1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 5 EXTERN PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat); 6 EXTERN PetscErrorCode DisAssemble_MPIBAIJ(Mat); 7 EXTERN PetscErrorCode MatIncreaseOverlap_MPIBAIJ(Mat,PetscInt,IS[],PetscInt); 8 EXTERN PetscErrorCode MatGetSubMatrices_MPIBAIJ(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]); 9 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []); 10 EXTERN PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 11 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 12 EXTERN PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 13 EXTERN PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]); 14 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar); 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 18 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 19 { 20 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 21 PetscErrorCode ierr; 22 PetscInt i,*idxb = 0; 23 PetscScalar *va,*vb; 24 Vec vtmp; 25 26 PetscFunctionBegin; 27 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 28 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 29 if (idx) { 30 for (i=0; i<A->cmap->n; i++) {if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;} 31 } 32 33 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 34 if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);} 35 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 36 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 37 38 for (i=0; i<A->rmap->n; i++){ 39 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {va[i] = vb[i]; if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);} 40 } 41 42 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 43 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 44 if (idxb) {ierr = PetscFree(idxb);CHKERRQ(ierr);} 45 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 46 PetscFunctionReturn(0); 47 } 48 49 EXTERN_C_BEGIN 50 #undef __FUNCT__ 51 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 52 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIBAIJ(Mat mat) 53 { 54 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 55 PetscErrorCode ierr; 56 57 PetscFunctionBegin; 58 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 59 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 60 PetscFunctionReturn(0); 61 } 62 EXTERN_C_END 63 64 EXTERN_C_BEGIN 65 #undef __FUNCT__ 66 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 67 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIBAIJ(Mat mat) 68 { 69 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data; 70 PetscErrorCode ierr; 71 72 PetscFunctionBegin; 73 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 74 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 75 PetscFunctionReturn(0); 76 } 77 EXTERN_C_END 78 79 /* 80 Local utility routine that creates a mapping from the global column 81 number to the local number in the off-diagonal part of the local 82 storage of the matrix. This is done in a non scable way since the 83 length of colmap equals the global matrix length. 84 */ 85 #undef __FUNCT__ 86 #define __FUNCT__ "CreateColmap_MPIBAIJ_Private" 87 PetscErrorCode CreateColmap_MPIBAIJ_Private(Mat mat) 88 { 89 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 90 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 91 PetscErrorCode ierr; 92 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 93 94 PetscFunctionBegin; 95 #if defined (PETSC_USE_CTABLE) 96 ierr = PetscTableCreate(baij->nbs,&baij->colmap);CHKERRQ(ierr); 97 for (i=0; i<nbs; i++){ 98 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1);CHKERRQ(ierr); 99 } 100 #else 101 ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr); 102 ierr = PetscLogObjectMemory(mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 103 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 104 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 105 #endif 106 PetscFunctionReturn(0); 107 } 108 109 #define CHUNKSIZE 10 110 111 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 112 { \ 113 \ 114 brow = row/bs; \ 115 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 116 rmax = aimax[brow]; nrow = ailen[brow]; \ 117 bcol = col/bs; \ 118 ridx = row % bs; cidx = col % bs; \ 119 low = 0; high = nrow; \ 120 while (high-low > 3) { \ 121 t = (low+high)/2; \ 122 if (rp[t] > bcol) high = t; \ 123 else low = t; \ 124 } \ 125 for (_i=low; _i<high; _i++) { \ 126 if (rp[_i] > bcol) break; \ 127 if (rp[_i] == bcol) { \ 128 bap = ap + bs2*_i + bs*cidx + ridx; \ 129 if (addv == ADD_VALUES) *bap += value; \ 130 else *bap = value; \ 131 goto a_noinsert; \ 132 } \ 133 } \ 134 if (a->nonew == 1) goto a_noinsert; \ 135 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 136 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 137 N = nrow++ - 1; \ 138 /* shift up all the later entries in this row */ \ 139 for (ii=N; ii>=_i; ii--) { \ 140 rp[ii+1] = rp[ii]; \ 141 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 142 } \ 143 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 144 rp[_i] = bcol; \ 145 ap[bs2*_i + bs*cidx + ridx] = value; \ 146 a_noinsert:; \ 147 ailen[brow] = nrow; \ 148 } 149 150 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 151 { \ 152 brow = row/bs; \ 153 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 154 rmax = bimax[brow]; nrow = bilen[brow]; \ 155 bcol = col/bs; \ 156 ridx = row % bs; cidx = col % bs; \ 157 low = 0; high = nrow; \ 158 while (high-low > 3) { \ 159 t = (low+high)/2; \ 160 if (rp[t] > bcol) high = t; \ 161 else low = t; \ 162 } \ 163 for (_i=low; _i<high; _i++) { \ 164 if (rp[_i] > bcol) break; \ 165 if (rp[_i] == bcol) { \ 166 bap = ap + bs2*_i + bs*cidx + ridx; \ 167 if (addv == ADD_VALUES) *bap += value; \ 168 else *bap = value; \ 169 goto b_noinsert; \ 170 } \ 171 } \ 172 if (b->nonew == 1) goto b_noinsert; \ 173 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 174 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 175 CHKMEMQ;\ 176 N = nrow++ - 1; \ 177 /* shift up all the later entries in this row */ \ 178 for (ii=N; ii>=_i; ii--) { \ 179 rp[ii+1] = rp[ii]; \ 180 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 181 } \ 182 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 183 rp[_i] = bcol; \ 184 ap[bs2*_i + bs*cidx + ridx] = value; \ 185 b_noinsert:; \ 186 bilen[brow] = nrow; \ 187 } 188 189 #undef __FUNCT__ 190 #define __FUNCT__ "MatSetValues_MPIBAIJ" 191 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 192 { 193 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 194 MatScalar value; 195 PetscTruth roworiented = baij->roworiented; 196 PetscErrorCode ierr; 197 PetscInt i,j,row,col; 198 PetscInt rstart_orig=mat->rmap->rstart; 199 PetscInt rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart; 200 PetscInt cend_orig=mat->cmap->rend,bs=mat->rmap->bs; 201 202 /* Some Variables required in the macro */ 203 Mat A = baij->A; 204 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 205 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 206 MatScalar *aa=a->a; 207 208 Mat B = baij->B; 209 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 210 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 211 MatScalar *ba=b->a; 212 213 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 214 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 215 MatScalar *ap,*bap; 216 217 PetscFunctionBegin; 218 for (i=0; i<m; i++) { 219 if (im[i] < 0) continue; 220 #if defined(PETSC_USE_DEBUG) 221 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 222 #endif 223 if (im[i] >= rstart_orig && im[i] < rend_orig) { 224 row = im[i] - rstart_orig; 225 for (j=0; j<n; j++) { 226 if (in[j] >= cstart_orig && in[j] < cend_orig){ 227 col = in[j] - cstart_orig; 228 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 229 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 230 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 231 } else if (in[j] < 0) continue; 232 #if defined(PETSC_USE_DEBUG) 233 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[i],mat->cmap->N-1);} 234 #endif 235 else { 236 if (mat->was_assembled) { 237 if (!baij->colmap) { 238 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 239 } 240 #if defined (PETSC_USE_CTABLE) 241 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 242 col = col - 1; 243 #else 244 col = baij->colmap[in[j]/bs] - 1; 245 #endif 246 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 247 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 248 col = in[j]; 249 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 250 B = baij->B; 251 b = (Mat_SeqBAIJ*)(B)->data; 252 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 253 ba=b->a; 254 } else col += in[j]%bs; 255 } else col = in[j]; 256 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 257 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 258 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 259 } 260 } 261 } else { 262 if (!baij->donotstash) { 263 if (roworiented) { 264 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 265 } else { 266 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 267 } 268 } 269 } 270 } 271 PetscFunctionReturn(0); 272 } 273 274 #undef __FUNCT__ 275 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 276 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 277 { 278 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 279 const PetscScalar *value; 280 MatScalar *barray=baij->barray; 281 PetscTruth roworiented = baij->roworiented; 282 PetscErrorCode ierr; 283 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 284 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 285 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 286 287 PetscFunctionBegin; 288 if(!barray) { 289 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 290 baij->barray = barray; 291 } 292 293 if (roworiented) { 294 stepval = (n-1)*bs; 295 } else { 296 stepval = (m-1)*bs; 297 } 298 for (i=0; i<m; i++) { 299 if (im[i] < 0) continue; 300 #if defined(PETSC_USE_DEBUG) 301 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 302 #endif 303 if (im[i] >= rstart && im[i] < rend) { 304 row = im[i] - rstart; 305 for (j=0; j<n; j++) { 306 /* If NumCol = 1 then a copy is not required */ 307 if ((roworiented) && (n == 1)) { 308 barray = (MatScalar*)v + i*bs2; 309 } else if((!roworiented) && (m == 1)) { 310 barray = (MatScalar*)v + j*bs2; 311 } else { /* Here a copy is required */ 312 if (roworiented) { 313 value = v + i*(stepval+bs)*bs + j*bs; 314 } else { 315 value = v + j*(stepval+bs)*bs + i*bs; 316 } 317 for (ii=0; ii<bs; ii++,value+=stepval) { 318 for (jj=0; jj<bs; jj++) { 319 *barray++ = *value++; 320 } 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_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 = CreateColmap_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_ERR_PLIB,"Incorrect colmap"); 344 } 345 #else 346 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(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 = DisAssemble_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 (!baij->donotstash) { 366 if (roworiented) { 367 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 368 } else { 369 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 370 } 371 } 372 } 373 } 374 PetscFunctionReturn(0); 375 } 376 377 #define HASH_KEY 0.6180339887 378 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 379 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 380 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 381 #undef __FUNCT__ 382 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 383 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 384 { 385 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 386 PetscTruth roworiented = baij->roworiented; 387 PetscErrorCode ierr; 388 PetscInt i,j,row,col; 389 PetscInt rstart_orig=mat->rmap->rstart; 390 PetscInt rend_orig=mat->rmap->rend,Nbs=baij->Nbs; 391 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 392 PetscReal tmp; 393 MatScalar **HD = baij->hd,value; 394 #if defined(PETSC_USE_DEBUG) 395 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 396 #endif 397 398 PetscFunctionBegin; 399 400 for (i=0; i<m; i++) { 401 #if defined(PETSC_USE_DEBUG) 402 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 403 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 404 #endif 405 row = im[i]; 406 if (row >= rstart_orig && row < rend_orig) { 407 for (j=0; j<n; j++) { 408 col = in[j]; 409 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 410 /* Look up PetscInto the Hash Table */ 411 key = (row/bs)*Nbs+(col/bs)+1; 412 h1 = HASH(size,key,tmp); 413 414 415 idx = h1; 416 #if defined(PETSC_USE_DEBUG) 417 insert_ct++; 418 total_ct++; 419 if (HT[idx] != key) { 420 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 421 if (idx == size) { 422 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 423 if (idx == h1) { 424 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 425 } 426 } 427 } 428 #else 429 if (HT[idx] != key) { 430 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 431 if (idx == size) { 432 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 433 if (idx == h1) { 434 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 435 } 436 } 437 } 438 #endif 439 /* A HASH table entry is found, so insert the values at the correct address */ 440 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 441 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 442 } 443 } else { 444 if (!baij->donotstash) { 445 if (roworiented) { 446 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 447 } else { 448 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 449 } 450 } 451 } 452 } 453 #if defined(PETSC_USE_DEBUG) 454 baij->ht_total_ct = total_ct; 455 baij->ht_insert_ct = insert_ct; 456 #endif 457 PetscFunctionReturn(0); 458 } 459 460 #undef __FUNCT__ 461 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 462 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 463 { 464 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 465 PetscTruth roworiented = baij->roworiented; 466 PetscErrorCode ierr; 467 PetscInt i,j,ii,jj,row,col; 468 PetscInt rstart=baij->rstartbs; 469 PetscInt rend=mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 470 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 471 PetscReal tmp; 472 MatScalar **HD = baij->hd,*baij_a; 473 const PetscScalar *v_t,*value; 474 #if defined(PETSC_USE_DEBUG) 475 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 476 #endif 477 478 PetscFunctionBegin; 479 480 if (roworiented) { 481 stepval = (n-1)*bs; 482 } else { 483 stepval = (m-1)*bs; 484 } 485 for (i=0; i<m; i++) { 486 #if defined(PETSC_USE_DEBUG) 487 if (im[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 488 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 489 #endif 490 row = im[i]; 491 v_t = v + i*nbs2; 492 if (row >= rstart && row < rend) { 493 for (j=0; j<n; j++) { 494 col = in[j]; 495 496 /* Look up into the Hash Table */ 497 key = row*Nbs+col+1; 498 h1 = HASH(size,key,tmp); 499 500 idx = h1; 501 #if defined(PETSC_USE_DEBUG) 502 total_ct++; 503 insert_ct++; 504 if (HT[idx] != key) { 505 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 506 if (idx == size) { 507 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 508 if (idx == h1) { 509 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 510 } 511 } 512 } 513 #else 514 if (HT[idx] != key) { 515 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++); 516 if (idx == size) { 517 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++); 518 if (idx == h1) { 519 SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 520 } 521 } 522 } 523 #endif 524 baij_a = HD[idx]; 525 if (roworiented) { 526 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 527 /* value = v + (i*(stepval+bs)+j)*bs; */ 528 value = v_t; 529 v_t += bs; 530 if (addv == ADD_VALUES) { 531 for (ii=0; ii<bs; ii++,value+=stepval) { 532 for (jj=ii; jj<bs2; jj+=bs) { 533 baij_a[jj] += *value++; 534 } 535 } 536 } else { 537 for (ii=0; ii<bs; ii++,value+=stepval) { 538 for (jj=ii; jj<bs2; jj+=bs) { 539 baij_a[jj] = *value++; 540 } 541 } 542 } 543 } else { 544 value = v + j*(stepval+bs)*bs + i*bs; 545 if (addv == ADD_VALUES) { 546 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 547 for (jj=0; jj<bs; jj++) { 548 baij_a[jj] += *value++; 549 } 550 } 551 } else { 552 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 553 for (jj=0; jj<bs; jj++) { 554 baij_a[jj] = *value++; 555 } 556 } 557 } 558 } 559 } 560 } else { 561 if (!baij->donotstash) { 562 if (roworiented) { 563 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 564 } else { 565 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 566 } 567 } 568 } 569 } 570 #if defined(PETSC_USE_DEBUG) 571 baij->ht_total_ct = total_ct; 572 baij->ht_insert_ct = insert_ct; 573 #endif 574 PetscFunctionReturn(0); 575 } 576 577 #undef __FUNCT__ 578 #define __FUNCT__ "MatGetValues_MPIBAIJ" 579 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 580 { 581 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 582 PetscErrorCode ierr; 583 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 584 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 585 586 PetscFunctionBegin; 587 for (i=0; i<m; i++) { 588 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 589 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 590 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 591 row = idxm[i] - bsrstart; 592 for (j=0; j<n; j++) { 593 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 594 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 595 if (idxn[j] >= bscstart && idxn[j] < bscend){ 596 col = idxn[j] - bscstart; 597 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 598 } else { 599 if (!baij->colmap) { 600 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 601 } 602 #if defined (PETSC_USE_CTABLE) 603 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 604 data --; 605 #else 606 data = baij->colmap[idxn[j]/bs]-1; 607 #endif 608 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 609 else { 610 col = data + idxn[j]%bs; 611 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 612 } 613 } 614 } 615 } else { 616 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 617 } 618 } 619 PetscFunctionReturn(0); 620 } 621 622 #undef __FUNCT__ 623 #define __FUNCT__ "MatNorm_MPIBAIJ" 624 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 625 { 626 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 627 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 628 PetscErrorCode ierr; 629 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 630 PetscReal sum = 0.0; 631 MatScalar *v; 632 633 PetscFunctionBegin; 634 if (baij->size == 1) { 635 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 636 } else { 637 if (type == NORM_FROBENIUS) { 638 v = amat->a; 639 nz = amat->nz*bs2; 640 for (i=0; i<nz; i++) { 641 #if defined(PETSC_USE_COMPLEX) 642 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 643 #else 644 sum += (*v)*(*v); v++; 645 #endif 646 } 647 v = bmat->a; 648 nz = bmat->nz*bs2; 649 for (i=0; i<nz; i++) { 650 #if defined(PETSC_USE_COMPLEX) 651 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 652 #else 653 sum += (*v)*(*v); v++; 654 #endif 655 } 656 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 657 *nrm = sqrt(*nrm); 658 } else if (type == NORM_1) { /* max column sum */ 659 PetscReal *tmp,*tmp2; 660 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 661 ierr = PetscMalloc((2*mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 662 tmp2 = tmp + mat->cmap->N; 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,MPI_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 = PetscFree(tmp);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,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 719 ierr = PetscFree(sums);CHKERRQ(ierr); 720 } else { 721 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 722 } 723 } 724 PetscFunctionReturn(0); 725 } 726 727 /* 728 Creates the hash table, and sets the table 729 This table is created only once. 730 If new entried need to be added to the matrix 731 then the hash table has to be destroyed and 732 recreated. 733 */ 734 #undef __FUNCT__ 735 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 736 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 737 { 738 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 739 Mat A = baij->A,B=baij->B; 740 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data,*b=(Mat_SeqBAIJ *)B->data; 741 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 742 PetscErrorCode ierr; 743 PetscInt size,bs2=baij->bs2,rstart=baij->rstartbs; 744 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 745 PetscInt *HT,key; 746 MatScalar **HD; 747 PetscReal tmp; 748 #if defined(PETSC_USE_INFO) 749 PetscInt ct=0,max=0; 750 #endif 751 752 PetscFunctionBegin; 753 baij->ht_size=(PetscInt)(factor*nz); 754 size = baij->ht_size; 755 756 if (baij->ht) { 757 PetscFunctionReturn(0); 758 } 759 760 /* Allocate Memory for Hash Table */ 761 ierr = PetscMalloc((size)*(sizeof(PetscInt)+sizeof(MatScalar*))+1,&baij->hd);CHKERRQ(ierr); 762 baij->ht = (PetscInt*)(baij->hd + size); 763 HD = baij->hd; 764 HT = baij->ht; 765 766 767 ierr = PetscMemzero(HD,size*(sizeof(PetscInt)+sizeof(PetscScalar*)));CHKERRQ(ierr); 768 769 770 /* Loop Over A */ 771 for (i=0; i<a->mbs; i++) { 772 for (j=ai[i]; j<ai[i+1]; j++) { 773 row = i+rstart; 774 col = aj[j]+cstart; 775 776 key = row*Nbs + col + 1; 777 h1 = HASH(size,key,tmp); 778 for (k=0; k<size; k++){ 779 if (!HT[(h1+k)%size]) { 780 HT[(h1+k)%size] = key; 781 HD[(h1+k)%size] = a->a + j*bs2; 782 break; 783 #if defined(PETSC_USE_INFO) 784 } else { 785 ct++; 786 #endif 787 } 788 } 789 #if defined(PETSC_USE_INFO) 790 if (k> max) max = k; 791 #endif 792 } 793 } 794 /* Loop Over B */ 795 for (i=0; i<b->mbs; i++) { 796 for (j=bi[i]; j<bi[i+1]; j++) { 797 row = i+rstart; 798 col = garray[bj[j]]; 799 key = row*Nbs + col + 1; 800 h1 = HASH(size,key,tmp); 801 for (k=0; k<size; k++){ 802 if (!HT[(h1+k)%size]) { 803 HT[(h1+k)%size] = key; 804 HD[(h1+k)%size] = b->a + j*bs2; 805 break; 806 #if defined(PETSC_USE_INFO) 807 } else { 808 ct++; 809 #endif 810 } 811 } 812 #if defined(PETSC_USE_INFO) 813 if (k> max) max = k; 814 #endif 815 } 816 } 817 818 /* Print Summary */ 819 #if defined(PETSC_USE_INFO) 820 for (i=0,j=0; i<size; i++) { 821 if (HT[i]) {j++;} 822 } 823 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 824 #endif 825 PetscFunctionReturn(0); 826 } 827 828 #undef __FUNCT__ 829 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 830 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 831 { 832 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 833 PetscErrorCode ierr; 834 PetscInt nstash,reallocs; 835 InsertMode addv; 836 837 PetscFunctionBegin; 838 if (baij->donotstash) { 839 PetscFunctionReturn(0); 840 } 841 842 /* make sure all processors are either in INSERTMODE or ADDMODE */ 843 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 844 if (addv == (ADD_VALUES|INSERT_VALUES)) { 845 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 846 } 847 mat->insertmode = addv; /* in case this processor had no cache */ 848 849 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 850 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 851 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 852 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 853 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 854 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 855 PetscFunctionReturn(0); 856 } 857 858 #undef __FUNCT__ 859 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 860 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 861 { 862 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 863 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data; 864 PetscErrorCode ierr; 865 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 866 PetscInt *row,*col; 867 PetscTruth r1,r2,r3,other_disassembled; 868 MatScalar *val; 869 InsertMode addv = mat->insertmode; 870 PetscMPIInt n; 871 872 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 873 PetscFunctionBegin; 874 if (!baij->donotstash) { 875 while (1) { 876 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 877 if (!flg) break; 878 879 for (i=0; i<n;) { 880 /* Now identify the consecutive vals belonging to the same row */ 881 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 882 if (j < n) ncols = j-i; 883 else ncols = n-i; 884 /* Now assemble all these values with a single function call */ 885 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 886 i = j; 887 } 888 } 889 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 890 /* Now process the block-stash. Since the values are stashed column-oriented, 891 set the roworiented flag to column oriented, and after MatSetValues() 892 restore the original flags */ 893 r1 = baij->roworiented; 894 r2 = a->roworiented; 895 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 896 baij->roworiented = PETSC_FALSE; 897 a->roworiented = PETSC_FALSE; 898 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 899 while (1) { 900 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 901 if (!flg) break; 902 903 for (i=0; i<n;) { 904 /* Now identify the consecutive vals belonging to the same row */ 905 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 906 if (j < n) ncols = j-i; 907 else ncols = n-i; 908 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 909 i = j; 910 } 911 } 912 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 913 baij->roworiented = r1; 914 a->roworiented = r2; 915 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 916 } 917 918 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 919 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 920 921 /* determine if any processor has disassembled, if so we must 922 also disassemble ourselfs, in order that we may reassemble. */ 923 /* 924 if nonzero structure of submatrix B cannot change then we know that 925 no processor disassembled thus we can skip this stuff 926 */ 927 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 928 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 929 if (mat->was_assembled && !other_disassembled) { 930 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 931 } 932 } 933 934 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 935 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 936 } 937 ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 938 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 939 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 940 941 #if defined(PETSC_USE_INFO) 942 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 943 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 944 baij->ht_total_ct = 0; 945 baij->ht_insert_ct = 0; 946 } 947 #endif 948 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 949 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 950 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 951 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 952 } 953 954 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 955 baij->rowvalues = 0; 956 PetscFunctionReturn(0); 957 } 958 959 #undef __FUNCT__ 960 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 961 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 962 { 963 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 964 PetscErrorCode ierr; 965 PetscMPIInt size = baij->size,rank = baij->rank; 966 PetscInt bs = mat->rmap->bs; 967 PetscTruth iascii,isdraw; 968 PetscViewer sviewer; 969 PetscViewerFormat format; 970 971 PetscFunctionBegin; 972 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 973 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 974 if (iascii) { 975 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 976 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 977 MatInfo info; 978 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 979 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 980 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 981 rank,mat->rmap->N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 982 mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 983 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 984 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 985 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 986 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 987 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 988 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 989 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 990 PetscFunctionReturn(0); 991 } else if (format == PETSC_VIEWER_ASCII_INFO) { 992 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 993 PetscFunctionReturn(0); 994 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 995 PetscFunctionReturn(0); 996 } 997 } 998 999 if (isdraw) { 1000 PetscDraw draw; 1001 PetscTruth isnull; 1002 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1003 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1004 } 1005 1006 if (size == 1) { 1007 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1008 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 1009 } else { 1010 /* assemble the entire matrix onto first processor. */ 1011 Mat A; 1012 Mat_SeqBAIJ *Aloc; 1013 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1014 MatScalar *a; 1015 1016 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1017 /* Perhaps this should be the type of mat? */ 1018 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1019 if (!rank) { 1020 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1021 } else { 1022 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1023 } 1024 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1025 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1026 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1027 1028 /* copy over the A part */ 1029 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1030 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1031 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1032 1033 for (i=0; i<mbs; i++) { 1034 rvals[0] = bs*(baij->rstartbs + i); 1035 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1036 for (j=ai[i]; j<ai[i+1]; j++) { 1037 col = (baij->cstartbs+aj[j])*bs; 1038 for (k=0; k<bs; k++) { 1039 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1040 col++; a += bs; 1041 } 1042 } 1043 } 1044 /* copy over the B part */ 1045 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1046 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1047 for (i=0; i<mbs; i++) { 1048 rvals[0] = bs*(baij->rstartbs + i); 1049 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1050 for (j=ai[i]; j<ai[i+1]; j++) { 1051 col = baij->garray[aj[j]]*bs; 1052 for (k=0; k<bs; k++) { 1053 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1054 col++; a += bs; 1055 } 1056 } 1057 } 1058 ierr = PetscFree(rvals);CHKERRQ(ierr); 1059 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1060 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1061 /* 1062 Everyone has to call to draw the matrix since the graphics waits are 1063 synchronized across all processors that share the PetscDraw object 1064 */ 1065 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1066 if (!rank) { 1067 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1068 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1069 } 1070 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1071 ierr = MatDestroy(A);CHKERRQ(ierr); 1072 } 1073 PetscFunctionReturn(0); 1074 } 1075 1076 #undef __FUNCT__ 1077 #define __FUNCT__ "MatView_MPIBAIJ" 1078 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1079 { 1080 PetscErrorCode ierr; 1081 PetscTruth iascii,isdraw,issocket,isbinary; 1082 1083 PetscFunctionBegin; 1084 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1085 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1086 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1087 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1088 if (iascii || isdraw || issocket || isbinary) { 1089 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1090 } else { 1091 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name); 1092 } 1093 PetscFunctionReturn(0); 1094 } 1095 1096 #undef __FUNCT__ 1097 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1098 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1099 { 1100 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1101 PetscErrorCode ierr; 1102 1103 PetscFunctionBegin; 1104 #if defined(PETSC_USE_LOG) 1105 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1106 #endif 1107 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1108 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1109 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 1110 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 1111 #if defined (PETSC_USE_CTABLE) 1112 if (baij->colmap) {ierr = PetscTableDestroy(baij->colmap);CHKERRQ(ierr);} 1113 #else 1114 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1115 #endif 1116 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1117 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 1118 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 1119 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 1120 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1121 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 1122 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1123 ierr = PetscFree(baij);CHKERRQ(ierr); 1124 1125 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1127 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1128 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1129 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1130 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1131 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1132 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C","",PETSC_NULL);CHKERRQ(ierr); 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "MatMult_MPIBAIJ" 1138 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1139 { 1140 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1141 PetscErrorCode ierr; 1142 PetscInt nt; 1143 1144 PetscFunctionBegin; 1145 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1146 if (nt != A->cmap->n) { 1147 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1148 } 1149 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1150 if (nt != A->rmap->n) { 1151 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1152 } 1153 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1154 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1155 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1156 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1157 PetscFunctionReturn(0); 1158 } 1159 1160 #undef __FUNCT__ 1161 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1162 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1163 { 1164 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1165 PetscErrorCode ierr; 1166 1167 PetscFunctionBegin; 1168 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1169 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1170 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1171 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1172 PetscFunctionReturn(0); 1173 } 1174 1175 #undef __FUNCT__ 1176 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1177 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1178 { 1179 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1180 PetscErrorCode ierr; 1181 PetscTruth merged; 1182 1183 PetscFunctionBegin; 1184 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1185 /* do nondiagonal part */ 1186 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1187 if (!merged) { 1188 /* send it on its way */ 1189 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1190 /* do local part */ 1191 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1192 /* receive remote parts: note this assumes the values are not actually */ 1193 /* inserted in yy until the next line */ 1194 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1195 } else { 1196 /* do local part */ 1197 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1198 /* send it on its way */ 1199 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1200 /* values actually were received in the Begin() but we need to call this nop */ 1201 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1202 } 1203 PetscFunctionReturn(0); 1204 } 1205 1206 #undef __FUNCT__ 1207 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1208 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1209 { 1210 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1211 PetscErrorCode ierr; 1212 1213 PetscFunctionBegin; 1214 /* do nondiagonal part */ 1215 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1216 /* send it on its way */ 1217 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1218 /* do local part */ 1219 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1220 /* receive remote parts: note this assumes the values are not actually */ 1221 /* inserted in yy until the next line, which is true for my implementation*/ 1222 /* but is not perhaps always true. */ 1223 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1224 PetscFunctionReturn(0); 1225 } 1226 1227 /* 1228 This only works correctly for square matrices where the subblock A->A is the 1229 diagonal block 1230 */ 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1233 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1234 { 1235 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1236 PetscErrorCode ierr; 1237 1238 PetscFunctionBegin; 1239 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1240 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatScale_MPIBAIJ" 1246 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1247 { 1248 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1249 PetscErrorCode ierr; 1250 1251 PetscFunctionBegin; 1252 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1253 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1254 PetscFunctionReturn(0); 1255 } 1256 1257 #undef __FUNCT__ 1258 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1259 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1260 { 1261 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1262 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1263 PetscErrorCode ierr; 1264 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1265 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1266 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1267 1268 PetscFunctionBegin; 1269 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1270 mat->getrowactive = PETSC_TRUE; 1271 1272 if (!mat->rowvalues && (idx || v)) { 1273 /* 1274 allocate enough space to hold information from the longest row. 1275 */ 1276 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1277 PetscInt max = 1,mbs = mat->mbs,tmp; 1278 for (i=0; i<mbs; i++) { 1279 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1280 if (max < tmp) { max = tmp; } 1281 } 1282 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1283 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 1284 } 1285 1286 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 1287 lrow = row - brstart; 1288 1289 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1290 if (!v) {pvA = 0; pvB = 0;} 1291 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1292 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1293 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1294 nztot = nzA + nzB; 1295 1296 cmap = mat->garray; 1297 if (v || idx) { 1298 if (nztot) { 1299 /* Sort by increasing column numbers, assuming A and B already sorted */ 1300 PetscInt imark = -1; 1301 if (v) { 1302 *v = v_p = mat->rowvalues; 1303 for (i=0; i<nzB; i++) { 1304 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1305 else break; 1306 } 1307 imark = i; 1308 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1309 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1310 } 1311 if (idx) { 1312 *idx = idx_p = mat->rowindices; 1313 if (imark > -1) { 1314 for (i=0; i<imark; i++) { 1315 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1316 } 1317 } else { 1318 for (i=0; i<nzB; i++) { 1319 if (cmap[cworkB[i]/bs] < cstart) 1320 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1321 else break; 1322 } 1323 imark = i; 1324 } 1325 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1326 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1327 } 1328 } else { 1329 if (idx) *idx = 0; 1330 if (v) *v = 0; 1331 } 1332 } 1333 *nz = nztot; 1334 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1335 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1336 PetscFunctionReturn(0); 1337 } 1338 1339 #undef __FUNCT__ 1340 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1341 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1342 { 1343 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1344 1345 PetscFunctionBegin; 1346 if (!baij->getrowactive) { 1347 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1348 } 1349 baij->getrowactive = PETSC_FALSE; 1350 PetscFunctionReturn(0); 1351 } 1352 1353 #undef __FUNCT__ 1354 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1355 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1356 { 1357 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1358 PetscErrorCode ierr; 1359 1360 PetscFunctionBegin; 1361 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1362 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1363 PetscFunctionReturn(0); 1364 } 1365 1366 #undef __FUNCT__ 1367 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1368 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1369 { 1370 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1371 Mat A = a->A,B = a->B; 1372 PetscErrorCode ierr; 1373 PetscReal isend[5],irecv[5]; 1374 1375 PetscFunctionBegin; 1376 info->block_size = (PetscReal)matin->rmap->bs; 1377 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1378 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1379 isend[3] = info->memory; isend[4] = info->mallocs; 1380 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1381 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1382 isend[3] += info->memory; isend[4] += info->mallocs; 1383 if (flag == MAT_LOCAL) { 1384 info->nz_used = isend[0]; 1385 info->nz_allocated = isend[1]; 1386 info->nz_unneeded = isend[2]; 1387 info->memory = isend[3]; 1388 info->mallocs = isend[4]; 1389 } else if (flag == MAT_GLOBAL_MAX) { 1390 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1391 info->nz_used = irecv[0]; 1392 info->nz_allocated = irecv[1]; 1393 info->nz_unneeded = irecv[2]; 1394 info->memory = irecv[3]; 1395 info->mallocs = irecv[4]; 1396 } else if (flag == MAT_GLOBAL_SUM) { 1397 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1398 info->nz_used = irecv[0]; 1399 info->nz_allocated = irecv[1]; 1400 info->nz_unneeded = irecv[2]; 1401 info->memory = irecv[3]; 1402 info->mallocs = irecv[4]; 1403 } else { 1404 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1405 } 1406 info->rows_global = (PetscReal)A->rmap->N; 1407 info->columns_global = (PetscReal)A->cmap->N; 1408 info->rows_local = (PetscReal)A->rmap->N; 1409 info->columns_local = (PetscReal)A->cmap->N; 1410 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1411 info->fill_ratio_needed = 0; 1412 info->factor_mallocs = 0; 1413 PetscFunctionReturn(0); 1414 } 1415 1416 #undef __FUNCT__ 1417 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1418 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscTruth flg) 1419 { 1420 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1421 PetscErrorCode ierr; 1422 1423 PetscFunctionBegin; 1424 switch (op) { 1425 case MAT_NEW_NONZERO_LOCATIONS: 1426 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1427 case MAT_KEEP_ZEROED_ROWS: 1428 case MAT_NEW_NONZERO_LOCATION_ERR: 1429 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1430 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1431 break; 1432 case MAT_ROW_ORIENTED: 1433 a->roworiented = flg; 1434 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1435 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1436 break; 1437 case MAT_NEW_DIAGONALS: 1438 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1439 break; 1440 case MAT_IGNORE_OFF_PROC_ENTRIES: 1441 a->donotstash = flg; 1442 break; 1443 case MAT_USE_HASH_TABLE: 1444 a->ht_flag = flg; 1445 break; 1446 case MAT_SYMMETRIC: 1447 case MAT_STRUCTURALLY_SYMMETRIC: 1448 case MAT_HERMITIAN: 1449 case MAT_SYMMETRY_ETERNAL: 1450 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1451 break; 1452 default: 1453 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1454 } 1455 PetscFunctionReturn(0); 1456 } 1457 1458 #undef __FUNCT__ 1459 #define __FUNCT__ "MatTranspose_MPIBAIJ(" 1460 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1461 { 1462 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1463 Mat_SeqBAIJ *Aloc; 1464 Mat B; 1465 PetscErrorCode ierr; 1466 PetscInt M=A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1467 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1468 MatScalar *a; 1469 1470 PetscFunctionBegin; 1471 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1472 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1473 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1474 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1475 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1476 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1477 } else { 1478 B = *matout; 1479 } 1480 1481 /* copy over the A part */ 1482 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1483 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1484 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 1485 1486 for (i=0; i<mbs; i++) { 1487 rvals[0] = bs*(baij->rstartbs + i); 1488 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1489 for (j=ai[i]; j<ai[i+1]; j++) { 1490 col = (baij->cstartbs+aj[j])*bs; 1491 for (k=0; k<bs; k++) { 1492 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1493 col++; a += bs; 1494 } 1495 } 1496 } 1497 /* copy over the B part */ 1498 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1499 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1500 for (i=0; i<mbs; i++) { 1501 rvals[0] = bs*(baij->rstartbs + i); 1502 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 1503 for (j=ai[i]; j<ai[i+1]; j++) { 1504 col = baij->garray[aj[j]]*bs; 1505 for (k=0; k<bs; k++) { 1506 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1507 col++; a += bs; 1508 } 1509 } 1510 } 1511 ierr = PetscFree(rvals);CHKERRQ(ierr); 1512 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1513 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1514 1515 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1516 *matout = B; 1517 } else { 1518 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1519 } 1520 PetscFunctionReturn(0); 1521 } 1522 1523 #undef __FUNCT__ 1524 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1525 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1526 { 1527 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1528 Mat a = baij->A,b = baij->B; 1529 PetscErrorCode ierr; 1530 PetscInt s1,s2,s3; 1531 1532 PetscFunctionBegin; 1533 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1534 if (rr) { 1535 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1536 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1537 /* Overlap communication with computation. */ 1538 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1539 } 1540 if (ll) { 1541 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1542 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1543 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1544 } 1545 /* scale the diagonal block */ 1546 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1547 1548 if (rr) { 1549 /* Do a scatter end and then right scale the off-diagonal block */ 1550 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1551 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1552 } 1553 1554 PetscFunctionReturn(0); 1555 } 1556 1557 #undef __FUNCT__ 1558 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1559 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 1560 { 1561 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1562 PetscErrorCode ierr; 1563 PetscMPIInt imdex,size = l->size,n,rank = l->rank; 1564 PetscInt i,*owners = A->rmap->range; 1565 PetscInt *nprocs,j,idx,nsends,row; 1566 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 1567 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1; 1568 PetscInt *lens,*lrows,*values,rstart_bs=A->rmap->rstart; 1569 MPI_Comm comm = ((PetscObject)A)->comm; 1570 MPI_Request *send_waits,*recv_waits; 1571 MPI_Status recv_status,*send_status; 1572 #if defined(PETSC_DEBUG) 1573 PetscTruth found = PETSC_FALSE; 1574 #endif 1575 1576 PetscFunctionBegin; 1577 /* first count number of contributors to each processor */ 1578 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 1579 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 1580 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 1581 j = 0; 1582 for (i=0; i<N; i++) { 1583 if (lastidx > (idx = rows[i])) j = 0; 1584 lastidx = idx; 1585 for (; j<size; j++) { 1586 if (idx >= owners[j] && idx < owners[j+1]) { 1587 nprocs[2*j]++; 1588 nprocs[2*j+1] = 1; 1589 owner[i] = j; 1590 #if defined(PETSC_DEBUG) 1591 found = PETSC_TRUE; 1592 #endif 1593 break; 1594 } 1595 } 1596 #if defined(PETSC_DEBUG) 1597 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1598 found = PETSC_FALSE; 1599 #endif 1600 } 1601 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 1602 1603 /* inform other processors of number of messages and max length*/ 1604 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 1605 1606 /* post receives: */ 1607 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 1608 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 1609 for (i=0; i<nrecvs; i++) { 1610 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1611 } 1612 1613 /* do sends: 1614 1) starts[i] gives the starting index in svalues for stuff going to 1615 the ith processor 1616 */ 1617 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 1618 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 1619 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 1620 starts[0] = 0; 1621 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1622 for (i=0; i<N; i++) { 1623 svalues[starts[owner[i]]++] = rows[i]; 1624 } 1625 1626 starts[0] = 0; 1627 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 1628 count = 0; 1629 for (i=0; i<size; i++) { 1630 if (nprocs[2*i+1]) { 1631 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1632 } 1633 } 1634 ierr = PetscFree(starts);CHKERRQ(ierr); 1635 1636 base = owners[rank]; 1637 1638 /* wait on receives */ 1639 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1640 source = lens + nrecvs; 1641 count = nrecvs; slen = 0; 1642 while (count) { 1643 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1644 /* unpack receives into our local space */ 1645 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 1646 source[imdex] = recv_status.MPI_SOURCE; 1647 lens[imdex] = n; 1648 slen += n; 1649 count--; 1650 } 1651 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1652 1653 /* move the data into the send scatter */ 1654 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1655 count = 0; 1656 for (i=0; i<nrecvs; i++) { 1657 values = rvalues + i*nmax; 1658 for (j=0; j<lens[i]; j++) { 1659 lrows[count++] = values[j] - base; 1660 } 1661 } 1662 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1663 ierr = PetscFree(lens);CHKERRQ(ierr); 1664 ierr = PetscFree(owner);CHKERRQ(ierr); 1665 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1666 1667 /* actually zap the local rows */ 1668 /* 1669 Zero the required rows. If the "diagonal block" of the matrix 1670 is square and the user wishes to set the diagonal we use separate 1671 code so that MatSetValues() is not called for each diagonal allocating 1672 new memory, thus calling lots of mallocs and slowing things down. 1673 1674 Contributed by: Matthew Knepley 1675 */ 1676 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1677 ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0);CHKERRQ(ierr); 1678 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1679 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag);CHKERRQ(ierr); 1680 } else if (diag != 0.0) { 1681 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1682 if (((Mat_SeqBAIJ*)l->A->data)->nonew) { 1683 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1684 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1685 } 1686 for (i=0; i<slen; i++) { 1687 row = lrows[i] + rstart_bs; 1688 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1689 } 1690 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1691 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1692 } else { 1693 ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0);CHKERRQ(ierr); 1694 } 1695 1696 ierr = PetscFree(lrows);CHKERRQ(ierr); 1697 1698 /* wait on sends */ 1699 if (nsends) { 1700 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1701 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1702 ierr = PetscFree(send_status);CHKERRQ(ierr); 1703 } 1704 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1705 ierr = PetscFree(svalues);CHKERRQ(ierr); 1706 1707 PetscFunctionReturn(0); 1708 } 1709 1710 #undef __FUNCT__ 1711 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1712 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1713 { 1714 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1715 PetscErrorCode ierr; 1716 1717 PetscFunctionBegin; 1718 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1719 PetscFunctionReturn(0); 1720 } 1721 1722 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *); 1723 1724 #undef __FUNCT__ 1725 #define __FUNCT__ "MatEqual_MPIBAIJ" 1726 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag) 1727 { 1728 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1729 Mat a,b,c,d; 1730 PetscTruth flg; 1731 PetscErrorCode ierr; 1732 1733 PetscFunctionBegin; 1734 a = matA->A; b = matA->B; 1735 c = matB->A; d = matB->B; 1736 1737 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1738 if (flg) { 1739 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1740 } 1741 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1742 PetscFunctionReturn(0); 1743 } 1744 1745 #undef __FUNCT__ 1746 #define __FUNCT__ "MatCopy_MPIBAIJ" 1747 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 1748 { 1749 PetscErrorCode ierr; 1750 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 1751 Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data; 1752 1753 PetscFunctionBegin; 1754 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1755 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1756 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1757 } else { 1758 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1759 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1760 } 1761 PetscFunctionReturn(0); 1762 } 1763 1764 #undef __FUNCT__ 1765 #define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ" 1766 PetscErrorCode MatSetUpPreallocation_MPIBAIJ(Mat A) 1767 { 1768 PetscErrorCode ierr; 1769 1770 PetscFunctionBegin; 1771 ierr = MatMPIBAIJSetPreallocation(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1772 PetscFunctionReturn(0); 1773 } 1774 1775 #include "petscblaslapack.h" 1776 #undef __FUNCT__ 1777 #define __FUNCT__ "MatAXPY_MPIBAIJ" 1778 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1779 { 1780 PetscErrorCode ierr; 1781 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ *)X->data,*yy=(Mat_MPIBAIJ *)Y->data; 1782 PetscBLASInt bnz,one=1; 1783 Mat_SeqBAIJ *x,*y; 1784 1785 PetscFunctionBegin; 1786 if (str == SAME_NONZERO_PATTERN) { 1787 PetscScalar alpha = a; 1788 x = (Mat_SeqBAIJ *)xx->A->data; 1789 y = (Mat_SeqBAIJ *)yy->A->data; 1790 bnz = PetscBLASIntCast(x->nz); 1791 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1792 x = (Mat_SeqBAIJ *)xx->B->data; 1793 y = (Mat_SeqBAIJ *)yy->B->data; 1794 bnz = PetscBLASIntCast(x->nz); 1795 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1796 } else { 1797 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1798 } 1799 PetscFunctionReturn(0); 1800 } 1801 1802 #undef __FUNCT__ 1803 #define __FUNCT__ "MatRealPart_MPIBAIJ" 1804 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 1805 { 1806 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1807 PetscErrorCode ierr; 1808 1809 PetscFunctionBegin; 1810 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1811 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1812 PetscFunctionReturn(0); 1813 } 1814 1815 #undef __FUNCT__ 1816 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 1817 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 1818 { 1819 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1820 PetscErrorCode ierr; 1821 1822 PetscFunctionBegin; 1823 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1824 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1825 PetscFunctionReturn(0); 1826 } 1827 1828 /* -------------------------------------------------------------------*/ 1829 static struct _MatOps MatOps_Values = { 1830 MatSetValues_MPIBAIJ, 1831 MatGetRow_MPIBAIJ, 1832 MatRestoreRow_MPIBAIJ, 1833 MatMult_MPIBAIJ, 1834 /* 4*/ MatMultAdd_MPIBAIJ, 1835 MatMultTranspose_MPIBAIJ, 1836 MatMultTransposeAdd_MPIBAIJ, 1837 0, 1838 0, 1839 0, 1840 /*10*/ 0, 1841 0, 1842 0, 1843 0, 1844 MatTranspose_MPIBAIJ, 1845 /*15*/ MatGetInfo_MPIBAIJ, 1846 MatEqual_MPIBAIJ, 1847 MatGetDiagonal_MPIBAIJ, 1848 MatDiagonalScale_MPIBAIJ, 1849 MatNorm_MPIBAIJ, 1850 /*20*/ MatAssemblyBegin_MPIBAIJ, 1851 MatAssemblyEnd_MPIBAIJ, 1852 0, 1853 MatSetOption_MPIBAIJ, 1854 MatZeroEntries_MPIBAIJ, 1855 /*25*/ MatZeroRows_MPIBAIJ, 1856 0, 1857 0, 1858 0, 1859 0, 1860 /*30*/ MatSetUpPreallocation_MPIBAIJ, 1861 0, 1862 0, 1863 0, 1864 0, 1865 /*35*/ MatDuplicate_MPIBAIJ, 1866 0, 1867 0, 1868 0, 1869 0, 1870 /*40*/ MatAXPY_MPIBAIJ, 1871 MatGetSubMatrices_MPIBAIJ, 1872 MatIncreaseOverlap_MPIBAIJ, 1873 MatGetValues_MPIBAIJ, 1874 MatCopy_MPIBAIJ, 1875 /*45*/ 0, 1876 MatScale_MPIBAIJ, 1877 0, 1878 0, 1879 0, 1880 /*50*/ 0, 1881 0, 1882 0, 1883 0, 1884 0, 1885 /*55*/ 0, 1886 0, 1887 MatSetUnfactored_MPIBAIJ, 1888 0, 1889 MatSetValuesBlocked_MPIBAIJ, 1890 /*60*/ 0, 1891 MatDestroy_MPIBAIJ, 1892 MatView_MPIBAIJ, 1893 0, 1894 0, 1895 /*65*/ 0, 1896 0, 1897 0, 1898 0, 1899 0, 1900 /*70*/ MatGetRowMaxAbs_MPIBAIJ, 1901 0, 1902 0, 1903 0, 1904 0, 1905 /*75*/ 0, 1906 0, 1907 0, 1908 0, 1909 0, 1910 /*80*/ 0, 1911 0, 1912 0, 1913 0, 1914 MatLoad_MPIBAIJ, 1915 /*85*/ 0, 1916 0, 1917 0, 1918 0, 1919 0, 1920 /*90*/ 0, 1921 0, 1922 0, 1923 0, 1924 0, 1925 /*95*/ 0, 1926 0, 1927 0, 1928 0, 1929 0, 1930 /*100*/0, 1931 0, 1932 0, 1933 0, 1934 0, 1935 /*105*/0, 1936 MatRealPart_MPIBAIJ, 1937 MatImaginaryPart_MPIBAIJ}; 1938 1939 1940 EXTERN_C_BEGIN 1941 #undef __FUNCT__ 1942 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 1943 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1944 { 1945 PetscFunctionBegin; 1946 *a = ((Mat_MPIBAIJ *)A->data)->A; 1947 *iscopy = PETSC_FALSE; 1948 PetscFunctionReturn(0); 1949 } 1950 EXTERN_C_END 1951 1952 EXTERN_C_BEGIN 1953 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 1954 EXTERN_C_END 1955 1956 EXTERN_C_BEGIN 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 1959 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 1960 { 1961 PetscInt m,rstart,cstart,cend; 1962 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 1963 const PetscInt *JJ=0; 1964 PetscScalar *values=0; 1965 PetscErrorCode ierr; 1966 1967 PetscFunctionBegin; 1968 1969 if (bs < 1) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 1970 B->rmap->bs = bs; 1971 B->cmap->bs = bs; 1972 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 1973 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 1974 m = B->rmap->n/bs; 1975 rstart = B->rmap->rstart/bs; 1976 cstart = B->cmap->rstart/bs; 1977 cend = B->cmap->rend/bs; 1978 1979 if (ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 1980 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1981 o_nnz = d_nnz + m; 1982 for (i=0; i<m; i++) { 1983 nz = ii[i+1] - ii[i]; 1984 if (nz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 1985 nz_max = PetscMax(nz_max,nz); 1986 JJ = jj + ii[i]; 1987 for (j=0; j<nz; j++) { 1988 if (*JJ >= cstart) break; 1989 JJ++; 1990 } 1991 d = 0; 1992 for (; j<nz; j++) { 1993 if (*JJ++ >= cend) break; 1994 d++; 1995 } 1996 d_nnz[i] = d; 1997 o_nnz[i] = nz - d; 1998 } 1999 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2000 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2001 2002 values = (PetscScalar*)V; 2003 if (!values) { 2004 ierr = PetscMalloc(bs*bs*(nz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2005 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2006 } 2007 for (i=0; i<m; i++) { 2008 PetscInt row = i + rstart; 2009 PetscInt ncols = ii[i+1] - ii[i]; 2010 const PetscInt *icols = jj + ii[i]; 2011 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2012 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2013 } 2014 2015 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2016 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2017 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2018 2019 PetscFunctionReturn(0); 2020 } 2021 EXTERN_C_END 2022 2023 #undef __FUNCT__ 2024 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2025 /*@C 2026 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2027 (the default parallel PETSc format). 2028 2029 Collective on MPI_Comm 2030 2031 Input Parameters: 2032 + A - the matrix 2033 . i - the indices into j for the start of each local row (starts with zero) 2034 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2035 - v - optional values in the matrix 2036 2037 Level: developer 2038 2039 .keywords: matrix, aij, compressed row, sparse, parallel 2040 2041 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ 2042 @*/ 2043 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2044 { 2045 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]); 2046 2047 PetscFunctionBegin; 2048 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2049 if (f) { 2050 ierr = (*f)(B,bs,i,j,v);CHKERRQ(ierr); 2051 } 2052 PetscFunctionReturn(0); 2053 } 2054 2055 EXTERN_C_BEGIN 2056 #undef __FUNCT__ 2057 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2058 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 2059 { 2060 Mat_MPIBAIJ *b; 2061 PetscErrorCode ierr; 2062 PetscInt i, newbs = PetscAbs(bs); 2063 2064 PetscFunctionBegin; 2065 B->preallocated = PETSC_TRUE; 2066 if (bs < 0) { 2067 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPIBAIJ matrix","Mat");CHKERRQ(ierr); 2068 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);CHKERRQ(ierr); 2069 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2070 bs = PetscAbs(bs); 2071 } 2072 if ((d_nnz || o_nnz) && newbs != bs) { 2073 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz"); 2074 } 2075 bs = newbs; 2076 2077 2078 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2079 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2080 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2081 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2082 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2083 2084 B->rmap->bs = bs; 2085 B->cmap->bs = bs; 2086 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2087 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2088 2089 if (d_nnz) { 2090 for (i=0; i<B->rmap->n/bs; i++) { 2091 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2092 } 2093 } 2094 if (o_nnz) { 2095 for (i=0; i<B->rmap->n/bs; i++) { 2096 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2097 } 2098 } 2099 2100 b = (Mat_MPIBAIJ*)B->data; 2101 b->bs2 = bs*bs; 2102 b->mbs = B->rmap->n/bs; 2103 b->nbs = B->cmap->n/bs; 2104 b->Mbs = B->rmap->N/bs; 2105 b->Nbs = B->cmap->N/bs; 2106 2107 for (i=0; i<=b->size; i++) { 2108 b->rangebs[i] = B->rmap->range[i]/bs; 2109 } 2110 b->rstartbs = B->rmap->rstart/bs; 2111 b->rendbs = B->rmap->rend/bs; 2112 b->cstartbs = B->cmap->rstart/bs; 2113 b->cendbs = B->cmap->rend/bs; 2114 2115 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2116 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2117 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2118 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2119 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2120 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2121 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2122 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2123 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2124 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2125 2126 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 2127 2128 PetscFunctionReturn(0); 2129 } 2130 EXTERN_C_END 2131 2132 EXTERN_C_BEGIN 2133 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2134 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2135 EXTERN_C_END 2136 2137 /*MC 2138 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2139 2140 Options Database Keys: 2141 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2142 . -mat_block_size <bs> - set the blocksize used to store the matrix 2143 - -mat_use_hash_table <fact> 2144 2145 Level: beginner 2146 2147 .seealso: MatCreateMPIBAIJ 2148 M*/ 2149 2150 EXTERN_C_BEGIN 2151 #undef __FUNCT__ 2152 #define __FUNCT__ "MatCreate_MPIBAIJ" 2153 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2154 { 2155 Mat_MPIBAIJ *b; 2156 PetscErrorCode ierr; 2157 PetscTruth flg; 2158 2159 PetscFunctionBegin; 2160 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2161 B->data = (void*)b; 2162 2163 2164 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2165 B->mapping = 0; 2166 B->assembled = PETSC_FALSE; 2167 2168 B->insertmode = NOT_SET_VALUES; 2169 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 2170 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 2171 2172 /* build local table of row and column ownerships */ 2173 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 2174 2175 /* build cache for off array entries formed */ 2176 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 2177 b->donotstash = PETSC_FALSE; 2178 b->colmap = PETSC_NULL; 2179 b->garray = PETSC_NULL; 2180 b->roworiented = PETSC_TRUE; 2181 2182 /* stuff used in block assembly */ 2183 b->barray = 0; 2184 2185 /* stuff used for matrix vector multiply */ 2186 b->lvec = 0; 2187 b->Mvctx = 0; 2188 2189 /* stuff for MatGetRow() */ 2190 b->rowindices = 0; 2191 b->rowvalues = 0; 2192 b->getrowactive = PETSC_FALSE; 2193 2194 /* hash table stuff */ 2195 b->ht = 0; 2196 b->hd = 0; 2197 b->ht_size = 0; 2198 b->ht_flag = PETSC_FALSE; 2199 b->ht_fact = 0; 2200 b->ht_total_ct = 0; 2201 b->ht_insert_ct = 0; 2202 2203 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 2204 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 2205 if (flg) { 2206 PetscReal fact = 1.39; 2207 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 2208 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 2209 if (fact <= 1.0) fact = 1.39; 2210 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2211 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 2212 } 2213 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2214 2215 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2216 "MatStoreValues_MPIBAIJ", 2217 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2218 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2219 "MatRetrieveValues_MPIBAIJ", 2220 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2221 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2222 "MatGetDiagonalBlock_MPIBAIJ", 2223 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2224 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2225 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2226 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2227 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2228 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 2229 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2230 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2231 "MatDiagonalScaleLocal_MPIBAIJ", 2232 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2233 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2234 "MatSetHashTableFactor_MPIBAIJ", 2235 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2236 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 2237 PetscFunctionReturn(0); 2238 } 2239 EXTERN_C_END 2240 2241 /*MC 2242 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2243 2244 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2245 and MATMPIBAIJ otherwise. 2246 2247 Options Database Keys: 2248 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2249 2250 Level: beginner 2251 2252 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2253 M*/ 2254 2255 EXTERN_C_BEGIN 2256 #undef __FUNCT__ 2257 #define __FUNCT__ "MatCreate_BAIJ" 2258 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2259 { 2260 PetscErrorCode ierr; 2261 PetscMPIInt size; 2262 2263 PetscFunctionBegin; 2264 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2265 if (size == 1) { 2266 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2267 } else { 2268 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2269 } 2270 PetscFunctionReturn(0); 2271 } 2272 EXTERN_C_END 2273 2274 #undef __FUNCT__ 2275 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2276 /*@C 2277 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2278 (block compressed row). For good matrix assembly performance 2279 the user should preallocate the matrix storage by setting the parameters 2280 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2281 performance can be increased by more than a factor of 50. 2282 2283 Collective on Mat 2284 2285 Input Parameters: 2286 + A - the matrix 2287 . bs - size of blockk 2288 . d_nz - number of block nonzeros per block row in diagonal portion of local 2289 submatrix (same for all local rows) 2290 . d_nnz - array containing the number of block nonzeros in the various block rows 2291 of the in diagonal portion of the local (possibly different for each block 2292 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2293 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2294 submatrix (same for all local rows). 2295 - o_nnz - array containing the number of nonzeros in the various block rows of the 2296 off-diagonal portion of the local submatrix (possibly different for 2297 each block row) or PETSC_NULL. 2298 2299 If the *_nnz parameter is given then the *_nz parameter is ignored 2300 2301 Options Database Keys: 2302 + -mat_block_size - size of the blocks to use 2303 - -mat_use_hash_table <fact> 2304 2305 Notes: 2306 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2307 than it must be used on all processors that share the object for that argument. 2308 2309 Storage Information: 2310 For a square global matrix we define each processor's diagonal portion 2311 to be its local rows and the corresponding columns (a square submatrix); 2312 each processor's off-diagonal portion encompasses the remainder of the 2313 local matrix (a rectangular submatrix). 2314 2315 The user can specify preallocated storage for the diagonal part of 2316 the local submatrix with either d_nz or d_nnz (not both). Set 2317 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2318 memory allocation. Likewise, specify preallocated storage for the 2319 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2320 2321 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2322 the figure below we depict these three local rows and all columns (0-11). 2323 2324 .vb 2325 0 1 2 3 4 5 6 7 8 9 10 11 2326 ------------------- 2327 row 3 | o o o d d d o o o o o o 2328 row 4 | o o o d d d o o o o o o 2329 row 5 | o o o d d d o o o o o o 2330 ------------------- 2331 .ve 2332 2333 Thus, any entries in the d locations are stored in the d (diagonal) 2334 submatrix, and any entries in the o locations are stored in the 2335 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2336 stored simply in the MATSEQBAIJ format for compressed row storage. 2337 2338 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2339 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2340 In general, for PDE problems in which most nonzeros are near the diagonal, 2341 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2342 or you will get TERRIBLE performance; see the users' manual chapter on 2343 matrices. 2344 2345 You can call MatGetInfo() to get information on how effective the preallocation was; 2346 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2347 You can also run with the option -info and look for messages with the string 2348 malloc in them to see if additional memory allocation was needed. 2349 2350 Level: intermediate 2351 2352 .keywords: matrix, block, aij, compressed row, sparse, parallel 2353 2354 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2355 @*/ 2356 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2357 { 2358 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2359 2360 PetscFunctionBegin; 2361 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2362 if (f) { 2363 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2364 } 2365 PetscFunctionReturn(0); 2366 } 2367 2368 #undef __FUNCT__ 2369 #define __FUNCT__ "MatCreateMPIBAIJ" 2370 /*@C 2371 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2372 (block compressed row). For good matrix assembly performance 2373 the user should preallocate the matrix storage by setting the parameters 2374 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2375 performance can be increased by more than a factor of 50. 2376 2377 Collective on MPI_Comm 2378 2379 Input Parameters: 2380 + comm - MPI communicator 2381 . bs - size of blockk 2382 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2383 This value should be the same as the local size used in creating the 2384 y vector for the matrix-vector product y = Ax. 2385 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2386 This value should be the same as the local size used in creating the 2387 x vector for the matrix-vector product y = Ax. 2388 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2389 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2390 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2391 submatrix (same for all local rows) 2392 . d_nnz - array containing the number of nonzero blocks in the various block rows 2393 of the in diagonal portion of the local (possibly different for each block 2394 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2395 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2396 submatrix (same for all local rows). 2397 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2398 off-diagonal portion of the local submatrix (possibly different for 2399 each block row) or PETSC_NULL. 2400 2401 Output Parameter: 2402 . A - the matrix 2403 2404 Options Database Keys: 2405 + -mat_block_size - size of the blocks to use 2406 - -mat_use_hash_table <fact> 2407 2408 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2409 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 2410 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 2411 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2412 2413 Notes: 2414 If the *_nnz parameter is given then the *_nz parameter is ignored 2415 2416 A nonzero block is any block that as 1 or more nonzeros in it 2417 2418 The user MUST specify either the local or global matrix dimensions 2419 (possibly both). 2420 2421 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2422 than it must be used on all processors that share the object for that argument. 2423 2424 Storage Information: 2425 For a square global matrix we define each processor's diagonal portion 2426 to be its local rows and the corresponding columns (a square submatrix); 2427 each processor's off-diagonal portion encompasses the remainder of the 2428 local matrix (a rectangular submatrix). 2429 2430 The user can specify preallocated storage for the diagonal part of 2431 the local submatrix with either d_nz or d_nnz (not both). Set 2432 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2433 memory allocation. Likewise, specify preallocated storage for the 2434 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2435 2436 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2437 the figure below we depict these three local rows and all columns (0-11). 2438 2439 .vb 2440 0 1 2 3 4 5 6 7 8 9 10 11 2441 ------------------- 2442 row 3 | o o o d d d o o o o o o 2443 row 4 | o o o d d d o o o o o o 2444 row 5 | o o o d d d o o o o o o 2445 ------------------- 2446 .ve 2447 2448 Thus, any entries in the d locations are stored in the d (diagonal) 2449 submatrix, and any entries in the o locations are stored in the 2450 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2451 stored simply in the MATSEQBAIJ format for compressed row storage. 2452 2453 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2454 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2455 In general, for PDE problems in which most nonzeros are near the diagonal, 2456 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2457 or you will get TERRIBLE performance; see the users' manual chapter on 2458 matrices. 2459 2460 Level: intermediate 2461 2462 .keywords: matrix, block, aij, compressed row, sparse, parallel 2463 2464 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2465 @*/ 2466 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIBAIJ(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) 2467 { 2468 PetscErrorCode ierr; 2469 PetscMPIInt size; 2470 2471 PetscFunctionBegin; 2472 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2473 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2474 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2475 if (size > 1) { 2476 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2477 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2478 } else { 2479 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2480 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2481 } 2482 PetscFunctionReturn(0); 2483 } 2484 2485 #undef __FUNCT__ 2486 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2487 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2488 { 2489 Mat mat; 2490 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2491 PetscErrorCode ierr; 2492 PetscInt len=0; 2493 2494 PetscFunctionBegin; 2495 *newmat = 0; 2496 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2497 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2498 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2499 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2500 2501 mat->factor = matin->factor; 2502 mat->preallocated = PETSC_TRUE; 2503 mat->assembled = PETSC_TRUE; 2504 mat->insertmode = NOT_SET_VALUES; 2505 2506 a = (Mat_MPIBAIJ*)mat->data; 2507 mat->rmap->bs = matin->rmap->bs; 2508 a->bs2 = oldmat->bs2; 2509 a->mbs = oldmat->mbs; 2510 a->nbs = oldmat->nbs; 2511 a->Mbs = oldmat->Mbs; 2512 a->Nbs = oldmat->Nbs; 2513 2514 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 2515 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 2516 2517 a->size = oldmat->size; 2518 a->rank = oldmat->rank; 2519 a->donotstash = oldmat->donotstash; 2520 a->roworiented = oldmat->roworiented; 2521 a->rowindices = 0; 2522 a->rowvalues = 0; 2523 a->getrowactive = PETSC_FALSE; 2524 a->barray = 0; 2525 a->rstartbs = oldmat->rstartbs; 2526 a->rendbs = oldmat->rendbs; 2527 a->cstartbs = oldmat->cstartbs; 2528 a->cendbs = oldmat->cendbs; 2529 2530 /* hash table stuff */ 2531 a->ht = 0; 2532 a->hd = 0; 2533 a->ht_size = 0; 2534 a->ht_flag = oldmat->ht_flag; 2535 a->ht_fact = oldmat->ht_fact; 2536 a->ht_total_ct = 0; 2537 a->ht_insert_ct = 0; 2538 2539 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 2540 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2541 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2542 if (oldmat->colmap) { 2543 #if defined (PETSC_USE_CTABLE) 2544 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2545 #else 2546 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2547 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2548 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2549 #endif 2550 } else a->colmap = 0; 2551 2552 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2553 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2554 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2555 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2556 } else a->garray = 0; 2557 2558 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2559 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2560 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2561 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2562 2563 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2564 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2565 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2566 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2567 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2568 *newmat = mat; 2569 2570 PetscFunctionReturn(0); 2571 } 2572 2573 #include "petscsys.h" 2574 2575 #undef __FUNCT__ 2576 #define __FUNCT__ "MatLoad_MPIBAIJ" 2577 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2578 { 2579 Mat A; 2580 PetscErrorCode ierr; 2581 int fd; 2582 PetscInt i,nz,j,rstart,rend; 2583 PetscScalar *vals,*buf; 2584 MPI_Comm comm = ((PetscObject)viewer)->comm; 2585 MPI_Status status; 2586 PetscMPIInt rank,size,maxnz; 2587 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2588 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 2589 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2590 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2591 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 2592 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2593 2594 PetscFunctionBegin; 2595 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 2596 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2597 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2598 2599 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2600 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2601 if (!rank) { 2602 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2603 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2604 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2605 } 2606 2607 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2608 M = header[1]; N = header[2]; 2609 2610 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2611 2612 /* 2613 This code adds extra rows to make sure the number of rows is 2614 divisible by the blocksize 2615 */ 2616 Mbs = M/bs; 2617 extra_rows = bs - M + bs*Mbs; 2618 if (extra_rows == bs) extra_rows = 0; 2619 else Mbs++; 2620 if (extra_rows && !rank) { 2621 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2622 } 2623 2624 /* determine ownership of all rows */ 2625 mbs = Mbs/size + ((Mbs % size) > rank); 2626 m = mbs*bs; 2627 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2628 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2629 2630 /* process 0 needs enough room for process with most rows */ 2631 if (!rank) { 2632 mmax = rowners[1]; 2633 for (i=2; i<size; i++) { 2634 mmax = PetscMax(mmax,rowners[i]); 2635 } 2636 mmax*=bs; 2637 } else mmax = m; 2638 2639 rowners[0] = 0; 2640 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2641 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2642 rstart = rowners[rank]; 2643 rend = rowners[rank+1]; 2644 2645 /* distribute row lengths to all processors */ 2646 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2647 if (!rank) { 2648 mend = m; 2649 if (size == 1) mend = mend - extra_rows; 2650 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2651 for (j=mend; j<m; j++) locrowlens[j] = 1; 2652 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2653 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2654 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2655 for (j=0; j<m; j++) { 2656 procsnz[0] += locrowlens[j]; 2657 } 2658 for (i=1; i<size; i++) { 2659 mend = browners[i+1] - browners[i]; 2660 if (i == size-1) mend = mend - extra_rows; 2661 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2662 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2663 /* calculate the number of nonzeros on each processor */ 2664 for (j=0; j<browners[i+1]-browners[i]; j++) { 2665 procsnz[i] += rowlengths[j]; 2666 } 2667 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2668 } 2669 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2670 } else { 2671 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2672 } 2673 2674 if (!rank) { 2675 /* determine max buffer needed and allocate it */ 2676 maxnz = procsnz[0]; 2677 for (i=1; i<size; i++) { 2678 maxnz = PetscMax(maxnz,procsnz[i]); 2679 } 2680 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2681 2682 /* read in my part of the matrix column indices */ 2683 nz = procsnz[0]; 2684 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2685 mycols = ibuf; 2686 if (size == 1) nz -= extra_rows; 2687 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2688 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2689 2690 /* read in every ones (except the last) and ship off */ 2691 for (i=1; i<size-1; i++) { 2692 nz = procsnz[i]; 2693 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2694 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2695 } 2696 /* read in the stuff for the last proc */ 2697 if (size != 1) { 2698 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2699 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2700 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2701 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2702 } 2703 ierr = PetscFree(cols);CHKERRQ(ierr); 2704 } else { 2705 /* determine buffer space needed for message */ 2706 nz = 0; 2707 for (i=0; i<m; i++) { 2708 nz += locrowlens[i]; 2709 } 2710 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2711 mycols = ibuf; 2712 /* receive message of column indices*/ 2713 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2714 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2715 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2716 } 2717 2718 /* loop over local rows, determining number of off diagonal entries */ 2719 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2720 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2721 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2722 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2723 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2724 rowcount = 0; nzcount = 0; 2725 for (i=0; i<mbs; i++) { 2726 dcount = 0; 2727 odcount = 0; 2728 for (j=0; j<bs; j++) { 2729 kmax = locrowlens[rowcount]; 2730 for (k=0; k<kmax; k++) { 2731 tmp = mycols[nzcount++]/bs; 2732 if (!mask[tmp]) { 2733 mask[tmp] = 1; 2734 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2735 else masked1[dcount++] = tmp; 2736 } 2737 } 2738 rowcount++; 2739 } 2740 2741 dlens[i] = dcount; 2742 odlens[i] = odcount; 2743 2744 /* zero out the mask elements we set */ 2745 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2746 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2747 } 2748 2749 /* create our matrix */ 2750 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2751 ierr = MatSetSizes(A,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2752 ierr = MatSetType(A,type);CHKERRQ(ierr) 2753 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2754 2755 if (!rank) { 2756 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2757 /* read in my part of the matrix numerical values */ 2758 nz = procsnz[0]; 2759 vals = buf; 2760 mycols = ibuf; 2761 if (size == 1) nz -= extra_rows; 2762 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2763 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2764 2765 /* insert into matrix */ 2766 jj = rstart*bs; 2767 for (i=0; i<m; i++) { 2768 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2769 mycols += locrowlens[i]; 2770 vals += locrowlens[i]; 2771 jj++; 2772 } 2773 /* read in other processors (except the last one) and ship out */ 2774 for (i=1; i<size-1; i++) { 2775 nz = procsnz[i]; 2776 vals = buf; 2777 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2778 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2779 } 2780 /* the last proc */ 2781 if (size != 1){ 2782 nz = procsnz[i] - extra_rows; 2783 vals = buf; 2784 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2785 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2786 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2787 } 2788 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2789 } else { 2790 /* receive numeric values */ 2791 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2792 2793 /* receive message of values*/ 2794 vals = buf; 2795 mycols = ibuf; 2796 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2797 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2798 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2799 2800 /* insert into matrix */ 2801 jj = rstart*bs; 2802 for (i=0; i<m; i++) { 2803 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2804 mycols += locrowlens[i]; 2805 vals += locrowlens[i]; 2806 jj++; 2807 } 2808 } 2809 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2810 ierr = PetscFree(buf);CHKERRQ(ierr); 2811 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2812 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2813 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2814 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2815 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2816 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2817 2818 *newmat = A; 2819 PetscFunctionReturn(0); 2820 } 2821 2822 #undef __FUNCT__ 2823 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2824 /*@ 2825 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2826 2827 Input Parameters: 2828 . mat - the matrix 2829 . fact - factor 2830 2831 Collective on Mat 2832 2833 Level: advanced 2834 2835 Notes: 2836 This can also be set by the command line option: -mat_use_hash_table <fact> 2837 2838 .keywords: matrix, hashtable, factor, HT 2839 2840 .seealso: MatSetOption() 2841 @*/ 2842 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2843 { 2844 PetscErrorCode ierr,(*f)(Mat,PetscReal); 2845 2846 PetscFunctionBegin; 2847 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 2848 if (f) { 2849 ierr = (*f)(mat,fact);CHKERRQ(ierr); 2850 } 2851 PetscFunctionReturn(0); 2852 } 2853 2854 EXTERN_C_BEGIN 2855 #undef __FUNCT__ 2856 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 2857 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 2858 { 2859 Mat_MPIBAIJ *baij; 2860 2861 PetscFunctionBegin; 2862 baij = (Mat_MPIBAIJ*)mat->data; 2863 baij->ht_fact = fact; 2864 PetscFunctionReturn(0); 2865 } 2866 EXTERN_C_END 2867 2868 #undef __FUNCT__ 2869 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2870 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 2871 { 2872 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2873 PetscFunctionBegin; 2874 *Ad = a->A; 2875 *Ao = a->B; 2876 *colmap = a->garray; 2877 PetscFunctionReturn(0); 2878 } 2879 2880 /* 2881 Special version for direct calls from Fortran (to eliminate two function call overheads 2882 */ 2883 #if defined(PETSC_HAVE_FORTRAN_CAPS) 2884 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 2885 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 2886 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 2887 #endif 2888 2889 #undef __FUNCT__ 2890 #define __FUNCT__ "matmpibiajsetvaluesblocked" 2891 /*@C 2892 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 2893 2894 Collective on Mat 2895 2896 Input Parameters: 2897 + mat - the matrix 2898 . min - number of input rows 2899 . im - input rows 2900 . nin - number of input columns 2901 . in - input columns 2902 . v - numerical values input 2903 - addvin - INSERT_VALUES or ADD_VALUES 2904 2905 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 2906 2907 Level: advanced 2908 2909 .seealso: MatSetValuesBlocked() 2910 @*/ 2911 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 2912 { 2913 /* convert input arguments to C version */ 2914 Mat mat = *matin; 2915 PetscInt m = *min, n = *nin; 2916 InsertMode addv = *addvin; 2917 2918 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 2919 const MatScalar *value; 2920 MatScalar *barray=baij->barray; 2921 PetscTruth roworiented = baij->roworiented; 2922 PetscErrorCode ierr; 2923 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 2924 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 2925 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 2926 2927 PetscFunctionBegin; 2928 /* tasks normally handled by MatSetValuesBlocked() */ 2929 if (mat->insertmode == NOT_SET_VALUES) { 2930 mat->insertmode = addv; 2931 } 2932 #if defined(PETSC_USE_DEBUG) 2933 else if (mat->insertmode != addv) { 2934 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 2935 } 2936 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2937 #endif 2938 if (mat->assembled) { 2939 mat->was_assembled = PETSC_TRUE; 2940 mat->assembled = PETSC_FALSE; 2941 } 2942 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 2943 2944 2945 if(!barray) { 2946 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 2947 baij->barray = barray; 2948 } 2949 2950 if (roworiented) { 2951 stepval = (n-1)*bs; 2952 } else { 2953 stepval = (m-1)*bs; 2954 } 2955 for (i=0; i<m; i++) { 2956 if (im[i] < 0) continue; 2957 #if defined(PETSC_USE_DEBUG) 2958 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 2959 #endif 2960 if (im[i] >= rstart && im[i] < rend) { 2961 row = im[i] - rstart; 2962 for (j=0; j<n; j++) { 2963 /* If NumCol = 1 then a copy is not required */ 2964 if ((roworiented) && (n == 1)) { 2965 barray = (MatScalar*)v + i*bs2; 2966 } else if((!roworiented) && (m == 1)) { 2967 barray = (MatScalar*)v + j*bs2; 2968 } else { /* Here a copy is required */ 2969 if (roworiented) { 2970 value = v + i*(stepval+bs)*bs + j*bs; 2971 } else { 2972 value = v + j*(stepval+bs)*bs + i*bs; 2973 } 2974 for (ii=0; ii<bs; ii++,value+=stepval) { 2975 for (jj=0; jj<bs; jj++) { 2976 *barray++ = *value++; 2977 } 2978 } 2979 barray -=bs2; 2980 } 2981 2982 if (in[j] >= cstart && in[j] < cend){ 2983 col = in[j] - cstart; 2984 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 2985 } 2986 else if (in[j] < 0) continue; 2987 #if defined(PETSC_USE_DEBUG) 2988 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 2989 #endif 2990 else { 2991 if (mat->was_assembled) { 2992 if (!baij->colmap) { 2993 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 2994 } 2995 2996 #if defined(PETSC_USE_DEBUG) 2997 #if defined (PETSC_USE_CTABLE) 2998 { PetscInt data; 2999 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3000 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 3001 } 3002 #else 3003 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 3004 #endif 3005 #endif 3006 #if defined (PETSC_USE_CTABLE) 3007 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3008 col = (col - 1)/bs; 3009 #else 3010 col = (baij->colmap[in[j]] - 1)/bs; 3011 #endif 3012 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3013 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3014 col = in[j]; 3015 } 3016 } 3017 else col = in[j]; 3018 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3019 } 3020 } 3021 } else { 3022 if (!baij->donotstash) { 3023 if (roworiented) { 3024 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3025 } else { 3026 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3027 } 3028 } 3029 } 3030 } 3031 3032 /* task normally handled by MatSetValuesBlocked() */ 3033 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3034 PetscFunctionReturn(0); 3035 } 3036