1 2 /* 3 Defines the basic matrix operations for the BAIJ (compressed row) 4 matrix storage format. 5 */ 6 #include <../src/mat/impls/baij/seq/baij.h> /*I "petscmat.h" I*/ 7 #include <petscblaslapack.h> 8 #include <petsc-private/kernels/blockinvert.h> 9 #include <petsc-private/kernels/blockmatmult.h> 10 11 #undef __FUNCT__ 12 #define __FUNCT__ "MatInvertBlockDiagonal_SeqBAIJ" 13 PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A,const PetscScalar **values) 14 { 15 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*) A->data; 16 PetscErrorCode ierr; 17 PetscInt *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs,ipvt[5],bs2 = bs*bs,*v_pivots; 18 MatScalar *v = a->a,*odiag,*diag,*mdiag,work[25],*v_work; 19 PetscReal shift = 0.0; 20 21 PetscFunctionBegin; 22 if (a->idiagvalid) { 23 if (values) *values = a->idiag; 24 PetscFunctionReturn(0); 25 } 26 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 27 diag_offset = a->diag; 28 if (!a->idiag) { 29 ierr = PetscMalloc1(2*bs2*mbs,&a->idiag);CHKERRQ(ierr); 30 ierr = PetscLogObjectMemory((PetscObject)A,2*bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 31 } 32 diag = a->idiag; 33 mdiag = a->idiag+bs2*mbs; 34 if (values) *values = a->idiag; 35 /* factor and invert each block */ 36 switch (bs) { 37 case 1: 38 for (i=0; i<mbs; i++) { 39 odiag = v + 1*diag_offset[i]; 40 diag[0] = odiag[0]; 41 mdiag[0] = odiag[0]; 42 diag[0] = (PetscScalar)1.0 / (diag[0] + shift); 43 diag += 1; 44 mdiag += 1; 45 } 46 break; 47 case 2: 48 for (i=0; i<mbs; i++) { 49 odiag = v + 4*diag_offset[i]; 50 diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; 51 mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3]; 52 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 53 diag += 4; 54 mdiag += 4; 55 } 56 break; 57 case 3: 58 for (i=0; i<mbs; i++) { 59 odiag = v + 9*diag_offset[i]; 60 diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; 61 diag[4] = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7]; 62 diag[8] = odiag[8]; 63 mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3]; 64 mdiag[4] = odiag[4]; mdiag[5] = odiag[5]; mdiag[6] = odiag[6]; mdiag[7] = odiag[7]; 65 mdiag[8] = odiag[8]; 66 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 67 diag += 9; 68 mdiag += 9; 69 } 70 break; 71 case 4: 72 for (i=0; i<mbs; i++) { 73 odiag = v + 16*diag_offset[i]; 74 ierr = PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));CHKERRQ(ierr); 75 ierr = PetscMemcpy(mdiag,odiag,16*sizeof(PetscScalar));CHKERRQ(ierr); 76 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 77 diag += 16; 78 mdiag += 16; 79 } 80 break; 81 case 5: 82 for (i=0; i<mbs; i++) { 83 odiag = v + 25*diag_offset[i]; 84 ierr = PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));CHKERRQ(ierr); 85 ierr = PetscMemcpy(mdiag,odiag,25*sizeof(PetscScalar));CHKERRQ(ierr); 86 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 87 diag += 25; 88 mdiag += 25; 89 } 90 break; 91 case 6: 92 for (i=0; i<mbs; i++) { 93 odiag = v + 36*diag_offset[i]; 94 ierr = PetscMemcpy(diag,odiag,36*sizeof(PetscScalar));CHKERRQ(ierr); 95 ierr = PetscMemcpy(mdiag,odiag,36*sizeof(PetscScalar));CHKERRQ(ierr); 96 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 97 diag += 36; 98 mdiag += 36; 99 } 100 break; 101 case 7: 102 for (i=0; i<mbs; i++) { 103 odiag = v + 49*diag_offset[i]; 104 ierr = PetscMemcpy(diag,odiag,49*sizeof(PetscScalar));CHKERRQ(ierr); 105 ierr = PetscMemcpy(mdiag,odiag,49*sizeof(PetscScalar));CHKERRQ(ierr); 106 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 107 diag += 49; 108 mdiag += 49; 109 } 110 break; 111 default: 112 ierr = PetscMalloc2(bs,&v_work,bs,&v_pivots);CHKERRQ(ierr); 113 for (i=0; i<mbs; i++) { 114 odiag = v + bs2*diag_offset[i]; 115 ierr = PetscMemcpy(diag,odiag,bs2*sizeof(PetscScalar));CHKERRQ(ierr); 116 ierr = PetscMemcpy(mdiag,odiag,bs2*sizeof(PetscScalar));CHKERRQ(ierr); 117 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 118 diag += bs2; 119 mdiag += bs2; 120 } 121 ierr = PetscFree2(v_work,v_pivots);CHKERRQ(ierr); 122 } 123 a->idiagvalid = PETSC_TRUE; 124 PetscFunctionReturn(0); 125 } 126 127 #undef __FUNCT__ 128 #define __FUNCT__ "MatSOR_SeqBAIJ" 129 PetscErrorCode MatSOR_SeqBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 130 { 131 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 132 PetscScalar *x,*work,*w,*workt,*t; 133 const MatScalar *v,*aa = a->a, *idiag; 134 const PetscScalar *b,*xb; 135 PetscScalar s[7], xw[7]={0}; /* avoid some compilers thinking xw is uninitialized */ 136 PetscErrorCode ierr; 137 PetscInt m = a->mbs,i,i2,nz,bs = A->rmap->bs,bs2 = bs*bs,k,j,idx,it; 138 const PetscInt *diag,*ai = a->i,*aj = a->j,*vi; 139 140 PetscFunctionBegin; 141 its = its*lits; 142 if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat"); 143 if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 144 if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for diagonal shift"); 145 if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor"); 146 if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts"); 147 148 if (!a->idiagvalid) {ierr = MatInvertBlockDiagonal(A,NULL);CHKERRQ(ierr);} 149 150 if (!m) PetscFunctionReturn(0); 151 diag = a->diag; 152 idiag = a->idiag; 153 k = PetscMax(A->rmap->n,A->cmap->n); 154 if (!a->mult_work) { 155 ierr = PetscMalloc1(k+1,&a->mult_work);CHKERRQ(ierr); 156 } 157 if (!a->sor_workt) { 158 ierr = PetscMalloc1(k,&a->sor_workt);CHKERRQ(ierr); 159 } 160 if (!a->sor_work) { 161 ierr = PetscMalloc1(bs,&a->sor_work);CHKERRQ(ierr); 162 } 163 work = a->mult_work; 164 t = a->sor_workt; 165 w = a->sor_work; 166 167 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 168 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 169 170 if (flag & SOR_ZERO_INITIAL_GUESS) { 171 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 172 switch (bs) { 173 case 1: 174 PetscKernel_v_gets_A_times_w_1(x,idiag,b); 175 t[0] = b[0]; 176 i2 = 1; 177 idiag += 1; 178 for (i=1; i<m; i++) { 179 v = aa + ai[i]; 180 vi = aj + ai[i]; 181 nz = diag[i] - ai[i]; 182 s[0] = b[i2]; 183 for (j=0; j<nz; j++) { 184 xw[0] = x[vi[j]]; 185 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 186 } 187 t[i2] = s[0]; 188 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 189 x[i2] = xw[0]; 190 idiag += 1; 191 i2 += 1; 192 } 193 break; 194 case 2: 195 PetscKernel_v_gets_A_times_w_2(x,idiag,b); 196 t[0] = b[0]; t[1] = b[1]; 197 i2 = 2; 198 idiag += 4; 199 for (i=1; i<m; i++) { 200 v = aa + 4*ai[i]; 201 vi = aj + ai[i]; 202 nz = diag[i] - ai[i]; 203 s[0] = b[i2]; s[1] = b[i2+1]; 204 for (j=0; j<nz; j++) { 205 idx = 2*vi[j]; 206 it = 4*j; 207 xw[0] = x[idx]; xw[1] = x[1+idx]; 208 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 209 } 210 t[i2] = s[0]; t[i2+1] = s[1]; 211 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 212 x[i2] = xw[0]; x[i2+1] = xw[1]; 213 idiag += 4; 214 i2 += 2; 215 } 216 break; 217 case 3: 218 PetscKernel_v_gets_A_times_w_3(x,idiag,b); 219 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; 220 i2 = 3; 221 idiag += 9; 222 for (i=1; i<m; i++) { 223 v = aa + 9*ai[i]; 224 vi = aj + ai[i]; 225 nz = diag[i] - ai[i]; 226 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 227 while (nz--) { 228 idx = 3*(*vi++); 229 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 230 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 231 v += 9; 232 } 233 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 234 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 235 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 236 idiag += 9; 237 i2 += 3; 238 } 239 break; 240 case 4: 241 PetscKernel_v_gets_A_times_w_4(x,idiag,b); 242 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; 243 i2 = 4; 244 idiag += 16; 245 for (i=1; i<m; i++) { 246 v = aa + 16*ai[i]; 247 vi = aj + ai[i]; 248 nz = diag[i] - ai[i]; 249 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 250 while (nz--) { 251 idx = 4*(*vi++); 252 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 253 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 254 v += 16; 255 } 256 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3]; 257 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 258 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 259 idiag += 16; 260 i2 += 4; 261 } 262 break; 263 case 5: 264 PetscKernel_v_gets_A_times_w_5(x,idiag,b); 265 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; 266 i2 = 5; 267 idiag += 25; 268 for (i=1; i<m; i++) { 269 v = aa + 25*ai[i]; 270 vi = aj + ai[i]; 271 nz = diag[i] - ai[i]; 272 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 273 while (nz--) { 274 idx = 5*(*vi++); 275 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 276 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 277 v += 25; 278 } 279 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4]; 280 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 281 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 282 idiag += 25; 283 i2 += 5; 284 } 285 break; 286 case 6: 287 PetscKernel_v_gets_A_times_w_6(x,idiag,b); 288 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; 289 i2 = 6; 290 idiag += 36; 291 for (i=1; i<m; i++) { 292 v = aa + 36*ai[i]; 293 vi = aj + ai[i]; 294 nz = diag[i] - ai[i]; 295 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; 296 while (nz--) { 297 idx = 6*(*vi++); 298 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 299 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 300 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 301 v += 36; 302 } 303 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 304 t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; 305 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 306 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; 307 idiag += 36; 308 i2 += 6; 309 } 310 break; 311 case 7: 312 PetscKernel_v_gets_A_times_w_7(x,idiag,b); 313 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; 314 t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6]; 315 i2 = 7; 316 idiag += 49; 317 for (i=1; i<m; i++) { 318 v = aa + 49*ai[i]; 319 vi = aj + ai[i]; 320 nz = diag[i] - ai[i]; 321 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 322 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 323 while (nz--) { 324 idx = 7*(*vi++); 325 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 326 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 327 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 328 v += 49; 329 } 330 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 331 t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6]; 332 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 333 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 334 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 335 idiag += 49; 336 i2 += 7; 337 } 338 break; 339 default: 340 PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x); 341 ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); 342 i2 = bs; 343 idiag += bs2; 344 for (i=1; i<m; i++) { 345 v = aa + bs2*ai[i]; 346 vi = aj + ai[i]; 347 nz = diag[i] - ai[i]; 348 349 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 350 /* copy all rows of x that are needed into contiguous space */ 351 workt = work; 352 for (j=0; j<nz; j++) { 353 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 354 workt += bs; 355 } 356 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 357 ierr = PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));CHKERRQ(ierr); 358 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 359 360 idiag += bs2; 361 i2 += bs; 362 } 363 break; 364 } 365 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 366 ierr = PetscLogFlops(1.0*bs2*a->nz);CHKERRQ(ierr); 367 xb = t; 368 } 369 else xb = b; 370 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 371 idiag = a->idiag+bs2*(a->mbs-1); 372 i2 = bs * (m-1); 373 switch (bs) { 374 case 1: 375 s[0] = xb[i2]; 376 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 377 x[i2] = xw[0]; 378 i2 -= 1; 379 for (i=m-2; i>=0; i--) { 380 v = aa + (diag[i]+1); 381 vi = aj + diag[i] + 1; 382 nz = ai[i+1] - diag[i] - 1; 383 s[0] = xb[i2]; 384 for (j=0; j<nz; j++) { 385 xw[0] = x[vi[j]]; 386 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 387 } 388 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 389 x[i2] = xw[0]; 390 idiag -= 1; 391 i2 -= 1; 392 } 393 break; 394 case 2: 395 s[0] = xb[i2]; s[1] = xb[i2+1]; 396 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 397 x[i2] = xw[0]; x[i2+1] = xw[1]; 398 i2 -= 2; 399 idiag -= 4; 400 for (i=m-2; i>=0; i--) { 401 v = aa + 4*(diag[i] + 1); 402 vi = aj + diag[i] + 1; 403 nz = ai[i+1] - diag[i] - 1; 404 s[0] = xb[i2]; s[1] = xb[i2+1]; 405 for (j=0; j<nz; j++) { 406 idx = 2*vi[j]; 407 it = 4*j; 408 xw[0] = x[idx]; xw[1] = x[1+idx]; 409 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 410 } 411 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 412 x[i2] = xw[0]; x[i2+1] = xw[1]; 413 idiag -= 4; 414 i2 -= 2; 415 } 416 break; 417 case 3: 418 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 419 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 420 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 421 i2 -= 3; 422 idiag -= 9; 423 for (i=m-2; i>=0; i--) { 424 v = aa + 9*(diag[i]+1); 425 vi = aj + diag[i] + 1; 426 nz = ai[i+1] - diag[i] - 1; 427 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 428 while (nz--) { 429 idx = 3*(*vi++); 430 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 431 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 432 v += 9; 433 } 434 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 435 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 436 idiag -= 9; 437 i2 -= 3; 438 } 439 break; 440 case 4: 441 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; 442 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 443 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 444 i2 -= 4; 445 idiag -= 16; 446 for (i=m-2; i>=0; i--) { 447 v = aa + 16*(diag[i]+1); 448 vi = aj + diag[i] + 1; 449 nz = ai[i+1] - diag[i] - 1; 450 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; 451 while (nz--) { 452 idx = 4*(*vi++); 453 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 454 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 455 v += 16; 456 } 457 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 458 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 459 idiag -= 16; 460 i2 -= 4; 461 } 462 break; 463 case 5: 464 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; 465 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 466 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 467 i2 -= 5; 468 idiag -= 25; 469 for (i=m-2; i>=0; i--) { 470 v = aa + 25*(diag[i]+1); 471 vi = aj + diag[i] + 1; 472 nz = ai[i+1] - diag[i] - 1; 473 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; 474 while (nz--) { 475 idx = 5*(*vi++); 476 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 477 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 478 v += 25; 479 } 480 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 481 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 482 idiag -= 25; 483 i2 -= 5; 484 } 485 break; 486 case 6: 487 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; 488 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 489 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; 490 i2 -= 6; 491 idiag -= 36; 492 for (i=m-2; i>=0; i--) { 493 v = aa + 36*(diag[i]+1); 494 vi = aj + diag[i] + 1; 495 nz = ai[i+1] - diag[i] - 1; 496 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; 497 while (nz--) { 498 idx = 6*(*vi++); 499 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 500 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 501 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 502 v += 36; 503 } 504 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 505 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; 506 idiag -= 36; 507 i2 -= 6; 508 } 509 break; 510 case 7: 511 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 512 s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6]; 513 PetscKernel_v_gets_A_times_w_7(x,idiag,b); 514 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 515 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 516 i2 -= 7; 517 idiag -= 49; 518 for (i=m-2; i>=0; i--) { 519 v = aa + 49*(diag[i]+1); 520 vi = aj + diag[i] + 1; 521 nz = ai[i+1] - diag[i] - 1; 522 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 523 s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6]; 524 while (nz--) { 525 idx = 7*(*vi++); 526 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 527 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 528 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 529 v += 49; 530 } 531 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 532 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 533 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 534 idiag -= 49; 535 i2 -= 7; 536 } 537 break; 538 default: 539 ierr = PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 540 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 541 i2 -= bs; 542 idiag -= bs2; 543 for (i=m-2; i>=0; i--) { 544 v = aa + bs2*(diag[i]+1); 545 vi = aj + diag[i] + 1; 546 nz = ai[i+1] - diag[i] - 1; 547 548 ierr = PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 549 /* copy all rows of x that are needed into contiguous space */ 550 workt = work; 551 for (j=0; j<nz; j++) { 552 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 553 workt += bs; 554 } 555 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 556 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 557 558 idiag -= bs2; 559 i2 -= bs; 560 } 561 break; 562 } 563 ierr = PetscLogFlops(1.0*bs2*(a->nz));CHKERRQ(ierr); 564 } 565 its--; 566 } 567 while (its--) { 568 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 569 idiag = a->idiag; 570 i2 = 0; 571 switch (bs) { 572 case 1: 573 for (i=0; i<m; i++) { 574 v = aa + ai[i]; 575 vi = aj + ai[i]; 576 nz = ai[i+1] - ai[i]; 577 s[0] = b[i2]; 578 for (j=0; j<nz; j++) { 579 xw[0] = x[vi[j]]; 580 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 581 } 582 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 583 x[i2] += xw[0]; 584 idiag += 1; 585 i2 += 1; 586 } 587 break; 588 case 2: 589 for (i=0; i<m; i++) { 590 v = aa + 4*ai[i]; 591 vi = aj + ai[i]; 592 nz = ai[i+1] - ai[i]; 593 s[0] = b[i2]; s[1] = b[i2+1]; 594 for (j=0; j<nz; j++) { 595 idx = 2*vi[j]; 596 it = 4*j; 597 xw[0] = x[idx]; xw[1] = x[1+idx]; 598 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 599 } 600 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 601 x[i2] += xw[0]; x[i2+1] += xw[1]; 602 idiag += 4; 603 i2 += 2; 604 } 605 break; 606 case 3: 607 for (i=0; i<m; i++) { 608 v = aa + 9*ai[i]; 609 vi = aj + ai[i]; 610 nz = ai[i+1] - ai[i]; 611 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 612 while (nz--) { 613 idx = 3*(*vi++); 614 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 615 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 616 v += 9; 617 } 618 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 619 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 620 idiag += 9; 621 i2 += 3; 622 } 623 break; 624 case 4: 625 for (i=0; i<m; i++) { 626 v = aa + 16*ai[i]; 627 vi = aj + ai[i]; 628 nz = ai[i+1] - ai[i]; 629 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 630 while (nz--) { 631 idx = 4*(*vi++); 632 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 633 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 634 v += 16; 635 } 636 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 637 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; 638 idiag += 16; 639 i2 += 4; 640 } 641 break; 642 case 5: 643 for (i=0; i<m; i++) { 644 v = aa + 25*ai[i]; 645 vi = aj + ai[i]; 646 nz = ai[i+1] - ai[i]; 647 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 648 while (nz--) { 649 idx = 5*(*vi++); 650 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 651 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 652 v += 25; 653 } 654 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 655 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4]; 656 idiag += 25; 657 i2 += 5; 658 } 659 break; 660 case 6: 661 for (i=0; i<m; i++) { 662 v = aa + 36*ai[i]; 663 vi = aj + ai[i]; 664 nz = ai[i+1] - ai[i]; 665 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; 666 while (nz--) { 667 idx = 6*(*vi++); 668 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 669 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 670 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 671 v += 36; 672 } 673 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 674 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 675 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; 676 idiag += 36; 677 i2 += 6; 678 } 679 break; 680 case 7: 681 for (i=0; i<m; i++) { 682 v = aa + 49*ai[i]; 683 vi = aj + ai[i]; 684 nz = ai[i+1] - ai[i]; 685 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 686 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 687 while (nz--) { 688 idx = 7*(*vi++); 689 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 690 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 691 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 692 v += 49; 693 } 694 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 695 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 696 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6]; 697 idiag += 49; 698 i2 += 7; 699 } 700 break; 701 default: 702 for (i=0; i<m; i++) { 703 v = aa + bs2*ai[i]; 704 vi = aj + ai[i]; 705 nz = ai[i+1] - ai[i]; 706 707 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 708 /* copy all rows of x that are needed into contiguous space */ 709 workt = work; 710 for (j=0; j<nz; j++) { 711 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 712 workt += bs; 713 } 714 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 715 PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2); 716 717 idiag += bs2; 718 i2 += bs; 719 } 720 break; 721 } 722 ierr = PetscLogFlops(2.0*bs2*a->nz);CHKERRQ(ierr); 723 } 724 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 725 idiag = a->idiag+bs2*(a->mbs-1); 726 i2 = bs * (m-1); 727 switch (bs) { 728 case 1: 729 for (i=m-1; i>=0; i--) { 730 v = aa + ai[i]; 731 vi = aj + ai[i]; 732 nz = ai[i+1] - ai[i]; 733 s[0] = b[i2]; 734 for (j=0; j<nz; j++) { 735 xw[0] = x[vi[j]]; 736 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 737 } 738 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 739 x[i2] += xw[0]; 740 idiag -= 1; 741 i2 -= 1; 742 } 743 break; 744 case 2: 745 for (i=m-1; i>=0; i--) { 746 v = aa + 4*ai[i]; 747 vi = aj + ai[i]; 748 nz = ai[i+1] - ai[i]; 749 s[0] = b[i2]; s[1] = b[i2+1]; 750 for (j=0; j<nz; j++) { 751 idx = 2*vi[j]; 752 it = 4*j; 753 xw[0] = x[idx]; xw[1] = x[1+idx]; 754 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 755 } 756 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 757 x[i2] += xw[0]; x[i2+1] += xw[1]; 758 idiag -= 4; 759 i2 -= 2; 760 } 761 break; 762 case 3: 763 for (i=m-1; i>=0; i--) { 764 v = aa + 9*ai[i]; 765 vi = aj + ai[i]; 766 nz = ai[i+1] - ai[i]; 767 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 768 while (nz--) { 769 idx = 3*(*vi++); 770 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 771 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 772 v += 9; 773 } 774 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 775 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 776 idiag -= 9; 777 i2 -= 3; 778 } 779 break; 780 case 4: 781 for (i=m-1; i>=0; i--) { 782 v = aa + 16*ai[i]; 783 vi = aj + ai[i]; 784 nz = ai[i+1] - ai[i]; 785 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 786 while (nz--) { 787 idx = 4*(*vi++); 788 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 789 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 790 v += 16; 791 } 792 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 793 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; 794 idiag -= 16; 795 i2 -= 4; 796 } 797 break; 798 case 5: 799 for (i=m-1; i>=0; i--) { 800 v = aa + 25*ai[i]; 801 vi = aj + ai[i]; 802 nz = ai[i+1] - ai[i]; 803 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 804 while (nz--) { 805 idx = 5*(*vi++); 806 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 807 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 808 v += 25; 809 } 810 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 811 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4]; 812 idiag -= 25; 813 i2 -= 5; 814 } 815 break; 816 case 6: 817 for (i=m-1; i>=0; i--) { 818 v = aa + 36*ai[i]; 819 vi = aj + ai[i]; 820 nz = ai[i+1] - ai[i]; 821 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; 822 while (nz--) { 823 idx = 6*(*vi++); 824 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 825 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 826 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 827 v += 36; 828 } 829 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 830 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 831 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; 832 idiag -= 36; 833 i2 -= 6; 834 } 835 break; 836 case 7: 837 for (i=m-1; i>=0; i--) { 838 v = aa + 49*ai[i]; 839 vi = aj + ai[i]; 840 nz = ai[i+1] - ai[i]; 841 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 842 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 843 while (nz--) { 844 idx = 7*(*vi++); 845 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 846 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 847 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 848 v += 49; 849 } 850 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 851 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 852 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6]; 853 idiag -= 49; 854 i2 -= 7; 855 } 856 break; 857 default: 858 for (i=m-1; i>=0; i--) { 859 v = aa + bs2*ai[i]; 860 vi = aj + ai[i]; 861 nz = ai[i+1] - ai[i]; 862 863 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 864 /* copy all rows of x that are needed into contiguous space */ 865 workt = work; 866 for (j=0; j<nz; j++) { 867 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 868 workt += bs; 869 } 870 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 871 PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2); 872 873 idiag -= bs2; 874 i2 -= bs; 875 } 876 break; 877 } 878 ierr = PetscLogFlops(2.0*bs2*(a->nz));CHKERRQ(ierr); 879 } 880 } 881 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 882 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 883 PetscFunctionReturn(0); 884 } 885 886 887 /* 888 Special version for direct calls from Fortran (Used in PETSc-fun3d) 889 */ 890 #if defined(PETSC_HAVE_FORTRAN_CAPS) 891 #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4 892 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 893 #define matsetvaluesblocked4_ matsetvaluesblocked4 894 #endif 895 896 #undef __FUNCT__ 897 #define __FUNCT__ "matsetvaluesblocked4_" 898 PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[]) 899 { 900 Mat A = *AA; 901 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 902 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn; 903 PetscInt *ai =a->i,*ailen=a->ilen; 904 PetscInt *aj =a->j,stepval,lastcol = -1; 905 const PetscScalar *value = v; 906 MatScalar *ap,*aa = a->a,*bap; 907 908 PetscFunctionBegin; 909 if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4"); 910 stepval = (n-1)*4; 911 for (k=0; k<m; k++) { /* loop over added rows */ 912 row = im[k]; 913 rp = aj + ai[row]; 914 ap = aa + 16*ai[row]; 915 nrow = ailen[row]; 916 low = 0; 917 high = nrow; 918 for (l=0; l<n; l++) { /* loop over added columns */ 919 col = in[l]; 920 if (col <= lastcol) low = 0; 921 else high = nrow; 922 lastcol = col; 923 value = v + k*(stepval+4 + l)*4; 924 while (high-low > 7) { 925 t = (low+high)/2; 926 if (rp[t] > col) high = t; 927 else low = t; 928 } 929 for (i=low; i<high; i++) { 930 if (rp[i] > col) break; 931 if (rp[i] == col) { 932 bap = ap + 16*i; 933 for (ii=0; ii<4; ii++,value+=stepval) { 934 for (jj=ii; jj<16; jj+=4) { 935 bap[jj] += *value++; 936 } 937 } 938 goto noinsert2; 939 } 940 } 941 N = nrow++ - 1; 942 high++; /* added new column index thus must search to one higher than before */ 943 /* shift up all the later entries in this row */ 944 for (ii=N; ii>=i; ii--) { 945 rp[ii+1] = rp[ii]; 946 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 947 } 948 if (N >= i) { 949 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 950 } 951 rp[i] = col; 952 bap = ap + 16*i; 953 for (ii=0; ii<4; ii++,value+=stepval) { 954 for (jj=ii; jj<16; jj+=4) { 955 bap[jj] = *value++; 956 } 957 } 958 noinsert2:; 959 low = i; 960 } 961 ailen[row] = nrow; 962 } 963 PetscFunctionReturnVoid(); 964 } 965 966 #if defined(PETSC_HAVE_FORTRAN_CAPS) 967 #define matsetvalues4_ MATSETVALUES4 968 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 969 #define matsetvalues4_ matsetvalues4 970 #endif 971 972 #undef __FUNCT__ 973 #define __FUNCT__ "MatSetValues4_" 974 PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v) 975 { 976 Mat A = *AA; 977 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 978 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm; 979 PetscInt *ai=a->i,*ailen=a->ilen; 980 PetscInt *aj=a->j,brow,bcol; 981 PetscInt ridx,cidx,lastcol = -1; 982 MatScalar *ap,value,*aa=a->a,*bap; 983 984 PetscFunctionBegin; 985 for (k=0; k<m; k++) { /* loop over added rows */ 986 row = im[k]; brow = row/4; 987 rp = aj + ai[brow]; 988 ap = aa + 16*ai[brow]; 989 nrow = ailen[brow]; 990 low = 0; 991 high = nrow; 992 for (l=0; l<n; l++) { /* loop over added columns */ 993 col = in[l]; bcol = col/4; 994 ridx = row % 4; cidx = col % 4; 995 value = v[l + k*n]; 996 if (col <= lastcol) low = 0; 997 else high = nrow; 998 lastcol = col; 999 while (high-low > 7) { 1000 t = (low+high)/2; 1001 if (rp[t] > bcol) high = t; 1002 else low = t; 1003 } 1004 for (i=low; i<high; i++) { 1005 if (rp[i] > bcol) break; 1006 if (rp[i] == bcol) { 1007 bap = ap + 16*i + 4*cidx + ridx; 1008 *bap += value; 1009 goto noinsert1; 1010 } 1011 } 1012 N = nrow++ - 1; 1013 high++; /* added new column thus must search to one higher than before */ 1014 /* shift up all the later entries in this row */ 1015 for (ii=N; ii>=i; ii--) { 1016 rp[ii+1] = rp[ii]; 1017 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 1018 } 1019 if (N>=i) { 1020 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 1021 } 1022 rp[i] = bcol; 1023 ap[16*i + 4*cidx + ridx] = value; 1024 noinsert1:; 1025 low = i; 1026 } 1027 ailen[brow] = nrow; 1028 } 1029 PetscFunctionReturnVoid(); 1030 } 1031 1032 /* 1033 Checks for missing diagonals 1034 */ 1035 #undef __FUNCT__ 1036 #define __FUNCT__ "MatMissingDiagonal_SeqBAIJ" 1037 PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool *missing,PetscInt *d) 1038 { 1039 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1040 PetscErrorCode ierr; 1041 PetscInt *diag,*ii = a->i,i; 1042 1043 PetscFunctionBegin; 1044 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 1045 *missing = PETSC_FALSE; 1046 if (A->rmap->n > 0 && !ii) { 1047 *missing = PETSC_TRUE; 1048 if (d) *d = 0; 1049 PetscInfo(A,"Matrix has no entries therefore is missing diagonal"); 1050 } else { 1051 diag = a->diag; 1052 for (i=0; i<a->mbs; i++) { 1053 if (diag[i] >= ii[i+1]) { 1054 *missing = PETSC_TRUE; 1055 if (d) *d = i; 1056 PetscInfo1(A,"Matrix is missing block diagonal number %D",i); 1057 break; 1058 } 1059 } 1060 } 1061 PetscFunctionReturn(0); 1062 } 1063 1064 #undef __FUNCT__ 1065 #define __FUNCT__ "MatMarkDiagonal_SeqBAIJ" 1066 PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A) 1067 { 1068 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1069 PetscErrorCode ierr; 1070 PetscInt i,j,m = a->mbs; 1071 1072 PetscFunctionBegin; 1073 if (!a->diag) { 1074 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1075 ierr = PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));CHKERRQ(ierr); 1076 a->free_diag = PETSC_TRUE; 1077 } 1078 for (i=0; i<m; i++) { 1079 a->diag[i] = a->i[i+1]; 1080 for (j=a->i[i]; j<a->i[i+1]; j++) { 1081 if (a->j[j] == i) { 1082 a->diag[i] = j; 1083 break; 1084 } 1085 } 1086 } 1087 PetscFunctionReturn(0); 1088 } 1089 1090 1091 #undef __FUNCT__ 1092 #define __FUNCT__ "MatGetRowIJ_SeqBAIJ" 1093 static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool *done) 1094 { 1095 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1096 PetscErrorCode ierr; 1097 PetscInt i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt; 1098 PetscInt **ia = (PetscInt**)inia,**ja = (PetscInt**)inja; 1099 1100 PetscFunctionBegin; 1101 *nn = n; 1102 if (!ia) PetscFunctionReturn(0); 1103 if (symmetric) { 1104 ierr = MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,0,0,&tia,&tja);CHKERRQ(ierr); 1105 nz = tia[n]; 1106 } else { 1107 tia = a->i; tja = a->j; 1108 } 1109 1110 if (!blockcompressed && bs > 1) { 1111 (*nn) *= bs; 1112 /* malloc & create the natural set of indices */ 1113 ierr = PetscMalloc1((n+1)*bs,ia);CHKERRQ(ierr); 1114 if (n) { 1115 (*ia)[0] = 0; 1116 for (j=1; j<bs; j++) { 1117 (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1]; 1118 } 1119 } 1120 1121 for (i=1; i<n; i++) { 1122 (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1]; 1123 for (j=1; j<bs; j++) { 1124 (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1]; 1125 } 1126 } 1127 if (n) { 1128 (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1]; 1129 } 1130 1131 if (inja) { 1132 ierr = PetscMalloc1(nz*bs*bs,ja);CHKERRQ(ierr); 1133 cnt = 0; 1134 for (i=0; i<n; i++) { 1135 for (j=0; j<bs; j++) { 1136 for (k=tia[i]; k<tia[i+1]; k++) { 1137 for (l=0; l<bs; l++) { 1138 (*ja)[cnt++] = bs*tja[k] + l; 1139 } 1140 } 1141 } 1142 } 1143 } 1144 1145 if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */ 1146 ierr = PetscFree(tia);CHKERRQ(ierr); 1147 ierr = PetscFree(tja);CHKERRQ(ierr); 1148 } 1149 } else if (oshift == 1) { 1150 if (symmetric) { 1151 nz = tia[A->rmap->n/bs]; 1152 /* add 1 to i and j indices */ 1153 for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1; 1154 *ia = tia; 1155 if (ja) { 1156 for (i=0; i<nz; i++) tja[i] = tja[i] + 1; 1157 *ja = tja; 1158 } 1159 } else { 1160 nz = a->i[A->rmap->n/bs]; 1161 /* malloc space and add 1 to i and j indices */ 1162 ierr = PetscMalloc1((A->rmap->n/bs+1),ia);CHKERRQ(ierr); 1163 for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1; 1164 if (ja) { 1165 ierr = PetscMalloc1(nz,ja);CHKERRQ(ierr); 1166 for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1; 1167 } 1168 } 1169 } else { 1170 *ia = tia; 1171 if (ja) *ja = tja; 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatRestoreRowIJ_SeqBAIJ" 1178 static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 1179 { 1180 PetscErrorCode ierr; 1181 1182 PetscFunctionBegin; 1183 if (!ia) PetscFunctionReturn(0); 1184 if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) { 1185 ierr = PetscFree(*ia);CHKERRQ(ierr); 1186 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 1187 } 1188 PetscFunctionReturn(0); 1189 } 1190 1191 #undef __FUNCT__ 1192 #define __FUNCT__ "MatDestroy_SeqBAIJ" 1193 PetscErrorCode MatDestroy_SeqBAIJ(Mat A) 1194 { 1195 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1196 PetscErrorCode ierr; 1197 1198 PetscFunctionBegin; 1199 #if defined(PETSC_USE_LOG) 1200 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz); 1201 #endif 1202 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1203 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1204 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1205 if (a->free_diag) {ierr = PetscFree(a->diag);CHKERRQ(ierr);} 1206 ierr = PetscFree(a->idiag);CHKERRQ(ierr); 1207 if (a->free_imax_ilen) {ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr);} 1208 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1209 ierr = PetscFree(a->mult_work);CHKERRQ(ierr); 1210 ierr = PetscFree(a->sor_workt);CHKERRQ(ierr); 1211 ierr = PetscFree(a->sor_work);CHKERRQ(ierr); 1212 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1213 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1214 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1215 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1216 1217 ierr = MatDestroy(&a->sbaijMat);CHKERRQ(ierr); 1218 ierr = MatDestroy(&a->parent);CHKERRQ(ierr); 1219 ierr = PetscFree(A->data);CHKERRQ(ierr); 1220 1221 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1222 ierr = PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);CHKERRQ(ierr); 1223 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1224 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1225 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1226 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);CHKERRQ(ierr); 1227 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1228 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1229 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1230 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);CHKERRQ(ierr); 1231 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1232 PetscFunctionReturn(0); 1233 } 1234 1235 #undef __FUNCT__ 1236 #define __FUNCT__ "MatSetOption_SeqBAIJ" 1237 PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg) 1238 { 1239 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1240 PetscErrorCode ierr; 1241 1242 PetscFunctionBegin; 1243 switch (op) { 1244 case MAT_ROW_ORIENTED: 1245 a->roworiented = flg; 1246 break; 1247 case MAT_KEEP_NONZERO_PATTERN: 1248 a->keepnonzeropattern = flg; 1249 break; 1250 case MAT_NEW_NONZERO_LOCATIONS: 1251 a->nonew = (flg ? 0 : 1); 1252 break; 1253 case MAT_NEW_NONZERO_LOCATION_ERR: 1254 a->nonew = (flg ? -1 : 0); 1255 break; 1256 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1257 a->nonew = (flg ? -2 : 0); 1258 break; 1259 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1260 a->nounused = (flg ? -1 : 0); 1261 break; 1262 case MAT_NEW_DIAGONALS: 1263 case MAT_IGNORE_OFF_PROC_ENTRIES: 1264 case MAT_USE_HASH_TABLE: 1265 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1266 break; 1267 case MAT_SPD: 1268 case MAT_SYMMETRIC: 1269 case MAT_STRUCTURALLY_SYMMETRIC: 1270 case MAT_HERMITIAN: 1271 case MAT_SYMMETRY_ETERNAL: 1272 /* These options are handled directly by MatSetOption() */ 1273 break; 1274 default: 1275 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1276 } 1277 PetscFunctionReturn(0); 1278 } 1279 1280 /* used for both SeqBAIJ and SeqSBAIJ matrices */ 1281 #undef __FUNCT__ 1282 #define __FUNCT__ "MatGetRow_SeqBAIJ_private" 1283 PetscErrorCode MatGetRow_SeqBAIJ_private(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v,PetscInt *ai,PetscInt *aj,PetscScalar *aa) 1284 { 1285 PetscErrorCode ierr; 1286 PetscInt itmp,i,j,k,M,bn,bp,*idx_i,bs,bs2; 1287 MatScalar *aa_i; 1288 PetscScalar *v_i; 1289 1290 PetscFunctionBegin; 1291 bs = A->rmap->bs; 1292 bs2 = bs*bs; 1293 if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row); 1294 1295 bn = row/bs; /* Block number */ 1296 bp = row % bs; /* Block Position */ 1297 M = ai[bn+1] - ai[bn]; 1298 *nz = bs*M; 1299 1300 if (v) { 1301 *v = 0; 1302 if (*nz) { 1303 ierr = PetscMalloc1((*nz),v);CHKERRQ(ierr); 1304 for (i=0; i<M; i++) { /* for each block in the block row */ 1305 v_i = *v + i*bs; 1306 aa_i = aa + bs2*(ai[bn] + i); 1307 for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j]; 1308 } 1309 } 1310 } 1311 1312 if (idx) { 1313 *idx = 0; 1314 if (*nz) { 1315 ierr = PetscMalloc1((*nz),idx);CHKERRQ(ierr); 1316 for (i=0; i<M; i++) { /* for each block in the block row */ 1317 idx_i = *idx + i*bs; 1318 itmp = bs*aj[ai[bn] + i]; 1319 for (j=0; j<bs; j++) idx_i[j] = itmp++; 1320 } 1321 } 1322 } 1323 PetscFunctionReturn(0); 1324 } 1325 1326 #undef __FUNCT__ 1327 #define __FUNCT__ "MatGetRow_SeqBAIJ" 1328 PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1329 { 1330 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1331 PetscErrorCode ierr; 1332 1333 PetscFunctionBegin; 1334 ierr = MatGetRow_SeqBAIJ_private(A,row,nz,idx,v,a->i,a->j,a->a);CHKERRQ(ierr); 1335 PetscFunctionReturn(0); 1336 } 1337 1338 #undef __FUNCT__ 1339 #define __FUNCT__ "MatRestoreRow_SeqBAIJ" 1340 PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1341 { 1342 PetscErrorCode ierr; 1343 1344 PetscFunctionBegin; 1345 if (idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);} 1346 if (v) {ierr = PetscFree(*v);CHKERRQ(ierr);} 1347 PetscFunctionReturn(0); 1348 } 1349 1350 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 1351 1352 #undef __FUNCT__ 1353 #define __FUNCT__ "MatTranspose_SeqBAIJ" 1354 PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B) 1355 { 1356 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1357 Mat C; 1358 PetscErrorCode ierr; 1359 PetscInt i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col; 1360 PetscInt *rows,*cols,bs2=a->bs2; 1361 MatScalar *array; 1362 1363 PetscFunctionBegin; 1364 if (reuse == MAT_REUSE_MATRIX && A == *B && mbs != nbs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1365 if (reuse == MAT_INITIAL_MATRIX || A == *B) { 1366 ierr = PetscCalloc1((1+nbs),&col);CHKERRQ(ierr); 1367 1368 for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1; 1369 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 1370 ierr = MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);CHKERRQ(ierr); 1371 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 1372 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(C,bs,0,col);CHKERRQ(ierr); 1373 ierr = PetscFree(col);CHKERRQ(ierr); 1374 } else { 1375 C = *B; 1376 } 1377 1378 array = a->a; 1379 ierr = PetscMalloc2(bs,&rows,bs,&cols);CHKERRQ(ierr); 1380 for (i=0; i<mbs; i++) { 1381 cols[0] = i*bs; 1382 for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1; 1383 len = ai[i+1] - ai[i]; 1384 for (j=0; j<len; j++) { 1385 rows[0] = (*aj++)*bs; 1386 for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1; 1387 ierr = MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);CHKERRQ(ierr); 1388 array += bs2; 1389 } 1390 } 1391 ierr = PetscFree2(rows,cols);CHKERRQ(ierr); 1392 1393 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1394 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1395 1396 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 1397 *B = C; 1398 } else { 1399 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1400 } 1401 PetscFunctionReturn(0); 1402 } 1403 1404 #undef __FUNCT__ 1405 #define __FUNCT__ "MatIsTranspose_SeqBAIJ" 1406 PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 1407 { 1408 PetscErrorCode ierr; 1409 Mat Btrans; 1410 1411 PetscFunctionBegin; 1412 *f = PETSC_FALSE; 1413 ierr = MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);CHKERRQ(ierr); 1414 ierr = MatEqual_SeqBAIJ(B,Btrans,f);CHKERRQ(ierr); 1415 ierr = MatDestroy(&Btrans);CHKERRQ(ierr); 1416 PetscFunctionReturn(0); 1417 } 1418 1419 #undef __FUNCT__ 1420 #define __FUNCT__ "MatView_SeqBAIJ_Binary" 1421 static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer) 1422 { 1423 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1424 PetscErrorCode ierr; 1425 PetscInt i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2; 1426 int fd; 1427 PetscScalar *aa; 1428 FILE *file; 1429 1430 PetscFunctionBegin; 1431 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1432 ierr = PetscMalloc1((4+A->rmap->N),&col_lens);CHKERRQ(ierr); 1433 col_lens[0] = MAT_FILE_CLASSID; 1434 1435 col_lens[1] = A->rmap->N; 1436 col_lens[2] = A->cmap->n; 1437 col_lens[3] = a->nz*bs2; 1438 1439 /* store lengths of each row and write (including header) to file */ 1440 count = 0; 1441 for (i=0; i<a->mbs; i++) { 1442 for (j=0; j<bs; j++) { 1443 col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]); 1444 } 1445 } 1446 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1447 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1448 1449 /* store column indices (zero start index) */ 1450 ierr = PetscMalloc1((a->nz+1)*bs2,&jj);CHKERRQ(ierr); 1451 count = 0; 1452 for (i=0; i<a->mbs; i++) { 1453 for (j=0; j<bs; j++) { 1454 for (k=a->i[i]; k<a->i[i+1]; k++) { 1455 for (l=0; l<bs; l++) { 1456 jj[count++] = bs*a->j[k] + l; 1457 } 1458 } 1459 } 1460 } 1461 ierr = PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1462 ierr = PetscFree(jj);CHKERRQ(ierr); 1463 1464 /* store nonzero values */ 1465 ierr = PetscMalloc1((a->nz+1)*bs2,&aa);CHKERRQ(ierr); 1466 count = 0; 1467 for (i=0; i<a->mbs; i++) { 1468 for (j=0; j<bs; j++) { 1469 for (k=a->i[i]; k<a->i[i+1]; k++) { 1470 for (l=0; l<bs; l++) { 1471 aa[count++] = a->a[bs2*k + l*bs + j]; 1472 } 1473 } 1474 } 1475 } 1476 ierr = PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1477 ierr = PetscFree(aa);CHKERRQ(ierr); 1478 1479 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1480 if (file) { 1481 fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs); 1482 } 1483 PetscFunctionReturn(0); 1484 } 1485 1486 #undef __FUNCT__ 1487 #define __FUNCT__ "MatView_SeqBAIJ_ASCII" 1488 static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer) 1489 { 1490 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1491 PetscErrorCode ierr; 1492 PetscInt i,j,bs = A->rmap->bs,k,l,bs2=a->bs2; 1493 PetscViewerFormat format; 1494 1495 PetscFunctionBegin; 1496 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1497 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1498 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1499 } else if (format == PETSC_VIEWER_ASCII_MATLAB) { 1500 const char *matname; 1501 Mat aij; 1502 ierr = MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);CHKERRQ(ierr); 1503 ierr = PetscObjectGetName((PetscObject)A,&matname);CHKERRQ(ierr); 1504 ierr = PetscObjectSetName((PetscObject)aij,matname);CHKERRQ(ierr); 1505 ierr = MatView(aij,viewer);CHKERRQ(ierr); 1506 ierr = MatDestroy(&aij);CHKERRQ(ierr); 1507 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1508 PetscFunctionReturn(0); 1509 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1510 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1511 for (i=0; i<a->mbs; i++) { 1512 for (j=0; j<bs; j++) { 1513 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1514 for (k=a->i[i]; k<a->i[i+1]; k++) { 1515 for (l=0; l<bs; l++) { 1516 #if defined(PETSC_USE_COMPLEX) 1517 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1518 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l, 1519 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1520 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1521 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l, 1522 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1523 } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1524 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1525 } 1526 #else 1527 if (a->a[bs2*k + l*bs + j] != 0.0) { 1528 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1529 } 1530 #endif 1531 } 1532 } 1533 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1534 } 1535 } 1536 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1537 } else { 1538 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1539 for (i=0; i<a->mbs; i++) { 1540 for (j=0; j<bs; j++) { 1541 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1542 for (k=a->i[i]; k<a->i[i+1]; k++) { 1543 for (l=0; l<bs; l++) { 1544 #if defined(PETSC_USE_COMPLEX) 1545 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) { 1546 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l, 1547 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1548 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) { 1549 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l, 1550 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1551 } else { 1552 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1553 } 1554 #else 1555 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1556 #endif 1557 } 1558 } 1559 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1560 } 1561 } 1562 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1563 } 1564 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1565 PetscFunctionReturn(0); 1566 } 1567 1568 #include <petscdraw.h> 1569 #undef __FUNCT__ 1570 #define __FUNCT__ "MatView_SeqBAIJ_Draw_Zoom" 1571 static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 1572 { 1573 Mat A = (Mat) Aa; 1574 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1575 PetscErrorCode ierr; 1576 PetscInt row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2; 1577 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1578 MatScalar *aa; 1579 PetscViewer viewer; 1580 PetscViewerFormat format; 1581 1582 PetscFunctionBegin; 1583 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1584 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1585 1586 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1587 1588 /* loop over matrix elements drawing boxes */ 1589 1590 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1591 color = PETSC_DRAW_BLUE; 1592 for (i=0,row=0; i<mbs; i++,row+=bs) { 1593 for (j=a->i[i]; j<a->i[i+1]; j++) { 1594 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1595 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1596 aa = a->a + j*bs2; 1597 for (k=0; k<bs; k++) { 1598 for (l=0; l<bs; l++) { 1599 if (PetscRealPart(*aa++) >= 0.) continue; 1600 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1601 } 1602 } 1603 } 1604 } 1605 color = PETSC_DRAW_CYAN; 1606 for (i=0,row=0; i<mbs; i++,row+=bs) { 1607 for (j=a->i[i]; j<a->i[i+1]; j++) { 1608 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1609 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1610 aa = a->a + j*bs2; 1611 for (k=0; k<bs; k++) { 1612 for (l=0; l<bs; l++) { 1613 if (PetscRealPart(*aa++) != 0.) continue; 1614 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1615 } 1616 } 1617 } 1618 } 1619 color = PETSC_DRAW_RED; 1620 for (i=0,row=0; i<mbs; i++,row+=bs) { 1621 for (j=a->i[i]; j<a->i[i+1]; j++) { 1622 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1623 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1624 aa = a->a + j*bs2; 1625 for (k=0; k<bs; k++) { 1626 for (l=0; l<bs; l++) { 1627 if (PetscRealPart(*aa++) <= 0.) continue; 1628 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1629 } 1630 } 1631 } 1632 } 1633 } else { 1634 /* use contour shading to indicate magnitude of values */ 1635 /* first determine max of all nonzero values */ 1636 PetscDraw popup; 1637 PetscReal scale,maxv = 0.0; 1638 1639 for (i=0; i<a->nz*a->bs2; i++) { 1640 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 1641 } 1642 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 1643 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1644 if (popup) { 1645 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 1646 } 1647 for (i=0,row=0; i<mbs; i++,row+=bs) { 1648 for (j=a->i[i]; j<a->i[i+1]; j++) { 1649 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1650 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1651 aa = a->a + j*bs2; 1652 for (k=0; k<bs; k++) { 1653 for (l=0; l<bs; l++) { 1654 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(*aa++)); 1655 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1656 } 1657 } 1658 } 1659 } 1660 } 1661 PetscFunctionReturn(0); 1662 } 1663 1664 #undef __FUNCT__ 1665 #define __FUNCT__ "MatView_SeqBAIJ_Draw" 1666 static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer) 1667 { 1668 PetscErrorCode ierr; 1669 PetscReal xl,yl,xr,yr,w,h; 1670 PetscDraw draw; 1671 PetscBool isnull; 1672 1673 PetscFunctionBegin; 1674 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1675 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1676 1677 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1678 xr = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0; 1679 xr += w; yr += h; xl = -w; yl = -h; 1680 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1681 ierr = PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);CHKERRQ(ierr); 1682 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1683 PetscFunctionReturn(0); 1684 } 1685 1686 #undef __FUNCT__ 1687 #define __FUNCT__ "MatView_SeqBAIJ" 1688 PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer) 1689 { 1690 PetscErrorCode ierr; 1691 PetscBool iascii,isbinary,isdraw; 1692 1693 PetscFunctionBegin; 1694 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1695 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1696 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1697 if (iascii) { 1698 ierr = MatView_SeqBAIJ_ASCII(A,viewer);CHKERRQ(ierr); 1699 } else if (isbinary) { 1700 ierr = MatView_SeqBAIJ_Binary(A,viewer);CHKERRQ(ierr); 1701 } else if (isdraw) { 1702 ierr = MatView_SeqBAIJ_Draw(A,viewer);CHKERRQ(ierr); 1703 } else { 1704 Mat B; 1705 ierr = MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);CHKERRQ(ierr); 1706 ierr = MatView(B,viewer);CHKERRQ(ierr); 1707 ierr = MatDestroy(&B);CHKERRQ(ierr); 1708 } 1709 PetscFunctionReturn(0); 1710 } 1711 1712 1713 #undef __FUNCT__ 1714 #define __FUNCT__ "MatGetValues_SeqBAIJ" 1715 PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 1716 { 1717 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1718 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 1719 PetscInt *ai = a->i,*ailen = a->ilen; 1720 PetscInt brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2; 1721 MatScalar *ap,*aa = a->a; 1722 1723 PetscFunctionBegin; 1724 for (k=0; k<m; k++) { /* loop over rows */ 1725 row = im[k]; brow = row/bs; 1726 if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */ 1727 if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row); 1728 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; 1729 nrow = ailen[brow]; 1730 for (l=0; l<n; l++) { /* loop over columns */ 1731 if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */ 1732 if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]); 1733 col = in[l]; 1734 bcol = col/bs; 1735 cidx = col%bs; 1736 ridx = row%bs; 1737 high = nrow; 1738 low = 0; /* assume unsorted */ 1739 while (high-low > 5) { 1740 t = (low+high)/2; 1741 if (rp[t] > bcol) high = t; 1742 else low = t; 1743 } 1744 for (i=low; i<high; i++) { 1745 if (rp[i] > bcol) break; 1746 if (rp[i] == bcol) { 1747 *v++ = ap[bs2*i+bs*cidx+ridx]; 1748 goto finished; 1749 } 1750 } 1751 *v++ = 0.0; 1752 finished:; 1753 } 1754 } 1755 PetscFunctionReturn(0); 1756 } 1757 1758 #undef __FUNCT__ 1759 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ" 1760 PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 1761 { 1762 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1763 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1; 1764 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 1765 PetscErrorCode ierr; 1766 PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval; 1767 PetscBool roworiented=a->roworiented; 1768 const PetscScalar *value = v; 1769 MatScalar *ap,*aa = a->a,*bap; 1770 1771 PetscFunctionBegin; 1772 if (roworiented) { 1773 stepval = (n-1)*bs; 1774 } else { 1775 stepval = (m-1)*bs; 1776 } 1777 for (k=0; k<m; k++) { /* loop over added rows */ 1778 row = im[k]; 1779 if (row < 0) continue; 1780 #if defined(PETSC_USE_DEBUG) 1781 if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1); 1782 #endif 1783 rp = aj + ai[row]; 1784 ap = aa + bs2*ai[row]; 1785 rmax = imax[row]; 1786 nrow = ailen[row]; 1787 low = 0; 1788 high = nrow; 1789 for (l=0; l<n; l++) { /* loop over added columns */ 1790 if (in[l] < 0) continue; 1791 #if defined(PETSC_USE_DEBUG) 1792 if (in[l] >= a->nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],a->nbs-1); 1793 #endif 1794 col = in[l]; 1795 if (roworiented) { 1796 value = v + (k*(stepval+bs) + l)*bs; 1797 } else { 1798 value = v + (l*(stepval+bs) + k)*bs; 1799 } 1800 if (col <= lastcol) low = 0; 1801 else high = nrow; 1802 lastcol = col; 1803 while (high-low > 7) { 1804 t = (low+high)/2; 1805 if (rp[t] > col) high = t; 1806 else low = t; 1807 } 1808 for (i=low; i<high; i++) { 1809 if (rp[i] > col) break; 1810 if (rp[i] == col) { 1811 bap = ap + bs2*i; 1812 if (roworiented) { 1813 if (is == ADD_VALUES) { 1814 for (ii=0; ii<bs; ii++,value+=stepval) { 1815 for (jj=ii; jj<bs2; jj+=bs) { 1816 bap[jj] += *value++; 1817 } 1818 } 1819 } else { 1820 for (ii=0; ii<bs; ii++,value+=stepval) { 1821 for (jj=ii; jj<bs2; jj+=bs) { 1822 bap[jj] = *value++; 1823 } 1824 } 1825 } 1826 } else { 1827 if (is == ADD_VALUES) { 1828 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 1829 for (jj=0; jj<bs; jj++) { 1830 bap[jj] += value[jj]; 1831 } 1832 bap += bs; 1833 } 1834 } else { 1835 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 1836 for (jj=0; jj<bs; jj++) { 1837 bap[jj] = value[jj]; 1838 } 1839 bap += bs; 1840 } 1841 } 1842 } 1843 goto noinsert2; 1844 } 1845 } 1846 if (nonew == 1) goto noinsert2; 1847 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1848 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 1849 N = nrow++ - 1; high++; 1850 /* shift up all the later entries in this row */ 1851 for (ii=N; ii>=i; ii--) { 1852 rp[ii+1] = rp[ii]; 1853 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 1854 } 1855 if (N >= i) { 1856 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1857 } 1858 rp[i] = col; 1859 bap = ap + bs2*i; 1860 if (roworiented) { 1861 for (ii=0; ii<bs; ii++,value+=stepval) { 1862 for (jj=ii; jj<bs2; jj+=bs) { 1863 bap[jj] = *value++; 1864 } 1865 } 1866 } else { 1867 for (ii=0; ii<bs; ii++,value+=stepval) { 1868 for (jj=0; jj<bs; jj++) { 1869 *bap++ = *value++; 1870 } 1871 } 1872 } 1873 noinsert2:; 1874 low = i; 1875 } 1876 ailen[row] = nrow; 1877 } 1878 PetscFunctionReturn(0); 1879 } 1880 1881 #undef __FUNCT__ 1882 #define __FUNCT__ "MatAssemblyEnd_SeqBAIJ" 1883 PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode) 1884 { 1885 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1886 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 1887 PetscInt m = A->rmap->N,*ip,N,*ailen = a->ilen; 1888 PetscErrorCode ierr; 1889 PetscInt mbs = a->mbs,bs2 = a->bs2,rmax = 0; 1890 MatScalar *aa = a->a,*ap; 1891 PetscReal ratio=0.6; 1892 1893 PetscFunctionBegin; 1894 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 1895 1896 if (m) rmax = ailen[0]; 1897 for (i=1; i<mbs; i++) { 1898 /* move each row back by the amount of empty slots (fshift) before it*/ 1899 fshift += imax[i-1] - ailen[i-1]; 1900 rmax = PetscMax(rmax,ailen[i]); 1901 if (fshift) { 1902 ip = aj + ai[i]; ap = aa + bs2*ai[i]; 1903 N = ailen[i]; 1904 for (j=0; j<N; j++) { 1905 ip[j-fshift] = ip[j]; 1906 1907 ierr = PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1908 } 1909 } 1910 ai[i] = ai[i-1] + ailen[i-1]; 1911 } 1912 if (mbs) { 1913 fshift += imax[mbs-1] - ailen[mbs-1]; 1914 ai[mbs] = ai[mbs-1] + ailen[mbs-1]; 1915 } 1916 1917 /* reset ilen and imax for each row */ 1918 a->nonzerorowcnt = 0; 1919 for (i=0; i<mbs; i++) { 1920 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1921 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1922 } 1923 a->nz = ai[mbs]; 1924 1925 /* diagonals may have moved, so kill the diagonal pointers */ 1926 a->idiagvalid = PETSC_FALSE; 1927 if (fshift && a->diag) { 1928 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1929 ierr = PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 1930 a->diag = 0; 1931 } 1932 if (fshift && a->nounused == -1) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2); 1933 ierr = PetscInfo5(A,"Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->cmap->n,A->rmap->bs,fshift*bs2,a->nz*bs2);CHKERRQ(ierr); 1934 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);CHKERRQ(ierr); 1935 ierr = PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);CHKERRQ(ierr); 1936 1937 A->info.mallocs += a->reallocs; 1938 a->reallocs = 0; 1939 A->info.nz_unneeded = (PetscReal)fshift*bs2; 1940 1941 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,mbs,ratio);CHKERRQ(ierr); 1942 PetscFunctionReturn(0); 1943 } 1944 1945 /* 1946 This function returns an array of flags which indicate the locations of contiguous 1947 blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] 1948 then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)] 1949 Assume: sizes should be long enough to hold all the values. 1950 */ 1951 #undef __FUNCT__ 1952 #define __FUNCT__ "MatZeroRows_SeqBAIJ_Check_Blocks" 1953 static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max) 1954 { 1955 PetscInt i,j,k,row; 1956 PetscBool flg; 1957 1958 PetscFunctionBegin; 1959 for (i=0,j=0; i<n; j++) { 1960 row = idx[i]; 1961 if (row%bs!=0) { /* Not the begining of a block */ 1962 sizes[j] = 1; 1963 i++; 1964 } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */ 1965 sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */ 1966 i++; 1967 } else { /* Begining of the block, so check if the complete block exists */ 1968 flg = PETSC_TRUE; 1969 for (k=1; k<bs; k++) { 1970 if (row+k != idx[i+k]) { /* break in the block */ 1971 flg = PETSC_FALSE; 1972 break; 1973 } 1974 } 1975 if (flg) { /* No break in the bs */ 1976 sizes[j] = bs; 1977 i += bs; 1978 } else { 1979 sizes[j] = 1; 1980 i++; 1981 } 1982 } 1983 } 1984 *bs_max = j; 1985 PetscFunctionReturn(0); 1986 } 1987 1988 #undef __FUNCT__ 1989 #define __FUNCT__ "MatZeroRows_SeqBAIJ" 1990 PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b) 1991 { 1992 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 1993 PetscErrorCode ierr; 1994 PetscInt i,j,k,count,*rows; 1995 PetscInt bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max; 1996 PetscScalar zero = 0.0; 1997 MatScalar *aa; 1998 const PetscScalar *xx; 1999 PetscScalar *bb; 2000 2001 PetscFunctionBegin; 2002 /* fix right hand side if needed */ 2003 if (x && b) { 2004 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2005 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2006 for (i=0; i<is_n; i++) { 2007 bb[is_idx[i]] = diag*xx[is_idx[i]]; 2008 } 2009 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2010 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2011 } 2012 2013 /* Make a copy of the IS and sort it */ 2014 /* allocate memory for rows,sizes */ 2015 ierr = PetscMalloc2(is_n,&rows,2*is_n,&sizes);CHKERRQ(ierr); 2016 2017 /* copy IS values to rows, and sort them */ 2018 for (i=0; i<is_n; i++) rows[i] = is_idx[i]; 2019 ierr = PetscSortInt(is_n,rows);CHKERRQ(ierr); 2020 2021 if (baij->keepnonzeropattern) { 2022 for (i=0; i<is_n; i++) sizes[i] = 1; 2023 bs_max = is_n; 2024 } else { 2025 ierr = MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);CHKERRQ(ierr); 2026 A->nonzerostate++; 2027 } 2028 2029 for (i=0,j=0; i<bs_max; j+=sizes[i],i++) { 2030 row = rows[j]; 2031 if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row); 2032 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 2033 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 2034 if (sizes[i] == bs && !baij->keepnonzeropattern) { 2035 if (diag != (PetscScalar)0.0) { 2036 if (baij->ilen[row/bs] > 0) { 2037 baij->ilen[row/bs] = 1; 2038 baij->j[baij->i[row/bs]] = row/bs; 2039 2040 ierr = PetscMemzero(aa,count*bs*sizeof(MatScalar));CHKERRQ(ierr); 2041 } 2042 /* Now insert all the diagonal values for this bs */ 2043 for (k=0; k<bs; k++) { 2044 ierr = (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);CHKERRQ(ierr); 2045 } 2046 } else { /* (diag == 0.0) */ 2047 baij->ilen[row/bs] = 0; 2048 } /* end (diag == 0.0) */ 2049 } else { /* (sizes[i] != bs) */ 2050 #if defined(PETSC_USE_DEBUG) 2051 if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1"); 2052 #endif 2053 for (k=0; k<count; k++) { 2054 aa[0] = zero; 2055 aa += bs; 2056 } 2057 if (diag != (PetscScalar)0.0) { 2058 ierr = (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);CHKERRQ(ierr); 2059 } 2060 } 2061 } 2062 2063 ierr = PetscFree2(rows,sizes);CHKERRQ(ierr); 2064 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2065 PetscFunctionReturn(0); 2066 } 2067 2068 #undef __FUNCT__ 2069 #define __FUNCT__ "MatZeroRowsColumns_SeqBAIJ" 2070 PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b) 2071 { 2072 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 2073 PetscErrorCode ierr; 2074 PetscInt i,j,k,count; 2075 PetscInt bs =A->rmap->bs,bs2=baij->bs2,row,col; 2076 PetscScalar zero = 0.0; 2077 MatScalar *aa; 2078 const PetscScalar *xx; 2079 PetscScalar *bb; 2080 PetscBool *zeroed,vecs = PETSC_FALSE; 2081 2082 PetscFunctionBegin; 2083 /* fix right hand side if needed */ 2084 if (x && b) { 2085 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2086 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2087 vecs = PETSC_TRUE; 2088 } 2089 2090 /* zero the columns */ 2091 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2092 for (i=0; i<is_n; i++) { 2093 if (is_idx[i] < 0 || is_idx[i] >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",is_idx[i]); 2094 zeroed[is_idx[i]] = PETSC_TRUE; 2095 } 2096 for (i=0; i<A->rmap->N; i++) { 2097 if (!zeroed[i]) { 2098 row = i/bs; 2099 for (j=baij->i[row]; j<baij->i[row+1]; j++) { 2100 for (k=0; k<bs; k++) { 2101 col = bs*baij->j[j] + k; 2102 if (zeroed[col]) { 2103 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 2104 if (vecs) bb[i] -= aa[0]*xx[col]; 2105 aa[0] = 0.0; 2106 } 2107 } 2108 } 2109 } else if (vecs) bb[i] = diag*xx[i]; 2110 } 2111 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2112 if (vecs) { 2113 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2114 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2115 } 2116 2117 /* zero the rows */ 2118 for (i=0; i<is_n; i++) { 2119 row = is_idx[i]; 2120 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 2121 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 2122 for (k=0; k<count; k++) { 2123 aa[0] = zero; 2124 aa += bs; 2125 } 2126 if (diag != (PetscScalar)0.0) { 2127 ierr = (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 2128 } 2129 } 2130 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2131 PetscFunctionReturn(0); 2132 } 2133 2134 #undef __FUNCT__ 2135 #define __FUNCT__ "MatSetValues_SeqBAIJ" 2136 PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 2137 { 2138 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2139 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1; 2140 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 2141 PetscInt *aj =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol; 2142 PetscErrorCode ierr; 2143 PetscInt ridx,cidx,bs2=a->bs2; 2144 PetscBool roworiented=a->roworiented; 2145 MatScalar *ap,value,*aa=a->a,*bap; 2146 2147 PetscFunctionBegin; 2148 for (k=0; k<m; k++) { /* loop over added rows */ 2149 row = im[k]; 2150 brow = row/bs; 2151 if (row < 0) continue; 2152 #if defined(PETSC_USE_DEBUG) 2153 if (row >= A->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1); 2154 #endif 2155 rp = aj + ai[brow]; 2156 ap = aa + bs2*ai[brow]; 2157 rmax = imax[brow]; 2158 nrow = ailen[brow]; 2159 low = 0; 2160 high = nrow; 2161 for (l=0; l<n; l++) { /* loop over added columns */ 2162 if (in[l] < 0) continue; 2163 #if defined(PETSC_USE_DEBUG) 2164 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 2165 #endif 2166 col = in[l]; bcol = col/bs; 2167 ridx = row % bs; cidx = col % bs; 2168 if (roworiented) { 2169 value = v[l + k*n]; 2170 } else { 2171 value = v[k + l*m]; 2172 } 2173 if (col <= lastcol) low = 0; else high = nrow; 2174 lastcol = col; 2175 while (high-low > 7) { 2176 t = (low+high)/2; 2177 if (rp[t] > bcol) high = t; 2178 else low = t; 2179 } 2180 for (i=low; i<high; i++) { 2181 if (rp[i] > bcol) break; 2182 if (rp[i] == bcol) { 2183 bap = ap + bs2*i + bs*cidx + ridx; 2184 if (is == ADD_VALUES) *bap += value; 2185 else *bap = value; 2186 goto noinsert1; 2187 } 2188 } 2189 if (nonew == 1) goto noinsert1; 2190 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 2191 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 2192 N = nrow++ - 1; high++; 2193 /* shift up all the later entries in this row */ 2194 for (ii=N; ii>=i; ii--) { 2195 rp[ii+1] = rp[ii]; 2196 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 2197 } 2198 if (N>=i) { 2199 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 2200 } 2201 rp[i] = bcol; 2202 ap[bs2*i + bs*cidx + ridx] = value; 2203 a->nz++; 2204 A->nonzerostate++; 2205 noinsert1:; 2206 low = i; 2207 } 2208 ailen[brow] = nrow; 2209 } 2210 PetscFunctionReturn(0); 2211 } 2212 2213 #undef __FUNCT__ 2214 #define __FUNCT__ "MatILUFactor_SeqBAIJ" 2215 PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2216 { 2217 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inA->data; 2218 Mat outA; 2219 PetscErrorCode ierr; 2220 PetscBool row_identity,col_identity; 2221 2222 PetscFunctionBegin; 2223 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU"); 2224 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2225 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2226 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU"); 2227 2228 outA = inA; 2229 inA->factortype = MAT_FACTOR_LU; 2230 2231 ierr = MatMarkDiagonal_SeqBAIJ(inA);CHKERRQ(ierr); 2232 2233 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2234 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2235 a->row = row; 2236 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2237 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2238 a->col = col; 2239 2240 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 2241 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2242 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2243 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2244 2245 ierr = MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));CHKERRQ(ierr); 2246 if (!a->solve_work) { 2247 ierr = PetscMalloc1((inA->rmap->N+inA->rmap->bs),&a->solve_work);CHKERRQ(ierr); 2248 ierr = PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));CHKERRQ(ierr); 2249 } 2250 ierr = MatLUFactorNumeric(outA,inA,info);CHKERRQ(ierr); 2251 PetscFunctionReturn(0); 2252 } 2253 2254 #undef __FUNCT__ 2255 #define __FUNCT__ "MatSeqBAIJSetColumnIndices_SeqBAIJ" 2256 PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices) 2257 { 2258 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data; 2259 PetscInt i,nz,mbs; 2260 2261 PetscFunctionBegin; 2262 nz = baij->maxnz; 2263 mbs = baij->mbs; 2264 for (i=0; i<nz; i++) { 2265 baij->j[i] = indices[i]; 2266 } 2267 baij->nz = nz; 2268 for (i=0; i<mbs; i++) { 2269 baij->ilen[i] = baij->imax[i]; 2270 } 2271 PetscFunctionReturn(0); 2272 } 2273 2274 #undef __FUNCT__ 2275 #define __FUNCT__ "MatSeqBAIJSetColumnIndices" 2276 /*@ 2277 MatSeqBAIJSetColumnIndices - Set the column indices for all the rows 2278 in the matrix. 2279 2280 Input Parameters: 2281 + mat - the SeqBAIJ matrix 2282 - indices - the column indices 2283 2284 Level: advanced 2285 2286 Notes: 2287 This can be called if you have precomputed the nonzero structure of the 2288 matrix and want to provide it to the matrix object to improve the performance 2289 of the MatSetValues() operation. 2290 2291 You MUST have set the correct numbers of nonzeros per row in the call to 2292 MatCreateSeqBAIJ(), and the columns indices MUST be sorted. 2293 2294 MUST be called before any calls to MatSetValues(); 2295 2296 @*/ 2297 PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices) 2298 { 2299 PetscErrorCode ierr; 2300 2301 PetscFunctionBegin; 2302 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2303 PetscValidPointer(indices,2); 2304 ierr = PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 2305 PetscFunctionReturn(0); 2306 } 2307 2308 #undef __FUNCT__ 2309 #define __FUNCT__ "MatGetRowMaxAbs_SeqBAIJ" 2310 PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[]) 2311 { 2312 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2313 PetscErrorCode ierr; 2314 PetscInt i,j,n,row,bs,*ai,*aj,mbs; 2315 PetscReal atmp; 2316 PetscScalar *x,zero = 0.0; 2317 MatScalar *aa; 2318 PetscInt ncols,brow,krow,kcol; 2319 2320 PetscFunctionBegin; 2321 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2322 bs = A->rmap->bs; 2323 aa = a->a; 2324 ai = a->i; 2325 aj = a->j; 2326 mbs = a->mbs; 2327 2328 ierr = VecSet(v,zero);CHKERRQ(ierr); 2329 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2330 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2331 if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2332 for (i=0; i<mbs; i++) { 2333 ncols = ai[1] - ai[0]; ai++; 2334 brow = bs*i; 2335 for (j=0; j<ncols; j++) { 2336 for (kcol=0; kcol<bs; kcol++) { 2337 for (krow=0; krow<bs; krow++) { 2338 atmp = PetscAbsScalar(*aa);aa++; 2339 row = brow + krow; /* row index */ 2340 if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;} 2341 } 2342 } 2343 aj++; 2344 } 2345 } 2346 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2347 PetscFunctionReturn(0); 2348 } 2349 2350 #undef __FUNCT__ 2351 #define __FUNCT__ "MatCopy_SeqBAIJ" 2352 PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str) 2353 { 2354 PetscErrorCode ierr; 2355 2356 PetscFunctionBegin; 2357 /* If the two matrices have the same copy implementation, use fast copy. */ 2358 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2359 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2360 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)B->data; 2361 PetscInt ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs; 2362 2363 if (a->i[ambs] != b->i[bmbs]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzero blocks in matrices A %D and B %D are different",a->i[ambs],b->i[bmbs]); 2364 if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs); 2365 ierr = PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));CHKERRQ(ierr); 2366 } else { 2367 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2368 } 2369 PetscFunctionReturn(0); 2370 } 2371 2372 #undef __FUNCT__ 2373 #define __FUNCT__ "MatSetUp_SeqBAIJ" 2374 PetscErrorCode MatSetUp_SeqBAIJ(Mat A) 2375 { 2376 PetscErrorCode ierr; 2377 2378 PetscFunctionBegin; 2379 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(A,A->rmap->bs,PETSC_DEFAULT,0);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatSeqBAIJGetArray_SeqBAIJ" 2385 PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[]) 2386 { 2387 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2388 2389 PetscFunctionBegin; 2390 *array = a->a; 2391 PetscFunctionReturn(0); 2392 } 2393 2394 #undef __FUNCT__ 2395 #define __FUNCT__ "MatSeqBAIJRestoreArray_SeqBAIJ" 2396 PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[]) 2397 { 2398 PetscFunctionBegin; 2399 PetscFunctionReturn(0); 2400 } 2401 2402 #undef __FUNCT__ 2403 #define __FUNCT__ "MatAXPYGetPreallocation_SeqBAIJ" 2404 PetscErrorCode MatAXPYGetPreallocation_SeqBAIJ(Mat Y,Mat X,PetscInt *nnz) 2405 { 2406 PetscInt bs = Y->rmap->bs,mbs = Y->rmap->N/bs; 2407 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 2408 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 2409 PetscErrorCode ierr; 2410 2411 PetscFunctionBegin; 2412 /* Set the number of nonzeros in the new matrix */ 2413 ierr = MatAXPYGetPreallocation_SeqX_private(mbs,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2414 PetscFunctionReturn(0); 2415 } 2416 2417 #undef __FUNCT__ 2418 #define __FUNCT__ "MatAXPY_SeqBAIJ" 2419 PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2420 { 2421 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data; 2422 PetscErrorCode ierr; 2423 PetscInt bs=Y->rmap->bs,bs2=bs*bs; 2424 PetscBLASInt one=1; 2425 2426 PetscFunctionBegin; 2427 if (str == SAME_NONZERO_PATTERN) { 2428 PetscScalar alpha = a; 2429 PetscBLASInt bnz; 2430 ierr = PetscBLASIntCast(x->nz*bs2,&bnz);CHKERRQ(ierr); 2431 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2432 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2433 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2434 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2435 } else { 2436 Mat B; 2437 PetscInt *nnz; 2438 if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size"); 2439 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2440 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2441 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2442 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2443 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2444 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2445 ierr = MatAXPYGetPreallocation_SeqBAIJ(Y,X,nnz);CHKERRQ(ierr); 2446 ierr = MatSeqBAIJSetPreallocation(B,bs,0,nnz);CHKERRQ(ierr); 2447 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2448 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2449 ierr = PetscFree(nnz);CHKERRQ(ierr); 2450 } 2451 PetscFunctionReturn(0); 2452 } 2453 2454 #undef __FUNCT__ 2455 #define __FUNCT__ "MatRealPart_SeqBAIJ" 2456 PetscErrorCode MatRealPart_SeqBAIJ(Mat A) 2457 { 2458 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2459 PetscInt i,nz = a->bs2*a->i[a->mbs]; 2460 MatScalar *aa = a->a; 2461 2462 PetscFunctionBegin; 2463 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 2464 PetscFunctionReturn(0); 2465 } 2466 2467 #undef __FUNCT__ 2468 #define __FUNCT__ "MatImaginaryPart_SeqBAIJ" 2469 PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A) 2470 { 2471 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2472 PetscInt i,nz = a->bs2*a->i[a->mbs]; 2473 MatScalar *aa = a->a; 2474 2475 PetscFunctionBegin; 2476 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 2477 PetscFunctionReturn(0); 2478 } 2479 2480 #undef __FUNCT__ 2481 #define __FUNCT__ "MatGetColumnIJ_SeqBAIJ" 2482 /* 2483 Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code 2484 */ 2485 PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 2486 { 2487 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2488 PetscErrorCode ierr; 2489 PetscInt bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs; 2490 PetscInt nz = a->i[m],row,*jj,mr,col; 2491 2492 PetscFunctionBegin; 2493 *nn = n; 2494 if (!ia) PetscFunctionReturn(0); 2495 if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices"); 2496 else { 2497 ierr = PetscCalloc1((n+1),&collengths);CHKERRQ(ierr); 2498 ierr = PetscMalloc1((n+1),&cia);CHKERRQ(ierr); 2499 ierr = PetscMalloc1((nz+1),&cja);CHKERRQ(ierr); 2500 jj = a->j; 2501 for (i=0; i<nz; i++) { 2502 collengths[jj[i]]++; 2503 } 2504 cia[0] = oshift; 2505 for (i=0; i<n; i++) { 2506 cia[i+1] = cia[i] + collengths[i]; 2507 } 2508 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2509 jj = a->j; 2510 for (row=0; row<m; row++) { 2511 mr = a->i[row+1] - a->i[row]; 2512 for (i=0; i<mr; i++) { 2513 col = *jj++; 2514 2515 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 2516 } 2517 } 2518 ierr = PetscFree(collengths);CHKERRQ(ierr); 2519 *ia = cia; *ja = cja; 2520 } 2521 PetscFunctionReturn(0); 2522 } 2523 2524 #undef __FUNCT__ 2525 #define __FUNCT__ "MatRestoreColumnIJ_SeqBAIJ" 2526 PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 2527 { 2528 PetscErrorCode ierr; 2529 2530 PetscFunctionBegin; 2531 if (!ia) PetscFunctionReturn(0); 2532 ierr = PetscFree(*ia);CHKERRQ(ierr); 2533 ierr = PetscFree(*ja);CHKERRQ(ierr); 2534 PetscFunctionReturn(0); 2535 } 2536 2537 /* 2538 MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from 2539 MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output 2540 spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate() 2541 */ 2542 #undef __FUNCT__ 2543 #define __FUNCT__ "MatGetColumnIJ_SeqBAIJ_Color" 2544 PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 2545 { 2546 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2547 PetscErrorCode ierr; 2548 PetscInt i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs; 2549 PetscInt nz = a->i[m],row,*jj,mr,col; 2550 PetscInt *cspidx; 2551 2552 PetscFunctionBegin; 2553 *nn = n; 2554 if (!ia) PetscFunctionReturn(0); 2555 2556 ierr = PetscCalloc1((n+1),&collengths);CHKERRQ(ierr); 2557 ierr = PetscMalloc1((n+1),&cia);CHKERRQ(ierr); 2558 ierr = PetscMalloc1((nz+1),&cja);CHKERRQ(ierr); 2559 ierr = PetscMalloc1((nz+1),&cspidx);CHKERRQ(ierr); 2560 jj = a->j; 2561 for (i=0; i<nz; i++) { 2562 collengths[jj[i]]++; 2563 } 2564 cia[0] = oshift; 2565 for (i=0; i<n; i++) { 2566 cia[i+1] = cia[i] + collengths[i]; 2567 } 2568 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2569 jj = a->j; 2570 for (row=0; row<m; row++) { 2571 mr = a->i[row+1] - a->i[row]; 2572 for (i=0; i<mr; i++) { 2573 col = *jj++; 2574 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 2575 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 2576 } 2577 } 2578 ierr = PetscFree(collengths);CHKERRQ(ierr); 2579 *ia = cia; *ja = cja; 2580 *spidx = cspidx; 2581 PetscFunctionReturn(0); 2582 } 2583 2584 #undef __FUNCT__ 2585 #define __FUNCT__ "MatRestoreColumnIJ_SeqBAIJ_Color" 2586 PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 2587 { 2588 PetscErrorCode ierr; 2589 2590 PetscFunctionBegin; 2591 ierr = MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 2592 ierr = PetscFree(*spidx);CHKERRQ(ierr); 2593 PetscFunctionReturn(0); 2594 } 2595 2596 /* -------------------------------------------------------------------*/ 2597 static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ, 2598 MatGetRow_SeqBAIJ, 2599 MatRestoreRow_SeqBAIJ, 2600 MatMult_SeqBAIJ_N, 2601 /* 4*/ MatMultAdd_SeqBAIJ_N, 2602 MatMultTranspose_SeqBAIJ, 2603 MatMultTransposeAdd_SeqBAIJ, 2604 0, 2605 0, 2606 0, 2607 /* 10*/ 0, 2608 MatLUFactor_SeqBAIJ, 2609 0, 2610 0, 2611 MatTranspose_SeqBAIJ, 2612 /* 15*/ MatGetInfo_SeqBAIJ, 2613 MatEqual_SeqBAIJ, 2614 MatGetDiagonal_SeqBAIJ, 2615 MatDiagonalScale_SeqBAIJ, 2616 MatNorm_SeqBAIJ, 2617 /* 20*/ 0, 2618 MatAssemblyEnd_SeqBAIJ, 2619 MatSetOption_SeqBAIJ, 2620 MatZeroEntries_SeqBAIJ, 2621 /* 24*/ MatZeroRows_SeqBAIJ, 2622 0, 2623 0, 2624 0, 2625 0, 2626 /* 29*/ MatSetUp_SeqBAIJ, 2627 0, 2628 0, 2629 0, 2630 0, 2631 /* 34*/ MatDuplicate_SeqBAIJ, 2632 0, 2633 0, 2634 MatILUFactor_SeqBAIJ, 2635 0, 2636 /* 39*/ MatAXPY_SeqBAIJ, 2637 MatGetSubMatrices_SeqBAIJ, 2638 MatIncreaseOverlap_SeqBAIJ, 2639 MatGetValues_SeqBAIJ, 2640 MatCopy_SeqBAIJ, 2641 /* 44*/ 0, 2642 MatScale_SeqBAIJ, 2643 0, 2644 0, 2645 MatZeroRowsColumns_SeqBAIJ, 2646 /* 49*/ 0, 2647 MatGetRowIJ_SeqBAIJ, 2648 MatRestoreRowIJ_SeqBAIJ, 2649 MatGetColumnIJ_SeqBAIJ, 2650 MatRestoreColumnIJ_SeqBAIJ, 2651 /* 54*/ MatFDColoringCreate_SeqXAIJ, 2652 0, 2653 0, 2654 0, 2655 MatSetValuesBlocked_SeqBAIJ, 2656 /* 59*/ MatGetSubMatrix_SeqBAIJ, 2657 MatDestroy_SeqBAIJ, 2658 MatView_SeqBAIJ, 2659 0, 2660 0, 2661 /* 64*/ 0, 2662 0, 2663 0, 2664 0, 2665 0, 2666 /* 69*/ MatGetRowMaxAbs_SeqBAIJ, 2667 0, 2668 MatConvert_Basic, 2669 0, 2670 0, 2671 /* 74*/ 0, 2672 MatFDColoringApply_BAIJ, 2673 0, 2674 0, 2675 0, 2676 /* 79*/ 0, 2677 0, 2678 0, 2679 0, 2680 MatLoad_SeqBAIJ, 2681 /* 84*/ 0, 2682 0, 2683 0, 2684 0, 2685 0, 2686 /* 89*/ 0, 2687 0, 2688 0, 2689 0, 2690 0, 2691 /* 94*/ 0, 2692 0, 2693 0, 2694 0, 2695 0, 2696 /* 99*/ 0, 2697 0, 2698 0, 2699 0, 2700 0, 2701 /*104*/ 0, 2702 MatRealPart_SeqBAIJ, 2703 MatImaginaryPart_SeqBAIJ, 2704 0, 2705 0, 2706 /*109*/ 0, 2707 0, 2708 0, 2709 0, 2710 MatMissingDiagonal_SeqBAIJ, 2711 /*114*/ 0, 2712 0, 2713 0, 2714 0, 2715 0, 2716 /*119*/ 0, 2717 0, 2718 MatMultHermitianTranspose_SeqBAIJ, 2719 MatMultHermitianTransposeAdd_SeqBAIJ, 2720 0, 2721 /*124*/ 0, 2722 0, 2723 MatInvertBlockDiagonal_SeqBAIJ, 2724 0, 2725 0, 2726 /*129*/ 0, 2727 0, 2728 0, 2729 0, 2730 0, 2731 /*134*/ 0, 2732 0, 2733 0, 2734 0, 2735 0, 2736 /*139*/ 0, 2737 0, 2738 0, 2739 MatFDColoringSetUp_SeqXAIJ 2740 }; 2741 2742 #undef __FUNCT__ 2743 #define __FUNCT__ "MatStoreValues_SeqBAIJ" 2744 PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat) 2745 { 2746 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data; 2747 PetscInt nz = aij->i[aij->mbs]*aij->bs2; 2748 PetscErrorCode ierr; 2749 2750 PetscFunctionBegin; 2751 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2752 2753 /* allocate space for values if not already there */ 2754 if (!aij->saved_values) { 2755 ierr = PetscMalloc1((nz+1),&aij->saved_values);CHKERRQ(ierr); 2756 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2757 } 2758 2759 /* copy values over */ 2760 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2761 PetscFunctionReturn(0); 2762 } 2763 2764 #undef __FUNCT__ 2765 #define __FUNCT__ "MatRetrieveValues_SeqBAIJ" 2766 PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat) 2767 { 2768 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data; 2769 PetscErrorCode ierr; 2770 PetscInt nz = aij->i[aij->mbs]*aij->bs2; 2771 2772 PetscFunctionBegin; 2773 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2774 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2775 2776 /* copy values over */ 2777 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2778 PetscFunctionReturn(0); 2779 } 2780 2781 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*); 2782 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*); 2783 2784 #undef __FUNCT__ 2785 #define __FUNCT__ "MatSeqBAIJSetPreallocation_SeqBAIJ" 2786 PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz) 2787 { 2788 Mat_SeqBAIJ *b; 2789 PetscErrorCode ierr; 2790 PetscInt i,mbs,nbs,bs2; 2791 PetscBool flg,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 2792 2793 PetscFunctionBegin; 2794 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 2795 if (nz == MAT_SKIP_ALLOCATION) { 2796 skipallocation = PETSC_TRUE; 2797 nz = 0; 2798 } 2799 2800 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2801 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2802 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2803 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2804 2805 B->preallocated = PETSC_TRUE; 2806 2807 mbs = B->rmap->n/bs; 2808 nbs = B->cmap->n/bs; 2809 bs2 = bs*bs; 2810 2811 if (mbs*bs!=B->rmap->n || nbs*bs!=B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->rmap->N,B->cmap->n,bs); 2812 2813 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2814 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 2815 if (nnz) { 2816 for (i=0; i<mbs; i++) { 2817 if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]); 2818 if (nnz[i] > nbs) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],nbs); 2819 } 2820 } 2821 2822 b = (Mat_SeqBAIJ*)B->data; 2823 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");CHKERRQ(ierr); 2824 ierr = PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 2825 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2826 2827 if (!flg) { 2828 switch (bs) { 2829 case 1: 2830 B->ops->mult = MatMult_SeqBAIJ_1; 2831 B->ops->multadd = MatMultAdd_SeqBAIJ_1; 2832 break; 2833 case 2: 2834 B->ops->mult = MatMult_SeqBAIJ_2; 2835 B->ops->multadd = MatMultAdd_SeqBAIJ_2; 2836 break; 2837 case 3: 2838 B->ops->mult = MatMult_SeqBAIJ_3; 2839 B->ops->multadd = MatMultAdd_SeqBAIJ_3; 2840 break; 2841 case 4: 2842 B->ops->mult = MatMult_SeqBAIJ_4; 2843 B->ops->multadd = MatMultAdd_SeqBAIJ_4; 2844 break; 2845 case 5: 2846 B->ops->mult = MatMult_SeqBAIJ_5; 2847 B->ops->multadd = MatMultAdd_SeqBAIJ_5; 2848 break; 2849 case 6: 2850 B->ops->mult = MatMult_SeqBAIJ_6; 2851 B->ops->multadd = MatMultAdd_SeqBAIJ_6; 2852 break; 2853 case 7: 2854 B->ops->mult = MatMult_SeqBAIJ_7; 2855 B->ops->multadd = MatMultAdd_SeqBAIJ_7; 2856 break; 2857 case 15: 2858 B->ops->mult = MatMult_SeqBAIJ_15_ver1; 2859 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2860 break; 2861 default: 2862 B->ops->mult = MatMult_SeqBAIJ_N; 2863 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2864 break; 2865 } 2866 } 2867 B->ops->sor = MatSOR_SeqBAIJ; 2868 b->mbs = mbs; 2869 b->nbs = nbs; 2870 if (!skipallocation) { 2871 if (!b->imax) { 2872 ierr = PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);CHKERRQ(ierr); 2873 ierr = PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));CHKERRQ(ierr); 2874 2875 b->free_imax_ilen = PETSC_TRUE; 2876 } 2877 /* b->ilen will count nonzeros in each block row so far. */ 2878 for (i=0; i<mbs; i++) b->ilen[i] = 0; 2879 if (!nnz) { 2880 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2881 else if (nz < 0) nz = 1; 2882 for (i=0; i<mbs; i++) b->imax[i] = nz; 2883 nz = nz*mbs; 2884 } else { 2885 nz = 0; 2886 for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 2887 } 2888 2889 /* allocate the matrix space */ 2890 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 2891 ierr = PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);CHKERRQ(ierr); 2892 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 2893 ierr = PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));CHKERRQ(ierr); 2894 ierr = PetscMemzero(b->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 2895 2896 b->singlemalloc = PETSC_TRUE; 2897 b->i[0] = 0; 2898 for (i=1; i<mbs+1; i++) { 2899 b->i[i] = b->i[i-1] + b->imax[i-1]; 2900 } 2901 b->free_a = PETSC_TRUE; 2902 b->free_ij = PETSC_TRUE; 2903 #if defined(PETSC_THREADCOMM_ACTIVE) 2904 ierr = MatZeroEntries_SeqBAIJ(B);CHKERRQ(ierr); 2905 #endif 2906 } else { 2907 b->free_a = PETSC_FALSE; 2908 b->free_ij = PETSC_FALSE; 2909 } 2910 2911 b->bs2 = bs2; 2912 b->mbs = mbs; 2913 b->nz = 0; 2914 b->maxnz = nz; 2915 B->info.nz_unneeded = (PetscReal)b->maxnz*bs2; 2916 if (realalloc) {ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);} 2917 PetscFunctionReturn(0); 2918 } 2919 2920 #undef __FUNCT__ 2921 #define __FUNCT__ "MatSeqBAIJSetPreallocationCSR_SeqBAIJ" 2922 PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2923 { 2924 PetscInt i,m,nz,nz_max=0,*nnz; 2925 PetscScalar *values=0; 2926 PetscBool roworiented = ((Mat_SeqBAIJ*)B->data)->roworiented; 2927 PetscErrorCode ierr; 2928 2929 PetscFunctionBegin; 2930 if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 2931 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2932 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2933 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2934 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2935 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2936 m = B->rmap->n/bs; 2937 2938 if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]); 2939 ierr = PetscMalloc1((m+1), &nnz);CHKERRQ(ierr); 2940 for (i=0; i<m; i++) { 2941 nz = ii[i+1]- ii[i]; 2942 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz); 2943 nz_max = PetscMax(nz_max, nz); 2944 nnz[i] = nz; 2945 } 2946 ierr = MatSeqBAIJSetPreallocation(B,bs,0,nnz);CHKERRQ(ierr); 2947 ierr = PetscFree(nnz);CHKERRQ(ierr); 2948 2949 values = (PetscScalar*)V; 2950 if (!values) { 2951 ierr = PetscCalloc1(bs*bs*(nz_max+1),&values);CHKERRQ(ierr); 2952 } 2953 for (i=0; i<m; i++) { 2954 PetscInt ncols = ii[i+1] - ii[i]; 2955 const PetscInt *icols = jj + ii[i]; 2956 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2957 if (!roworiented) { 2958 ierr = MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2959 } else { 2960 PetscInt j; 2961 for (j=0; j<ncols; j++) { 2962 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2963 ierr = MatSetValuesBlocked_SeqBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2964 } 2965 } 2966 } 2967 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2968 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2969 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2970 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2971 PetscFunctionReturn(0); 2972 } 2973 2974 PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_petsc(Mat,MatFactorType,Mat*); 2975 PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_bstrm(Mat,MatFactorType,Mat*); 2976 #if defined(PETSC_HAVE_MUMPS) 2977 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2978 #endif 2979 extern PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat,MatFactorType,PetscBool*); 2980 2981 /*MC 2982 MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on 2983 block sparse compressed row format. 2984 2985 Options Database Keys: 2986 . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions() 2987 2988 Level: beginner 2989 2990 .seealso: MatCreateSeqBAIJ() 2991 M*/ 2992 2993 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*); 2994 2995 #undef __FUNCT__ 2996 #define __FUNCT__ "MatCreate_SeqBAIJ" 2997 PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B) 2998 { 2999 PetscErrorCode ierr; 3000 PetscMPIInt size; 3001 Mat_SeqBAIJ *b; 3002 3003 PetscFunctionBegin; 3004 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3005 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 3006 3007 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3008 B->data = (void*)b; 3009 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3010 3011 b->row = 0; 3012 b->col = 0; 3013 b->icol = 0; 3014 b->reallocs = 0; 3015 b->saved_values = 0; 3016 3017 b->roworiented = PETSC_TRUE; 3018 b->nonew = 0; 3019 b->diag = 0; 3020 B->spptr = 0; 3021 B->info.nz_unneeded = (PetscReal)b->maxnz*b->bs2; 3022 b->keepnonzeropattern = PETSC_FALSE; 3023 b->xtoy = 0; 3024 b->XtoY = 0; 3025 3026 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqbaij_petsc);CHKERRQ(ierr); 3027 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqbaij_petsc);CHKERRQ(ierr); 3028 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bstrm_C",MatGetFactor_seqbaij_bstrm);CHKERRQ(ierr); 3029 #if defined(PETSC_HAVE_MUMPS) 3030 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C", MatGetFactor_baij_mumps);CHKERRQ(ierr); 3031 #endif 3032 ierr = PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);CHKERRQ(ierr); 3033 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);CHKERRQ(ierr); 3034 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);CHKERRQ(ierr); 3035 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);CHKERRQ(ierr); 3036 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);CHKERRQ(ierr); 3037 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);CHKERRQ(ierr); 3038 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);CHKERRQ(ierr); 3039 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);CHKERRQ(ierr); 3040 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqbstrm_C",MatConvert_SeqBAIJ_SeqBSTRM);CHKERRQ(ierr); 3041 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);CHKERRQ(ierr); 3042 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);CHKERRQ(ierr); 3043 PetscFunctionReturn(0); 3044 } 3045 3046 #undef __FUNCT__ 3047 #define __FUNCT__ "MatDuplicateNoCreate_SeqBAIJ" 3048 PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 3049 { 3050 Mat_SeqBAIJ *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data; 3051 PetscErrorCode ierr; 3052 PetscInt i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2; 3053 3054 PetscFunctionBegin; 3055 if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix"); 3056 3057 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3058 c->imax = a->imax; 3059 c->ilen = a->ilen; 3060 c->free_imax_ilen = PETSC_FALSE; 3061 } else { 3062 ierr = PetscMalloc2(mbs,&c->imax,mbs,&c->ilen);CHKERRQ(ierr); 3063 ierr = PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));CHKERRQ(ierr); 3064 for (i=0; i<mbs; i++) { 3065 c->imax[i] = a->imax[i]; 3066 c->ilen[i] = a->ilen[i]; 3067 } 3068 c->free_imax_ilen = PETSC_TRUE; 3069 } 3070 3071 /* allocate the matrix space */ 3072 if (mallocmatspace) { 3073 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3074 ierr = PetscCalloc1(bs2*nz,&c->a);CHKERRQ(ierr); 3075 ierr = PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));CHKERRQ(ierr); 3076 3077 c->i = a->i; 3078 c->j = a->j; 3079 c->singlemalloc = PETSC_FALSE; 3080 c->free_a = PETSC_TRUE; 3081 c->free_ij = PETSC_FALSE; 3082 c->parent = A; 3083 C->preallocated = PETSC_TRUE; 3084 C->assembled = PETSC_TRUE; 3085 3086 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 3087 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3088 ierr = MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3089 } else { 3090 ierr = PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);CHKERRQ(ierr); 3091 ierr = PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3092 3093 c->singlemalloc = PETSC_TRUE; 3094 c->free_a = PETSC_TRUE; 3095 c->free_ij = PETSC_TRUE; 3096 3097 ierr = PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3098 if (mbs > 0) { 3099 ierr = PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 3100 if (cpvalues == MAT_COPY_VALUES) { 3101 ierr = PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 3102 } else { 3103 ierr = PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 3104 } 3105 } 3106 C->preallocated = PETSC_TRUE; 3107 C->assembled = PETSC_TRUE; 3108 } 3109 } 3110 3111 c->roworiented = a->roworiented; 3112 c->nonew = a->nonew; 3113 3114 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 3115 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 3116 3117 c->bs2 = a->bs2; 3118 c->mbs = a->mbs; 3119 c->nbs = a->nbs; 3120 3121 if (a->diag) { 3122 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3123 c->diag = a->diag; 3124 c->free_diag = PETSC_FALSE; 3125 } else { 3126 ierr = PetscMalloc1((mbs+1),&c->diag);CHKERRQ(ierr); 3127 ierr = PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3128 for (i=0; i<mbs; i++) c->diag[i] = a->diag[i]; 3129 c->free_diag = PETSC_TRUE; 3130 } 3131 } else c->diag = 0; 3132 3133 c->nz = a->nz; 3134 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 3135 c->solve_work = NULL; 3136 c->mult_work = NULL; 3137 c->sor_workt = NULL; 3138 c->sor_work = NULL; 3139 3140 c->compressedrow.use = a->compressedrow.use; 3141 c->compressedrow.nrows = a->compressedrow.nrows; 3142 if (a->compressedrow.use) { 3143 i = a->compressedrow.nrows; 3144 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i+1,&c->compressedrow.rindex);CHKERRQ(ierr); 3145 ierr = PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3146 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3147 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 3148 } else { 3149 c->compressedrow.use = PETSC_FALSE; 3150 c->compressedrow.i = NULL; 3151 c->compressedrow.rindex = NULL; 3152 } 3153 C->nonzerostate = A->nonzerostate; 3154 3155 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 3156 ierr = PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3157 PetscFunctionReturn(0); 3158 } 3159 3160 #undef __FUNCT__ 3161 #define __FUNCT__ "MatDuplicate_SeqBAIJ" 3162 PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 3163 { 3164 PetscErrorCode ierr; 3165 3166 PetscFunctionBegin; 3167 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 3168 ierr = MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);CHKERRQ(ierr); 3169 ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr); 3170 ierr = MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 3171 PetscFunctionReturn(0); 3172 } 3173 3174 #undef __FUNCT__ 3175 #define __FUNCT__ "MatLoad_SeqBAIJ" 3176 PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer) 3177 { 3178 Mat_SeqBAIJ *a; 3179 PetscErrorCode ierr; 3180 PetscInt i,nz,header[4],*rowlengths=0,M,N,bs = newmat->rmap->bs; 3181 PetscInt *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount; 3182 PetscInt kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols; 3183 PetscInt *masked,nmask,tmp,bs2,ishift; 3184 PetscMPIInt size; 3185 int fd; 3186 PetscScalar *aa; 3187 MPI_Comm comm; 3188 3189 PetscFunctionBegin; 3190 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3191 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");CHKERRQ(ierr); 3192 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3193 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3194 if (bs < 0) bs = 1; 3195 bs2 = bs*bs; 3196 3197 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3198 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 3199 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3200 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 3201 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object"); 3202 M = header[1]; N = header[2]; nz = header[3]; 3203 3204 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ"); 3205 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 3206 3207 /* 3208 This code adds extra rows to make sure the number of rows is 3209 divisible by the blocksize 3210 */ 3211 mbs = M/bs; 3212 extra_rows = bs - M + bs*(mbs); 3213 if (extra_rows == bs) extra_rows = 0; 3214 else mbs++; 3215 if (extra_rows) { 3216 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3217 } 3218 3219 /* Set global sizes if not already set */ 3220 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 3221 ierr = MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3222 } else { /* Check if the matrix global sizes are correct */ 3223 ierr = MatGetSize(newmat,&rows,&cols);CHKERRQ(ierr); 3224 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 3225 ierr = MatGetLocalSize(newmat,&rows,&cols);CHKERRQ(ierr); 3226 } 3227 if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,rows,cols); 3228 } 3229 3230 /* read in row lengths */ 3231 ierr = PetscMalloc1((M+extra_rows),&rowlengths);CHKERRQ(ierr); 3232 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 3233 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 3234 3235 /* read in column indices */ 3236 ierr = PetscMalloc1((nz+extra_rows),&jj);CHKERRQ(ierr); 3237 ierr = PetscBinaryRead(fd,jj,nz,PETSC_INT);CHKERRQ(ierr); 3238 for (i=0; i<extra_rows; i++) jj[nz+i] = M+i; 3239 3240 /* loop over row lengths determining block row lengths */ 3241 ierr = PetscCalloc1(mbs,&browlengths);CHKERRQ(ierr); 3242 ierr = PetscMalloc2(mbs,&mask,mbs,&masked);CHKERRQ(ierr); 3243 ierr = PetscMemzero(mask,mbs*sizeof(PetscInt));CHKERRQ(ierr); 3244 rowcount = 0; 3245 nzcount = 0; 3246 for (i=0; i<mbs; i++) { 3247 nmask = 0; 3248 for (j=0; j<bs; j++) { 3249 kmax = rowlengths[rowcount]; 3250 for (k=0; k<kmax; k++) { 3251 tmp = jj[nzcount++]/bs; 3252 if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;} 3253 } 3254 rowcount++; 3255 } 3256 browlengths[i] += nmask; 3257 /* zero out the mask elements we set */ 3258 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 3259 } 3260 3261 /* Do preallocation */ 3262 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(newmat,bs,0,browlengths);CHKERRQ(ierr); 3263 a = (Mat_SeqBAIJ*)newmat->data; 3264 3265 /* set matrix "i" values */ 3266 a->i[0] = 0; 3267 for (i=1; i<= mbs; i++) { 3268 a->i[i] = a->i[i-1] + browlengths[i-1]; 3269 a->ilen[i-1] = browlengths[i-1]; 3270 } 3271 a->nz = 0; 3272 for (i=0; i<mbs; i++) a->nz += browlengths[i]; 3273 3274 /* read in nonzero values */ 3275 ierr = PetscMalloc1((nz+extra_rows),&aa);CHKERRQ(ierr); 3276 ierr = PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);CHKERRQ(ierr); 3277 for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0; 3278 3279 /* set "a" and "j" values into matrix */ 3280 nzcount = 0; jcount = 0; 3281 for (i=0; i<mbs; i++) { 3282 nzcountb = nzcount; 3283 nmask = 0; 3284 for (j=0; j<bs; j++) { 3285 kmax = rowlengths[i*bs+j]; 3286 for (k=0; k<kmax; k++) { 3287 tmp = jj[nzcount++]/bs; 3288 if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;} 3289 } 3290 } 3291 /* sort the masked values */ 3292 ierr = PetscSortInt(nmask,masked);CHKERRQ(ierr); 3293 3294 /* set "j" values into matrix */ 3295 maskcount = 1; 3296 for (j=0; j<nmask; j++) { 3297 a->j[jcount++] = masked[j]; 3298 mask[masked[j]] = maskcount++; 3299 } 3300 /* set "a" values into matrix */ 3301 ishift = bs2*a->i[i]; 3302 for (j=0; j<bs; j++) { 3303 kmax = rowlengths[i*bs+j]; 3304 for (k=0; k<kmax; k++) { 3305 tmp = jj[nzcountb]/bs; 3306 block = mask[tmp] - 1; 3307 point = jj[nzcountb] - bs*tmp; 3308 idx = ishift + bs2*block + j + bs*point; 3309 a->a[idx] = (MatScalar)aa[nzcountb++]; 3310 } 3311 } 3312 /* zero out the mask elements we set */ 3313 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 3314 } 3315 if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix"); 3316 3317 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3318 ierr = PetscFree(browlengths);CHKERRQ(ierr); 3319 ierr = PetscFree(aa);CHKERRQ(ierr); 3320 ierr = PetscFree(jj);CHKERRQ(ierr); 3321 ierr = PetscFree2(mask,masked);CHKERRQ(ierr); 3322 3323 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3324 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3325 PetscFunctionReturn(0); 3326 } 3327 3328 #undef __FUNCT__ 3329 #define __FUNCT__ "MatCreateSeqBAIJ" 3330 /*@C 3331 MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block 3332 compressed row) format. For good matrix assembly performance the 3333 user should preallocate the matrix storage by setting the parameter nz 3334 (or the array nnz). By setting these parameters accurately, performance 3335 during matrix assembly can be increased by more than a factor of 50. 3336 3337 Collective on MPI_Comm 3338 3339 Input Parameters: 3340 + comm - MPI communicator, set to PETSC_COMM_SELF 3341 . bs - size of block 3342 . m - number of rows 3343 . n - number of columns 3344 . nz - number of nonzero blocks per block row (same for all rows) 3345 - nnz - array containing the number of nonzero blocks in the various block rows 3346 (possibly different for each block row) or NULL 3347 3348 Output Parameter: 3349 . A - the matrix 3350 3351 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3352 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3353 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3354 3355 Options Database Keys: 3356 . -mat_no_unroll - uses code that does not unroll the loops in the 3357 block calculations (much slower) 3358 . -mat_block_size - size of the blocks to use 3359 3360 Level: intermediate 3361 3362 Notes: 3363 The number of rows and columns must be divisible by blocksize. 3364 3365 If the nnz parameter is given then the nz parameter is ignored 3366 3367 A nonzero block is any block that as 1 or more nonzeros in it 3368 3369 The block AIJ format is fully compatible with standard Fortran 77 3370 storage. That is, the stored row and column indices can begin at 3371 either one (as in Fortran) or zero. See the users' manual for details. 3372 3373 Specify the preallocated storage with either nz or nnz (not both). 3374 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3375 allocation. See Users-Manual: ch_mat for details. 3376 matrices. 3377 3378 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ() 3379 @*/ 3380 PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3381 { 3382 PetscErrorCode ierr; 3383 3384 PetscFunctionBegin; 3385 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3386 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3387 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3388 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(*A,bs,nz,(PetscInt*)nnz);CHKERRQ(ierr); 3389 PetscFunctionReturn(0); 3390 } 3391 3392 #undef __FUNCT__ 3393 #define __FUNCT__ "MatSeqBAIJSetPreallocation" 3394 /*@C 3395 MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros 3396 per row in the matrix. For good matrix assembly performance the 3397 user should preallocate the matrix storage by setting the parameter nz 3398 (or the array nnz). By setting these parameters accurately, performance 3399 during matrix assembly can be increased by more than a factor of 50. 3400 3401 Collective on MPI_Comm 3402 3403 Input Parameters: 3404 + B - the matrix 3405 . bs - size of block 3406 . nz - number of block nonzeros per block row (same for all rows) 3407 - nnz - array containing the number of block nonzeros in the various block rows 3408 (possibly different for each block row) or NULL 3409 3410 Options Database Keys: 3411 . -mat_no_unroll - uses code that does not unroll the loops in the 3412 block calculations (much slower) 3413 . -mat_block_size - size of the blocks to use 3414 3415 Level: intermediate 3416 3417 Notes: 3418 If the nnz parameter is given then the nz parameter is ignored 3419 3420 You can call MatGetInfo() to get information on how effective the preallocation was; 3421 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3422 You can also run with the option -info and look for messages with the string 3423 malloc in them to see if additional memory allocation was needed. 3424 3425 The block AIJ format is fully compatible with standard Fortran 77 3426 storage. That is, the stored row and column indices can begin at 3427 either one (as in Fortran) or zero. See the users' manual for details. 3428 3429 Specify the preallocated storage with either nz or nnz (not both). 3430 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3431 allocation. See Users-Manual: ch_mat for details. 3432 3433 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo() 3434 @*/ 3435 PetscErrorCode MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[]) 3436 { 3437 PetscErrorCode ierr; 3438 3439 PetscFunctionBegin; 3440 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3441 PetscValidType(B,1); 3442 PetscValidLogicalCollectiveInt(B,bs,2); 3443 ierr = PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));CHKERRQ(ierr); 3444 PetscFunctionReturn(0); 3445 } 3446 3447 #undef __FUNCT__ 3448 #define __FUNCT__ "MatSeqBAIJSetPreallocationCSR" 3449 /*@C 3450 MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format 3451 (the default sequential PETSc format). 3452 3453 Collective on MPI_Comm 3454 3455 Input Parameters: 3456 + B - the matrix 3457 . i - the indices into j for the start of each local row (starts with zero) 3458 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3459 - v - optional values in the matrix 3460 3461 Level: developer 3462 3463 Notes: 3464 The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 3465 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 3466 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 3467 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 3468 block column and the second index is over columns within a block. 3469 3470 .keywords: matrix, aij, compressed row, sparse 3471 3472 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ 3473 @*/ 3474 PetscErrorCode MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3475 { 3476 PetscErrorCode ierr; 3477 3478 PetscFunctionBegin; 3479 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3480 PetscValidType(B,1); 3481 PetscValidLogicalCollectiveInt(B,bs,2); 3482 ierr = PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 3483 PetscFunctionReturn(0); 3484 } 3485 3486 3487 #undef __FUNCT__ 3488 #define __FUNCT__ "MatCreateSeqBAIJWithArrays" 3489 /*@ 3490 MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user. 3491 3492 Collective on MPI_Comm 3493 3494 Input Parameters: 3495 + comm - must be an MPI communicator of size 1 3496 . bs - size of block 3497 . m - number of rows 3498 . n - number of columns 3499 . i - row indices 3500 . j - column indices 3501 - a - matrix values 3502 3503 Output Parameter: 3504 . mat - the matrix 3505 3506 Level: advanced 3507 3508 Notes: 3509 The i, j, and a arrays are not copied by this routine, the user must free these arrays 3510 once the matrix is destroyed 3511 3512 You cannot set new nonzero locations into this matrix, that will generate an error. 3513 3514 The i and j indices are 0 based 3515 3516 When block size is greater than 1 the matrix values must be stored using the BAIJ storage format (see the BAIJ code to determine this). 3517 3518 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3519 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3520 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3521 with column-major ordering within blocks. 3522 3523 .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ() 3524 3525 @*/ 3526 PetscErrorCode MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 3527 { 3528 PetscErrorCode ierr; 3529 PetscInt ii; 3530 Mat_SeqBAIJ *baij; 3531 3532 PetscFunctionBegin; 3533 if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs); 3534 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3535 3536 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3537 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 3538 ierr = MatSetType(*mat,MATSEQBAIJ);CHKERRQ(ierr); 3539 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 3540 baij = (Mat_SeqBAIJ*)(*mat)->data; 3541 ierr = PetscMalloc2(m,&baij->imax,m,&baij->ilen);CHKERRQ(ierr); 3542 ierr = PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));CHKERRQ(ierr); 3543 3544 baij->i = i; 3545 baij->j = j; 3546 baij->a = a; 3547 3548 baij->singlemalloc = PETSC_FALSE; 3549 baij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 3550 baij->free_a = PETSC_FALSE; 3551 baij->free_ij = PETSC_FALSE; 3552 3553 for (ii=0; ii<m; ii++) { 3554 baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii]; 3555 #if defined(PETSC_USE_DEBUG) 3556 if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]); 3557 #endif 3558 } 3559 #if defined(PETSC_USE_DEBUG) 3560 for (ii=0; ii<baij->i[m]; ii++) { 3561 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 3562 if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]); 3563 } 3564 #endif 3565 3566 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3567 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3568 PetscFunctionReturn(0); 3569 } 3570