size] = key; 738 HD[(h1+k)%ht_size] = a->a + j*bs2; 739 break; 740 #if defined(PETSC_USE_INFO) 741 } else { 742 ct++; 743 #endif 744 } 745 } 746 #if defined(PETSC_USE_INFO) 747 if (k> max) max = k; 748 #endif 749 } 750 } 751 /* Loop Over B */ 752 for (i=0; i<b->mbs; i++) { 753 for (j=bi[i]; j<bi[i+1]; j++) { 754 row = i+rstart; 755 col = garray[bj[j]]; 756 key = row*Nbs + col + 1; 757 h1 = HASH(ht_size,key,tmp); 758 for (k=0; k<ht_size; k++) { 759 if (!HT[(h1+k)%ht_size]) { 760 HT[(h1+k)%ht_size] = key; 761 HD[(h1+k)%ht_size] = b->a + j*bs2; 762 break; 763 #if defined(PETSC_USE_INFO) 764 } else { 765 ct++; 766 #endif 767 } 768 } 769 #if defined(PETSC_USE_INFO) 770 if (k> max) max = k; 771 #endif 772 } 773 } 774 775 /* Print Summary */ 776 #if defined(PETSC_USE_INFO) 777 for (i=0,j=0; i<ht_size; i++) { 778 if (HT[i]) j++; 779 } 780 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 781 #endif 782 PetscFunctionReturn(0); 783 } 784 785 #undef __FUNCT__ 786 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 787 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 788 { 789 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 790 PetscErrorCode ierr; 791 PetscInt nstash,reallocs; 792 InsertMode addv; 793 794 PetscFunctionBegin; 795 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 796 797 /* make sure all processors are either in INSERTMODE or ADDMODE */ 798 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 799 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 800 mat->insertmode = addv; /* in case this processor had no cache */ 801 802 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 803 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 804 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 805 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 806 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 807 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 808 PetscFunctionReturn(0); 809 } 810 811 #undef __FUNCT__ 812 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 813 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 814 { 815 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 816 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)baij->A->data; 817 PetscErrorCode ierr; 818 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 819 PetscInt *row,*col; 820 PetscBool r1,r2,r3,other_disassembled; 821 MatScalar *val; 822 InsertMode addv = mat->insertmode; 823 PetscMPIInt n; 824 825 PetscFunctionBegin; 826 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 827 if (!baij->donotstash && !mat->nooffprocentries) { 828 while (1) { 829 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 830 if (!flg) break; 831 832 for (i=0; i<n;) { 833 /* Now identify the consecutive vals belonging to the same row */ 834 for (j=i,rstart=row[j]; j<n; j++) { 835 if (row[j] != rstart) break; 836 } 837 if (j < n) ncols = j-i; 838 else ncols = n-i; 839 /* Now assemble all these values with a single function call */ 840 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 841 i = j; 842 } 843 } 844 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 845 /* Now process the block-stash. Since the values are stashed column-oriented, 846 set the roworiented flag to column oriented, and after MatSetValues() 847 restore the original flags */ 848 r1 = baij->roworiented; 849 r2 = a->roworiented; 850 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 851 852 baij->roworiented = PETSC_FALSE; 853 a->roworiented = PETSC_FALSE; 854 855 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 856 while (1) { 857 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 858 if (!flg) break; 859 860 for (i=0; i<n;) { 861 /* Now identify the consecutive vals belonging to the same row */ 862 for (j=i,rstart=row[j]; j<n; j++) { 863 if (row[j] != rstart) break; 864 } 865 if (j < n) ncols = j-i; 866 else ncols = n-i; 867 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 868 i = j; 869 } 870 } 871 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 872 873 baij->roworiented = r1; 874 a->roworiented = r2; 875 876 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 877 } 878 879 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 880 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 881 882 /* determine if any processor has disassembled, if so we must 883 also disassemble ourselfs, in order that we may reassemble. */ 884 /* 885 if nonzero structure of submatrix B cannot change then we know that 886 no processor disassembled thus we can skip this stuff 887 */ 888 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 889 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 890 if (mat->was_assembled && !other_disassembled) { 891 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 892 } 893 } 894 895 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 896 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 897 } 898 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 899 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 900 901 #if defined(PETSC_USE_INFO) 902 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 903 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 904 905 baij->ht_total_ct = 0; 906 baij->ht_insert_ct = 0; 907 } 908 #endif 909 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 910 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 911 912 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 913 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 914 } 915 916 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 917 918 baij->rowvalues = 0; 919 920 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 921 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 922 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 923 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 924 } 925 PetscFunctionReturn(0); 926 } 927 928 extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer); 929 #include <petscdraw.h> 930 #undef __FUNCT__ 931 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 932 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 933 { 934 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 935 PetscErrorCode ierr; 936 PetscMPIInt rank = baij->rank; 937 PetscInt bs = mat->rmap->bs; 938 PetscBool iascii,isdraw; 939 PetscViewer sviewer; 940 PetscViewerFormat format; 941 942 PetscFunctionBegin; 943 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 944 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 945 if (iascii) { 946 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 947 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 948 MatInfo info; 949 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 950 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 951 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 952 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 953 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 954 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 955 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 956 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 957 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 958 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 959 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 960 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 961 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 962 PetscFunctionReturn(0); 963 } else if (format == PETSC_VIEWER_ASCII_INFO) { 964 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 965 PetscFunctionReturn(0); 966 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 967 PetscFunctionReturn(0); 968 } 969 } 970 971 if (isdraw) { 972 PetscDraw draw; 973 PetscBool isnull; 974 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 975 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 976 } 977 978 { 979 /* assemble the entire matrix onto first processor. */ 980 Mat A; 981 Mat_SeqBAIJ *Aloc; 982 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 983 MatScalar *a; 984 const char *matname; 985 986 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 987 /* Perhaps this should be the type of mat? */ 988 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 989 if (!rank) { 990 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 991 } else { 992 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 993 } 994 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 995 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 996 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 997 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 998 999 /* copy over the A part */ 1000 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1001 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1002 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1003 1004 for (i=0; i<mbs; i++) { 1005 rvals[0] = bs*(baij->rstartbs + i); 1006 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1007 for (j=ai[i]; j<ai[i+1]; j++) { 1008 col = (baij->cstartbs+aj[j])*bs; 1009 for (k=0; k<bs; k++) { 1010 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1011 col++; a += bs; 1012 } 1013 } 1014 } 1015 /* copy over the B part */ 1016 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1017 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1018 for (i=0; i<mbs; i++) { 1019 rvals[0] = bs*(baij->rstartbs + i); 1020 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1021 for (j=ai[i]; j<ai[i+1]; j++) { 1022 col = baij->garray[aj[j]]*bs; 1023 for (k=0; k<bs; k++) { 1024 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1025 col++; a += bs; 1026 } 1027 } 1028 } 1029 ierr = PetscFree(rvals);CHKERRQ(ierr); 1030 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1031 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1032 /* 1033 Everyone has to call to draw the matrix since the graphics waits are 1034 synchronized across all processors that share the PetscDraw object 1035 */ 1036 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1037 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 1038 if (!rank) { 1039 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 1040 ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1041 } 1042 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1043 ierr = MatDestroy(&A);CHKERRQ(ierr); 1044 } 1045 PetscFunctionReturn(0); 1046 } 1047 1048 #undef __FUNCT__ 1049 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1050 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1051 { 1052 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1053 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1054 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1055 PetscErrorCode ierr; 1056 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1057 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1058 int fd; 1059 PetscScalar *column_values; 1060 FILE *file; 1061 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1062 PetscInt message_count,flowcontrolcount; 1063 1064 PetscFunctionBegin; 1065 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1066 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1067 nz = bs2*(A->nz + B->nz); 1068 rlen = mat->rmap->n; 1069 if (!rank) { 1070 header[0] = MAT_FILE_CLASSID; 1071 header[1] = mat->rmap->N; 1072 header[2] = mat->cmap->N; 1073 1074 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1075 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1076 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1077 /* get largest number of rows any processor has */ 1078 range = mat->rmap->range; 1079 for (i=1; i<size; i++) { 1080 rlen = PetscMax(rlen,range[i+1] - range[i]); 1081 } 1082 } else { 1083 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1084 } 1085 1086 ierr = PetscMalloc1((rlen/bs),&crow_lens);CHKERRQ(ierr); 1087 /* compute lengths of each row */ 1088 for (i=0; i<a->mbs; i++) { 1089 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1090 } 1091 /* store the row lengths to the file */ 1092 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1093 if (!rank) { 1094 MPI_Status status; 1095 ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr); 1096 rlen = (range[1] - range[0])/bs; 1097 for (i=0; i<rlen; i++) { 1098 for (j=0; j<bs; j++) { 1099 row_lens[i*bs+j] = bs*crow_lens[i]; 1100 } 1101 } 1102 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1103 for (i=1; i<size; i++) { 1104 rlen = (range[i+1] - range[i])/bs; 1105 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1106 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1107 for (k=0; k<rlen; k++) { 1108 for (j=0; j<bs; j++) { 1109 row_lens[k*bs+j] = bs*crow_lens[k]; 1110 } 1111 } 1112 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1113 } 1114 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1115 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1116 } else { 1117 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1118 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1119 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1120 } 1121 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1122 1123 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1124 information needed to make it for each row from a block row. This does require more communication but still not more than 1125 the communication needed for the nonzero values */ 1126 nzmax = nz; /* space a largest processor needs */ 1127 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1128 ierr = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr); 1129 cnt = 0; 1130 for (i=0; i<a->mbs; i++) { 1131 pcnt = cnt; 1132 for (j=B->i[i]; j<B->i[i+1]; j++) { 1133 if ((col = garray[B->j[j]]) > cstart) break; 1134 for (l=0; l<bs; l++) { 1135 column_indices[cnt++] = bs*col+l; 1136 } 1137 } 1138 for (k=A->i[i]; k<A->i[i+1]; k++) { 1139 for (l=0; l<bs; l++) { 1140 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1141 } 1142 } 1143 for (; j<B->i[i+1]; j++) { 1144 for (l=0; l<bs; l++) { 1145 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1146 } 1147 } 1148 len = cnt - pcnt; 1149 for (k=1; k<bs; k++) { 1150 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1151 cnt += len; 1152 } 1153 } 1154 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1155 1156 /* store the columns to the file */ 1157 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1158 if (!rank) { 1159 MPI_Status status; 1160 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1161 for (i=1; i<size; i++) { 1162 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1163 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1164 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1165 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1166 } 1167 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1168 } else { 1169 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1170 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1171 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1172 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1173 } 1174 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1175 1176 /* load up the numerical values */ 1177 ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr); 1178 cnt = 0; 1179 for (i=0; i<a->mbs; i++) { 1180 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1181 for (j=B->i[i]; j<B->i[i+1]; j++) { 1182 if (garray[B->j[j]] > cstart) break; 1183 for (l=0; l<bs; l++) { 1184 for (ll=0; ll<bs; ll++) { 1185 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1186 } 1187 } 1188 cnt += bs; 1189 } 1190 for (k=A->i[i]; k<A->i[i+1]; k++) { 1191 for (l=0; l<bs; l++) { 1192 for (ll=0; ll<bs; ll++) { 1193 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1194 } 1195 } 1196 cnt += bs; 1197 } 1198 for (; j<B->i[i+1]; j++) { 1199 for (l=0; l<bs; l++) { 1200 for (ll=0; ll<bs; ll++) { 1201 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1202 } 1203 } 1204 cnt += bs; 1205 } 1206 cnt += (bs-1)*rlen; 1207 } 1208 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1209 1210 /* store the column values to the file */ 1211 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1212 if (!rank) { 1213 MPI_Status status; 1214 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1215 for (i=1; i<size; i++) { 1216 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1217 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1218 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1219 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1220 } 1221 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1222 } else { 1223 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1224 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1225 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1226 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1227 } 1228 ierr = PetscFree(column_values);CHKERRQ(ierr); 1229 1230 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1231 if (file) { 1232 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1233 } 1234 PetscFunctionReturn(0); 1235 } 1236 1237 #undef __FUNCT__ 1238 #define __FUNCT__ "MatView_MPIBAIJ" 1239 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1240 { 1241 PetscErrorCode ierr; 1242 PetscBool iascii,isdraw,issocket,isbinary; 1243 1244 PetscFunctionBegin; 1245 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1246 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1247 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1248 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1249 if (iascii || isdraw || issocket) { 1250 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1251 } else if (isbinary) { 1252 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1253 } 1254 PetscFunctionReturn(0); 1255 } 1256 1257 #undef __FUNCT__ 1258 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1259 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1260 { 1261 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1262 PetscErrorCode ierr; 1263 1264 PetscFunctionBegin; 1265 #if defined(PETSC_USE_LOG) 1266 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1267 #endif 1268 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1269 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1270 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1271 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1272 #if defined(PETSC_USE_CTABLE) 1273 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1274 #else 1275 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1276 #endif 1277 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1278 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1279 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1280 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1281 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1282 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1283 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1284 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1285 1286 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1287 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1288 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1289 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1290 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1291 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1292 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1293 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1294 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1295 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1296 PetscFunctionReturn(0); 1297 } 1298 1299 #undef __FUNCT__ 1300 #define __FUNCT__ "MatMult_MPIBAIJ" 1301 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1302 { 1303 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1304 PetscErrorCode ierr; 1305 PetscInt nt; 1306 1307 PetscFunctionBegin; 1308 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1309 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1310 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1311 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1312 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1313 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1314 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1315 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1316 PetscFunctionReturn(0); 1317 } 1318 1319 #undef __FUNCT__ 1320 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1321 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1322 { 1323 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1324 PetscErrorCode ierr; 1325 1326 PetscFunctionBegin; 1327 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1328 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1329 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1330 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1331 PetscFunctionReturn(0); 1332 } 1333 1334 #undef __FUNCT__ 1335 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1336 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1337 { 1338 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1339 PetscErrorCode ierr; 1340 PetscBool merged; 1341 1342 PetscFunctionBegin; 1343 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1344 /* do nondiagonal part */ 1345 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1346 if (!merged) { 1347 /* send it on its way */ 1348 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1349 /* do local part */ 1350 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1351 /* receive remote parts: note this assumes the values are not actually */ 1352 /* inserted in yy until the next line */ 1353 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1354 } else { 1355 /* do local part */ 1356 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1357 /* send it on its way */ 1358 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1359 /* values actually were received in the Begin() but we need to call this nop */ 1360 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1361 } 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNCT__ 1366 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1367 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1368 { 1369 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1370 PetscErrorCode ierr; 1371 1372 PetscFunctionBegin; 1373 /* do nondiagonal part */ 1374 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1375 /* send it on its way */ 1376 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1377 /* do local part */ 1378 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1379 /* receive remote parts: note this assumes the values are not actually */ 1380 /* inserted in yy until the next line, which is true for my implementation*/ 1381 /* but is not perhaps always true. */ 1382 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1383 PetscFunctionReturn(0); 1384 } 1385 1386 /* 1387 This only works correctly for square matrices where the subblock A->A is the 1388 diagonal block 1389 */ 1390 #undef __FUNCT__ 1391 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1392 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1393 { 1394 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1395 PetscErrorCode ierr; 1396 1397 PetscFunctionBegin; 1398 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1399 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1400 PetscFunctionReturn(0); 1401 } 1402 1403 #undef __FUNCT__ 1404 #define __FUNCT__ "MatScale_MPIBAIJ" 1405 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1406 { 1407 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1408 PetscErrorCode ierr; 1409 1410 PetscFunctionBegin; 1411 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1412 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1413 PetscFunctionReturn(0); 1414 } 1415 1416 #undef __FUNCT__ 1417 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1418 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1419 { 1420 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1421 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1422 PetscErrorCode ierr; 1423 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1424 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1425 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1426 1427 PetscFunctionBegin; 1428 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1429 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1430 mat->getrowactive = PETSC_TRUE; 1431 1432 if (!mat->rowvalues && (idx || v)) { 1433 /* 1434 allocate enough space to hold information from the longest row. 1435 */ 1436 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1437 PetscInt max = 1,mbs = mat->mbs,tmp; 1438 for (i=0; i<mbs; i++) { 1439 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1440 if (max < tmp) max = tmp; 1441 } 1442 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1443 } 1444 lrow = row - brstart; 1445 1446 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1447 if (!v) {pvA = 0; pvB = 0;} 1448 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1449 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1450 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1451 nztot = nzA + nzB; 1452 1453 cmap = mat->garray; 1454 if (v || idx) { 1455 if (nztot) { 1456 /* Sort by increasing column numbers, assuming A and B already sorted */ 1457 PetscInt imark = -1; 1458 if (v) { 1459 *v = v_p = mat->rowvalues; 1460 for (i=0; i<nzB; i++) { 1461 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1462 else break; 1463 } 1464 imark = i; 1465 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1466 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1467 } 1468 if (idx) { 1469 *idx = idx_p = mat->rowindices; 1470 if (imark > -1) { 1471 for (i=0; i<imark; i++) { 1472 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1473 } 1474 } else { 1475 for (i=0; i<nzB; i++) { 1476 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1477 else break; 1478 } 1479 imark = i; 1480 } 1481 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1482 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1483 } 1484 } else { 1485 if (idx) *idx = 0; 1486 if (v) *v = 0; 1487 } 1488 } 1489 *nz = nztot; 1490 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1491 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1492 PetscFunctionReturn(0); 1493 } 1494 1495 #undef __FUNCT__ 1496 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1497 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1498 { 1499 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1500 1501 PetscFunctionBegin; 1502 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1503 baij->getrowactive = PETSC_FALSE; 1504 PetscFunctionReturn(0); 1505 } 1506 1507 #undef __FUNCT__ 1508 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1509 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1510 { 1511 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1512 PetscErrorCode ierr; 1513 1514 PetscFunctionBegin; 1515 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1516 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1517 PetscFunctionReturn(0); 1518 } 1519 1520 #undef __FUNCT__ 1521 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1522 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1523 { 1524 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1525 Mat A = a->A,B = a->B; 1526 PetscErrorCode ierr; 1527 PetscReal isend[5],irecv[5]; 1528 1529 PetscFunctionBegin; 1530 info->block_size = (PetscReal)matin->rmap->bs; 1531 1532 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1533 1534 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1535 isend[3] = info->memory; isend[4] = info->mallocs; 1536 1537 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1538 1539 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1540 isend[3] += info->memory; isend[4] += info->mallocs; 1541 1542 if (flag == MAT_LOCAL) { 1543 info->nz_used = isend[0]; 1544 info->nz_allocated = isend[1]; 1545 info->nz_unneeded = isend[2]; 1546 info->memory = isend[3]; 1547 info->mallocs = isend[4]; 1548 } else if (flag == MAT_GLOBAL_MAX) { 1549 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1550 1551 info->nz_used = irecv[0]; 1552 info->nz_allocated = irecv[1]; 1553 info->nz_unneeded = irecv[2]; 1554 info->memory = irecv[3]; 1555 info->mallocs = irecv[4]; 1556 } else if (flag == MAT_GLOBAL_SUM) { 1557 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,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 SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1565 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1566 info->fill_ratio_needed = 0; 1567 info->factor_mallocs = 0; 1568 PetscFunctionReturn(0); 1569 } 1570 1571 #undef __FUNCT__ 1572 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1573 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1574 { 1575 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1576 PetscErrorCode ierr; 1577 1578 PetscFunctionBegin; 1579 switch (op) { 1580 case MAT_NEW_NONZERO_LOCATIONS: 1581 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1582 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1583 case MAT_KEEP_NONZERO_PATTERN: 1584 case MAT_NEW_NONZERO_LOCATION_ERR: 1585 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1586 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1587 break; 1588 case MAT_ROW_ORIENTED: 1589 a->roworiented = flg; 1590 1591 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1592 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1593 break; 1594 case MAT_NEW_DIAGONALS: 1595 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1596 break; 1597 case MAT_IGNORE_OFF_PROC_ENTRIES: 1598 a->donotstash = flg; 1599 break; 1600 case MAT_USE_HASH_TABLE: 1601 a->ht_flag = flg; 1602 break; 1603 case MAT_SYMMETRIC: 1604 case MAT_STRUCTURALLY_SYMMETRIC: 1605 case MAT_HERMITIAN: 1606 case MAT_SYMMETRY_ETERNAL: 1607 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1608 break; 1609 default: 1610 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1611 } 1612 PetscFunctionReturn(0); 1613 } 1614 1615 #undef __FUNCT__ 1616 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1617 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1618 { 1619 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1620 Mat_SeqBAIJ *Aloc; 1621 Mat B; 1622 PetscErrorCode ierr; 1623 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1624 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1625 MatScalar *a; 1626 1627 PetscFunctionBegin; 1628 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1629 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1630 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1631 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1632 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1633 /* Do not know preallocation information, but must set block size */ 1634 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1635 } else { 1636 B = *matout; 1637 } 1638 1639 /* copy over the A part */ 1640 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1641 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1642 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1643 1644 for (i=0; i<mbs; i++) { 1645 rvals[0] = bs*(baij->rstartbs + i); 1646 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1647 for (j=ai[i]; j<ai[i+1]; j++) { 1648 col = (baij->cstartbs+aj[j])*bs; 1649 for (k=0; k<bs; k++) { 1650 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1651 1652 col++; a += bs; 1653 } 1654 } 1655 } 1656 /* copy over the B part */ 1657 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1658 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1659 for (i=0; i<mbs; i++) { 1660 rvals[0] = bs*(baij->rstartbs + i); 1661 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1662 for (j=ai[i]; j<ai[i+1]; j++) { 1663 col = baij->garray[aj[j]]*bs; 1664 for (k=0; k<bs; k++) { 1665 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1666 col++; 1667 a += bs; 1668 } 1669 } 1670 } 1671 ierr = PetscFree(rvals);CHKERRQ(ierr); 1672 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1673 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1674 1675 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1676 else { 1677 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1678 } 1679 PetscFunctionReturn(0); 1680 } 1681 1682 #undef __FUNCT__ 1683 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1684 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1685 { 1686 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1687 Mat a = baij->A,b = baij->B; 1688 PetscErrorCode ierr; 1689 PetscInt s1,s2,s3; 1690 1691 PetscFunctionBegin; 1692 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1693 if (rr) { 1694 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1695 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1696 /* Overlap communication with computation. */ 1697 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1698 } 1699 if (ll) { 1700 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1701 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1702 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1703 } 1704 /* scale the diagonal block */ 1705 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1706 1707 if (rr) { 1708 /* Do a scatter end and then right scale the off-diagonal block */ 1709 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1710 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1711 } 1712 PetscFunctionReturn(0); 1713 } 1714 1715 #undef __FUNCT__ 1716 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1717 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1718 { 1719 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1720 PetscInt *owners = A->rmap->range; 1721 PetscInt n = A->rmap->n; 1722 PetscSF sf; 1723 PetscInt *lrows; 1724 PetscSFNode *rrows; 1725 PetscInt r, p = 0, len = 0; 1726 PetscErrorCode ierr; 1727 1728 PetscFunctionBegin; 1729 /* Create SF where leaves are input rows and roots are owned rows */ 1730 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1731 for (r = 0; r < n; ++r) lrows[r] = -1; 1732 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 1733 for (r = 0; r < N; ++r) { 1734 const PetscInt idx = rows[r]; 1735 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); 1736 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1737 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1738 } 1739 if (A->nooffproczerorows) { 1740 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); 1741 lrows[len++] = idx - owners[p]; 1742 } else { 1743 rrows[r].rank = p; 1744 rrows[r].index = rows[r] - owners[p]; 1745 } 1746 } 1747 if (!A->nooffproczerorows) { 1748 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1749 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1750 /* Collect flags for rows to be zeroed */ 1751 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1752 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1753 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1754 /* Compress and put in row numbers */ 1755 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1756 } 1757 /* fix right hand side if needed */ 1758 if (x && b) { 1759 const PetscScalar *xx; 1760 PetscScalar *bb; 1761 1762 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1763 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1764 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1765 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1766 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1767 } 1768 1769 /* actually zap the local rows */ 1770 /* 1771 Zero the required rows. If the "diagonal block" of the matrix 1772 is square and the user wishes to set the diagonal we use separate 1773 code so that MatSetValues() is not called for each diagonal allocating 1774 new memory, thus calling lots of mallocs and slowing things down. 1775 1776 */ 1777 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1778 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1779 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1780 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1781 } else if (diag != 0.0) { 1782 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1783 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\ 1784 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1785 for (r = 0; r < len; ++r) { 1786 const PetscInt row = lrows[r] + A->rmap->rstart; 1787 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1788 } 1789 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1790 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1791 } else { 1792 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1793 } 1794 ierr = PetscFree(lrows);CHKERRQ(ierr); 1795 1796 /* only change matrix nonzero state if pattern was allowed to be changed */ 1797 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1798 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1799 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1800 } 1801 PetscFunctionReturn(0); 1802 } 1803 1804 #undef __FUNCT__ 1805 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1806 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1807 { 1808 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1809 PetscErrorCode ierr; 1810 PetscMPIInt n = A->rmap->n; 1811 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1812 PetscInt *lrows,*owners = A->rmap->range; 1813 PetscSFNode *rrows; 1814 PetscSF sf; 1815 const PetscScalar *xx; 1816 PetscScalar *bb,*mask; 1817 Vec xmask,lmask; 1818 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1819 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1820 PetscScalar *aa; 1821 1822 PetscFunctionBegin; 1823 /* Create SF where leaves are input rows and roots are owned rows */ 1824 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1825 for (r = 0; r < n; ++r) lrows[r] = -1; 1826 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1827 for (r = 0; r < N; ++r) { 1828 const PetscInt idx = rows[r]; 1829 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); 1830 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1831 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1832 } 1833 rrows[r].rank = p; 1834 rrows[r].index = rows[r] - owners[p]; 1835 } 1836 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1837 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1838 /* Collect flags for rows to be zeroed */ 1839 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1840 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1841 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1842 /* Compress and put in row numbers */ 1843 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1844 /* zero diagonal part of matrix */ 1845 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1846 /* handle off diagonal part of matrix */ 1847 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1848 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1849 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1850 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1851 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1852 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1853 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1854 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1855 if (x) { 1856 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1857 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1858 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1859 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1860 } 1861 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1862 /* remove zeroed rows of off diagonal matrix */ 1863 for (i = 0; i < len; ++i) { 1864 row = lrows[i]; 1865 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1866 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1867 for (k = 0; k < count; ++k) { 1868 aa[0] = 0.0; 1869 aa += bs; 1870 } 1871 } 1872 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1873 for (i = 0; i < l->B->rmap->N; ++i) { 1874 row = i/bs; 1875 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1876 for (k = 0; k < bs; ++k) { 1877 col = bs*baij->j[j] + k; 1878 if (PetscAbsScalar(mask[col])) { 1879 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1880 if (b) bb[i] -= aa[0]*xx[col]; 1881 aa[0] = 0.0; 1882 } 1883 } 1884 } 1885 } 1886 if (x) { 1887 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1888 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1889 } 1890 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1891 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1892 ierr = PetscFree(lrows);CHKERRQ(ierr); 1893 1894 /* only change matrix nonzero state if pattern was allowed to be changed */ 1895 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1896 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1897 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1898 } 1899 PetscFunctionReturn(0); 1900 } 1901 1902 #undef __FUNCT__ 1903 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1904 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1905 { 1906 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1907 PetscErrorCode ierr; 1908 1909 PetscFunctionBegin; 1910 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1911 PetscFunctionReturn(0); 1912 } 1913 1914 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1915 1916 #undef __FUNCT__ 1917 #define __FUNCT__ "MatEqual_MPIBAIJ" 1918 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1919 { 1920 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1921 Mat a,b,c,d; 1922 PetscBool flg; 1923 PetscErrorCode ierr; 1924 1925 PetscFunctionBegin; 1926 a = matA->A; b = matA->B; 1927 c = matB->A; d = matB->B; 1928 1929 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1930 if (flg) { 1931 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1932 } 1933 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1934 PetscFunctionReturn(0); 1935 } 1936 1937 #undef __FUNCT__ 1938 #define __FUNCT__ "MatCopy_MPIBAIJ" 1939 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1940 { 1941 PetscErrorCode ierr; 1942 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1943 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 1944 1945 PetscFunctionBegin; 1946 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1947 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1948 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1949 } else { 1950 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1951 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1952 } 1953 PetscFunctionReturn(0); 1954 } 1955 1956 #undef __FUNCT__ 1957 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1958 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1959 { 1960 PetscErrorCode ierr; 1961 1962 PetscFunctionBegin; 1963 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1964 PetscFunctionReturn(0); 1965 } 1966 1967 #undef __FUNCT__ 1968 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 1969 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 1970 { 1971 PetscErrorCode ierr; 1972 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 1973 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 1974 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 1975 1976 PetscFunctionBegin; 1977 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 1978 PetscFunctionReturn(0); 1979 } 1980 1981 #undef __FUNCT__ 1982 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1983 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1984 { 1985 PetscErrorCode ierr; 1986 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 1987 PetscBLASInt bnz,one=1; 1988 Mat_SeqBAIJ *x,*y; 1989 1990 PetscFunctionBegin; 1991 if (str == SAME_NONZERO_PATTERN) { 1992 PetscScalar alpha = a; 1993 x = (Mat_SeqBAIJ*)xx->A->data; 1994 y = (Mat_SeqBAIJ*)yy->A->data; 1995 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 1996 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 1997 x = (Mat_SeqBAIJ*)xx->B->data; 1998 y = (Mat_SeqBAIJ*)yy->B->data; 1999 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2000 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2001 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2002 } else { 2003 Mat B; 2004 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2005 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2006 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2007 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2008 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2009 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2010 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2011 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2012 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2013 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2014 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2015 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2016 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2017 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2018 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2019 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2020 } 2021 PetscFunctionReturn(0); 2022 } 2023 2024 #undef __FUNCT__ 2025 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2026 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2027 { 2028 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2029 PetscErrorCode ierr; 2030 2031 PetscFunctionBegin; 2032 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2033 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2034 PetscFunctionReturn(0); 2035 } 2036 2037 #undef __FUNCT__ 2038 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2039 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2040 { 2041 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2042 PetscErrorCode ierr; 2043 2044 PetscFunctionBegin; 2045 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2046 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2047 PetscFunctionReturn(0); 2048 } 2049 2050 #undef __FUNCT__ 2051 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2052 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2053 { 2054 PetscErrorCode ierr; 2055 IS iscol_local; 2056 PetscInt csize; 2057 2058 PetscFunctionBegin; 2059 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2060 if (call == MAT_REUSE_MATRIX) { 2061 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2062 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2063 } else { 2064 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2065 } 2066 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2067 if (call == MAT_INITIAL_MATRIX) { 2068 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2069 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2070 } 2071 PetscFunctionReturn(0); 2072 } 2073 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2074 #undef __FUNCT__ 2075 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2076 /* 2077 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2078 in local and then by concatenating the local matrices the end result. 2079 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2080 */ 2081 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2082 { 2083 PetscErrorCode ierr; 2084 PetscMPIInt rank,size; 2085 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2086 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2087 Mat M,Mreuse; 2088 MatScalar *vwork,*aa; 2089 MPI_Comm comm; 2090 IS isrow_new, iscol_new; 2091 PetscBool idflag,allrows, allcols; 2092 Mat_SeqBAIJ *aij; 2093 2094 PetscFunctionBegin; 2095 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2096 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2097 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2098 /* The compression and expansion should be avoided. Doesn't point 2099 out errors, might change the indices, hence buggey */ 2100 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2101 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2102 2103 /* Check for special case: each processor gets entire matrix columns */ 2104 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2105 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2106 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2107 else allcols = PETSC_FALSE; 2108 2109 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2110 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2111 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2112 else allrows = PETSC_FALSE; 2113 2114 if (call == MAT_REUSE_MATRIX) { 2115 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2116 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2117 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2118 } else { 2119 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2120 } 2121 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2122 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2123 /* 2124 m - number of local rows 2125 n - number of columns (same on all processors) 2126 rstart - first row in new global matrix generated 2127 */ 2128 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2129 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2130 m = m/bs; 2131 n = n/bs; 2132 2133 if (call == MAT_INITIAL_MATRIX) { 2134 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2135 ii = aij->i; 2136 jj = aij->j; 2137 2138 /* 2139 Determine the number of non-zeros in the diagonal and off-diagonal 2140 portions of the matrix in order to do correct preallocation 2141 */ 2142 2143 /* first get start and end of "diagonal" columns */ 2144 if (csize == PETSC_DECIDE) { 2145 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2146 if (mglobal == n*bs) { /* square matrix */ 2147 nlocal = m; 2148 } else { 2149 nlocal = n/size + ((n % size) > rank); 2150 } 2151 } else { 2152 nlocal = csize/bs; 2153 } 2154 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2155 rstart = rend - nlocal; 2156 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); 2157 2158 /* next, compute all the lengths */ 2159 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2160 for (i=0; i<m; i++) { 2161 jend = ii[i+1] - ii[i]; 2162 olen = 0; 2163 dlen = 0; 2164 for (j=0; j<jend; j++) { 2165 if (*jj < rstart || *jj >= rend) olen++; 2166 else dlen++; 2167 jj++; 2168 } 2169 olens[i] = olen; 2170 dlens[i] = dlen; 2171 } 2172 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2173 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2174 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2175 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2176 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2177 } else { 2178 PetscInt ml,nl; 2179 2180 M = *newmat; 2181 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2182 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2183 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2184 /* 2185 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2186 rather than the slower MatSetValues(). 2187 */ 2188 M->was_assembled = PETSC_TRUE; 2189 M->assembled = PETSC_FALSE; 2190 } 2191 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2192 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2193 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2194 ii = aij->i; 2195 jj = aij->j; 2196 aa = aij->a; 2197 for (i=0; i<m; i++) { 2198 row = rstart/bs + i; 2199 nz = ii[i+1] - ii[i]; 2200 cwork = jj; jj += nz; 2201 vwork = aa; aa += nz*bs*bs; 2202 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2203 } 2204 2205 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2206 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2207 *newmat = M; 2208 2209 /* save submatrix used in processor for next request */ 2210 if (call == MAT_INITIAL_MATRIX) { 2211 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2212 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2213 } 2214 PetscFunctionReturn(0); 2215 } 2216 2217 #undef __FUNCT__ 2218 #define __FUNCT__ "MatPermute_MPIBAIJ" 2219 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2220 { 2221 MPI_Comm comm,pcomm; 2222 PetscInt clocal_size,nrows; 2223 const PetscInt *rows; 2224 PetscMPIInt size; 2225 IS crowp,lcolp; 2226 PetscErrorCode ierr; 2227 2228 PetscFunctionBegin; 2229 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2230 /* make a collective version of 'rowp' */ 2231 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2232 if (pcomm==comm) { 2233 crowp = rowp; 2234 } else { 2235 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2236 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2237 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2238 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2239 } 2240 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2241 /* make a local version of 'colp' */ 2242 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2243 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2244 if (size==1) { 2245 lcolp = colp; 2246 } else { 2247 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2248 } 2249 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2250 /* now we just get the submatrix */ 2251 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2252 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2253 /* clean up */ 2254 if (pcomm!=comm) { 2255 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2256 } 2257 if (size>1) { 2258 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2259 } 2260 PetscFunctionReturn(0); 2261 } 2262 2263 #undef __FUNCT__ 2264 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2265 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2266 { 2267 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2268 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2269 2270 PetscFunctionBegin; 2271 if (nghosts) *nghosts = B->nbs; 2272 if (ghosts) *ghosts = baij->garray; 2273 PetscFunctionReturn(0); 2274 } 2275 2276 #undef __FUNCT__ 2277 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2278 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2279 { 2280 Mat B; 2281 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2282 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2283 Mat_SeqAIJ *b; 2284 PetscErrorCode ierr; 2285 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2286 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2287 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2288 2289 PetscFunctionBegin; 2290 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2291 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2292 2293 /* ---------------------------------------------------------------- 2294 Tell every processor the number of nonzeros per row 2295 */ 2296 ierr = PetscMalloc1((A->rmap->N/bs),&lens);CHKERRQ(ierr); 2297 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2298 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]; 2299 } 2300 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2301 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2302 displs = recvcounts + size; 2303 for (i=0; i<size; i++) { 2304 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2305 displs[i] = A->rmap->range[i]/bs; 2306 } 2307 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2308 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2309 #else 2310 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2311 #endif 2312 /* --------------------------------------------------------------- 2313 Create the sequential matrix of the same type as the local block diagonal 2314 */ 2315 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2316 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2317 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2318 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2319 b = (Mat_SeqAIJ*)B->data; 2320 2321 /*-------------------------------------------------------------------- 2322 Copy my part of matrix column indices over 2323 */ 2324 sendcount = ad->nz + bd->nz; 2325 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2326 a_jsendbuf = ad->j; 2327 b_jsendbuf = bd->j; 2328 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2329 cnt = 0; 2330 for (i=0; i<n; i++) { 2331 2332 /* put in lower diagonal portion */ 2333 m = bd->i[i+1] - bd->i[i]; 2334 while (m > 0) { 2335 /* is it above diagonal (in bd (compressed) numbering) */ 2336 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2337 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2338 m--; 2339 } 2340 2341 /* put in diagonal portion */ 2342 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2343 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2344 } 2345 2346 /* put in upper diagonal portion */ 2347 while (m-- > 0) { 2348 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2349 } 2350 } 2351 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2352 2353 /*-------------------------------------------------------------------- 2354 Gather all column indices to all processors 2355 */ 2356 for (i=0; i<size; i++) { 2357 recvcounts[i] = 0; 2358 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2359 recvcounts[i] += lens[j]; 2360 } 2361 } 2362 displs[0] = 0; 2363 for (i=1; i<size; i++) { 2364 displs[i] = displs[i-1] + recvcounts[i-1]; 2365 } 2366 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2367 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2368 #else 2369 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2370 #endif 2371 /*-------------------------------------------------------------------- 2372 Assemble the matrix into useable form (note numerical values not yet set) 2373 */ 2374 /* set the b->ilen (length of each row) values */ 2375 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2376 /* set the b->i indices */ 2377 b->i[0] = 0; 2378 for (i=1; i<=A->rmap->N/bs; i++) { 2379 b->i[i] = b->i[i-1] + lens[i-1]; 2380 } 2381 ierr = PetscFree(lens);CHKERRQ(ierr); 2382 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2383 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2384 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2385 2386 if (A->symmetric) { 2387 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2388 } else if (A->hermitian) { 2389 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2390 } else if (A->structurally_symmetric) { 2391 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2392 } 2393 *newmat = B; 2394 PetscFunctionReturn(0); 2395 } 2396 2397 #undef __FUNCT__ 2398 #define __FUNCT__ "MatSOR_MPIBAIJ" 2399 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2400 { 2401 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2402 PetscErrorCode ierr; 2403 Vec bb1 = 0; 2404 2405 PetscFunctionBegin; 2406 if (flag == SOR_APPLY_UPPER) { 2407 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2408 PetscFunctionReturn(0); 2409 } 2410 2411 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2412 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2413 } 2414 2415 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2416 if (flag & SOR_ZERO_INITIAL_GUESS) { 2417 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2418 its--; 2419 } 2420 2421 while (its--) { 2422 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2423 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2424 2425 /* update rhs: bb1 = bb - B*x */ 2426 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2427 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2428 2429 /* local sweep */ 2430 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2431 } 2432 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2433 if (flag & SOR_ZERO_INITIAL_GUESS) { 2434 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2435 its--; 2436 } 2437 while (its--) { 2438 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2439 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2440 2441 /* update rhs: bb1 = bb - B*x */ 2442 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2443 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2444 2445 /* local sweep */ 2446 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2447 } 2448 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2449 if (flag & SOR_ZERO_INITIAL_GUESS) { 2450 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2451 its--; 2452 } 2453 while (its--) { 2454 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2455 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2456 2457 /* update rhs: bb1 = bb - B*x */ 2458 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2459 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2460 2461 /* local sweep */ 2462 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2463 } 2464 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2465 2466 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2467 PetscFunctionReturn(0); 2468 } 2469 2470 #undef __FUNCT__ 2471 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2472 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2473 { 2474 PetscErrorCode ierr; 2475 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2476 PetscInt N,i,*garray = aij->garray; 2477 PetscInt ib,jb,bs = A->rmap->bs; 2478 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2479 MatScalar *a_val = a_aij->a; 2480 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2481 MatScalar *b_val = b_aij->a; 2482 PetscReal *work; 2483 2484 PetscFunctionBegin; 2485 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2486 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2487 if (type == NORM_2) { 2488 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2489 for (jb=0; jb<bs; jb++) { 2490 for (ib=0; ib<bs; ib++) { 2491 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2492 a_val++; 2493 } 2494 } 2495 } 2496 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2497 for (jb=0; jb<bs; jb++) { 2498 for (ib=0; ib<bs; ib++) { 2499 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2500 b_val++; 2501 } 2502 } 2503 } 2504 } else if (type == NORM_1) { 2505 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2506 for (jb=0; jb<bs; jb++) { 2507 for (ib=0; ib<bs; ib++) { 2508 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2509 a_val++; 2510 } 2511 } 2512 } 2513 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2514 for (jb=0; jb<bs; jb++) { 2515 for (ib=0; ib<bs; ib++) { 2516 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2517 b_val++; 2518 } 2519 } 2520 } 2521 } else if (type == NORM_INFINITY) { 2522 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2523 for (jb=0; jb<bs; jb++) { 2524 for (ib=0; ib<bs; ib++) { 2525 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2526 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2527 a_val++; 2528 } 2529 } 2530 } 2531 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2532 for (jb=0; jb<bs; jb++) { 2533 for (ib=0; ib<bs; ib++) { 2534 int col = garray[b_aij->j[i]] * bs + jb; 2535 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2536 b_val++; 2537 } 2538 } 2539 } 2540 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2541 if (type == NORM_INFINITY) { 2542 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2543 } else { 2544 ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2545 } 2546 ierr = PetscFree(work);CHKERRQ(ierr); 2547 if (type == NORM_2) { 2548 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2549 } 2550 PetscFunctionReturn(0); 2551 } 2552 2553 #undef __FUNCT__ 2554 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2555 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2556 { 2557 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2558 PetscErrorCode ierr; 2559 2560 PetscFunctionBegin; 2561 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2562 PetscFunctionReturn(0); 2563 } 2564 2565 2566 /* -------------------------------------------------------------------*/ 2567 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2568 MatGetRow_MPIBAIJ, 2569 MatRestoreRow_MPIBAIJ, 2570 MatMult_MPIBAIJ, 2571 /* 4*/ MatMultAdd_MPIBAIJ, 2572 MatMultTranspose_MPIBAIJ, 2573 MatMultTransposeAdd_MPIBAIJ, 2574 0, 2575 0, 2576 0, 2577 /*10*/ 0, 2578 0, 2579 0, 2580 MatSOR_MPIBAIJ, 2581 MatTranspose_MPIBAIJ, 2582 /*15*/ MatGetInfo_MPIBAIJ, 2583 MatEqual_MPIBAIJ, 2584 MatGetDiagonal_MPIBAIJ, 2585 MatDiagonalScale_MPIBAIJ, 2586 MatNorm_MPIBAIJ, 2587 /*20*/ MatAssemblyBegin_MPIBAIJ, 2588 MatAssemblyEnd_MPIBAIJ, 2589 MatSetOption_MPIBAIJ, 2590 MatZeroEntries_MPIBAIJ, 2591 /*24*/ MatZeroRows_MPIBAIJ, 2592 0, 2593 0, 2594 0, 2595 0, 2596 /*29*/ MatSetUp_MPIBAIJ, 2597 0, 2598 0, 2599 0, 2600 0, 2601 /*34*/ MatDuplicate_MPIBAIJ, 2602 0, 2603 0, 2604 0, 2605 0, 2606 /*39*/ MatAXPY_MPIBAIJ, 2607 MatGetSubMatrices_MPIBAIJ, 2608 MatIncreaseOverlap_MPIBAIJ, 2609 MatGetValues_MPIBAIJ, 2610 MatCopy_MPIBAIJ, 2611 /*44*/ 0, 2612 MatScale_MPIBAIJ, 2613 0, 2614 0, 2615 MatZeroRowsColumns_MPIBAIJ, 2616 /*49*/ 0, 2617 0, 2618 0, 2619 0, 2620 0, 2621 /*54*/ MatFDColoringCreate_MPIXAIJ, 2622 0, 2623 MatSetUnfactored_MPIBAIJ, 2624 MatPermute_MPIBAIJ, 2625 MatSetValuesBlocked_MPIBAIJ, 2626 /*59*/ MatGetSubMatrix_MPIBAIJ, 2627 MatDestroy_MPIBAIJ, 2628 MatView_MPIBAIJ, 2629 0, 2630 0, 2631 /*64*/ 0, 2632 0, 2633 0, 2634 0, 2635 0, 2636 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2637 0, 2638 0, 2639 0, 2640 0, 2641 /*74*/ 0, 2642 MatFDColoringApply_BAIJ, 2643 0, 2644 0, 2645 0, 2646 /*79*/ 0, 2647 0, 2648 0, 2649 0, 2650 MatLoad_MPIBAIJ, 2651 /*84*/ 0, 2652 0, 2653 0, 2654 0, 2655 0, 2656 /*89*/ 0, 2657 0, 2658 0, 2659 0, 2660 0, 2661 /*94*/ 0, 2662 0, 2663 0, 2664 0, 2665 0, 2666 /*99*/ 0, 2667 0, 2668 0, 2669 0, 2670 0, 2671 /*104*/0, 2672 MatRealPart_MPIBAIJ, 2673 MatImaginaryPart_MPIBAIJ, 2674 0, 2675 0, 2676 /*109*/0, 2677 0, 2678 0, 2679 0, 2680 0, 2681 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2682 0, 2683 MatGetGhosts_MPIBAIJ, 2684 0, 2685 0, 2686 /*119*/0, 2687 0, 2688 0, 2689 0, 2690 MatGetMultiProcBlock_MPIBAIJ, 2691 /*124*/0, 2692 MatGetColumnNorms_MPIBAIJ, 2693 MatInvertBlockDiagonal_MPIBAIJ, 2694 0, 2695 0, 2696 /*129*/ 0, 2697 0, 2698 0, 2699 0, 2700 0, 2701 /*134*/ 0, 2702 0, 2703 0, 2704 0, 2705 0, 2706 /*139*/ 0, 2707 0, 2708 0, 2709 MatFDColoringSetUp_MPIXAIJ 2710 }; 2711 2712 #undef __FUNCT__ 2713 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2714 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2715 { 2716 PetscFunctionBegin; 2717 *a = ((Mat_MPIBAIJ*)A->data)->A; 2718 PetscFunctionReturn(0); 2719 } 2720 2721 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2722 2723 #undef __FUNCT__ 2724 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2725 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2726 { 2727 PetscInt m,rstart,cstart,cend; 2728 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2729 const PetscInt *JJ =0; 2730 PetscScalar *values=0; 2731 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2732 PetscErrorCode ierr; 2733 2734 PetscFunctionBegin; 2735 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2736 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2737 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2738 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2739 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2740 m = B->rmap->n/bs; 2741 rstart = B->rmap->rstart/bs; 2742 cstart = B->cmap->rstart/bs; 2743 cend = B->cmap->rend/bs; 2744 2745 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2746 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2747 for (i=0; i<m; i++) { 2748 nz = ii[i+1] - ii[i]; 2749 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2750 nz_max = PetscMax(nz_max,nz); 2751 JJ = jj + ii[i]; 2752 for (j=0; j<nz; j++) { 2753 if (*JJ >= cstart) break; 2754 JJ++; 2755 } 2756 d = 0; 2757 for (; j<nz; j++) { 2758 if (*JJ++ >= cend) break; 2759 d++; 2760 } 2761 d_nnz[i] = d; 2762 o_nnz[i] = nz - d; 2763 } 2764 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2765 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2766 2767 values = (PetscScalar*)V; 2768 if (!values) { 2769 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2770 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2771 } 2772 for (i=0; i<m; i++) { 2773 PetscInt row = i + rstart; 2774 PetscInt ncols = ii[i+1] - ii[i]; 2775 const PetscInt *icols = jj + ii[i]; 2776 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2777 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2778 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2779 } else { /* block ordering does not match so we can only insert one block at a time. */ 2780 PetscInt j; 2781 for (j=0; j<ncols; j++) { 2782 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2783 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2784 } 2785 } 2786 } 2787 2788 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2789 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2790 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2791 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2792 PetscFunctionReturn(0); 2793 } 2794 2795 #undef __FUNCT__ 2796 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2797 /*@C 2798 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2799 (the default parallel PETSc format). 2800 2801 Collective on MPI_Comm 2802 2803 Input Parameters: 2804 + B - the matrix 2805 . bs - the block size 2806 . i - the indices into j for the start of each local row (starts with zero) 2807 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2808 - v - optional values in the matrix 2809 2810 Level: developer 2811 2812 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2813 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2814 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2815 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2816 block column and the second index is over columns within a block. 2817 2818 .keywords: matrix, aij, compressed row, sparse, parallel 2819 2820 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2821 @*/ 2822 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2823 { 2824 PetscErrorCode ierr; 2825 2826 PetscFunctionBegin; 2827 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2828 PetscValidType(B,1); 2829 PetscValidLogicalCollectiveInt(B,bs,2); 2830 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2831 PetscFunctionReturn(0); 2832 } 2833 2834 #undef __FUNCT__ 2835 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2836 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2837 { 2838 Mat_MPIBAIJ *b; 2839 PetscErrorCode ierr; 2840 PetscInt i; 2841 2842 PetscFunctionBegin; 2843 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2844 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2845 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2846 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2847 2848 if (d_nnz) { 2849 for (i=0; i<B->rmap->n/bs; i++) { 2850 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]); 2851 } 2852 } 2853 if (o_nnz) { 2854 for (i=0; i<B->rmap->n/bs; i++) { 2855 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]); 2856 } 2857 } 2858 2859 b = (Mat_MPIBAIJ*)B->data; 2860 b->bs2 = bs*bs; 2861 b->mbs = B->rmap->n/bs; 2862 b->nbs = B->cmap->n/bs; 2863 b->Mbs = B->rmap->N/bs; 2864 b->Nbs = B->cmap->N/bs; 2865 2866 for (i=0; i<=b->size; i++) { 2867 b->rangebs[i] = B->rmap->range[i]/bs; 2868 } 2869 b->rstartbs = B->rmap->rstart/bs; 2870 b->rendbs = B->rmap->rend/bs; 2871 b->cstartbs = B->cmap->rstart/bs; 2872 b->cendbs = B->cmap->rend/bs; 2873 2874 if (!B->preallocated) { 2875 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2876 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2877 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2878 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2879 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2880 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2881 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2882 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2883 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 2884 } 2885 2886 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2887 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2888 B->preallocated = PETSC_TRUE; 2889 PetscFunctionReturn(0); 2890 } 2891 2892 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2893 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2894 2895 #undef __FUNCT__ 2896 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 2897 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 2898 { 2899 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2900 PetscErrorCode ierr; 2901 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 2902 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 2903 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 2904 2905 PetscFunctionBegin; 2906 ierr = PetscMalloc1((M+1),&ii);CHKERRQ(ierr); 2907 ii[0] = 0; 2908 for (i=0; i<M; i++) { 2909 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]); 2910 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]); 2911 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 2912 /* remove one from count of matrix has diagonal */ 2913 for (j=id[i]; j<id[i+1]; j++) { 2914 if (jd[j] == i) {ii[i+1]--;break;} 2915 } 2916 } 2917 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 2918 cnt = 0; 2919 for (i=0; i<M; i++) { 2920 for (j=io[i]; j<io[i+1]; j++) { 2921 if (garray[jo[j]] > rstart) break; 2922 jj[cnt++] = garray[jo[j]]; 2923 } 2924 for (k=id[i]; k<id[i+1]; k++) { 2925 if (jd[k] != i) { 2926 jj[cnt++] = rstart + jd[k]; 2927 } 2928 } 2929 for (; j<io[i+1]; j++) { 2930 jj[cnt++] = garray[jo[j]]; 2931 } 2932 } 2933 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 2934 PetscFunctionReturn(0); 2935 } 2936 2937 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2938 2939 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 2940 2941 #undef __FUNCT__ 2942 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 2943 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 2944 { 2945 PetscErrorCode ierr; 2946 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2947 Mat B; 2948 Mat_MPIAIJ *b; 2949 2950 PetscFunctionBegin; 2951 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 2952 2953 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2954 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 2955 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2956 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 2957 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 2958 b = (Mat_MPIAIJ*) B->data; 2959 2960 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 2961 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2962 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 2963 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 2964 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 2965 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2966 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2967 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2968 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2969 if (reuse == MAT_REUSE_MATRIX) { 2970 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 2971 } else { 2972 *newmat = B; 2973 } 2974 PetscFunctionReturn(0); 2975 } 2976 2977 #if defined(PETSC_HAVE_MUMPS) 2978 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2979 #endif 2980 2981 /*MC 2982 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2983 2984 Options Database Keys: 2985 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2986 . -mat_block_size <bs> - set the blocksize used to store the matrix 2987 - -mat_use_hash_table <fact> 2988 2989 Level: beginner 2990 2991 .seealso: MatCreateMPIBAIJ 2992 M*/ 2993 2994 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 2995 2996 #undef __FUNCT__ 2997 #define __FUNCT__ "MatCreate_MPIBAIJ" 2998 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 2999 { 3000 Mat_MPIBAIJ *b; 3001 PetscErrorCode ierr; 3002 PetscBool flg; 3003 3004 PetscFunctionBegin; 3005 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3006 B->data = (void*)b; 3007 3008 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3009 B->assembled = PETSC_FALSE; 3010 3011 B->insertmode = NOT_SET_VALUES; 3012 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3013 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3014 3015 /* build local table of row and column ownerships */ 3016 ierr = PetscMalloc1((b->size+1),&b->rangebs);CHKERRQ(ierr); 3017 3018 /* build cache for off array entries formed */ 3019 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3020 3021 b->donotstash = PETSC_FALSE; 3022 b->colmap = NULL; 3023 b->garray = NULL; 3024 b->roworiented = PETSC_TRUE; 3025 3026 /* stuff used in block assembly */ 3027 b->barray = 0; 3028 3029 /* stuff used for matrix vector multiply */ 3030 b->lvec = 0; 3031 b->Mvctx = 0; 3032 3033 /* stuff for MatGetRow() */ 3034 b->rowindices = 0; 3035 b->rowvalues = 0; 3036 b->getrowactive = PETSC_FALSE; 3037 3038 /* hash table stuff */ 3039 b->ht = 0; 3040 b->hd = 0; 3041 b->ht_size = 0; 3042 b->ht_flag = PETSC_FALSE; 3043 b->ht_fact = 0; 3044 b->ht_total_ct = 0; 3045 b->ht_insert_ct = 0; 3046 3047 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3048 b->ijonly = PETSC_FALSE; 3049 3050 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3051 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 3052 if (flg) { 3053 PetscReal fact = 1.39; 3054 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3055 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3056 if (fact <= 1.0) fact = 1.39; 3057 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3058 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3059 } 3060 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3061 3062 #if defined(PETSC_HAVE_MUMPS) 3063 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3064 #endif 3065 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3066 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3067 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3068 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3069 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3070 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3071 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3072 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3073 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3074 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3075 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3076 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3077 PetscFunctionReturn(0); 3078 } 3079 3080 /*MC 3081 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3082 3083 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3084 and MATMPIBAIJ otherwise. 3085 3086 Options Database Keys: 3087 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3088 3089 Level: beginner 3090 3091 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3092 M*/ 3093 3094 #undef __FUNCT__ 3095 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3096 /*@C 3097 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3098 (block compressed row). For good matrix assembly performance 3099 the user should preallocate the matrix storage by setting the parameters 3100 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3101 performance can be increased by more than a factor of 50. 3102 3103 Collective on Mat 3104 3105 Input Parameters: 3106 + B - the matrix 3107 . bs - size of block 3108 . d_nz - number of block nonzeros per block row in diagonal portion of local 3109 submatrix (same for all local rows) 3110 . d_nnz - array containing the number of block nonzeros in the various block rows 3111 of the in diagonal portion of the local (possibly different for each block 3112 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3113 set it even if it is zero. 3114 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3115 submatrix (same for all local rows). 3116 - o_nnz - array containing the number of nonzeros in the various block rows of the 3117 off-diagonal portion of the local submatrix (possibly different for 3118 each block row) or NULL. 3119 3120 If the *_nnz parameter is given then the *_nz parameter is ignored 3121 3122 Options Database Keys: 3123 + -mat_block_size - size of the blocks to use 3124 - -mat_use_hash_table <fact> 3125 3126 Notes: 3127 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3128 than it must be used on all processors that share the object for that argument. 3129 3130 Storage Information: 3131 For a square global matrix we define each processor's diagonal portion 3132 to be its local rows and the corresponding columns (a square submatrix); 3133 each processor's off-diagonal portion encompasses the remainder of the 3134 local matrix (a rectangular submatrix). 3135 3136 The user can specify preallocated storage for the diagonal part of 3137 the local submatrix with either d_nz or d_nnz (not both). Set 3138 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3139 memory allocation. Likewise, specify preallocated storage for the 3140 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3141 3142 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3143 the figure below we depict these three local rows and all columns (0-11). 3144 3145 .vb 3146 0 1 2 3 4 5 6 7 8 9 10 11 3147 -------------------------- 3148 row 3 |o o o d d d o o o o o o 3149 row 4 |o o o d d d o o o o o o 3150 row 5 |o o o d d d o o o o o o 3151 -------------------------- 3152 .ve 3153 3154 Thus, any entries in the d locations are stored in the d (diagonal) 3155 submatrix, and any entries in the o locations are stored in the 3156 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3157 stored simply in the MATSEQBAIJ format for compressed row storage. 3158 3159 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3160 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3161 In general, for PDE problems in which most nonzeros are near the diagonal, 3162 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3163 or you will get TERRIBLE performance; see the users' manual chapter on 3164 matrices. 3165 3166 You can call MatGetInfo() to get information on how effective the preallocation was; 3167 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3168 You can also run with the option -info and look for messages with the string 3169 malloc in them to see if additional memory allocation was needed. 3170 3171 Level: intermediate 3172 3173 .keywords: matrix, block, aij, compressed row, sparse, parallel 3174 3175 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3176 @*/ 3177 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3178 { 3179 PetscErrorCode ierr; 3180 3181 PetscFunctionBegin; 3182 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3183 PetscValidType(B,1); 3184 PetscValidLogicalCollectiveInt(B,bs,2); 3185 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); 3186 PetscFunctionReturn(0); 3187 } 3188 3189 #undef __FUNCT__ 3190 #define __FUNCT__ "MatCreateBAIJ" 3191 /*@C 3192 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3193 (block compressed row). For good matrix assembly performance 3194 the user should preallocate the matrix storage by setting the parameters 3195 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3196 performance can be increased by more than a factor of 50. 3197 3198 Collective on MPI_Comm 3199 3200 Input Parameters: 3201 + comm - MPI communicator 3202 . bs - size of blockk 3203 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3204 This value should be the same as the local size used in creating the 3205 y vector for the matrix-vector product y = Ax. 3206 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3207 This value should be the same as the local size used in creating the 3208 x vector for the matrix-vector product y = Ax. 3209 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3210 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3211 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3212 submatrix (same for all local rows) 3213 . d_nnz - array containing the number of nonzero blocks in the various block rows 3214 of the in diagonal portion of the local (possibly different for each block 3215 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3216 and set it even if it is zero. 3217 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3218 submatrix (same for all local rows). 3219 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3220 off-diagonal portion of the local submatrix (possibly different for 3221 each block row) or NULL. 3222 3223 Output Parameter: 3224 . A - the matrix 3225 3226 Options Database Keys: 3227 + -mat_block_size - size of the blocks to use 3228 - -mat_use_hash_table <fact> 3229 3230 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3231 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3232 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3233 3234 Notes: 3235 If the *_nnz parameter is given then the *_nz parameter is ignored 3236 3237 A nonzero block is any block that as 1 or more nonzeros in it 3238 3239 The user MUST specify either the local or global matrix dimensions 3240 (possibly both). 3241 3242 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3243 than it must be used on all processors that share the object for that argument. 3244 3245 Storage Information: 3246 For a square global matrix we define each processor's diagonal portion 3247 to be its local rows and the corresponding columns (a square submatrix); 3248 each processor's off-diagonal portion encompasses the remainder of the 3249 local matrix (a rectangular submatrix). 3250 3251 The user can specify preallocated storage for the diagonal part of 3252 the local submatrix with either d_nz or d_nnz (not both). Set 3253 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3254 memory allocation. Likewise, specify preallocated storage for the 3255 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3256 3257 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3258 the figure below we depict these three local rows and all columns (0-11). 3259 3260 .vb 3261 0 1 2 3 4 5 6 7 8 9 10 11 3262 -------------------------- 3263 row 3 |o o o d d d o o o o o o 3264 row 4 |o o o d d d o o o o o o 3265 row 5 |o o o d d d o o o o o o 3266 -------------------------- 3267 .ve 3268 3269 Thus, any entries in the d locations are stored in the d (diagonal) 3270 submatrix, and any entries in the o locations are stored in the 3271 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3272 stored simply in the MATSEQBAIJ format for compressed row storage. 3273 3274 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3275 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3276 In general, for PDE problems in which most nonzeros are near the diagonal, 3277 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3278 or you will get TERRIBLE performance; see the users' manual chapter on 3279 matrices. 3280 3281 Level: intermediate 3282 3283 .keywords: matrix, block, aij, compressed row, sparse, parallel 3284 3285 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3286 @*/ 3287 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) 3288 { 3289 PetscErrorCode ierr; 3290 PetscMPIInt size; 3291 3292 PetscFunctionBegin; 3293 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3294 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3295 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3296 if (size > 1) { 3297 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3298 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3299 } else { 3300 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3301 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3302 } 3303 PetscFunctionReturn(0); 3304 } 3305 3306 #undef __FUNCT__ 3307 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3308 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3309 { 3310 Mat mat; 3311 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3312 PetscErrorCode ierr; 3313 PetscInt len=0; 3314 3315 PetscFunctionBegin; 3316 *newmat = 0; 3317 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3318 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3319 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3320 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3321 3322 mat->factortype = matin->factortype; 3323 mat->preallocated = PETSC_TRUE; 3324 mat->assembled = PETSC_TRUE; 3325 mat->insertmode = NOT_SET_VALUES; 3326 3327 a = (Mat_MPIBAIJ*)mat->data; 3328 mat->rmap->bs = matin->rmap->bs; 3329 a->bs2 = oldmat->bs2; 3330 a->mbs = oldmat->mbs; 3331 a->nbs = oldmat->nbs; 3332 a->Mbs = oldmat->Mbs; 3333 a->Nbs = oldmat->Nbs; 3334 3335 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3336 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3337 3338 a->size = oldmat->size; 3339 a->rank = oldmat->rank; 3340 a->donotstash = oldmat->donotstash; 3341 a->roworiented = oldmat->roworiented; 3342 a->rowindices = 0; 3343 a->rowvalues = 0; 3344 a->getrowactive = PETSC_FALSE; 3345 a->barray = 0; 3346 a->rstartbs = oldmat->rstartbs; 3347 a->rendbs = oldmat->rendbs; 3348 a->cstartbs = oldmat->cstartbs; 3349 a->cendbs = oldmat->cendbs; 3350 3351 /* hash table stuff */ 3352 a->ht = 0; 3353 a->hd = 0; 3354 a->ht_size = 0; 3355 a->ht_flag = oldmat->ht_flag; 3356 a->ht_fact = oldmat->ht_fact; 3357 a->ht_total_ct = 0; 3358 a->ht_insert_ct = 0; 3359 3360 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3361 if (oldmat->colmap) { 3362 #if defined(PETSC_USE_CTABLE) 3363 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3364 #else 3365 ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr); 3366 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3367 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3368 #endif 3369 } else a->colmap = 0; 3370 3371 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3372 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3373 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3374 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3375 } else a->garray = 0; 3376 3377 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3378 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3379 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3380 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3381 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3382 3383 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3384 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3385 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3386 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3387 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3388 *newmat = mat; 3389 PetscFunctionReturn(0); 3390 } 3391 3392 #undef __FUNCT__ 3393 #define __FUNCT__ "MatLoad_MPIBAIJ" 3394 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3395 { 3396 PetscErrorCode ierr; 3397 int fd; 3398 PetscInt i,nz,j,rstart,rend; 3399 PetscScalar *vals,*buf; 3400 MPI_Comm comm; 3401 MPI_Status status; 3402 PetscMPIInt rank,size,maxnz; 3403 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3404 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3405 PetscInt jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax; 3406 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3407 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3408 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3409 3410 PetscFunctionBegin; 3411 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3412 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3413 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3414 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3415 if (bs < 0) bs = 1; 3416 3417 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3418 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3419 if (!rank) { 3420 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3421 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3422 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3423 } 3424 3425 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3426 3427 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3428 M = header[1]; N = header[2]; 3429 3430 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3431 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3432 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3433 3434 /* If global sizes are set, check if they are consistent with that given in the file */ 3435 if (sizesset) { 3436 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3437 } 3438 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); 3439 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); 3440 3441 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3442 3443 /* 3444 This code adds extra rows to make sure the number of rows is 3445 divisible by the blocksize 3446 */ 3447 Mbs = M/bs; 3448 extra_rows = bs - M + bs*Mbs; 3449 if (extra_rows == bs) extra_rows = 0; 3450 else Mbs++; 3451 if (extra_rows && !rank) { 3452 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3453 } 3454 3455 /* determine ownership of all rows */ 3456 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3457 mbs = Mbs/size + ((Mbs % size) > rank); 3458 m = mbs*bs; 3459 } else { /* User set */ 3460 m = newmat->rmap->n; 3461 mbs = m/bs; 3462 } 3463 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3464 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3465 3466 /* process 0 needs enough room for process with most rows */ 3467 if (!rank) { 3468 mmax = rowners[1]; 3469 for (i=2; i<=size; i++) { 3470 mmax = PetscMax(mmax,rowners[i]); 3471 } 3472 mmax*=bs; 3473 } else mmax = -1; /* unused, but compiler warns anyway */ 3474 3475 rowners[0] = 0; 3476 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3477 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3478 rstart = rowners[rank]; 3479 rend = rowners[rank+1]; 3480 3481 /* distribute row lengths to all processors */ 3482 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3483 if (!rank) { 3484 mend = m; 3485 if (size == 1) mend = mend - extra_rows; 3486 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3487 for (j=mend; j<m; j++) locrowlens[j] = 1; 3488 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3489 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3490 for (j=0; j<m; j++) { 3491 procsnz[0] += locrowlens[j]; 3492 } 3493 for (i=1; i<size; i++) { 3494 mend = browners[i+1] - browners[i]; 3495 if (i == size-1) mend = mend - extra_rows; 3496 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3497 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3498 /* calculate the number of nonzeros on each processor */ 3499 for (j=0; j<browners[i+1]-browners[i]; j++) { 3500 procsnz[i] += rowlengths[j]; 3501 } 3502 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3503 } 3504 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3505 } else { 3506 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3507 } 3508 3509 if (!rank) { 3510 /* determine max buffer needed and allocate it */ 3511 maxnz = procsnz[0]; 3512 for (i=1; i<size; i++) { 3513 maxnz = PetscMax(maxnz,procsnz[i]); 3514 } 3515 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3516 3517 /* read in my part of the matrix column indices */ 3518 nz = procsnz[0]; 3519 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3520 mycols = ibuf; 3521 if (size == 1) nz -= extra_rows; 3522 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3523 if (size == 1) { 3524 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3525 } 3526 3527 /* read in every ones (except the last) and ship off */ 3528 for (i=1; i<size-1; i++) { 3529 nz = procsnz[i]; 3530 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3531 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3532 } 3533 /* read in the stuff for the last proc */ 3534 if (size != 1) { 3535 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3536 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3537 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3538 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3539 } 3540 ierr = PetscFree(cols);CHKERRQ(ierr); 3541 } else { 3542 /* determine buffer space needed for message */ 3543 nz = 0; 3544 for (i=0; i<m; i++) { 3545 nz += locrowlens[i]; 3546 } 3547 ierr = PetscMalloc1((nz+1),&ibuf);CHKERRQ(ierr); 3548 mycols = ibuf; 3549 /* receive message of column indices*/ 3550 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3551 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3552 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3553 } 3554 3555 /* loop over local rows, determining number of off diagonal entries */ 3556 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3557 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3558 rowcount = 0; nzcount = 0; 3559 for (i=0; i<mbs; i++) { 3560 dcount = 0; 3561 odcount = 0; 3562 for (j=0; j<bs; j++) { 3563 kmax = locrowlens[rowcount]; 3564 for (k=0; k<kmax; k++) { 3565 tmp = mycols[nzcount++]/bs; 3566 if (!mask[tmp]) { 3567 mask[tmp] = 1; 3568 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3569 else masked1[dcount++] = tmp; 3570 } 3571 } 3572 rowcount++; 3573 } 3574 3575 dlens[i] = dcount; 3576 odlens[i] = odcount; 3577 3578 /* zero out the mask elements we set */ 3579 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3580 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3581 } 3582 3583 3584 if (!sizesset) { 3585 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3586 } 3587 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3588 3589 if (!rank) { 3590 ierr = PetscMalloc1((maxnz+1),&buf);CHKERRQ(ierr); 3591 /* read in my part of the matrix numerical values */ 3592 nz = procsnz[0]; 3593 vals = buf; 3594 mycols = ibuf; 3595 if (size == 1) nz -= extra_rows; 3596 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3597 if (size == 1) { 3598 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3599 } 3600 3601 /* insert into matrix */ 3602 jj = rstart*bs; 3603 for (i=0; i<m; i++) { 3604 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3605 mycols += locrowlens[i]; 3606 vals += locrowlens[i]; 3607 jj++; 3608 } 3609 /* read in other processors (except the last one) and ship out */ 3610 for (i=1; i<size-1; i++) { 3611 nz = procsnz[i]; 3612 vals = buf; 3613 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3614 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3615 } 3616 /* the last proc */ 3617 if (size != 1) { 3618 nz = procsnz[i] - extra_rows; 3619 vals = buf; 3620 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3621 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3622 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3623 } 3624 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3625 } else { 3626 /* receive numeric values */ 3627 ierr = PetscMalloc1((nz+1),&buf);CHKERRQ(ierr); 3628 3629 /* receive message of values*/ 3630 vals = buf; 3631 mycols = ibuf; 3632 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3633 3634 /* insert into matrix */ 3635 jj = rstart*bs; 3636 for (i=0; i<m; i++) { 3637 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3638 mycols += locrowlens[i]; 3639 vals += locrowlens[i]; 3640 jj++; 3641 } 3642 } 3643 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3644 ierr = PetscFree(buf);CHKERRQ(ierr); 3645 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3646 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3647 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3648 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3649 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3650 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3651 PetscFunctionReturn(0); 3652 } 3653 3654 #undef __FUNCT__ 3655 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3656 /*@ 3657 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3658 3659 Input Parameters: 3660 . mat - the matrix 3661 . fact - factor 3662 3663 Not Collective, each process can use a different factor 3664 3665 Level: advanced 3666 3667 Notes: 3668 This can also be set by the command line option: -mat_use_hash_table <fact> 3669 3670 .keywords: matrix, hashtable, factor, HT 3671 3672 .seealso: MatSetOption() 3673 @*/ 3674 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3675 { 3676 PetscErrorCode ierr; 3677 3678 PetscFunctionBegin; 3679 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3680 PetscFunctionReturn(0); 3681 } 3682 3683 #undef __FUNCT__ 3684 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3685 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3686 { 3687 Mat_MPIBAIJ *baij; 3688 3689 PetscFunctionBegin; 3690 baij = (Mat_MPIBAIJ*)mat->data; 3691 baij->ht_fact = fact; 3692 PetscFunctionReturn(0); 3693 } 3694 3695 #undef __FUNCT__ 3696 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3697 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3698 { 3699 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3700 3701 PetscFunctionBegin; 3702 if (Ad) *Ad = a->A; 3703 if (Ao) *Ao = a->B; 3704 if (colmap) *colmap = a->garray; 3705 PetscFunctionReturn(0); 3706 } 3707 3708 /* 3709 Special version for direct calls from Fortran (to eliminate two function call overheads 3710 */ 3711 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3712 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3713 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3714 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3715 #endif 3716 3717 #undef __FUNCT__ 3718 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3719 /*@C 3720 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3721 3722 Collective on Mat 3723 3724 Input Parameters: 3725 + mat - the matrix 3726 . min - number of input rows 3727 . im - input rows 3728 . nin - number of input columns 3729 . in - input columns 3730 . v - numerical values input 3731 - addvin - INSERT_VALUES or ADD_VALUES 3732 3733 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3734 3735 Level: advanced 3736 3737 .seealso: MatSetValuesBlocked() 3738 @*/ 3739 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3740 { 3741 /* convert input arguments to C version */ 3742 Mat mat = *matin; 3743 PetscInt m = *min, n = *nin; 3744 InsertMode addv = *addvin; 3745 3746 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3747 const MatScalar *value; 3748 MatScalar *barray = baij->barray; 3749 PetscBool roworiented = baij->roworiented; 3750 PetscErrorCode ierr; 3751 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3752 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3753 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3754 3755 PetscFunctionBegin; 3756 /* tasks normally handled by MatSetValuesBlocked() */ 3757 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3758 #if defined(PETSC_USE_DEBUG) 3759 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3760 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3761 #endif 3762 if (mat->assembled) { 3763 mat->was_assembled = PETSC_TRUE; 3764 mat->assembled = PETSC_FALSE; 3765 } 3766 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3767 3768 3769 if (!barray) { 3770 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3771 baij->barray = barray; 3772 } 3773 3774 if (roworiented) stepval = (n-1)*bs; 3775 else stepval = (m-1)*bs; 3776 3777 for (i=0; i<m; i++) { 3778 if (im[i] < 0) continue; 3779 #if defined(PETSC_USE_DEBUG) 3780 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); 3781 #endif 3782 if (im[i] >= rstart && im[i] < rend) { 3783 row = im[i] - rstart; 3784 for (j=0; j<n; j++) { 3785 /* If NumCol = 1 then a copy is not required */ 3786 if ((roworiented) && (n == 1)) { 3787 barray = (MatScalar*)v + i*bs2; 3788 } else if ((!roworiented) && (m == 1)) { 3789 barray = (MatScalar*)v + j*bs2; 3790 } else { /* Here a copy is required */ 3791 if (roworiented) { 3792 value = v + i*(stepval+bs)*bs + j*bs; 3793 } else { 3794 value = v + j*(stepval+bs)*bs + i*bs; 3795 } 3796 for (ii=0; ii<bs; ii++,value+=stepval) { 3797 for (jj=0; jj<bs; jj++) { 3798 *barray++ = *value++; 3799 } 3800 } 3801 barray -=bs2; 3802 } 3803 3804 if (in[j] >= cstart && in[j] < cend) { 3805 col = in[j] - cstart; 3806 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3807 } else if (in[j] < 0) continue; 3808 #if defined(PETSC_USE_DEBUG) 3809 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); 3810 #endif 3811 else { 3812 if (mat->was_assembled) { 3813 if (!baij->colmap) { 3814 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3815 } 3816 3817 #if defined(PETSC_USE_DEBUG) 3818 #if defined(PETSC_USE_CTABLE) 3819 { PetscInt data; 3820 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3821 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3822 } 3823 #else 3824 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3825 #endif 3826 #endif 3827 #if defined(PETSC_USE_CTABLE) 3828 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3829 col = (col - 1)/bs; 3830 #else 3831 col = (baij->colmap[in[j]] - 1)/bs; 3832 #endif 3833 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3834 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3835 col = in[j]; 3836 } 3837 } else col = in[j]; 3838 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3839 } 3840 } 3841 } else { 3842 if (!baij->donotstash) { 3843 if (roworiented) { 3844 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3845 } else { 3846 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3847 } 3848 } 3849 } 3850 } 3851 3852 /* task normally handled by MatSetValuesBlocked() */ 3853 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3854 PetscFunctionReturn(0); 3855 } 3856 3857 #undef __FUNCT__ 3858 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3859 /*@ 3860 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3861 CSR format the local rows. 3862 3863 Collective on MPI_Comm 3864 3865 Input Parameters: 3866 + comm - MPI communicator 3867 . bs - the block size, only a block size of 1 is supported 3868 . m - number of local rows (Cannot be PETSC_DECIDE) 3869 . n - This value should be the same as the local size used in creating the 3870 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3871 calculated if N is given) For square matrices n is almost always m. 3872 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3873 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3874 . i - row indices 3875 . j - column indices 3876 - a - matrix values 3877 3878 Output Parameter: 3879 . mat - the matrix 3880 3881 Level: intermediate 3882 3883 Notes: 3884 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3885 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3886 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3887 3888 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3889 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3890 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3891 with column-major ordering within blocks. 3892 3893 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3894 3895 .keywords: matrix, aij, compressed row, sparse, parallel 3896 3897 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3898 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3899 @*/ 3900 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) 3901 { 3902 PetscErrorCode ierr; 3903 3904 PetscFunctionBegin; 3905 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3906 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3907 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3908 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3909 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 3910 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 3911 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 3912 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 3913 PetscFunctionReturn(0); 3914 } 3915