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 = PetscMalloc(2*bs2*mbs*sizeof(PetscScalar),&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,MatScalar,&v_work,bs,PetscInt,&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 = PetscMalloc((2*k+1)*sizeof(PetscScalar),&a->mult_work);CHKERRQ(ierr); 156 } 157 work = a->mult_work; 158 t = work + k+1; 159 if (!a->sor_work) { 160 ierr = PetscMalloc(bs*sizeof(PetscScalar),&a->sor_work);CHKERRQ(ierr); 161 } 162 w = a->sor_work; 163 164 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 165 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 166 167 if (flag & SOR_ZERO_INITIAL_GUESS) { 168 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 169 switch (bs) { 170 case 1: 171 PetscKernel_v_gets_A_times_w_1(x,idiag,b); 172 t[0] = b[0]; 173 i2 = 1; 174 idiag += 1; 175 for (i=1; i<m; i++) { 176 v = aa + ai[i]; 177 vi = aj + ai[i]; 178 nz = diag[i] - ai[i]; 179 s[0] = b[i2]; 180 for (j=0; j<nz; j++) { 181 xw[0] = x[vi[j]]; 182 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 183 } 184 t[i2] = s[0]; 185 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 186 x[i2] = xw[0]; 187 idiag += 1; 188 i2 += 1; 189 } 190 break; 191 case 2: 192 PetscKernel_v_gets_A_times_w_2(x,idiag,b); 193 t[0] = b[0]; t[1] = b[1]; 194 i2 = 2; 195 idiag += 4; 196 for (i=1; i<m; i++) { 197 v = aa + 4*ai[i]; 198 vi = aj + ai[i]; 199 nz = diag[i] - ai[i]; 200 s[0] = b[i2]; s[1] = b[i2+1]; 201 for (j=0; j<nz; j++) { 202 idx = 2*vi[j]; 203 it = 4*j; 204 xw[0] = x[idx]; xw[1] = x[1+idx]; 205 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 206 } 207 t[i2] = s[0]; t[i2+1] = s[1]; 208 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 209 x[i2] = xw[0]; x[i2+1] = xw[1]; 210 idiag += 4; 211 i2 += 2; 212 } 213 break; 214 case 3: 215 PetscKernel_v_gets_A_times_w_3(x,idiag,b); 216 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; 217 i2 = 3; 218 idiag += 9; 219 for (i=1; i<m; i++) { 220 v = aa + 9*ai[i]; 221 vi = aj + ai[i]; 222 nz = diag[i] - ai[i]; 223 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 224 while (nz--) { 225 idx = 3*(*vi++); 226 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 227 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 228 v += 9; 229 } 230 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 231 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 232 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 233 idiag += 9; 234 i2 += 3; 235 } 236 break; 237 case 4: 238 PetscKernel_v_gets_A_times_w_4(x,idiag,b); 239 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; 240 i2 = 4; 241 idiag += 16; 242 for (i=1; i<m; i++) { 243 v = aa + 16*ai[i]; 244 vi = aj + ai[i]; 245 nz = diag[i] - ai[i]; 246 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 247 while (nz--) { 248 idx = 4*(*vi++); 249 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 250 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 251 v += 16; 252 } 253 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3]; 254 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 255 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 256 idiag += 16; 257 i2 += 4; 258 } 259 break; 260 case 5: 261 PetscKernel_v_gets_A_times_w_5(x,idiag,b); 262 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; 263 i2 = 5; 264 idiag += 25; 265 for (i=1; i<m; i++) { 266 v = aa + 25*ai[i]; 267 vi = aj + ai[i]; 268 nz = diag[i] - ai[i]; 269 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 270 while (nz--) { 271 idx = 5*(*vi++); 272 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 273 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 274 v += 25; 275 } 276 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4]; 277 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 278 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 279 idiag += 25; 280 i2 += 5; 281 } 282 break; 283 case 6: 284 PetscKernel_v_gets_A_times_w_6(x,idiag,b); 285 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; 286 i2 = 6; 287 idiag += 36; 288 for (i=1; i<m; i++) { 289 v = aa + 36*ai[i]; 290 vi = aj + ai[i]; 291 nz = diag[i] - ai[i]; 292 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]; 293 while (nz--) { 294 idx = 6*(*vi++); 295 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 296 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 297 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 298 v += 36; 299 } 300 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 301 t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; 302 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 303 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]; 304 idiag += 36; 305 i2 += 6; 306 } 307 break; 308 case 7: 309 PetscKernel_v_gets_A_times_w_7(x,idiag,b); 310 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; 311 t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6]; 312 i2 = 7; 313 idiag += 49; 314 for (i=1; i<m; i++) { 315 v = aa + 49*ai[i]; 316 vi = aj + ai[i]; 317 nz = diag[i] - ai[i]; 318 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 319 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 320 while (nz--) { 321 idx = 7*(*vi++); 322 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 323 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 324 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 325 v += 49; 326 } 327 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 328 t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6]; 329 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 330 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 331 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 332 idiag += 49; 333 i2 += 7; 334 } 335 break; 336 default: 337 PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x); 338 ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); 339 i2 = bs; 340 idiag += bs2; 341 for (i=1; i<m; i++) { 342 v = aa + bs2*ai[i]; 343 vi = aj + ai[i]; 344 nz = diag[i] - ai[i]; 345 346 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 347 /* copy all rows of x that are needed into contiguous space */ 348 workt = work; 349 for (j=0; j<nz; j++) { 350 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 351 workt += bs; 352 } 353 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 354 ierr = PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));CHKERRQ(ierr); 355 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 356 357 idiag += bs2; 358 i2 += bs; 359 } 360 break; 361 } 362 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 363 ierr = PetscLogFlops(1.0*bs2*a->nz);CHKERRQ(ierr); 364 xb = t; 365 } 366 else xb = b; 367 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 368 idiag = a->idiag+bs2*(a->mbs-1); 369 i2 = bs * (m-1); 370 switch (bs) { 371 case 1: 372 s[0] = xb[i2]; 373 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 374 x[i2] = xw[0]; 375 i2 -= 1; 376 for (i=m-2; i>=0; i--) { 377 v = aa + (diag[i]+1); 378 vi = aj + diag[i] + 1; 379 nz = ai[i+1] - diag[i] - 1; 380 s[0] = xb[i2]; 381 for (j=0; j<nz; j++) { 382 xw[0] = x[vi[j]]; 383 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 384 } 385 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 386 x[i2] = xw[0]; 387 idiag -= 1; 388 i2 -= 1; 389 } 390 break; 391 case 2: 392 s[0] = xb[i2]; s[1] = xb[i2+1]; 393 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 394 x[i2] = xw[0]; x[i2+1] = xw[1]; 395 i2 -= 2; 396 idiag -= 4; 397 for (i=m-2; i>=0; i--) { 398 v = aa + 4*(diag[i] + 1); 399 vi = aj + diag[i] + 1; 400 nz = ai[i+1] - diag[i] - 1; 401 s[0] = xb[i2]; s[1] = xb[i2+1]; 402 for (j=0; j<nz; j++) { 403 idx = 2*vi[j]; 404 it = 4*j; 405 xw[0] = x[idx]; xw[1] = x[1+idx]; 406 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 407 } 408 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 409 x[i2] = xw[0]; x[i2+1] = xw[1]; 410 idiag -= 4; 411 i2 -= 2; 412 } 413 break; 414 case 3: 415 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 416 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 417 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 418 i2 -= 3; 419 idiag -= 9; 420 for (i=m-2; i>=0; i--) { 421 v = aa + 9*(diag[i]+1); 422 vi = aj + diag[i] + 1; 423 nz = ai[i+1] - diag[i] - 1; 424 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 425 while (nz--) { 426 idx = 3*(*vi++); 427 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 428 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 429 v += 9; 430 } 431 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 432 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 433 idiag -= 9; 434 i2 -= 3; 435 } 436 break; 437 case 4: 438 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; 439 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 440 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 441 i2 -= 4; 442 idiag -= 16; 443 for (i=m-2; i>=0; i--) { 444 v = aa + 16*(diag[i]+1); 445 vi = aj + diag[i] + 1; 446 nz = ai[i+1] - diag[i] - 1; 447 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; 448 while (nz--) { 449 idx = 4*(*vi++); 450 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 451 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 452 v += 16; 453 } 454 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 455 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 456 idiag -= 16; 457 i2 -= 4; 458 } 459 break; 460 case 5: 461 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; 462 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 463 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 464 i2 -= 5; 465 idiag -= 25; 466 for (i=m-2; i>=0; i--) { 467 v = aa + 25*(diag[i]+1); 468 vi = aj + diag[i] + 1; 469 nz = ai[i+1] - diag[i] - 1; 470 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; 471 while (nz--) { 472 idx = 5*(*vi++); 473 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 474 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 475 v += 25; 476 } 477 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 478 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 479 idiag -= 25; 480 i2 -= 5; 481 } 482 break; 483 case 6: 484 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]; 485 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 486 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]; 487 i2 -= 6; 488 idiag -= 36; 489 for (i=m-2; i>=0; i--) { 490 v = aa + 36*(diag[i]+1); 491 vi = aj + diag[i] + 1; 492 nz = ai[i+1] - diag[i] - 1; 493 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]; 494 while (nz--) { 495 idx = 6*(*vi++); 496 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 497 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 498 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 499 v += 36; 500 } 501 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 502 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]; 503 idiag -= 36; 504 i2 -= 6; 505 } 506 break; 507 case 7: 508 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 509 s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6]; 510 PetscKernel_v_gets_A_times_w_7(x,idiag,b); 511 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 512 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 513 i2 -= 7; 514 idiag -= 49; 515 for (i=m-2; i>=0; i--) { 516 v = aa + 49*(diag[i]+1); 517 vi = aj + diag[i] + 1; 518 nz = ai[i+1] - diag[i] - 1; 519 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 520 s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6]; 521 while (nz--) { 522 idx = 7*(*vi++); 523 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 524 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 525 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 526 v += 49; 527 } 528 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 529 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 530 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 531 idiag -= 49; 532 i2 -= 7; 533 } 534 break; 535 default: 536 ierr = PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 537 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 538 i2 -= bs; 539 idiag -= bs2; 540 for (i=m-2; i>=0; i--) { 541 v = aa + bs2*(diag[i]+1); 542 vi = aj + diag[i] + 1; 543 nz = ai[i+1] - diag[i] - 1; 544 545 ierr = PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 546 /* copy all rows of x that are needed into contiguous space */ 547 workt = work; 548 for (j=0; j<nz; j++) { 549 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 550 workt += bs; 551 } 552 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 553 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 554 555 idiag -= bs2; 556 i2 -= bs; 557 } 558 break; 559 } 560 ierr = PetscLogFlops(1.0*bs2*(a->nz));CHKERRQ(ierr); 561 } 562 its--; 563 } 564 while (its--) { 565 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 566 idiag = a->idiag; 567 i2 = 0; 568 switch (bs) { 569 case 1: 570 for (i=0; i<m; i++) { 571 v = aa + ai[i]; 572 vi = aj + ai[i]; 573 nz = ai[i+1] - ai[i]; 574 s[0] = b[i2]; 575 for (j=0; j<nz; j++) { 576 xw[0] = x[vi[j]]; 577 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 578 } 579 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 580 x[i2] += xw[0]; 581 idiag += 1; 582 i2 += 1; 583 } 584 break; 585 case 2: 586 for (i=0; i<m; i++) { 587 v = aa + 4*ai[i]; 588 vi = aj + ai[i]; 589 nz = ai[i+1] - ai[i]; 590 s[0] = b[i2]; s[1] = b[i2+1]; 591 for (j=0; j<nz; j++) { 592 idx = 2*vi[j]; 593 it = 4*j; 594 xw[0] = x[idx]; xw[1] = x[1+idx]; 595 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 596 } 597 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 598 x[i2] += xw[0]; x[i2+1] += xw[1]; 599 idiag += 4; 600 i2 += 2; 601 } 602 break; 603 case 3: 604 for (i=0; i<m; i++) { 605 v = aa + 9*ai[i]; 606 vi = aj + ai[i]; 607 nz = ai[i+1] - ai[i]; 608 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 609 while (nz--) { 610 idx = 3*(*vi++); 611 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 612 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 613 v += 9; 614 } 615 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 616 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 617 idiag += 9; 618 i2 += 3; 619 } 620 break; 621 case 4: 622 for (i=0; i<m; i++) { 623 v = aa + 16*ai[i]; 624 vi = aj + ai[i]; 625 nz = ai[i+1] - ai[i]; 626 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 627 while (nz--) { 628 idx = 4*(*vi++); 629 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 630 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 631 v += 16; 632 } 633 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 634 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; 635 idiag += 16; 636 i2 += 4; 637 } 638 break; 639 case 5: 640 for (i=0; i<m; i++) { 641 v = aa + 25*ai[i]; 642 vi = aj + ai[i]; 643 nz = ai[i+1] - ai[i]; 644 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 645 while (nz--) { 646 idx = 5*(*vi++); 647 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 648 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 649 v += 25; 650 } 651 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 652 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4]; 653 idiag += 25; 654 i2 += 5; 655 } 656 break; 657 case 6: 658 for (i=0; i<m; i++) { 659 v = aa + 36*ai[i]; 660 vi = aj + ai[i]; 661 nz = ai[i+1] - ai[i]; 662 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]; 663 while (nz--) { 664 idx = 6*(*vi++); 665 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 666 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 667 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 668 v += 36; 669 } 670 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 671 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 672 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; 673 idiag += 36; 674 i2 += 6; 675 } 676 break; 677 case 7: 678 for (i=0; i<m; i++) { 679 v = aa + 49*ai[i]; 680 vi = aj + ai[i]; 681 nz = ai[i+1] - ai[i]; 682 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 683 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 684 while (nz--) { 685 idx = 7*(*vi++); 686 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 687 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 688 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 689 v += 49; 690 } 691 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 692 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 693 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6]; 694 idiag += 49; 695 i2 += 7; 696 } 697 break; 698 default: 699 for (i=0; i<m; i++) { 700 v = aa + bs2*ai[i]; 701 vi = aj + ai[i]; 702 nz = ai[i+1] - ai[i]; 703 704 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 705 /* copy all rows of x that are needed into contiguous space */ 706 workt = work; 707 for (j=0; j<nz; j++) { 708 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 709 workt += bs; 710 } 711 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 712 PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2); 713 714 idiag += bs2; 715 i2 += bs; 716 } 717 break; 718 } 719 ierr = PetscLogFlops(2.0*bs2*a->nz);CHKERRQ(ierr); 720 } 721 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 722 idiag = a->idiag+bs2*(a->mbs-1); 723 i2 = bs * (m-1); 724 switch (bs) { 725 case 1: 726 for (i=m-1; i>=0; i--) { 727 v = aa + ai[i]; 728 vi = aj + ai[i]; 729 nz = ai[i+1] - ai[i]; 730 s[0] = b[i2]; 731 for (j=0; j<nz; j++) { 732 xw[0] = x[vi[j]]; 733 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 734 } 735 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 736 x[i2] += xw[0]; 737 idiag -= 1; 738 i2 -= 1; 739 } 740 break; 741 case 2: 742 for (i=m-1; i>=0; i--) { 743 v = aa + 4*ai[i]; 744 vi = aj + ai[i]; 745 nz = ai[i+1] - ai[i]; 746 s[0] = b[i2]; s[1] = b[i2+1]; 747 for (j=0; j<nz; j++) { 748 idx = 2*vi[j]; 749 it = 4*j; 750 xw[0] = x[idx]; xw[1] = x[1+idx]; 751 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 752 } 753 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 754 x[i2] += xw[0]; x[i2+1] += xw[1]; 755 idiag -= 4; 756 i2 -= 2; 757 } 758 break; 759 case 3: 760 for (i=m-1; i>=0; i--) { 761 v = aa + 9*ai[i]; 762 vi = aj + ai[i]; 763 nz = ai[i+1] - ai[i]; 764 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 765 while (nz--) { 766 idx = 3*(*vi++); 767 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 768 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 769 v += 9; 770 } 771 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 772 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 773 idiag -= 9; 774 i2 -= 3; 775 } 776 break; 777 case 4: 778 for (i=m-1; i>=0; i--) { 779 v = aa + 16*ai[i]; 780 vi = aj + ai[i]; 781 nz = ai[i+1] - ai[i]; 782 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 783 while (nz--) { 784 idx = 4*(*vi++); 785 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 786 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 787 v += 16; 788 } 789 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 790 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; 791 idiag -= 16; 792 i2 -= 4; 793 } 794 break; 795 case 5: 796 for (i=m-1; i>=0; i--) { 797 v = aa + 25*ai[i]; 798 vi = aj + ai[i]; 799 nz = ai[i+1] - ai[i]; 800 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 801 while (nz--) { 802 idx = 5*(*vi++); 803 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 804 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 805 v += 25; 806 } 807 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 808 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4]; 809 idiag -= 25; 810 i2 -= 5; 811 } 812 break; 813 case 6: 814 for (i=m-1; i>=0; i--) { 815 v = aa + 36*ai[i]; 816 vi = aj + ai[i]; 817 nz = ai[i+1] - ai[i]; 818 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]; 819 while (nz--) { 820 idx = 6*(*vi++); 821 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 822 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 823 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 824 v += 36; 825 } 826 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 827 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 828 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; 829 idiag -= 36; 830 i2 -= 6; 831 } 832 break; 833 case 7: 834 for (i=m-1; i>=0; i--) { 835 v = aa + 49*ai[i]; 836 vi = aj + ai[i]; 837 nz = ai[i+1] - ai[i]; 838 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 839 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 840 while (nz--) { 841 idx = 7*(*vi++); 842 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 843 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 844 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 845 v += 49; 846 } 847 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 848 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 849 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6]; 850 idiag -= 49; 851 i2 -= 7; 852 } 853 break; 854 default: 855 for (i=m-1; i>=0; i--) { 856 v = aa + bs2*ai[i]; 857 vi = aj + ai[i]; 858 nz = ai[i+1] - ai[i]; 859 860 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 861 /* copy all rows of x that are needed into contiguous space */ 862 workt = work; 863 for (j=0; j<nz; j++) { 864 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 865 workt += bs; 866 } 867 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 868 PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2); 869 870 idiag -= bs2; 871 i2 -= bs; 872 } 873 break; 874 } 875 ierr = PetscLogFlops(2.0*bs2*(a->nz));CHKERRQ(ierr); 876 } 877 } 878 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 879 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 880 PetscFunctionReturn(0); 881 } 882 883 884 /* 885 Special version for direct calls from Fortran (Used in PETSc-fun3d) 886 */ 887 #if defined(PETSC_HAVE_FORTRAN_CAPS) 888 #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4 889 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 890 #define matsetvaluesblocked4_ matsetvaluesblocked4 891 #endif 892 893 #undef __FUNCT__ 894 #define __FUNCT__ "matsetvaluesblocked4_" 895 PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[]) 896 { 897 Mat A = *AA; 898 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 899 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn; 900 PetscInt *ai =a->i,*ailen=a->ilen; 901 PetscInt *aj =a->j,stepval,lastcol = -1; 902 const PetscScalar *value = v; 903 MatScalar *ap,*aa = a->a,*bap; 904 905 PetscFunctionBegin; 906 if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4"); 907 stepval = (n-1)*4; 908 for (k=0; k<m; k++) { /* loop over added rows */ 909 row = im[k]; 910 rp = aj + ai[row]; 911 ap = aa + 16*ai[row]; 912 nrow = ailen[row]; 913 low = 0; 914 high = nrow; 915 for (l=0; l<n; l++) { /* loop over added columns */ 916 col = in[l]; 917 if (col <= lastcol) low = 0; 918 else high = nrow; 919 lastcol = col; 920 value = v + k*(stepval+4 + l)*4; 921 while (high-low > 7) { 922 t = (low+high)/2; 923 if (rp[t] > col) high = t; 924 else low = t; 925 } 926 for (i=low; i<high; i++) { 927 if (rp[i] > col) break; 928 if (rp[i] == col) { 929 bap = ap + 16*i; 930 for (ii=0; ii<4; ii++,value+=stepval) { 931 for (jj=ii; jj<16; jj+=4) { 932 bap[jj] += *value++; 933 } 934 } 935 goto noinsert2; 936 } 937 } 938 N = nrow++ - 1; 939 high++; /* added new column index thus must search to one higher than before */ 940 /* shift up all the later entries in this row */ 941 for (ii=N; ii>=i; ii--) { 942 rp[ii+1] = rp[ii]; 943 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 944 } 945 if (N >= i) { 946 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 947 } 948 rp[i] = col; 949 bap = ap + 16*i; 950 for (ii=0; ii<4; ii++,value+=stepval) { 951 for (jj=ii; jj<16; jj+=4) { 952 bap[jj] = *value++; 953 } 954 } 955 noinsert2:; 956 low = i; 957 } 958 ailen[row] = nrow; 959 } 960 PetscFunctionReturnVoid(); 961 } 962 963 #if defined(PETSC_HAVE_FORTRAN_CAPS) 964 #define matsetvalues4_ MATSETVALUES4 965 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 966 #define matsetvalues4_ matsetvalues4 967 #endif 968 969 #undef __FUNCT__ 970 #define __FUNCT__ "MatSetValues4_" 971 PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v) 972 { 973 Mat A = *AA; 974 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 975 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm; 976 PetscInt *ai=a->i,*ailen=a->ilen; 977 PetscInt *aj=a->j,brow,bcol; 978 PetscInt ridx,cidx,lastcol = -1; 979 MatScalar *ap,value,*aa=a->a,*bap; 980 981 PetscFunctionBegin; 982 for (k=0; k<m; k++) { /* loop over added rows */ 983 row = im[k]; brow = row/4; 984 rp = aj + ai[brow]; 985 ap = aa + 16*ai[brow]; 986 nrow = ailen[brow]; 987 low = 0; 988 high = nrow; 989 for (l=0; l<n; l++) { /* loop over added columns */ 990 col = in[l]; bcol = col/4; 991 ridx = row % 4; cidx = col % 4; 992 value = v[l + k*n]; 993 if (col <= lastcol) low = 0; 994 else high = nrow; 995 lastcol = col; 996 while (high-low > 7) { 997 t = (low+high)/2; 998 if (rp[t] > bcol) high = t; 999 else low = t; 1000 } 1001 for (i=low; i<high; i++) { 1002 if (rp[i] > bcol) break; 1003 if (rp[i] == bcol) { 1004 bap = ap + 16*i + 4*cidx + ridx; 1005 *bap += value; 1006 goto noinsert1; 1007 } 1008 } 1009 N = nrow++ - 1; 1010 high++; /* added new column thus must search to one higher than before */ 1011 /* shift up all the later entries in this row */ 1012 for (ii=N; ii>=i; ii--) { 1013 rp[ii+1] = rp[ii]; 1014 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 1015 } 1016 if (N>=i) { 1017 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 1018 } 1019 rp[i] = bcol; 1020 ap[16*i + 4*cidx + ridx] = value; 1021 noinsert1:; 1022 low = i; 1023 } 1024 ailen[brow] = nrow; 1025 } 1026 PetscFunctionReturnVoid(); 1027 } 1028 1029 /* 1030 Checks for missing diagonals 1031 */ 1032 #undef __FUNCT__ 1033 #define __FUNCT__ "MatMissingDiagonal_SeqBAIJ" 1034 PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool *missing,PetscInt *d) 1035 { 1036 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1037 PetscErrorCode ierr; 1038 PetscInt *diag,*jj = a->j,i; 1039 1040 PetscFunctionBegin; 1041 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 1042 *missing = PETSC_FALSE; 1043 if (A->rmap->n > 0 && !jj) { 1044 *missing = PETSC_TRUE; 1045 if (d) *d = 0; 1046 PetscInfo(A,"Matrix has no entries therefore is missing diagonal"); 1047 } else { 1048 diag = a->diag; 1049 for (i=0; i<a->mbs; i++) { 1050 if (jj[diag[i]] != i) { 1051 *missing = PETSC_TRUE; 1052 if (d) *d = i; 1053 PetscInfo1(A,"Matrix is missing block diagonal number %D",i); 1054 break; 1055 } 1056 } 1057 } 1058 PetscFunctionReturn(0); 1059 } 1060 1061 #undef __FUNCT__ 1062 #define __FUNCT__ "MatMarkDiagonal_SeqBAIJ" 1063 PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A) 1064 { 1065 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1066 PetscErrorCode ierr; 1067 PetscInt i,j,m = a->mbs; 1068 1069 PetscFunctionBegin; 1070 if (!a->diag) { 1071 ierr = PetscMalloc(m*sizeof(PetscInt),&a->diag);CHKERRQ(ierr); 1072 ierr = PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));CHKERRQ(ierr); 1073 a->free_diag = PETSC_TRUE; 1074 } 1075 for (i=0; i<m; i++) { 1076 a->diag[i] = a->i[i+1]; 1077 for (j=a->i[i]; j<a->i[i+1]; j++) { 1078 if (a->j[j] == i) { 1079 a->diag[i] = j; 1080 break; 1081 } 1082 } 1083 } 1084 PetscFunctionReturn(0); 1085 } 1086 1087 1088 #undef __FUNCT__ 1089 #define __FUNCT__ "MatGetRowIJ_SeqBAIJ" 1090 static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool *done) 1091 { 1092 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1093 PetscErrorCode ierr; 1094 PetscInt i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt; 1095 PetscInt **ia = (PetscInt**)inia,**ja = (PetscInt**)inja; 1096 1097 PetscFunctionBegin; 1098 *nn = n; 1099 if (!ia) PetscFunctionReturn(0); 1100 if (symmetric) { 1101 ierr = MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,0,0,&tia,&tja);CHKERRQ(ierr); 1102 nz = tia[n]; 1103 } else { 1104 tia = a->i; tja = a->j; 1105 } 1106 1107 if (!blockcompressed && bs > 1) { 1108 (*nn) *= bs; 1109 /* malloc & create the natural set of indices */ 1110 ierr = PetscMalloc((n+1)*bs*sizeof(PetscInt),ia);CHKERRQ(ierr); 1111 if (n) { 1112 (*ia)[0] = 0; 1113 for (j=1; j<bs; j++) { 1114 (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1]; 1115 } 1116 } 1117 1118 for (i=1; i<n; i++) { 1119 (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1]; 1120 for (j=1; j<bs; j++) { 1121 (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1]; 1122 } 1123 } 1124 if (n) { 1125 (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1]; 1126 } 1127 1128 if (inja) { 1129 ierr = PetscMalloc(nz*bs*bs*sizeof(PetscInt),ja);CHKERRQ(ierr); 1130 cnt = 0; 1131 for (i=0; i<n; i++) { 1132 for (j=0; j<bs; j++) { 1133 for (k=tia[i]; k<tia[i+1]; k++) { 1134 for (l=0; l<bs; l++) { 1135 (*ja)[cnt++] = bs*tja[k] + l; 1136 } 1137 } 1138 } 1139 } 1140 } 1141 1142 if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */ 1143 ierr = PetscFree(tia);CHKERRQ(ierr); 1144 ierr = PetscFree(tja);CHKERRQ(ierr); 1145 } 1146 } else if (oshift == 1) { 1147 if (symmetric) { 1148 nz = tia[A->rmap->n/bs]; 1149 /* add 1 to i and j indices */ 1150 for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1; 1151 *ia = tia; 1152 if (ja) { 1153 for (i=0; i<nz; i++) tja[i] = tja[i] + 1; 1154 *ja = tja; 1155 } 1156 } else { 1157 nz = a->i[A->rmap->n/bs]; 1158 /* malloc space and add 1 to i and j indices */ 1159 ierr = PetscMalloc((A->rmap->n/bs+1)*sizeof(PetscInt),ia);CHKERRQ(ierr); 1160 for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1; 1161 if (ja) { 1162 ierr = PetscMalloc(nz*sizeof(PetscInt),ja);CHKERRQ(ierr); 1163 for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1; 1164 } 1165 } 1166 } else { 1167 *ia = tia; 1168 if (ja) *ja = tja; 1169 } 1170 PetscFunctionReturn(0); 1171 } 1172 1173 #undef __FUNCT__ 1174 #define __FUNCT__ "MatRestoreRowIJ_SeqBAIJ" 1175 static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 1176 { 1177 PetscErrorCode ierr; 1178 1179 PetscFunctionBegin; 1180 if (!ia) PetscFunctionReturn(0); 1181 if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) { 1182 ierr = PetscFree(*ia);CHKERRQ(ierr); 1183 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 1184 } 1185 PetscFunctionReturn(0); 1186 } 1187 1188 #undef __FUNCT__ 1189 #define __FUNCT__ "MatDestroy_SeqBAIJ" 1190 PetscErrorCode MatDestroy_SeqBAIJ(Mat A) 1191 { 1192 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1193 PetscErrorCode ierr; 1194 1195 PetscFunctionBegin; 1196 #if defined(PETSC_USE_LOG) 1197 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz); 1198 #endif 1199 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1200 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1201 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1202 if (a->free_diag) {ierr = PetscFree(a->diag);CHKERRQ(ierr);} 1203 ierr = PetscFree(a->idiag);CHKERRQ(ierr); 1204 if (a->free_imax_ilen) {ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr);} 1205 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1206 ierr = PetscFree(a->mult_work);CHKERRQ(ierr); 1207 ierr = PetscFree(a->sor_work);CHKERRQ(ierr); 1208 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1209 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1210 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1211 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1212 1213 ierr = MatDestroy(&a->sbaijMat);CHKERRQ(ierr); 1214 ierr = MatDestroy(&a->parent);CHKERRQ(ierr); 1215 ierr = PetscFree(A->data);CHKERRQ(ierr); 1216 1217 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1218 ierr = PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);CHKERRQ(ierr); 1219 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1220 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1221 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1222 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);CHKERRQ(ierr); 1223 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1224 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1225 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1226 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);CHKERRQ(ierr); 1227 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1228 PetscFunctionReturn(0); 1229 } 1230 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatSetOption_SeqBAIJ" 1233 PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg) 1234 { 1235 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1236 PetscErrorCode ierr; 1237 1238 PetscFunctionBegin; 1239 switch (op) { 1240 case MAT_ROW_ORIENTED: 1241 a->roworiented = flg; 1242 break; 1243 case MAT_KEEP_NONZERO_PATTERN: 1244 a->keepnonzeropattern = flg; 1245 break; 1246 case MAT_NEW_NONZERO_LOCATIONS: 1247 a->nonew = (flg ? 0 : 1); 1248 break; 1249 case MAT_NEW_NONZERO_LOCATION_ERR: 1250 a->nonew = (flg ? -1 : 0); 1251 break; 1252 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1253 a->nonew = (flg ? -2 : 0); 1254 break; 1255 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1256 a->nounused = (flg ? -1 : 0); 1257 break; 1258 case MAT_CHECK_COMPRESSED_ROW: 1259 a->compressedrow.check = flg; 1260 break; 1261 case MAT_NEW_DIAGONALS: 1262 case MAT_IGNORE_OFF_PROC_ENTRIES: 1263 case MAT_USE_HASH_TABLE: 1264 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1265 break; 1266 case MAT_SPD: 1267 case MAT_SYMMETRIC: 1268 case MAT_STRUCTURALLY_SYMMETRIC: 1269 case MAT_HERMITIAN: 1270 case MAT_SYMMETRY_ETERNAL: 1271 /* These options are handled directly by MatSetOption() */ 1272 break; 1273 default: 1274 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1275 } 1276 PetscFunctionReturn(0); 1277 } 1278 1279 #undef __FUNCT__ 1280 #define __FUNCT__ "MatGetRow_SeqBAIJ" 1281 PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1282 { 1283 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1284 PetscErrorCode ierr; 1285 PetscInt itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*idx_i,bs2; 1286 MatScalar *aa,*aa_i; 1287 PetscScalar *v_i; 1288 1289 PetscFunctionBegin; 1290 bs = A->rmap->bs; 1291 ai = a->i; 1292 aj = a->j; 1293 aa = a->a; 1294 bs2 = a->bs2; 1295 1296 if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row); 1297 1298 bn = row/bs; /* Block number */ 1299 bp = row % bs; /* Block Position */ 1300 M = ai[bn+1] - ai[bn]; 1301 *nz = bs*M; 1302 1303 if (v) { 1304 *v = 0; 1305 if (*nz) { 1306 ierr = PetscMalloc((*nz)*sizeof(PetscScalar),v);CHKERRQ(ierr); 1307 for (i=0; i<M; i++) { /* for each block in the block row */ 1308 v_i = *v + i*bs; 1309 aa_i = aa + bs2*(ai[bn] + i); 1310 for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j]; 1311 } 1312 } 1313 } 1314 1315 if (idx) { 1316 *idx = 0; 1317 if (*nz) { 1318 ierr = PetscMalloc((*nz)*sizeof(PetscInt),idx);CHKERRQ(ierr); 1319 for (i=0; i<M; i++) { /* for each block in the block row */ 1320 idx_i = *idx + i*bs; 1321 itmp = bs*aj[ai[bn] + i]; 1322 for (j=0; j<bs; j++) idx_i[j] = itmp++; 1323 } 1324 } 1325 } 1326 PetscFunctionReturn(0); 1327 } 1328 1329 #undef __FUNCT__ 1330 #define __FUNCT__ "MatRestoreRow_SeqBAIJ" 1331 PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1332 { 1333 PetscErrorCode ierr; 1334 1335 PetscFunctionBegin; 1336 if (idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);} 1337 if (v) {ierr = PetscFree(*v);CHKERRQ(ierr);} 1338 PetscFunctionReturn(0); 1339 } 1340 1341 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 1342 1343 #undef __FUNCT__ 1344 #define __FUNCT__ "MatTranspose_SeqBAIJ" 1345 PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B) 1346 { 1347 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1348 Mat C; 1349 PetscErrorCode ierr; 1350 PetscInt i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col; 1351 PetscInt *rows,*cols,bs2=a->bs2; 1352 MatScalar *array; 1353 1354 PetscFunctionBegin; 1355 if (reuse == MAT_REUSE_MATRIX && A == *B && mbs != nbs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1356 if (reuse == MAT_INITIAL_MATRIX || A == *B) { 1357 ierr = PetscMalloc((1+nbs)*sizeof(PetscInt),&col);CHKERRQ(ierr); 1358 ierr = PetscMemzero(col,(1+nbs)*sizeof(PetscInt));CHKERRQ(ierr); 1359 1360 for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1; 1361 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 1362 ierr = MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);CHKERRQ(ierr); 1363 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 1364 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(C,bs,0,col);CHKERRQ(ierr); 1365 ierr = PetscFree(col);CHKERRQ(ierr); 1366 } else { 1367 C = *B; 1368 } 1369 1370 array = a->a; 1371 ierr = PetscMalloc2(bs,PetscInt,&rows,bs,PetscInt,&cols);CHKERRQ(ierr); 1372 for (i=0; i<mbs; i++) { 1373 cols[0] = i*bs; 1374 for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1; 1375 len = ai[i+1] - ai[i]; 1376 for (j=0; j<len; j++) { 1377 rows[0] = (*aj++)*bs; 1378 for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1; 1379 ierr = MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);CHKERRQ(ierr); 1380 array += bs2; 1381 } 1382 } 1383 ierr = PetscFree2(rows,cols);CHKERRQ(ierr); 1384 1385 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1386 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1387 1388 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 1389 *B = C; 1390 } else { 1391 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1392 } 1393 PetscFunctionReturn(0); 1394 } 1395 1396 #undef __FUNCT__ 1397 #define __FUNCT__ "MatIsTranspose_SeqBAIJ" 1398 PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 1399 { 1400 PetscErrorCode ierr; 1401 Mat Btrans; 1402 1403 PetscFunctionBegin; 1404 *f = PETSC_FALSE; 1405 ierr = MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);CHKERRQ(ierr); 1406 ierr = MatEqual_SeqBAIJ(B,Btrans,f);CHKERRQ(ierr); 1407 ierr = MatDestroy(&Btrans);CHKERRQ(ierr); 1408 PetscFunctionReturn(0); 1409 } 1410 1411 #undef __FUNCT__ 1412 #define __FUNCT__ "MatView_SeqBAIJ_Binary" 1413 static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer) 1414 { 1415 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1416 PetscErrorCode ierr; 1417 PetscInt i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2; 1418 int fd; 1419 PetscScalar *aa; 1420 FILE *file; 1421 1422 PetscFunctionBegin; 1423 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1424 ierr = PetscMalloc((4+A->rmap->N)*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 1425 col_lens[0] = MAT_FILE_CLASSID; 1426 1427 col_lens[1] = A->rmap->N; 1428 col_lens[2] = A->cmap->n; 1429 col_lens[3] = a->nz*bs2; 1430 1431 /* store lengths of each row and write (including header) to file */ 1432 count = 0; 1433 for (i=0; i<a->mbs; i++) { 1434 for (j=0; j<bs; j++) { 1435 col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]); 1436 } 1437 } 1438 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1439 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1440 1441 /* store column indices (zero start index) */ 1442 ierr = PetscMalloc((a->nz+1)*bs2*sizeof(PetscInt),&jj);CHKERRQ(ierr); 1443 count = 0; 1444 for (i=0; i<a->mbs; i++) { 1445 for (j=0; j<bs; j++) { 1446 for (k=a->i[i]; k<a->i[i+1]; k++) { 1447 for (l=0; l<bs; l++) { 1448 jj[count++] = bs*a->j[k] + l; 1449 } 1450 } 1451 } 1452 } 1453 ierr = PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1454 ierr = PetscFree(jj);CHKERRQ(ierr); 1455 1456 /* store nonzero values */ 1457 ierr = PetscMalloc((a->nz+1)*bs2*sizeof(PetscScalar),&aa);CHKERRQ(ierr); 1458 count = 0; 1459 for (i=0; i<a->mbs; i++) { 1460 for (j=0; j<bs; j++) { 1461 for (k=a->i[i]; k<a->i[i+1]; k++) { 1462 for (l=0; l<bs; l++) { 1463 aa[count++] = a->a[bs2*k + l*bs + j]; 1464 } 1465 } 1466 } 1467 } 1468 ierr = PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1469 ierr = PetscFree(aa);CHKERRQ(ierr); 1470 1471 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1472 if (file) { 1473 fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs); 1474 } 1475 PetscFunctionReturn(0); 1476 } 1477 1478 #undef __FUNCT__ 1479 #define __FUNCT__ "MatView_SeqBAIJ_ASCII" 1480 static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer) 1481 { 1482 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1483 PetscErrorCode ierr; 1484 PetscInt i,j,bs = A->rmap->bs,k,l,bs2=a->bs2; 1485 PetscViewerFormat format; 1486 1487 PetscFunctionBegin; 1488 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1489 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1490 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1491 } else if (format == PETSC_VIEWER_ASCII_MATLAB) { 1492 Mat aij; 1493 ierr = MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);CHKERRQ(ierr); 1494 ierr = MatView(aij,viewer);CHKERRQ(ierr); 1495 ierr = MatDestroy(&aij);CHKERRQ(ierr); 1496 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1497 PetscFunctionReturn(0); 1498 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1499 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1500 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 1501 for (i=0; i<a->mbs; i++) { 1502 for (j=0; j<bs; j++) { 1503 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1504 for (k=a->i[i]; k<a->i[i+1]; k++) { 1505 for (l=0; l<bs; l++) { 1506 #if defined(PETSC_USE_COMPLEX) 1507 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1508 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %Gi) ",bs*a->j[k]+l, 1509 PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1510 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1511 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %Gi) ",bs*a->j[k]+l, 1512 PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1513 } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1514 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1515 } 1516 #else 1517 if (a->a[bs2*k + l*bs + j] != 0.0) { 1518 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1519 } 1520 #endif 1521 } 1522 } 1523 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1524 } 1525 } 1526 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1527 } else { 1528 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1529 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 1530 for (i=0; i<a->mbs; i++) { 1531 for (j=0; j<bs; j++) { 1532 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1533 for (k=a->i[i]; k<a->i[i+1]; k++) { 1534 for (l=0; l<bs; l++) { 1535 #if defined(PETSC_USE_COMPLEX) 1536 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) { 1537 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i) ",bs*a->j[k]+l, 1538 PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1539 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) { 1540 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %G i) ",bs*a->j[k]+l, 1541 PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1542 } else { 1543 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1544 } 1545 #else 1546 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1547 #endif 1548 } 1549 } 1550 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1551 } 1552 } 1553 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1554 } 1555 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1556 PetscFunctionReturn(0); 1557 } 1558 1559 #include <petscdraw.h> 1560 #undef __FUNCT__ 1561 #define __FUNCT__ "MatView_SeqBAIJ_Draw_Zoom" 1562 static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 1563 { 1564 Mat A = (Mat) Aa; 1565 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1566 PetscErrorCode ierr; 1567 PetscInt row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2; 1568 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1569 MatScalar *aa; 1570 PetscViewer viewer; 1571 PetscViewerFormat format; 1572 1573 PetscFunctionBegin; 1574 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1575 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1576 1577 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1578 1579 /* loop over matrix elements drawing boxes */ 1580 1581 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1582 color = PETSC_DRAW_BLUE; 1583 for (i=0,row=0; i<mbs; i++,row+=bs) { 1584 for (j=a->i[i]; j<a->i[i+1]; j++) { 1585 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1586 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1587 aa = a->a + j*bs2; 1588 for (k=0; k<bs; k++) { 1589 for (l=0; l<bs; l++) { 1590 if (PetscRealPart(*aa++) >= 0.) continue; 1591 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1592 } 1593 } 1594 } 1595 } 1596 color = PETSC_DRAW_CYAN; 1597 for (i=0,row=0; i<mbs; i++,row+=bs) { 1598 for (j=a->i[i]; j<a->i[i+1]; j++) { 1599 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1600 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1601 aa = a->a + j*bs2; 1602 for (k=0; k<bs; k++) { 1603 for (l=0; l<bs; l++) { 1604 if (PetscRealPart(*aa++) != 0.) continue; 1605 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1606 } 1607 } 1608 } 1609 } 1610 color = PETSC_DRAW_RED; 1611 for (i=0,row=0; i<mbs; i++,row+=bs) { 1612 for (j=a->i[i]; j<a->i[i+1]; j++) { 1613 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1614 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1615 aa = a->a + j*bs2; 1616 for (k=0; k<bs; k++) { 1617 for (l=0; l<bs; l++) { 1618 if (PetscRealPart(*aa++) <= 0.) continue; 1619 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1620 } 1621 } 1622 } 1623 } 1624 } else { 1625 /* use contour shading to indicate magnitude of values */ 1626 /* first determine max of all nonzero values */ 1627 PetscDraw popup; 1628 PetscReal scale,maxv = 0.0; 1629 1630 for (i=0; i<a->nz*a->bs2; i++) { 1631 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 1632 } 1633 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 1634 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1635 if (popup) { 1636 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 1637 } 1638 for (i=0,row=0; i<mbs; i++,row+=bs) { 1639 for (j=a->i[i]; j<a->i[i+1]; j++) { 1640 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1641 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1642 aa = a->a + j*bs2; 1643 for (k=0; k<bs; k++) { 1644 for (l=0; l<bs; l++) { 1645 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(*aa++)); 1646 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1647 } 1648 } 1649 } 1650 } 1651 } 1652 PetscFunctionReturn(0); 1653 } 1654 1655 #undef __FUNCT__ 1656 #define __FUNCT__ "MatView_SeqBAIJ_Draw" 1657 static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer) 1658 { 1659 PetscErrorCode ierr; 1660 PetscReal xl,yl,xr,yr,w,h; 1661 PetscDraw draw; 1662 PetscBool isnull; 1663 1664 PetscFunctionBegin; 1665 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1666 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1667 1668 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1669 xr = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0; 1670 xr += w; yr += h; xl = -w; yl = -h; 1671 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1672 ierr = PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);CHKERRQ(ierr); 1673 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1674 PetscFunctionReturn(0); 1675 } 1676 1677 #undef __FUNCT__ 1678 #define __FUNCT__ "MatView_SeqBAIJ" 1679 PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer) 1680 { 1681 PetscErrorCode ierr; 1682 PetscBool iascii,isbinary,isdraw; 1683 1684 PetscFunctionBegin; 1685 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1686 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1687 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1688 if (iascii) { 1689 ierr = MatView_SeqBAIJ_ASCII(A,viewer);CHKERRQ(ierr); 1690 } else if (isbinary) { 1691 ierr = MatView_SeqBAIJ_Binary(A,viewer);CHKERRQ(ierr); 1692 } else if (isdraw) { 1693 ierr = MatView_SeqBAIJ_Draw(A,viewer);CHKERRQ(ierr); 1694 } else { 1695 Mat B; 1696 ierr = MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);CHKERRQ(ierr); 1697 ierr = MatView(B,viewer);CHKERRQ(ierr); 1698 ierr = MatDestroy(&B);CHKERRQ(ierr); 1699 } 1700 PetscFunctionReturn(0); 1701 } 1702 1703 1704 #undef __FUNCT__ 1705 #define __FUNCT__ "MatGetValues_SeqBAIJ" 1706 PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 1707 { 1708 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1709 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 1710 PetscInt *ai = a->i,*ailen = a->ilen; 1711 PetscInt brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2; 1712 MatScalar *ap,*aa = a->a; 1713 1714 PetscFunctionBegin; 1715 for (k=0; k<m; k++) { /* loop over rows */ 1716 row = im[k]; brow = row/bs; 1717 if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */ 1718 if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row); 1719 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; 1720 nrow = ailen[brow]; 1721 for (l=0; l<n; l++) { /* loop over columns */ 1722 if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */ 1723 if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]); 1724 col = in[l]; 1725 bcol = col/bs; 1726 cidx = col%bs; 1727 ridx = row%bs; 1728 high = nrow; 1729 low = 0; /* assume unsorted */ 1730 while (high-low > 5) { 1731 t = (low+high)/2; 1732 if (rp[t] > bcol) high = t; 1733 else low = t; 1734 } 1735 for (i=low; i<high; i++) { 1736 if (rp[i] > bcol) break; 1737 if (rp[i] == bcol) { 1738 *v++ = ap[bs2*i+bs*cidx+ridx]; 1739 goto finished; 1740 } 1741 } 1742 *v++ = 0.0; 1743 finished:; 1744 } 1745 } 1746 PetscFunctionReturn(0); 1747 } 1748 1749 #undef __FUNCT__ 1750 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ" 1751 PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 1752 { 1753 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1754 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1; 1755 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 1756 PetscErrorCode ierr; 1757 PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval; 1758 PetscBool roworiented=a->roworiented; 1759 const PetscScalar *value = v; 1760 MatScalar *ap,*aa = a->a,*bap; 1761 1762 PetscFunctionBegin; 1763 if (roworiented) { 1764 stepval = (n-1)*bs; 1765 } else { 1766 stepval = (m-1)*bs; 1767 } 1768 for (k=0; k<m; k++) { /* loop over added rows */ 1769 row = im[k]; 1770 if (row < 0) continue; 1771 #if defined(PETSC_USE_DEBUG) 1772 if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1); 1773 #endif 1774 rp = aj + ai[row]; 1775 ap = aa + bs2*ai[row]; 1776 rmax = imax[row]; 1777 nrow = ailen[row]; 1778 low = 0; 1779 high = nrow; 1780 for (l=0; l<n; l++) { /* loop over added columns */ 1781 if (in[l] < 0) continue; 1782 #if defined(PETSC_USE_DEBUG) 1783 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); 1784 #endif 1785 col = in[l]; 1786 if (roworiented) { 1787 value = v + (k*(stepval+bs) + l)*bs; 1788 } else { 1789 value = v + (l*(stepval+bs) + k)*bs; 1790 } 1791 if (col <= lastcol) low = 0; 1792 else high = nrow; 1793 lastcol = col; 1794 while (high-low > 7) { 1795 t = (low+high)/2; 1796 if (rp[t] > col) high = t; 1797 else low = t; 1798 } 1799 for (i=low; i<high; i++) { 1800 if (rp[i] > col) break; 1801 if (rp[i] == col) { 1802 bap = ap + bs2*i; 1803 if (roworiented) { 1804 if (is == ADD_VALUES) { 1805 for (ii=0; ii<bs; ii++,value+=stepval) { 1806 for (jj=ii; jj<bs2; jj+=bs) { 1807 bap[jj] += *value++; 1808 } 1809 } 1810 } else { 1811 for (ii=0; ii<bs; ii++,value+=stepval) { 1812 for (jj=ii; jj<bs2; jj+=bs) { 1813 bap[jj] = *value++; 1814 } 1815 } 1816 } 1817 } else { 1818 if (is == ADD_VALUES) { 1819 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 1820 for (jj=0; jj<bs; jj++) { 1821 bap[jj] += value[jj]; 1822 } 1823 bap += bs; 1824 } 1825 } else { 1826 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 1827 for (jj=0; jj<bs; jj++) { 1828 bap[jj] = value[jj]; 1829 } 1830 bap += bs; 1831 } 1832 } 1833 } 1834 goto noinsert2; 1835 } 1836 } 1837 if (nonew == 1) goto noinsert2; 1838 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1839 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 1840 N = nrow++ - 1; high++; 1841 /* shift up all the later entries in this row */ 1842 for (ii=N; ii>=i; ii--) { 1843 rp[ii+1] = rp[ii]; 1844 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 1845 } 1846 if (N >= i) { 1847 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1848 } 1849 rp[i] = col; 1850 bap = ap + bs2*i; 1851 if (roworiented) { 1852 for (ii=0; ii<bs; ii++,value+=stepval) { 1853 for (jj=ii; jj<bs2; jj+=bs) { 1854 bap[jj] = *value++; 1855 } 1856 } 1857 } else { 1858 for (ii=0; ii<bs; ii++,value+=stepval) { 1859 for (jj=0; jj<bs; jj++) { 1860 *bap++ = *value++; 1861 } 1862 } 1863 } 1864 noinsert2:; 1865 low = i; 1866 } 1867 ailen[row] = nrow; 1868 } 1869 PetscFunctionReturn(0); 1870 } 1871 1872 #undef __FUNCT__ 1873 #define __FUNCT__ "MatAssemblyEnd_SeqBAIJ" 1874 PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode) 1875 { 1876 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1877 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 1878 PetscInt m = A->rmap->N,*ip,N,*ailen = a->ilen; 1879 PetscErrorCode ierr; 1880 PetscInt mbs = a->mbs,bs2 = a->bs2,rmax = 0; 1881 MatScalar *aa = a->a,*ap; 1882 PetscReal ratio=0.6; 1883 1884 PetscFunctionBegin; 1885 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 1886 1887 if (m) rmax = ailen[0]; 1888 for (i=1; i<mbs; i++) { 1889 /* move each row back by the amount of empty slots (fshift) before it*/ 1890 fshift += imax[i-1] - ailen[i-1]; 1891 rmax = PetscMax(rmax,ailen[i]); 1892 if (fshift) { 1893 ip = aj + ai[i]; ap = aa + bs2*ai[i]; 1894 N = ailen[i]; 1895 for (j=0; j<N; j++) { 1896 ip[j-fshift] = ip[j]; 1897 1898 ierr = PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1899 } 1900 } 1901 ai[i] = ai[i-1] + ailen[i-1]; 1902 } 1903 if (mbs) { 1904 fshift += imax[mbs-1] - ailen[mbs-1]; 1905 ai[mbs] = ai[mbs-1] + ailen[mbs-1]; 1906 } 1907 /* reset ilen and imax for each row */ 1908 for (i=0; i<mbs; i++) { 1909 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1910 } 1911 a->nz = ai[mbs]; 1912 1913 /* diagonals may have moved, so kill the diagonal pointers */ 1914 a->idiagvalid = PETSC_FALSE; 1915 if (fshift && a->diag) { 1916 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1917 ierr = PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 1918 a->diag = 0; 1919 } 1920 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); 1921 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); 1922 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);CHKERRQ(ierr); 1923 ierr = PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);CHKERRQ(ierr); 1924 1925 A->info.mallocs += a->reallocs; 1926 a->reallocs = 0; 1927 A->info.nz_unneeded = (PetscReal)fshift*bs2; 1928 1929 ierr = MatCheckCompressedRow(A,&a->compressedrow,a->i,mbs,ratio);CHKERRQ(ierr); 1930 1931 A->same_nonzero = PETSC_TRUE; 1932 PetscFunctionReturn(0); 1933 } 1934 1935 /* 1936 This function returns an array of flags which indicate the locations of contiguous 1937 blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] 1938 then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)] 1939 Assume: sizes should be long enough to hold all the values. 1940 */ 1941 #undef __FUNCT__ 1942 #define __FUNCT__ "MatZeroRows_SeqBAIJ_Check_Blocks" 1943 static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max) 1944 { 1945 PetscInt i,j,k,row; 1946 PetscBool flg; 1947 1948 PetscFunctionBegin; 1949 for (i=0,j=0; i<n; j++) { 1950 row = idx[i]; 1951 if (row%bs!=0) { /* Not the begining of a block */ 1952 sizes[j] = 1; 1953 i++; 1954 } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */ 1955 sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */ 1956 i++; 1957 } else { /* Begining of the block, so check if the complete block exists */ 1958 flg = PETSC_TRUE; 1959 for (k=1; k<bs; k++) { 1960 if (row+k != idx[i+k]) { /* break in the block */ 1961 flg = PETSC_FALSE; 1962 break; 1963 } 1964 } 1965 if (flg) { /* No break in the bs */ 1966 sizes[j] = bs; 1967 i += bs; 1968 } else { 1969 sizes[j] = 1; 1970 i++; 1971 } 1972 } 1973 } 1974 *bs_max = j; 1975 PetscFunctionReturn(0); 1976 } 1977 1978 #undef __FUNCT__ 1979 #define __FUNCT__ "MatZeroRows_SeqBAIJ" 1980 PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b) 1981 { 1982 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 1983 PetscErrorCode ierr; 1984 PetscInt i,j,k,count,*rows; 1985 PetscInt bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max; 1986 PetscScalar zero = 0.0; 1987 MatScalar *aa; 1988 const PetscScalar *xx; 1989 PetscScalar *bb; 1990 1991 PetscFunctionBegin; 1992 /* fix right hand side if needed */ 1993 if (x && b) { 1994 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1995 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1996 for (i=0; i<is_n; i++) { 1997 bb[is_idx[i]] = diag*xx[is_idx[i]]; 1998 } 1999 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2000 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2001 } 2002 2003 /* Make a copy of the IS and sort it */ 2004 /* allocate memory for rows,sizes */ 2005 ierr = PetscMalloc2(is_n,PetscInt,&rows,2*is_n,PetscInt,&sizes);CHKERRQ(ierr); 2006 2007 /* copy IS values to rows, and sort them */ 2008 for (i=0; i<is_n; i++) rows[i] = is_idx[i]; 2009 ierr = PetscSortInt(is_n,rows);CHKERRQ(ierr); 2010 2011 if (baij->keepnonzeropattern) { 2012 for (i=0; i<is_n; i++) sizes[i] = 1; 2013 bs_max = is_n; 2014 A->same_nonzero = PETSC_TRUE; 2015 } else { 2016 ierr = MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);CHKERRQ(ierr); 2017 2018 A->same_nonzero = PETSC_FALSE; 2019 } 2020 2021 for (i=0,j=0; i<bs_max; j+=sizes[i],i++) { 2022 row = rows[j]; 2023 if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row); 2024 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 2025 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 2026 if (sizes[i] == bs && !baij->keepnonzeropattern) { 2027 if (diag != (PetscScalar)0.0) { 2028 if (baij->ilen[row/bs] > 0) { 2029 baij->ilen[row/bs] = 1; 2030 baij->j[baij->i[row/bs]] = row/bs; 2031 2032 ierr = PetscMemzero(aa,count*bs*sizeof(MatScalar));CHKERRQ(ierr); 2033 } 2034 /* Now insert all the diagonal values for this bs */ 2035 for (k=0; k<bs; k++) { 2036 ierr = (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);CHKERRQ(ierr); 2037 } 2038 } else { /* (diag == 0.0) */ 2039 baij->ilen[row/bs] = 0; 2040 } /* end (diag == 0.0) */ 2041 } else { /* (sizes[i] != bs) */ 2042 #if defined(PETSC_USE_DEBUG) 2043 if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1"); 2044 #endif 2045 for (k=0; k<count; k++) { 2046 aa[0] = zero; 2047 aa += bs; 2048 } 2049 if (diag != (PetscScalar)0.0) { 2050 ierr = (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);CHKERRQ(ierr); 2051 } 2052 } 2053 } 2054 2055 ierr = PetscFree2(rows,sizes);CHKERRQ(ierr); 2056 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2057 PetscFunctionReturn(0); 2058 } 2059 2060 #undef __FUNCT__ 2061 #define __FUNCT__ "MatZeroRowsColumns_SeqBAIJ" 2062 PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b) 2063 { 2064 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 2065 PetscErrorCode ierr; 2066 PetscInt i,j,k,count; 2067 PetscInt bs =A->rmap->bs,bs2=baij->bs2,row,col; 2068 PetscScalar zero = 0.0; 2069 MatScalar *aa; 2070 const PetscScalar *xx; 2071 PetscScalar *bb; 2072 PetscBool *zeroed,vecs = PETSC_FALSE; 2073 2074 PetscFunctionBegin; 2075 /* fix right hand side if needed */ 2076 if (x && b) { 2077 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2078 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2079 vecs = PETSC_TRUE; 2080 } 2081 A->same_nonzero = PETSC_TRUE; 2082 2083 /* zero the columns */ 2084 ierr = PetscMalloc(A->rmap->n*sizeof(PetscBool),&zeroed);CHKERRQ(ierr); 2085 ierr = PetscMemzero(zeroed,A->rmap->n*sizeof(PetscBool));CHKERRQ(ierr); 2086 for (i=0; i<is_n; i++) { 2087 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]); 2088 zeroed[is_idx[i]] = PETSC_TRUE; 2089 } 2090 for (i=0; i<A->rmap->N; i++) { 2091 if (!zeroed[i]) { 2092 row = i/bs; 2093 for (j=baij->i[row]; j<baij->i[row+1]; j++) { 2094 for (k=0; k<bs; k++) { 2095 col = bs*baij->j[j] + k; 2096 if (zeroed[col]) { 2097 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 2098 if (vecs) bb[i] -= aa[0]*xx[col]; 2099 aa[0] = 0.0; 2100 } 2101 } 2102 } 2103 } else if (vecs) bb[i] = diag*xx[i]; 2104 } 2105 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2106 if (vecs) { 2107 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2108 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2109 } 2110 2111 /* zero the rows */ 2112 for (i=0; i<is_n; i++) { 2113 row = is_idx[i]; 2114 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 2115 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 2116 for (k=0; k<count; k++) { 2117 aa[0] = zero; 2118 aa += bs; 2119 } 2120 if (diag != (PetscScalar)0.0) { 2121 ierr = (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 2122 } 2123 } 2124 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2125 PetscFunctionReturn(0); 2126 } 2127 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatSetValues_SeqBAIJ" 2130 PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 2131 { 2132 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2133 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1; 2134 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 2135 PetscInt *aj =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol; 2136 PetscErrorCode ierr; 2137 PetscInt ridx,cidx,bs2=a->bs2; 2138 PetscBool roworiented=a->roworiented; 2139 MatScalar *ap,value,*aa=a->a,*bap; 2140 2141 PetscFunctionBegin; 2142 if (v) PetscValidScalarPointer(v,6); 2143 for (k=0; k<m; k++) { /* loop over added rows */ 2144 row = im[k]; 2145 brow = row/bs; 2146 if (row < 0) continue; 2147 #if defined(PETSC_USE_DEBUG) 2148 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); 2149 #endif 2150 rp = aj + ai[brow]; 2151 ap = aa + bs2*ai[brow]; 2152 rmax = imax[brow]; 2153 nrow = ailen[brow]; 2154 low = 0; 2155 high = nrow; 2156 for (l=0; l<n; l++) { /* loop over added columns */ 2157 if (in[l] < 0) continue; 2158 #if defined(PETSC_USE_DEBUG) 2159 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); 2160 #endif 2161 col = in[l]; bcol = col/bs; 2162 ridx = row % bs; cidx = col % bs; 2163 if (roworiented) { 2164 value = v[l + k*n]; 2165 } else { 2166 value = v[k + l*m]; 2167 } 2168 if (col <= lastcol) low = 0; else high = nrow; 2169 lastcol = col; 2170 while (high-low > 7) { 2171 t = (low+high)/2; 2172 if (rp[t] > bcol) high = t; 2173 else low = t; 2174 } 2175 for (i=low; i<high; i++) { 2176 if (rp[i] > bcol) break; 2177 if (rp[i] == bcol) { 2178 bap = ap + bs2*i + bs*cidx + ridx; 2179 if (is == ADD_VALUES) *bap += value; 2180 else *bap = value; 2181 goto noinsert1; 2182 } 2183 } 2184 if (nonew == 1) goto noinsert1; 2185 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 2186 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 2187 N = nrow++ - 1; high++; 2188 /* shift up all the later entries in this row */ 2189 for (ii=N; ii>=i; ii--) { 2190 rp[ii+1] = rp[ii]; 2191 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 2192 } 2193 if (N>=i) { 2194 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 2195 } 2196 rp[i] = bcol; 2197 ap[bs2*i + bs*cidx + ridx] = value; 2198 a->nz++; 2199 noinsert1:; 2200 low = i; 2201 } 2202 ailen[brow] = nrow; 2203 } 2204 A->same_nonzero = PETSC_FALSE; 2205 PetscFunctionReturn(0); 2206 } 2207 2208 #undef __FUNCT__ 2209 #define __FUNCT__ "MatILUFactor_SeqBAIJ" 2210 PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2211 { 2212 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inA->data; 2213 Mat outA; 2214 PetscErrorCode ierr; 2215 PetscBool row_identity,col_identity; 2216 2217 PetscFunctionBegin; 2218 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU"); 2219 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2220 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2221 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU"); 2222 2223 outA = inA; 2224 inA->factortype = MAT_FACTOR_LU; 2225 2226 ierr = MatMarkDiagonal_SeqBAIJ(inA);CHKERRQ(ierr); 2227 2228 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2229 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2230 a->row = row; 2231 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2232 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2233 a->col = col; 2234 2235 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 2236 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2237 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2238 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2239 2240 ierr = MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));CHKERRQ(ierr); 2241 if (!a->solve_work) { 2242 ierr = PetscMalloc((inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 2243 ierr = PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));CHKERRQ(ierr); 2244 } 2245 ierr = MatLUFactorNumeric(outA,inA,info);CHKERRQ(ierr); 2246 PetscFunctionReturn(0); 2247 } 2248 2249 #undef __FUNCT__ 2250 #define __FUNCT__ "MatSeqBAIJSetColumnIndices_SeqBAIJ" 2251 PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices) 2252 { 2253 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data; 2254 PetscInt i,nz,mbs; 2255 2256 PetscFunctionBegin; 2257 nz = baij->maxnz; 2258 mbs = baij->mbs; 2259 for (i=0; i<nz; i++) { 2260 baij->j[i] = indices[i]; 2261 } 2262 baij->nz = nz; 2263 for (i=0; i<mbs; i++) { 2264 baij->ilen[i] = baij->imax[i]; 2265 } 2266 PetscFunctionReturn(0); 2267 } 2268 2269 #undef __FUNCT__ 2270 #define __FUNCT__ "MatSeqBAIJSetColumnIndices" 2271 /*@ 2272 MatSeqBAIJSetColumnIndices - Set the column indices for all the rows 2273 in the matrix. 2274 2275 Input Parameters: 2276 + mat - the SeqBAIJ matrix 2277 - indices - the column indices 2278 2279 Level: advanced 2280 2281 Notes: 2282 This can be called if you have precomputed the nonzero structure of the 2283 matrix and want to provide it to the matrix object to improve the performance 2284 of the MatSetValues() operation. 2285 2286 You MUST have set the correct numbers of nonzeros per row in the call to 2287 MatCreateSeqBAIJ(), and the columns indices MUST be sorted. 2288 2289 MUST be called before any calls to MatSetValues(); 2290 2291 @*/ 2292 PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices) 2293 { 2294 PetscErrorCode ierr; 2295 2296 PetscFunctionBegin; 2297 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2298 PetscValidPointer(indices,2); 2299 ierr = PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 2300 PetscFunctionReturn(0); 2301 } 2302 2303 #undef __FUNCT__ 2304 #define __FUNCT__ "MatGetRowMaxAbs_SeqBAIJ" 2305 PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[]) 2306 { 2307 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2308 PetscErrorCode ierr; 2309 PetscInt i,j,n,row,bs,*ai,*aj,mbs; 2310 PetscReal atmp; 2311 PetscScalar *x,zero = 0.0; 2312 MatScalar *aa; 2313 PetscInt ncols,brow,krow,kcol; 2314 2315 PetscFunctionBegin; 2316 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2317 bs = A->rmap->bs; 2318 aa = a->a; 2319 ai = a->i; 2320 aj = a->j; 2321 mbs = a->mbs; 2322 2323 ierr = VecSet(v,zero);CHKERRQ(ierr); 2324 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2325 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2326 if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2327 for (i=0; i<mbs; i++) { 2328 ncols = ai[1] - ai[0]; ai++; 2329 brow = bs*i; 2330 for (j=0; j<ncols; j++) { 2331 for (kcol=0; kcol<bs; kcol++) { 2332 for (krow=0; krow<bs; krow++) { 2333 atmp = PetscAbsScalar(*aa);aa++; 2334 row = brow + krow; /* row index */ 2335 /* printf("val[%d,%d]: %G\n",row,bcol+kcol,atmp); */ 2336 if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;} 2337 } 2338 } 2339 aj++; 2340 } 2341 } 2342 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2343 PetscFunctionReturn(0); 2344 } 2345 2346 #undef __FUNCT__ 2347 #define __FUNCT__ "MatCopy_SeqBAIJ" 2348 PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str) 2349 { 2350 PetscErrorCode ierr; 2351 2352 PetscFunctionBegin; 2353 /* If the two matrices have the same copy implementation, use fast copy. */ 2354 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2355 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2356 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)B->data; 2357 PetscInt ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs; 2358 2359 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]); 2360 if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs); 2361 ierr = PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));CHKERRQ(ierr); 2362 } else { 2363 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2364 } 2365 PetscFunctionReturn(0); 2366 } 2367 2368 #undef __FUNCT__ 2369 #define __FUNCT__ "MatSetUp_SeqBAIJ" 2370 PetscErrorCode MatSetUp_SeqBAIJ(Mat A) 2371 { 2372 PetscErrorCode ierr; 2373 2374 PetscFunctionBegin; 2375 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(A,A->rmap->bs,PETSC_DEFAULT,0);CHKERRQ(ierr); 2376 PetscFunctionReturn(0); 2377 } 2378 2379 #undef __FUNCT__ 2380 #define __FUNCT__ "MatSeqBAIJGetArray_SeqBAIJ" 2381 PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[]) 2382 { 2383 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2384 2385 PetscFunctionBegin; 2386 *array = a->a; 2387 PetscFunctionReturn(0); 2388 } 2389 2390 #undef __FUNCT__ 2391 #define __FUNCT__ "MatSeqBAIJRestoreArray_SeqBAIJ" 2392 PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[]) 2393 { 2394 PetscFunctionBegin; 2395 PetscFunctionReturn(0); 2396 } 2397 2398 #undef __FUNCT__ 2399 #define __FUNCT__ "MatAXPY_SeqBAIJ" 2400 PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2401 { 2402 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data; 2403 PetscErrorCode ierr; 2404 PetscInt i,bs=Y->rmap->bs,j,bs2=bs*bs; 2405 PetscBLASInt one=1; 2406 2407 PetscFunctionBegin; 2408 if (str == SAME_NONZERO_PATTERN) { 2409 PetscScalar alpha = a; 2410 PetscBLASInt bnz; 2411 ierr = PetscBLASIntCast(x->nz*bs2,&bnz);CHKERRQ(ierr); 2412 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2413 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2414 if (y->xtoy && y->XtoY != X) { 2415 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2416 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2417 } 2418 if (!y->xtoy) { /* get xtoy */ 2419 ierr = MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 2420 y->XtoY = X; 2421 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2422 } 2423 for (i=0; i<x->nz; i++) { 2424 j = 0; 2425 while (j < bs2) { 2426 y->a[bs2*y->xtoy[i]+j] += a*(x->a[bs2*i+j]); 2427 j++; 2428 } 2429 } 2430 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %D/%D = %G\n",bs2*x->nz,bs2*y->nz,(PetscReal)(bs2*x->nz)/(bs2*y->nz));CHKERRQ(ierr); 2431 } else { 2432 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2433 } 2434 PetscFunctionReturn(0); 2435 } 2436 2437 #undef __FUNCT__ 2438 #define __FUNCT__ "MatRealPart_SeqBAIJ" 2439 PetscErrorCode MatRealPart_SeqBAIJ(Mat A) 2440 { 2441 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2442 PetscInt i,nz = a->bs2*a->i[a->mbs]; 2443 MatScalar *aa = a->a; 2444 2445 PetscFunctionBegin; 2446 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 2447 PetscFunctionReturn(0); 2448 } 2449 2450 #undef __FUNCT__ 2451 #define __FUNCT__ "MatImaginaryPart_SeqBAIJ" 2452 PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A) 2453 { 2454 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2455 PetscInt i,nz = a->bs2*a->i[a->mbs]; 2456 MatScalar *aa = a->a; 2457 2458 PetscFunctionBegin; 2459 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 2460 PetscFunctionReturn(0); 2461 } 2462 2463 #undef __FUNCT__ 2464 #define __FUNCT__ "MatGetColumnIJ_SeqBAIJ" 2465 /* 2466 Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code 2467 */ 2468 PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 2469 { 2470 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2471 PetscErrorCode ierr; 2472 PetscInt bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs; 2473 PetscInt nz = a->i[m],row,*jj,mr,col; 2474 2475 PetscFunctionBegin; 2476 *nn = n; 2477 if (!ia) PetscFunctionReturn(0); 2478 if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices"); 2479 else { 2480 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 2481 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2482 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 2483 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 2484 jj = a->j; 2485 for (i=0; i<nz; i++) { 2486 collengths[jj[i]]++; 2487 } 2488 cia[0] = oshift; 2489 for (i=0; i<n; i++) { 2490 cia[i+1] = cia[i] + collengths[i]; 2491 } 2492 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2493 jj = a->j; 2494 for (row=0; row<m; row++) { 2495 mr = a->i[row+1] - a->i[row]; 2496 for (i=0; i<mr; i++) { 2497 col = *jj++; 2498 2499 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 2500 } 2501 } 2502 ierr = PetscFree(collengths);CHKERRQ(ierr); 2503 *ia = cia; *ja = cja; 2504 } 2505 PetscFunctionReturn(0); 2506 } 2507 2508 #undef __FUNCT__ 2509 #define __FUNCT__ "MatRestoreColumnIJ_SeqBAIJ" 2510 PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 2511 { 2512 PetscErrorCode ierr; 2513 2514 PetscFunctionBegin; 2515 if (!ia) PetscFunctionReturn(0); 2516 ierr = PetscFree(*ia);CHKERRQ(ierr); 2517 ierr = PetscFree(*ja);CHKERRQ(ierr); 2518 PetscFunctionReturn(0); 2519 } 2520 2521 /* 2522 MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from 2523 MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output 2524 spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate() 2525 */ 2526 #undef __FUNCT__ 2527 #define __FUNCT__ "MatGetColumnIJ_SeqBAIJ_Color" 2528 PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 2529 { 2530 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2531 PetscErrorCode ierr; 2532 PetscInt i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs; 2533 PetscInt nz = a->i[m],row,*jj,mr,col; 2534 PetscInt *cspidx; 2535 2536 PetscFunctionBegin; 2537 *nn = n; 2538 if (!ia) PetscFunctionReturn(0); 2539 2540 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 2541 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2542 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 2543 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 2544 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cspidx);CHKERRQ(ierr); 2545 jj = a->j; 2546 for (i=0; i<nz; i++) { 2547 collengths[jj[i]]++; 2548 } 2549 cia[0] = oshift; 2550 for (i=0; i<n; i++) { 2551 cia[i+1] = cia[i] + collengths[i]; 2552 } 2553 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2554 jj = a->j; 2555 for (row=0; row<m; row++) { 2556 mr = a->i[row+1] - a->i[row]; 2557 for (i=0; i<mr; i++) { 2558 col = *jj++; 2559 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 2560 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 2561 } 2562 } 2563 ierr = PetscFree(collengths);CHKERRQ(ierr); 2564 *ia = cia; *ja = cja; 2565 *spidx = cspidx; 2566 PetscFunctionReturn(0); 2567 } 2568 2569 #undef __FUNCT__ 2570 #define __FUNCT__ "MatRestoreColumnIJ_SeqBAIJ_Color" 2571 PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 2572 { 2573 PetscErrorCode ierr; 2574 2575 PetscFunctionBegin; 2576 ierr = MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 2577 ierr = PetscFree(*spidx);CHKERRQ(ierr); 2578 PetscFunctionReturn(0); 2579 } 2580 2581 /* -------------------------------------------------------------------*/ 2582 static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ, 2583 MatGetRow_SeqBAIJ, 2584 MatRestoreRow_SeqBAIJ, 2585 MatMult_SeqBAIJ_N, 2586 /* 4*/ MatMultAdd_SeqBAIJ_N, 2587 MatMultTranspose_SeqBAIJ, 2588 MatMultTransposeAdd_SeqBAIJ, 2589 0, 2590 0, 2591 0, 2592 /* 10*/ 0, 2593 MatLUFactor_SeqBAIJ, 2594 0, 2595 0, 2596 MatTranspose_SeqBAIJ, 2597 /* 15*/ MatGetInfo_SeqBAIJ, 2598 MatEqual_SeqBAIJ, 2599 MatGetDiagonal_SeqBAIJ, 2600 MatDiagonalScale_SeqBAIJ, 2601 MatNorm_SeqBAIJ, 2602 /* 20*/ 0, 2603 MatAssemblyEnd_SeqBAIJ, 2604 MatSetOption_SeqBAIJ, 2605 MatZeroEntries_SeqBAIJ, 2606 /* 24*/ MatZeroRows_SeqBAIJ, 2607 0, 2608 0, 2609 0, 2610 0, 2611 /* 29*/ MatSetUp_SeqBAIJ, 2612 0, 2613 0, 2614 0, 2615 0, 2616 /* 34*/ MatDuplicate_SeqBAIJ, 2617 0, 2618 0, 2619 MatILUFactor_SeqBAIJ, 2620 0, 2621 /* 39*/ MatAXPY_SeqBAIJ, 2622 MatGetSubMatrices_SeqBAIJ, 2623 MatIncreaseOverlap_SeqBAIJ, 2624 MatGetValues_SeqBAIJ, 2625 MatCopy_SeqBAIJ, 2626 /* 44*/ 0, 2627 MatScale_SeqBAIJ, 2628 0, 2629 0, 2630 MatZeroRowsColumns_SeqBAIJ, 2631 /* 49*/ 0, 2632 MatGetRowIJ_SeqBAIJ, 2633 MatRestoreRowIJ_SeqBAIJ, 2634 MatGetColumnIJ_SeqBAIJ, 2635 MatRestoreColumnIJ_SeqBAIJ, 2636 /* 54*/ 0, 2637 0, 2638 0, 2639 0, 2640 MatSetValuesBlocked_SeqBAIJ, 2641 /* 59*/ MatGetSubMatrix_SeqBAIJ, 2642 MatDestroy_SeqBAIJ, 2643 MatView_SeqBAIJ, 2644 0, 2645 0, 2646 /* 64*/ 0, 2647 0, 2648 0, 2649 0, 2650 0, 2651 /* 69*/ MatGetRowMaxAbs_SeqBAIJ, 2652 0, 2653 MatConvert_Basic, 2654 0, 2655 0, 2656 /* 74*/ 0, 2657 MatFDColoringApply_BAIJ, 2658 0, 2659 0, 2660 0, 2661 /* 79*/ 0, 2662 0, 2663 0, 2664 0, 2665 MatLoad_SeqBAIJ, 2666 /* 84*/ 0, 2667 0, 2668 0, 2669 0, 2670 0, 2671 /* 89*/ 0, 2672 0, 2673 0, 2674 0, 2675 0, 2676 /* 94*/ 0, 2677 0, 2678 0, 2679 0, 2680 0, 2681 /* 99*/ 0, 2682 0, 2683 0, 2684 0, 2685 0, 2686 /*104*/ 0, 2687 MatRealPart_SeqBAIJ, 2688 MatImaginaryPart_SeqBAIJ, 2689 0, 2690 0, 2691 /*109*/ 0, 2692 0, 2693 0, 2694 0, 2695 MatMissingDiagonal_SeqBAIJ, 2696 /*114*/ 0, 2697 0, 2698 0, 2699 0, 2700 0, 2701 /*119*/ 0, 2702 0, 2703 MatMultHermitianTranspose_SeqBAIJ, 2704 MatMultHermitianTransposeAdd_SeqBAIJ, 2705 0, 2706 /*124*/ 0, 2707 0, 2708 MatInvertBlockDiagonal_SeqBAIJ, 2709 0, 2710 0, 2711 /*129*/ 0, 2712 0, 2713 0, 2714 0, 2715 0, 2716 /*134*/ 0, 2717 0, 2718 0, 2719 0, 2720 0, 2721 /*139*/ 0, 2722 0, 2723 MatFDColoringSetUp_SeqXAIJ 2724 }; 2725 2726 #undef __FUNCT__ 2727 #define __FUNCT__ "MatStoreValues_SeqBAIJ" 2728 PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat) 2729 { 2730 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data; 2731 PetscInt nz = aij->i[aij->mbs]*aij->bs2; 2732 PetscErrorCode ierr; 2733 2734 PetscFunctionBegin; 2735 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2736 2737 /* allocate space for values if not already there */ 2738 if (!aij->saved_values) { 2739 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 2740 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2741 } 2742 2743 /* copy values over */ 2744 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2745 PetscFunctionReturn(0); 2746 } 2747 2748 #undef __FUNCT__ 2749 #define __FUNCT__ "MatRetrieveValues_SeqBAIJ" 2750 PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat) 2751 { 2752 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data; 2753 PetscErrorCode ierr; 2754 PetscInt nz = aij->i[aij->mbs]*aij->bs2; 2755 2756 PetscFunctionBegin; 2757 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2758 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2759 2760 /* copy values over */ 2761 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2762 PetscFunctionReturn(0); 2763 } 2764 2765 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*); 2766 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*); 2767 2768 #undef __FUNCT__ 2769 #define __FUNCT__ "MatSeqBAIJSetPreallocation_SeqBAIJ" 2770 PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz) 2771 { 2772 Mat_SeqBAIJ *b; 2773 PetscErrorCode ierr; 2774 PetscInt i,mbs,nbs,bs2; 2775 PetscBool flg,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 2776 2777 PetscFunctionBegin; 2778 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 2779 if (nz == MAT_SKIP_ALLOCATION) { 2780 skipallocation = PETSC_TRUE; 2781 nz = 0; 2782 } 2783 2784 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2785 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2786 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2787 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2788 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2789 2790 B->preallocated = PETSC_TRUE; 2791 2792 mbs = B->rmap->n/bs; 2793 nbs = B->cmap->n/bs; 2794 bs2 = bs*bs; 2795 2796 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); 2797 2798 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2799 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 2800 if (nnz) { 2801 for (i=0; i<mbs; i++) { 2802 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]); 2803 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); 2804 } 2805 } 2806 2807 b = (Mat_SeqBAIJ*)B->data; 2808 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");CHKERRQ(ierr); 2809 ierr = PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 2810 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2811 2812 if (!flg) { 2813 switch (bs) { 2814 case 1: 2815 B->ops->mult = MatMult_SeqBAIJ_1; 2816 B->ops->multadd = MatMultAdd_SeqBAIJ_1; 2817 break; 2818 case 2: 2819 B->ops->mult = MatMult_SeqBAIJ_2; 2820 B->ops->multadd = MatMultAdd_SeqBAIJ_2; 2821 break; 2822 case 3: 2823 B->ops->mult = MatMult_SeqBAIJ_3; 2824 B->ops->multadd = MatMultAdd_SeqBAIJ_3; 2825 break; 2826 case 4: 2827 B->ops->mult = MatMult_SeqBAIJ_4; 2828 B->ops->multadd = MatMultAdd_SeqBAIJ_4; 2829 break; 2830 case 5: 2831 B->ops->mult = MatMult_SeqBAIJ_5; 2832 B->ops->multadd = MatMultAdd_SeqBAIJ_5; 2833 break; 2834 case 6: 2835 B->ops->mult = MatMult_SeqBAIJ_6; 2836 B->ops->multadd = MatMultAdd_SeqBAIJ_6; 2837 break; 2838 case 7: 2839 B->ops->mult = MatMult_SeqBAIJ_7; 2840 B->ops->multadd = MatMultAdd_SeqBAIJ_7; 2841 break; 2842 case 15: 2843 B->ops->mult = MatMult_SeqBAIJ_15_ver1; 2844 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2845 break; 2846 default: 2847 B->ops->mult = MatMult_SeqBAIJ_N; 2848 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2849 break; 2850 } 2851 } 2852 B->ops->sor = MatSOR_SeqBAIJ; 2853 b->mbs = mbs; 2854 b->nbs = nbs; 2855 if (!skipallocation) { 2856 if (!b->imax) { 2857 ierr = PetscMalloc2(mbs,PetscInt,&b->imax,mbs,PetscInt,&b->ilen);CHKERRQ(ierr); 2858 ierr = PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));CHKERRQ(ierr); 2859 2860 b->free_imax_ilen = PETSC_TRUE; 2861 } 2862 /* b->ilen will count nonzeros in each block row so far. */ 2863 for (i=0; i<mbs; i++) b->ilen[i] = 0; 2864 if (!nnz) { 2865 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2866 else if (nz < 0) nz = 1; 2867 for (i=0; i<mbs; i++) b->imax[i] = nz; 2868 nz = nz*mbs; 2869 } else { 2870 nz = 0; 2871 for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 2872 } 2873 2874 /* allocate the matrix space */ 2875 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 2876 ierr = PetscMalloc3(bs2*nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->N+1,PetscInt,&b->i);CHKERRQ(ierr); 2877 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 2878 ierr = PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));CHKERRQ(ierr); 2879 ierr = PetscMemzero(b->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 2880 2881 b->singlemalloc = PETSC_TRUE; 2882 b->i[0] = 0; 2883 for (i=1; i<mbs+1; i++) { 2884 b->i[i] = b->i[i-1] + b->imax[i-1]; 2885 } 2886 b->free_a = PETSC_TRUE; 2887 b->free_ij = PETSC_TRUE; 2888 } else { 2889 b->free_a = PETSC_FALSE; 2890 b->free_ij = PETSC_FALSE; 2891 } 2892 2893 b->bs2 = bs2; 2894 b->mbs = mbs; 2895 b->nz = 0; 2896 b->maxnz = nz; 2897 B->info.nz_unneeded = (PetscReal)b->maxnz*bs2; 2898 if (realalloc) {ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);} 2899 PetscFunctionReturn(0); 2900 } 2901 2902 #undef __FUNCT__ 2903 #define __FUNCT__ "MatSeqBAIJSetPreallocationCSR_SeqBAIJ" 2904 PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2905 { 2906 PetscInt i,m,nz,nz_max=0,*nnz; 2907 PetscScalar *values=0; 2908 PetscErrorCode ierr; 2909 2910 PetscFunctionBegin; 2911 if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 2912 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2913 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2914 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2915 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2916 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2917 m = B->rmap->n/bs; 2918 2919 if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]); 2920 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 2921 for (i=0; i<m; i++) { 2922 nz = ii[i+1]- ii[i]; 2923 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz); 2924 nz_max = PetscMax(nz_max, nz); 2925 nnz[i] = nz; 2926 } 2927 ierr = MatSeqBAIJSetPreallocation(B,bs,0,nnz);CHKERRQ(ierr); 2928 ierr = PetscFree(nnz);CHKERRQ(ierr); 2929 2930 values = (PetscScalar*)V; 2931 if (!values) { 2932 ierr = PetscMalloc(bs*bs*(nz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2933 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2934 } 2935 for (i=0; i<m; i++) { 2936 PetscInt ncols = ii[i+1] - ii[i]; 2937 const PetscInt *icols = jj + ii[i]; 2938 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2939 ierr = MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2940 } 2941 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2942 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2943 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2944 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2945 PetscFunctionReturn(0); 2946 } 2947 2948 PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_petsc(Mat,MatFactorType,Mat*); 2949 PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_bstrm(Mat,MatFactorType,Mat*); 2950 #if defined(PETSC_HAVE_MUMPS) 2951 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2952 #endif 2953 extern PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat,MatFactorType,PetscBool*); 2954 2955 /*MC 2956 MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on 2957 block sparse compressed row format. 2958 2959 Options Database Keys: 2960 . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions() 2961 2962 Level: beginner 2963 2964 .seealso: MatCreateSeqBAIJ() 2965 M*/ 2966 2967 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*); 2968 2969 #undef __FUNCT__ 2970 #define __FUNCT__ "MatCreate_SeqBAIJ" 2971 PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B) 2972 { 2973 PetscErrorCode ierr; 2974 PetscMPIInt size; 2975 Mat_SeqBAIJ *b; 2976 2977 PetscFunctionBegin; 2978 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2979 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2980 2981 ierr = PetscNewLog(B,Mat_SeqBAIJ,&b);CHKERRQ(ierr); 2982 B->data = (void*)b; 2983 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2984 2985 b->row = 0; 2986 b->col = 0; 2987 b->icol = 0; 2988 b->reallocs = 0; 2989 b->saved_values = 0; 2990 2991 b->roworiented = PETSC_TRUE; 2992 b->nonew = 0; 2993 b->diag = 0; 2994 b->solve_work = 0; 2995 b->mult_work = 0; 2996 B->spptr = 0; 2997 B->info.nz_unneeded = (PetscReal)b->maxnz*b->bs2; 2998 b->keepnonzeropattern = PETSC_FALSE; 2999 b->xtoy = 0; 3000 b->XtoY = 0; 3001 B->same_nonzero = PETSC_FALSE; 3002 3003 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqbaij_petsc);CHKERRQ(ierr); 3004 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqbaij_petsc);CHKERRQ(ierr); 3005 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bstrm_C",MatGetFactor_seqbaij_bstrm);CHKERRQ(ierr); 3006 #if defined(PETSC_HAVE_MUMPS) 3007 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C", MatGetFactor_baij_mumps);CHKERRQ(ierr); 3008 #endif 3009 ierr = PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);CHKERRQ(ierr); 3010 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);CHKERRQ(ierr); 3011 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);CHKERRQ(ierr); 3012 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);CHKERRQ(ierr); 3013 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);CHKERRQ(ierr); 3014 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);CHKERRQ(ierr); 3015 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);CHKERRQ(ierr); 3016 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);CHKERRQ(ierr); 3017 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqbstrm_C",MatConvert_SeqBAIJ_SeqBSTRM);CHKERRQ(ierr); 3018 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);CHKERRQ(ierr); 3019 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);CHKERRQ(ierr); 3020 PetscFunctionReturn(0); 3021 } 3022 3023 #undef __FUNCT__ 3024 #define __FUNCT__ "MatDuplicateNoCreate_SeqBAIJ" 3025 PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 3026 { 3027 Mat_SeqBAIJ *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data; 3028 PetscErrorCode ierr; 3029 PetscInt i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2; 3030 3031 PetscFunctionBegin; 3032 if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix"); 3033 3034 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3035 c->imax = a->imax; 3036 c->ilen = a->ilen; 3037 c->free_imax_ilen = PETSC_FALSE; 3038 } else { 3039 ierr = PetscMalloc2(mbs,PetscInt,&c->imax,mbs,PetscInt,&c->ilen);CHKERRQ(ierr); 3040 ierr = PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));CHKERRQ(ierr); 3041 for (i=0; i<mbs; i++) { 3042 c->imax[i] = a->imax[i]; 3043 c->ilen[i] = a->ilen[i]; 3044 } 3045 c->free_imax_ilen = PETSC_TRUE; 3046 } 3047 3048 /* allocate the matrix space */ 3049 if (mallocmatspace) { 3050 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3051 ierr = PetscMalloc(bs2*nz*sizeof(PetscScalar),&c->a);CHKERRQ(ierr); 3052 ierr = PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));CHKERRQ(ierr); 3053 ierr = PetscMemzero(c->a,bs2*nz*sizeof(PetscScalar));CHKERRQ(ierr); 3054 3055 c->i = a->i; 3056 c->j = a->j; 3057 c->singlemalloc = PETSC_FALSE; 3058 c->free_a = PETSC_TRUE; 3059 c->free_ij = PETSC_FALSE; 3060 c->parent = A; 3061 C->preallocated = PETSC_TRUE; 3062 C->assembled = PETSC_TRUE; 3063 3064 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 3065 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3066 ierr = MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3067 } else { 3068 ierr = PetscMalloc3(bs2*nz,PetscScalar,&c->a,nz,PetscInt,&c->j,mbs+1,PetscInt,&c->i);CHKERRQ(ierr); 3069 ierr = PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3070 3071 c->singlemalloc = PETSC_TRUE; 3072 c->free_a = PETSC_TRUE; 3073 c->free_ij = PETSC_TRUE; 3074 3075 ierr = PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3076 if (mbs > 0) { 3077 ierr = PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 3078 if (cpvalues == MAT_COPY_VALUES) { 3079 ierr = PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 3080 } else { 3081 ierr = PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 3082 } 3083 } 3084 C->preallocated = PETSC_TRUE; 3085 C->assembled = PETSC_TRUE; 3086 } 3087 } 3088 3089 c->roworiented = a->roworiented; 3090 c->nonew = a->nonew; 3091 3092 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 3093 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 3094 3095 c->bs2 = a->bs2; 3096 c->mbs = a->mbs; 3097 c->nbs = a->nbs; 3098 3099 if (a->diag) { 3100 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3101 c->diag = a->diag; 3102 c->free_diag = PETSC_FALSE; 3103 } else { 3104 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 3105 ierr = PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3106 for (i=0; i<mbs; i++) c->diag[i] = a->diag[i]; 3107 c->free_diag = PETSC_TRUE; 3108 } 3109 } else c->diag = 0; 3110 3111 c->nz = a->nz; 3112 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 3113 c->solve_work = 0; 3114 c->mult_work = 0; 3115 3116 c->compressedrow.use = a->compressedrow.use; 3117 c->compressedrow.nrows = a->compressedrow.nrows; 3118 c->compressedrow.check = a->compressedrow.check; 3119 if (a->compressedrow.use) { 3120 i = a->compressedrow.nrows; 3121 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i+1,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 3122 ierr = PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3123 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3124 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 3125 } else { 3126 c->compressedrow.use = PETSC_FALSE; 3127 c->compressedrow.i = NULL; 3128 c->compressedrow.rindex = NULL; 3129 } 3130 C->same_nonzero = A->same_nonzero; 3131 3132 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 3133 ierr = PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3134 PetscFunctionReturn(0); 3135 } 3136 3137 #undef __FUNCT__ 3138 #define __FUNCT__ "MatDuplicate_SeqBAIJ" 3139 PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 3140 { 3141 PetscErrorCode ierr; 3142 3143 PetscFunctionBegin; 3144 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 3145 ierr = MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);CHKERRQ(ierr); 3146 ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr); 3147 ierr = MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 3148 PetscFunctionReturn(0); 3149 } 3150 3151 #undef __FUNCT__ 3152 #define __FUNCT__ "MatLoad_SeqBAIJ" 3153 PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer) 3154 { 3155 Mat_SeqBAIJ *a; 3156 PetscErrorCode ierr; 3157 PetscInt i,nz,header[4],*rowlengths=0,M,N,bs=1; 3158 PetscInt *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount; 3159 PetscInt kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols; 3160 PetscInt *masked,nmask,tmp,bs2,ishift; 3161 PetscMPIInt size; 3162 int fd; 3163 PetscScalar *aa; 3164 MPI_Comm comm; 3165 3166 PetscFunctionBegin; 3167 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3168 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");CHKERRQ(ierr); 3169 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3170 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3171 bs2 = bs*bs; 3172 3173 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3174 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 3175 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3176 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 3177 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object"); 3178 M = header[1]; N = header[2]; nz = header[3]; 3179 3180 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ"); 3181 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 3182 3183 /* 3184 This code adds extra rows to make sure the number of rows is 3185 divisible by the blocksize 3186 */ 3187 mbs = M/bs; 3188 extra_rows = bs - M + bs*(mbs); 3189 if (extra_rows == bs) extra_rows = 0; 3190 else mbs++; 3191 if (extra_rows) { 3192 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3193 } 3194 3195 /* Set global sizes if not already set */ 3196 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 3197 ierr = MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3198 } else { /* Check if the matrix global sizes are correct */ 3199 ierr = MatGetSize(newmat,&rows,&cols);CHKERRQ(ierr); 3200 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 3201 ierr = MatGetLocalSize(newmat,&rows,&cols);CHKERRQ(ierr); 3202 } 3203 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); 3204 } 3205 3206 /* read in row lengths */ 3207 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3208 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 3209 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 3210 3211 /* read in column indices */ 3212 ierr = PetscMalloc((nz+extra_rows)*sizeof(PetscInt),&jj);CHKERRQ(ierr); 3213 ierr = PetscBinaryRead(fd,jj,nz,PETSC_INT);CHKERRQ(ierr); 3214 for (i=0; i<extra_rows; i++) jj[nz+i] = M+i; 3215 3216 /* loop over row lengths determining block row lengths */ 3217 ierr = PetscMalloc(mbs*sizeof(PetscInt),&browlengths);CHKERRQ(ierr); 3218 ierr = PetscMemzero(browlengths,mbs*sizeof(PetscInt));CHKERRQ(ierr); 3219 ierr = PetscMalloc2(mbs,PetscInt,&mask,mbs,PetscInt,&masked);CHKERRQ(ierr); 3220 ierr = PetscMemzero(mask,mbs*sizeof(PetscInt));CHKERRQ(ierr); 3221 rowcount = 0; 3222 nzcount = 0; 3223 for (i=0; i<mbs; i++) { 3224 nmask = 0; 3225 for (j=0; j<bs; j++) { 3226 kmax = rowlengths[rowcount]; 3227 for (k=0; k<kmax; k++) { 3228 tmp = jj[nzcount++]/bs; 3229 if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;} 3230 } 3231 rowcount++; 3232 } 3233 browlengths[i] += nmask; 3234 /* zero out the mask elements we set */ 3235 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 3236 } 3237 3238 /* Do preallocation */ 3239 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(newmat,bs,0,browlengths);CHKERRQ(ierr); 3240 a = (Mat_SeqBAIJ*)newmat->data; 3241 3242 /* set matrix "i" values */ 3243 a->i[0] = 0; 3244 for (i=1; i<= mbs; i++) { 3245 a->i[i] = a->i[i-1] + browlengths[i-1]; 3246 a->ilen[i-1] = browlengths[i-1]; 3247 } 3248 a->nz = 0; 3249 for (i=0; i<mbs; i++) a->nz += browlengths[i]; 3250 3251 /* read in nonzero values */ 3252 ierr = PetscMalloc((nz+extra_rows)*sizeof(PetscScalar),&aa);CHKERRQ(ierr); 3253 ierr = PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);CHKERRQ(ierr); 3254 for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0; 3255 3256 /* set "a" and "j" values into matrix */ 3257 nzcount = 0; jcount = 0; 3258 for (i=0; i<mbs; i++) { 3259 nzcountb = nzcount; 3260 nmask = 0; 3261 for (j=0; j<bs; j++) { 3262 kmax = rowlengths[i*bs+j]; 3263 for (k=0; k<kmax; k++) { 3264 tmp = jj[nzcount++]/bs; 3265 if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;} 3266 } 3267 } 3268 /* sort the masked values */ 3269 ierr = PetscSortInt(nmask,masked);CHKERRQ(ierr); 3270 3271 /* set "j" values into matrix */ 3272 maskcount = 1; 3273 for (j=0; j<nmask; j++) { 3274 a->j[jcount++] = masked[j]; 3275 mask[masked[j]] = maskcount++; 3276 } 3277 /* set "a" values into matrix */ 3278 ishift = bs2*a->i[i]; 3279 for (j=0; j<bs; j++) { 3280 kmax = rowlengths[i*bs+j]; 3281 for (k=0; k<kmax; k++) { 3282 tmp = jj[nzcountb]/bs; 3283 block = mask[tmp] - 1; 3284 point = jj[nzcountb] - bs*tmp; 3285 idx = ishift + bs2*block + j + bs*point; 3286 a->a[idx] = (MatScalar)aa[nzcountb++]; 3287 } 3288 } 3289 /* zero out the mask elements we set */ 3290 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 3291 } 3292 if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix"); 3293 3294 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3295 ierr = PetscFree(browlengths);CHKERRQ(ierr); 3296 ierr = PetscFree(aa);CHKERRQ(ierr); 3297 ierr = PetscFree(jj);CHKERRQ(ierr); 3298 ierr = PetscFree2(mask,masked);CHKERRQ(ierr); 3299 3300 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3301 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3302 PetscFunctionReturn(0); 3303 } 3304 3305 #undef __FUNCT__ 3306 #define __FUNCT__ "MatCreateSeqBAIJ" 3307 /*@C 3308 MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block 3309 compressed row) format. For good matrix assembly performance the 3310 user should preallocate the matrix storage by setting the parameter nz 3311 (or the array nnz). By setting these parameters accurately, performance 3312 during matrix assembly can be increased by more than a factor of 50. 3313 3314 Collective on MPI_Comm 3315 3316 Input Parameters: 3317 + comm - MPI communicator, set to PETSC_COMM_SELF 3318 . bs - size of block 3319 . m - number of rows 3320 . n - number of columns 3321 . nz - number of nonzero blocks per block row (same for all rows) 3322 - nnz - array containing the number of nonzero blocks in the various block rows 3323 (possibly different for each block row) or NULL 3324 3325 Output Parameter: 3326 . A - the matrix 3327 3328 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3329 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3330 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3331 3332 Options Database Keys: 3333 . -mat_no_unroll - uses code that does not unroll the loops in the 3334 block calculations (much slower) 3335 . -mat_block_size - size of the blocks to use 3336 3337 Level: intermediate 3338 3339 Notes: 3340 The number of rows and columns must be divisible by blocksize. 3341 3342 If the nnz parameter is given then the nz parameter is ignored 3343 3344 A nonzero block is any block that as 1 or more nonzeros in it 3345 3346 The block AIJ format is fully compatible with standard Fortran 77 3347 storage. That is, the stored row and column indices can begin at 3348 either one (as in Fortran) or zero. See the users' manual for details. 3349 3350 Specify the preallocated storage with either nz or nnz (not both). 3351 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3352 allocation. See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 3353 matrices. 3354 3355 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ() 3356 @*/ 3357 PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3358 { 3359 PetscErrorCode ierr; 3360 3361 PetscFunctionBegin; 3362 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3363 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3364 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3365 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(*A,bs,nz,(PetscInt*)nnz);CHKERRQ(ierr); 3366 PetscFunctionReturn(0); 3367 } 3368 3369 #undef __FUNCT__ 3370 #define __FUNCT__ "MatSeqBAIJSetPreallocation" 3371 /*@C 3372 MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros 3373 per row in the matrix. For good matrix assembly performance the 3374 user should preallocate the matrix storage by setting the parameter nz 3375 (or the array nnz). By setting these parameters accurately, performance 3376 during matrix assembly can be increased by more than a factor of 50. 3377 3378 Collective on MPI_Comm 3379 3380 Input Parameters: 3381 + A - the matrix 3382 . bs - size of block 3383 . nz - number of block nonzeros per block row (same for all rows) 3384 - nnz - array containing the number of block nonzeros in the various block rows 3385 (possibly different for each block row) or NULL 3386 3387 Options Database Keys: 3388 . -mat_no_unroll - uses code that does not unroll the loops in the 3389 block calculations (much slower) 3390 . -mat_block_size - size of the blocks to use 3391 3392 Level: intermediate 3393 3394 Notes: 3395 If the nnz parameter is given then the nz parameter is ignored 3396 3397 You can call MatGetInfo() to get information on how effective the preallocation was; 3398 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3399 You can also run with the option -info and look for messages with the string 3400 malloc in them to see if additional memory allocation was needed. 3401 3402 The block AIJ format is fully compatible with standard Fortran 77 3403 storage. That is, the stored row and column indices can begin at 3404 either one (as in Fortran) or zero. See the users' manual for details. 3405 3406 Specify the preallocated storage with either nz or nnz (not both). 3407 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3408 allocation. See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 3409 3410 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo() 3411 @*/ 3412 PetscErrorCode MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[]) 3413 { 3414 PetscErrorCode ierr; 3415 3416 PetscFunctionBegin; 3417 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3418 PetscValidType(B,1); 3419 PetscValidLogicalCollectiveInt(B,bs,2); 3420 ierr = PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));CHKERRQ(ierr); 3421 PetscFunctionReturn(0); 3422 } 3423 3424 #undef __FUNCT__ 3425 #define __FUNCT__ "MatSeqBAIJSetPreallocationCSR" 3426 /*@C 3427 MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format 3428 (the default sequential PETSc format). 3429 3430 Collective on MPI_Comm 3431 3432 Input Parameters: 3433 + A - the matrix 3434 . i - the indices into j for the start of each local row (starts with zero) 3435 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3436 - v - optional values in the matrix 3437 3438 Level: developer 3439 3440 .keywords: matrix, aij, compressed row, sparse 3441 3442 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ 3443 @*/ 3444 PetscErrorCode MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3445 { 3446 PetscErrorCode ierr; 3447 3448 PetscFunctionBegin; 3449 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3450 PetscValidType(B,1); 3451 PetscValidLogicalCollectiveInt(B,bs,2); 3452 ierr = PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 3453 PetscFunctionReturn(0); 3454 } 3455 3456 3457 #undef __FUNCT__ 3458 #define __FUNCT__ "MatCreateSeqBAIJWithArrays" 3459 /*@ 3460 MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user. 3461 3462 Collective on MPI_Comm 3463 3464 Input Parameters: 3465 + comm - must be an MPI communicator of size 1 3466 . bs - size of block 3467 . m - number of rows 3468 . n - number of columns 3469 . i - row indices 3470 . j - column indices 3471 - a - matrix values 3472 3473 Output Parameter: 3474 . mat - the matrix 3475 3476 Level: advanced 3477 3478 Notes: 3479 The i, j, and a arrays are not copied by this routine, the user must free these arrays 3480 once the matrix is destroyed 3481 3482 You cannot set new nonzero locations into this matrix, that will generate an error. 3483 3484 The i and j indices are 0 based 3485 3486 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). 3487 3488 3489 .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ() 3490 3491 @*/ 3492 PetscErrorCode MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 3493 { 3494 PetscErrorCode ierr; 3495 PetscInt ii; 3496 Mat_SeqBAIJ *baij; 3497 3498 PetscFunctionBegin; 3499 if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs); 3500 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3501 3502 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3503 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 3504 ierr = MatSetType(*mat,MATSEQBAIJ);CHKERRQ(ierr); 3505 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 3506 baij = (Mat_SeqBAIJ*)(*mat)->data; 3507 ierr = PetscMalloc2(m,PetscInt,&baij->imax,m,PetscInt,&baij->ilen);CHKERRQ(ierr); 3508 ierr = PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));CHKERRQ(ierr); 3509 3510 baij->i = i; 3511 baij->j = j; 3512 baij->a = a; 3513 3514 baij->singlemalloc = PETSC_FALSE; 3515 baij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 3516 baij->free_a = PETSC_FALSE; 3517 baij->free_ij = PETSC_FALSE; 3518 3519 for (ii=0; ii<m; ii++) { 3520 baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii]; 3521 #if defined(PETSC_USE_DEBUG) 3522 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]); 3523 #endif 3524 } 3525 #if defined(PETSC_USE_DEBUG) 3526 for (ii=0; ii<baij->i[m]; ii++) { 3527 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 3528 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]); 3529 } 3530 #endif 3531 3532 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3533 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3534 PetscFunctionReturn(0); 3535 } 3536