1 #define PETSCMAT_DLL 2 3 #include "../src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "mpisbaij.h" 5 #include "../src/mat/impls/sbaij/seq/sbaij.h" 6 7 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat); 8 EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat); 9 EXTERN PetscErrorCode DisAssemble_MPISBAIJ(Mat); 10 EXTERN PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt); 11 EXTERN PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 12 EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []); 13 EXTERN PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode); 14 EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 15 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 16 EXTERN PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 17 EXTERN PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**); 18 EXTERN PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*); 19 EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *); 20 EXTERN PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]); 21 EXTERN PetscErrorCode MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec); 22 23 EXTERN_C_BEGIN 24 #undef __FUNCT__ 25 #define __FUNCT__ "MatStoreValues_MPISBAIJ" 26 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPISBAIJ(Mat mat) 27 { 28 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 29 PetscErrorCode ierr; 30 31 PetscFunctionBegin; 32 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 33 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 34 PetscFunctionReturn(0); 35 } 36 EXTERN_C_END 37 38 EXTERN_C_BEGIN 39 #undef __FUNCT__ 40 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ" 41 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPISBAIJ(Mat mat) 42 { 43 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 44 PetscErrorCode ierr; 45 46 PetscFunctionBegin; 47 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 48 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 49 PetscFunctionReturn(0); 50 } 51 EXTERN_C_END 52 53 54 #define CHUNKSIZE 10 55 56 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 57 { \ 58 \ 59 brow = row/bs; \ 60 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 61 rmax = aimax[brow]; nrow = ailen[brow]; \ 62 bcol = col/bs; \ 63 ridx = row % bs; cidx = col % bs; \ 64 low = 0; high = nrow; \ 65 while (high-low > 3) { \ 66 t = (low+high)/2; \ 67 if (rp[t] > bcol) high = t; \ 68 else low = t; \ 69 } \ 70 for (_i=low; _i<high; _i++) { \ 71 if (rp[_i] > bcol) break; \ 72 if (rp[_i] == bcol) { \ 73 bap = ap + bs2*_i + bs*cidx + ridx; \ 74 if (addv == ADD_VALUES) *bap += value; \ 75 else *bap = value; \ 76 goto a_noinsert; \ 77 } \ 78 } \ 79 if (a->nonew == 1) goto a_noinsert; \ 80 if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 81 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 82 N = nrow++ - 1; \ 83 /* shift up all the later entries in this row */ \ 84 for (ii=N; ii>=_i; ii--) { \ 85 rp[ii+1] = rp[ii]; \ 86 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 87 } \ 88 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 89 rp[_i] = bcol; \ 90 ap[bs2*_i + bs*cidx + ridx] = value; \ 91 a_noinsert:; \ 92 ailen[brow] = nrow; \ 93 } 94 95 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 96 { \ 97 brow = row/bs; \ 98 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 99 rmax = bimax[brow]; nrow = bilen[brow]; \ 100 bcol = col/bs; \ 101 ridx = row % bs; cidx = col % bs; \ 102 low = 0; high = nrow; \ 103 while (high-low > 3) { \ 104 t = (low+high)/2; \ 105 if (rp[t] > bcol) high = t; \ 106 else low = t; \ 107 } \ 108 for (_i=low; _i<high; _i++) { \ 109 if (rp[_i] > bcol) break; \ 110 if (rp[_i] == bcol) { \ 111 bap = ap + bs2*_i + bs*cidx + ridx; \ 112 if (addv == ADD_VALUES) *bap += value; \ 113 else *bap = value; \ 114 goto b_noinsert; \ 115 } \ 116 } \ 117 if (b->nonew == 1) goto b_noinsert; \ 118 if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 119 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 120 N = nrow++ - 1; \ 121 /* shift up all the later entries in this row */ \ 122 for (ii=N; ii>=_i; ii--) { \ 123 rp[ii+1] = rp[ii]; \ 124 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 125 } \ 126 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 127 rp[_i] = bcol; \ 128 ap[bs2*_i + bs*cidx + ridx] = value; \ 129 b_noinsert:; \ 130 bilen[brow] = nrow; \ 131 } 132 133 /* Only add/insert a(i,j) with i<=j (blocks). 134 Any a(i,j) with i>j input by user is ingored. 135 */ 136 #undef __FUNCT__ 137 #define __FUNCT__ "MatSetValues_MPISBAIJ" 138 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 139 { 140 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 141 MatScalar value; 142 PetscTruth roworiented = baij->roworiented; 143 PetscErrorCode ierr; 144 PetscInt i,j,row,col; 145 PetscInt rstart_orig=mat->rmap->rstart; 146 PetscInt rend_orig=mat->rmap->rend,cstart_orig=mat->cmap->rstart; 147 PetscInt cend_orig=mat->cmap->rend,bs=mat->rmap->bs; 148 149 /* Some Variables required in the macro */ 150 Mat A = baij->A; 151 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 152 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 153 MatScalar *aa=a->a; 154 155 Mat B = baij->B; 156 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 157 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 158 MatScalar *ba=b->a; 159 160 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 161 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 162 MatScalar *ap,*bap; 163 164 /* for stash */ 165 PetscInt n_loc, *in_loc = PETSC_NULL; 166 MatScalar *v_loc = PETSC_NULL; 167 168 PetscFunctionBegin; 169 170 if (!baij->donotstash){ 171 if (n > baij->n_loc) { 172 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 173 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 174 ierr = PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);CHKERRQ(ierr); 175 ierr = PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);CHKERRQ(ierr); 176 baij->n_loc = n; 177 } 178 in_loc = baij->in_loc; 179 v_loc = baij->v_loc; 180 } 181 182 for (i=0; i<m; i++) { 183 if (im[i] < 0) continue; 184 #if defined(PETSC_USE_DEBUG) 185 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 186 #endif 187 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 188 row = im[i] - rstart_orig; /* local row index */ 189 for (j=0; j<n; j++) { 190 if (im[i]/bs > in[j]/bs){ 191 if (a->ignore_ltriangular){ 192 continue; /* ignore lower triangular blocks */ 193 } else { 194 SETERRQ(PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 195 } 196 } 197 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 198 col = in[j] - cstart_orig; /* local col index */ 199 brow = row/bs; bcol = col/bs; 200 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 201 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 202 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 203 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 204 } else if (in[j] < 0) continue; 205 #if defined(PETSC_USE_DEBUG) 206 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);} 207 #endif 208 else { /* off-diag entry (B) */ 209 if (mat->was_assembled) { 210 if (!baij->colmap) { 211 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 212 } 213 #if defined (PETSC_USE_CTABLE) 214 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 215 col = col - 1; 216 #else 217 col = baij->colmap[in[j]/bs] - 1; 218 #endif 219 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 220 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 221 col = in[j]; 222 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 223 B = baij->B; 224 b = (Mat_SeqBAIJ*)(B)->data; 225 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 226 ba=b->a; 227 } else col += in[j]%bs; 228 } else col = in[j]; 229 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 230 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 231 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 232 } 233 } 234 } else { /* off processor entry */ 235 if (!baij->donotstash) { 236 n_loc = 0; 237 for (j=0; j<n; j++){ 238 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 239 in_loc[n_loc] = in[j]; 240 if (roworiented) { 241 v_loc[n_loc] = v[i*n+j]; 242 } else { 243 v_loc[n_loc] = v[j*m+i]; 244 } 245 n_loc++; 246 } 247 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 248 } 249 } 250 } 251 PetscFunctionReturn(0); 252 } 253 254 #undef __FUNCT__ 255 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ" 256 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv) 257 { 258 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 259 const MatScalar *value; 260 MatScalar *barray=baij->barray; 261 PetscTruth roworiented = baij->roworiented; 262 PetscErrorCode ierr; 263 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 264 PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval; 265 PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2; 266 267 PetscFunctionBegin; 268 if(!barray) { 269 ierr = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr); 270 baij->barray = barray; 271 } 272 273 if (roworiented) { 274 stepval = (n-1)*bs; 275 } else { 276 stepval = (m-1)*bs; 277 } 278 for (i=0; i<m; i++) { 279 if (im[i] < 0) continue; 280 #if defined(PETSC_USE_DEBUG) 281 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 282 #endif 283 if (im[i] >= rstart && im[i] < rend) { 284 row = im[i] - rstart; 285 for (j=0; j<n; j++) { 286 /* If NumCol = 1 then a copy is not required */ 287 if ((roworiented) && (n == 1)) { 288 barray = (MatScalar*) v + i*bs2; 289 } else if((!roworiented) && (m == 1)) { 290 barray = (MatScalar*) v + j*bs2; 291 } else { /* Here a copy is required */ 292 if (roworiented) { 293 value = v + i*(stepval+bs)*bs + j*bs; 294 } else { 295 value = v + j*(stepval+bs)*bs + i*bs; 296 } 297 for (ii=0; ii<bs; ii++,value+=stepval) { 298 for (jj=0; jj<bs; jj++) { 299 *barray++ = *value++; 300 } 301 } 302 barray -=bs2; 303 } 304 305 if (in[j] >= cstart && in[j] < cend){ 306 col = in[j] - cstart; 307 ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 308 } 309 else if (in[j] < 0) continue; 310 #if defined(PETSC_USE_DEBUG) 311 else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);} 312 #endif 313 else { 314 if (mat->was_assembled) { 315 if (!baij->colmap) { 316 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 317 } 318 319 #if defined(PETSC_USE_DEBUG) 320 #if defined (PETSC_USE_CTABLE) 321 { PetscInt data; 322 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 323 if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 324 } 325 #else 326 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap"); 327 #endif 328 #endif 329 #if defined (PETSC_USE_CTABLE) 330 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 331 col = (col - 1)/bs; 332 #else 333 col = (baij->colmap[in[j]] - 1)/bs; 334 #endif 335 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 336 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 337 col = in[j]; 338 } 339 } 340 else col = in[j]; 341 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 342 } 343 } 344 } else { 345 if (!baij->donotstash) { 346 if (roworiented) { 347 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 348 } else { 349 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 350 } 351 } 352 } 353 } 354 PetscFunctionReturn(0); 355 } 356 357 #undef __FUNCT__ 358 #define __FUNCT__ "MatGetValues_MPISBAIJ" 359 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 360 { 361 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 362 PetscErrorCode ierr; 363 PetscInt bs=mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 364 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 365 366 PetscFunctionBegin; 367 for (i=0; i<m; i++) { 368 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */ 369 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 370 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 371 row = idxm[i] - bsrstart; 372 for (j=0; j<n; j++) { 373 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */ 374 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 375 if (idxn[j] >= bscstart && idxn[j] < bscend){ 376 col = idxn[j] - bscstart; 377 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 378 } else { 379 if (!baij->colmap) { 380 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 381 } 382 #if defined (PETSC_USE_CTABLE) 383 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 384 data --; 385 #else 386 data = baij->colmap[idxn[j]/bs]-1; 387 #endif 388 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 389 else { 390 col = data + idxn[j]%bs; 391 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 392 } 393 } 394 } 395 } else { 396 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 397 } 398 } 399 PetscFunctionReturn(0); 400 } 401 402 #undef __FUNCT__ 403 #define __FUNCT__ "MatNorm_MPISBAIJ" 404 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 405 { 406 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 407 PetscErrorCode ierr; 408 PetscReal sum[2],*lnorm2; 409 410 PetscFunctionBegin; 411 if (baij->size == 1) { 412 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 413 } else { 414 if (type == NORM_FROBENIUS) { 415 ierr = PetscMalloc(2*sizeof(PetscReal),&lnorm2);CHKERRQ(ierr); 416 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 417 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 418 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 419 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 420 ierr = MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 421 *norm = sqrt(sum[0] + 2*sum[1]); 422 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 423 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 424 Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data; 425 Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data; 426 PetscReal *rsum,*rsum2,vabs; 427 PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz; 428 PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs; 429 MatScalar *v; 430 431 ierr = PetscMalloc((2*mat->cmap->N+1)*sizeof(PetscReal),&rsum);CHKERRQ(ierr); 432 rsum2 = rsum + mat->cmap->N; 433 ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 434 /* Amat */ 435 v = amat->a; jj = amat->j; 436 for (brow=0; brow<mbs; brow++) { 437 grow = bs*(rstart + brow); 438 nz = amat->i[brow+1] - amat->i[brow]; 439 for (bcol=0; bcol<nz; bcol++){ 440 gcol = bs*(rstart + *jj); jj++; 441 for (col=0; col<bs; col++){ 442 for (row=0; row<bs; row++){ 443 vabs = PetscAbsScalar(*v); v++; 444 rsum[gcol+col] += vabs; 445 /* non-diagonal block */ 446 if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs; 447 } 448 } 449 } 450 } 451 /* Bmat */ 452 v = bmat->a; jj = bmat->j; 453 for (brow=0; brow<mbs; brow++) { 454 grow = bs*(rstart + brow); 455 nz = bmat->i[brow+1] - bmat->i[brow]; 456 for (bcol=0; bcol<nz; bcol++){ 457 gcol = bs*garray[*jj]; jj++; 458 for (col=0; col<bs; col++){ 459 for (row=0; row<bs; row++){ 460 vabs = PetscAbsScalar(*v); v++; 461 rsum[gcol+col] += vabs; 462 rsum[grow+row] += vabs; 463 } 464 } 465 } 466 } 467 ierr = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 468 *norm = 0.0; 469 for (col=0; col<mat->cmap->N; col++) { 470 if (rsum2[col] > *norm) *norm = rsum2[col]; 471 } 472 ierr = PetscFree(rsum);CHKERRQ(ierr); 473 } else { 474 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 475 } 476 } 477 PetscFunctionReturn(0); 478 } 479 480 #undef __FUNCT__ 481 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ" 482 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 483 { 484 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 485 PetscErrorCode ierr; 486 PetscInt nstash,reallocs; 487 InsertMode addv; 488 489 PetscFunctionBegin; 490 if (baij->donotstash) { 491 PetscFunctionReturn(0); 492 } 493 494 /* make sure all processors are either in INSERTMODE or ADDMODE */ 495 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 496 if (addv == (ADD_VALUES|INSERT_VALUES)) { 497 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 498 } 499 mat->insertmode = addv; /* in case this processor had no cache */ 500 501 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 502 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 503 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 504 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 505 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 506 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 507 PetscFunctionReturn(0); 508 } 509 510 #undef __FUNCT__ 511 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ" 512 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 513 { 514 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 515 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 516 PetscErrorCode ierr; 517 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 518 PetscInt *row,*col; 519 PetscTruth other_disassembled; 520 PetscMPIInt n; 521 PetscTruth r1,r2,r3; 522 MatScalar *val; 523 InsertMode addv = mat->insertmode; 524 525 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 526 PetscFunctionBegin; 527 528 if (!baij->donotstash) { 529 while (1) { 530 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 531 if (!flg) break; 532 533 for (i=0; i<n;) { 534 /* Now identify the consecutive vals belonging to the same row */ 535 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 536 if (j < n) ncols = j-i; 537 else ncols = n-i; 538 /* Now assemble all these values with a single function call */ 539 ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 540 i = j; 541 } 542 } 543 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 544 /* Now process the block-stash. Since the values are stashed column-oriented, 545 set the roworiented flag to column oriented, and after MatSetValues() 546 restore the original flags */ 547 r1 = baij->roworiented; 548 r2 = a->roworiented; 549 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 550 baij->roworiented = PETSC_FALSE; 551 a->roworiented = PETSC_FALSE; 552 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 553 while (1) { 554 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 555 if (!flg) break; 556 557 for (i=0; i<n;) { 558 /* Now identify the consecutive vals belonging to the same row */ 559 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 560 if (j < n) ncols = j-i; 561 else ncols = n-i; 562 ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 563 i = j; 564 } 565 } 566 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 567 baij->roworiented = r1; 568 a->roworiented = r2; 569 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */ 570 } 571 572 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 573 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 574 575 /* determine if any processor has disassembled, if so we must 576 also disassemble ourselfs, in order that we may reassemble. */ 577 /* 578 if nonzero structure of submatrix B cannot change then we know that 579 no processor disassembled thus we can skip this stuff 580 */ 581 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 582 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 583 if (mat->was_assembled && !other_disassembled) { 584 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 585 } 586 } 587 588 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 589 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */ 590 } 591 ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 592 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 593 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 594 595 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 596 baij->rowvalues = 0; 597 598 PetscFunctionReturn(0); 599 } 600 601 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 602 #undef __FUNCT__ 603 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 604 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 605 { 606 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 607 PetscErrorCode ierr; 608 PetscInt bs = mat->rmap->bs; 609 PetscMPIInt size = baij->size,rank = baij->rank; 610 PetscTruth iascii,isdraw; 611 PetscViewer sviewer; 612 PetscViewerFormat format; 613 614 PetscFunctionBegin; 615 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 616 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 617 if (iascii) { 618 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 619 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 620 MatInfo info; 621 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 622 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 623 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 624 rank,mat->rmap->N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs, 625 mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 626 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 627 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 628 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 629 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);CHKERRQ(ierr); 630 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 631 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 632 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 633 PetscFunctionReturn(0); 634 } else if (format == PETSC_VIEWER_ASCII_INFO) { 635 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 636 PetscFunctionReturn(0); 637 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 638 PetscFunctionReturn(0); 639 } 640 } 641 642 if (isdraw) { 643 PetscDraw draw; 644 PetscTruth isnull; 645 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 646 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 647 } 648 649 if (size == 1) { 650 ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 651 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 652 } else { 653 /* assemble the entire matrix onto first processor. */ 654 Mat A; 655 Mat_SeqSBAIJ *Aloc; 656 Mat_SeqBAIJ *Bloc; 657 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 658 MatScalar *a; 659 660 /* Should this be the same type as mat? */ 661 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 662 if (!rank) { 663 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 664 } else { 665 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 666 } 667 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 668 ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 669 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 670 671 /* copy over the A part */ 672 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 673 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 674 ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr); 675 676 for (i=0; i<mbs; i++) { 677 rvals[0] = bs*(baij->rstartbs + i); 678 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 679 for (j=ai[i]; j<ai[i+1]; j++) { 680 col = (baij->cstartbs+aj[j])*bs; 681 for (k=0; k<bs; k++) { 682 ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 683 col++; a += bs; 684 } 685 } 686 } 687 /* copy over the B part */ 688 Bloc = (Mat_SeqBAIJ*)baij->B->data; 689 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 690 for (i=0; i<mbs; i++) { 691 692 rvals[0] = bs*(baij->rstartbs + i); 693 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 694 for (j=ai[i]; j<ai[i+1]; j++) { 695 col = baij->garray[aj[j]]*bs; 696 for (k=0; k<bs; k++) { 697 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 698 col++; a += bs; 699 } 700 } 701 } 702 ierr = PetscFree(rvals);CHKERRQ(ierr); 703 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 704 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 705 /* 706 Everyone has to call to draw the matrix since the graphics waits are 707 synchronized across all processors that share the PetscDraw object 708 */ 709 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 710 if (!rank) { 711 ierr = PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 712 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 713 } 714 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 715 ierr = MatDestroy(A);CHKERRQ(ierr); 716 } 717 PetscFunctionReturn(0); 718 } 719 720 #undef __FUNCT__ 721 #define __FUNCT__ "MatView_MPISBAIJ" 722 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 723 { 724 PetscErrorCode ierr; 725 PetscTruth iascii,isdraw,issocket,isbinary; 726 727 PetscFunctionBegin; 728 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 729 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 730 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 731 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 732 if (iascii || isdraw || issocket || isbinary) { 733 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 734 } else { 735 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 736 } 737 PetscFunctionReturn(0); 738 } 739 740 #undef __FUNCT__ 741 #define __FUNCT__ "MatDestroy_MPISBAIJ" 742 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 743 { 744 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 745 PetscErrorCode ierr; 746 747 PetscFunctionBegin; 748 #if defined(PETSC_USE_LOG) 749 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 750 #endif 751 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 752 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 753 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 754 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 755 #if defined (PETSC_USE_CTABLE) 756 if (baij->colmap) {ierr = PetscTableDestroy(baij->colmap);CHKERRQ(ierr);} 757 #else 758 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 759 #endif 760 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 761 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 762 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 763 if (baij->slvec0) { 764 ierr = VecDestroy(baij->slvec0);CHKERRQ(ierr); 765 ierr = VecDestroy(baij->slvec0b);CHKERRQ(ierr); 766 } 767 if (baij->slvec1) { 768 ierr = VecDestroy(baij->slvec1);CHKERRQ(ierr); 769 ierr = VecDestroy(baij->slvec1a);CHKERRQ(ierr); 770 ierr = VecDestroy(baij->slvec1b);CHKERRQ(ierr); 771 } 772 if (baij->sMvctx) {ierr = VecScatterDestroy(baij->sMvctx);CHKERRQ(ierr);} 773 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 774 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 775 ierr = PetscFree(baij->hd);CHKERRQ(ierr); 776 #if defined(PETSC_USE_MAT_SINGLE) 777 ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr); 778 #endif 779 ierr = PetscFree(baij->in_loc);CHKERRQ(ierr); 780 ierr = PetscFree(baij->v_loc);CHKERRQ(ierr); 781 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 782 ierr = PetscFree(baij);CHKERRQ(ierr); 783 784 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 785 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 786 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 787 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 788 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 789 PetscFunctionReturn(0); 790 } 791 792 #undef __FUNCT__ 793 #define __FUNCT__ "MatMult_MPISBAIJ" 794 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 795 { 796 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 797 PetscErrorCode ierr; 798 PetscInt nt,mbs=a->mbs,bs=A->rmap->bs; 799 PetscScalar *x,*from,zero=0.0; 800 801 PetscFunctionBegin; 802 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 803 if (nt != A->cmap->n) { 804 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 805 } 806 807 /* diagonal part */ 808 ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr); 809 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 810 811 /* subdiagonal part */ 812 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 813 814 /* copy x into the vec slvec0 */ 815 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 816 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 817 818 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 819 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 820 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 821 822 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 823 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 824 /* supperdiagonal part */ 825 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr); 826 PetscFunctionReturn(0); 827 } 828 829 #undef __FUNCT__ 830 #define __FUNCT__ "MatMult_MPISBAIJ_2comm" 831 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy) 832 { 833 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 834 PetscErrorCode ierr; 835 PetscInt nt; 836 837 PetscFunctionBegin; 838 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 839 if (nt != A->cmap->n) { 840 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 841 } 842 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 843 if (nt != A->rmap->N) { 844 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 845 } 846 847 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 848 /* do diagonal part */ 849 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 850 /* do supperdiagonal part */ 851 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 852 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 853 /* do subdiagonal part */ 854 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 855 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 856 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 857 858 PetscFunctionReturn(0); 859 } 860 861 #undef __FUNCT__ 862 #define __FUNCT__ "MatMultAdd_MPISBAIJ" 863 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 864 { 865 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 866 PetscErrorCode ierr; 867 PetscInt mbs=a->mbs,bs=A->rmap->bs; 868 PetscScalar *x,*from,zero=0.0; 869 870 PetscFunctionBegin; 871 /* 872 PetscSynchronizedPrintf(((PetscObject)A)->comm," MatMultAdd is called ...\n"); 873 PetscSynchronizedFlush(((PetscObject)A)->comm); 874 */ 875 /* diagonal part */ 876 ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr); 877 ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr); 878 879 /* subdiagonal part */ 880 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr); 881 882 /* copy x into the vec slvec0 */ 883 ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr); 884 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 885 ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 886 ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr); 887 888 ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 889 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 890 ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 891 892 /* supperdiagonal part */ 893 ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr); 894 895 PetscFunctionReturn(0); 896 } 897 898 #undef __FUNCT__ 899 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm" 900 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz) 901 { 902 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 903 PetscErrorCode ierr; 904 905 PetscFunctionBegin; 906 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 907 /* do diagonal part */ 908 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 909 /* do supperdiagonal part */ 910 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 911 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 912 913 /* do subdiagonal part */ 914 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 915 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 916 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 917 918 PetscFunctionReturn(0); 919 } 920 921 /* 922 This only works correctly for square matrices where the subblock A->A is the 923 diagonal block 924 */ 925 #undef __FUNCT__ 926 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ" 927 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 928 { 929 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 930 PetscErrorCode ierr; 931 932 PetscFunctionBegin; 933 /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 934 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 935 PetscFunctionReturn(0); 936 } 937 938 #undef __FUNCT__ 939 #define __FUNCT__ "MatScale_MPISBAIJ" 940 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa) 941 { 942 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 943 PetscErrorCode ierr; 944 945 PetscFunctionBegin; 946 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 947 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNCT__ 952 #define __FUNCT__ "MatGetRow_MPISBAIJ" 953 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 954 { 955 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 956 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 957 PetscErrorCode ierr; 958 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 959 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 960 PetscInt *cmap,*idx_p,cstart = mat->rstartbs; 961 962 PetscFunctionBegin; 963 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 964 mat->getrowactive = PETSC_TRUE; 965 966 if (!mat->rowvalues && (idx || v)) { 967 /* 968 allocate enough space to hold information from the longest row. 969 */ 970 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 971 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 972 PetscInt max = 1,mbs = mat->mbs,tmp; 973 for (i=0; i<mbs; i++) { 974 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 975 if (max < tmp) { max = tmp; } 976 } 977 ierr = PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 978 mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2); 979 } 980 981 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 982 lrow = row - brstart; /* local row index */ 983 984 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 985 if (!v) {pvA = 0; pvB = 0;} 986 if (!idx) {pcA = 0; if (!v) pcB = 0;} 987 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 988 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 989 nztot = nzA + nzB; 990 991 cmap = mat->garray; 992 if (v || idx) { 993 if (nztot) { 994 /* Sort by increasing column numbers, assuming A and B already sorted */ 995 PetscInt imark = -1; 996 if (v) { 997 *v = v_p = mat->rowvalues; 998 for (i=0; i<nzB; i++) { 999 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1000 else break; 1001 } 1002 imark = i; 1003 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1004 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1005 } 1006 if (idx) { 1007 *idx = idx_p = mat->rowindices; 1008 if (imark > -1) { 1009 for (i=0; i<imark; i++) { 1010 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1011 } 1012 } else { 1013 for (i=0; i<nzB; i++) { 1014 if (cmap[cworkB[i]/bs] < cstart) 1015 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1016 else break; 1017 } 1018 imark = i; 1019 } 1020 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1021 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1022 } 1023 } else { 1024 if (idx) *idx = 0; 1025 if (v) *v = 0; 1026 } 1027 } 1028 *nz = nztot; 1029 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1030 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1031 PetscFunctionReturn(0); 1032 } 1033 1034 #undef __FUNCT__ 1035 #define __FUNCT__ "MatRestoreRow_MPISBAIJ" 1036 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1037 { 1038 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1039 1040 PetscFunctionBegin; 1041 if (!baij->getrowactive) { 1042 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1043 } 1044 baij->getrowactive = PETSC_FALSE; 1045 PetscFunctionReturn(0); 1046 } 1047 1048 #undef __FUNCT__ 1049 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ" 1050 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1051 { 1052 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1053 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1054 1055 PetscFunctionBegin; 1056 aA->getrow_utriangular = PETSC_TRUE; 1057 PetscFunctionReturn(0); 1058 } 1059 #undef __FUNCT__ 1060 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ" 1061 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1062 { 1063 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1064 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1065 1066 PetscFunctionBegin; 1067 aA->getrow_utriangular = PETSC_FALSE; 1068 PetscFunctionReturn(0); 1069 } 1070 1071 #undef __FUNCT__ 1072 #define __FUNCT__ "MatRealPart_MPISBAIJ" 1073 PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1074 { 1075 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1076 PetscErrorCode ierr; 1077 1078 PetscFunctionBegin; 1079 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1080 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1081 PetscFunctionReturn(0); 1082 } 1083 1084 #undef __FUNCT__ 1085 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ" 1086 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1087 { 1088 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1089 PetscErrorCode ierr; 1090 1091 PetscFunctionBegin; 1092 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1093 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1094 PetscFunctionReturn(0); 1095 } 1096 1097 #undef __FUNCT__ 1098 #define __FUNCT__ "MatZeroEntries_MPISBAIJ" 1099 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1100 { 1101 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1102 PetscErrorCode ierr; 1103 1104 PetscFunctionBegin; 1105 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1106 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1107 PetscFunctionReturn(0); 1108 } 1109 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "MatGetInfo_MPISBAIJ" 1112 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1113 { 1114 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1115 Mat A = a->A,B = a->B; 1116 PetscErrorCode ierr; 1117 PetscReal isend[5],irecv[5]; 1118 1119 PetscFunctionBegin; 1120 info->block_size = (PetscReal)matin->rmap->bs; 1121 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1122 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1123 isend[3] = info->memory; isend[4] = info->mallocs; 1124 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1125 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1126 isend[3] += info->memory; isend[4] += info->mallocs; 1127 if (flag == MAT_LOCAL) { 1128 info->nz_used = isend[0]; 1129 info->nz_allocated = isend[1]; 1130 info->nz_unneeded = isend[2]; 1131 info->memory = isend[3]; 1132 info->mallocs = isend[4]; 1133 } else if (flag == MAT_GLOBAL_MAX) { 1134 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1135 info->nz_used = irecv[0]; 1136 info->nz_allocated = irecv[1]; 1137 info->nz_unneeded = irecv[2]; 1138 info->memory = irecv[3]; 1139 info->mallocs = irecv[4]; 1140 } else if (flag == MAT_GLOBAL_SUM) { 1141 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1142 info->nz_used = irecv[0]; 1143 info->nz_allocated = irecv[1]; 1144 info->nz_unneeded = irecv[2]; 1145 info->memory = irecv[3]; 1146 info->mallocs = irecv[4]; 1147 } else { 1148 SETERRQ1(PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1149 } 1150 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1151 info->fill_ratio_needed = 0; 1152 info->factor_mallocs = 0; 1153 PetscFunctionReturn(0); 1154 } 1155 1156 #undef __FUNCT__ 1157 #define __FUNCT__ "MatSetOption_MPISBAIJ" 1158 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscTruth flg) 1159 { 1160 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1161 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data; 1162 PetscErrorCode ierr; 1163 1164 PetscFunctionBegin; 1165 switch (op) { 1166 case MAT_NEW_NONZERO_LOCATIONS: 1167 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1168 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1169 case MAT_KEEP_NONZERO_PATTERN: 1170 case MAT_NEW_NONZERO_LOCATION_ERR: 1171 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1172 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1173 break; 1174 case MAT_ROW_ORIENTED: 1175 a->roworiented = flg; 1176 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1177 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1178 break; 1179 case MAT_NEW_DIAGONALS: 1180 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1181 break; 1182 case MAT_IGNORE_OFF_PROC_ENTRIES: 1183 a->donotstash = flg; 1184 break; 1185 case MAT_USE_HASH_TABLE: 1186 a->ht_flag = flg; 1187 break; 1188 case MAT_HERMITIAN: 1189 if (flg) SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1190 case MAT_SYMMETRIC: 1191 case MAT_STRUCTURALLY_SYMMETRIC: 1192 case MAT_SYMMETRY_ETERNAL: 1193 if (!flg) SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); 1194 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1195 break; 1196 case MAT_IGNORE_LOWER_TRIANGULAR: 1197 aA->ignore_ltriangular = flg; 1198 break; 1199 case MAT_ERROR_LOWER_TRIANGULAR: 1200 aA->ignore_ltriangular = flg; 1201 break; 1202 case MAT_GETROW_UPPERTRIANGULAR: 1203 aA->getrow_utriangular = flg; 1204 break; 1205 default: 1206 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1207 } 1208 PetscFunctionReturn(0); 1209 } 1210 1211 #undef __FUNCT__ 1212 #define __FUNCT__ "MatTranspose_MPISBAIJ" 1213 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B) 1214 { 1215 PetscErrorCode ierr; 1216 PetscFunctionBegin; 1217 if (MAT_INITIAL_MATRIX || *B != A) { 1218 ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr); 1219 } 1220 PetscFunctionReturn(0); 1221 } 1222 1223 #undef __FUNCT__ 1224 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ" 1225 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1226 { 1227 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1228 Mat a=baij->A, b=baij->B; 1229 PetscErrorCode ierr; 1230 PetscInt nv,m,n; 1231 PetscTruth flg; 1232 1233 PetscFunctionBegin; 1234 if (ll != rr){ 1235 ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr); 1236 if (!flg) 1237 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1238 } 1239 if (!ll) PetscFunctionReturn(0); 1240 1241 ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr); 1242 if (m != n) SETERRQ2(PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n); 1243 1244 ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr); 1245 if (nv!=n) SETERRQ(PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size"); 1246 1247 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1248 1249 /* left diagonalscale the off-diagonal part */ 1250 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1251 1252 /* scale the diagonal part */ 1253 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1254 1255 /* right diagonalscale the off-diagonal part */ 1256 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1257 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1258 PetscFunctionReturn(0); 1259 } 1260 1261 #undef __FUNCT__ 1262 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ" 1263 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1264 { 1265 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1266 PetscErrorCode ierr; 1267 1268 PetscFunctionBegin; 1269 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1270 PetscFunctionReturn(0); 1271 } 1272 1273 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1274 1275 #undef __FUNCT__ 1276 #define __FUNCT__ "MatEqual_MPISBAIJ" 1277 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1278 { 1279 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1280 Mat a,b,c,d; 1281 PetscTruth flg; 1282 PetscErrorCode ierr; 1283 1284 PetscFunctionBegin; 1285 a = matA->A; b = matA->B; 1286 c = matB->A; d = matB->B; 1287 1288 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1289 if (flg) { 1290 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1291 } 1292 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1293 PetscFunctionReturn(0); 1294 } 1295 1296 #undef __FUNCT__ 1297 #define __FUNCT__ "MatCopy_MPISBAIJ" 1298 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str) 1299 { 1300 PetscErrorCode ierr; 1301 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1302 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1303 1304 PetscFunctionBegin; 1305 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1306 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1307 ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr); 1308 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1309 ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr); 1310 } else { 1311 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1312 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1313 } 1314 PetscFunctionReturn(0); 1315 } 1316 1317 #undef __FUNCT__ 1318 #define __FUNCT__ "MatSetUpPreallocation_MPISBAIJ" 1319 PetscErrorCode MatSetUpPreallocation_MPISBAIJ(Mat A) 1320 { 1321 PetscErrorCode ierr; 1322 1323 PetscFunctionBegin; 1324 ierr = MatMPISBAIJSetPreallocation(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1325 PetscFunctionReturn(0); 1326 } 1327 1328 #include "petscblaslapack.h" 1329 #undef __FUNCT__ 1330 #define __FUNCT__ "MatAXPY_MPISBAIJ" 1331 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1332 { 1333 PetscErrorCode ierr; 1334 Mat_MPISBAIJ *xx=(Mat_MPISBAIJ *)X->data,*yy=(Mat_MPISBAIJ *)Y->data; 1335 PetscBLASInt bnz,one=1; 1336 Mat_SeqSBAIJ *xa,*ya; 1337 Mat_SeqBAIJ *xb,*yb; 1338 1339 PetscFunctionBegin; 1340 if (str == SAME_NONZERO_PATTERN) { 1341 PetscScalar alpha = a; 1342 xa = (Mat_SeqSBAIJ *)xx->A->data; 1343 ya = (Mat_SeqSBAIJ *)yy->A->data; 1344 bnz = PetscBLASIntCast(xa->nz); 1345 BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one); 1346 xb = (Mat_SeqBAIJ *)xx->B->data; 1347 yb = (Mat_SeqBAIJ *)yy->B->data; 1348 bnz = PetscBLASIntCast(xb->nz); 1349 BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one); 1350 } else { 1351 ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr); 1352 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1353 ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr); 1354 } 1355 PetscFunctionReturn(0); 1356 } 1357 1358 #undef __FUNCT__ 1359 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ" 1360 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1361 { 1362 PetscErrorCode ierr; 1363 PetscInt i; 1364 PetscTruth flg; 1365 1366 PetscFunctionBegin; 1367 for (i=0; i<n; i++) { 1368 ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr); 1369 if (!flg) { 1370 SETERRQ(PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices"); 1371 } 1372 } 1373 ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr); 1374 PetscFunctionReturn(0); 1375 } 1376 1377 1378 /* -------------------------------------------------------------------*/ 1379 static struct _MatOps MatOps_Values = { 1380 MatSetValues_MPISBAIJ, 1381 MatGetRow_MPISBAIJ, 1382 MatRestoreRow_MPISBAIJ, 1383 MatMult_MPISBAIJ, 1384 /* 4*/ MatMultAdd_MPISBAIJ, 1385 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1386 MatMultAdd_MPISBAIJ, 1387 0, 1388 0, 1389 0, 1390 /*10*/ 0, 1391 0, 1392 0, 1393 MatRelax_MPISBAIJ, 1394 MatTranspose_MPISBAIJ, 1395 /*15*/ MatGetInfo_MPISBAIJ, 1396 MatEqual_MPISBAIJ, 1397 MatGetDiagonal_MPISBAIJ, 1398 MatDiagonalScale_MPISBAIJ, 1399 MatNorm_MPISBAIJ, 1400 /*20*/ MatAssemblyBegin_MPISBAIJ, 1401 MatAssemblyEnd_MPISBAIJ, 1402 MatSetOption_MPISBAIJ, 1403 MatZeroEntries_MPISBAIJ, 1404 /*24*/ 0, 1405 0, 1406 0, 1407 0, 1408 0, 1409 /*29*/ MatSetUpPreallocation_MPISBAIJ, 1410 0, 1411 0, 1412 0, 1413 0, 1414 /*34*/ MatDuplicate_MPISBAIJ, 1415 0, 1416 0, 1417 0, 1418 0, 1419 /*39*/ MatAXPY_MPISBAIJ, 1420 MatGetSubMatrices_MPISBAIJ, 1421 MatIncreaseOverlap_MPISBAIJ, 1422 MatGetValues_MPISBAIJ, 1423 MatCopy_MPISBAIJ, 1424 /*44*/ 0, 1425 MatScale_MPISBAIJ, 1426 0, 1427 0, 1428 0, 1429 /*49*/ 0, 1430 0, 1431 0, 1432 0, 1433 0, 1434 /*54*/ 0, 1435 0, 1436 MatSetUnfactored_MPISBAIJ, 1437 0, 1438 MatSetValuesBlocked_MPISBAIJ, 1439 /*59*/ 0, 1440 0, 1441 0, 1442 0, 1443 0, 1444 /*64*/ 0, 1445 0, 1446 0, 1447 0, 1448 0, 1449 /*69*/ MatGetRowMaxAbs_MPISBAIJ, 1450 0, 1451 0, 1452 0, 1453 0, 1454 /*74*/ 0, 1455 0, 1456 0, 1457 0, 1458 0, 1459 /*79*/ 0, 1460 0, 1461 0, 1462 0, 1463 MatLoad_MPISBAIJ, 1464 /*84*/ 0, 1465 0, 1466 0, 1467 0, 1468 0, 1469 /*89*/ 0, 1470 0, 1471 0, 1472 0, 1473 0, 1474 /*94*/ 0, 1475 0, 1476 0, 1477 0, 1478 0, 1479 /*99*/ 0, 1480 0, 1481 0, 1482 0, 1483 0, 1484 /*104*/0, 1485 MatRealPart_MPISBAIJ, 1486 MatImaginaryPart_MPISBAIJ, 1487 MatGetRowUpperTriangular_MPISBAIJ, 1488 MatRestoreRowUpperTriangular_MPISBAIJ 1489 }; 1490 1491 1492 EXTERN_C_BEGIN 1493 #undef __FUNCT__ 1494 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1495 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1496 { 1497 PetscFunctionBegin; 1498 *a = ((Mat_MPISBAIJ *)A->data)->A; 1499 *iscopy = PETSC_FALSE; 1500 PetscFunctionReturn(0); 1501 } 1502 EXTERN_C_END 1503 1504 EXTERN_C_BEGIN 1505 #undef __FUNCT__ 1506 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1507 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1508 { 1509 Mat_MPISBAIJ *b; 1510 PetscErrorCode ierr; 1511 PetscInt i,mbs,Mbs,newbs = PetscAbs(bs); 1512 1513 PetscFunctionBegin; 1514 if (bs < 0){ 1515 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPISBAIJ matrix","Mat");CHKERRQ(ierr); 1516 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);CHKERRQ(ierr); 1517 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1518 bs = PetscAbs(bs); 1519 } 1520 if ((d_nnz || o_nnz) && newbs != bs) { 1521 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz"); 1522 } 1523 bs = newbs; 1524 1525 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1526 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1527 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1528 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1529 1530 B->rmap->bs = B->cmap->bs = bs; 1531 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 1532 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 1533 1534 if (d_nnz) { 1535 for (i=0; i<B->rmap->n/bs; i++) { 1536 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]); 1537 } 1538 } 1539 if (o_nnz) { 1540 for (i=0; i<B->rmap->n/bs; i++) { 1541 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]); 1542 } 1543 } 1544 1545 b = (Mat_MPISBAIJ*)B->data; 1546 mbs = B->rmap->n/bs; 1547 Mbs = B->rmap->N/bs; 1548 if (mbs*bs != B->rmap->n) { 1549 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs); 1550 } 1551 1552 B->rmap->bs = bs; 1553 b->bs2 = bs*bs; 1554 b->mbs = mbs; 1555 b->nbs = mbs; 1556 b->Mbs = Mbs; 1557 b->Nbs = Mbs; 1558 1559 for (i=0; i<=b->size; i++) { 1560 b->rangebs[i] = B->rmap->range[i]/bs; 1561 } 1562 b->rstartbs = B->rmap->rstart/bs; 1563 b->rendbs = B->rmap->rend/bs; 1564 1565 b->cstartbs = B->cmap->rstart/bs; 1566 b->cendbs = B->cmap->rend/bs; 1567 1568 if (!B->preallocated) { 1569 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1570 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1571 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1572 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1573 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1574 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1575 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1576 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1577 /* build cache for off array entries formed */ 1578 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 1579 } 1580 1581 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1582 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1583 B->preallocated = PETSC_TRUE; 1584 PetscFunctionReturn(0); 1585 } 1586 EXTERN_C_END 1587 1588 EXTERN_C_BEGIN 1589 #if defined(PETSC_HAVE_MUMPS) 1590 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_mpisbaij_mumps(Mat,MatFactorType,Mat*); 1591 #endif 1592 #if defined(PETSC_HAVE_SPOOLES) 1593 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_mpisbaij_spooles(Mat,MatFactorType,Mat*); 1594 #endif 1595 #if defined(PETSC_HAVE_PASTIX) 1596 extern PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*); 1597 #endif 1598 EXTERN_C_END 1599 1600 /*MC 1601 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1602 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1603 1604 Options Database Keys: 1605 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1606 1607 Level: beginner 1608 1609 .seealso: MatCreateMPISBAIJ 1610 M*/ 1611 1612 EXTERN_C_BEGIN 1613 #undef __FUNCT__ 1614 #define __FUNCT__ "MatCreate_MPISBAIJ" 1615 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPISBAIJ(Mat B) 1616 { 1617 Mat_MPISBAIJ *b; 1618 PetscErrorCode ierr; 1619 PetscTruth flg; 1620 1621 PetscFunctionBegin; 1622 1623 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1624 B->data = (void*)b; 1625 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1626 1627 B->ops->destroy = MatDestroy_MPISBAIJ; 1628 B->ops->view = MatView_MPISBAIJ; 1629 B->mapping = 0; 1630 B->assembled = PETSC_FALSE; 1631 1632 B->insertmode = NOT_SET_VALUES; 1633 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 1634 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 1635 1636 /* build local table of row and column ownerships */ 1637 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1638 1639 /* build cache for off array entries formed */ 1640 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 1641 b->donotstash = PETSC_FALSE; 1642 b->colmap = PETSC_NULL; 1643 b->garray = PETSC_NULL; 1644 b->roworiented = PETSC_TRUE; 1645 1646 /* stuff used in block assembly */ 1647 b->barray = 0; 1648 1649 /* stuff used for matrix vector multiply */ 1650 b->lvec = 0; 1651 b->Mvctx = 0; 1652 b->slvec0 = 0; 1653 b->slvec0b = 0; 1654 b->slvec1 = 0; 1655 b->slvec1a = 0; 1656 b->slvec1b = 0; 1657 b->sMvctx = 0; 1658 1659 /* stuff for MatGetRow() */ 1660 b->rowindices = 0; 1661 b->rowvalues = 0; 1662 b->getrowactive = PETSC_FALSE; 1663 1664 /* hash table stuff */ 1665 b->ht = 0; 1666 b->hd = 0; 1667 b->ht_size = 0; 1668 b->ht_flag = PETSC_FALSE; 1669 b->ht_fact = 0; 1670 b->ht_total_ct = 0; 1671 b->ht_insert_ct = 0; 1672 1673 b->in_loc = 0; 1674 b->v_loc = 0; 1675 b->n_loc = 0; 1676 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1677 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 1678 if (flg) { 1679 PetscReal fact = 1.39; 1680 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1681 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 1682 if (fact <= 1.0) fact = 1.39; 1683 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1684 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1685 } 1686 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1687 1688 #if defined(PETSC_HAVE_PASTIX) 1689 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_pastix_C", 1690 "MatGetFactor_mpisbaij_pastix", 1691 MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr); 1692 #endif 1693 #if defined(PETSC_HAVE_MUMPS) 1694 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_mumps_C", 1695 "MatGetFactor_mpisbaij_mumps", 1696 MatGetFactor_mpisbaij_mumps);CHKERRQ(ierr); 1697 #endif 1698 #if defined(PETSC_HAVE_SPOOLES) 1699 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_spooles_C", 1700 "MatGetFactor_mpisbaij_spooles", 1701 MatGetFactor_mpisbaij_spooles);CHKERRQ(ierr); 1702 #endif 1703 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1704 "MatStoreValues_MPISBAIJ", 1705 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1706 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1707 "MatRetrieveValues_MPISBAIJ", 1708 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1709 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1710 "MatGetDiagonalBlock_MPISBAIJ", 1711 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1712 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1713 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1714 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1715 B->symmetric = PETSC_TRUE; 1716 B->structurally_symmetric = PETSC_TRUE; 1717 B->symmetric_set = PETSC_TRUE; 1718 B->structurally_symmetric_set = PETSC_TRUE; 1719 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1720 PetscFunctionReturn(0); 1721 } 1722 EXTERN_C_END 1723 1724 /*MC 1725 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1726 1727 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1728 and MATMPISBAIJ otherwise. 1729 1730 Options Database Keys: 1731 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1732 1733 Level: beginner 1734 1735 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1736 M*/ 1737 1738 EXTERN_C_BEGIN 1739 #undef __FUNCT__ 1740 #define __FUNCT__ "MatCreate_SBAIJ" 1741 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SBAIJ(Mat A) 1742 { 1743 PetscErrorCode ierr; 1744 PetscMPIInt size; 1745 1746 PetscFunctionBegin; 1747 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 1748 if (size == 1) { 1749 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1750 } else { 1751 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1752 } 1753 PetscFunctionReturn(0); 1754 } 1755 EXTERN_C_END 1756 1757 #undef __FUNCT__ 1758 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1759 /*@C 1760 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1761 the user should preallocate the matrix storage by setting the parameters 1762 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1763 performance can be increased by more than a factor of 50. 1764 1765 Collective on Mat 1766 1767 Input Parameters: 1768 + A - the matrix 1769 . bs - size of blockk 1770 . d_nz - number of block nonzeros per block row in diagonal portion of local 1771 submatrix (same for all local rows) 1772 . d_nnz - array containing the number of block nonzeros in the various block rows 1773 in the upper triangular and diagonal part of the in diagonal portion of the local 1774 (possibly different for each block row) or PETSC_NULL. You must leave room 1775 for the diagonal entry even if it is zero. 1776 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1777 submatrix (same for all local rows). 1778 - o_nnz - array containing the number of nonzeros in the various block rows of the 1779 off-diagonal portion of the local submatrix (possibly different for 1780 each block row) or PETSC_NULL. 1781 1782 1783 Options Database Keys: 1784 . -mat_no_unroll - uses code that does not unroll the loops in the 1785 block calculations (much slower) 1786 . -mat_block_size - size of the blocks to use 1787 1788 Notes: 1789 1790 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1791 than it must be used on all processors that share the object for that argument. 1792 1793 If the *_nnz parameter is given then the *_nz parameter is ignored 1794 1795 Storage Information: 1796 For a square global matrix we define each processor's diagonal portion 1797 to be its local rows and the corresponding columns (a square submatrix); 1798 each processor's off-diagonal portion encompasses the remainder of the 1799 local matrix (a rectangular submatrix). 1800 1801 The user can specify preallocated storage for the diagonal part of 1802 the local submatrix with either d_nz or d_nnz (not both). Set 1803 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1804 memory allocation. Likewise, specify preallocated storage for the 1805 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1806 1807 You can call MatGetInfo() to get information on how effective the preallocation was; 1808 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1809 You can also run with the option -info and look for messages with the string 1810 malloc in them to see if additional memory allocation was needed. 1811 1812 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1813 the figure below we depict these three local rows and all columns (0-11). 1814 1815 .vb 1816 0 1 2 3 4 5 6 7 8 9 10 11 1817 ------------------- 1818 row 3 | o o o d d d o o o o o o 1819 row 4 | o o o d d d o o o o o o 1820 row 5 | o o o d d d o o o o o o 1821 ------------------- 1822 .ve 1823 1824 Thus, any entries in the d locations are stored in the d (diagonal) 1825 submatrix, and any entries in the o locations are stored in the 1826 o (off-diagonal) submatrix. Note that the d matrix is stored in 1827 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1828 1829 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1830 plus the diagonal part of the d matrix, 1831 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1832 In general, for PDE problems in which most nonzeros are near the diagonal, 1833 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1834 or you will get TERRIBLE performance; see the users' manual chapter on 1835 matrices. 1836 1837 Level: intermediate 1838 1839 .keywords: matrix, block, aij, compressed row, sparse, parallel 1840 1841 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1842 @*/ 1843 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1844 { 1845 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1846 1847 PetscFunctionBegin; 1848 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1849 if (f) { 1850 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1851 } 1852 PetscFunctionReturn(0); 1853 } 1854 1855 #undef __FUNCT__ 1856 #define __FUNCT__ "MatCreateMPISBAIJ" 1857 /*@C 1858 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1859 (block compressed row). For good matrix assembly performance 1860 the user should preallocate the matrix storage by setting the parameters 1861 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1862 performance can be increased by more than a factor of 50. 1863 1864 Collective on MPI_Comm 1865 1866 Input Parameters: 1867 + comm - MPI communicator 1868 . bs - size of blockk 1869 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1870 This value should be the same as the local size used in creating the 1871 y vector for the matrix-vector product y = Ax. 1872 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1873 This value should be the same as the local size used in creating the 1874 x vector for the matrix-vector product y = Ax. 1875 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1876 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1877 . d_nz - number of block nonzeros per block row in diagonal portion of local 1878 submatrix (same for all local rows) 1879 . d_nnz - array containing the number of block nonzeros in the various block rows 1880 in the upper triangular portion of the in diagonal portion of the local 1881 (possibly different for each block block row) or PETSC_NULL. 1882 You must leave room for the diagonal entry even if it is zero. 1883 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1884 submatrix (same for all local rows). 1885 - o_nnz - array containing the number of nonzeros in the various block rows of the 1886 off-diagonal portion of the local submatrix (possibly different for 1887 each block row) or PETSC_NULL. 1888 1889 Output Parameter: 1890 . A - the matrix 1891 1892 Options Database Keys: 1893 . -mat_no_unroll - uses code that does not unroll the loops in the 1894 block calculations (much slower) 1895 . -mat_block_size - size of the blocks to use 1896 . -mat_mpi - use the parallel matrix data structures even on one processor 1897 (defaults to using SeqBAIJ format on one processor) 1898 1899 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1900 MatXXXXSetPreallocation() paradgm instead of this routine directly. 1901 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 1902 1903 Notes: 1904 The number of rows and columns must be divisible by blocksize. 1905 This matrix type does not support complex Hermitian operation. 1906 1907 The user MUST specify either the local or global matrix dimensions 1908 (possibly both). 1909 1910 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1911 than it must be used on all processors that share the object for that argument. 1912 1913 If the *_nnz parameter is given then the *_nz parameter is ignored 1914 1915 Storage Information: 1916 For a square global matrix we define each processor's diagonal portion 1917 to be its local rows and the corresponding columns (a square submatrix); 1918 each processor's off-diagonal portion encompasses the remainder of the 1919 local matrix (a rectangular submatrix). 1920 1921 The user can specify preallocated storage for the diagonal part of 1922 the local submatrix with either d_nz or d_nnz (not both). Set 1923 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1924 memory allocation. Likewise, specify preallocated storage for the 1925 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1926 1927 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1928 the figure below we depict these three local rows and all columns (0-11). 1929 1930 .vb 1931 0 1 2 3 4 5 6 7 8 9 10 11 1932 ------------------- 1933 row 3 | o o o d d d o o o o o o 1934 row 4 | o o o d d d o o o o o o 1935 row 5 | o o o d d d o o o o o o 1936 ------------------- 1937 .ve 1938 1939 Thus, any entries in the d locations are stored in the d (diagonal) 1940 submatrix, and any entries in the o locations are stored in the 1941 o (off-diagonal) submatrix. Note that the d matrix is stored in 1942 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1943 1944 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1945 plus the diagonal part of the d matrix, 1946 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1947 In general, for PDE problems in which most nonzeros are near the diagonal, 1948 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1949 or you will get TERRIBLE performance; see the users' manual chapter on 1950 matrices. 1951 1952 Level: intermediate 1953 1954 .keywords: matrix, block, aij, compressed row, sparse, parallel 1955 1956 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1957 @*/ 1958 1959 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPISBAIJ(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) 1960 { 1961 PetscErrorCode ierr; 1962 PetscMPIInt size; 1963 1964 PetscFunctionBegin; 1965 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1966 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1967 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1968 if (size > 1) { 1969 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1970 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1971 } else { 1972 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1973 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1974 } 1975 PetscFunctionReturn(0); 1976 } 1977 1978 1979 #undef __FUNCT__ 1980 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1981 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1982 { 1983 Mat mat; 1984 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1985 PetscErrorCode ierr; 1986 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 1987 PetscScalar *array; 1988 1989 PetscFunctionBegin; 1990 *newmat = 0; 1991 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 1992 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 1993 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 1994 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1995 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 1996 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 1997 1998 mat->factor = matin->factor; 1999 mat->preallocated = PETSC_TRUE; 2000 mat->assembled = PETSC_TRUE; 2001 mat->insertmode = NOT_SET_VALUES; 2002 2003 a = (Mat_MPISBAIJ*)mat->data; 2004 a->bs2 = oldmat->bs2; 2005 a->mbs = oldmat->mbs; 2006 a->nbs = oldmat->nbs; 2007 a->Mbs = oldmat->Mbs; 2008 a->Nbs = oldmat->Nbs; 2009 2010 2011 a->size = oldmat->size; 2012 a->rank = oldmat->rank; 2013 a->donotstash = oldmat->donotstash; 2014 a->roworiented = oldmat->roworiented; 2015 a->rowindices = 0; 2016 a->rowvalues = 0; 2017 a->getrowactive = PETSC_FALSE; 2018 a->barray = 0; 2019 a->rstartbs = oldmat->rstartbs; 2020 a->rendbs = oldmat->rendbs; 2021 a->cstartbs = oldmat->cstartbs; 2022 a->cendbs = oldmat->cendbs; 2023 2024 /* hash table stuff */ 2025 a->ht = 0; 2026 a->hd = 0; 2027 a->ht_size = 0; 2028 a->ht_flag = oldmat->ht_flag; 2029 a->ht_fact = oldmat->ht_fact; 2030 a->ht_total_ct = 0; 2031 a->ht_insert_ct = 0; 2032 2033 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2034 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2035 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2036 if (oldmat->colmap) { 2037 #if defined (PETSC_USE_CTABLE) 2038 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2039 #else 2040 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2041 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2042 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2043 #endif 2044 } else a->colmap = 0; 2045 2046 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2047 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2048 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2049 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2050 } else a->garray = 0; 2051 2052 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2053 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2054 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2055 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2056 2057 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2058 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2059 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2060 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2061 2062 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2063 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2064 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2065 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2066 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2067 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2068 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2069 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2070 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2071 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2072 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2073 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2074 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2075 2076 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2077 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2078 a->sMvctx = oldmat->sMvctx; 2079 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2080 2081 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2082 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2083 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2084 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2085 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2086 *newmat = mat; 2087 PetscFunctionReturn(0); 2088 } 2089 2090 #include "petscsys.h" 2091 2092 #undef __FUNCT__ 2093 #define __FUNCT__ "MatLoad_MPISBAIJ" 2094 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2095 { 2096 Mat A; 2097 PetscErrorCode ierr; 2098 PetscInt i,nz,j,rstart,rend; 2099 PetscScalar *vals,*buf; 2100 MPI_Comm comm = ((PetscObject)viewer)->comm; 2101 MPI_Status status; 2102 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,*locrowlens,mmbs; 2103 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2104 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2105 PetscInt bs=1,Mbs,mbs,extra_rows; 2106 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2107 PetscInt dcount,kmax,k,nzcount,tmp; 2108 int fd; 2109 2110 PetscFunctionBegin; 2111 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2112 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2113 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2114 2115 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2116 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2117 if (!rank) { 2118 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2119 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2120 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2121 if (header[3] < 0) { 2122 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2123 } 2124 } 2125 2126 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2127 M = header[1]; N = header[2]; 2128 2129 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2130 2131 /* 2132 This code adds extra rows to make sure the number of rows is 2133 divisible by the blocksize 2134 */ 2135 Mbs = M/bs; 2136 extra_rows = bs - M + bs*(Mbs); 2137 if (extra_rows == bs) extra_rows = 0; 2138 else Mbs++; 2139 if (extra_rows &&!rank) { 2140 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2141 } 2142 2143 /* determine ownership of all rows */ 2144 mbs = Mbs/size + ((Mbs % size) > rank); 2145 m = mbs*bs; 2146 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2147 browners = rowners + size + 1; 2148 mmbs = PetscMPIIntCast(mbs); 2149 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2150 rowners[0] = 0; 2151 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2152 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2153 rstart = rowners[rank]; 2154 rend = rowners[rank+1]; 2155 2156 /* distribute row lengths to all processors */ 2157 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscMPIInt),&locrowlens);CHKERRQ(ierr); 2158 if (!rank) { 2159 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2160 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2161 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2162 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2163 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2164 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2165 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2166 } else { 2167 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2168 } 2169 2170 if (!rank) { /* procs[0] */ 2171 /* calculate the number of nonzeros on each processor */ 2172 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2173 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2174 for (i=0; i<size; i++) { 2175 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2176 procsnz[i] += rowlengths[j]; 2177 } 2178 } 2179 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2180 2181 /* determine max buffer needed and allocate it */ 2182 maxnz = 0; 2183 for (i=0; i<size; i++) { 2184 maxnz = PetscMax(maxnz,procsnz[i]); 2185 } 2186 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2187 2188 /* read in my part of the matrix column indices */ 2189 nz = procsnz[0]; 2190 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2191 mycols = ibuf; 2192 if (size == 1) nz -= extra_rows; 2193 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2194 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2195 2196 /* read in every ones (except the last) and ship off */ 2197 for (i=1; i<size-1; i++) { 2198 nz = procsnz[i]; 2199 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2200 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2201 } 2202 /* read in the stuff for the last proc */ 2203 if (size != 1) { 2204 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2205 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2206 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2207 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2208 } 2209 ierr = PetscFree(cols);CHKERRQ(ierr); 2210 } else { /* procs[i], i>0 */ 2211 /* determine buffer space needed for message */ 2212 nz = 0; 2213 for (i=0; i<m; i++) { 2214 nz += locrowlens[i]; 2215 } 2216 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2217 mycols = ibuf; 2218 /* receive message of column indices*/ 2219 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2220 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2221 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2222 } 2223 2224 /* loop over local rows, determining number of off diagonal entries */ 2225 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2226 odlens = dlens + (rend-rstart); 2227 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2228 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2229 masked1 = mask + Mbs; 2230 masked2 = masked1 + Mbs; 2231 rowcount = 0; nzcount = 0; 2232 for (i=0; i<mbs; i++) { 2233 dcount = 0; 2234 odcount = 0; 2235 for (j=0; j<bs; j++) { 2236 kmax = locrowlens[rowcount]; 2237 for (k=0; k<kmax; k++) { 2238 tmp = mycols[nzcount++]/bs; /* block col. index */ 2239 if (!mask[tmp]) { 2240 mask[tmp] = 1; 2241 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2242 else masked1[dcount++] = tmp; /* entry in diag portion */ 2243 } 2244 } 2245 rowcount++; 2246 } 2247 2248 dlens[i] = dcount; /* d_nzz[i] */ 2249 odlens[i] = odcount; /* o_nzz[i] */ 2250 2251 /* zero out the mask elements we set */ 2252 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2253 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2254 } 2255 2256 /* create our matrix */ 2257 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2258 ierr = MatSetSizes(A,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2259 ierr = MatSetType(A,type);CHKERRQ(ierr); 2260 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2261 2262 if (!rank) { 2263 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2264 /* read in my part of the matrix numerical values */ 2265 nz = procsnz[0]; 2266 vals = buf; 2267 mycols = ibuf; 2268 if (size == 1) nz -= extra_rows; 2269 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2270 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2271 2272 /* insert into matrix */ 2273 jj = rstart*bs; 2274 for (i=0; i<m; i++) { 2275 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2276 mycols += locrowlens[i]; 2277 vals += locrowlens[i]; 2278 jj++; 2279 } 2280 2281 /* read in other processors (except the last one) and ship out */ 2282 for (i=1; i<size-1; i++) { 2283 nz = procsnz[i]; 2284 vals = buf; 2285 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2286 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2287 } 2288 /* the last proc */ 2289 if (size != 1){ 2290 nz = procsnz[i] - extra_rows; 2291 vals = buf; 2292 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2293 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2294 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2295 } 2296 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2297 2298 } else { 2299 /* receive numeric values */ 2300 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2301 2302 /* receive message of values*/ 2303 vals = buf; 2304 mycols = ibuf; 2305 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2306 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2307 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2308 2309 /* insert into matrix */ 2310 jj = rstart*bs; 2311 for (i=0; i<m; i++) { 2312 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2313 mycols += locrowlens[i]; 2314 vals += locrowlens[i]; 2315 jj++; 2316 } 2317 } 2318 2319 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2320 ierr = PetscFree(buf);CHKERRQ(ierr); 2321 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2322 ierr = PetscFree(rowners);CHKERRQ(ierr); 2323 ierr = PetscFree(dlens);CHKERRQ(ierr); 2324 ierr = PetscFree(mask);CHKERRQ(ierr); 2325 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2326 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2327 *newmat = A; 2328 PetscFunctionReturn(0); 2329 } 2330 2331 #undef __FUNCT__ 2332 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2333 /*XXXXX@ 2334 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2335 2336 Input Parameters: 2337 . mat - the matrix 2338 . fact - factor 2339 2340 Collective on Mat 2341 2342 Level: advanced 2343 2344 Notes: 2345 This can also be set by the command line option: -mat_use_hash_table fact 2346 2347 .keywords: matrix, hashtable, factor, HT 2348 2349 .seealso: MatSetOption() 2350 @XXXXX*/ 2351 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2355 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2356 { 2357 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2358 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2359 PetscReal atmp; 2360 PetscReal *work,*svalues,*rvalues; 2361 PetscErrorCode ierr; 2362 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2363 PetscMPIInt rank,size; 2364 PetscInt *rowners_bs,dest,count,source; 2365 PetscScalar *va; 2366 MatScalar *ba; 2367 MPI_Status stat; 2368 2369 PetscFunctionBegin; 2370 if (idx) SETERRQ(PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2371 ierr = MatGetRowMaxAbs(a->A,v,PETSC_NULL);CHKERRQ(ierr); 2372 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2373 2374 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2375 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 2376 2377 bs = A->rmap->bs; 2378 mbs = a->mbs; 2379 Mbs = a->Mbs; 2380 ba = b->a; 2381 bi = b->i; 2382 bj = b->j; 2383 2384 /* find ownerships */ 2385 rowners_bs = A->rmap->range; 2386 2387 /* each proc creates an array to be distributed */ 2388 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2389 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2390 2391 /* row_max for B */ 2392 if (rank != size-1){ 2393 for (i=0; i<mbs; i++) { 2394 ncols = bi[1] - bi[0]; bi++; 2395 brow = bs*i; 2396 for (j=0; j<ncols; j++){ 2397 bcol = bs*(*bj); 2398 for (kcol=0; kcol<bs; kcol++){ 2399 col = bcol + kcol; /* local col index */ 2400 col += rowners_bs[rank+1]; /* global col index */ 2401 for (krow=0; krow<bs; krow++){ 2402 atmp = PetscAbsScalar(*ba); ba++; 2403 row = brow + krow; /* local row index */ 2404 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2405 if (work[col] < atmp) work[col] = atmp; 2406 } 2407 } 2408 bj++; 2409 } 2410 } 2411 2412 /* send values to its owners */ 2413 for (dest=rank+1; dest<size; dest++){ 2414 svalues = work + rowners_bs[dest]; 2415 count = rowners_bs[dest+1]-rowners_bs[dest]; 2416 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,((PetscObject)A)->comm);CHKERRQ(ierr); 2417 } 2418 } 2419 2420 /* receive values */ 2421 if (rank){ 2422 rvalues = work; 2423 count = rowners_bs[rank+1]-rowners_bs[rank]; 2424 for (source=0; source<rank; source++){ 2425 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,((PetscObject)A)->comm,&stat);CHKERRQ(ierr); 2426 /* process values */ 2427 for (i=0; i<count; i++){ 2428 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2429 } 2430 } 2431 } 2432 2433 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2434 ierr = PetscFree(work);CHKERRQ(ierr); 2435 PetscFunctionReturn(0); 2436 } 2437 2438 #undef __FUNCT__ 2439 #define __FUNCT__ "MatRelax_MPISBAIJ" 2440 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2441 { 2442 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2443 PetscErrorCode ierr; 2444 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2445 PetscScalar *x,*b,*ptr,zero=0.0; 2446 Vec bb1; 2447 2448 PetscFunctionBegin; 2449 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2450 if (bs > 1) SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2451 2452 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2453 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2454 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2455 its--; 2456 } 2457 2458 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2459 while (its--){ 2460 2461 /* lower triangular part: slvec0b = - B^T*xx */ 2462 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2463 2464 /* copy xx into slvec0a */ 2465 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2466 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2467 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2468 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2469 2470 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2471 2472 /* copy bb into slvec1a */ 2473 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2474 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2475 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2476 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2477 2478 /* set slvec1b = 0 */ 2479 ierr = VecSet(mat->slvec1b,zero);CHKERRQ(ierr); 2480 2481 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2482 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2483 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2484 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2485 2486 /* upper triangular part: bb1 = bb1 - B*x */ 2487 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2488 2489 /* local diagonal sweep */ 2490 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2491 } 2492 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2493 } else { 2494 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2495 } 2496 PetscFunctionReturn(0); 2497 } 2498 2499 #undef __FUNCT__ 2500 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2501 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2502 { 2503 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2504 PetscErrorCode ierr; 2505 Vec lvec1,bb1; 2506 2507 PetscFunctionBegin; 2508 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2509 if (matin->rmap->bs > 1) SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2510 2511 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2512 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2513 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2514 its--; 2515 } 2516 2517 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2518 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2519 while (its--){ 2520 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2521 2522 /* lower diagonal part: bb1 = bb - B^T*xx */ 2523 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2524 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2525 2526 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2527 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2528 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2529 2530 /* upper diagonal part: bb1 = bb1 - B*x */ 2531 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2532 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2533 2534 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2535 2536 /* diagonal sweep */ 2537 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2538 } 2539 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2540 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2541 } else { 2542 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2543 } 2544 PetscFunctionReturn(0); 2545 } 2546 2547