1 #define PETSCMAT_DLL 2 3 /* 4 Factorization code for BAIJ format. 5 */ 6 #include "../src/mat/impls/baij/seq/baij.h" 7 #include "../src/mat/blockinvert.h" 8 9 #undef __FUNCT__ 10 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2" 11 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2(Mat B,Mat A,const MatFactorInfo *info) 12 { 13 Mat C=B; 14 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data; 15 IS isrow = b->row,isicol = b->icol; 16 PetscErrorCode ierr; 17 const PetscInt *r,*ic,*ics; 18 PetscInt i,j,k,nz,nzL,row,*pj; 19 const PetscInt n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,bs2=a->bs2; 20 const PetscInt *ajtmp,*bjtmp,*bdiag=b->diag; 21 MatScalar *rtmp,*pc,*mwork,*pv; 22 MatScalar *aa=a->a,*v; 23 PetscInt flg; 24 PetscReal shift = info->shiftamount; 25 26 PetscFunctionBegin; 27 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 28 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 29 30 /* generate work space needed by the factorization */ 31 ierr = PetscMalloc2(bs2*n,MatScalar,&rtmp,bs2,MatScalar,&mwork);CHKERRQ(ierr); 32 ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr); 33 ics = ic; 34 35 for (i=0; i<n; i++){ 36 /* zero rtmp */ 37 /* L part */ 38 nz = bi[i+1] - bi[i]; 39 bjtmp = bj + bi[i]; 40 for (j=0; j<nz; j++){ 41 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 42 } 43 44 /* U part */ 45 nz = bdiag[i] - bdiag[i+1]; 46 bjtmp = bj + bdiag[i+1]+1; 47 for (j=0; j<nz; j++){ 48 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 49 } 50 51 /* load in initial (unfactored row) */ 52 nz = ai[r[i]+1] - ai[r[i]]; 53 ajtmp = aj + ai[r[i]]; 54 v = aa + bs2*ai[r[i]]; 55 for (j=0; j<nz; j++) { 56 ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr); 57 } 58 59 /* elimination */ 60 bjtmp = bj + bi[i]; 61 nzL = bi[i+1] - bi[i]; 62 for(k=0;k < nzL;k++) { 63 row = bjtmp[k]; 64 pc = rtmp + bs2*row; 65 for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=0.0) { flg = 1; break; }} 66 if (flg) { 67 pv = b->a + bs2*bdiag[row]; 68 /* Kernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */ 69 ierr = Kernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr); 70 71 pj = b->j + bdiag[row+1]+1; /* begining of U(row,:) */ 72 pv = b->a + bs2*(bdiag[row+1]+1); 73 nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */ 74 for (j=0; j<nz; j++) { 75 /* Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */ 76 /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */ 77 v = rtmp + 4*pj[j]; 78 ierr = Kernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr); 79 pv += 4; 80 } 81 ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */ 82 } 83 } 84 85 /* finished row so stick it into b->a */ 86 /* L part */ 87 pv = b->a + bs2*bi[i] ; 88 pj = b->j + bi[i] ; 89 nz = bi[i+1] - bi[i]; 90 for (j=0; j<nz; j++) { 91 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 92 } 93 94 /* Mark diagonal and invert diagonal for simplier triangular solves */ 95 pv = b->a + bs2*bdiag[i]; 96 pj = b->j + bdiag[i]; 97 ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr); 98 /* ierr = Kernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */ 99 ierr = Kernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr); 100 101 /* U part */ 102 pv = b->a + bs2*(bdiag[i+1]+1); 103 pj = b->j + bdiag[i+1]+1; 104 nz = bdiag[i] - bdiag[i+1] - 1; 105 for (j=0; j<nz; j++){ 106 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 107 } 108 } 109 110 ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr); 111 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 112 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 113 C->ops->solve = MatSolve_SeqBAIJ_2; 114 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2; 115 116 C->assembled = PETSC_TRUE; 117 ierr = PetscLogFlops(1.333333333333*2*2*2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */ 118 PetscFunctionReturn(0); 119 } 120 121 #undef __FUNCT__ 122 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering" 123 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 124 { 125 Mat C=B; 126 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data; 127 PetscErrorCode ierr; 128 PetscInt i,j,k,nz,nzL,row,*pj; 129 const PetscInt n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,bs2=a->bs2; 130 const PetscInt *ajtmp,*bjtmp,*bdiag=b->diag; 131 MatScalar *rtmp,*pc,*mwork,*pv; 132 MatScalar *aa=a->a,*v; 133 PetscInt flg; 134 PetscReal shift = info->shiftamount; 135 136 PetscFunctionBegin; 137 /* generate work space needed by the factorization */ 138 ierr = PetscMalloc2(bs2*n,MatScalar,&rtmp,bs2,MatScalar,&mwork);CHKERRQ(ierr); 139 ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr); 140 141 for (i=0; i<n; i++){ 142 /* zero rtmp */ 143 /* L part */ 144 nz = bi[i+1] - bi[i]; 145 bjtmp = bj + bi[i]; 146 for (j=0; j<nz; j++){ 147 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 148 } 149 150 /* U part */ 151 nz = bdiag[i] - bdiag[i+1]; 152 bjtmp = bj + bdiag[i+1]+1; 153 for (j=0; j<nz; j++){ 154 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 155 } 156 157 /* load in initial (unfactored row) */ 158 nz = ai[i+1] - ai[i]; 159 ajtmp = aj + ai[i]; 160 v = aa + bs2*ai[i]; 161 for (j=0; j<nz; j++) { 162 ierr = PetscMemcpy(rtmp+bs2*ajtmp[j],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr); 163 } 164 165 /* elimination */ 166 bjtmp = bj + bi[i]; 167 nzL = bi[i+1] - bi[i]; 168 for(k=0;k < nzL;k++) { 169 row = bjtmp[k]; 170 pc = rtmp + bs2*row; 171 for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=0.0) { flg = 1; break; }} 172 if (flg) { 173 pv = b->a + bs2*bdiag[row]; 174 /* Kernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */ 175 ierr = Kernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr); 176 177 pj = b->j + bdiag[row+1]+1; /* beginning of U(row,:) */ 178 pv = b->a + bs2*(bdiag[row+1]+1); 179 nz = bdiag[row]-bdiag[row+1] - 1; /* num of entries in U(row,:) excluding diag */ 180 for (j=0; j<nz; j++) { 181 /* Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */ 182 /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */ 183 v = rtmp + 4*pj[j]; 184 ierr = Kernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr); 185 pv += 4; 186 } 187 ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */ 188 } 189 } 190 191 /* finished row so stick it into b->a */ 192 /* L part */ 193 pv = b->a + bs2*bi[i] ; 194 pj = b->j + bi[i] ; 195 nz = bi[i+1] - bi[i]; 196 for (j=0; j<nz; j++) { 197 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 198 } 199 200 /* Mark diagonal and invert diagonal for simplier triangular solves */ 201 pv = b->a + bs2*bdiag[i]; 202 pj = b->j + bdiag[i]; 203 ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr); 204 /* ierr = Kernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */ 205 ierr = Kernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr); 206 207 /* U part */ 208 /* 209 pv = b->a + bs2*bi[2*n-i]; 210 pj = b->j + bi[2*n-i]; 211 nz = bi[2*n-i+1] - bi[2*n-i] - 1; 212 */ 213 pv = b->a + bs2*(bdiag[i+1]+1); 214 pj = b->j + bdiag[i+1]+1; 215 nz = bdiag[i] - bdiag[i+1] - 1; 216 for (j=0; j<nz; j++){ 217 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 218 } 219 } 220 ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr); 221 222 C->ops->solve = MatSolve_SeqBAIJ_2_NaturalOrdering; 223 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering; 224 C->assembled = PETSC_TRUE; 225 ierr = PetscLogFlops(1.333333333333*2*2*2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */ 226 PetscFunctionReturn(0); 227 } 228 229 #undef __FUNCT__ 230 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_inplace" 231 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_inplace(Mat B,Mat A,const MatFactorInfo *info) 232 { 233 Mat C = B; 234 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data; 235 IS isrow = b->row,isicol = b->icol; 236 PetscErrorCode ierr; 237 const PetscInt *r,*ic; 238 PetscInt i,j,n = a->mbs,*bi = b->i,*bj = b->j; 239 PetscInt *ajtmpold,*ajtmp,nz,row; 240 PetscInt *diag_offset=b->diag,idx,*ai=a->i,*aj=a->j,*pj; 241 MatScalar *pv,*v,*rtmp,m1,m2,m3,m4,*pc,*w,*x,x1,x2,x3,x4; 242 MatScalar p1,p2,p3,p4; 243 MatScalar *ba = b->a,*aa = a->a; 244 PetscReal shift = info->shiftamount; 245 246 PetscFunctionBegin; 247 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 248 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 249 ierr = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 250 251 for (i=0; i<n; i++) { 252 nz = bi[i+1] - bi[i]; 253 ajtmp = bj + bi[i]; 254 for (j=0; j<nz; j++) { 255 x = rtmp+4*ajtmp[j]; x[0] = x[1] = x[2] = x[3] = 0.0; 256 } 257 /* load in initial (unfactored row) */ 258 idx = r[i]; 259 nz = ai[idx+1] - ai[idx]; 260 ajtmpold = aj + ai[idx]; 261 v = aa + 4*ai[idx]; 262 for (j=0; j<nz; j++) { 263 x = rtmp+4*ic[ajtmpold[j]]; 264 x[0] = v[0]; x[1] = v[1]; x[2] = v[2]; x[3] = v[3]; 265 v += 4; 266 } 267 row = *ajtmp++; 268 while (row < i) { 269 pc = rtmp + 4*row; 270 p1 = pc[0]; p2 = pc[1]; p3 = pc[2]; p4 = pc[3]; 271 if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0) { 272 pv = ba + 4*diag_offset[row]; 273 pj = bj + diag_offset[row] + 1; 274 x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3]; 275 pc[0] = m1 = p1*x1 + p3*x2; 276 pc[1] = m2 = p2*x1 + p4*x2; 277 pc[2] = m3 = p1*x3 + p3*x4; 278 pc[3] = m4 = p2*x3 + p4*x4; 279 nz = bi[row+1] - diag_offset[row] - 1; 280 pv += 4; 281 for (j=0; j<nz; j++) { 282 x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3]; 283 x = rtmp + 4*pj[j]; 284 x[0] -= m1*x1 + m3*x2; 285 x[1] -= m2*x1 + m4*x2; 286 x[2] -= m1*x3 + m3*x4; 287 x[3] -= m2*x3 + m4*x4; 288 pv += 4; 289 } 290 ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr); 291 } 292 row = *ajtmp++; 293 } 294 /* finished row so stick it into b->a */ 295 pv = ba + 4*bi[i]; 296 pj = bj + bi[i]; 297 nz = bi[i+1] - bi[i]; 298 for (j=0; j<nz; j++) { 299 x = rtmp+4*pj[j]; 300 pv[0] = x[0]; pv[1] = x[1]; pv[2] = x[2]; pv[3] = x[3]; 301 pv += 4; 302 } 303 /* invert diagonal block */ 304 w = ba + 4*diag_offset[i]; 305 ierr = Kernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr); 306 } 307 308 ierr = PetscFree(rtmp);CHKERRQ(ierr); 309 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 310 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 311 C->ops->solve = MatSolve_SeqBAIJ_2_inplace; 312 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_inplace; 313 C->assembled = PETSC_TRUE; 314 ierr = PetscLogFlops(1.333333333333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 315 PetscFunctionReturn(0); 316 } 317 /* 318 Version for when blocks are 2 by 2 Using natural ordering 319 */ 320 #undef __FUNCT__ 321 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace" 322 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info) 323 { 324 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data; 325 PetscErrorCode ierr; 326 PetscInt i,j,n = a->mbs,*bi = b->i,*bj = b->j; 327 PetscInt *ajtmpold,*ajtmp,nz,row; 328 PetscInt *diag_offset = b->diag,*ai=a->i,*aj=a->j,*pj; 329 MatScalar *pv,*v,*rtmp,*pc,*w,*x; 330 MatScalar p1,p2,p3,p4,m1,m2,m3,m4,x1,x2,x3,x4; 331 MatScalar *ba = b->a,*aa = a->a; 332 PetscReal shift = info->shiftamount; 333 334 PetscFunctionBegin; 335 ierr = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 336 for (i=0; i<n; i++) { 337 nz = bi[i+1] - bi[i]; 338 ajtmp = bj + bi[i]; 339 for (j=0; j<nz; j++) { 340 x = rtmp+4*ajtmp[j]; 341 x[0] = x[1] = x[2] = x[3] = 0.0; 342 } 343 /* load in initial (unfactored row) */ 344 nz = ai[i+1] - ai[i]; 345 ajtmpold = aj + ai[i]; 346 v = aa + 4*ai[i]; 347 for (j=0; j<nz; j++) { 348 x = rtmp+4*ajtmpold[j]; 349 x[0] = v[0]; x[1] = v[1]; x[2] = v[2]; x[3] = v[3]; 350 v += 4; 351 } 352 row = *ajtmp++; 353 while (row < i) { 354 pc = rtmp + 4*row; 355 p1 = pc[0]; p2 = pc[1]; p3 = pc[2]; p4 = pc[3]; 356 if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0) { 357 pv = ba + 4*diag_offset[row]; 358 pj = bj + diag_offset[row] + 1; 359 x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3]; 360 pc[0] = m1 = p1*x1 + p3*x2; 361 pc[1] = m2 = p2*x1 + p4*x2; 362 pc[2] = m3 = p1*x3 + p3*x4; 363 pc[3] = m4 = p2*x3 + p4*x4; 364 nz = bi[row+1] - diag_offset[row] - 1; 365 pv += 4; 366 for (j=0; j<nz; j++) { 367 x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3]; 368 x = rtmp + 4*pj[j]; 369 x[0] -= m1*x1 + m3*x2; 370 x[1] -= m2*x1 + m4*x2; 371 x[2] -= m1*x3 + m3*x4; 372 x[3] -= m2*x3 + m4*x4; 373 pv += 4; 374 } 375 ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr); 376 } 377 row = *ajtmp++; 378 } 379 /* finished row so stick it into b->a */ 380 pv = ba + 4*bi[i]; 381 pj = bj + bi[i]; 382 nz = bi[i+1] - bi[i]; 383 for (j=0; j<nz; j++) { 384 x = rtmp+4*pj[j]; 385 pv[0] = x[0]; pv[1] = x[1]; pv[2] = x[2]; pv[3] = x[3]; 386 /* 387 printf(" col %d:",pj[j]); 388 PetscInt j1; 389 for (j1=0; j1<4; j1++) printf(" %g,",*(pv+j1)); 390 printf("\n"); 391 */ 392 pv += 4; 393 } 394 /* invert diagonal block */ 395 w = ba + 4*diag_offset[i]; 396 /* 397 printf(" \n%d -th: diag: ",i); 398 for (j=0; j<4; j++){ 399 printf(" %g,",w[j]); 400 } 401 printf("\n----------------------------\n"); 402 */ 403 ierr = Kernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr); 404 } 405 406 ierr = PetscFree(rtmp);CHKERRQ(ierr); 407 C->ops->solve = MatSolve_SeqBAIJ_2_NaturalOrdering_inplace; 408 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering_inplace; 409 C->assembled = PETSC_TRUE; 410 ierr = PetscLogFlops(1.333333333333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 411 PetscFunctionReturn(0); 412 } 413 414 /* ----------------------------------------------------------- */ 415 /* 416 Version for when blocks are 1 by 1. 417 */ 418 #undef __FUNCT__ 419 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_1_inplace" 420 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info) 421 { 422 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data; 423 IS isrow = b->row,isicol = b->icol; 424 PetscErrorCode ierr; 425 const PetscInt *r,*ic; 426 PetscInt i,j,n = a->mbs,*bi = b->i,*bj = b->j; 427 PetscInt *ajtmpold,*ajtmp,nz,row,*ai = a->i,*aj = a->j; 428 PetscInt *diag_offset = b->diag,diag,*pj; 429 MatScalar *pv,*v,*rtmp,multiplier,*pc; 430 MatScalar *ba = b->a,*aa = a->a; 431 PetscTruth row_identity, col_identity; 432 433 PetscFunctionBegin; 434 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 435 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 436 ierr = PetscMalloc((n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 437 438 for (i=0; i<n; i++) { 439 nz = bi[i+1] - bi[i]; 440 ajtmp = bj + bi[i]; 441 for (j=0; j<nz; j++) rtmp[ajtmp[j]] = 0.0; 442 443 /* load in initial (unfactored row) */ 444 nz = ai[r[i]+1] - ai[r[i]]; 445 ajtmpold = aj + ai[r[i]]; 446 v = aa + ai[r[i]]; 447 for (j=0; j<nz; j++) rtmp[ic[ajtmpold[j]]] = v[j]; 448 449 row = *ajtmp++; 450 while (row < i) { 451 pc = rtmp + row; 452 if (*pc != 0.0) { 453 pv = ba + diag_offset[row]; 454 pj = bj + diag_offset[row] + 1; 455 multiplier = *pc * *pv++; 456 *pc = multiplier; 457 nz = bi[row+1] - diag_offset[row] - 1; 458 for (j=0; j<nz; j++) rtmp[pj[j]] -= multiplier * pv[j]; 459 ierr = PetscLogFlops(1.0+2.0*nz);CHKERRQ(ierr); 460 } 461 row = *ajtmp++; 462 } 463 /* finished row so stick it into b->a */ 464 pv = ba + bi[i]; 465 pj = bj + bi[i]; 466 nz = bi[i+1] - bi[i]; 467 for (j=0; j<nz; j++) {pv[j] = rtmp[pj[j]];} 468 diag = diag_offset[i] - bi[i]; 469 /* check pivot entry for current row */ 470 if (pv[diag] == 0.0) { 471 SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot: row in original ordering %D in permuted ordering %D",r[i],i); 472 } 473 pv[diag] = 1.0/pv[diag]; 474 } 475 476 ierr = PetscFree(rtmp);CHKERRQ(ierr); 477 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 478 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 479 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 480 ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr); 481 if (row_identity && col_identity) { 482 C->ops->solve = MatSolve_SeqBAIJ_1_NaturalOrdering_inplace; 483 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_NaturalOrdering_inplace; 484 } else { 485 C->ops->solve = MatSolve_SeqBAIJ_1_inplace; 486 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_inplace; 487 } 488 C->assembled = PETSC_TRUE; 489 ierr = PetscLogFlops(C->cmap->n);CHKERRQ(ierr); 490 PetscFunctionReturn(0); 491 } 492 493 EXTERN_C_BEGIN 494 #undef __FUNCT__ 495 #define __FUNCT__ "MatGetFactor_seqbaij_petsc" 496 PetscErrorCode MatGetFactor_seqbaij_petsc(Mat A,MatFactorType ftype,Mat *B) 497 { 498 PetscInt n = A->rmap->n; 499 PetscErrorCode ierr; 500 501 PetscFunctionBegin; 502 ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr); 503 ierr = MatSetSizes(*B,n,n,n,n);CHKERRQ(ierr); 504 if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU || ftype == MAT_FACTOR_ILUDT) { 505 ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr); 506 (*B)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqBAIJ; 507 (*B)->ops->ilufactorsymbolic = MatILUFactorSymbolic_SeqBAIJ; 508 } else if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) { 509 ierr = MatSetType(*B,MATSEQSBAIJ);CHKERRQ(ierr); 510 ierr = MatSeqSBAIJSetPreallocation(*B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 511 (*B)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqBAIJ; 512 (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqBAIJ; 513 } else SETERRQ(PETSC_ERR_SUP,"Factor type not supported"); 514 (*B)->factor = ftype; 515 PetscFunctionReturn(0); 516 } 517 EXTERN_C_END 518 519 EXTERN_C_BEGIN 520 #undef __FUNCT__ 521 #define __FUNCT__ "MatGetFactorAvailable_seqaij_petsc" 522 PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat A,MatFactorType ftype,PetscTruth *flg) 523 { 524 PetscFunctionBegin; 525 *flg = PETSC_TRUE; 526 PetscFunctionReturn(0); 527 } 528 EXTERN_C_END 529 530 /* ----------------------------------------------------------- */ 531 #undef __FUNCT__ 532 #define __FUNCT__ "MatLUFactor_SeqBAIJ" 533 PetscErrorCode MatLUFactor_SeqBAIJ(Mat A,IS row,IS col,const MatFactorInfo *info) 534 { 535 PetscErrorCode ierr; 536 Mat C; 537 538 PetscFunctionBegin; 539 ierr = MatGetFactor(A,MAT_SOLVER_PETSC,MAT_FACTOR_LU,&C);CHKERRQ(ierr); 540 ierr = MatLUFactorSymbolic(C,A,row,col,info);CHKERRQ(ierr); 541 ierr = MatLUFactorNumeric(C,A,info);CHKERRQ(ierr); 542 A->ops->solve = C->ops->solve; 543 A->ops->solvetranspose = C->ops->solvetranspose; 544 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 545 ierr = PetscLogObjectParent(A,((Mat_SeqBAIJ*)(A->data))->icol);CHKERRQ(ierr); 546 PetscFunctionReturn(0); 547 } 548 549 #include "../src/mat/impls/sbaij/seq/sbaij.h" 550 #undef __FUNCT__ 551 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N" 552 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N(Mat C,Mat A,const MatFactorInfo *info) 553 { 554 PetscErrorCode ierr; 555 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 556 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)C->data; 557 IS ip=b->row; 558 const PetscInt *rip; 559 PetscInt i,j,mbs=a->mbs,bs=A->rmap->bs,*bi=b->i,*bj=b->j,*bcol; 560 PetscInt *ai=a->i,*aj=a->j; 561 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 562 MatScalar *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi; 563 PetscReal zeropivot,rs; 564 ChShift_Ctx sctx; 565 PetscInt newshift; 566 567 PetscFunctionBegin; 568 if (bs > 1) { 569 if (!a->sbaijMat){ 570 ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr); 571 } 572 ierr = (a->sbaijMat)->ops->choleskyfactornumeric(C,a->sbaijMat,info);CHKERRQ(ierr); 573 ierr = MatDestroy(a->sbaijMat);CHKERRQ(ierr); 574 a->sbaijMat = PETSC_NULL; 575 PetscFunctionReturn(0); 576 } 577 578 /* initialization */ 579 zeropivot = info->zeropivot; 580 581 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 582 ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 583 584 sctx.shift_amount = 0.; 585 sctx.nshift = 0; 586 do { 587 sctx.chshift = PETSC_FALSE; 588 for (i=0; i<mbs; i++) { 589 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 590 } 591 592 for (k = 0; k<mbs; k++){ 593 bval = ba + bi[k]; 594 /* initialize k-th row by the perm[k]-th row of A */ 595 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 596 for (j = jmin; j < jmax; j++){ 597 col = rip[aj[j]]; 598 if (col >= k){ /* only take upper triangular entry */ 599 rtmp[col] = aa[j]; 600 *bval++ = 0.0; /* for in-place factorization */ 601 } 602 } 603 604 /* shift the diagonal of the matrix */ 605 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 606 607 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 608 dk = rtmp[k]; 609 i = jl[k]; /* first row to be added to k_th row */ 610 611 while (i < k){ 612 nexti = jl[i]; /* next row to be added to k_th row */ 613 614 /* compute multiplier, update diag(k) and U(i,k) */ 615 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 616 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 617 dk += uikdi*ba[ili]; 618 ba[ili] = uikdi; /* -U(i,k) */ 619 620 /* add multiple of row i to k-th row */ 621 jmin = ili + 1; jmax = bi[i+1]; 622 if (jmin < jmax){ 623 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 624 /* update il and jl for row i */ 625 il[i] = jmin; 626 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 627 } 628 i = nexti; 629 } 630 631 /* shift the diagonals when zero pivot is detected */ 632 /* compute rs=sum of abs(off-diagonal) */ 633 rs = 0.0; 634 jmin = bi[k]+1; 635 nz = bi[k+1] - jmin; 636 if (nz){ 637 bcol = bj + jmin; 638 while (nz--){ 639 rs += PetscAbsScalar(rtmp[*bcol]); 640 bcol++; 641 } 642 } 643 644 sctx.rs = rs; 645 sctx.pv = dk; 646 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 647 if (newshift == 1) break; 648 649 /* copy data into U(k,:) */ 650 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 651 jmin = bi[k]+1; jmax = bi[k+1]; 652 if (jmin < jmax) { 653 for (j=jmin; j<jmax; j++){ 654 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 655 } 656 /* add the k-th row into il and jl */ 657 il[k] = jmin; 658 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 659 } 660 } 661 } while (sctx.chshift); 662 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 663 664 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 665 C->assembled = PETSC_TRUE; 666 C->preallocated = PETSC_TRUE; 667 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 668 if (sctx.nshift){ 669 if (info->shifttype == MAT_SHIFT_POSITIVE_DEFINITE) { 670 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 671 } else if (info->shifttype == MAT_SHIFT_NONZERO) { 672 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 673 } 674 } 675 PetscFunctionReturn(0); 676 } 677 678 #undef __FUNCT__ 679 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering" 680 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 681 { 682 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 683 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)C->data; 684 PetscErrorCode ierr; 685 PetscInt i,j,am=a->mbs; 686 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 687 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 688 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 689 PetscReal zeropivot,rs; 690 ChShift_Ctx sctx; 691 PetscInt newshift; 692 693 PetscFunctionBegin; 694 /* initialization */ 695 zeropivot = info->zeropivot; 696 697 ierr = PetscMalloc3(am,MatScalar,&rtmp,am,PetscInt,&il,am,PetscInt,&jl);CHKERRQ(ierr); 698 699 sctx.shift_amount = 0.; 700 sctx.nshift = 0; 701 do { 702 sctx.chshift = PETSC_FALSE; 703 for (i=0; i<am; i++) { 704 rtmp[i] = 0.0; jl[i] = am; il[0] = 0; 705 } 706 707 for (k = 0; k<am; k++){ 708 /* initialize k-th row with elements nonzero in row perm(k) of A */ 709 nz = ai[k+1] - ai[k]; 710 acol = aj + ai[k]; 711 aval = aa + ai[k]; 712 bval = ba + bi[k]; 713 while (nz -- ){ 714 if (*acol < k) { /* skip lower triangular entries */ 715 acol++; aval++; 716 } else { 717 rtmp[*acol++] = *aval++; 718 *bval++ = 0.0; /* for in-place factorization */ 719 } 720 } 721 722 /* shift the diagonal of the matrix */ 723 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 724 725 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 726 dk = rtmp[k]; 727 i = jl[k]; /* first row to be added to k_th row */ 728 729 while (i < k){ 730 nexti = jl[i]; /* next row to be added to k_th row */ 731 /* compute multiplier, update D(k) and U(i,k) */ 732 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 733 uikdi = - ba[ili]*ba[bi[i]]; 734 dk += uikdi*ba[ili]; 735 ba[ili] = uikdi; /* -U(i,k) */ 736 737 /* add multiple of row i to k-th row ... */ 738 jmin = ili + 1; 739 nz = bi[i+1] - jmin; 740 if (nz > 0){ 741 bcol = bj + jmin; 742 bval = ba + jmin; 743 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 744 /* update il and jl for i-th row */ 745 il[i] = jmin; 746 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 747 } 748 i = nexti; 749 } 750 751 /* shift the diagonals when zero pivot is detected */ 752 /* compute rs=sum of abs(off-diagonal) */ 753 rs = 0.0; 754 jmin = bi[k]+1; 755 nz = bi[k+1] - jmin; 756 if (nz){ 757 bcol = bj + jmin; 758 while (nz--){ 759 rs += PetscAbsScalar(rtmp[*bcol]); 760 bcol++; 761 } 762 } 763 764 sctx.rs = rs; 765 sctx.pv = dk; 766 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 767 if (newshift == 1) break; /* sctx.shift_amount is updated */ 768 769 /* copy data into U(k,:) */ 770 ba[bi[k]] = 1.0/dk; 771 jmin = bi[k]+1; 772 nz = bi[k+1] - jmin; 773 if (nz){ 774 bcol = bj + jmin; 775 bval = ba + jmin; 776 while (nz--){ 777 *bval++ = rtmp[*bcol]; 778 rtmp[*bcol++] = 0.0; 779 } 780 /* add k-th row into il and jl */ 781 il[k] = jmin; 782 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 783 } 784 } 785 } while (sctx.chshift); 786 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 787 788 C->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 789 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 790 C->assembled = PETSC_TRUE; 791 C->preallocated = PETSC_TRUE; 792 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 793 if (sctx.nshift){ 794 if (info->shifttype == MAT_SHIFT_NONZERO) { 795 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 796 } else if (info->shifttype == MAT_SHIFT_POSITIVE_DEFINITE) { 797 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 798 } 799 } 800 PetscFunctionReturn(0); 801 } 802 803 #include "petscbt.h" 804 #include "../src/mat/utils/freespace.h" 805 #undef __FUNCT__ 806 #define __FUNCT__ "MatICCFactorSymbolic_SeqBAIJ" 807 PetscErrorCode MatICCFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info) 808 { 809 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 810 Mat_SeqSBAIJ *b; 811 Mat B; 812 PetscErrorCode ierr; 813 PetscTruth perm_identity; 814 PetscInt reallocs=0,i,*ai=a->i,*aj=a->j,am=a->mbs,bs=A->rmap->bs,*ui; 815 const PetscInt *rip; 816 PetscInt jmin,jmax,nzk,k,j,*jl,prow,*il,nextprow; 817 PetscInt nlnk,*lnk,*lnk_lvl=PETSC_NULL,ncols,ncols_upper,*cols,*cols_lvl,*uj,**uj_ptr,**uj_lvl_ptr; 818 PetscReal fill=info->fill,levels=info->levels; 819 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 820 PetscFreeSpaceList free_space_lvl=PETSC_NULL,current_space_lvl=PETSC_NULL; 821 PetscBT lnkbt; 822 823 PetscFunctionBegin; 824 if (bs > 1){ 825 if (!a->sbaijMat){ 826 ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr); 827 } 828 (fact)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ; /* undue the change made in MatGetFactor_seqbaij_petsc */ 829 ierr = MatICCFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr); 830 PetscFunctionReturn(0); 831 } 832 833 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 834 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 835 836 /* special case that simply copies fill pattern */ 837 if (!levels && perm_identity) { 838 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 839 ierr = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 840 for (i=0; i<am; i++) { 841 ui[i] = ai[i+1] - a->diag[i]; /* ui: rowlengths - changes when !perm_identity */ 842 } 843 B = fact; 844 ierr = MatSeqSBAIJSetPreallocation(B,1,0,ui);CHKERRQ(ierr); 845 846 847 b = (Mat_SeqSBAIJ*)B->data; 848 uj = b->j; 849 for (i=0; i<am; i++) { 850 aj = a->j + a->diag[i]; 851 for (j=0; j<ui[i]; j++){ 852 *uj++ = *aj++; 853 } 854 b->ilen[i] = ui[i]; 855 } 856 ierr = PetscFree(ui);CHKERRQ(ierr); 857 B->factor = MAT_FACTOR_NONE; 858 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 859 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 860 B->factor = MAT_FACTOR_ICC; 861 862 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering; 863 PetscFunctionReturn(0); 864 } 865 866 /* initialization */ 867 ierr = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 868 ui[0] = 0; 869 ierr = PetscMalloc((2*am+1)*sizeof(PetscInt),&cols_lvl);CHKERRQ(ierr); 870 871 /* jl: linked list for storing indices of the pivot rows 872 il: il[i] points to the 1st nonzero entry of U(i,k:am-1) */ 873 ierr = PetscMalloc4(am,PetscInt*,&uj_ptr,am,PetscInt*,&uj_lvl_ptr,am,PetscInt,&il,am,PetscInt,&jl);CHKERRQ(ierr); 874 for (i=0; i<am; i++){ 875 jl[i] = am; il[i] = 0; 876 } 877 878 /* create and initialize a linked list for storing column indices of the active row k */ 879 nlnk = am + 1; 880 ierr = PetscIncompleteLLCreate(am,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 881 882 /* initial FreeSpace size is fill*(ai[am]+1) */ 883 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+1)),&free_space);CHKERRQ(ierr); 884 current_space = free_space; 885 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+1)),&free_space_lvl);CHKERRQ(ierr); 886 current_space_lvl = free_space_lvl; 887 888 for (k=0; k<am; k++){ /* for each active row k */ 889 /* initialize lnk by the column indices of row rip[k] of A */ 890 nzk = 0; 891 ncols = ai[rip[k]+1] - ai[rip[k]]; 892 ncols_upper = 0; 893 cols = cols_lvl + am; 894 for (j=0; j<ncols; j++){ 895 i = rip[*(aj + ai[rip[k]] + j)]; 896 if (i >= k){ /* only take upper triangular entry */ 897 cols[ncols_upper] = i; 898 cols_lvl[ncols_upper] = -1; /* initialize level for nonzero entries */ 899 ncols_upper++; 900 } 901 } 902 ierr = PetscIncompleteLLAdd(ncols_upper,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 903 nzk += nlnk; 904 905 /* update lnk by computing fill-in for each pivot row to be merged in */ 906 prow = jl[k]; /* 1st pivot row */ 907 908 while (prow < k){ 909 nextprow = jl[prow]; 910 911 /* merge prow into k-th row */ 912 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:am-1) */ 913 jmax = ui[prow+1]; 914 ncols = jmax-jmin; 915 i = jmin - ui[prow]; 916 cols = uj_ptr[prow] + i; /* points to the 2nd nzero entry in U(prow,k:am-1) */ 917 for (j=0; j<ncols; j++) cols_lvl[j] = *(uj_lvl_ptr[prow] + i + j); 918 ierr = PetscIncompleteLLAddSorted(ncols,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 919 nzk += nlnk; 920 921 /* update il and jl for prow */ 922 if (jmin < jmax){ 923 il[prow] = jmin; 924 j = *cols; jl[prow] = jl[j]; jl[j] = prow; 925 } 926 prow = nextprow; 927 } 928 929 /* if free space is not available, make more free space */ 930 if (current_space->local_remaining<nzk) { 931 i = am - k + 1; /* num of unfactored rows */ 932 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 933 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 934 ierr = PetscFreeSpaceGet(i,¤t_space_lvl);CHKERRQ(ierr); 935 reallocs++; 936 } 937 938 /* copy data into free_space and free_space_lvl, then initialize lnk */ 939 ierr = PetscIncompleteLLClean(am,am,nzk,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr); 940 941 /* add the k-th row into il and jl */ 942 if (nzk-1 > 0){ 943 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:am-1) */ 944 jl[k] = jl[i]; jl[i] = k; 945 il[k] = ui[k] + 1; 946 } 947 uj_ptr[k] = current_space->array; 948 uj_lvl_ptr[k] = current_space_lvl->array; 949 950 current_space->array += nzk; 951 current_space->local_used += nzk; 952 current_space->local_remaining -= nzk; 953 954 current_space_lvl->array += nzk; 955 current_space_lvl->local_used += nzk; 956 current_space_lvl->local_remaining -= nzk; 957 958 ui[k+1] = ui[k] + nzk; 959 } 960 961 #if defined(PETSC_USE_INFO) 962 if (ai[am] != 0) { 963 PetscReal af = ((PetscReal)(2*ui[am]-am))/((PetscReal)ai[am]); 964 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 965 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 966 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 967 } else { 968 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 969 } 970 #endif 971 972 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 973 ierr = PetscFree4(uj_ptr,uj_lvl_ptr,il,jl);CHKERRQ(ierr); 974 ierr = PetscFree(cols_lvl);CHKERRQ(ierr); 975 976 /* destroy list of free space and other temporary array(s) */ 977 ierr = PetscMalloc((ui[am]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 978 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 979 ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 980 ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr); 981 982 /* put together the new matrix in MATSEQSBAIJ format */ 983 B = fact; 984 ierr = MatSeqSBAIJSetPreallocation(B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 985 986 b = (Mat_SeqSBAIJ*)B->data; 987 b->singlemalloc = PETSC_FALSE; 988 b->free_a = PETSC_TRUE; 989 b->free_ij = PETSC_TRUE; 990 ierr = PetscMalloc((ui[am]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 991 b->j = uj; 992 b->i = ui; 993 b->diag = 0; 994 b->ilen = 0; 995 b->imax = 0; 996 b->row = perm; 997 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 998 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 999 b->icol = perm; 1000 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 1001 ierr = PetscMalloc((am+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 1002 ierr = PetscLogObjectMemory(B,(ui[am]-am)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 1003 b->maxnz = b->nz = ui[am]; 1004 1005 B->info.factor_mallocs = reallocs; 1006 B->info.fill_ratio_given = fill; 1007 if (ai[am] != 0.) { 1008 B->info.fill_ratio_needed = ((PetscReal)ui[am])/((PetscReal)ai[am]); 1009 } else { 1010 B->info.fill_ratio_needed = 0.0; 1011 } 1012 if (perm_identity){ 1013 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1014 B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1015 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering; 1016 } else { 1017 (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N; 1018 } 1019 PetscFunctionReturn(0); 1020 } 1021 1022 #undef __FUNCT__ 1023 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqBAIJ" 1024 PetscErrorCode MatCholeskyFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info) 1025 { 1026 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1027 Mat_SeqSBAIJ *b; 1028 Mat B; 1029 PetscErrorCode ierr; 1030 PetscTruth perm_identity; 1031 PetscReal fill = info->fill; 1032 const PetscInt *rip; 1033 PetscInt i,mbs=a->mbs,bs=A->rmap->bs,*ai=a->i,*aj=a->j,reallocs=0,prow; 1034 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 1035 PetscInt nlnk,*lnk,ncols,ncols_upper,*cols,*uj,**ui_ptr,*uj_ptr; 1036 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 1037 PetscBT lnkbt; 1038 1039 PetscFunctionBegin; 1040 if (bs > 1) { /* convert to seqsbaij */ 1041 if (!a->sbaijMat){ 1042 ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr); 1043 } 1044 (fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ; /* undue the change made in MatGetFactor_seqbaij_petsc */ 1045 ierr = MatCholeskyFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr); 1046 PetscFunctionReturn(0); 1047 } 1048 1049 /* check whether perm is the identity mapping */ 1050 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 1051 if (!perm_identity) SETERRQ(PETSC_ERR_SUP,"Matrix reordering is not supported"); 1052 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 1053 1054 /* initialization */ 1055 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 1056 ui[0] = 0; 1057 1058 /* jl: linked list for storing indices of the pivot rows 1059 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 1060 ierr = PetscMalloc4(mbs,PetscInt*,&ui_ptr,mbs,PetscInt,&il,mbs,PetscInt,&jl,mbs,PetscInt,&cols);CHKERRQ(ierr); 1061 for (i=0; i<mbs; i++){ 1062 jl[i] = mbs; il[i] = 0; 1063 } 1064 1065 /* create and initialize a linked list for storing column indices of the active row k */ 1066 nlnk = mbs + 1; 1067 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 1068 1069 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 1070 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 1071 current_space = free_space; 1072 1073 for (k=0; k<mbs; k++){ /* for each active row k */ 1074 /* initialize lnk by the column indices of row rip[k] of A */ 1075 nzk = 0; 1076 ncols = ai[rip[k]+1] - ai[rip[k]]; 1077 ncols_upper = 0; 1078 for (j=0; j<ncols; j++){ 1079 i = rip[*(aj + ai[rip[k]] + j)]; 1080 if (i >= k){ /* only take upper triangular entry */ 1081 cols[ncols_upper] = i; 1082 ncols_upper++; 1083 } 1084 } 1085 ierr = PetscLLAdd(ncols_upper,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 1086 nzk += nlnk; 1087 1088 /* update lnk by computing fill-in for each pivot row to be merged in */ 1089 prow = jl[k]; /* 1st pivot row */ 1090 1091 while (prow < k){ 1092 nextprow = jl[prow]; 1093 /* merge prow into k-th row */ 1094 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 1095 jmax = ui[prow+1]; 1096 ncols = jmax-jmin; 1097 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 1098 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 1099 nzk += nlnk; 1100 1101 /* update il and jl for prow */ 1102 if (jmin < jmax){ 1103 il[prow] = jmin; 1104 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 1105 } 1106 prow = nextprow; 1107 } 1108 1109 /* if free space is not available, make more free space */ 1110 if (current_space->local_remaining<nzk) { 1111 i = mbs - k + 1; /* num of unfactored rows */ 1112 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 1113 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 1114 reallocs++; 1115 } 1116 1117 /* copy data into free space, then initialize lnk */ 1118 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 1119 1120 /* add the k-th row into il and jl */ 1121 if (nzk-1 > 0){ 1122 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 1123 jl[k] = jl[i]; jl[i] = k; 1124 il[k] = ui[k] + 1; 1125 } 1126 ui_ptr[k] = current_space->array; 1127 current_space->array += nzk; 1128 current_space->local_used += nzk; 1129 current_space->local_remaining -= nzk; 1130 1131 ui[k+1] = ui[k] + nzk; 1132 } 1133 1134 #if defined(PETSC_USE_INFO) 1135 if (ai[mbs] != 0.) { 1136 PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 1137 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 1138 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 1139 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 1140 } else { 1141 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 1142 } 1143 #endif 1144 1145 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 1146 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 1147 1148 /* destroy list of free space and other temporary array(s) */ 1149 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 1150 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 1151 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 1152 1153 /* put together the new matrix in MATSEQSBAIJ format */ 1154 B = fact; 1155 ierr = MatSeqSBAIJSetPreallocation(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 1156 1157 b = (Mat_SeqSBAIJ*)B->data; 1158 b->singlemalloc = PETSC_FALSE; 1159 b->free_a = PETSC_TRUE; 1160 b->free_ij = PETSC_TRUE; 1161 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 1162 b->j = uj; 1163 b->i = ui; 1164 b->diag = 0; 1165 b->ilen = 0; 1166 b->imax = 0; 1167 b->row = perm; 1168 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 1169 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 1170 b->icol = perm; 1171 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 1172 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 1173 ierr = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 1174 b->maxnz = b->nz = ui[mbs]; 1175 1176 B->info.factor_mallocs = reallocs; 1177 B->info.fill_ratio_given = fill; 1178 if (ai[mbs] != 0.) { 1179 B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 1180 } else { 1181 B->info.fill_ratio_needed = 0.0; 1182 } 1183 if (perm_identity){ 1184 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering; 1185 } else { 1186 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N; 1187 } 1188 PetscFunctionReturn(0); 1189 } 1190 1191 #undef __FUNCT__ 1192 #define __FUNCT__ "MatSolve_SeqBAIJ_N_NaturalOrdering" 1193 PetscErrorCode MatSolve_SeqBAIJ_N_NaturalOrdering(Mat A,Vec bb,Vec xx) 1194 { 1195 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data; 1196 PetscErrorCode ierr; 1197 const PetscInt *ai=a->i,*aj=a->j,*adiag=a->diag,*vi; 1198 PetscInt i,k,n=a->mbs; 1199 PetscInt nz,bs=A->rmap->bs,bs2=a->bs2; 1200 MatScalar *aa=a->a,*v; 1201 PetscScalar *x,*b,*s,*t,*ls; 1202 1203 PetscFunctionBegin; 1204 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 1205 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1206 t = a->solve_work; 1207 1208 /* forward solve the lower triangular */ 1209 ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy 1st block of b to t */ 1210 1211 for (i=1; i<n; i++) { 1212 v = aa + bs2*ai[i]; 1213 vi = aj + ai[i]; 1214 nz = ai[i+1] - ai[i]; 1215 s = t + bs*i; 1216 ierr = PetscMemcpy(s,b+bs*i,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy i_th block of b to t */ 1217 for(k=0;k<nz;k++){ 1218 Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[k]); 1219 v += bs2; 1220 } 1221 } 1222 1223 /* backward solve the upper triangular */ 1224 ls = a->solve_work + A->cmap->n; 1225 for (i=n-1; i>=0; i--){ 1226 v = aa + bs2*(adiag[i+1]+1); 1227 vi = aj + adiag[i+1]+1; 1228 nz = adiag[i] - adiag[i+1]-1; 1229 ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr); 1230 for(k=0;k<nz;k++){ 1231 Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[k]); 1232 v += bs2; 1233 } 1234 Kernel_w_gets_A_times_v(bs,ls,aa+bs2*adiag[i],t+i*bs); /* *inv(diagonal[i]) */ 1235 ierr = PetscMemcpy(x+i*bs,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr); 1236 } 1237 1238 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 1239 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1240 ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr); 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatSolve_SeqBAIJ_N" 1246 PetscErrorCode MatSolve_SeqBAIJ_N(Mat A,Vec bb,Vec xx) 1247 { 1248 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data; 1249 IS iscol=a->col,isrow=a->row; 1250 PetscErrorCode ierr; 1251 const PetscInt *r,*c,*rout,*cout,*ai=a->i,*aj=a->j,*adiag=a->diag,*vi; 1252 PetscInt i,m,n=a->mbs; 1253 PetscInt nz,bs=A->rmap->bs,bs2=a->bs2; 1254 MatScalar *aa=a->a,*v; 1255 PetscScalar *x,*b,*s,*t,*ls; 1256 1257 PetscFunctionBegin; 1258 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 1259 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1260 t = a->solve_work; 1261 1262 ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout; 1263 ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout; 1264 1265 /* forward solve the lower triangular */ 1266 ierr = PetscMemcpy(t,b+bs*r[0],bs*sizeof(PetscScalar));CHKERRQ(ierr); 1267 for (i=1; i<n; i++) { 1268 v = aa + bs2*ai[i]; 1269 vi = aj + ai[i]; 1270 nz = ai[i+1] - ai[i]; 1271 s = t + bs*i; 1272 ierr = PetscMemcpy(s,b+bs*r[i],bs*sizeof(PetscScalar));CHKERRQ(ierr); 1273 for(m=0;m<nz;m++){ 1274 Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[m]); 1275 v += bs2; 1276 } 1277 } 1278 1279 /* backward solve the upper triangular */ 1280 ls = a->solve_work + A->cmap->n; 1281 for (i=n-1; i>=0; i--){ 1282 v = aa + bs2*(adiag[i+1]+1); 1283 vi = aj + adiag[i+1]+1; 1284 nz = adiag[i] - adiag[i+1] - 1; 1285 ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr); 1286 for(m=0;m<nz;m++){ 1287 Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[m]); 1288 v += bs2; 1289 } 1290 Kernel_w_gets_A_times_v(bs,ls,v,t+i*bs); /* *inv(diagonal[i]) */ 1291 ierr = PetscMemcpy(x + bs*c[i],t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr); 1292 } 1293 ierr = ISRestoreIndices(isrow,&rout);CHKERRQ(ierr); 1294 ierr = ISRestoreIndices(iscol,&cout);CHKERRQ(ierr); 1295 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 1296 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1297 ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr); 1298 PetscFunctionReturn(0); 1299 } 1300 1301 #undef __FUNCT__ 1302 #define __FUNCT__ "BlockAbs_privat" 1303 PetscErrorCode BlockAbs_private(PetscInt nbs,PetscInt bs2,PetscScalar *blockarray,PetscReal *absarray) 1304 { 1305 PetscErrorCode ierr; 1306 PetscInt i,j; 1307 PetscFunctionBegin; 1308 ierr = PetscMemzero(absarray,(nbs+1)*sizeof(PetscReal));CHKERRQ(ierr); 1309 for (i=0; i<nbs; i++){ 1310 for (j=0; j<bs2; j++){ 1311 if (absarray[i] < PetscAbsScalar(blockarray[i*nbs+j])) absarray[i] = PetscAbsScalar(blockarray[i*nbs+j]); 1312 } 1313 } 1314 PetscFunctionReturn(0); 1315 } 1316 1317 #undef __FUNCT__ 1318 #define __FUNCT__ "MatILUDTFactor_SeqBAIJ" 1319 /* 1320 This needs to be renamed and called by the regular MatILUFactor_SeqBAIJ when drop tolerance is used 1321 */ 1322 PetscErrorCode MatILUDTFactor_SeqBAIJ(Mat A,IS isrow,IS iscol,const MatFactorInfo *info,Mat *fact) 1323 { 1324 Mat B = *fact; 1325 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data,*b; 1326 IS isicol; 1327 PetscErrorCode ierr; 1328 const PetscInt *r,*ic; 1329 PetscInt i,mbs=a->mbs,bs=A->rmap->bs,bs2=a->bs2,*ai=a->i,*aj=a->j,*ajtmp,*adiag; 1330 PetscInt *bi,*bj,*bdiag; 1331 1332 PetscInt row,nzi,nzi_bl,nzi_bu,*im,dtcount,nzi_al,nzi_au; 1333 PetscInt nlnk,*lnk; 1334 PetscBT lnkbt; 1335 PetscTruth row_identity,icol_identity,both_identity; 1336 MatScalar *aatmp,*pv,*batmp,*ba,*rtmp,*pc,*multiplier,*vtmp; 1337 const PetscInt *ics; 1338 PetscInt j,nz,*pj,*bjtmp,k,ncut,*jtmp; 1339 1340 PetscReal dt=info->dt; /* shift=info->shiftamount; */ 1341 PetscInt nnz_max; 1342 PetscTruth missing; 1343 PetscReal *vtmp_abs; 1344 MatScalar *v_work; 1345 PetscInt *v_pivots; 1346 1347 PetscFunctionBegin; 1348 /* ------- symbolic factorization, can be reused ---------*/ 1349 ierr = MatMissingDiagonal(A,&missing,&i);CHKERRQ(ierr); 1350 if (missing) SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",i); 1351 adiag=a->diag; 1352 1353 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 1354 1355 /* bdiag is location of diagonal in factor */ 1356 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&bdiag);CHKERRQ(ierr); 1357 1358 /* allocate row pointers bi */ 1359 ierr = PetscMalloc((2*mbs+2)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 1360 1361 /* allocate bj and ba; max num of nonzero entries is (ai[n]+2*n*dtcount+2) */ 1362 dtcount = (PetscInt)info->dtcount; 1363 if (dtcount > mbs-1) dtcount = mbs-1; 1364 nnz_max = ai[mbs]+2*mbs*dtcount +2; 1365 /* printf("MatILUDTFactor_SeqBAIJ, bs %d, ai[mbs] %d, nnz_max %d, dtcount %d\n",bs,ai[mbs],nnz_max,dtcount); */ 1366 ierr = PetscMalloc(nnz_max*sizeof(PetscInt),&bj);CHKERRQ(ierr); 1367 nnz_max = nnz_max*bs2; 1368 ierr = PetscMalloc(nnz_max*sizeof(MatScalar),&ba);CHKERRQ(ierr); 1369 1370 /* put together the new matrix */ 1371 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 1372 ierr = PetscLogObjectParent(B,isicol);CHKERRQ(ierr); 1373 b = (Mat_SeqBAIJ*)(B)->data; 1374 b->free_a = PETSC_TRUE; 1375 b->free_ij = PETSC_TRUE; 1376 b->singlemalloc = PETSC_FALSE; 1377 b->a = ba; 1378 b->j = bj; 1379 b->i = bi; 1380 b->diag = bdiag; 1381 b->ilen = 0; 1382 b->imax = 0; 1383 b->row = isrow; 1384 b->col = iscol; 1385 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 1386 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 1387 b->icol = isicol; 1388 ierr = PetscMalloc((bs*(mbs+1))*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 1389 1390 ierr = PetscLogObjectMemory(B,nnz_max*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 1391 b->maxnz = nnz_max/bs2; 1392 1393 (B)->factor = MAT_FACTOR_ILUDT; 1394 (B)->info.factor_mallocs = 0; 1395 (B)->info.fill_ratio_given = ((PetscReal)nnz_max)/((PetscReal)(ai[mbs]*bs2)); 1396 CHKMEMQ; 1397 /* ------- end of symbolic factorization ---------*/ 1398 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 1399 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 1400 ics = ic; 1401 1402 /* linked list for storing column indices of the active row */ 1403 nlnk = mbs + 1; 1404 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 1405 1406 /* im: used by PetscLLAddSortedLU(); jtmp: working array for column indices of active row */ 1407 ierr = PetscMalloc2(mbs,PetscInt,&im,mbs,PetscInt,&jtmp);CHKERRQ(ierr); 1408 /* rtmp, vtmp: working arrays for sparse and contiguous row entries of active row */ 1409 ierr = PetscMalloc2(mbs*bs2,MatScalar,&rtmp,mbs*bs2,MatScalar,&vtmp);CHKERRQ(ierr); 1410 ierr = PetscMalloc((mbs+1)*sizeof(PetscReal),&vtmp_abs);CHKERRQ(ierr); 1411 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs2,MatScalar,&multiplier,bs,PetscInt,&v_pivots);CHKERRQ(ierr); 1412 1413 bi[0] = 0; 1414 bdiag[0] = (nnz_max/bs2)-1; /* location of diagonal in factor B */ 1415 bi[2*mbs+1] = bdiag[0]+1; /* endof bj and ba array */ 1416 for (i=0; i<mbs; i++) { 1417 /* copy initial fill into linked list */ 1418 nzi = 0; /* nonzeros for active row i */ 1419 nzi = ai[r[i]+1] - ai[r[i]]; 1420 if (!nzi) SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[i],i); 1421 nzi_al = adiag[r[i]] - ai[r[i]]; 1422 nzi_au = ai[r[i]+1] - adiag[r[i]] -1; 1423 /* printf("row %d, nzi_al/au %d %d\n",i,nzi_al,nzi_au); */ 1424 1425 /* load in initial unfactored row */ 1426 ajtmp = aj + ai[r[i]]; 1427 ierr = PetscLLAddPerm(nzi,ajtmp,ic,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 1428 ierr = PetscMemzero(rtmp,mbs*bs2*sizeof(PetscScalar));CHKERRQ(ierr); 1429 aatmp = a->a + bs2*ai[r[i]]; 1430 for (j=0; j<nzi; j++) { 1431 ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],aatmp+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1432 } 1433 1434 /* add pivot rows into linked list */ 1435 row = lnk[mbs]; 1436 while (row < i) { 1437 nzi_bl = bi[row+1] - bi[row] + 1; 1438 bjtmp = bj + bdiag[row+1]+1; /* points to 1st column next to the diagonal in U */ 1439 ierr = PetscLLAddSortedLU(bjtmp,row,nlnk,lnk,lnkbt,i,nzi_bl,im);CHKERRQ(ierr); 1440 nzi += nlnk; 1441 row = lnk[row]; 1442 } 1443 1444 /* copy data from lnk into jtmp, then initialize lnk */ 1445 ierr = PetscLLClean(mbs,mbs,nzi,lnk,jtmp,lnkbt);CHKERRQ(ierr); 1446 1447 /* numerical factorization */ 1448 bjtmp = jtmp; 1449 row = *bjtmp++; /* 1st pivot row */ 1450 1451 while (row < i) { 1452 pc = rtmp + bs2*row; 1453 pv = ba + bs2*bdiag[row]; /* inv(diag) of the pivot row */ 1454 Kernel_A_gets_A_times_B(bs,pc,pv,multiplier); /* pc= multiplier = pc*inv(diag[row]) */ 1455 ierr = BlockAbs_private(1,bs2,pc,vtmp_abs);CHKERRQ(ierr); 1456 if (vtmp_abs[0] > dt){ /* apply tolerance dropping rule */ 1457 pj = bj + bdiag[row+1] + 1; /* point to 1st entry of U(row,:) */ 1458 pv = ba + bs2*(bdiag[row+1] + 1); 1459 nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries in U(row,:), excluding diagonal */ 1460 for (j=0; j<nz; j++){ 1461 Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); 1462 } 1463 /* ierr = PetscLogFlops(bslog*(nz+1.0)-bs);CHKERRQ(ierr); */ 1464 } 1465 row = *bjtmp++; 1466 } 1467 1468 /* copy sparse rtmp into contiguous vtmp; separate L and U part */ 1469 nzi_bl = 0; j = 0; 1470 while (jtmp[j] < i){ /* L-part. Note: jtmp is sorted */ 1471 ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 1472 nzi_bl++; j++; 1473 } 1474 nzi_bu = nzi - nzi_bl -1; 1475 /* printf("nzi %d, nzi_bl %d, nzi_bu %d\n",nzi,nzi_bl,nzi_bu); */ 1476 1477 while (j < nzi){ /* U-part */ 1478 ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 1479 /* 1480 printf(" col %d: ",jtmp[j]); 1481 for (j1=0; j1<bs2; j1++) printf(" %g",*(vtmp+bs2*j+j1)); 1482 printf(" \n"); 1483 */ 1484 j++; 1485 } 1486 1487 ierr = BlockAbs_private(nzi,bs2,vtmp,vtmp_abs);CHKERRQ(ierr); 1488 /* 1489 printf(" row %d, nzi %d, vtmp_abs\n",i,nzi); 1490 for (j1=0; j1<nzi; j1++) printf(" (%d %g),",jtmp[j1],vtmp_abs[j1]); 1491 printf(" \n"); 1492 */ 1493 bjtmp = bj + bi[i]; 1494 batmp = ba + bs2*bi[i]; 1495 /* apply level dropping rule to L part */ 1496 ncut = nzi_al + dtcount; 1497 if (ncut < nzi_bl){ 1498 ierr = PetscSortSplitReal(ncut,nzi_bl,vtmp_abs,jtmp);CHKERRQ(ierr); 1499 ierr = PetscSortIntWithScalarArray(ncut,jtmp,vtmp);CHKERRQ(ierr); 1500 } else { 1501 ncut = nzi_bl; 1502 } 1503 for (j=0; j<ncut; j++){ 1504 bjtmp[j] = jtmp[j]; 1505 ierr = PetscMemcpy(batmp+bs2*j,rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 1506 /* 1507 printf(" col %d: ",bjtmp[j]); 1508 for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*j+j1)); 1509 printf("\n"); 1510 */ 1511 } 1512 bi[i+1] = bi[i] + ncut; 1513 nzi = ncut + 1; 1514 1515 /* apply level dropping rule to U part */ 1516 ncut = nzi_au + dtcount; 1517 if (ncut < nzi_bu){ 1518 ierr = PetscSortSplitReal(ncut,nzi_bu,vtmp_abs+nzi_bl+1,jtmp+nzi_bl+1);CHKERRQ(ierr); 1519 ierr = PetscSortIntWithScalarArray(ncut,jtmp+nzi_bl+1,vtmp+nzi_bl+1);CHKERRQ(ierr); 1520 } else { 1521 ncut = nzi_bu; 1522 } 1523 nzi += ncut; 1524 1525 /* mark bdiagonal */ 1526 bdiag[i+1] = bdiag[i] - (ncut + 1); 1527 bi[2*mbs - i] = bi[2*mbs - i +1] - (ncut + 1); 1528 1529 bjtmp = bj + bdiag[i]; 1530 batmp = ba + bs2*bdiag[i]; 1531 ierr = PetscMemcpy(batmp,rtmp+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1532 *bjtmp = i; 1533 /* 1534 printf(" diag %d: ",*bjtmp); 1535 for (j=0; j<bs2; j++){ 1536 printf(" %g,",batmp[j]); 1537 } 1538 printf("\n"); 1539 */ 1540 bjtmp = bj + bdiag[i+1]+1; 1541 batmp = ba + (bdiag[i+1]+1)*bs2; 1542 1543 for (k=0; k<ncut; k++){ 1544 bjtmp[k] = jtmp[nzi_bl+1+k]; 1545 ierr = PetscMemcpy(batmp+bs2*k,rtmp+bs2*bjtmp[k],bs2*sizeof(MatScalar));CHKERRQ(ierr); 1546 /* 1547 printf(" col %d:",bjtmp[k]); 1548 for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*k+j1)); 1549 printf("\n"); 1550 */ 1551 } 1552 1553 im[i] = nzi; /* used by PetscLLAddSortedLU() */ 1554 1555 /* invert diagonal block for simplier triangular solves - add shift??? */ 1556 batmp = ba + bs2*bdiag[i]; 1557 ierr = Kernel_A_gets_inverse_A(bs,batmp,v_pivots,v_work);CHKERRQ(ierr); 1558 } /* for (i=0; i<mbs; i++) */ 1559 ierr = PetscFree3(v_work,multiplier,v_pivots);CHKERRQ(ierr); 1560 1561 /* printf("end of L %d, beginning of U %d\n",bi[mbs],bdiag[mbs]); */ 1562 if (bi[mbs] >= bdiag[mbs]) SETERRQ2(PETSC_ERR_ARG_SIZ,"end of L array %d cannot >= the beginning of U array %d",bi[mbs],bdiag[mbs]); 1563 1564 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 1565 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 1566 1567 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 1568 1569 ierr = PetscFree2(im,jtmp);CHKERRQ(ierr); 1570 ierr = PetscFree2(rtmp,vtmp);CHKERRQ(ierr); 1571 1572 ierr = PetscLogFlops(bs2*B->cmap->n);CHKERRQ(ierr); 1573 b->maxnz = b->nz = bi[mbs] + bdiag[0] - bdiag[mbs]; 1574 1575 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 1576 ierr = ISIdentity(isicol,&icol_identity);CHKERRQ(ierr); 1577 both_identity = (PetscTruth) (row_identity && icol_identity); 1578 if (row_identity && icol_identity) { 1579 B->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering; 1580 } else { 1581 B->ops->solve = MatSolve_SeqBAIJ_N; 1582 } 1583 1584 B->ops->solveadd = 0; 1585 B->ops->solvetranspose = 0; 1586 B->ops->solvetransposeadd = 0; 1587 B->ops->matsolve = 0; 1588 B->assembled = PETSC_TRUE; 1589 B->preallocated = PETSC_TRUE; 1590 PetscFunctionReturn(0); 1591 } 1592