1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 #include <petscblaslapack.h> 4 5 extern PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 extern PetscErrorCode MatDisAssemble_MPIBAIJ(Mat); 7 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 8 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 9 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 10 extern PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 11 extern PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 12 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec); 13 14 #undef __FUNCT__ 15 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 16 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 17 { 18 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 19 PetscErrorCode ierr; 20 PetscInt i,*idxb = 0; 21 PetscScalar *va,*vb; 22 Vec vtmp; 23 24 PetscFunctionBegin; 25 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 26 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 27 if (idx) { 28 for (i=0; i<A->rmap->n; i++) {if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;} 29 } 30 31 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 32 if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);} 33 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 34 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 35 36 for (i=0; i<A->rmap->n; i++){ 37 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {va[i] = vb[i]; if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);} 38 } 39 40 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 41 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 42 ierr = PetscFree(idxb);CHKERRQ(ierr); 43 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 44 PetscFunctionReturn(0); 45 } 46 47 EXTERN_C_BEGIN 48 #undef __FUNCT__ 49 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 50 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 51 { 52 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 53 PetscErrorCode ierr; 54 55 PetscFunctionBegin; 56 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 57 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 58 PetscFunctionReturn(0); 59 } 60 EXTERN_C_END 61 62 EXTERN_C_BEGIN 63 #undef __FUNCT__ 64 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 65 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 66 { 67 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 68 PetscErrorCode ierr; 69 70 PetscFunctionBegin; 71 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 72 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 73 PetscFunctionReturn(0); 74 } 75 EXTERN_C_END 76 77 /* 78 Local utility routine that creates a mapping from the global column 79 number to the local number in the off-diagonal part of the local 80 storage of the matrix. This is done in a non scalable way since the 81 length of colmap equals the global matrix length. 82 */ 83 #undef __FUNCT__ 84 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 85 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 86 { 87 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 88 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 89 PetscErrorCode ierr; 90 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 91 92 PetscFunctionBegin; 93 #if defined (PETSC_USE_CTABLE) 94 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 95 for (i=0; i<nbs; i++){ 96 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 97 } 98 #else 99 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 100 ierr = PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 101 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 102 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 103 #endif 104 PetscFunctionReturn(0); 105 } 106 107 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 108 { \ 109 \ 110 brow = row/bs; \ 111 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 112 rmax = aimax[brow]; nrow = ailen[brow]; \ 113 bcol = col/bs; \ 114 ridx = row % bs; cidx = col % bs; \ 115 low = 0; high = nrow; \ 116 while (high-low > 3) { \ 117 t = (low+high)/2; \ 118 if (rp[t] > bcol) high = t; \ 119 else low = t; \ 120 } \ 121 for (_i=low; _i<high; _i++) { \ 122 if (rp[_i] > bcol) break; \ 123 if (rp[_i] == bcol) { \ 124 bap = ap + bs2*_i + bs*cidx + ridx; \ 125 if (addv == ADD_VALUES) *bap += value; \ 126 else *bap = value; \ 127 goto a_noinsert; \ 128 } \ 129 } \ 130 if (a->nonew == 1) goto a_noinsert; \ 131 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 132 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 133 N = nrow++ - 1; \ 134 /* shift up all the later entries in this row */ \ 135 for (ii=N; ii>=_i; ii--) { \ 136 rp[ii+1] = rp[ii]; \ 137 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 138 } \ 139 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 140 rp[_i] = bcol; \ 141 ap[bs2*_i + bs*cidx + ridx] = value; \ 142 a_noinsert:; \ 143 ailen[brow] = nrow; \ 144 } 145 146 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 147 { \ 148 brow = row/bs; \ 149 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 150 rmax = bimax[brow]; nrow = bilen[brow]; \ 151 bcol = col/bs; \ 152 ridx = row % bs; cidx = col % bs; \ 153 low = 0; high = nrow; \ 154 while (high-low > 3) { \ 155 t = (low+high)/2; \ 156 if (rp[t] > bcol) high = t; \ 157 else low = t; \ 158 } \ 159 for (_i=low; _i<high; _i++) { \ 160 if (rp[_i] > bcol) break; \ 161 if (rp[_i] == bcol) { \ 162 bap = ap + bs2*_i + bs*cidx + ridx; \ 163 if (addv == ADD_VALUES) *bap += value; \ 164 else *bap = value; \ 165 goto b_noinsert; \ 166 } \ 167 } \ 168 if (b->nonew == 1) goto b_noinsert; \ 169 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 170 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 171 CHKMEMQ;\ 172 N = nrow++ - 1; \ 173 /* shift up all the later entries in this row */ \ 174 for (ii=N; ii>=_i; ii--) { \ 175 rp[ii+1] = rp[ii]; \ 176 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 177 } \ 178 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 179 rp[_i] = bcol; \ 180 ap[bs2*_i + bs*cidx + ridx] = value; \ 181 b_noinsert:; \ 182 bilen[brow] = nrow; \ 183 } 184 185 #undef __FUNCT__ 186 #define __FUNCT__ "MatSetValues_MPIBAIJ" 187 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 188 { 189 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 190 MatScalar value; 191 PetscBool roworiented = baij->roworiented; 192 PetscErrorCode ierr; 193 PetscInt i,j,row,col; 194 PetscInt rstart_orig=mat->rmap->rstart; 195 PetscInt rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart; 196 PetscInt cend_orig=mat->cmap->rend,bs=mat->rmap->bs; 197 198 /* Some Variables required in the macro */ 199 Mat A = baij->A; 200 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 201 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 202 MatScalar *aa=a->a; 203 204 Mat B = baij->B; 205 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 206 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 207 MatScalar *ba=b->a; 208 209 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 210 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 211 MatScalar *ap,*bap; 212 213 PetscFunctionBegin; 214 if (v) PetscValidScalarPointer(v,6); 215 for (i=0; i<m; i++) { 216 if (im[i] < 0) continue; 217 #if defined(PETSC_USE_DEBUG) 218 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 219 #endif 220 if (im[i] >= rstart_orig && im[i] < rend_orig) { 221 row = im[i] - rstart_orig; 222 for (j=0; j<n; j++) { 223 if (in[j] >= cstart_orig && in[j] < cend_orig){ 224 col = in[j] - cstart_orig; 225 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 226 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 227 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 228 } else if (in[j] < 0) continue; 229 #if defined(PETSC_USE_DEBUG) 230 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); 231 #endif 232 else { 233 if (mat->was_assembled) { 234 if (!baij->colmap) { 235 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 236 } 237 #if defined (PETSC_USE_CTABLE) 238 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 239 col = col - 1; 240 #else 241 col = baij->colmap[in[j]/bs] - 1; 242 #endif 243 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 244 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 245 col = in[j]; 246 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 247 B = baij->B; 248 b = (Mat_SeqBAIJ*)(B)->data; 249 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 250 ba=b->a; 251 } else col += in[j]%bs; 252 } else col = in[j]; 253 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 254 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 255 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 256 } 257 } 258 } else { 259 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]); 260 if (!baij->donotstash) { 261 mat->assembled = PETSC_FALSE; 262 if (roworiented) { 263 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 264 } else { 265 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 266 } 267 } 268 } 269 } 270 PetscFunctionReturn(0); 271 } 272 273 #undef __FUNCT__ 274 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 275 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 276 { 277 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 278 const PetscScalar *value; 279 MatScalar *barray=baij->barray; 280 PetscBool roworiented = baij->roworiented; 281 PetscErrorCode ierr; 282 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 283 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 284 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 285 286 PetscFunctionBegin; 287 if(!barray) { 288 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 289 baij->barray = barray; 290 } 291 292 if (roworiented) { 293 stepval = (n-1)*bs; 294 } else { 295 stepval = (m-1)*bs; 296 } 297 for (i=0; i<m; i++) { 298 if (im[i] < 0) continue; 299 #if defined(PETSC_USE_DEBUG) 300 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); 301 #endif 302 if (im[i] >= rstart && im[i] < rend) { 303 row = im[i] - rstart; 304 for (j=0; j<n; j++) { 305 /* If NumCol = 1 then a copy is not required */ 306 if ((roworiented) && (n == 1)) { 307 barray = (MatScalar*)v + i*bs2; 308 } else if((!roworiented) && (m == 1)) { 309 barray = (MatScalar*)v + j*bs2; 310 } else { /* Here a copy is required */ 311 if (roworiented) { 312 value = v + (i*(stepval+bs) + j)*bs; 313 } else { 314 value = v + (j*(stepval+bs) + i)*bs; 315 } 316 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 317 for (jj=0; jj<bs; jj++) { 318 barray[jj] = value[jj]; 319 } 320 barray += bs; 321 } 322 barray -= bs2; 323 } 324 325 if (in[j] >= cstart && in[j] < cend){ 326 col = in[j] - cstart; 327 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 328 } 329 else if (in[j] < 0) continue; 330 #if defined(PETSC_USE_DEBUG) 331 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1); 332 #endif 333 else { 334 if (mat->was_assembled) { 335 if (!baij->colmap) { 336 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 337 } 338 339 #if defined(PETSC_USE_DEBUG) 340 #if defined (PETSC_USE_CTABLE) 341 { PetscInt data; 342 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 343 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 344 } 345 #else 346 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 347 #endif 348 #endif 349 #if defined (PETSC_USE_CTABLE) 350 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 351 col = (col - 1)/bs; 352 #else 353 col = (baij->colmap[in[j]] - 1)/bs; 354 #endif 355 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 356 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 357 col = in[j]; 358 } 359 } 360 else col = in[j]; 361 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 362 } 363 } 364 } else { 365 if (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]); 366 if (!baij->donotstash) { 367 if (roworiented) { 368 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 369 } else { 370 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 371 } 372 } 373 } 374 } 375 PetscFunctionReturn(0); 376 } 377 378 #define HASH_KEY 0.6180339887 379 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 380 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 381 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 382 #undef __FUNCT__ 383 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 384 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 385 { 386 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 387 PetscBool roworiented = baij->roworiented; 388 PetscErrorCode ierr; 389 PetscInt i,j,row,col; 390 PetscInt rstart_orig=mat->rmap->rstart; 391 PetscInt rend_orig=mat->rmap->rend,Nbs=baij->Nbs; 392 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 393 PetscReal tmp; 394 MatScalar **HD = baij->hd,value; 395 #if defined(PETSC_USE_DEBUG) 396 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 397 #endif 398 399 PetscFunctionBegin; 400 if (v) PetscValidScalarPointer(v,6); 401 for (i=0; i<m; i++) { 402 #if defined(PETSC_USE_DEBUG) 403 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 404 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); 405 #endif 406 row = im[i]; 407 if (row >= rstart_orig && row < rend_orig) { 408 for (j=0; j<n; j++) { 409 col = in[j]; 410 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 411 /* Look up PetscInto the Hash Table */ 412 key = (row/bs)*Nbs+(col/bs)+1; 413 h1 = HASH(size,key,tmp); 414 415 416 idx = h1; 417 #if defined(PETSC_USE_DEBUG) 418 insert_ct++; 419 total_ct++; 420 if (HT[idx] != key) { 421 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 422 if (idx == size) { 423 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 424 if (idx == h1) { 425 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 426 } 427 } 428 } 429 #else 430 if (HT[idx] != key) { 431 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 432 if (idx == size) { 433 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 434 if (idx == h1) { 435 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 436 } 437 } 438 } 439 #endif 440 /* A HASH table entry is found, so insert the values at the correct address */ 441 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 442 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 443 } 444 } else { 445 if (!baij->donotstash) { 446 if (roworiented) { 447 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 448 } else { 449 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 450 } 451 } 452 } 453 } 454 #if defined(PETSC_USE_DEBUG) 455 baij->ht_total_ct = total_ct; 456 baij->ht_insert_ct = insert_ct; 457 #endif 458 PetscFunctionReturn(0); 459 } 460 461 #undef __FUNCT__ 462 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 463 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 464 { 465 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 466 PetscBool roworiented = baij->roworiented; 467 PetscErrorCode ierr; 468 PetscInt i,j,ii,jj,row,col; 469 PetscInt rstart=baij->rstartbs; 470 PetscInt rend=mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 471 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 472 PetscReal tmp; 473 MatScalar **HD = baij->hd,*baij_a; 474 const PetscScalar *v_t,*value; 475 #if defined(PETSC_USE_DEBUG) 476 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 477 #endif 478 479 PetscFunctionBegin; 480 481 if (roworiented) { 482 stepval = (n-1)*bs; 483 } else { 484 stepval = (m-1)*bs; 485 } 486 for (i=0; i<m; i++) { 487 #if defined(PETSC_USE_DEBUG) 488 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 489 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); 490 #endif 491 row = im[i]; 492 v_t = v + i*nbs2; 493 if (row >= rstart && row < rend) { 494 for (j=0; j<n; j++) { 495 col = in[j]; 496 497 /* Look up into the Hash Table */ 498 key = row*Nbs+col+1; 499 h1 = HASH(size,key,tmp); 500 501 idx = h1; 502 #if defined(PETSC_USE_DEBUG) 503 total_ct++; 504 insert_ct++; 505 if (HT[idx] != key) { 506 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 507 if (idx == size) { 508 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 509 if (idx == h1) { 510 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 511 } 512 } 513 } 514 #else 515 if (HT[idx] != key) { 516 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 517 if (idx == size) { 518 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 519 if (idx == h1) { 520 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 521 } 522 } 523 } 524 #endif 525 baij_a = HD[idx]; 526 if (roworiented) { 527 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 528 /* value = v + (i*(stepval+bs)+j)*bs; */ 529 value = v_t; 530 v_t += bs; 531 if (addv == ADD_VALUES) { 532 for (ii=0; ii<bs; ii++,value+=stepval) { 533 for (jj=ii; jj<bs2; jj+=bs) { 534 baij_a[jj] += *value++; 535 } 536 } 537 } else { 538 for (ii=0; ii<bs; ii++,value+=stepval) { 539 for (jj=ii; jj<bs2; jj+=bs) { 540 baij_a[jj] = *value++; 541 } 542 } 543 } 544 } else { 545 value = v + j*(stepval+bs)*bs + i*bs; 546 if (addv == ADD_VALUES) { 547 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 548 for (jj=0; jj<bs; jj++) { 549 baij_a[jj] += *value++; 550 } 551 } 552 } else { 553 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 554 for (jj=0; jj<bs; jj++) { 555 baij_a[jj] = *value++; 556 } 557 } 558 } 559 } 560 } 561 } else { 562 if (!baij->donotstash) { 563 if (roworiented) { 564 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 565 } else { 566 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 567 } 568 } 569 } 570 } 571 #if defined(PETSC_USE_DEBUG) 572 baij->ht_total_ct = total_ct; 573 baij->ht_insert_ct = insert_ct; 574 #endif 575 PetscFunctionReturn(0); 576 } 577 578 #undef __FUNCT__ 579 #define __FUNCT__ "MatGetValues_MPIBAIJ" 580 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 581 { 582 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 583 PetscErrorCode ierr; 584 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 585 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 586 587 PetscFunctionBegin; 588 for (i=0; i<m; i++) { 589 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 590 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); 591 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 592 row = idxm[i] - bsrstart; 593 for (j=0; j<n; j++) { 594 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 595 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); 596 if (idxn[j] >= bscstart && idxn[j] < bscend){ 597 col = idxn[j] - bscstart; 598 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 599 } else { 600 if (!baij->colmap) { 601 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 602 } 603 #if defined (PETSC_USE_CTABLE) 604 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 605 data --; 606 #else 607 data = baij->colmap[idxn[j]/bs]-1; 608 #endif 609 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 610 else { 611 col = data + idxn[j]%bs; 612 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 613 } 614 } 615 } 616 } else { 617 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 618 } 619 } 620 PetscFunctionReturn(0); 621 } 622 623 #undef __FUNCT__ 624 #define __FUNCT__ "MatNorm_MPIBAIJ" 625 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 626 { 627 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 628 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 629 PetscErrorCode ierr; 630 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 631 PetscReal sum = 0.0; 632 MatScalar *v; 633 634 PetscFunctionBegin; 635 if (baij->size == 1) { 636 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 637 } else { 638 if (type == NORM_FROBENIUS) { 639 v = amat->a; 640 nz = amat->nz*bs2; 641 for (i=0; i<nz; i++) { 642 #if defined(PETSC_USE_COMPLEX) 643 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 644 #else 645 sum += (*v)*(*v); v++; 646 #endif 647 } 648 v = bmat->a; 649 nz = bmat->nz*bs2; 650 for (i=0; i<nz; i++) { 651 #if defined(PETSC_USE_COMPLEX) 652 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 653 #else 654 sum += (*v)*(*v); v++; 655 #endif 656 } 657 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 658 *nrm = PetscSqrtReal(*nrm); 659 } else if (type == NORM_1) { /* max column sum */ 660 PetscReal *tmp,*tmp2; 661 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 662 ierr = PetscMalloc2(mat->cmap->N,PetscReal,&tmp,mat->cmap->N,PetscReal,&tmp2);CHKERRQ(ierr); 663 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 664 v = amat->a; jj = amat->j; 665 for (i=0; i<amat->nz; i++) { 666 for (j=0; j<bs; j++){ 667 col = bs*(cstart + *jj) + j; /* column index */ 668 for (row=0; row<bs; row++){ 669 tmp[col] += PetscAbsScalar(*v); v++; 670 } 671 } 672 jj++; 673 } 674 v = bmat->a; jj = bmat->j; 675 for (i=0; i<bmat->nz; i++) { 676 for (j=0; j<bs; j++){ 677 col = bs*garray[*jj] + j; 678 for (row=0; row<bs; row++){ 679 tmp[col] += PetscAbsScalar(*v); v++; 680 } 681 } 682 jj++; 683 } 684 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 685 *nrm = 0.0; 686 for (j=0; j<mat->cmap->N; j++) { 687 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 688 } 689 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 690 } else if (type == NORM_INFINITY) { /* max row sum */ 691 PetscReal *sums; 692 ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr); 693 sum = 0.0; 694 for (j=0; j<amat->mbs; j++) { 695 for (row=0; row<bs; row++) sums[row] = 0.0; 696 v = amat->a + bs2*amat->i[j]; 697 nz = amat->i[j+1]-amat->i[j]; 698 for (i=0; i<nz; i++) { 699 for (col=0; col<bs; col++){ 700 for (row=0; row<bs; row++){ 701 sums[row] += PetscAbsScalar(*v); v++; 702 } 703 } 704 } 705 v = bmat->a + bs2*bmat->i[j]; 706 nz = bmat->i[j+1]-bmat->i[j]; 707 for (i=0; i<nz; i++) { 708 for (col=0; col<bs; col++){ 709 for (row=0; row<bs; row++){ 710 sums[row] += PetscAbsScalar(*v); v++; 711 } 712 } 713 } 714 for (row=0; row<bs; row++){ 715 if (sums[row] > sum) sum = sums[row]; 716 } 717 } 718 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 719 ierr = PetscFree(sums);CHKERRQ(ierr); 720 } else SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_SUP,"No support for this norm yet"); 721 } 722 PetscFunctionReturn(0); 723 } 724 725 /* 726 Creates the hash table, and sets the table 727 This table is created only once. 728 If new entried need to be added to the matrix 729 then the hash table has to be destroyed and 730 recreated. 731 */ 732 #undef __FUNCT__ 733 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 734 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 735 { 736 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 737 Mat A = baij->A,B=baij->B; 738 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 739 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 740 PetscErrorCode ierr; 741 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 742 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 743 PetscInt *HT,key; 744 MatScalar **HD; 745 PetscReal tmp; 746 #if defined(PETSC_USE_INFO) 747 PetscInt ct=0,max=0; 748 #endif 749 750 PetscFunctionBegin; 751 if (baij->ht) PetscFunctionReturn(0); 752 753 baij->ht_size = (PetscInt)(factor*nz); 754 ht_size = baij->ht_size; 755 756 /* Allocate Memory for Hash Table */ 757 ierr = PetscMalloc2(ht_size,MatScalar*,&baij->hd,ht_size,PetscInt,&baij->ht);CHKERRQ(ierr); 758 ierr = PetscMemzero(baij->hd,ht_size*sizeof(MatScalar*));CHKERRQ(ierr); 759 ierr = PetscMemzero(baij->ht,ht_size*sizeof(PetscInt));CHKERRQ(ierr); 760 HD = baij->hd; 761 HT = baij->ht; 762 763 /* Loop Over A */ 764 for (i=0; i<a->mbs; i++) { 765 for (j=ai[i]; j<ai[i+1]; j++) { 766 row = i+rstart; 767 col = aj[j]+cstart; 768 769 key = row*Nbs + col + 1; 770 h1 = HASH(ht_size,key,tmp); 771 for (k=0; k<ht_size; k++){ 772 if (!HT[(h1+k)%ht_size]) { 773 HT[(h1+k)%ht_size] = key; 774 HD[(h1+k)%ht_size] = a->a + j*bs2; 775 break; 776 #if defined(PETSC_USE_INFO) 777 } else { 778 ct++; 779 #endif 780 } 781 } 782 #if defined(PETSC_USE_INFO) 783 if (k> max) max = k; 784 #endif 785 } 786 } 787 /* Loop Over B */ 788 for (i=0; i<b->mbs; i++) { 789 for (j=bi[i]; j<bi[i+1]; j++) { 790 row = i+rstart; 791 col = garray[bj[j]]; 792 key = row*Nbs + col + 1; 793 h1 = HASH(ht_size,key,tmp); 794 for (k=0; k<ht_size; k++){ 795 if (!HT[(h1+k)%ht_size]) { 796 HT[(h1+k)%ht_size] = key; 797 HD[(h1+k)%ht_size] = b->a + j*bs2; 798 break; 799 #if defined(PETSC_USE_INFO) 800 } else { 801 ct++; 802 #endif 803 } 804 } 805 #if defined(PETSC_USE_INFO) 806 if (k> max) max = k; 807 #endif 808 } 809 } 810 811 /* Print Summary */ 812 #if defined(PETSC_USE_INFO) 813 for (i=0,j=0; i<ht_size; i++) { 814 if (HT[i]) {j++;} 815 } 816 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 817 #endif 818 PetscFunctionReturn(0); 819 } 820 821 #undef __FUNCT__ 822 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 823 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 824 { 825 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 826 PetscErrorCode ierr; 827 PetscInt nstash,reallocs; 828 InsertMode addv; 829 830 PetscFunctionBegin; 831 if (baij->donotstash || mat->nooffprocentries) { 832 PetscFunctionReturn(0); 833 } 834 835 /* make sure all processors are either in INSERTMODE or ADDMODE */ 836 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 837 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 838 mat->insertmode = addv; /* in case this processor had no cache */ 839 840 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 841 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 842 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 843 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 844 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 845 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 846 PetscFunctionReturn(0); 847 } 848 849 #undef __FUNCT__ 850 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 851 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 852 { 853 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 854 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data; 855 PetscErrorCode ierr; 856 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 857 PetscInt *row,*col; 858 PetscBool r1,r2,r3,other_disassembled; 859 MatScalar *val; 860 InsertMode addv = mat->insertmode; 861 PetscMPIInt n; 862 863 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 864 PetscFunctionBegin; 865 if (!baij->donotstash && !mat->nooffprocentries) { 866 while (1) { 867 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 868 if (!flg) break; 869 870 for (i=0; i<n;) { 871 /* Now identify the consecutive vals belonging to the same row */ 872 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 873 if (j < n) ncols = j-i; 874 else ncols = n-i; 875 /* Now assemble all these values with a single function call */ 876 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 877 i = j; 878 } 879 } 880 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 881 /* Now process the block-stash. Since the values are stashed column-oriented, 882 set the roworiented flag to column oriented, and after MatSetValues() 883 restore the original flags */ 884 r1 = baij->roworiented; 885 r2 = a->roworiented; 886 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 887 baij->roworiented = PETSC_FALSE; 888 a->roworiented = PETSC_FALSE; 889 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 890 while (1) { 891 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 892 if (!flg) break; 893 894 for (i=0; i<n;) { 895 /* Now identify the consecutive vals belonging to the same row */ 896 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 897 if (j < n) ncols = j-i; 898 else ncols = n-i; 899 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 900 i = j; 901 } 902 } 903 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 904 baij->roworiented = r1; 905 a->roworiented = r2; 906 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 907 } 908 909 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 910 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 911 912 /* determine if any processor has disassembled, if so we must 913 also disassemble ourselfs, in order that we may reassemble. */ 914 /* 915 if nonzero structure of submatrix B cannot change then we know that 916 no processor disassembled thus we can skip this stuff 917 */ 918 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 919 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 920 if (mat->was_assembled && !other_disassembled) { 921 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 922 } 923 } 924 925 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 926 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 927 } 928 ierr = MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 929 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 930 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 931 932 #if defined(PETSC_USE_INFO) 933 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 934 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 935 baij->ht_total_ct = 0; 936 baij->ht_insert_ct = 0; 937 } 938 #endif 939 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 940 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 941 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 942 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 943 } 944 945 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 946 baij->rowvalues = 0; 947 PetscFunctionReturn(0); 948 } 949 950 #undef __FUNCT__ 951 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 952 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 953 { 954 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 955 PetscErrorCode ierr; 956 PetscMPIInt size = baij->size,rank = baij->rank; 957 PetscInt bs = mat->rmap->bs; 958 PetscBool iascii,isdraw; 959 PetscViewer sviewer; 960 PetscViewerFormat format; 961 962 PetscFunctionBegin; 963 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 964 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 965 if (iascii) { 966 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 967 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 968 MatInfo info; 969 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 970 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 971 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 972 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 973 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 974 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 975 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 976 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 977 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 978 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 979 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 980 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 981 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 982 PetscFunctionReturn(0); 983 } else if (format == PETSC_VIEWER_ASCII_INFO) { 984 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 985 PetscFunctionReturn(0); 986 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 987 PetscFunctionReturn(0); 988 } 989 } 990 991 if (isdraw) { 992 PetscDraw draw; 993 PetscBool isnull; 994 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 995 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 996 } 997 998 if (size == 1) { 999 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1000 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1001 } else { 1002 /* assemble the entire matrix onto first processor. */ 1003 Mat A; 1004 Mat_SeqBAIJ *Aloc; 1005 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1006 MatScalar *a; 1007 1008 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1009 /* Perhaps this should be the type of mat? */ 1010 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1011 if (!rank) { 1012 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1013 } else { 1014 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1015 } 1016 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1017 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1018 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1019 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1020 1021 /* copy over the A part */ 1022 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1023 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1024 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1025 1026 for (i=0; i<mbs; i++) { 1027 rvals[0] = bs*(baij->rstartbs + i); 1028 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1029 for (j=ai[i]; j<ai[i+1]; j++) { 1030 col = (baij->cstartbs+aj[j])*bs; 1031 for (k=0; k<bs; k++) { 1032 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1033 col++; a += bs; 1034 } 1035 } 1036 } 1037 /* copy over the B part */ 1038 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1039 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1040 for (i=0; i<mbs; i++) { 1041 rvals[0] = bs*(baij->rstartbs + i); 1042 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1043 for (j=ai[i]; j<ai[i+1]; j++) { 1044 col = baij->garray[aj[j]]*bs; 1045 for (k=0; k<bs; k++) { 1046 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1047 col++; a += bs; 1048 } 1049 } 1050 } 1051 ierr = PetscFree(rvals);CHKERRQ(ierr); 1052 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1053 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1054 /* 1055 Everyone has to call to draw the matrix since the graphics waits are 1056 synchronized across all processors that share the PetscDraw object 1057 */ 1058 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1059 if (!rank) { 1060 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1061 /* Set the type name to MATMPIBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqBAIJ_ASCII()*/ 1062 PetscStrcpy(((PetscObject)((Mat_MPIBAIJ*)(A->data))->A)->type_name,MATMPIBAIJ); 1063 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1064 } 1065 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1066 ierr = MatDestroy(&A);CHKERRQ(ierr); 1067 } 1068 PetscFunctionReturn(0); 1069 } 1070 1071 #undef __FUNCT__ 1072 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1073 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1074 { 1075 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1076 Mat_SeqBAIJ* A = (Mat_SeqBAIJ*)a->A->data; 1077 Mat_SeqBAIJ* B = (Mat_SeqBAIJ*)a->B->data; 1078 PetscErrorCode ierr; 1079 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1080 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1081 int fd; 1082 PetscScalar *column_values; 1083 FILE *file; 1084 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1085 PetscInt message_count,flowcontrolcount; 1086 1087 PetscFunctionBegin; 1088 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1089 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 1090 nz = bs2*(A->nz + B->nz); 1091 rlen = mat->rmap->n; 1092 if (!rank) { 1093 header[0] = MAT_FILE_CLASSID; 1094 header[1] = mat->rmap->N; 1095 header[2] = mat->cmap->N; 1096 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1097 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1098 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1099 /* get largest number of rows any processor has */ 1100 range = mat->rmap->range; 1101 for (i=1; i<size; i++) { 1102 rlen = PetscMax(rlen,range[i+1] - range[i]); 1103 } 1104 } else { 1105 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1106 } 1107 1108 ierr = PetscMalloc((rlen/bs)*sizeof(PetscInt),&crow_lens);CHKERRQ(ierr); 1109 /* compute lengths of each row */ 1110 for (i=0; i<a->mbs; i++) { 1111 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1112 } 1113 /* store the row lengths to the file */ 1114 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1115 if (!rank) { 1116 MPI_Status status; 1117 ierr = PetscMalloc(rlen*sizeof(PetscInt),&row_lens);CHKERRQ(ierr); 1118 rlen = (range[1] - range[0])/bs; 1119 for (i=0; i<rlen; i++) { 1120 for (j=0; j<bs; j++) { 1121 row_lens[i*bs+j] = bs*crow_lens[i]; 1122 } 1123 } 1124 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1125 for (i=1; i<size; i++) { 1126 rlen = (range[i+1] - range[i])/bs; 1127 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1128 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1129 for (k=0; k<rlen; k++) { 1130 for (j=0; j<bs; j++) { 1131 row_lens[k*bs+j] = bs*crow_lens[k]; 1132 } 1133 } 1134 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1135 } 1136 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1137 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1138 } else { 1139 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1140 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1141 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1142 } 1143 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1144 1145 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1146 information needed to make it for each row from a block row. This does require more communication but still not more than 1147 the communication needed for the nonzero values */ 1148 nzmax = nz; /* space a largest processor needs */ 1149 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1150 ierr = PetscMalloc(nzmax*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1151 cnt = 0; 1152 for (i=0; i<a->mbs; i++) { 1153 pcnt = cnt; 1154 for (j=B->i[i]; j<B->i[i+1]; j++) { 1155 if ( (col = garray[B->j[j]]) > cstart) break; 1156 for (l=0; l<bs; l++) { 1157 column_indices[cnt++] = bs*col+l; 1158 } 1159 } 1160 for (k=A->i[i]; k<A->i[i+1]; k++) { 1161 for (l=0; l<bs; l++) { 1162 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1163 } 1164 } 1165 for (; j<B->i[i+1]; j++) { 1166 for (l=0; l<bs; l++) { 1167 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1168 } 1169 } 1170 len = cnt - pcnt; 1171 for (k=1; k<bs; k++) { 1172 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1173 cnt += len; 1174 } 1175 } 1176 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1177 1178 /* store the columns to the file */ 1179 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1180 if (!rank) { 1181 MPI_Status status; 1182 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1183 for (i=1; i<size; i++) { 1184 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1185 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1186 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1187 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1188 } 1189 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1190 } else { 1191 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1192 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1193 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1194 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1195 } 1196 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1197 1198 /* load up the numerical values */ 1199 ierr = PetscMalloc(nzmax*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1200 cnt = 0; 1201 for (i=0; i<a->mbs; i++) { 1202 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1203 for (j=B->i[i]; j<B->i[i+1]; j++) { 1204 if ( garray[B->j[j]] > cstart) break; 1205 for (l=0; l<bs; l++) { 1206 for (ll=0; ll<bs; ll++) { 1207 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1208 } 1209 } 1210 cnt += bs; 1211 } 1212 for (k=A->i[i]; k<A->i[i+1]; k++) { 1213 for (l=0; l<bs; l++) { 1214 for (ll=0; ll<bs; ll++) { 1215 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1216 } 1217 } 1218 cnt += bs; 1219 } 1220 for (; j<B->i[i+1]; j++) { 1221 for (l=0; l<bs; l++) { 1222 for (ll=0; ll<bs; ll++) { 1223 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1224 } 1225 } 1226 cnt += bs; 1227 } 1228 cnt += (bs-1)*rlen; 1229 } 1230 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1231 1232 /* store the column values to the file */ 1233 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1234 if (!rank) { 1235 MPI_Status status; 1236 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1237 for (i=1; i<size; i++) { 1238 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1239 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1240 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1241 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1242 } 1243 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1244 } else { 1245 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1246 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1247 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1248 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1249 } 1250 ierr = PetscFree(column_values);CHKERRQ(ierr); 1251 1252 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1253 if (file) { 1254 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1255 } 1256 PetscFunctionReturn(0); 1257 } 1258 1259 #undef __FUNCT__ 1260 #define __FUNCT__ "MatView_MPIBAIJ" 1261 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1262 { 1263 PetscErrorCode ierr; 1264 PetscBool iascii,isdraw,issocket,isbinary; 1265 1266 PetscFunctionBegin; 1267 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1268 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1269 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1270 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1271 if (iascii || isdraw || issocket) { 1272 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1273 } else if (isbinary) { 1274 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1275 } else { 1276 SETERRQ1(((PetscObject)mat)->comm,PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1277 } 1278 PetscFunctionReturn(0); 1279 } 1280 1281 #undef __FUNCT__ 1282 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1283 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1284 { 1285 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1286 PetscErrorCode ierr; 1287 1288 PetscFunctionBegin; 1289 #if defined(PETSC_USE_LOG) 1290 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1291 #endif 1292 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1293 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1294 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1295 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1296 #if defined (PETSC_USE_CTABLE) 1297 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1298 #else 1299 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1300 #endif 1301 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1302 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1303 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1304 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1305 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1306 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1307 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1308 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1309 1310 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1311 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1312 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1313 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1314 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1315 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1316 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1317 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1318 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C","",PETSC_NULL);CHKERRQ(ierr); 1319 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C","",PETSC_NULL);CHKERRQ(ierr); 1320 PetscFunctionReturn(0); 1321 } 1322 1323 #undef __FUNCT__ 1324 #define __FUNCT__ "MatMult_MPIBAIJ" 1325 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1326 { 1327 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1328 PetscErrorCode ierr; 1329 PetscInt nt; 1330 1331 PetscFunctionBegin; 1332 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1333 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1334 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1335 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1336 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1337 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1338 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1339 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1340 PetscFunctionReturn(0); 1341 } 1342 1343 #undef __FUNCT__ 1344 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1345 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1346 { 1347 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1348 PetscErrorCode ierr; 1349 1350 PetscFunctionBegin; 1351 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1352 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1353 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1354 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1355 PetscFunctionReturn(0); 1356 } 1357 1358 #undef __FUNCT__ 1359 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1360 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1361 { 1362 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1363 PetscErrorCode ierr; 1364 PetscBool merged; 1365 1366 PetscFunctionBegin; 1367 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1368 /* do nondiagonal part */ 1369 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1370 if (!merged) { 1371 /* send it on its way */ 1372 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1373 /* do local part */ 1374 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1375 /* receive remote parts: note this assumes the values are not actually */ 1376 /* inserted in yy until the next line */ 1377 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1378 } else { 1379 /* do local part */ 1380 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1381 /* send it on its way */ 1382 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1383 /* values actually were received in the Begin() but we need to call this nop */ 1384 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1385 } 1386 PetscFunctionReturn(0); 1387 } 1388 1389 #undef __FUNCT__ 1390 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1391 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1392 { 1393 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1394 PetscErrorCode ierr; 1395 1396 PetscFunctionBegin; 1397 /* do nondiagonal part */ 1398 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1399 /* send it on its way */ 1400 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1401 /* do local part */ 1402 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1403 /* receive remote parts: note this assumes the values are not actually */ 1404 /* inserted in yy until the next line, which is true for my implementation*/ 1405 /* but is not perhaps always true. */ 1406 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1407 PetscFunctionReturn(0); 1408 } 1409 1410 /* 1411 This only works correctly for square matrices where the subblock A->A is the 1412 diagonal block 1413 */ 1414 #undef __FUNCT__ 1415 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1416 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1417 { 1418 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1419 PetscErrorCode ierr; 1420 1421 PetscFunctionBegin; 1422 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1423 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1424 PetscFunctionReturn(0); 1425 } 1426 1427 #undef __FUNCT__ 1428 #define __FUNCT__ "MatScale_MPIBAIJ" 1429 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1430 { 1431 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1432 PetscErrorCode ierr; 1433 1434 PetscFunctionBegin; 1435 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1436 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1437 PetscFunctionReturn(0); 1438 } 1439 1440 #undef __FUNCT__ 1441 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1442 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1443 { 1444 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1445 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1446 PetscErrorCode ierr; 1447 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1448 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1449 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1450 1451 PetscFunctionBegin; 1452 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1453 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1454 mat->getrowactive = PETSC_TRUE; 1455 1456 if (!mat->rowvalues && (idx || v)) { 1457 /* 1458 allocate enough space to hold information from the longest row. 1459 */ 1460 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1461 PetscInt max = 1,mbs = mat->mbs,tmp; 1462 for (i=0; i<mbs; i++) { 1463 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1464 if (max < tmp) { max = tmp; } 1465 } 1466 ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1467 } 1468 lrow = row - brstart; 1469 1470 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1471 if (!v) {pvA = 0; pvB = 0;} 1472 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1473 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1474 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1475 nztot = nzA + nzB; 1476 1477 cmap = mat->garray; 1478 if (v || idx) { 1479 if (nztot) { 1480 /* Sort by increasing column numbers, assuming A and B already sorted */ 1481 PetscInt imark = -1; 1482 if (v) { 1483 *v = v_p = mat->rowvalues; 1484 for (i=0; i<nzB; i++) { 1485 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1486 else break; 1487 } 1488 imark = i; 1489 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1490 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1491 } 1492 if (idx) { 1493 *idx = idx_p = mat->rowindices; 1494 if (imark > -1) { 1495 for (i=0; i<imark; i++) { 1496 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1497 } 1498 } else { 1499 for (i=0; i<nzB; i++) { 1500 if (cmap[cworkB[i]/bs] < cstart) 1501 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1502 else break; 1503 } 1504 imark = i; 1505 } 1506 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1507 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1508 } 1509 } else { 1510 if (idx) *idx = 0; 1511 if (v) *v = 0; 1512 } 1513 } 1514 *nz = nztot; 1515 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1516 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1517 PetscFunctionReturn(0); 1518 } 1519 1520 #undef __FUNCT__ 1521 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1522 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1523 { 1524 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1525 1526 PetscFunctionBegin; 1527 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1528 baij->getrowactive = PETSC_FALSE; 1529 PetscFunctionReturn(0); 1530 } 1531 1532 #undef __FUNCT__ 1533 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1534 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1535 { 1536 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1537 PetscErrorCode ierr; 1538 1539 PetscFunctionBegin; 1540 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1541 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1542 PetscFunctionReturn(0); 1543 } 1544 1545 #undef __FUNCT__ 1546 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1547 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1548 { 1549 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1550 Mat A = a->A,B = a->B; 1551 PetscErrorCode ierr; 1552 PetscReal isend[5],irecv[5]; 1553 1554 PetscFunctionBegin; 1555 info->block_size = (PetscReal)matin->rmap->bs; 1556 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1557 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1558 isend[3] = info->memory; isend[4] = info->mallocs; 1559 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1560 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1561 isend[3] += info->memory; isend[4] += info->mallocs; 1562 if (flag == MAT_LOCAL) { 1563 info->nz_used = isend[0]; 1564 info->nz_allocated = isend[1]; 1565 info->nz_unneeded = isend[2]; 1566 info->memory = isend[3]; 1567 info->mallocs = isend[4]; 1568 } else if (flag == MAT_GLOBAL_MAX) { 1569 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1570 info->nz_used = irecv[0]; 1571 info->nz_allocated = irecv[1]; 1572 info->nz_unneeded = irecv[2]; 1573 info->memory = irecv[3]; 1574 info->mallocs = irecv[4]; 1575 } else if (flag == MAT_GLOBAL_SUM) { 1576 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1577 info->nz_used = irecv[0]; 1578 info->nz_allocated = irecv[1]; 1579 info->nz_unneeded = irecv[2]; 1580 info->memory = irecv[3]; 1581 info->mallocs = irecv[4]; 1582 } else { 1583 SETERRQ1(((PetscObject)matin)->comm,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1584 } 1585 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1586 info->fill_ratio_needed = 0; 1587 info->factor_mallocs = 0; 1588 PetscFunctionReturn(0); 1589 } 1590 1591 #undef __FUNCT__ 1592 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1593 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1594 { 1595 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1596 PetscErrorCode ierr; 1597 1598 PetscFunctionBegin; 1599 switch (op) { 1600 case MAT_NEW_NONZERO_LOCATIONS: 1601 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1602 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1603 case MAT_KEEP_NONZERO_PATTERN: 1604 case MAT_NEW_NONZERO_LOCATION_ERR: 1605 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1606 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1607 break; 1608 case MAT_ROW_ORIENTED: 1609 a->roworiented = flg; 1610 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1611 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1612 break; 1613 case MAT_NEW_DIAGONALS: 1614 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1615 break; 1616 case MAT_IGNORE_OFF_PROC_ENTRIES: 1617 a->donotstash = flg; 1618 break; 1619 case MAT_USE_HASH_TABLE: 1620 a->ht_flag = flg; 1621 break; 1622 case MAT_SYMMETRIC: 1623 case MAT_STRUCTURALLY_SYMMETRIC: 1624 case MAT_HERMITIAN: 1625 case MAT_SYMMETRY_ETERNAL: 1626 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1627 break; 1628 default: 1629 SETERRQ1(((PetscObject)A)->comm,PETSC_ERR_SUP,"unknown option %d",op); 1630 } 1631 PetscFunctionReturn(0); 1632 } 1633 1634 #undef __FUNCT__ 1635 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1636 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1637 { 1638 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1639 Mat_SeqBAIJ *Aloc; 1640 Mat B; 1641 PetscErrorCode ierr; 1642 PetscInt M=A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1643 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1644 MatScalar *a; 1645 1646 PetscFunctionBegin; 1647 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1648 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1649 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1650 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1651 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1652 /* Do not know preallocation information, but must set block size */ 1653 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,PETSC_NULL,PETSC_DECIDE,PETSC_NULL);CHKERRQ(ierr); 1654 } else { 1655 B = *matout; 1656 } 1657 1658 /* copy over the A part */ 1659 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1660 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1661 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1662 1663 for (i=0; i<mbs; i++) { 1664 rvals[0] = bs*(baij->rstartbs + i); 1665 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1666 for (j=ai[i]; j<ai[i+1]; j++) { 1667 col = (baij->cstartbs+aj[j])*bs; 1668 for (k=0; k<bs; k++) { 1669 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1670 col++; a += bs; 1671 } 1672 } 1673 } 1674 /* copy over the B part */ 1675 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1676 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1677 for (i=0; i<mbs; i++) { 1678 rvals[0] = bs*(baij->rstartbs + i); 1679 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1680 for (j=ai[i]; j<ai[i+1]; j++) { 1681 col = baij->garray[aj[j]]*bs; 1682 for (k=0; k<bs; k++) { 1683 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1684 col++; a += bs; 1685 } 1686 } 1687 } 1688 ierr = PetscFree(rvals);CHKERRQ(ierr); 1689 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1690 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1691 1692 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1693 *matout = B; 1694 } else { 1695 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 1696 } 1697 PetscFunctionReturn(0); 1698 } 1699 1700 #undef __FUNCT__ 1701 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1702 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1703 { 1704 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1705 Mat a = baij->A,b = baij->B; 1706 PetscErrorCode ierr; 1707 PetscInt s1,s2,s3; 1708 1709 PetscFunctionBegin; 1710 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1711 if (rr) { 1712 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1713 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1714 /* Overlap communication with computation. */ 1715 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1716 } 1717 if (ll) { 1718 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1719 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1720 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1721 } 1722 /* scale the diagonal block */ 1723 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1724 1725 if (rr) { 1726 /* Do a scatter end and then right scale the off-diagonal block */ 1727 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1728 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1729 } 1730 1731 PetscFunctionReturn(0); 1732 } 1733 1734 #undef __FUNCT__ 1735 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1736 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1737 { 1738 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1739 PetscErrorCode ierr; 1740 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1741 PetscInt i,*owners = A->rmap->range; 1742 PetscInt *nprocs,j,idx,nsends,row; 1743 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1744 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1745 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1746 MPI_Comm comm = ((PetscObject)A)->comm; 1747 MPI_Request *send_waits,*recv_waits; 1748 MPI_Status recv_status,*send_status; 1749 const PetscScalar *xx; 1750 PetscScalar *bb; 1751 #if defined(PETSC_DEBUG) 1752 PetscBool found = PETSC_FALSE; 1753 #endif 1754 1755 PetscFunctionBegin; 1756 /* first count number of contributors to each processor */ 1757 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1758 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1759 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1760 j = 0; 1761 for (i=0; i<N; i++) { 1762 if (lastidx > (idx = rows[i])) j = 0; 1763 lastidx = idx; 1764 for (; j<size; j++) { 1765 if (idx >= owners[j] && idx < owners[j+1]) { 1766 nprocs[2*j]++; 1767 nprocs[2*j+1] = 1; 1768 owner[i] = j; 1769 #if defined(PETSC_DEBUG) 1770 found = PETSC_TRUE; 1771 #endif 1772 break; 1773 } 1774 } 1775 #if defined(PETSC_DEBUG) 1776 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1777 found = PETSC_FALSE; 1778 #endif 1779 } 1780 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1781 1782 if (A->nooffproczerorows) { 1783 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 1784 nrecvs = nsends; 1785 nmax = N; 1786 } else { 1787 /* inform other processors of number of messages and max length*/ 1788 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1789 } 1790 1791 /* post receives: */ 1792 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1793 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1794 for (i=0; i<nrecvs; i++) { 1795 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1796 } 1797 1798 /* do sends: 1799 1) starts[i] gives the starting index in svalues for stuff going to 1800 the ith processor 1801 */ 1802 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1803 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1804 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1805 starts[0] = 0; 1806 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1807 for (i=0; i<N; i++) { 1808 svalues[starts[owner[i]]++] = rows[i]; 1809 } 1810 1811 starts[0] = 0; 1812 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1813 count = 0; 1814 for (i=0; i<size; i++) { 1815 if (nprocs[2*i+1]) { 1816 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1817 } 1818 } 1819 ierr = PetscFree(starts);CHKERRQ(ierr); 1820 1821 base = owners[rank]; 1822 1823 /* wait on receives */ 1824 ierr = PetscMalloc2(nrecvs+1,PetscInt,&lens,nrecvs+1,PetscInt,&source);CHKERRQ(ierr); 1825 count = nrecvs; 1826 slen = 0; 1827 while (count) { 1828 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1829 /* unpack receives into our local space */ 1830 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1831 source[imdex] = recv_status.MPI_SOURCE; 1832 lens[imdex] = n; 1833 slen += n; 1834 count--; 1835 } 1836 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1837 1838 /* move the data into the send scatter */ 1839 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1840 count = 0; 1841 for (i=0; i<nrecvs; i++) { 1842 values = rvalues + i*nmax; 1843 for (j=0; j<lens[i]; j++) { 1844 lrows[count++] = values[j] - base; 1845 } 1846 } 1847 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1848 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1849 ierr = PetscFree(owner);CHKERRQ(ierr); 1850 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1851 1852 /* fix right hand side if needed */ 1853 if (x && b) { 1854 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1855 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1856 for (i=0; i<slen; i++) { 1857 bb[lrows[i]] = diag*xx[lrows[i]]; 1858 } 1859 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1860 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1861 } 1862 1863 /* actually zap the local rows */ 1864 /* 1865 Zero the required rows. If the "diagonal block" of the matrix 1866 is square and the user wishes to set the diagonal we use separate 1867 code so that MatSetValues() is not called for each diagonal allocating 1868 new memory, thus calling lots of mallocs and slowing things down. 1869 1870 */ 1871 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1872 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1873 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1874 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 1875 } else if (diag != 0.0) { 1876 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1877 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\ 1878 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1879 for (i=0; i<slen; i++) { 1880 row = lrows[i] + rstart_bs; 1881 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1882 } 1883 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1884 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1885 } else { 1886 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 1887 } 1888 1889 ierr = PetscFree(lrows);CHKERRQ(ierr); 1890 1891 /* wait on sends */ 1892 if (nsends) { 1893 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1894 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1895 ierr = PetscFree(send_status);CHKERRQ(ierr); 1896 } 1897 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1898 ierr = PetscFree(svalues);CHKERRQ(ierr); 1899 1900 PetscFunctionReturn(0); 1901 } 1902 1903 #undef __FUNCT__ 1904 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1905 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1906 { 1907 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1908 PetscErrorCode ierr; 1909 1910 PetscFunctionBegin; 1911 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatEqual_MPIBAIJ" 1919 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1920 { 1921 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1922 Mat a,b,c,d; 1923 PetscBool flg; 1924 PetscErrorCode ierr; 1925 1926 PetscFunctionBegin; 1927 a = matA->A; b = matA->B; 1928 c = matB->A; d = matB->B; 1929 1930 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1931 if (flg) { 1932 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1933 } 1934 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1935 PetscFunctionReturn(0); 1936 } 1937 1938 #undef __FUNCT__ 1939 #define __FUNCT__ "MatCopy_MPIBAIJ" 1940 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1941 { 1942 PetscErrorCode ierr; 1943 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 1944 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 1945 1946 PetscFunctionBegin; 1947 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1948 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1949 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1950 } else { 1951 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1952 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1953 } 1954 PetscFunctionReturn(0); 1955 } 1956 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatSetUp_MPIBAIJ" 1959 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 1960 { 1961 PetscErrorCode ierr; 1962 1963 PetscFunctionBegin; 1964 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1965 PetscFunctionReturn(0); 1966 } 1967 1968 #undef __FUNCT__ 1969 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1970 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1971 { 1972 PetscErrorCode ierr; 1973 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ *)X->data,*yy=(Mat_MPIBAIJ *)Y->data; 1974 PetscBLASInt bnz,one=1; 1975 Mat_SeqBAIJ *x,*y; 1976 1977 PetscFunctionBegin; 1978 if (str == SAME_NONZERO_PATTERN) { 1979 PetscScalar alpha = a; 1980 x = (Mat_SeqBAIJ *)xx->A->data; 1981 y = (Mat_SeqBAIJ *)yy->A->data; 1982 bnz = PetscBLASIntCast(x->nz); 1983 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1984 x = (Mat_SeqBAIJ *)xx->B->data; 1985 y = (Mat_SeqBAIJ *)yy->B->data; 1986 bnz = PetscBLASIntCast(x->nz); 1987 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1988 } else { 1989 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1990 } 1991 PetscFunctionReturn(0); 1992 } 1993 1994 #undef __FUNCT__ 1995 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1996 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1997 { 1998 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1999 PetscErrorCode ierr; 2000 2001 PetscFunctionBegin; 2002 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2003 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2004 PetscFunctionReturn(0); 2005 } 2006 2007 #undef __FUNCT__ 2008 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2009 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2010 { 2011 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2012 PetscErrorCode ierr; 2013 2014 PetscFunctionBegin; 2015 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2016 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2017 PetscFunctionReturn(0); 2018 } 2019 2020 #undef __FUNCT__ 2021 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2022 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2023 { 2024 PetscErrorCode ierr; 2025 IS iscol_local; 2026 PetscInt csize; 2027 2028 PetscFunctionBegin; 2029 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2030 if (call == MAT_REUSE_MATRIX) { 2031 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2032 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2033 } else { 2034 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2035 } 2036 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2037 if (call == MAT_INITIAL_MATRIX) { 2038 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2039 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2040 } 2041 PetscFunctionReturn(0); 2042 } 2043 2044 #undef __FUNCT__ 2045 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2046 /* 2047 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2048 in local and then by concatenating the local matrices the end result. 2049 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ() 2050 */ 2051 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2052 { 2053 PetscErrorCode ierr; 2054 PetscMPIInt rank,size; 2055 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2056 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2057 Mat *local,M,Mreuse; 2058 MatScalar *vwork,*aa; 2059 MPI_Comm comm = ((PetscObject)mat)->comm; 2060 Mat_SeqBAIJ *aij; 2061 2062 2063 PetscFunctionBegin; 2064 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2065 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2066 2067 if (call == MAT_REUSE_MATRIX) { 2068 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2069 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2070 local = &Mreuse; 2071 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2072 } else { 2073 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2074 Mreuse = *local; 2075 ierr = PetscFree(local);CHKERRQ(ierr); 2076 } 2077 2078 /* 2079 m - number of local rows 2080 n - number of columns (same on all processors) 2081 rstart - first row in new global matrix generated 2082 */ 2083 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2084 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2085 m = m/bs; 2086 n = n/bs; 2087 2088 if (call == MAT_INITIAL_MATRIX) { 2089 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2090 ii = aij->i; 2091 jj = aij->j; 2092 2093 /* 2094 Determine the number of non-zeros in the diagonal and off-diagonal 2095 portions of the matrix in order to do correct preallocation 2096 */ 2097 2098 /* first get start and end of "diagonal" columns */ 2099 if (csize == PETSC_DECIDE) { 2100 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2101 if (mglobal == n*bs) { /* square matrix */ 2102 nlocal = m; 2103 } else { 2104 nlocal = n/size + ((n % size) > rank); 2105 } 2106 } else { 2107 nlocal = csize/bs; 2108 } 2109 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2110 rstart = rend - nlocal; 2111 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); 2112 2113 /* next, compute all the lengths */ 2114 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2115 olens = dlens + m; 2116 for (i=0; i<m; i++) { 2117 jend = ii[i+1] - ii[i]; 2118 olen = 0; 2119 dlen = 0; 2120 for (j=0; j<jend; j++) { 2121 if (*jj < rstart || *jj >= rend) olen++; 2122 else dlen++; 2123 jj++; 2124 } 2125 olens[i] = olen; 2126 dlens[i] = dlen; 2127 } 2128 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2129 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2130 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2131 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2132 ierr = PetscFree(dlens);CHKERRQ(ierr); 2133 } else { 2134 PetscInt ml,nl; 2135 2136 M = *newmat; 2137 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2138 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2139 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2140 /* 2141 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2142 rather than the slower MatSetValues(). 2143 */ 2144 M->was_assembled = PETSC_TRUE; 2145 M->assembled = PETSC_FALSE; 2146 } 2147 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2148 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2149 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2150 ii = aij->i; 2151 jj = aij->j; 2152 aa = aij->a; 2153 for (i=0; i<m; i++) { 2154 row = rstart/bs + i; 2155 nz = ii[i+1] - ii[i]; 2156 cwork = jj; jj += nz; 2157 vwork = aa; aa += nz; 2158 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2159 } 2160 2161 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2162 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2163 *newmat = M; 2164 2165 /* save submatrix used in processor for next request */ 2166 if (call == MAT_INITIAL_MATRIX) { 2167 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2168 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2169 } 2170 2171 PetscFunctionReturn(0); 2172 } 2173 2174 #undef __FUNCT__ 2175 #define __FUNCT__ "MatPermute_MPIBAIJ" 2176 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2177 { 2178 MPI_Comm comm,pcomm; 2179 PetscInt first,local_size,nrows; 2180 const PetscInt *rows; 2181 PetscMPIInt size; 2182 IS crowp,growp,irowp,lrowp,lcolp,icolp; 2183 PetscErrorCode ierr; 2184 2185 PetscFunctionBegin; 2186 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2187 /* make a collective version of 'rowp' */ 2188 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2189 if (pcomm==comm) { 2190 crowp = rowp; 2191 } else { 2192 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2193 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2194 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2195 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2196 } 2197 /* collect the global row permutation and invert it */ 2198 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 2199 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 2200 if (pcomm!=comm) { 2201 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2202 } 2203 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2204 /* get the local target indices */ 2205 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL);CHKERRQ(ierr); 2206 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL);CHKERRQ(ierr); 2207 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 2208 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,PETSC_COPY_VALUES,&lrowp);CHKERRQ(ierr); 2209 ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr); 2210 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2211 /* the column permutation is so much easier; 2212 make a local version of 'colp' and invert it */ 2213 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2214 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2215 if (size==1) { 2216 lcolp = colp; 2217 } else { 2218 ierr = ISGetSize(colp,&nrows);CHKERRQ(ierr); 2219 ierr = ISGetIndices(colp,&rows);CHKERRQ(ierr); 2220 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,PETSC_COPY_VALUES,&lcolp);CHKERRQ(ierr); 2221 } 2222 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2223 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2224 ierr = ISSetPermutation(icolp);CHKERRQ(ierr); 2225 if (size>1) { 2226 ierr = ISRestoreIndices(colp,&rows);CHKERRQ(ierr); 2227 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2228 } 2229 /* now we just get the submatrix */ 2230 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2231 /* clean up */ 2232 ierr = ISDestroy(&lrowp);CHKERRQ(ierr); 2233 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2234 PetscFunctionReturn(0); 2235 } 2236 2237 #undef __FUNCT__ 2238 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2239 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2240 { 2241 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2242 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2243 2244 PetscFunctionBegin; 2245 if (nghosts) { *nghosts = B->nbs;} 2246 if (ghosts) {*ghosts = baij->garray;} 2247 PetscFunctionReturn(0); 2248 } 2249 2250 extern PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat); 2251 2252 #undef __FUNCT__ 2253 #define __FUNCT__ "MatFDColoringCreate_MPIBAIJ" 2254 /* 2255 This routine is almost identical to MatFDColoringCreate_MPIBAIJ()! 2256 */ 2257 PetscErrorCode MatFDColoringCreate_MPIBAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 2258 { 2259 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 2260 PetscErrorCode ierr; 2261 PetscMPIInt size,*ncolsonproc,*disp,nn; 2262 PetscInt bs,i,n,nrows,j,k,m,*rows = 0,*A_ci,*A_cj,ncols,col; 2263 const PetscInt *is; 2264 PetscInt nis = iscoloring->n,nctot,*cols,*B_ci,*B_cj; 2265 PetscInt *rowhit,M,cstart,cend,colb; 2266 PetscInt *columnsforrow,l; 2267 IS *isa; 2268 PetscBool done,flg; 2269 ISLocalToGlobalMapping map = mat->cmap->bmapping; 2270 PetscInt *ltog = (map ? map->indices : (PetscInt*) PETSC_NULL) ,ctype=c->ctype; 2271 2272 PetscFunctionBegin; 2273 if (!mat->assembled) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be assembled first; MatAssemblyBegin/End();"); 2274 if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMappingBlock"); 2275 2276 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 2277 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2278 M = mat->rmap->n/bs; 2279 cstart = mat->cmap->rstart/bs; 2280 cend = mat->cmap->rend/bs; 2281 c->M = mat->rmap->N/bs; /* set the global rows and columns and local rows */ 2282 c->N = mat->cmap->N/bs; 2283 c->m = mat->rmap->n/bs; 2284 c->rstart = mat->rmap->rstart/bs; 2285 2286 c->ncolors = nis; 2287 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr); 2288 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr); 2289 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr); 2290 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr); 2291 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr); 2292 ierr = PetscLogObjectMemory(c,5*nis*sizeof(PetscInt));CHKERRQ(ierr); 2293 2294 /* Allow access to data structures of local part of matrix */ 2295 if (!baij->colmap) { 2296 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 2297 } 2298 ierr = MatGetColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 2299 ierr = MatGetColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 2300 2301 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);CHKERRQ(ierr); 2302 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);CHKERRQ(ierr); 2303 2304 for (i=0; i<nis; i++) { 2305 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 2306 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 2307 c->ncolumns[i] = n; 2308 if (n) { 2309 ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr); 2310 ierr = PetscLogObjectMemory(c,n*sizeof(PetscInt));CHKERRQ(ierr); 2311 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 2312 } else { 2313 c->columns[i] = 0; 2314 } 2315 2316 if (ctype == IS_COLORING_GLOBAL){ 2317 /* Determine the total (parallel) number of columns of this color */ 2318 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 2319 ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr); 2320 2321 nn = PetscMPIIntCast(n); 2322 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,((PetscObject)mat)->comm);CHKERRQ(ierr); 2323 nctot = 0; for (j=0; j<size; j++) {nctot += ncolsonproc[j];} 2324 if (!nctot) { 2325 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 2326 } 2327 2328 disp[0] = 0; 2329 for (j=1; j<size; j++) { 2330 disp[j] = disp[j-1] + ncolsonproc[j-1]; 2331 } 2332 2333 /* Get complete list of columns for color on each processor */ 2334 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2335 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,((PetscObject)mat)->comm);CHKERRQ(ierr); 2336 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 2337 } else if (ctype == IS_COLORING_GHOSTED){ 2338 /* Determine local number of columns of this color on this process, including ghost points */ 2339 nctot = n; 2340 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2341 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 2342 } else { 2343 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 2344 } 2345 2346 /* 2347 Mark all rows affect by these columns 2348 */ 2349 /* Temporary option to allow for debugging/testing */ 2350 flg = PETSC_FALSE; 2351 ierr = PetscOptionsGetBool(PETSC_NULL,"-matfdcoloring_slow",&flg,PETSC_NULL);CHKERRQ(ierr); 2352 if (!flg) {/*-----------------------------------------------------------------------------*/ 2353 /* crude, fast version */ 2354 ierr = PetscMemzero(rowhit,M*sizeof(PetscInt));CHKERRQ(ierr); 2355 /* loop over columns*/ 2356 for (j=0; j<nctot; j++) { 2357 if (ctype == IS_COLORING_GHOSTED) { 2358 col = ltog[cols[j]]; 2359 } else { 2360 col = cols[j]; 2361 } 2362 if (col >= cstart && col < cend) { 2363 /* column is in diagonal block of matrix */ 2364 rows = A_cj + A_ci[col-cstart]; 2365 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 2366 } else { 2367 #if defined (PETSC_USE_CTABLE) 2368 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2369 colb --; 2370 #else 2371 colb = baij->colmap[col] - 1; 2372 #endif 2373 if (colb == -1) { 2374 m = 0; 2375 } else { 2376 colb = colb/bs; 2377 rows = B_cj + B_ci[colb]; 2378 m = B_ci[colb+1] - B_ci[colb]; 2379 } 2380 } 2381 /* loop over columns marking them in rowhit */ 2382 for (k=0; k<m; k++) { 2383 rowhit[*rows++] = col + 1; 2384 } 2385 } 2386 2387 /* count the number of hits */ 2388 nrows = 0; 2389 for (j=0; j<M; j++) { 2390 if (rowhit[j]) nrows++; 2391 } 2392 c->nrows[i] = nrows; 2393 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 2394 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 2395 ierr = PetscLogObjectMemory(c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 2396 nrows = 0; 2397 for (j=0; j<M; j++) { 2398 if (rowhit[j]) { 2399 c->rows[i][nrows] = j; 2400 c->columnsforrow[i][nrows] = rowhit[j] - 1; 2401 nrows++; 2402 } 2403 } 2404 } else {/*-------------------------------------------------------------------------------*/ 2405 /* slow version, using rowhit as a linked list */ 2406 PetscInt currentcol,fm,mfm; 2407 rowhit[M] = M; 2408 nrows = 0; 2409 /* loop over columns*/ 2410 for (j=0; j<nctot; j++) { 2411 if (ctype == IS_COLORING_GHOSTED) { 2412 col = ltog[cols[j]]; 2413 } else { 2414 col = cols[j]; 2415 } 2416 if (col >= cstart && col < cend) { 2417 /* column is in diagonal block of matrix */ 2418 rows = A_cj + A_ci[col-cstart]; 2419 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 2420 } else { 2421 #if defined (PETSC_USE_CTABLE) 2422 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2423 colb --; 2424 #else 2425 colb = baij->colmap[col] - 1; 2426 #endif 2427 if (colb == -1) { 2428 m = 0; 2429 } else { 2430 colb = colb/bs; 2431 rows = B_cj + B_ci[colb]; 2432 m = B_ci[colb+1] - B_ci[colb]; 2433 } 2434 } 2435 2436 /* loop over columns marking them in rowhit */ 2437 fm = M; /* fm points to first entry in linked list */ 2438 for (k=0; k<m; k++) { 2439 currentcol = *rows++; 2440 /* is it already in the list? */ 2441 do { 2442 mfm = fm; 2443 fm = rowhit[fm]; 2444 } while (fm < currentcol); 2445 /* not in list so add it */ 2446 if (fm != currentcol) { 2447 nrows++; 2448 columnsforrow[currentcol] = col; 2449 /* next three lines insert new entry into linked list */ 2450 rowhit[mfm] = currentcol; 2451 rowhit[currentcol] = fm; 2452 fm = currentcol; 2453 /* fm points to present position in list since we know the columns are sorted */ 2454 } else { 2455 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected"); 2456 } 2457 } 2458 } 2459 c->nrows[i] = nrows; 2460 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 2461 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 2462 ierr = PetscLogObjectMemory(c,(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 2463 /* now store the linked list of rows into c->rows[i] */ 2464 nrows = 0; 2465 fm = rowhit[M]; 2466 do { 2467 c->rows[i][nrows] = fm; 2468 c->columnsforrow[i][nrows++] = columnsforrow[fm]; 2469 fm = rowhit[fm]; 2470 } while (fm < M); 2471 } /* ---------------------------------------------------------------------------------------*/ 2472 ierr = PetscFree(cols);CHKERRQ(ierr); 2473 } 2474 2475 /* Optimize by adding the vscale, and scaleforrow[][] fields */ 2476 /* 2477 vscale will contain the "diagonal" on processor scalings followed by the off processor 2478 */ 2479 if (ctype == IS_COLORING_GLOBAL) { 2480 PetscInt *garray; 2481 ierr = PetscMalloc(baij->B->cmap->n*sizeof(PetscInt),&garray);CHKERRQ(ierr); 2482 for (i=0; i<baij->B->cmap->n/bs; i++) { 2483 for (j=0; j<bs; j++) { 2484 garray[i*bs+j] = bs*baij->garray[i]+j; 2485 } 2486 } 2487 ierr = VecCreateGhost(((PetscObject)mat)->comm,baij->A->rmap->n,PETSC_DETERMINE,baij->B->cmap->n,garray,&c->vscale);CHKERRQ(ierr); 2488 ierr = PetscFree(garray);CHKERRQ(ierr); 2489 CHKMEMQ; 2490 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 2491 for (k=0; k<c->ncolors; k++) { 2492 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 2493 for (l=0; l<c->nrows[k]; l++) { 2494 col = c->columnsforrow[k][l]; 2495 if (col >= cstart && col < cend) { 2496 /* column is in diagonal block of matrix */ 2497 colb = col - cstart; 2498 } else { 2499 /* column is in "off-processor" part */ 2500 #if defined (PETSC_USE_CTABLE) 2501 ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr); 2502 colb --; 2503 #else 2504 colb = baij->colmap[col] - 1; 2505 #endif 2506 colb = colb/bs; 2507 colb += cend - cstart; 2508 } 2509 c->vscaleforrow[k][l] = colb; 2510 } 2511 } 2512 } else if (ctype == IS_COLORING_GHOSTED) { 2513 /* Get gtol mapping */ 2514 PetscInt N = mat->cmap->N, *gtol; 2515 ierr = PetscMalloc((N+1)*sizeof(PetscInt),>ol);CHKERRQ(ierr); 2516 for (i=0; i<N; i++) gtol[i] = -1; 2517 for (i=0; i<map->n; i++) gtol[ltog[i]] = i; 2518 2519 c->vscale = 0; /* will be created in MatFDColoringApply() */ 2520 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 2521 for (k=0; k<c->ncolors; k++) { 2522 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 2523 for (l=0; l<c->nrows[k]; l++) { 2524 col = c->columnsforrow[k][l]; /* global column index */ 2525 c->vscaleforrow[k][l] = gtol[col]; /* local column index */ 2526 } 2527 } 2528 ierr = PetscFree(gtol);CHKERRQ(ierr); 2529 } 2530 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 2531 2532 ierr = PetscFree(rowhit);CHKERRQ(ierr); 2533 ierr = PetscFree(columnsforrow);CHKERRQ(ierr); 2534 ierr = MatRestoreColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 2535 ierr = MatRestoreColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 2536 CHKMEMQ; 2537 PetscFunctionReturn(0); 2538 } 2539 2540 #undef __FUNCT__ 2541 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2542 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2543 { 2544 Mat B; 2545 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2546 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2547 Mat_SeqAIJ *b; 2548 PetscErrorCode ierr; 2549 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2550 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2551 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2552 2553 PetscFunctionBegin; 2554 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2555 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 2556 2557 /* ---------------------------------------------------------------- 2558 Tell every processor the number of nonzeros per row 2559 */ 2560 ierr = PetscMalloc((A->rmap->N/bs)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2561 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2562 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]; 2563 } 2564 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2565 ierr = PetscMalloc(2*size*sizeof(PetscMPIInt),&recvcounts);CHKERRQ(ierr); 2566 displs = recvcounts + size; 2567 for (i=0; i<size; i++) { 2568 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2569 displs[i] = A->rmap->range[i]/bs; 2570 } 2571 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2572 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,((PetscObject)A)->comm);CHKERRQ(ierr); 2573 #else 2574 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,((PetscObject)A)->comm);CHKERRQ(ierr); 2575 #endif 2576 /* --------------------------------------------------------------- 2577 Create the sequential matrix of the same type as the local block diagonal 2578 */ 2579 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2580 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2581 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2582 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2583 b = (Mat_SeqAIJ *)B->data; 2584 2585 /*-------------------------------------------------------------------- 2586 Copy my part of matrix column indices over 2587 */ 2588 sendcount = ad->nz + bd->nz; 2589 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2590 a_jsendbuf = ad->j; 2591 b_jsendbuf = bd->j; 2592 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2593 cnt = 0; 2594 for (i=0; i<n; i++) { 2595 2596 /* put in lower diagonal portion */ 2597 m = bd->i[i+1] - bd->i[i]; 2598 while (m > 0) { 2599 /* is it above diagonal (in bd (compressed) numbering) */ 2600 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2601 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2602 m--; 2603 } 2604 2605 /* put in diagonal portion */ 2606 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2607 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2608 } 2609 2610 /* put in upper diagonal portion */ 2611 while (m-- > 0) { 2612 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2613 } 2614 } 2615 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2616 2617 /*-------------------------------------------------------------------- 2618 Gather all column indices to all processors 2619 */ 2620 for (i=0; i<size; i++) { 2621 recvcounts[i] = 0; 2622 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2623 recvcounts[i] += lens[j]; 2624 } 2625 } 2626 displs[0] = 0; 2627 for (i=1; i<size; i++) { 2628 displs[i] = displs[i-1] + recvcounts[i-1]; 2629 } 2630 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2631 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,((PetscObject)A)->comm);CHKERRQ(ierr); 2632 #else 2633 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,((PetscObject)A)->comm);CHKERRQ(ierr); 2634 #endif 2635 /*-------------------------------------------------------------------- 2636 Assemble the matrix into useable form (note numerical values not yet set) 2637 */ 2638 /* set the b->ilen (length of each row) values */ 2639 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2640 /* set the b->i indices */ 2641 b->i[0] = 0; 2642 for (i=1; i<=A->rmap->N/bs; i++) { 2643 b->i[i] = b->i[i-1] + lens[i-1]; 2644 } 2645 ierr = PetscFree(lens);CHKERRQ(ierr); 2646 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2647 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2648 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2649 2650 if (A->symmetric){ 2651 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2652 } else if (A->hermitian) { 2653 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2654 } else if (A->structurally_symmetric) { 2655 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2656 } 2657 *newmat = B; 2658 PetscFunctionReturn(0); 2659 } 2660 2661 #undef __FUNCT__ 2662 #define __FUNCT__ "MatSOR_MPIBAIJ" 2663 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2664 { 2665 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2666 PetscErrorCode ierr; 2667 Vec bb1 = 0; 2668 2669 PetscFunctionBegin; 2670 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2671 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2672 } 2673 2674 if (flag == SOR_APPLY_UPPER) { 2675 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2676 PetscFunctionReturn(0); 2677 } 2678 2679 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2680 if (flag & SOR_ZERO_INITIAL_GUESS) { 2681 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2682 its--; 2683 } 2684 2685 while (its--) { 2686 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2687 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2688 2689 /* update rhs: bb1 = bb - B*x */ 2690 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2691 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2692 2693 /* local sweep */ 2694 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2695 } 2696 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 2697 if (flag & SOR_ZERO_INITIAL_GUESS) { 2698 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2699 its--; 2700 } 2701 while (its--) { 2702 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2703 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2704 2705 /* update rhs: bb1 = bb - B*x */ 2706 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2707 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2708 2709 /* local sweep */ 2710 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2711 } 2712 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 2713 if (flag & SOR_ZERO_INITIAL_GUESS) { 2714 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2715 its--; 2716 } 2717 while (its--) { 2718 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2719 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2720 2721 /* update rhs: bb1 = bb - B*x */ 2722 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2723 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2724 2725 /* local sweep */ 2726 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2727 } 2728 } else SETERRQ(((PetscObject)matin)->comm,PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2729 2730 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2731 PetscFunctionReturn(0); 2732 } 2733 2734 extern PetscErrorCode MatFDColoringApply_BAIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 2735 2736 #undef __FUNCT__ 2737 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2738 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,PetscScalar **values) 2739 { 2740 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2741 PetscErrorCode ierr; 2742 2743 PetscFunctionBegin; 2744 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2745 PetscFunctionReturn(0); 2746 } 2747 2748 2749 /* -------------------------------------------------------------------*/ 2750 static struct _MatOps MatOps_Values = { 2751 MatSetValues_MPIBAIJ, 2752 MatGetRow_MPIBAIJ, 2753 MatRestoreRow_MPIBAIJ, 2754 MatMult_MPIBAIJ, 2755 /* 4*/ MatMultAdd_MPIBAIJ, 2756 MatMultTranspose_MPIBAIJ, 2757 MatMultTransposeAdd_MPIBAIJ, 2758 0, 2759 0, 2760 0, 2761 /*10*/ 0, 2762 0, 2763 0, 2764 MatSOR_MPIBAIJ, 2765 MatTranspose_MPIBAIJ, 2766 /*15*/ MatGetInfo_MPIBAIJ, 2767 MatEqual_MPIBAIJ, 2768 MatGetDiagonal_MPIBAIJ, 2769 MatDiagonalScale_MPIBAIJ, 2770 MatNorm_MPIBAIJ, 2771 /*20*/ MatAssemblyBegin_MPIBAIJ, 2772 MatAssemblyEnd_MPIBAIJ, 2773 MatSetOption_MPIBAIJ, 2774 MatZeroEntries_MPIBAIJ, 2775 /*24*/ MatZeroRows_MPIBAIJ, 2776 0, 2777 0, 2778 0, 2779 0, 2780 /*29*/ MatSetUp_MPIBAIJ, 2781 0, 2782 0, 2783 0, 2784 0, 2785 /*34*/ MatDuplicate_MPIBAIJ, 2786 0, 2787 0, 2788 0, 2789 0, 2790 /*39*/ MatAXPY_MPIBAIJ, 2791 MatGetSubMatrices_MPIBAIJ, 2792 MatIncreaseOverlap_MPIBAIJ, 2793 MatGetValues_MPIBAIJ, 2794 MatCopy_MPIBAIJ, 2795 /*44*/ 0, 2796 MatScale_MPIBAIJ, 2797 0, 2798 0, 2799 0, 2800 /*49*/ 0, 2801 0, 2802 0, 2803 0, 2804 0, 2805 /*54*/ MatFDColoringCreate_MPIBAIJ, 2806 0, 2807 MatSetUnfactored_MPIBAIJ, 2808 MatPermute_MPIBAIJ, 2809 MatSetValuesBlocked_MPIBAIJ, 2810 /*59*/ MatGetSubMatrix_MPIBAIJ, 2811 MatDestroy_MPIBAIJ, 2812 MatView_MPIBAIJ, 2813 0, 2814 0, 2815 /*64*/ 0, 2816 0, 2817 0, 2818 0, 2819 0, 2820 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2821 0, 2822 0, 2823 0, 2824 0, 2825 /*74*/ 0, 2826 MatFDColoringApply_BAIJ, 2827 0, 2828 0, 2829 0, 2830 /*79*/ 0, 2831 0, 2832 0, 2833 0, 2834 MatLoad_MPIBAIJ, 2835 /*84*/ 0, 2836 0, 2837 0, 2838 0, 2839 0, 2840 /*89*/ 0, 2841 0, 2842 0, 2843 0, 2844 0, 2845 /*94*/ 0, 2846 0, 2847 0, 2848 0, 2849 0, 2850 /*99*/ 0, 2851 0, 2852 0, 2853 0, 2854 0, 2855 /*104*/0, 2856 MatRealPart_MPIBAIJ, 2857 MatImaginaryPart_MPIBAIJ, 2858 0, 2859 0, 2860 /*109*/0, 2861 0, 2862 0, 2863 0, 2864 0, 2865 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2866 0, 2867 MatGetGhosts_MPIBAIJ, 2868 0, 2869 0, 2870 /*119*/0, 2871 0, 2872 0, 2873 0, 2874 0, 2875 /*124*/0, 2876 0, 2877 MatInvertBlockDiagonal_MPIBAIJ 2878 }; 2879 2880 EXTERN_C_BEGIN 2881 #undef __FUNCT__ 2882 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2883 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2884 { 2885 PetscFunctionBegin; 2886 *a = ((Mat_MPIBAIJ *)A->data)->A; 2887 PetscFunctionReturn(0); 2888 } 2889 EXTERN_C_END 2890 2891 EXTERN_C_BEGIN 2892 extern PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2893 EXTERN_C_END 2894 2895 EXTERN_C_BEGIN 2896 #undef __FUNCT__ 2897 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2898 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2899 { 2900 PetscInt m,rstart,cstart,cend; 2901 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2902 const PetscInt *JJ=0; 2903 PetscScalar *values=0; 2904 PetscErrorCode ierr; 2905 2906 PetscFunctionBegin; 2907 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2908 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2909 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2910 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2911 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2912 m = B->rmap->n/bs; 2913 rstart = B->rmap->rstart/bs; 2914 cstart = B->cmap->rstart/bs; 2915 cend = B->cmap->rend/bs; 2916 2917 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2918 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 2919 for (i=0; i<m; i++) { 2920 nz = ii[i+1] - ii[i]; 2921 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2922 nz_max = PetscMax(nz_max,nz); 2923 JJ = jj + ii[i]; 2924 for (j=0; j<nz; j++) { 2925 if (*JJ >= cstart) break; 2926 JJ++; 2927 } 2928 d = 0; 2929 for (; j<nz; j++) { 2930 if (*JJ++ >= cend) break; 2931 d++; 2932 } 2933 d_nnz[i] = d; 2934 o_nnz[i] = nz - d; 2935 } 2936 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2937 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2938 2939 values = (PetscScalar*)V; 2940 if (!values) { 2941 ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2942 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2943 } 2944 for (i=0; i<m; i++) { 2945 PetscInt row = i + rstart; 2946 PetscInt ncols = ii[i+1] - ii[i]; 2947 const PetscInt *icols = jj + ii[i]; 2948 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2949 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2950 } 2951 2952 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2953 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2954 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2955 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2956 PetscFunctionReturn(0); 2957 } 2958 EXTERN_C_END 2959 2960 #undef __FUNCT__ 2961 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2962 /*@C 2963 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2964 (the default parallel PETSc format). 2965 2966 Collective on MPI_Comm 2967 2968 Input Parameters: 2969 + A - the matrix 2970 . bs - the block size 2971 . i - the indices into j for the start of each local row (starts with zero) 2972 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2973 - v - optional values in the matrix 2974 2975 Level: developer 2976 2977 .keywords: matrix, aij, compressed row, sparse, parallel 2978 2979 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ 2980 @*/ 2981 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2982 { 2983 PetscErrorCode ierr; 2984 2985 PetscFunctionBegin; 2986 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2987 PetscValidType(B,1); 2988 PetscValidLogicalCollectiveInt(B,bs,2); 2989 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2990 PetscFunctionReturn(0); 2991 } 2992 2993 EXTERN_C_BEGIN 2994 #undef __FUNCT__ 2995 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2996 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2997 { 2998 Mat_MPIBAIJ *b; 2999 PetscErrorCode ierr; 3000 PetscInt i; 3001 PetscBool d_realalloc = PETSC_FALSE,o_realalloc = PETSC_FALSE; 3002 3003 PetscFunctionBegin; 3004 if (d_nz >= 0 || d_nnz) d_realalloc = PETSC_TRUE; 3005 if (o_nz >= 0 || o_nnz) o_realalloc = PETSC_TRUE; 3006 3007 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 3008 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 3009 if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 3010 if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 3011 3012 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 3013 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 3014 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3015 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3016 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 3017 3018 if (d_nnz) { 3019 for (i=0; i<B->rmap->n/bs; i++) { 3020 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]); 3021 } 3022 } 3023 if (o_nnz) { 3024 for (i=0; i<B->rmap->n/bs; i++) { 3025 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]); 3026 } 3027 } 3028 3029 b = (Mat_MPIBAIJ*)B->data; 3030 b->bs2 = bs*bs; 3031 b->mbs = B->rmap->n/bs; 3032 b->nbs = B->cmap->n/bs; 3033 b->Mbs = B->rmap->N/bs; 3034 b->Nbs = B->cmap->N/bs; 3035 3036 for (i=0; i<=b->size; i++) { 3037 b->rangebs[i] = B->rmap->range[i]/bs; 3038 } 3039 b->rstartbs = B->rmap->rstart/bs; 3040 b->rendbs = B->rmap->rend/bs; 3041 b->cstartbs = B->cmap->rstart/bs; 3042 b->cendbs = B->cmap->rend/bs; 3043 3044 if (!B->preallocated) { 3045 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3046 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3047 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 3048 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3049 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3050 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3051 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 3052 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3053 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 3054 } 3055 3056 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3057 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 3058 /* Do not error if the user did not give real preallocation information. Ugly because this would overwrite a previous user call to MatSetOption(). */ 3059 if (!d_realalloc) {ierr = MatSetOption(b->A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);} 3060 if (!o_realalloc) {ierr = MatSetOption(b->B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);} 3061 B->preallocated = PETSC_TRUE; 3062 PetscFunctionReturn(0); 3063 } 3064 EXTERN_C_END 3065 3066 EXTERN_C_BEGIN 3067 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 3068 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 3069 EXTERN_C_END 3070 3071 3072 EXTERN_C_BEGIN 3073 #undef __FUNCT__ 3074 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 3075 PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, const MatType newtype,MatReuse reuse,Mat *adj) 3076 { 3077 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 3078 PetscErrorCode ierr; 3079 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 3080 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 3081 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 3082 3083 PetscFunctionBegin; 3084 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr); 3085 ii[0] = 0; 3086 CHKMEMQ; 3087 for (i=0; i<M; i++) { 3088 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]); 3089 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]); 3090 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 3091 /* remove one from count of matrix has diagonal */ 3092 for (j=id[i]; j<id[i+1]; j++) { 3093 if (jd[j] == i) {ii[i+1]--;break;} 3094 } 3095 CHKMEMQ; 3096 } 3097 ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr); 3098 cnt = 0; 3099 for (i=0; i<M; i++) { 3100 for (j=io[i]; j<io[i+1]; j++) { 3101 if (garray[jo[j]] > rstart) break; 3102 jj[cnt++] = garray[jo[j]]; 3103 CHKMEMQ; 3104 } 3105 for (k=id[i]; k<id[i+1]; k++) { 3106 if (jd[k] != i) { 3107 jj[cnt++] = rstart + jd[k]; 3108 CHKMEMQ; 3109 } 3110 } 3111 for (;j<io[i+1]; j++) { 3112 jj[cnt++] = garray[jo[j]]; 3113 CHKMEMQ; 3114 } 3115 } 3116 ierr = MatCreateMPIAdj(((PetscObject)B)->comm,M,B->cmap->N/B->rmap->bs,ii,jj,PETSC_NULL,adj);CHKERRQ(ierr); 3117 PetscFunctionReturn(0); 3118 } 3119 EXTERN_C_END 3120 3121 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3122 EXTERN_C_BEGIN 3123 PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,const MatType,MatReuse,Mat*); 3124 EXTERN_C_END 3125 3126 EXTERN_C_BEGIN 3127 #undef __FUNCT__ 3128 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 3129 PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,const MatType newtype,MatReuse reuse,Mat *newmat) 3130 { 3131 PetscErrorCode ierr; 3132 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3133 Mat B; 3134 Mat_MPIAIJ *b; 3135 3136 PetscFunctionBegin; 3137 if (!A->assembled) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_SUP,"Matrix must be assembled"); 3138 3139 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 3140 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 3141 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 3142 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3143 ierr = MatMPIAIJSetPreallocation(B,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 3144 b = (Mat_MPIAIJ*) B->data; 3145 3146 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 3147 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 3148 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 3149 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 3150 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 3151 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3152 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3153 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3154 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3155 if (reuse == MAT_REUSE_MATRIX) { 3156 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 3157 } else { 3158 *newmat = B; 3159 } 3160 PetscFunctionReturn(0); 3161 } 3162 EXTERN_C_END 3163 3164 EXTERN_C_BEGIN 3165 #if defined(PETSC_HAVE_MUMPS) 3166 extern PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 3167 #endif 3168 EXTERN_C_END 3169 3170 /*MC 3171 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 3172 3173 Options Database Keys: 3174 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3175 . -mat_block_size <bs> - set the blocksize used to store the matrix 3176 - -mat_use_hash_table <fact> 3177 3178 Level: beginner 3179 3180 .seealso: MatCreateMPIBAIJ 3181 M*/ 3182 3183 EXTERN_C_BEGIN 3184 extern PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,const MatType,MatReuse,Mat*); 3185 EXTERN_C_END 3186 3187 EXTERN_C_BEGIN 3188 #undef __FUNCT__ 3189 #define __FUNCT__ "MatCreate_MPIBAIJ" 3190 PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3191 { 3192 Mat_MPIBAIJ *b; 3193 PetscErrorCode ierr; 3194 PetscBool flg; 3195 3196 PetscFunctionBegin; 3197 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 3198 B->data = (void*)b; 3199 3200 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3201 B->assembled = PETSC_FALSE; 3202 3203 B->insertmode = NOT_SET_VALUES; 3204 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 3205 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 3206 3207 /* build local table of row and column ownerships */ 3208 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 3209 3210 /* build cache for off array entries formed */ 3211 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 3212 b->donotstash = PETSC_FALSE; 3213 b->colmap = PETSC_NULL; 3214 b->garray = PETSC_NULL; 3215 b->roworiented = PETSC_TRUE; 3216 3217 /* stuff used in block assembly */ 3218 b->barray = 0; 3219 3220 /* stuff used for matrix vector multiply */ 3221 b->lvec = 0; 3222 b->Mvctx = 0; 3223 3224 /* stuff for MatGetRow() */ 3225 b->rowindices = 0; 3226 b->rowvalues = 0; 3227 b->getrowactive = PETSC_FALSE; 3228 3229 /* hash table stuff */ 3230 b->ht = 0; 3231 b->hd = 0; 3232 b->ht_size = 0; 3233 b->ht_flag = PETSC_FALSE; 3234 b->ht_fact = 0; 3235 b->ht_total_ct = 0; 3236 b->ht_insert_ct = 0; 3237 3238 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3239 b->ijonly = PETSC_FALSE; 3240 3241 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3242 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 3243 if (flg) { 3244 PetscReal fact = 1.39; 3245 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3246 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 3247 if (fact <= 1.0) fact = 1.39; 3248 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3249 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3250 } 3251 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3252 3253 #if defined(PETSC_HAVE_MUMPS) 3254 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", "MatGetFactor_baij_mumps",MatGetFactor_baij_mumps);CHKERRQ(ierr); 3255 #endif 3256 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpiadj_C", 3257 "MatConvert_MPIBAIJ_MPIAdj", 3258 MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3259 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpiaij_C", 3260 "MatConvert_MPIBAIJ_MPIAIJ", 3261 MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3262 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C", 3263 "MatConvert_MPIBAIJ_MPISBAIJ", 3264 MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3265 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 3266 "MatStoreValues_MPIBAIJ", 3267 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3268 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 3269 "MatRetrieveValues_MPIBAIJ", 3270 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3271 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 3272 "MatGetDiagonalBlock_MPIBAIJ", 3273 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3274 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 3275 "MatMPIBAIJSetPreallocation_MPIBAIJ", 3276 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3277 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 3278 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 3279 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3280 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 3281 "MatDiagonalScaleLocal_MPIBAIJ", 3282 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3283 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 3284 "MatSetHashTableFactor_MPIBAIJ", 3285 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3286 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C", 3287 "MatConvert_MPIBAIJ_MPIBSTRM", 3288 MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr); 3289 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3290 PetscFunctionReturn(0); 3291 } 3292 EXTERN_C_END 3293 3294 /*MC 3295 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3296 3297 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3298 and MATMPIBAIJ otherwise. 3299 3300 Options Database Keys: 3301 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3302 3303 Level: beginner 3304 3305 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3306 M*/ 3307 3308 #undef __FUNCT__ 3309 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3310 /*@C 3311 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3312 (block compressed row). For good matrix assembly performance 3313 the user should preallocate the matrix storage by setting the parameters 3314 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3315 performance can be increased by more than a factor of 50. 3316 3317 Collective on Mat 3318 3319 Input Parameters: 3320 + A - the matrix 3321 . bs - size of blockk 3322 . d_nz - number of block nonzeros per block row in diagonal portion of local 3323 submatrix (same for all local rows) 3324 . d_nnz - array containing the number of block nonzeros in the various block rows 3325 of the in diagonal portion of the local (possibly different for each block 3326 row) or PETSC_NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3327 set it even if it is zero. 3328 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3329 submatrix (same for all local rows). 3330 - o_nnz - array containing the number of nonzeros in the various block rows of the 3331 off-diagonal portion of the local submatrix (possibly different for 3332 each block row) or PETSC_NULL. 3333 3334 If the *_nnz parameter is given then the *_nz parameter is ignored 3335 3336 Options Database Keys: 3337 + -mat_block_size - size of the blocks to use 3338 - -mat_use_hash_table <fact> 3339 3340 Notes: 3341 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3342 than it must be used on all processors that share the object for that argument. 3343 3344 Storage Information: 3345 For a square global matrix we define each processor's diagonal portion 3346 to be its local rows and the corresponding columns (a square submatrix); 3347 each processor's off-diagonal portion encompasses the remainder of the 3348 local matrix (a rectangular submatrix). 3349 3350 The user can specify preallocated storage for the diagonal part of 3351 the local submatrix with either d_nz or d_nnz (not both). Set 3352 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 3353 memory allocation. Likewise, specify preallocated storage for the 3354 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3355 3356 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3357 the figure below we depict these three local rows and all columns (0-11). 3358 3359 .vb 3360 0 1 2 3 4 5 6 7 8 9 10 11 3361 ------------------- 3362 row 3 | o o o d d d o o o o o o 3363 row 4 | o o o d d d o o o o o o 3364 row 5 | o o o d d d o o o o o o 3365 ------------------- 3366 .ve 3367 3368 Thus, any entries in the d locations are stored in the d (diagonal) 3369 submatrix, and any entries in the o locations are stored in the 3370 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3371 stored simply in the MATSEQBAIJ format for compressed row storage. 3372 3373 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3374 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3375 In general, for PDE problems in which most nonzeros are near the diagonal, 3376 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3377 or you will get TERRIBLE performance; see the users' manual chapter on 3378 matrices. 3379 3380 You can call MatGetInfo() to get information on how effective the preallocation was; 3381 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3382 You can also run with the option -info and look for messages with the string 3383 malloc in them to see if additional memory allocation was needed. 3384 3385 Level: intermediate 3386 3387 .keywords: matrix, block, aij, compressed row, sparse, parallel 3388 3389 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR() 3390 @*/ 3391 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3392 { 3393 PetscErrorCode ierr; 3394 3395 PetscFunctionBegin; 3396 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3397 PetscValidType(B,1); 3398 PetscValidLogicalCollectiveInt(B,bs,2); 3399 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); 3400 PetscFunctionReturn(0); 3401 } 3402 3403 #undef __FUNCT__ 3404 #define __FUNCT__ "MatCreateBAIJ" 3405 /*@C 3406 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3407 (block compressed row). For good matrix assembly performance 3408 the user should preallocate the matrix storage by setting the parameters 3409 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3410 performance can be increased by more than a factor of 50. 3411 3412 Collective on MPI_Comm 3413 3414 Input Parameters: 3415 + comm - MPI communicator 3416 . bs - size of blockk 3417 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3418 This value should be the same as the local size used in creating the 3419 y vector for the matrix-vector product y = Ax. 3420 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3421 This value should be the same as the local size used in creating the 3422 x vector for the matrix-vector product y = Ax. 3423 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3424 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3425 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3426 submatrix (same for all local rows) 3427 . d_nnz - array containing the number of nonzero blocks in the various block rows 3428 of the in diagonal portion of the local (possibly different for each block 3429 row) or PETSC_NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3430 and set it even if it is zero. 3431 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3432 submatrix (same for all local rows). 3433 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3434 off-diagonal portion of the local submatrix (possibly different for 3435 each block row) or PETSC_NULL. 3436 3437 Output Parameter: 3438 . A - the matrix 3439 3440 Options Database Keys: 3441 + -mat_block_size - size of the blocks to use 3442 - -mat_use_hash_table <fact> 3443 3444 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3445 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3446 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3447 3448 Notes: 3449 If the *_nnz parameter is given then the *_nz parameter is ignored 3450 3451 A nonzero block is any block that as 1 or more nonzeros in it 3452 3453 The user MUST specify either the local or global matrix dimensions 3454 (possibly both). 3455 3456 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3457 than it must be used on all processors that share the object for that argument. 3458 3459 Storage Information: 3460 For a square global matrix we define each processor's diagonal portion 3461 to be its local rows and the corresponding columns (a square submatrix); 3462 each processor's off-diagonal portion encompasses the remainder of the 3463 local matrix (a rectangular submatrix). 3464 3465 The user can specify preallocated storage for the diagonal part of 3466 the local submatrix with either d_nz or d_nnz (not both). Set 3467 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 3468 memory allocation. Likewise, specify preallocated storage for the 3469 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3470 3471 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3472 the figure below we depict these three local rows and all columns (0-11). 3473 3474 .vb 3475 0 1 2 3 4 5 6 7 8 9 10 11 3476 ------------------- 3477 row 3 | o o o d d d o o o o o o 3478 row 4 | o o o d d d o o o o o o 3479 row 5 | o o o d d d o o o o o o 3480 ------------------- 3481 .ve 3482 3483 Thus, any entries in the d locations are stored in the d (diagonal) 3484 submatrix, and any entries in the o locations are stored in the 3485 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3486 stored simply in the MATSEQBAIJ format for compressed row storage. 3487 3488 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3489 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3490 In general, for PDE problems in which most nonzeros are near the diagonal, 3491 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3492 or you will get TERRIBLE performance; see the users' manual chapter on 3493 matrices. 3494 3495 Level: intermediate 3496 3497 .keywords: matrix, block, aij, compressed row, sparse, parallel 3498 3499 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3500 @*/ 3501 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) 3502 { 3503 PetscErrorCode ierr; 3504 PetscMPIInt size; 3505 3506 PetscFunctionBegin; 3507 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3508 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3509 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3510 if (size > 1) { 3511 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3512 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3513 } else { 3514 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3515 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3516 } 3517 PetscFunctionReturn(0); 3518 } 3519 3520 #undef __FUNCT__ 3521 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3522 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3523 { 3524 Mat mat; 3525 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3526 PetscErrorCode ierr; 3527 PetscInt len=0; 3528 3529 PetscFunctionBegin; 3530 *newmat = 0; 3531 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 3532 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3533 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3534 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3535 3536 mat->factortype = matin->factortype; 3537 mat->preallocated = PETSC_TRUE; 3538 mat->assembled = PETSC_TRUE; 3539 mat->insertmode = NOT_SET_VALUES; 3540 3541 a = (Mat_MPIBAIJ*)mat->data; 3542 mat->rmap->bs = matin->rmap->bs; 3543 a->bs2 = oldmat->bs2; 3544 a->mbs = oldmat->mbs; 3545 a->nbs = oldmat->nbs; 3546 a->Mbs = oldmat->Mbs; 3547 a->Nbs = oldmat->Nbs; 3548 3549 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3550 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3551 3552 a->size = oldmat->size; 3553 a->rank = oldmat->rank; 3554 a->donotstash = oldmat->donotstash; 3555 a->roworiented = oldmat->roworiented; 3556 a->rowindices = 0; 3557 a->rowvalues = 0; 3558 a->getrowactive = PETSC_FALSE; 3559 a->barray = 0; 3560 a->rstartbs = oldmat->rstartbs; 3561 a->rendbs = oldmat->rendbs; 3562 a->cstartbs = oldmat->cstartbs; 3563 a->cendbs = oldmat->cendbs; 3564 3565 /* hash table stuff */ 3566 a->ht = 0; 3567 a->hd = 0; 3568 a->ht_size = 0; 3569 a->ht_flag = oldmat->ht_flag; 3570 a->ht_fact = oldmat->ht_fact; 3571 a->ht_total_ct = 0; 3572 a->ht_insert_ct = 0; 3573 3574 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3575 if (oldmat->colmap) { 3576 #if defined (PETSC_USE_CTABLE) 3577 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3578 #else 3579 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3580 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3581 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3582 #endif 3583 } else a->colmap = 0; 3584 3585 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3586 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3587 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3588 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3589 } else a->garray = 0; 3590 3591 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3592 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3593 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3594 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3595 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3596 3597 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3598 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3599 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3600 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3601 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3602 *newmat = mat; 3603 3604 PetscFunctionReturn(0); 3605 } 3606 3607 #undef __FUNCT__ 3608 #define __FUNCT__ "MatLoad_MPIBAIJ" 3609 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3610 { 3611 PetscErrorCode ierr; 3612 int fd; 3613 PetscInt i,nz,j,rstart,rend; 3614 PetscScalar *vals,*buf; 3615 MPI_Comm comm = ((PetscObject)viewer)->comm; 3616 MPI_Status status; 3617 PetscMPIInt rank,size,maxnz; 3618 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3619 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 3620 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 3621 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3622 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 3623 PetscInt dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols; 3624 3625 PetscFunctionBegin; 3626 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3627 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 3628 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3629 3630 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3631 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3632 if (!rank) { 3633 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3634 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 3635 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3636 } 3637 3638 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 3639 3640 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3641 M = header[1]; N = header[2]; 3642 3643 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3644 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 3645 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 3646 3647 /* If global sizes are set, check if they are consistent with that given in the file */ 3648 if (sizesset) { 3649 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 3650 } 3651 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); 3652 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); 3653 3654 if (M != N) SETERRQ(((PetscObject)viewer)->comm,PETSC_ERR_SUP,"Can only do square matrices"); 3655 3656 /* 3657 This code adds extra rows to make sure the number of rows is 3658 divisible by the blocksize 3659 */ 3660 Mbs = M/bs; 3661 extra_rows = bs - M + bs*Mbs; 3662 if (extra_rows == bs) extra_rows = 0; 3663 else Mbs++; 3664 if (extra_rows && !rank) { 3665 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3666 } 3667 3668 /* determine ownership of all rows */ 3669 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3670 mbs = Mbs/size + ((Mbs % size) > rank); 3671 m = mbs*bs; 3672 } else { /* User set */ 3673 m = newmat->rmap->n; 3674 mbs = m/bs; 3675 } 3676 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 3677 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3678 3679 /* process 0 needs enough room for process with most rows */ 3680 if (!rank) { 3681 mmax = rowners[1]; 3682 for (i=2; i<size; i++) { 3683 mmax = PetscMax(mmax,rowners[i]); 3684 } 3685 mmax*=bs; 3686 } else mmax = m; 3687 3688 rowners[0] = 0; 3689 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3690 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3691 rstart = rowners[rank]; 3692 rend = rowners[rank+1]; 3693 3694 /* distribute row lengths to all processors */ 3695 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 3696 if (!rank) { 3697 mend = m; 3698 if (size == 1) mend = mend - extra_rows; 3699 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3700 for (j=mend; j<m; j++) locrowlens[j] = 1; 3701 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3702 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3703 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3704 for (j=0; j<m; j++) { 3705 procsnz[0] += locrowlens[j]; 3706 } 3707 for (i=1; i<size; i++) { 3708 mend = browners[i+1] - browners[i]; 3709 if (i == size-1) mend = mend - extra_rows; 3710 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3711 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3712 /* calculate the number of nonzeros on each processor */ 3713 for (j=0; j<browners[i+1]-browners[i]; j++) { 3714 procsnz[i] += rowlengths[j]; 3715 } 3716 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3717 } 3718 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3719 } else { 3720 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3721 } 3722 3723 if (!rank) { 3724 /* determine max buffer needed and allocate it */ 3725 maxnz = procsnz[0]; 3726 for (i=1; i<size; i++) { 3727 maxnz = PetscMax(maxnz,procsnz[i]); 3728 } 3729 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3730 3731 /* read in my part of the matrix column indices */ 3732 nz = procsnz[0]; 3733 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3734 mycols = ibuf; 3735 if (size == 1) nz -= extra_rows; 3736 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3737 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 3738 3739 /* read in every ones (except the last) and ship off */ 3740 for (i=1; i<size-1; i++) { 3741 nz = procsnz[i]; 3742 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3743 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3744 } 3745 /* read in the stuff for the last proc */ 3746 if (size != 1) { 3747 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3748 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3749 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3750 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3751 } 3752 ierr = PetscFree(cols);CHKERRQ(ierr); 3753 } else { 3754 /* determine buffer space needed for message */ 3755 nz = 0; 3756 for (i=0; i<m; i++) { 3757 nz += locrowlens[i]; 3758 } 3759 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 3760 mycols = ibuf; 3761 /* receive message of column indices*/ 3762 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3763 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3764 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3765 } 3766 3767 /* loop over local rows, determining number of off diagonal entries */ 3768 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 3769 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 3770 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3771 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3772 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 3773 rowcount = 0; nzcount = 0; 3774 for (i=0; i<mbs; i++) { 3775 dcount = 0; 3776 odcount = 0; 3777 for (j=0; j<bs; j++) { 3778 kmax = locrowlens[rowcount]; 3779 for (k=0; k<kmax; k++) { 3780 tmp = mycols[nzcount++]/bs; 3781 if (!mask[tmp]) { 3782 mask[tmp] = 1; 3783 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3784 else masked1[dcount++] = tmp; 3785 } 3786 } 3787 rowcount++; 3788 } 3789 3790 dlens[i] = dcount; 3791 odlens[i] = odcount; 3792 3793 /* zero out the mask elements we set */ 3794 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3795 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3796 } 3797 3798 3799 if (!sizesset) { 3800 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3801 } 3802 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3803 3804 if (!rank) { 3805 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3806 /* read in my part of the matrix numerical values */ 3807 nz = procsnz[0]; 3808 vals = buf; 3809 mycols = ibuf; 3810 if (size == 1) nz -= extra_rows; 3811 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3812 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 3813 3814 /* insert into matrix */ 3815 jj = rstart*bs; 3816 for (i=0; i<m; i++) { 3817 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3818 mycols += locrowlens[i]; 3819 vals += locrowlens[i]; 3820 jj++; 3821 } 3822 /* read in other processors (except the last one) and ship out */ 3823 for (i=1; i<size-1; i++) { 3824 nz = procsnz[i]; 3825 vals = buf; 3826 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3827 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3828 } 3829 /* the last proc */ 3830 if (size != 1){ 3831 nz = procsnz[i] - extra_rows; 3832 vals = buf; 3833 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3834 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3835 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3836 } 3837 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3838 } else { 3839 /* receive numeric values */ 3840 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 3841 3842 /* receive message of values*/ 3843 vals = buf; 3844 mycols = ibuf; 3845 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 3846 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 3847 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3848 3849 /* insert into matrix */ 3850 jj = rstart*bs; 3851 for (i=0; i<m; i++) { 3852 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3853 mycols += locrowlens[i]; 3854 vals += locrowlens[i]; 3855 jj++; 3856 } 3857 } 3858 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3859 ierr = PetscFree(buf);CHKERRQ(ierr); 3860 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3861 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3862 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3863 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3864 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3865 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3866 3867 PetscFunctionReturn(0); 3868 } 3869 3870 #undef __FUNCT__ 3871 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3872 /*@ 3873 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3874 3875 Input Parameters: 3876 . mat - the matrix 3877 . fact - factor 3878 3879 Not Collective, each process can use a different factor 3880 3881 Level: advanced 3882 3883 Notes: 3884 This can also be set by the command line option: -mat_use_hash_table <fact> 3885 3886 .keywords: matrix, hashtable, factor, HT 3887 3888 .seealso: MatSetOption() 3889 @*/ 3890 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3891 { 3892 PetscErrorCode ierr; 3893 3894 PetscFunctionBegin; 3895 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3896 PetscFunctionReturn(0); 3897 } 3898 3899 EXTERN_C_BEGIN 3900 #undef __FUNCT__ 3901 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3902 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3903 { 3904 Mat_MPIBAIJ *baij; 3905 3906 PetscFunctionBegin; 3907 baij = (Mat_MPIBAIJ*)mat->data; 3908 baij->ht_fact = fact; 3909 PetscFunctionReturn(0); 3910 } 3911 EXTERN_C_END 3912 3913 #undef __FUNCT__ 3914 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3915 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3916 { 3917 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 3918 PetscFunctionBegin; 3919 *Ad = a->A; 3920 *Ao = a->B; 3921 *colmap = a->garray; 3922 PetscFunctionReturn(0); 3923 } 3924 3925 /* 3926 Special version for direct calls from Fortran (to eliminate two function call overheads 3927 */ 3928 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3929 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3930 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3931 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3932 #endif 3933 3934 #undef __FUNCT__ 3935 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3936 /*@C 3937 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3938 3939 Collective on Mat 3940 3941 Input Parameters: 3942 + mat - the matrix 3943 . min - number of input rows 3944 . im - input rows 3945 . nin - number of input columns 3946 . in - input columns 3947 . v - numerical values input 3948 - addvin - INSERT_VALUES or ADD_VALUES 3949 3950 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3951 3952 Level: advanced 3953 3954 .seealso: MatSetValuesBlocked() 3955 @*/ 3956 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3957 { 3958 /* convert input arguments to C version */ 3959 Mat mat = *matin; 3960 PetscInt m = *min, n = *nin; 3961 InsertMode addv = *addvin; 3962 3963 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3964 const MatScalar *value; 3965 MatScalar *barray=baij->barray; 3966 PetscBool roworiented = baij->roworiented; 3967 PetscErrorCode ierr; 3968 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3969 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3970 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3971 3972 PetscFunctionBegin; 3973 /* tasks normally handled by MatSetValuesBlocked() */ 3974 if (mat->insertmode == NOT_SET_VALUES) { 3975 mat->insertmode = addv; 3976 } 3977 #if defined(PETSC_USE_DEBUG) 3978 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3979 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3980 #endif 3981 if (mat->assembled) { 3982 mat->was_assembled = PETSC_TRUE; 3983 mat->assembled = PETSC_FALSE; 3984 } 3985 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3986 3987 3988 if(!barray) { 3989 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 3990 baij->barray = barray; 3991 } 3992 3993 if (roworiented) { 3994 stepval = (n-1)*bs; 3995 } else { 3996 stepval = (m-1)*bs; 3997 } 3998 for (i=0; i<m; i++) { 3999 if (im[i] < 0) continue; 4000 #if defined(PETSC_USE_DEBUG) 4001 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); 4002 #endif 4003 if (im[i] >= rstart && im[i] < rend) { 4004 row = im[i] - rstart; 4005 for (j=0; j<n; j++) { 4006 /* If NumCol = 1 then a copy is not required */ 4007 if ((roworiented) && (n == 1)) { 4008 barray = (MatScalar*)v + i*bs2; 4009 } else if((!roworiented) && (m == 1)) { 4010 barray = (MatScalar*)v + j*bs2; 4011 } else { /* Here a copy is required */ 4012 if (roworiented) { 4013 value = v + i*(stepval+bs)*bs + j*bs; 4014 } else { 4015 value = v + j*(stepval+bs)*bs + i*bs; 4016 } 4017 for (ii=0; ii<bs; ii++,value+=stepval) { 4018 for (jj=0; jj<bs; jj++) { 4019 *barray++ = *value++; 4020 } 4021 } 4022 barray -=bs2; 4023 } 4024 4025 if (in[j] >= cstart && in[j] < cend){ 4026 col = in[j] - cstart; 4027 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 4028 } 4029 else if (in[j] < 0) continue; 4030 #if defined(PETSC_USE_DEBUG) 4031 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); 4032 #endif 4033 else { 4034 if (mat->was_assembled) { 4035 if (!baij->colmap) { 4036 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 4037 } 4038 4039 #if defined(PETSC_USE_DEBUG) 4040 #if defined (PETSC_USE_CTABLE) 4041 { PetscInt data; 4042 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 4043 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 4044 } 4045 #else 4046 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 4047 #endif 4048 #endif 4049 #if defined (PETSC_USE_CTABLE) 4050 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4051 col = (col - 1)/bs; 4052 #else 4053 col = (baij->colmap[in[j]] - 1)/bs; 4054 #endif 4055 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 4056 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 4057 col = in[j]; 4058 } 4059 } 4060 else col = in[j]; 4061 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 4062 } 4063 } 4064 } else { 4065 if (!baij->donotstash) { 4066 if (roworiented) { 4067 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 4068 } else { 4069 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 4070 } 4071 } 4072 } 4073 } 4074 4075 /* task normally handled by MatSetValuesBlocked() */ 4076 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 4077 PetscFunctionReturn(0); 4078 } 4079 4080 #undef __FUNCT__ 4081 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 4082 /*@ 4083 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 4084 CSR format the local rows. 4085 4086 Collective on MPI_Comm 4087 4088 Input Parameters: 4089 + comm - MPI communicator 4090 . bs - the block size, only a block size of 1 is supported 4091 . m - number of local rows (Cannot be PETSC_DECIDE) 4092 . n - This value should be the same as the local size used in creating the 4093 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4094 calculated if N is given) For square matrices n is almost always m. 4095 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4096 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4097 . i - row indices 4098 . j - column indices 4099 - a - matrix values 4100 4101 Output Parameter: 4102 . mat - the matrix 4103 4104 Level: intermediate 4105 4106 Notes: 4107 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4108 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4109 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4110 4111 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4112 4113 .keywords: matrix, aij, compressed row, sparse, parallel 4114 4115 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4116 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4117 @*/ 4118 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) 4119 { 4120 PetscErrorCode ierr; 4121 4122 4123 PetscFunctionBegin; 4124 if (i[0]) { 4125 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4126 } 4127 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4128 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4129 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4130 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 4131 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 4132 PetscFunctionReturn(0); 4133 } 4134