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 == PETSC_TRUE) 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_ZEROED_ROWS: 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 0, 1403 MatSetOption_MPISBAIJ, 1404 MatZeroEntries_MPISBAIJ, 1405 /*25*/ 0, 1406 0, 1407 0, 1408 0, 1409 0, 1410 /*30*/ MatSetUpPreallocation_MPISBAIJ, 1411 0, 1412 0, 1413 0, 1414 0, 1415 /*35*/ MatDuplicate_MPISBAIJ, 1416 0, 1417 0, 1418 0, 1419 0, 1420 /*40*/ MatAXPY_MPISBAIJ, 1421 MatGetSubMatrices_MPISBAIJ, 1422 MatIncreaseOverlap_MPISBAIJ, 1423 MatGetValues_MPISBAIJ, 1424 MatCopy_MPISBAIJ, 1425 /*45*/ 0, 1426 MatScale_MPISBAIJ, 1427 0, 1428 0, 1429 0, 1430 /*50*/ 0, 1431 0, 1432 0, 1433 0, 1434 0, 1435 /*55*/ 0, 1436 0, 1437 MatSetUnfactored_MPISBAIJ, 1438 0, 1439 MatSetValuesBlocked_MPISBAIJ, 1440 /*60*/ 0, 1441 0, 1442 0, 1443 0, 1444 0, 1445 /*65*/ 0, 1446 0, 1447 0, 1448 0, 1449 0, 1450 /*70*/ MatGetRowMaxAbs_MPISBAIJ, 1451 0, 1452 0, 1453 0, 1454 0, 1455 /*75*/ 0, 1456 0, 1457 0, 1458 0, 1459 0, 1460 /*80*/ 0, 1461 0, 1462 0, 1463 0, 1464 MatLoad_MPISBAIJ, 1465 /*85*/ 0, 1466 0, 1467 0, 1468 0, 1469 0, 1470 /*90*/ 0, 1471 0, 1472 0, 1473 0, 1474 0, 1475 /*95*/ 0, 1476 0, 1477 0, 1478 0, 1479 0, 1480 /*100*/0, 1481 0, 1482 0, 1483 0, 1484 0, 1485 /*105*/0, 1486 MatRealPart_MPISBAIJ, 1487 MatImaginaryPart_MPISBAIJ, 1488 MatGetRowUpperTriangular_MPISBAIJ, 1489 MatRestoreRowUpperTriangular_MPISBAIJ 1490 }; 1491 1492 1493 EXTERN_C_BEGIN 1494 #undef __FUNCT__ 1495 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ" 1496 PetscErrorCode PETSCMAT_DLLEXPORT MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1497 { 1498 PetscFunctionBegin; 1499 *a = ((Mat_MPISBAIJ *)A->data)->A; 1500 *iscopy = PETSC_FALSE; 1501 PetscFunctionReturn(0); 1502 } 1503 EXTERN_C_END 1504 1505 EXTERN_C_BEGIN 1506 #undef __FUNCT__ 1507 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ" 1508 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,PetscInt *d_nnz,PetscInt o_nz,PetscInt *o_nnz) 1509 { 1510 Mat_MPISBAIJ *b; 1511 PetscErrorCode ierr; 1512 PetscInt i,mbs,Mbs,newbs = PetscAbs(bs); 1513 1514 PetscFunctionBegin; 1515 if (bs < 0){ 1516 ierr = PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPISBAIJ matrix","Mat");CHKERRQ(ierr); 1517 ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatMPIBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);CHKERRQ(ierr); 1518 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1519 bs = PetscAbs(bs); 1520 } 1521 if ((d_nnz || o_nnz) && newbs != bs) { 1522 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting d_nnz or o_nnz"); 1523 } 1524 bs = newbs; 1525 1526 if (d_nz == PETSC_DECIDE || d_nz == PETSC_DEFAULT) d_nz = 3; 1527 if (o_nz == PETSC_DECIDE || o_nz == PETSC_DEFAULT) o_nz = 1; 1528 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 1529 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 1530 1531 B->rmap->bs = B->cmap->bs = bs; 1532 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 1533 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 1534 1535 if (d_nnz) { 1536 for (i=0; i<B->rmap->n/bs; i++) { 1537 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]); 1538 } 1539 } 1540 if (o_nnz) { 1541 for (i=0; i<B->rmap->n/bs; i++) { 1542 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]); 1543 } 1544 } 1545 B->preallocated = PETSC_TRUE; 1546 1547 b = (Mat_MPISBAIJ*)B->data; 1548 mbs = B->rmap->n/bs; 1549 Mbs = B->rmap->N/bs; 1550 if (mbs*bs != B->rmap->n) { 1551 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs); 1552 } 1553 1554 B->rmap->bs = bs; 1555 b->bs2 = bs*bs; 1556 b->mbs = mbs; 1557 b->nbs = mbs; 1558 b->Mbs = Mbs; 1559 b->Nbs = Mbs; 1560 1561 for (i=0; i<=b->size; i++) { 1562 b->rangebs[i] = B->rmap->range[i]/bs; 1563 } 1564 b->rstartbs = B->rmap->rstart/bs; 1565 b->rendbs = B->rmap->rend/bs; 1566 1567 b->cstartbs = B->cmap->rstart/bs; 1568 b->cendbs = B->cmap->rend/bs; 1569 1570 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 1571 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 1572 ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr); 1573 ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1574 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 1575 1576 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 1577 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 1578 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 1579 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 1580 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 1581 1582 /* build cache for off array entries formed */ 1583 ierr = MatStashCreate_Private(((PetscObject)B)->comm,bs,&B->bstash);CHKERRQ(ierr); 1584 1585 PetscFunctionReturn(0); 1586 } 1587 EXTERN_C_END 1588 1589 EXTERN_C_BEGIN 1590 #if defined(PETSC_HAVE_MUMPS) 1591 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_mpisbaij_mumps(Mat,MatFactorType,Mat*); 1592 #endif 1593 #if defined(PETSC_HAVE_SPOOLES) 1594 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_mpisbaij_spooles(Mat,MatFactorType,Mat*); 1595 #endif 1596 EXTERN_C_END 1597 1598 /*MC 1599 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 1600 based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. 1601 1602 Options Database Keys: 1603 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions() 1604 1605 Level: beginner 1606 1607 .seealso: MatCreateMPISBAIJ 1608 M*/ 1609 1610 EXTERN_C_BEGIN 1611 #undef __FUNCT__ 1612 #define __FUNCT__ "MatCreate_MPISBAIJ" 1613 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPISBAIJ(Mat B) 1614 { 1615 Mat_MPISBAIJ *b; 1616 PetscErrorCode ierr; 1617 PetscTruth flg; 1618 1619 PetscFunctionBegin; 1620 1621 ierr = PetscNewLog(B,Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1622 B->data = (void*)b; 1623 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1624 1625 B->ops->destroy = MatDestroy_MPISBAIJ; 1626 B->ops->view = MatView_MPISBAIJ; 1627 B->mapping = 0; 1628 B->assembled = PETSC_FALSE; 1629 1630 B->insertmode = NOT_SET_VALUES; 1631 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 1632 ierr = MPI_Comm_size(((PetscObject)B)->comm,&b->size);CHKERRQ(ierr); 1633 1634 /* build local table of row and column ownerships */ 1635 ierr = PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr); 1636 1637 /* build cache for off array entries formed */ 1638 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 1639 b->donotstash = PETSC_FALSE; 1640 b->colmap = PETSC_NULL; 1641 b->garray = PETSC_NULL; 1642 b->roworiented = PETSC_TRUE; 1643 1644 /* stuff used in block assembly */ 1645 b->barray = 0; 1646 1647 /* stuff used for matrix vector multiply */ 1648 b->lvec = 0; 1649 b->Mvctx = 0; 1650 b->slvec0 = 0; 1651 b->slvec0b = 0; 1652 b->slvec1 = 0; 1653 b->slvec1a = 0; 1654 b->slvec1b = 0; 1655 b->sMvctx = 0; 1656 1657 /* stuff for MatGetRow() */ 1658 b->rowindices = 0; 1659 b->rowvalues = 0; 1660 b->getrowactive = PETSC_FALSE; 1661 1662 /* hash table stuff */ 1663 b->ht = 0; 1664 b->hd = 0; 1665 b->ht_size = 0; 1666 b->ht_flag = PETSC_FALSE; 1667 b->ht_fact = 0; 1668 b->ht_total_ct = 0; 1669 b->ht_insert_ct = 0; 1670 1671 b->in_loc = 0; 1672 b->v_loc = 0; 1673 b->n_loc = 0; 1674 ierr = PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr); 1675 ierr = PetscOptionsTruth("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,PETSC_NULL);CHKERRQ(ierr); 1676 if (flg) { 1677 PetscReal fact = 1.39; 1678 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 1679 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,PETSC_NULL);CHKERRQ(ierr); 1680 if (fact <= 1.0) fact = 1.39; 1681 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1682 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 1683 } 1684 ierr = PetscOptionsEnd();CHKERRQ(ierr); 1685 1686 #if defined(PETSC_HAVE_MUMPS) 1687 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_mumps_C", 1688 "MatGetFactor_mpisbaij_mumps", 1689 MatGetFactor_mpisbaij_mumps);CHKERRQ(ierr); 1690 #endif 1691 #if defined(PETSC_HAVE_SPOOLES) 1692 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpisbaij_spooles_C", 1693 "MatGetFactor_mpisbaij_spooles", 1694 MatGetFactor_mpisbaij_spooles);CHKERRQ(ierr); 1695 #endif 1696 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1697 "MatStoreValues_MPISBAIJ", 1698 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1699 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1700 "MatRetrieveValues_MPISBAIJ", 1701 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1702 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1703 "MatGetDiagonalBlock_MPISBAIJ", 1704 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1705 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPISBAIJSetPreallocation_C", 1706 "MatMPISBAIJSetPreallocation_MPISBAIJ", 1707 MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr); 1708 B->symmetric = PETSC_TRUE; 1709 B->structurally_symmetric = PETSC_TRUE; 1710 B->symmetric_set = PETSC_TRUE; 1711 B->structurally_symmetric_set = PETSC_TRUE; 1712 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr); 1713 PetscFunctionReturn(0); 1714 } 1715 EXTERN_C_END 1716 1717 /*MC 1718 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 1719 1720 This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator, 1721 and MATMPISBAIJ otherwise. 1722 1723 Options Database Keys: 1724 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions() 1725 1726 Level: beginner 1727 1728 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ 1729 M*/ 1730 1731 EXTERN_C_BEGIN 1732 #undef __FUNCT__ 1733 #define __FUNCT__ "MatCreate_SBAIJ" 1734 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SBAIJ(Mat A) 1735 { 1736 PetscErrorCode ierr; 1737 PetscMPIInt size; 1738 1739 PetscFunctionBegin; 1740 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 1741 if (size == 1) { 1742 ierr = MatSetType(A,MATSEQSBAIJ);CHKERRQ(ierr); 1743 } else { 1744 ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr); 1745 } 1746 PetscFunctionReturn(0); 1747 } 1748 EXTERN_C_END 1749 1750 #undef __FUNCT__ 1751 #define __FUNCT__ "MatMPISBAIJSetPreallocation" 1752 /*@C 1753 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1754 the user should preallocate the matrix storage by setting the parameters 1755 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1756 performance can be increased by more than a factor of 50. 1757 1758 Collective on Mat 1759 1760 Input Parameters: 1761 + A - the matrix 1762 . bs - size of blockk 1763 . d_nz - number of block nonzeros per block row in diagonal portion of local 1764 submatrix (same for all local rows) 1765 . d_nnz - array containing the number of block nonzeros in the various block rows 1766 in the upper triangular and diagonal part of the in diagonal portion of the local 1767 (possibly different for each block row) or PETSC_NULL. You must leave room 1768 for the diagonal entry even if it is zero. 1769 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1770 submatrix (same for all local rows). 1771 - o_nnz - array containing the number of nonzeros in the various block rows of the 1772 off-diagonal portion of the local submatrix (possibly different for 1773 each block row) or PETSC_NULL. 1774 1775 1776 Options Database Keys: 1777 . -mat_no_unroll - uses code that does not unroll the loops in the 1778 block calculations (much slower) 1779 . -mat_block_size - size of the blocks to use 1780 1781 Notes: 1782 1783 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1784 than it must be used on all processors that share the object for that argument. 1785 1786 If the *_nnz parameter is given then the *_nz parameter is ignored 1787 1788 Storage Information: 1789 For a square global matrix we define each processor's diagonal portion 1790 to be its local rows and the corresponding columns (a square submatrix); 1791 each processor's off-diagonal portion encompasses the remainder of the 1792 local matrix (a rectangular submatrix). 1793 1794 The user can specify preallocated storage for the diagonal part of 1795 the local submatrix with either d_nz or d_nnz (not both). Set 1796 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1797 memory allocation. Likewise, specify preallocated storage for the 1798 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1799 1800 You can call MatGetInfo() to get information on how effective the preallocation was; 1801 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1802 You can also run with the option -info and look for messages with the string 1803 malloc in them to see if additional memory allocation was needed. 1804 1805 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1806 the figure below we depict these three local rows and all columns (0-11). 1807 1808 .vb 1809 0 1 2 3 4 5 6 7 8 9 10 11 1810 ------------------- 1811 row 3 | o o o d d d o o o o o o 1812 row 4 | o o o d d d o o o o o o 1813 row 5 | o o o d d d o o o o o o 1814 ------------------- 1815 .ve 1816 1817 Thus, any entries in the d locations are stored in the d (diagonal) 1818 submatrix, and any entries in the o locations are stored in the 1819 o (off-diagonal) submatrix. Note that the d matrix is stored in 1820 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1821 1822 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1823 plus the diagonal part of the d matrix, 1824 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1825 In general, for PDE problems in which most nonzeros are near the diagonal, 1826 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1827 or you will get TERRIBLE performance; see the users' manual chapter on 1828 matrices. 1829 1830 Level: intermediate 1831 1832 .keywords: matrix, block, aij, compressed row, sparse, parallel 1833 1834 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1835 @*/ 1836 PetscErrorCode PETSCMAT_DLLEXPORT MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 1837 { 1838 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 1839 1840 PetscFunctionBegin; 1841 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 1842 if (f) { 1843 ierr = (*f)(B,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1844 } 1845 PetscFunctionReturn(0); 1846 } 1847 1848 #undef __FUNCT__ 1849 #define __FUNCT__ "MatCreateMPISBAIJ" 1850 /*@C 1851 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1852 (block compressed row). For good matrix assembly performance 1853 the user should preallocate the matrix storage by setting the parameters 1854 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1855 performance can be increased by more than a factor of 50. 1856 1857 Collective on MPI_Comm 1858 1859 Input Parameters: 1860 + comm - MPI communicator 1861 . bs - size of blockk 1862 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1863 This value should be the same as the local size used in creating the 1864 y vector for the matrix-vector product y = Ax. 1865 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1866 This value should be the same as the local size used in creating the 1867 x vector for the matrix-vector product y = Ax. 1868 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1869 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1870 . d_nz - number of block nonzeros per block row in diagonal portion of local 1871 submatrix (same for all local rows) 1872 . d_nnz - array containing the number of block nonzeros in the various block rows 1873 in the upper triangular portion of the in diagonal portion of the local 1874 (possibly different for each block block row) or PETSC_NULL. 1875 You must leave room for the diagonal entry even if it is zero. 1876 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1877 submatrix (same for all local rows). 1878 - o_nnz - array containing the number of nonzeros in the various block rows of the 1879 off-diagonal portion of the local submatrix (possibly different for 1880 each block row) or PETSC_NULL. 1881 1882 Output Parameter: 1883 . A - the matrix 1884 1885 Options Database Keys: 1886 . -mat_no_unroll - uses code that does not unroll the loops in the 1887 block calculations (much slower) 1888 . -mat_block_size - size of the blocks to use 1889 . -mat_mpi - use the parallel matrix data structures even on one processor 1890 (defaults to using SeqBAIJ format on one processor) 1891 1892 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 1893 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 1894 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 1895 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 1896 1897 Notes: 1898 The number of rows and columns must be divisible by blocksize. 1899 This matrix type does not support complex Hermitian operation. 1900 1901 The user MUST specify either the local or global matrix dimensions 1902 (possibly both). 1903 1904 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1905 than it must be used on all processors that share the object for that argument. 1906 1907 If the *_nnz parameter is given then the *_nz parameter is ignored 1908 1909 Storage Information: 1910 For a square global matrix we define each processor's diagonal portion 1911 to be its local rows and the corresponding columns (a square submatrix); 1912 each processor's off-diagonal portion encompasses the remainder of the 1913 local matrix (a rectangular submatrix). 1914 1915 The user can specify preallocated storage for the diagonal part of 1916 the local submatrix with either d_nz or d_nnz (not both). Set 1917 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1918 memory allocation. Likewise, specify preallocated storage for the 1919 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1920 1921 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1922 the figure below we depict these three local rows and all columns (0-11). 1923 1924 .vb 1925 0 1 2 3 4 5 6 7 8 9 10 11 1926 ------------------- 1927 row 3 | o o o d d d o o o o o o 1928 row 4 | o o o d d d o o o o o o 1929 row 5 | o o o d d d o o o o o o 1930 ------------------- 1931 .ve 1932 1933 Thus, any entries in the d locations are stored in the d (diagonal) 1934 submatrix, and any entries in the o locations are stored in the 1935 o (off-diagonal) submatrix. Note that the d matrix is stored in 1936 MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format. 1937 1938 Now d_nz should indicate the number of block nonzeros per row in the upper triangular 1939 plus the diagonal part of the d matrix, 1940 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1941 In general, for PDE problems in which most nonzeros are near the diagonal, 1942 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1943 or you will get TERRIBLE performance; see the users' manual chapter on 1944 matrices. 1945 1946 Level: intermediate 1947 1948 .keywords: matrix, block, aij, compressed row, sparse, parallel 1949 1950 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1951 @*/ 1952 1953 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) 1954 { 1955 PetscErrorCode ierr; 1956 PetscMPIInt size; 1957 1958 PetscFunctionBegin; 1959 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1960 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1961 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1962 if (size > 1) { 1963 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1964 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1965 } else { 1966 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1967 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1968 } 1969 PetscFunctionReturn(0); 1970 } 1971 1972 1973 #undef __FUNCT__ 1974 #define __FUNCT__ "MatDuplicate_MPISBAIJ" 1975 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1976 { 1977 Mat mat; 1978 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1979 PetscErrorCode ierr; 1980 PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs; 1981 PetscScalar *array; 1982 1983 PetscFunctionBegin; 1984 *newmat = 0; 1985 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 1986 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 1987 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 1988 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1989 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 1990 ierr = PetscMapCopy(((PetscObject)matin)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 1991 1992 mat->factor = matin->factor; 1993 mat->preallocated = PETSC_TRUE; 1994 mat->assembled = PETSC_TRUE; 1995 mat->insertmode = NOT_SET_VALUES; 1996 1997 a = (Mat_MPISBAIJ*)mat->data; 1998 a->bs2 = oldmat->bs2; 1999 a->mbs = oldmat->mbs; 2000 a->nbs = oldmat->nbs; 2001 a->Mbs = oldmat->Mbs; 2002 a->Nbs = oldmat->Nbs; 2003 2004 2005 a->size = oldmat->size; 2006 a->rank = oldmat->rank; 2007 a->donotstash = oldmat->donotstash; 2008 a->roworiented = oldmat->roworiented; 2009 a->rowindices = 0; 2010 a->rowvalues = 0; 2011 a->getrowactive = PETSC_FALSE; 2012 a->barray = 0; 2013 a->rstartbs = oldmat->rstartbs; 2014 a->rendbs = oldmat->rendbs; 2015 a->cstartbs = oldmat->cstartbs; 2016 a->cendbs = oldmat->cendbs; 2017 2018 /* hash table stuff */ 2019 a->ht = 0; 2020 a->hd = 0; 2021 a->ht_size = 0; 2022 a->ht_flag = oldmat->ht_flag; 2023 a->ht_fact = oldmat->ht_fact; 2024 a->ht_total_ct = 0; 2025 a->ht_insert_ct = 0; 2026 2027 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr); 2028 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2029 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 2030 if (oldmat->colmap) { 2031 #if defined (PETSC_USE_CTABLE) 2032 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2033 #else 2034 ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2035 ierr = PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2036 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 2037 #endif 2038 } else a->colmap = 0; 2039 2040 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 2041 ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2042 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2043 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 2044 } else a->garray = 0; 2045 2046 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2047 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2048 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2049 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2050 2051 ierr = VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr); 2052 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2053 ierr = VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr); 2054 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2055 2056 ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr); 2057 ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr); 2058 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr); 2059 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr); 2060 ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr); 2061 ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr); 2062 ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr); 2063 ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr); 2064 ierr = PetscLogObjectParent(mat,a->slvec0);CHKERRQ(ierr); 2065 ierr = PetscLogObjectParent(mat,a->slvec1);CHKERRQ(ierr); 2066 ierr = PetscLogObjectParent(mat,a->slvec0b);CHKERRQ(ierr); 2067 ierr = PetscLogObjectParent(mat,a->slvec1a);CHKERRQ(ierr); 2068 ierr = PetscLogObjectParent(mat,a->slvec1b);CHKERRQ(ierr); 2069 2070 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2071 ierr = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr); 2072 a->sMvctx = oldmat->sMvctx; 2073 ierr = PetscLogObjectParent(mat,a->sMvctx);CHKERRQ(ierr); 2074 2075 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2076 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2077 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2078 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2079 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2080 *newmat = mat; 2081 PetscFunctionReturn(0); 2082 } 2083 2084 #include "petscsys.h" 2085 2086 #undef __FUNCT__ 2087 #define __FUNCT__ "MatLoad_MPISBAIJ" 2088 PetscErrorCode MatLoad_MPISBAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2089 { 2090 Mat A; 2091 PetscErrorCode ierr; 2092 PetscInt i,nz,j,rstart,rend; 2093 PetscScalar *vals,*buf; 2094 MPI_Comm comm = ((PetscObject)viewer)->comm; 2095 MPI_Status status; 2096 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,*locrowlens,mmbs; 2097 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2098 PetscInt *procsnz = 0,jj,*mycols,*ibuf; 2099 PetscInt bs=1,Mbs,mbs,extra_rows; 2100 PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2101 PetscInt dcount,kmax,k,nzcount,tmp; 2102 int fd; 2103 2104 PetscFunctionBegin; 2105 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr); 2106 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 2107 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2108 2109 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2110 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2111 if (!rank) { 2112 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2113 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2114 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2115 if (header[3] < 0) { 2116 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2117 } 2118 } 2119 2120 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2121 M = header[1]; N = header[2]; 2122 2123 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2124 2125 /* 2126 This code adds extra rows to make sure the number of rows is 2127 divisible by the blocksize 2128 */ 2129 Mbs = M/bs; 2130 extra_rows = bs - M + bs*(Mbs); 2131 if (extra_rows == bs) extra_rows = 0; 2132 else Mbs++; 2133 if (extra_rows &&!rank) { 2134 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 2135 } 2136 2137 /* determine ownership of all rows */ 2138 mbs = Mbs/size + ((Mbs % size) > rank); 2139 m = mbs*bs; 2140 ierr = PetscMalloc(2*(size+2)*sizeof(PetscMPIInt),&rowners);CHKERRQ(ierr); 2141 browners = rowners + size + 1; 2142 mmbs = PetscMPIIntCast(mbs); 2143 ierr = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2144 rowners[0] = 0; 2145 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2146 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2147 rstart = rowners[rank]; 2148 rend = rowners[rank+1]; 2149 2150 /* distribute row lengths to all processors */ 2151 ierr = PetscMalloc((rend-rstart)*bs*sizeof(PetscMPIInt),&locrowlens);CHKERRQ(ierr); 2152 if (!rank) { 2153 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2154 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2155 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2156 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);CHKERRQ(ierr); 2157 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2158 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2159 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2160 } else { 2161 ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr); 2162 } 2163 2164 if (!rank) { /* procs[0] */ 2165 /* calculate the number of nonzeros on each processor */ 2166 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2167 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2168 for (i=0; i<size; i++) { 2169 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2170 procsnz[i] += rowlengths[j]; 2171 } 2172 } 2173 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2174 2175 /* determine max buffer needed and allocate it */ 2176 maxnz = 0; 2177 for (i=0; i<size; i++) { 2178 maxnz = PetscMax(maxnz,procsnz[i]); 2179 } 2180 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2181 2182 /* read in my part of the matrix column indices */ 2183 nz = procsnz[0]; 2184 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2185 mycols = ibuf; 2186 if (size == 1) nz -= extra_rows; 2187 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2188 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2189 2190 /* read in every ones (except the last) and ship off */ 2191 for (i=1; i<size-1; i++) { 2192 nz = procsnz[i]; 2193 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2194 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2195 } 2196 /* read in the stuff for the last proc */ 2197 if (size != 1) { 2198 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2199 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2200 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2201 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 2202 } 2203 ierr = PetscFree(cols);CHKERRQ(ierr); 2204 } else { /* procs[i], i>0 */ 2205 /* determine buffer space needed for message */ 2206 nz = 0; 2207 for (i=0; i<m; i++) { 2208 nz += locrowlens[i]; 2209 } 2210 ierr = PetscMalloc(nz*sizeof(PetscInt),&ibuf);CHKERRQ(ierr); 2211 mycols = ibuf; 2212 /* receive message of column indices*/ 2213 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2214 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2215 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2216 } 2217 2218 /* loop over local rows, determining number of off diagonal entries */ 2219 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2220 odlens = dlens + (rend-rstart); 2221 ierr = PetscMalloc(3*Mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2222 ierr = PetscMemzero(mask,3*Mbs*sizeof(PetscInt));CHKERRQ(ierr); 2223 masked1 = mask + Mbs; 2224 masked2 = masked1 + Mbs; 2225 rowcount = 0; nzcount = 0; 2226 for (i=0; i<mbs; i++) { 2227 dcount = 0; 2228 odcount = 0; 2229 for (j=0; j<bs; j++) { 2230 kmax = locrowlens[rowcount]; 2231 for (k=0; k<kmax; k++) { 2232 tmp = mycols[nzcount++]/bs; /* block col. index */ 2233 if (!mask[tmp]) { 2234 mask[tmp] = 1; 2235 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2236 else masked1[dcount++] = tmp; /* entry in diag portion */ 2237 } 2238 } 2239 rowcount++; 2240 } 2241 2242 dlens[i] = dcount; /* d_nzz[i] */ 2243 odlens[i] = odcount; /* o_nzz[i] */ 2244 2245 /* zero out the mask elements we set */ 2246 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2247 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2248 } 2249 2250 /* create our matrix */ 2251 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2252 ierr = MatSetSizes(A,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2253 ierr = MatSetType(A,type);CHKERRQ(ierr); 2254 ierr = MatMPISBAIJSetPreallocation(A,bs,0,dlens,0,odlens);CHKERRQ(ierr); 2255 2256 if (!rank) { 2257 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2258 /* read in my part of the matrix numerical values */ 2259 nz = procsnz[0]; 2260 vals = buf; 2261 mycols = ibuf; 2262 if (size == 1) nz -= extra_rows; 2263 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2264 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2265 2266 /* insert into matrix */ 2267 jj = rstart*bs; 2268 for (i=0; i<m; i++) { 2269 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2270 mycols += locrowlens[i]; 2271 vals += locrowlens[i]; 2272 jj++; 2273 } 2274 2275 /* read in other processors (except the last one) and ship out */ 2276 for (i=1; i<size-1; i++) { 2277 nz = procsnz[i]; 2278 vals = buf; 2279 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2280 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2281 } 2282 /* the last proc */ 2283 if (size != 1){ 2284 nz = procsnz[i] - extra_rows; 2285 vals = buf; 2286 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2287 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2288 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2289 } 2290 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2291 2292 } else { 2293 /* receive numeric values */ 2294 ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr); 2295 2296 /* receive message of values*/ 2297 vals = buf; 2298 mycols = ibuf; 2299 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2300 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2301 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2302 2303 /* insert into matrix */ 2304 jj = rstart*bs; 2305 for (i=0; i<m; i++) { 2306 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2307 mycols += locrowlens[i]; 2308 vals += locrowlens[i]; 2309 jj++; 2310 } 2311 } 2312 2313 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2314 ierr = PetscFree(buf);CHKERRQ(ierr); 2315 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2316 ierr = PetscFree(rowners);CHKERRQ(ierr); 2317 ierr = PetscFree(dlens);CHKERRQ(ierr); 2318 ierr = PetscFree(mask);CHKERRQ(ierr); 2319 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2320 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2321 *newmat = A; 2322 PetscFunctionReturn(0); 2323 } 2324 2325 #undef __FUNCT__ 2326 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor" 2327 /*XXXXX@ 2328 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2329 2330 Input Parameters: 2331 . mat - the matrix 2332 . fact - factor 2333 2334 Collective on Mat 2335 2336 Level: advanced 2337 2338 Notes: 2339 This can also be set by the command line option: -mat_use_hash_table fact 2340 2341 .keywords: matrix, hashtable, factor, HT 2342 2343 .seealso: MatSetOption() 2344 @XXXXX*/ 2345 2346 2347 #undef __FUNCT__ 2348 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ" 2349 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[]) 2350 { 2351 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2352 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2353 PetscReal atmp; 2354 PetscReal *work,*svalues,*rvalues; 2355 PetscErrorCode ierr; 2356 PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2357 PetscMPIInt rank,size; 2358 PetscInt *rowners_bs,dest,count,source; 2359 PetscScalar *va; 2360 MatScalar *ba; 2361 MPI_Status stat; 2362 2363 PetscFunctionBegin; 2364 if (idx) SETERRQ(PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov"); 2365 ierr = MatGetRowMaxAbs(a->A,v,PETSC_NULL);CHKERRQ(ierr); 2366 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2367 2368 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2369 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 2370 2371 bs = A->rmap->bs; 2372 mbs = a->mbs; 2373 Mbs = a->Mbs; 2374 ba = b->a; 2375 bi = b->i; 2376 bj = b->j; 2377 2378 /* find ownerships */ 2379 rowners_bs = A->rmap->range; 2380 2381 /* each proc creates an array to be distributed */ 2382 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);CHKERRQ(ierr); 2383 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2384 2385 /* row_max for B */ 2386 if (rank != size-1){ 2387 for (i=0; i<mbs; i++) { 2388 ncols = bi[1] - bi[0]; bi++; 2389 brow = bs*i; 2390 for (j=0; j<ncols; j++){ 2391 bcol = bs*(*bj); 2392 for (kcol=0; kcol<bs; kcol++){ 2393 col = bcol + kcol; /* local col index */ 2394 col += rowners_bs[rank+1]; /* global col index */ 2395 for (krow=0; krow<bs; krow++){ 2396 atmp = PetscAbsScalar(*ba); ba++; 2397 row = brow + krow; /* local row index */ 2398 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2399 if (work[col] < atmp) work[col] = atmp; 2400 } 2401 } 2402 bj++; 2403 } 2404 } 2405 2406 /* send values to its owners */ 2407 for (dest=rank+1; dest<size; dest++){ 2408 svalues = work + rowners_bs[dest]; 2409 count = rowners_bs[dest+1]-rowners_bs[dest]; 2410 ierr = MPI_Send(svalues,count,MPIU_REAL,dest,rank,((PetscObject)A)->comm);CHKERRQ(ierr); 2411 } 2412 } 2413 2414 /* receive values */ 2415 if (rank){ 2416 rvalues = work; 2417 count = rowners_bs[rank+1]-rowners_bs[rank]; 2418 for (source=0; source<rank; source++){ 2419 ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,((PetscObject)A)->comm,&stat);CHKERRQ(ierr); 2420 /* process values */ 2421 for (i=0; i<count; i++){ 2422 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2423 } 2424 } 2425 } 2426 2427 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2428 ierr = PetscFree(work);CHKERRQ(ierr); 2429 PetscFunctionReturn(0); 2430 } 2431 2432 #undef __FUNCT__ 2433 #define __FUNCT__ "MatRelax_MPISBAIJ" 2434 PetscErrorCode MatRelax_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2435 { 2436 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2437 PetscErrorCode ierr; 2438 PetscInt mbs=mat->mbs,bs=matin->rmap->bs; 2439 PetscScalar *x,*b,*ptr,zero=0.0; 2440 Vec bb1; 2441 2442 PetscFunctionBegin; 2443 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2444 if (bs > 1) 2445 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2446 2447 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2448 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2449 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2450 its--; 2451 } 2452 2453 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2454 while (its--){ 2455 2456 /* lower triangular part: slvec0b = - B^T*xx */ 2457 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr); 2458 2459 /* copy xx into slvec0a */ 2460 ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2461 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 2462 ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2463 ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr); 2464 2465 ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr); 2466 2467 /* copy bb into slvec1a */ 2468 ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2469 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 2470 ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr); 2471 ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr); 2472 2473 /* set slvec1b = 0 */ 2474 ierr = VecSet(mat->slvec1b,zero);CHKERRQ(ierr); 2475 2476 ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2477 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2478 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 2479 ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2480 2481 /* upper triangular part: bb1 = bb1 - B*x */ 2482 ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr); 2483 2484 /* local diagonal sweep */ 2485 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2486 } 2487 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2488 } else { 2489 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2490 } 2491 PetscFunctionReturn(0); 2492 } 2493 2494 #undef __FUNCT__ 2495 #define __FUNCT__ "MatRelax_MPISBAIJ_2comm" 2496 PetscErrorCode MatRelax_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2497 { 2498 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 2499 PetscErrorCode ierr; 2500 Vec lvec1,bb1; 2501 2502 PetscFunctionBegin; 2503 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 2504 if (matin->rmap->bs > 1) 2505 SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 2506 2507 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 2508 if ( flag & SOR_ZERO_INITIAL_GUESS ) { 2509 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 2510 its--; 2511 } 2512 2513 ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr); 2514 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2515 while (its--){ 2516 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2517 2518 /* lower diagonal part: bb1 = bb - B^T*xx */ 2519 ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr); 2520 ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr); 2521 2522 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2523 ierr = VecCopy(bb,bb1);CHKERRQ(ierr); 2524 ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2525 2526 /* upper diagonal part: bb1 = bb1 - B*x */ 2527 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2528 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 2529 2530 ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 2531 2532 /* diagonal sweep */ 2533 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 2534 } 2535 ierr = VecDestroy(lvec1);CHKERRQ(ierr); 2536 ierr = VecDestroy(bb1);CHKERRQ(ierr); 2537 } else { 2538 SETERRQ(PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format"); 2539 } 2540 PetscFunctionReturn(0); 2541 } 2542 2543