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 I[],const PetscInt J[],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 (I[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"I[0] must be 0 but it is %D",I[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 = I[i+1] - I[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 = J + I[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 = I[i+1] - I[i]; 2010 const PetscInt *icols = J + I[i]; 2011 const PetscScalar *svals = values + (V ? (bs*bs*I[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; 2063 2064 PetscFunctionBegin; 2065 B->preallocated = PETSC_TRUE; 2066 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPIBAIJ matrix","Mat");CHKERRQ(ierr); 2067 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2068 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2069 2070 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 2071 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2072 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2073 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2074 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2075 2076 B->rmap.bs = bs; 2077 B->cmap.bs = bs; 2078 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2079 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2080 2081 if (d_nnz) { 2082 for (i=0; i<B->rmap.n/bs; i++) { 2083 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]); 2084 } 2085 } 2086 if (o_nnz) { 2087 for (i=0; i<B->rmap.n/bs; i++) { 2088 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]); 2089 } 2090 } 2091 2092 b = (Mat_MPIBAIJ*)B->data; 2093 b->bs2 = bs*bs; 2094 b->mbs = B->rmap.n/bs; 2095 b->nbs = B->cmap.n/bs; 2096 b->Mbs = B->rmap.N/bs; 2097 b->Nbs = B->cmap.N/bs; 2098 2099 for (i=0; i<=b->size; i++) { 2100 b->rangebs[i] = B->rmap.range[i]/bs; 2101 } 2102 b->rstartbs = B->rmap.rstart/bs; 2103 b->rendbs = B->rmap.rend/bs; 2104 b->cstartbs = B->cmap.rstart/bs; 2105 b->cendbs = B->cmap.rend/bs; 2106 2107 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2108 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 2109 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 2110 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2111 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2112 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2113 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 2114 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 2115 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 2116 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2117 2118 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 2119 2120 PetscFunctionReturn(0); 2121 } 2122 EXTERN_C_END 2123 2124 EXTERN_C_BEGIN 2125 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 2126 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 2127 EXTERN_C_END 2128 2129 /*MC 2130 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 2131 2132 Options Database Keys: 2133 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 2134 . -mat_block_size <bs> - set the blocksize used to store the matrix 2135 - -mat_use_hash_table <fact> 2136 2137 Level: beginner 2138 2139 .seealso: MatCreateMPIBAIJ 2140 M*/ 2141 2142 EXTERN_C_BEGIN 2143 #undef __FUNCT__ 2144 #define __FUNCT__ "MatCreate_MPIBAIJ" 2145 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIBAIJ(Mat B) 2146 { 2147 Mat_MPIBAIJ *b; 2148 PetscErrorCode ierr; 2149 PetscTruth flg; 2150 2151 PetscFunctionBegin; 2152 ierr = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr); 2153 B->data = (void*)b; 2154 2155 2156 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2157 B->mapping = 0; 2158 B->factor = 0; 2159 B->assembled = PETSC_FALSE; 2160 2161 B->insertmode = NOT_SET_VALUES; 2162 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 2163 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 2164 2165 /* build local table of row and column ownerships */ 2166 ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 2167 2168 /* build cache for off array entries formed */ 2169 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 2170 b->donotstash = PETSC_FALSE; 2171 b->colmap = PETSC_NULL; 2172 b->garray = PETSC_NULL; 2173 b->roworiented = PETSC_TRUE; 2174 2175 /* stuff used in block assembly */ 2176 b->barray = 0; 2177 2178 /* stuff used for matrix vector multiply */ 2179 b->lvec = 0; 2180 b->Mvctx = 0; 2181 2182 /* stuff for MatGetRow() */ 2183 b->rowindices = 0; 2184 b->rowvalues = 0; 2185 b->getrowactive = PETSC_FALSE; 2186 2187 /* hash table stuff */ 2188 b->ht = 0; 2189 b->hd = 0; 2190 b->ht_size = 0; 2191 b->ht_flag = PETSC_FALSE; 2192 b->ht_fact = 0; 2193 b->ht_total_ct = 0; 2194 b->ht_insert_ct = 0; 2195 2196 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 2197 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 2198 if (flg) { 2199 PetscReal fact = 1.39; 2200 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 2201 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 2202 if (fact <= 1.0) fact = 1.39; 2203 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 2204 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 2205 } 2206 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2207 2208 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2209 "MatStoreValues_MPIBAIJ", 2210 MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 2211 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2212 "MatRetrieveValues_MPIBAIJ", 2213 MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 2214 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 2215 "MatGetDiagonalBlock_MPIBAIJ", 2216 MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 2217 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocation_C", 2218 "MatMPIBAIJSetPreallocation_MPIBAIJ", 2219 MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 2220 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C", 2221 "MatMPIBAIJSetPreallocationCSR_MPIBAIJ", 2222 MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 2223 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 2224 "MatDiagonalScaleLocal_MPIBAIJ", 2225 MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 2226 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSetHashTableFactor_C", 2227 "MatSetHashTableFactor_MPIBAIJ", 2228 MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 2229 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 EXTERN_C_END 2233 2234 /*MC 2235 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 2236 2237 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 2238 and MATMPIBAIJ otherwise. 2239 2240 Options Database Keys: 2241 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 2242 2243 Level: beginner 2244 2245 .seealso: MatCreateMPIBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2246 M*/ 2247 2248 EXTERN_C_BEGIN 2249 #undef __FUNCT__ 2250 #define __FUNCT__ "MatCreate_BAIJ" 2251 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_BAIJ(Mat A) 2252 { 2253 PetscErrorCode ierr; 2254 PetscMPIInt size; 2255 2256 PetscFunctionBegin; 2257 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2258 if (size == 1) { 2259 ierr = MatSetType(A,MATSEQBAIJ);CHKERRQ(ierr); 2260 } else { 2261 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 2262 } 2263 PetscFunctionReturn(0); 2264 } 2265 EXTERN_C_END 2266 2267 #undef __FUNCT__ 2268 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 2269 /*@C 2270 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 2271 (block compressed row). For good matrix assembly performance 2272 the user should preallocate the matrix storage by setting the parameters 2273 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2274 performance can be increased by more than a factor of 50. 2275 2276 Collective on Mat 2277 2278 Input Parameters: 2279 + A - the matrix 2280 . bs - size of blockk 2281 . d_nz - number of block nonzeros per block row in diagonal portion of local 2282 submatrix (same for all local rows) 2283 . d_nnz - array containing the number of block nonzeros in the various block rows 2284 of the in diagonal portion of the local (possibly different for each block 2285 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2286 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2287 submatrix (same for all local rows). 2288 - o_nnz - array containing the number of nonzeros in the various block rows of the 2289 off-diagonal portion of the local submatrix (possibly different for 2290 each block row) or PETSC_NULL. 2291 2292 If the *_nnz parameter is given then the *_nz parameter is ignored 2293 2294 Options Database Keys: 2295 + -mat_block_size - size of the blocks to use 2296 - -mat_use_hash_table <fact> 2297 2298 Notes: 2299 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2300 than it must be used on all processors that share the object for that argument. 2301 2302 Storage Information: 2303 For a square global matrix we define each processor's diagonal portion 2304 to be its local rows and the corresponding columns (a square submatrix); 2305 each processor's off-diagonal portion encompasses the remainder of the 2306 local matrix (a rectangular submatrix). 2307 2308 The user can specify preallocated storage for the diagonal part of 2309 the local submatrix with either d_nz or d_nnz (not both). Set 2310 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2311 memory allocation. Likewise, specify preallocated storage for the 2312 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2313 2314 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2315 the figure below we depict these three local rows and all columns (0-11). 2316 2317 .vb 2318 0 1 2 3 4 5 6 7 8 9 10 11 2319 ------------------- 2320 row 3 | o o o d d d o o o o o o 2321 row 4 | o o o d d d o o o o o o 2322 row 5 | o o o d d d o o o o o o 2323 ------------------- 2324 .ve 2325 2326 Thus, any entries in the d locations are stored in the d (diagonal) 2327 submatrix, and any entries in the o locations are stored in the 2328 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2329 stored simply in the MATSEQBAIJ format for compressed row storage. 2330 2331 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2332 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2333 In general, for PDE problems in which most nonzeros are near the diagonal, 2334 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2335 or you will get TERRIBLE performance; see the users' manual chapter on 2336 matrices. 2337 2338 You can call MatGetInfo() to get information on how effective the preallocation was; 2339 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2340 You can also run with the option -info and look for messages with the string 2341 malloc in them to see if additional memory allocation was needed. 2342 2343 Level: intermediate 2344 2345 .keywords: matrix, block, aij, compressed row, sparse, parallel 2346 2347 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR() 2348 @*/ 2349 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2350 { 2351 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2352 2353 PetscFunctionBegin; 2354 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2355 if (f) { 2356 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2357 } 2358 PetscFunctionReturn(0); 2359 } 2360 2361 #undef __FUNCT__ 2362 #define __FUNCT__ "MatCreateMPIBAIJ" 2363 /*@C 2364 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 2365 (block compressed row). For good matrix assembly performance 2366 the user should preallocate the matrix storage by setting the parameters 2367 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2368 performance can be increased by more than a factor of 50. 2369 2370 Collective on MPI_Comm 2371 2372 Input Parameters: 2373 + comm - MPI communicator 2374 . bs - size of blockk 2375 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2376 This value should be the same as the local size used in creating the 2377 y vector for the matrix-vector product y = Ax. 2378 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 2379 This value should be the same as the local size used in creating the 2380 x vector for the matrix-vector product y = Ax. 2381 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2382 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2383 . d_nz - number of nonzero blocks per block row in diagonal portion of local 2384 submatrix (same for all local rows) 2385 . d_nnz - array containing the number of nonzero blocks in the various block rows 2386 of the in diagonal portion of the local (possibly different for each block 2387 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 2388 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 2389 submatrix (same for all local rows). 2390 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 2391 off-diagonal portion of the local submatrix (possibly different for 2392 each block row) or PETSC_NULL. 2393 2394 Output Parameter: 2395 . A - the matrix 2396 2397 Options Database Keys: 2398 + -mat_block_size - size of the blocks to use 2399 - -mat_use_hash_table <fact> 2400 2401 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2402 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 2403 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 2404 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2405 2406 Notes: 2407 If the *_nnz parameter is given then the *_nz parameter is ignored 2408 2409 A nonzero block is any block that as 1 or more nonzeros in it 2410 2411 The user MUST specify either the local or global matrix dimensions 2412 (possibly both). 2413 2414 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 2415 than it must be used on all processors that share the object for that argument. 2416 2417 Storage Information: 2418 For a square global matrix we define each processor's diagonal portion 2419 to be its local rows and the corresponding columns (a square submatrix); 2420 each processor's off-diagonal portion encompasses the remainder of the 2421 local matrix (a rectangular submatrix). 2422 2423 The user can specify preallocated storage for the diagonal part of 2424 the local submatrix with either d_nz or d_nnz (not both). Set 2425 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 2426 memory allocation. Likewise, specify preallocated storage for the 2427 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 2428 2429 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2430 the figure below we depict these three local rows and all columns (0-11). 2431 2432 .vb 2433 0 1 2 3 4 5 6 7 8 9 10 11 2434 ------------------- 2435 row 3 | o o o d d d o o o o o o 2436 row 4 | o o o d d d o o o o o o 2437 row 5 | o o o d d d o o o o o o 2438 ------------------- 2439 .ve 2440 2441 Thus, any entries in the d locations are stored in the d (diagonal) 2442 submatrix, and any entries in the o locations are stored in the 2443 o (off-diagonal) submatrix. Note that the d and the o submatrices are 2444 stored simply in the MATSEQBAIJ format for compressed row storage. 2445 2446 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 2447 and o_nz should indicate the number of block nonzeros per row in the o matrix. 2448 In general, for PDE problems in which most nonzeros are near the diagonal, 2449 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 2450 or you will get TERRIBLE performance; see the users' manual chapter on 2451 matrices. 2452 2453 Level: intermediate 2454 2455 .keywords: matrix, block, aij, compressed row, sparse, parallel 2456 2457 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 2458 @*/ 2459 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) 2460 { 2461 PetscErrorCode ierr; 2462 PetscMPIInt size; 2463 2464 PetscFunctionBegin; 2465 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2466 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 2467 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2468 if (size > 1) { 2469 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 2470 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2471 } else { 2472 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2473 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 2474 } 2475 PetscFunctionReturn(0); 2476 } 2477 2478 #undef __FUNCT__ 2479 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 2480 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2481 { 2482 Mat mat; 2483 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 2484 PetscErrorCode ierr; 2485 PetscInt len=0; 2486 2487 PetscFunctionBegin; 2488 *newmat = 0; 2489 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2490 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2491 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2492 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2493 2494 mat->factor = matin->factor; 2495 mat->preallocated = PETSC_TRUE; 2496 mat->assembled = PETSC_TRUE; 2497 mat->insertmode = NOT_SET_VALUES; 2498 2499 a = (Mat_MPIBAIJ*)mat->data; 2500 mat->rmap.bs = matin->rmap.bs; 2501 a->bs2 = oldmat->bs2; 2502 a->mbs = oldmat->mbs; 2503 a->nbs = oldmat->nbs; 2504 a->Mbs = oldmat->Mbs; 2505 a->Nbs = oldmat->Nbs; 2506 2507 ierr = PetscMapCopy(((PetscObject)matin)->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2508 ierr = PetscMapCopy(((PetscObject)matin)->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2509 2510 a->size = oldmat->size; 2511 a->rank = oldmat->rank; 2512 a->donotstash = oldmat->donotstash; 2513 a->roworiented = oldmat->roworiented; 2514 a->rowindices = 0; 2515 a->rowvalues = 0; 2516 a->getrowactive = PETSC_FALSE; 2517 a->barray = 0; 2518 a->rstartbs = oldmat->rstartbs; 2519 a->rendbs = oldmat->rendbs; 2520 a->cstartbs = oldmat->cstartbs; 2521 a->cendbs = oldmat->cendbs; 2522 2523 /* hash table stuff */ 2524 a->ht = 0; 2525 a->hd = 0; 2526 a->ht_size = 0; 2527 a->ht_flag = oldmat->ht_flag; 2528 a->ht_fact = oldmat->ht_fact; 2529 a->ht_total_ct = 0; 2530 a->ht_insert_ct = 0; 2531 2532 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 2533 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2534 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap.bs,&mat->bstash);CHKERRQ(ierr); 2535 if (oldmat->colmap) { 2536 #if defined (PETSC_USE_CTABLE) 2537 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2538 #else 2539 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2540 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2541 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2542 #endif 2543 } else a->colmap = 0; 2544 2545 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2546 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2547 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2548 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2549 } else a->garray = 0; 2550 2551 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2552 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2553 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2554 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2555 2556 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2557 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2558 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2559 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2560 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2561 *newmat = mat; 2562 2563 PetscFunctionReturn(0); 2564 } 2565 2566 #include "petscsys.h" 2567 2568 #undef __FUNCT__ 2569 #define __FUNCT__ "MatLoad_MPIBAIJ" 2570 PetscErrorCode MatLoad_MPIBAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2571 { 2572 Mat A; 2573 PetscErrorCode ierr; 2574 int fd; 2575 PetscInt i,nz,j,rstart,rend; 2576 PetscScalar *vals,*buf; 2577 MPI_Comm comm = ((PetscObject)viewer)->comm; 2578 MPI_Status status; 2579 PetscMPIInt rank,size,maxnz; 2580 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 2581 PetscInt *locrowlens = PETSC_NULL,*procsnz = PETSC_NULL,*browners = PETSC_NULL; 2582 PetscInt jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax; 2583 PetscMPIInt tag = ((PetscObject)viewer)->tag; 2584 PetscInt *dlens = PETSC_NULL,*odlens = PETSC_NULL,*mask = PETSC_NULL,*masked1 = PETSC_NULL,*masked2 = PETSC_NULL,rowcount,odcount; 2585 PetscInt dcount,kmax,k,nzcount,tmp,mend; 2586 2587 PetscFunctionBegin; 2588 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 2589 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2590 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2591 2592 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2593 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2594 if (!rank) { 2595 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2596 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2597 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2598 } 2599 2600 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2601 M = header[1]; N = header[2]; 2602 2603 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2604 2605 /* 2606 This code adds extra rows to make sure the number of rows is 2607 divisible by the blocksize 2608 */ 2609 Mbs = M/bs; 2610 extra_rows = bs - M + bs*Mbs; 2611 if (extra_rows == bs) extra_rows = 0; 2612 else Mbs++; 2613 if (extra_rows && !rank) { 2614 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2615 } 2616 2617 /* determine ownership of all rows */ 2618 mbs = Mbs/size + ((Mbs % size) > rank); 2619 m = mbs*bs; 2620 ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr); 2621 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2622 2623 /* process 0 needs enough room for process with most rows */ 2624 if (!rank) { 2625 mmax = rowners[1]; 2626 for (i=2; i<size; i++) { 2627 mmax = PetscMax(mmax,rowners[i]); 2628 } 2629 mmax*=bs; 2630 } else mmax = m; 2631 2632 rowners[0] = 0; 2633 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2634 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2635 rstart = rowners[rank]; 2636 rend = rowners[rank+1]; 2637 2638 /* distribute row lengths to all processors */ 2639 ierr = PetscMalloc((mmax+1)*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr); 2640 if (!rank) { 2641 mend = m; 2642 if (size == 1) mend = mend - extra_rows; 2643 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 2644 for (j=mend; j<m; j++) locrowlens[j] = 1; 2645 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2646 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2647 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2648 for (j=0; j<m; j++) { 2649 procsnz[0] += locrowlens[j]; 2650 } 2651 for (i=1; i<size; i++) { 2652 mend = browners[i+1] - browners[i]; 2653 if (i == size-1) mend = mend - extra_rows; 2654 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 2655 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 2656 /* calculate the number of nonzeros on each processor */ 2657 for (j=0; j<browners[i+1]-browners[i]; j++) { 2658 procsnz[i] += rowlengths[j]; 2659 } 2660 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2661 } 2662 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2663 } else { 2664 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2665 } 2666 2667 if (!rank) { 2668 /* determine max buffer needed and allocate it */ 2669 maxnz = procsnz[0]; 2670 for (i=1; i<size; i++) { 2671 maxnz = PetscMax(maxnz,procsnz[i]); 2672 } 2673 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2674 2675 /* read in my part of the matrix column indices */ 2676 nz = procsnz[0]; 2677 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2678 mycols = ibuf; 2679 if (size == 1) nz -= extra_rows; 2680 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2681 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2682 2683 /* read in every ones (except the last) and ship off */ 2684 for (i=1; i<size-1; i++) { 2685 nz = procsnz[i]; 2686 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2687 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2688 } 2689 /* read in the stuff for the last proc */ 2690 if (size != 1) { 2691 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2692 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2693 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2694 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2695 } 2696 ierr = PetscFree(cols);CHKERRQ(ierr); 2697 } else { 2698 /* determine buffer space needed for message */ 2699 nz = 0; 2700 for (i=0; i<m; i++) { 2701 nz += locrowlens[i]; 2702 } 2703 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2704 mycols = ibuf; 2705 /* receive message of column indices*/ 2706 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2707 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2708 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2709 } 2710 2711 /* loop over local rows, determining number of off diagonal entries */ 2712 ierr = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr); 2713 ierr = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr); 2714 ierr = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2715 ierr = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2716 ierr = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2717 rowcount = 0; nzcount = 0; 2718 for (i=0; i<mbs; i++) { 2719 dcount = 0; 2720 odcount = 0; 2721 for (j=0; j<bs; j++) { 2722 kmax = locrowlens[rowcount]; 2723 for (k=0; k<kmax; k++) { 2724 tmp = mycols[nzcount++]/bs; 2725 if (!mask[tmp]) { 2726 mask[tmp] = 1; 2727 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 2728 else masked1[dcount++] = tmp; 2729 } 2730 } 2731 rowcount++; 2732 } 2733 2734 dlens[i] = dcount; 2735 odlens[i] = odcount; 2736 2737 /* zero out the mask elements we set */ 2738 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2739 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2740 } 2741 2742 /* create our matrix */ 2743 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2744 ierr = MatSetSizes(A,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 2745 ierr = MatSetType(A,type);CHKERRQ(ierr) 2746 ierr = MatMPIBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2747 2748 if (!rank) { 2749 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2750 /* read in my part of the matrix numerical values */ 2751 nz = procsnz[0]; 2752 vals = buf; 2753 mycols = ibuf; 2754 if (size == 1) nz -= extra_rows; 2755 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2756 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2757 2758 /* insert into matrix */ 2759 jj = rstart*bs; 2760 for (i=0; i<m; i++) { 2761 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2762 mycols += locrowlens[i]; 2763 vals += locrowlens[i]; 2764 jj++; 2765 } 2766 /* read in other processors (except the last one) and ship out */ 2767 for (i=1; i<size-1; i++) { 2768 nz = procsnz[i]; 2769 vals = buf; 2770 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2771 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2772 } 2773 /* the last proc */ 2774 if (size != 1){ 2775 nz = procsnz[i] - extra_rows; 2776 vals = buf; 2777 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2778 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2779 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2780 } 2781 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2782 } else { 2783 /* receive numeric values */ 2784 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2785 2786 /* receive message of values*/ 2787 vals = buf; 2788 mycols = ibuf; 2789 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2790 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2791 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2792 2793 /* insert into matrix */ 2794 jj = rstart*bs; 2795 for (i=0; i<m; i++) { 2796 ierr = MatSetValues_MPIBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2797 mycols += locrowlens[i]; 2798 vals += locrowlens[i]; 2799 jj++; 2800 } 2801 } 2802 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2803 ierr = PetscFree(buf);CHKERRQ(ierr); 2804 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2805 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 2806 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 2807 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 2808 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2809 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2810 2811 *newmat = A; 2812 PetscFunctionReturn(0); 2813 } 2814 2815 #undef __FUNCT__ 2816 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 2817 /*@ 2818 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2819 2820 Input Parameters: 2821 . mat - the matrix 2822 . fact - factor 2823 2824 Collective on Mat 2825 2826 Level: advanced 2827 2828 Notes: 2829 This can also be set by the command line option: -mat_use_hash_table <fact> 2830 2831 .keywords: matrix, hashtable, factor, HT 2832 2833 .seealso: MatSetOption() 2834 @*/ 2835 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2836 { 2837 PetscErrorCode ierr,(*f)(Mat,PetscReal); 2838 2839 PetscFunctionBegin; 2840 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSetHashTableFactor_C",(void (**)(void))&f);CHKERRQ(ierr); 2841 if (f) { 2842 ierr = (*f)(mat,fact);CHKERRQ(ierr); 2843 } 2844 PetscFunctionReturn(0); 2845 } 2846 2847 EXTERN_C_BEGIN 2848 #undef __FUNCT__ 2849 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 2850 PetscErrorCode PETSCMAT_DLLEXPORT MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 2851 { 2852 Mat_MPIBAIJ *baij; 2853 2854 PetscFunctionBegin; 2855 baij = (Mat_MPIBAIJ*)mat->data; 2856 baij->ht_fact = fact; 2857 PetscFunctionReturn(0); 2858 } 2859 EXTERN_C_END 2860 2861 #undef __FUNCT__ 2862 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 2863 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 2864 { 2865 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data; 2866 PetscFunctionBegin; 2867 *Ad = a->A; 2868 *Ao = a->B; 2869 *colmap = a->garray; 2870 PetscFunctionReturn(0); 2871 } 2872 2873 /* 2874 Special version for direct calls from Fortran (to eliminate two function call overheads 2875 */ 2876 #if defined(PETSC_HAVE_FORTRAN_CAPS) 2877 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 2878 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 2879 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 2880 #endif 2881 2882 #undef __FUNCT__ 2883 #define __FUNCT__ "matmpibiajsetvaluesblocked" 2884 /*@C 2885 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 2886 2887 Collective on Mat 2888 2889 Input Parameters: 2890 + mat - the matrix 2891 . min - number of input rows 2892 . im - input rows 2893 . nin - number of input columns 2894 . in - input columns 2895 . v - numerical values input 2896 - addvin - INSERT_VALUES or ADD_VALUES 2897 2898 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 2899 2900 Level: advanced 2901 2902 .seealso: MatSetValuesBlocked() 2903 @*/ 2904 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 2905 { 2906 /* convert input arguments to C version */ 2907 Mat mat = *matin; 2908 PetscInt m = *min, n = *nin; 2909 InsertMode addv = *addvin; 2910 2911 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 2912 const MatScalar *value; 2913 MatScalar *barray=baij->barray; 2914 PetscTruth roworiented = baij->roworiented; 2915 PetscErrorCode ierr; 2916 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 2917 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 2918 PetscInt cend=baij->cendbs,bs=mat->rmap.bs,bs2=baij->bs2; 2919 2920 PetscFunctionBegin; 2921 /* tasks normally handled by MatSetValuesBlocked() */ 2922 if (mat->insertmode == NOT_SET_VALUES) { 2923 mat->insertmode = addv; 2924 } 2925 #if defined(PETSC_USE_DEBUG) 2926 else if (mat->insertmode != addv) { 2927 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 2928 } 2929 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2930 #endif 2931 if (mat->assembled) { 2932 mat->was_assembled = PETSC_TRUE; 2933 mat->assembled = PETSC_FALSE; 2934 } 2935 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 2936 2937 2938 if(!barray) { 2939 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 2940 baij->barray = barray; 2941 } 2942 2943 if (roworiented) { 2944 stepval = (n-1)*bs; 2945 } else { 2946 stepval = (m-1)*bs; 2947 } 2948 for (i=0; i<m; i++) { 2949 if (im[i] < 0) continue; 2950 #if defined(PETSC_USE_DEBUG) 2951 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 2952 #endif 2953 if (im[i] >= rstart && im[i] < rend) { 2954 row = im[i] - rstart; 2955 for (j=0; j<n; j++) { 2956 /* If NumCol = 1 then a copy is not required */ 2957 if ((roworiented) && (n == 1)) { 2958 barray = (MatScalar*)v + i*bs2; 2959 } else if((!roworiented) && (m == 1)) { 2960 barray = (MatScalar*)v + j*bs2; 2961 } else { /* Here a copy is required */ 2962 if (roworiented) { 2963 value = v + i*(stepval+bs)*bs + j*bs; 2964 } else { 2965 value = v + j*(stepval+bs)*bs + i*bs; 2966 } 2967 for (ii=0; ii<bs; ii++,value+=stepval) { 2968 for (jj=0; jj<bs; jj++) { 2969 *barray++ = *value++; 2970 } 2971 } 2972 barray -=bs2; 2973 } 2974 2975 if (in[j] >= cstart && in[j] < cend){ 2976 col = in[j] - cstart; 2977 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 2978 } 2979 else if (in[j] < 0) continue; 2980 #if defined(PETSC_USE_DEBUG) 2981 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 2982 #endif 2983 else { 2984 if (mat->was_assembled) { 2985 if (!baij->colmap) { 2986 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 2987 } 2988 2989 #if defined(PETSC_USE_DEBUG) 2990 #if defined (PETSC_USE_CTABLE) 2991 { PetscInt data; 2992 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 2993 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 2994 } 2995 #else 2996 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 2997 #endif 2998 #endif 2999 #if defined (PETSC_USE_CTABLE) 3000 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3001 col = (col - 1)/bs; 3002 #else 3003 col = (baij->colmap[in[j]] - 1)/bs; 3004 #endif 3005 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3006 ierr = DisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3007 col = in[j]; 3008 } 3009 } 3010 else col = in[j]; 3011 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 3012 } 3013 } 3014 } else { 3015 if (!baij->donotstash) { 3016 if (roworiented) { 3017 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3018 } else { 3019 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3020 } 3021 } 3022 } 3023 } 3024 3025 /* task normally handled by MatSetValuesBlocked() */ 3026 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3027 PetscFunctionReturn(0); 3028 } 3029