1 /* 2 Defines the basic matrix operations for the BAIJ (compressed row) 3 matrix storage format. 4 */ 5 #include "src/mat/impls/baij/seq/baij.h" 6 #include "src/inline/spops.h" 7 #include "petscsys.h" /*I "petscmat.h" I*/ 8 9 #include "src/inline/ilu.h" 10 11 #undef __FUNCT__ 12 #define __FUNCT__ "MatInvertBlockDiagonal_SeqBAIJ" 13 PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A) 14 { 15 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*) A->data; 16 PetscErrorCode ierr; 17 PetscInt *diag_offset,i,bs = A->bs,mbs = a->mbs; 18 PetscScalar *v = a->a,*odiag,*diag,*mdiag; 19 20 PetscFunctionBegin; 21 if (a->idiagvalid) PetscFunctionReturn(0); 22 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 23 diag_offset = a->diag; 24 if (!a->idiag) { 25 ierr = PetscMalloc(2*bs*bs*mbs*sizeof(PetscScalar),&a->idiag);CHKERRQ(ierr); 26 } 27 diag = a->idiag; 28 mdiag = a->idiag+bs*bs*mbs; 29 /* factor and invert each block */ 30 switch (bs){ 31 case 2: 32 for (i=0; i<mbs; i++) { 33 odiag = v + 4*diag_offset[i]; 34 diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; 35 mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3]; 36 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 37 diag += 4; 38 mdiag += 4; 39 } 40 break; 41 case 3: 42 for (i=0; i<mbs; i++) { 43 odiag = v + 9*diag_offset[i]; 44 diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; 45 diag[4] = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7]; 46 diag[8] = odiag[8]; 47 mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3]; 48 mdiag[4] = odiag[4]; mdiag[5] = odiag[5]; mdiag[6] = odiag[6]; mdiag[7] = odiag[7]; 49 mdiag[8] = odiag[8]; 50 ierr = Kernel_A_gets_inverse_A_3(diag);CHKERRQ(ierr); 51 diag += 9; 52 mdiag += 9; 53 } 54 break; 55 case 4: 56 for (i=0; i<mbs; i++) { 57 odiag = v + 16*diag_offset[i]; 58 ierr = PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));CHKERRQ(ierr); 59 ierr = PetscMemcpy(mdiag,odiag,16*sizeof(PetscScalar));CHKERRQ(ierr); 60 ierr = Kernel_A_gets_inverse_A_4(diag);CHKERRQ(ierr); 61 diag += 16; 62 mdiag += 16; 63 } 64 break; 65 case 5: 66 for (i=0; i<mbs; i++) { 67 odiag = v + 25*diag_offset[i]; 68 ierr = PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));CHKERRQ(ierr); 69 ierr = PetscMemcpy(mdiag,odiag,25*sizeof(PetscScalar));CHKERRQ(ierr); 70 ierr = Kernel_A_gets_inverse_A_5(diag);CHKERRQ(ierr); 71 diag += 25; 72 mdiag += 25; 73 } 74 break; 75 default: 76 SETERRQ1(PETSC_ERR_SUP,"not supported for block size %D",bs); 77 } 78 a->idiagvalid = PETSC_TRUE; 79 PetscFunctionReturn(0); 80 } 81 82 #undef __FUNCT__ 83 #define __FUNCT__ "MatPBRelax_SeqBAIJ_2" 84 PetscErrorCode MatPBRelax_SeqBAIJ_2(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 85 { 86 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 87 PetscScalar *x,x1,x2,s1,s2; 88 const PetscScalar *v,*aa = a->a, *b, *idiag,*mdiag; 89 PetscErrorCode ierr; 90 PetscInt m = a->mbs,i,i2,nz,idx; 91 const PetscInt *diag,*ai = a->i,*aj = a->j,*vi; 92 93 PetscFunctionBegin; 94 its = its*lits; 95 if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 96 if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift"); 97 if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor"); 98 if ((flag & SOR_EISENSTAT) ||(flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER) ) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for Eisenstat trick"); 99 if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations"); 100 101 if (!a->idiagvalid){ierr = MatInvertBlockDiagonal_SeqBAIJ(A);CHKERRQ(ierr);} 102 103 diag = a->diag; 104 idiag = a->idiag; 105 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 106 ierr = VecGetArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 107 108 if (flag & SOR_ZERO_INITIAL_GUESS) { 109 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 110 x[0] = b[0]*idiag[0] + b[1]*idiag[2]; 111 x[1] = b[0]*idiag[1] + b[1]*idiag[3]; 112 i2 = 2; 113 idiag += 4; 114 for (i=1; i<m; i++) { 115 v = aa + 4*ai[i]; 116 vi = aj + ai[i]; 117 nz = diag[i] - ai[i]; 118 s1 = b[i2]; s2 = b[i2+1]; 119 while (nz--) { 120 idx = 2*(*vi++); 121 x1 = x[idx]; x2 = x[1+idx]; 122 s1 -= v[0]*x1 + v[2]*x2; 123 s2 -= v[1]*x1 + v[3]*x2; 124 v += 4; 125 } 126 x[i2] = idiag[0]*s1 + idiag[2]*s2; 127 x[i2+1] = idiag[1]*s1 + idiag[3]*s2; 128 idiag += 4; 129 i2 += 2; 130 } 131 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 132 PetscLogFlops(4*(a->nz)); 133 } 134 if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) && 135 (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) { 136 i2 = 0; 137 mdiag = a->idiag+4*a->mbs; 138 for (i=0; i<m; i++) { 139 x1 = x[i2]; x2 = x[i2+1]; 140 x[i2] = mdiag[0]*x1 + mdiag[2]*x2; 141 x[i2+1] = mdiag[1]*x1 + mdiag[3]*x2; 142 mdiag += 4; 143 i2 += 2; 144 } 145 PetscLogFlops(6*m); 146 } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 147 ierr = PetscMemcpy(x,b,A->m*sizeof(PetscScalar));CHKERRQ(ierr); 148 } 149 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 150 idiag = a->idiag+4*a->mbs - 4; 151 i2 = 2*m - 2; 152 x1 = x[i2]; x2 = x[i2+1]; 153 x[i2] = idiag[0]*x1 + idiag[2]*x2; 154 x[i2+1] = idiag[1]*x1 + idiag[3]*x2; 155 idiag -= 4; 156 i2 -= 2; 157 for (i=m-2; i>=0; i--) { 158 v = aa + 4*(diag[i]+1); 159 vi = aj + diag[i] + 1; 160 nz = ai[i+1] - diag[i] - 1; 161 s1 = x[i2]; s2 = x[i2+1]; 162 while (nz--) { 163 idx = 2*(*vi++); 164 x1 = x[idx]; x2 = x[1+idx]; 165 s1 -= v[0]*x1 + v[2]*x2; 166 s2 -= v[1]*x1 + v[3]*x2; 167 v += 4; 168 } 169 x[i2] = idiag[0]*s1 + idiag[2]*s2; 170 x[i2+1] = idiag[1]*s1 + idiag[3]*s2; 171 idiag -= 4; 172 i2 -= 2; 173 } 174 PetscLogFlops(4*(a->nz)); 175 } 176 } else { 177 SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess"); 178 } 179 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 180 ierr = VecRestoreArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 181 PetscFunctionReturn(0); 182 } 183 184 #undef __FUNCT__ 185 #define __FUNCT__ "MatPBRelax_SeqBAIJ_3" 186 PetscErrorCode MatPBRelax_SeqBAIJ_3(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 187 { 188 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 189 PetscScalar *x,x1,x2,x3,s1,s2,s3; 190 const PetscScalar *v,*aa = a->a, *b, *idiag,*mdiag; 191 PetscErrorCode ierr; 192 PetscInt m = a->mbs,i,i2,nz,idx; 193 const PetscInt *diag,*ai = a->i,*aj = a->j,*vi; 194 195 PetscFunctionBegin; 196 its = its*lits; 197 if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 198 if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift"); 199 if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor"); 200 if ((flag & SOR_EISENSTAT) ||(flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER) ) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for Eisenstat trick"); 201 if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations"); 202 203 if (!a->idiagvalid){ierr = MatInvertBlockDiagonal_SeqBAIJ(A);CHKERRQ(ierr);} 204 205 diag = a->diag; 206 idiag = a->idiag; 207 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 208 ierr = VecGetArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 209 210 if (flag & SOR_ZERO_INITIAL_GUESS) { 211 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 212 x[0] = b[0]*idiag[0] + b[1]*idiag[3] + b[2]*idiag[6]; 213 x[1] = b[0]*idiag[1] + b[1]*idiag[4] + b[2]*idiag[7]; 214 x[2] = b[0]*idiag[2] + b[1]*idiag[5] + b[2]*idiag[8]; 215 i2 = 3; 216 idiag += 9; 217 for (i=1; i<m; i++) { 218 v = aa + 9*ai[i]; 219 vi = aj + ai[i]; 220 nz = diag[i] - ai[i]; 221 s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; 222 while (nz--) { 223 idx = 3*(*vi++); 224 x1 = x[idx]; x2 = x[1+idx];x3 = x[2+idx]; 225 s1 -= v[0]*x1 + v[3]*x2 + v[6]*x3; 226 s2 -= v[1]*x1 + v[4]*x2 + v[7]*x3; 227 s3 -= v[2]*x1 + v[5]*x2 + v[8]*x3; 228 v += 9; 229 } 230 x[i2] = idiag[0]*s1 + idiag[3]*s2 + idiag[6]*s3; 231 x[i2+1] = idiag[1]*s1 + idiag[4]*s2 + idiag[7]*s3; 232 x[i2+2] = idiag[2]*s1 + idiag[5]*s2 + idiag[8]*s3; 233 idiag += 9; 234 i2 += 3; 235 } 236 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 237 PetscLogFlops(9*(a->nz)); 238 } 239 if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) && 240 (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) { 241 i2 = 0; 242 mdiag = a->idiag+9*a->mbs; 243 for (i=0; i<m; i++) { 244 x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; 245 x[i2] = mdiag[0]*x1 + mdiag[3]*x2 + mdiag[6]*x3; 246 x[i2+1] = mdiag[1]*x1 + mdiag[4]*x2 + mdiag[7]*x3; 247 x[i2+2] = mdiag[2]*x1 + mdiag[5]*x2 + mdiag[8]*x3; 248 mdiag += 9; 249 i2 += 3; 250 } 251 PetscLogFlops(15*m); 252 } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 253 ierr = PetscMemcpy(x,b,A->m*sizeof(PetscScalar));CHKERRQ(ierr); 254 } 255 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 256 idiag = a->idiag+9*a->mbs - 9; 257 i2 = 3*m - 3; 258 x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; 259 x[i2] = idiag[0]*x1 + idiag[3]*x2 + idiag[6]*x3; 260 x[i2+1] = idiag[1]*x1 + idiag[4]*x2 + idiag[7]*x3; 261 x[i2+2] = idiag[2]*x1 + idiag[5]*x2 + idiag[8]*x3; 262 idiag -= 9; 263 i2 -= 3; 264 for (i=m-2; i>=0; i--) { 265 v = aa + 9*(diag[i]+1); 266 vi = aj + diag[i] + 1; 267 nz = ai[i+1] - diag[i] - 1; 268 s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; 269 while (nz--) { 270 idx = 3*(*vi++); 271 x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; 272 s1 -= v[0]*x1 + v[3]*x2 + v[6]*x3; 273 s2 -= v[1]*x1 + v[4]*x2 + v[7]*x3; 274 s3 -= v[2]*x1 + v[5]*x2 + v[8]*x3; 275 v += 9; 276 } 277 x[i2] = idiag[0]*s1 + idiag[3]*s2 + idiag[6]*s3; 278 x[i2+1] = idiag[1]*s1 + idiag[4]*s2 + idiag[7]*s3; 279 x[i2+2] = idiag[2]*s1 + idiag[5]*s2 + idiag[8]*s3; 280 idiag -= 9; 281 i2 -= 3; 282 } 283 PetscLogFlops(9*(a->nz)); 284 } 285 } else { 286 SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess"); 287 } 288 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 289 ierr = VecRestoreArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 290 PetscFunctionReturn(0); 291 } 292 293 #undef __FUNCT__ 294 #define __FUNCT__ "MatPBRelax_SeqBAIJ_4" 295 PetscErrorCode MatPBRelax_SeqBAIJ_4(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 296 { 297 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 298 PetscScalar *x,x1,x2,x3,x4,s1,s2,s3,s4; 299 const PetscScalar *v,*aa = a->a, *b, *idiag,*mdiag; 300 PetscErrorCode ierr; 301 PetscInt m = a->mbs,i,i2,nz,idx; 302 const PetscInt *diag,*ai = a->i,*aj = a->j,*vi; 303 304 PetscFunctionBegin; 305 its = its*lits; 306 if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 307 if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift"); 308 if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor"); 309 if ((flag & SOR_EISENSTAT) ||(flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER) ) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for Eisenstat trick"); 310 if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations"); 311 312 if (!a->idiagvalid){ierr = MatInvertBlockDiagonal_SeqBAIJ(A);CHKERRQ(ierr);} 313 314 diag = a->diag; 315 idiag = a->idiag; 316 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 317 ierr = VecGetArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 318 319 if (flag & SOR_ZERO_INITIAL_GUESS) { 320 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 321 x[0] = b[0]*idiag[0] + b[1]*idiag[4] + b[2]*idiag[8] + b[3]*idiag[12]; 322 x[1] = b[0]*idiag[1] + b[1]*idiag[5] + b[2]*idiag[9] + b[3]*idiag[13]; 323 x[2] = b[0]*idiag[2] + b[1]*idiag[6] + b[2]*idiag[10] + b[3]*idiag[14]; 324 x[3] = b[0]*idiag[3] + b[1]*idiag[7] + b[2]*idiag[11] + b[3]*idiag[15]; 325 i2 = 4; 326 idiag += 16; 327 for (i=1; i<m; i++) { 328 v = aa + 16*ai[i]; 329 vi = aj + ai[i]; 330 nz = diag[i] - ai[i]; 331 s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; s4 = b[i2+3]; 332 while (nz--) { 333 idx = 4*(*vi++); 334 x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; 335 s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3 + v[12]*x4; 336 s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3 + v[13]*x4; 337 s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4; 338 s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4; 339 v += 16; 340 } 341 x[i2] = idiag[0]*s1 + idiag[4]*s2 + idiag[8]*s3 + idiag[12]*s4; 342 x[i2+1] = idiag[1]*s1 + idiag[5]*s2 + idiag[9]*s3 + idiag[13]*s4; 343 x[i2+2] = idiag[2]*s1 + idiag[6]*s2 + idiag[10]*s3 + idiag[14]*s4; 344 x[i2+3] = idiag[3]*s1 + idiag[7]*s2 + idiag[11]*s3 + idiag[15]*s4; 345 idiag += 16; 346 i2 += 4; 347 } 348 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 349 PetscLogFlops(16*(a->nz)); 350 } 351 if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) && 352 (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) { 353 i2 = 0; 354 mdiag = a->idiag+16*a->mbs; 355 for (i=0; i<m; i++) { 356 x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; 357 x[i2] = mdiag[0]*x1 + mdiag[4]*x2 + mdiag[8]*x3 + mdiag[12]*x4; 358 x[i2+1] = mdiag[1]*x1 + mdiag[5]*x2 + mdiag[9]*x3 + mdiag[13]*x4; 359 x[i2+2] = mdiag[2]*x1 + mdiag[6]*x2 + mdiag[10]*x3 + mdiag[14]*x4; 360 x[i2+3] = mdiag[3]*x1 + mdiag[7]*x2 + mdiag[11]*x3 + mdiag[15]*x4; 361 mdiag += 16; 362 i2 += 4; 363 } 364 PetscLogFlops(28*m); 365 } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 366 ierr = PetscMemcpy(x,b,A->m*sizeof(PetscScalar));CHKERRQ(ierr); 367 } 368 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 369 idiag = a->idiag+16*a->mbs - 16; 370 i2 = 4*m - 4; 371 x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; 372 x[i2] = idiag[0]*x1 + idiag[4]*x2 + idiag[8]*x3 + idiag[12]*x4; 373 x[i2+1] = idiag[1]*x1 + idiag[5]*x2 + idiag[9]*x3 + idiag[13]*x4; 374 x[i2+2] = idiag[2]*x1 + idiag[6]*x2 + idiag[10]*x3 + idiag[14]*x4; 375 x[i2+3] = idiag[3]*x1 + idiag[7]*x2 + idiag[11]*x3 + idiag[15]*x4; 376 idiag -= 16; 377 i2 -= 4; 378 for (i=m-2; i>=0; i--) { 379 v = aa + 16*(diag[i]+1); 380 vi = aj + diag[i] + 1; 381 nz = ai[i+1] - diag[i] - 1; 382 s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; s4 = x[i2+3]; 383 while (nz--) { 384 idx = 4*(*vi++); 385 x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; 386 s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3 + v[12]*x4; 387 s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3 + v[13]*x4; 388 s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4; 389 s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4; 390 v += 16; 391 } 392 x[i2] = idiag[0]*s1 + idiag[4]*s2 + idiag[8]*s3 + idiag[12]*s4; 393 x[i2+1] = idiag[1]*s1 + idiag[5]*s2 + idiag[9]*s3 + idiag[13]*s4; 394 x[i2+2] = idiag[2]*s1 + idiag[6]*s2 + idiag[10]*s3 + idiag[14]*s4; 395 x[i2+3] = idiag[3]*s1 + idiag[7]*s2 + idiag[11]*s3 + idiag[15]*s4; 396 idiag -= 16; 397 i2 -= 4; 398 } 399 PetscLogFlops(16*(a->nz)); 400 } 401 } else { 402 SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess"); 403 } 404 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 405 ierr = VecRestoreArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 406 PetscFunctionReturn(0); 407 } 408 409 #undef __FUNCT__ 410 #define __FUNCT__ "MatPBRelax_SeqBAIJ_5" 411 PetscErrorCode MatPBRelax_SeqBAIJ_5(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 412 { 413 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 414 PetscScalar *x,x1,x2,x3,x4,x5,s1,s2,s3,s4,s5; 415 const PetscScalar *v,*aa = a->a, *b, *idiag,*mdiag; 416 PetscErrorCode ierr; 417 PetscInt m = a->mbs,i,i2,nz,idx; 418 const PetscInt *diag,*ai = a->i,*aj = a->j,*vi; 419 420 PetscFunctionBegin; 421 its = its*lits; 422 if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 423 if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift"); 424 if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor"); 425 if ((flag & SOR_EISENSTAT) ||(flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER) ) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for Eisenstat trick"); 426 if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations"); 427 428 if (!a->idiagvalid){ierr = MatInvertBlockDiagonal_SeqBAIJ(A);CHKERRQ(ierr);} 429 430 diag = a->diag; 431 idiag = a->idiag; 432 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 433 ierr = VecGetArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 434 435 if (flag & SOR_ZERO_INITIAL_GUESS) { 436 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 437 x[0] = b[0]*idiag[0] + b[1]*idiag[5] + b[2]*idiag[10] + b[3]*idiag[15] + b[4]*idiag[20]; 438 x[1] = b[0]*idiag[1] + b[1]*idiag[6] + b[2]*idiag[11] + b[3]*idiag[16] + b[4]*idiag[21]; 439 x[2] = b[0]*idiag[2] + b[1]*idiag[7] + b[2]*idiag[12] + b[3]*idiag[17] + b[4]*idiag[22]; 440 x[3] = b[0]*idiag[3] + b[1]*idiag[8] + b[2]*idiag[13] + b[3]*idiag[18] + b[4]*idiag[23]; 441 x[4] = b[0]*idiag[4] + b[1]*idiag[9] + b[2]*idiag[14] + b[3]*idiag[19] + b[4]*idiag[24]; 442 i2 = 5; 443 idiag += 25; 444 for (i=1; i<m; i++) { 445 v = aa + 25*ai[i]; 446 vi = aj + ai[i]; 447 nz = diag[i] - ai[i]; 448 s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; s4 = b[i2+3]; s5 = b[i2+4]; 449 while (nz--) { 450 idx = 5*(*vi++); 451 x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx]; 452 s1 -= v[0]*x1 + v[5]*x2 + v[10]*x3 + v[15]*x4 + v[20]*x5; 453 s2 -= v[1]*x1 + v[6]*x2 + v[11]*x3 + v[16]*x4 + v[21]*x5; 454 s3 -= v[2]*x1 + v[7]*x2 + v[12]*x3 + v[17]*x4 + v[22]*x5; 455 s4 -= v[3]*x1 + v[8]*x2 + v[13]*x3 + v[18]*x4 + v[23]*x5; 456 s5 -= v[4]*x1 + v[9]*x2 + v[14]*x3 + v[19]*x4 + v[24]*x5; 457 v += 25; 458 } 459 x[i2] = idiag[0]*s1 + idiag[5]*s2 + idiag[10]*s3 + idiag[15]*s4 + idiag[20]*s5; 460 x[i2+1] = idiag[1]*s1 + idiag[6]*s2 + idiag[11]*s3 + idiag[16]*s4 + idiag[21]*s5; 461 x[i2+2] = idiag[2]*s1 + idiag[7]*s2 + idiag[12]*s3 + idiag[17]*s4 + idiag[22]*s5; 462 x[i2+3] = idiag[3]*s1 + idiag[8]*s2 + idiag[13]*s3 + idiag[18]*s4 + idiag[23]*s5; 463 x[i2+4] = idiag[4]*s1 + idiag[9]*s2 + idiag[14]*s3 + idiag[19]*s4 + idiag[24]*s5; 464 idiag += 25; 465 i2 += 5; 466 } 467 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 468 PetscLogFlops(25*(a->nz)); 469 } 470 if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) && 471 (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) { 472 i2 = 0; 473 mdiag = a->idiag+25*a->mbs; 474 for (i=0; i<m; i++) { 475 x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4]; 476 x[i2] = mdiag[0]*x1 + mdiag[5]*x2 + mdiag[10]*x3 + mdiag[15]*x4 + mdiag[20]*x5; 477 x[i2+1] = mdiag[1]*x1 + mdiag[6]*x2 + mdiag[11]*x3 + mdiag[16]*x4 + mdiag[21]*x5; 478 x[i2+2] = mdiag[2]*x1 + mdiag[7]*x2 + mdiag[12]*x3 + mdiag[17]*x4 + mdiag[22]*x5; 479 x[i2+3] = mdiag[3]*x1 + mdiag[8]*x2 + mdiag[13]*x3 + mdiag[18]*x4 + mdiag[23]*x5; 480 x[i2+4] = mdiag[4]*x1 + mdiag[9]*x2 + mdiag[14]*x3 + mdiag[19]*x4 + mdiag[24]*x5; 481 mdiag += 25; 482 i2 += 5; 483 } 484 PetscLogFlops(45*m); 485 } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 486 ierr = PetscMemcpy(x,b,A->m*sizeof(PetscScalar));CHKERRQ(ierr); 487 } 488 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 489 idiag = a->idiag+25*a->mbs - 25; 490 i2 = 5*m - 5; 491 x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4]; 492 x[i2] = idiag[0]*x1 + idiag[5]*x2 + idiag[10]*x3 + idiag[15]*x4 + idiag[20]*x5; 493 x[i2+1] = idiag[1]*x1 + idiag[6]*x2 + idiag[11]*x3 + idiag[16]*x4 + idiag[21]*x5; 494 x[i2+2] = idiag[2]*x1 + idiag[7]*x2 + idiag[12]*x3 + idiag[17]*x4 + idiag[22]*x5; 495 x[i2+3] = idiag[3]*x1 + idiag[8]*x2 + idiag[13]*x3 + idiag[18]*x4 + idiag[23]*x5; 496 x[i2+4] = idiag[4]*x1 + idiag[9]*x2 + idiag[14]*x3 + idiag[19]*x4 + idiag[24]*x5; 497 idiag -= 25; 498 i2 -= 5; 499 for (i=m-2; i>=0; i--) { 500 v = aa + 25*(diag[i]+1); 501 vi = aj + diag[i] + 1; 502 nz = ai[i+1] - diag[i] - 1; 503 s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; s4 = x[i2+3]; s5 = x[i2+4]; 504 while (nz--) { 505 idx = 5*(*vi++); 506 x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx]; 507 s1 -= v[0]*x1 + v[5]*x2 + v[10]*x3 + v[15]*x4 + v[20]*x5; 508 s2 -= v[1]*x1 + v[6]*x2 + v[11]*x3 + v[16]*x4 + v[21]*x5; 509 s3 -= v[2]*x1 + v[7]*x2 + v[12]*x3 + v[17]*x4 + v[22]*x5; 510 s4 -= v[3]*x1 + v[8]*x2 + v[13]*x3 + v[18]*x4 + v[23]*x5; 511 s5 -= v[4]*x1 + v[9]*x2 + v[14]*x3 + v[19]*x4 + v[24]*x5; 512 v += 25; 513 } 514 x[i2] = idiag[0]*s1 + idiag[5]*s2 + idiag[10]*s3 + idiag[15]*s4 + idiag[20]*s5; 515 x[i2+1] = idiag[1]*s1 + idiag[6]*s2 + idiag[11]*s3 + idiag[16]*s4 + idiag[21]*s5; 516 x[i2+2] = idiag[2]*s1 + idiag[7]*s2 + idiag[12]*s3 + idiag[17]*s4 + idiag[22]*s5; 517 x[i2+3] = idiag[3]*s1 + idiag[8]*s2 + idiag[13]*s3 + idiag[18]*s4 + idiag[23]*s5; 518 x[i2+4] = idiag[4]*s1 + idiag[9]*s2 + idiag[14]*s3 + idiag[19]*s4 + idiag[24]*s5; 519 idiag -= 25; 520 i2 -= 5; 521 } 522 PetscLogFlops(25*(a->nz)); 523 } 524 } else { 525 SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess"); 526 } 527 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 528 ierr = VecRestoreArray(bb,(PetscScalar**)&b);CHKERRQ(ierr); 529 PetscFunctionReturn(0); 530 } 531 532 /* 533 Special version for Fun3d sequential benchmark 534 */ 535 #if defined(PETSC_HAVE_FORTRAN_CAPS) 536 #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4 537 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 538 #define matsetvaluesblocked4_ matsetvaluesblocked4 539 #endif 540 541 EXTERN_C_BEGIN 542 #undef __FUNCT__ 543 #define __FUNCT__ "matsetvaluesblocked4_" 544 void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[]) 545 { 546 Mat A = *AA; 547 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 548 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn; 549 PetscInt *ai=a->i,*ailen=a->ilen; 550 PetscInt *aj=a->j,stepval; 551 const PetscScalar *value = v; 552 MatScalar *ap,*aa = a->a,*bap; 553 554 PetscFunctionBegin; 555 stepval = (n-1)*4; 556 for (k=0; k<m; k++) { /* loop over added rows */ 557 row = im[k]; 558 rp = aj + ai[row]; 559 ap = aa + 16*ai[row]; 560 nrow = ailen[row]; 561 low = 0; 562 for (l=0; l<n; l++) { /* loop over added columns */ 563 col = in[l]; 564 value = v + k*(stepval+4)*4 + l*4; 565 low = 0; high = nrow; 566 while (high-low > 7) { 567 t = (low+high)/2; 568 if (rp[t] > col) high = t; 569 else low = t; 570 } 571 for (i=low; i<high; i++) { 572 if (rp[i] > col) break; 573 if (rp[i] == col) { 574 bap = ap + 16*i; 575 for (ii=0; ii<4; ii++,value+=stepval) { 576 for (jj=ii; jj<16; jj+=4) { 577 bap[jj] += *value++; 578 } 579 } 580 goto noinsert2; 581 } 582 } 583 N = nrow++ - 1; 584 /* shift up all the later entries in this row */ 585 for (ii=N; ii>=i; ii--) { 586 rp[ii+1] = rp[ii]; 587 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 588 } 589 if (N >= i) { 590 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 591 } 592 rp[i] = col; 593 bap = ap + 16*i; 594 for (ii=0; ii<4; ii++,value+=stepval) { 595 for (jj=ii; jj<16; jj+=4) { 596 bap[jj] = *value++; 597 } 598 } 599 noinsert2:; 600 low = i; 601 } 602 ailen[row] = nrow; 603 } 604 } 605 EXTERN_C_END 606 607 #if defined(PETSC_HAVE_FORTRAN_CAPS) 608 #define matsetvalues4_ MATSETVALUES4 609 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 610 #define matsetvalues4_ matsetvalues4 611 #endif 612 613 EXTERN_C_BEGIN 614 #undef __FUNCT__ 615 #define __FUNCT__ "MatSetValues4_" 616 void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v) 617 { 618 Mat A = *AA; 619 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 620 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm; 621 PetscInt *ai=a->i,*ailen=a->ilen; 622 PetscInt *aj=a->j,brow,bcol; 623 PetscInt ridx,cidx; 624 MatScalar *ap,value,*aa=a->a,*bap; 625 626 PetscFunctionBegin; 627 for (k=0; k<m; k++) { /* loop over added rows */ 628 row = im[k]; brow = row/4; 629 rp = aj + ai[brow]; 630 ap = aa + 16*ai[brow]; 631 nrow = ailen[brow]; 632 low = 0; 633 for (l=0; l<n; l++) { /* loop over added columns */ 634 col = in[l]; bcol = col/4; 635 ridx = row % 4; cidx = col % 4; 636 value = v[l + k*n]; 637 low = 0; high = nrow; 638 while (high-low > 7) { 639 t = (low+high)/2; 640 if (rp[t] > bcol) high = t; 641 else low = t; 642 } 643 for (i=low; i<high; i++) { 644 if (rp[i] > bcol) break; 645 if (rp[i] == bcol) { 646 bap = ap + 16*i + 4*cidx + ridx; 647 *bap += value; 648 goto noinsert1; 649 } 650 } 651 N = nrow++ - 1; 652 /* shift up all the later entries in this row */ 653 for (ii=N; ii>=i; ii--) { 654 rp[ii+1] = rp[ii]; 655 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 656 } 657 if (N>=i) { 658 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 659 } 660 rp[i] = bcol; 661 ap[16*i + 4*cidx + ridx] = value; 662 noinsert1:; 663 low = i; 664 } 665 ailen[brow] = nrow; 666 } 667 } 668 EXTERN_C_END 669 670 /* UGLY, ugly, ugly 671 When MatScalar == PetscScalar the function MatSetValuesBlocked_SeqBAIJ_MatScalar() does 672 not exist. Otherwise ..._MatScalar() takes matrix dlements in single precision and 673 inserts them into the single precision data structure. The function MatSetValuesBlocked_SeqBAIJ() 674 converts the entries into single precision and then calls ..._MatScalar() to put them 675 into the single precision data structures. 676 */ 677 #if defined(PETSC_USE_MAT_SINGLE) 678 EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode); 679 #else 680 #define MatSetValuesBlocked_SeqBAIJ_MatScalar MatSetValuesBlocked_SeqBAIJ 681 #endif 682 683 #define CHUNKSIZE 10 684 685 /* 686 Checks for missing diagonals 687 */ 688 #undef __FUNCT__ 689 #define __FUNCT__ "MatMissingDiagonal_SeqBAIJ" 690 PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A) 691 { 692 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 693 PetscErrorCode ierr; 694 PetscInt *diag,*jj = a->j,i; 695 696 PetscFunctionBegin; 697 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 698 diag = a->diag; 699 for (i=0; i<a->mbs; i++) { 700 if (jj[diag[i]] != i) { 701 SETERRQ1(PETSC_ERR_PLIB,"Matrix is missing diagonal number %D",i); 702 } 703 } 704 PetscFunctionReturn(0); 705 } 706 707 #undef __FUNCT__ 708 #define __FUNCT__ "MatMarkDiagonal_SeqBAIJ" 709 PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A) 710 { 711 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 712 PetscErrorCode ierr; 713 PetscInt i,j,*diag,m = a->mbs; 714 715 PetscFunctionBegin; 716 if (a->diag) PetscFunctionReturn(0); 717 718 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&diag);CHKERRQ(ierr); 719 PetscLogObjectMemory(A,(m+1)*sizeof(PetscInt)); 720 for (i=0; i<m; i++) { 721 diag[i] = a->i[i+1]; 722 for (j=a->i[i]; j<a->i[i+1]; j++) { 723 if (a->j[j] == i) { 724 diag[i] = j; 725 break; 726 } 727 } 728 } 729 a->diag = diag; 730 PetscFunctionReturn(0); 731 } 732 733 734 EXTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt,PetscInt*,PetscInt*,PetscInt,PetscInt,PetscInt**,PetscInt**); 735 736 #undef __FUNCT__ 737 #define __FUNCT__ "MatGetRowIJ_SeqBAIJ" 738 static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done) 739 { 740 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 741 PetscErrorCode ierr; 742 PetscInt n = a->mbs,i; 743 744 PetscFunctionBegin; 745 *nn = n; 746 if (!ia) PetscFunctionReturn(0); 747 if (symmetric) { 748 ierr = MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,0,oshift,ia,ja);CHKERRQ(ierr); 749 } else if (oshift == 1) { 750 /* temporarily add 1 to i and j indices */ 751 PetscInt nz = a->i[n]; 752 for (i=0; i<nz; i++) a->j[i]++; 753 for (i=0; i<n+1; i++) a->i[i]++; 754 *ia = a->i; *ja = a->j; 755 } else { 756 *ia = a->i; *ja = a->j; 757 } 758 759 PetscFunctionReturn(0); 760 } 761 762 #undef __FUNCT__ 763 #define __FUNCT__ "MatRestoreRowIJ_SeqBAIJ" 764 static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done) 765 { 766 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 767 PetscErrorCode ierr; 768 PetscInt i,n = a->mbs; 769 770 PetscFunctionBegin; 771 if (!ia) PetscFunctionReturn(0); 772 if (symmetric) { 773 ierr = PetscFree(*ia);CHKERRQ(ierr); 774 ierr = PetscFree(*ja);CHKERRQ(ierr); 775 } else if (oshift == 1) { 776 PetscInt nz = a->i[n]-1; 777 for (i=0; i<nz; i++) a->j[i]--; 778 for (i=0; i<n+1; i++) a->i[i]--; 779 } 780 PetscFunctionReturn(0); 781 } 782 783 #undef __FUNCT__ 784 #define __FUNCT__ "MatDestroy_SeqBAIJ" 785 PetscErrorCode MatDestroy_SeqBAIJ(Mat A) 786 { 787 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 788 PetscErrorCode ierr; 789 790 PetscFunctionBegin; 791 #if defined(PETSC_USE_LOG) 792 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->m,A->n,a->nz); 793 #endif 794 ierr = PetscFree(a->a);CHKERRQ(ierr); 795 if (!a->singlemalloc) { 796 ierr = PetscFree(a->i);CHKERRQ(ierr); 797 ierr = PetscFree(a->j);CHKERRQ(ierr); 798 } 799 if (a->row) { 800 ierr = ISDestroy(a->row);CHKERRQ(ierr); 801 } 802 if (a->col) { 803 ierr = ISDestroy(a->col);CHKERRQ(ierr); 804 } 805 if (a->diag) {ierr = PetscFree(a->diag);CHKERRQ(ierr);} 806 if (a->idiag) {ierr = PetscFree(a->idiag);CHKERRQ(ierr);} 807 if (a->ilen) {ierr = PetscFree(a->ilen);CHKERRQ(ierr);} 808 if (a->imax) {ierr = PetscFree(a->imax);CHKERRQ(ierr);} 809 if (a->solve_work) {ierr = PetscFree(a->solve_work);CHKERRQ(ierr);} 810 if (a->mult_work) {ierr = PetscFree(a->mult_work);CHKERRQ(ierr);} 811 if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} 812 if (a->saved_values) {ierr = PetscFree(a->saved_values);CHKERRQ(ierr);} 813 #if defined(PETSC_USE_MAT_SINGLE) 814 if (a->setvaluescopy) {ierr = PetscFree(a->setvaluescopy);CHKERRQ(ierr);} 815 #endif 816 if (a->xtoy) {ierr = PetscFree(a->xtoy);CHKERRQ(ierr);} 817 if (a->compressedrow.use){ierr = PetscFree(a->compressedrow.i);} 818 819 ierr = PetscFree(a);CHKERRQ(ierr); 820 821 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 822 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 823 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C","",PETSC_NULL);CHKERRQ(ierr); 824 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C","",PETSC_NULL);CHKERRQ(ierr); 825 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C","",PETSC_NULL);CHKERRQ(ierr); 826 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 827 PetscFunctionReturn(0); 828 } 829 830 #undef __FUNCT__ 831 #define __FUNCT__ "MatSetOption_SeqBAIJ" 832 PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op) 833 { 834 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 835 836 PetscFunctionBegin; 837 switch (op) { 838 case MAT_ROW_ORIENTED: 839 a->roworiented = PETSC_TRUE; 840 break; 841 case MAT_COLUMN_ORIENTED: 842 a->roworiented = PETSC_FALSE; 843 break; 844 case MAT_COLUMNS_SORTED: 845 a->sorted = PETSC_TRUE; 846 break; 847 case MAT_COLUMNS_UNSORTED: 848 a->sorted = PETSC_FALSE; 849 break; 850 case MAT_KEEP_ZEROED_ROWS: 851 a->keepzeroedrows = PETSC_TRUE; 852 break; 853 case MAT_NO_NEW_NONZERO_LOCATIONS: 854 a->nonew = 1; 855 break; 856 case MAT_NEW_NONZERO_LOCATION_ERR: 857 a->nonew = -1; 858 break; 859 case MAT_NEW_NONZERO_ALLOCATION_ERR: 860 a->nonew = -2; 861 break; 862 case MAT_YES_NEW_NONZERO_LOCATIONS: 863 a->nonew = 0; 864 break; 865 case MAT_ROWS_SORTED: 866 case MAT_ROWS_UNSORTED: 867 case MAT_YES_NEW_DIAGONALS: 868 case MAT_IGNORE_OFF_PROC_ENTRIES: 869 case MAT_USE_HASH_TABLE: 870 PetscLogInfo(A,"MatSetOption_SeqBAIJ:Option ignored\n"); 871 break; 872 case MAT_NO_NEW_DIAGONALS: 873 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 874 case MAT_SYMMETRIC: 875 case MAT_STRUCTURALLY_SYMMETRIC: 876 case MAT_NOT_SYMMETRIC: 877 case MAT_NOT_STRUCTURALLY_SYMMETRIC: 878 case MAT_HERMITIAN: 879 case MAT_NOT_HERMITIAN: 880 case MAT_SYMMETRY_ETERNAL: 881 case MAT_NOT_SYMMETRY_ETERNAL: 882 break; 883 default: 884 SETERRQ(PETSC_ERR_SUP,"unknown option"); 885 } 886 PetscFunctionReturn(0); 887 } 888 889 #undef __FUNCT__ 890 #define __FUNCT__ "MatGetRow_SeqBAIJ" 891 PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 892 { 893 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 894 PetscErrorCode ierr; 895 PetscInt itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*idx_i,bs2; 896 MatScalar *aa,*aa_i; 897 PetscScalar *v_i; 898 899 PetscFunctionBegin; 900 bs = A->bs; 901 ai = a->i; 902 aj = a->j; 903 aa = a->a; 904 bs2 = a->bs2; 905 906 if (row < 0 || row >= A->m) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row); 907 908 bn = row/bs; /* Block number */ 909 bp = row % bs; /* Block Position */ 910 M = ai[bn+1] - ai[bn]; 911 *nz = bs*M; 912 913 if (v) { 914 *v = 0; 915 if (*nz) { 916 ierr = PetscMalloc((*nz)*sizeof(PetscScalar),v);CHKERRQ(ierr); 917 for (i=0; i<M; i++) { /* for each block in the block row */ 918 v_i = *v + i*bs; 919 aa_i = aa + bs2*(ai[bn] + i); 920 for (j=bp,k=0; j<bs2; j+=bs,k++) {v_i[k] = aa_i[j];} 921 } 922 } 923 } 924 925 if (idx) { 926 *idx = 0; 927 if (*nz) { 928 ierr = PetscMalloc((*nz)*sizeof(PetscInt),idx);CHKERRQ(ierr); 929 for (i=0; i<M; i++) { /* for each block in the block row */ 930 idx_i = *idx + i*bs; 931 itmp = bs*aj[ai[bn] + i]; 932 for (j=0; j<bs; j++) {idx_i[j] = itmp++;} 933 } 934 } 935 } 936 PetscFunctionReturn(0); 937 } 938 939 #undef __FUNCT__ 940 #define __FUNCT__ "MatRestoreRow_SeqBAIJ" 941 PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 942 { 943 PetscErrorCode ierr; 944 945 PetscFunctionBegin; 946 if (idx) {if (*idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);}} 947 if (v) {if (*v) {ierr = PetscFree(*v);CHKERRQ(ierr);}} 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNCT__ 952 #define __FUNCT__ "MatTranspose_SeqBAIJ" 953 PetscErrorCode MatTranspose_SeqBAIJ(Mat A,Mat *B) 954 { 955 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data; 956 Mat C; 957 PetscErrorCode ierr; 958 PetscInt i,j,k,*aj=a->j,*ai=a->i,bs=A->bs,mbs=a->mbs,nbs=a->nbs,len,*col; 959 PetscInt *rows,*cols,bs2=a->bs2; 960 PetscScalar *array; 961 962 PetscFunctionBegin; 963 if (!B && mbs!=nbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Square matrix only for in-place"); 964 ierr = PetscMalloc((1+nbs)*sizeof(PetscInt),&col);CHKERRQ(ierr); 965 ierr = PetscMemzero(col,(1+nbs)*sizeof(PetscInt));CHKERRQ(ierr); 966 967 #if defined(PETSC_USE_MAT_SINGLE) 968 ierr = PetscMalloc(a->bs2*a->nz*sizeof(PetscScalar),&array);CHKERRQ(ierr); 969 for (i=0; i<a->bs2*a->nz; i++) array[i] = (PetscScalar)a->a[i]; 970 #else 971 array = a->a; 972 #endif 973 974 for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1; 975 ierr = MatCreate(A->comm,A->n,A->m,A->n,A->m,&C);CHKERRQ(ierr); 976 ierr = MatSetType(C,A->type_name);CHKERRQ(ierr); 977 ierr = MatSeqBAIJSetPreallocation(C,bs,PETSC_NULL,col);CHKERRQ(ierr); 978 ierr = PetscFree(col);CHKERRQ(ierr); 979 ierr = PetscMalloc(2*bs*sizeof(PetscInt),&rows);CHKERRQ(ierr); 980 cols = rows + bs; 981 for (i=0; i<mbs; i++) { 982 cols[0] = i*bs; 983 for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1; 984 len = ai[i+1] - ai[i]; 985 for (j=0; j<len; j++) { 986 rows[0] = (*aj++)*bs; 987 for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1; 988 ierr = MatSetValues(C,bs,rows,bs,cols,array,INSERT_VALUES);CHKERRQ(ierr); 989 array += bs2; 990 } 991 } 992 ierr = PetscFree(rows);CHKERRQ(ierr); 993 #if defined(PETSC_USE_MAT_SINGLE) 994 ierr = PetscFree(array); 995 #endif 996 997 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 998 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 999 1000 if (B) { 1001 *B = C; 1002 } else { 1003 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1004 } 1005 PetscFunctionReturn(0); 1006 } 1007 1008 #undef __FUNCT__ 1009 #define __FUNCT__ "MatView_SeqBAIJ_Binary" 1010 static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer) 1011 { 1012 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1013 PetscErrorCode ierr; 1014 PetscInt i,*col_lens,bs = A->bs,count,*jj,j,k,l,bs2=a->bs2; 1015 int fd; 1016 PetscScalar *aa; 1017 FILE *file; 1018 1019 PetscFunctionBegin; 1020 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1021 ierr = PetscMalloc((4+A->m)*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 1022 col_lens[0] = MAT_FILE_COOKIE; 1023 1024 col_lens[1] = A->m; 1025 col_lens[2] = A->n; 1026 col_lens[3] = a->nz*bs2; 1027 1028 /* store lengths of each row and write (including header) to file */ 1029 count = 0; 1030 for (i=0; i<a->mbs; i++) { 1031 for (j=0; j<bs; j++) { 1032 col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]); 1033 } 1034 } 1035 ierr = PetscBinaryWrite(fd,col_lens,4+A->m,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1036 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1037 1038 /* store column indices (zero start index) */ 1039 ierr = PetscMalloc((a->nz+1)*bs2*sizeof(PetscInt),&jj);CHKERRQ(ierr); 1040 count = 0; 1041 for (i=0; i<a->mbs; i++) { 1042 for (j=0; j<bs; j++) { 1043 for (k=a->i[i]; k<a->i[i+1]; k++) { 1044 for (l=0; l<bs; l++) { 1045 jj[count++] = bs*a->j[k] + l; 1046 } 1047 } 1048 } 1049 } 1050 ierr = PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1051 ierr = PetscFree(jj);CHKERRQ(ierr); 1052 1053 /* store nonzero values */ 1054 ierr = PetscMalloc((a->nz+1)*bs2*sizeof(PetscScalar),&aa);CHKERRQ(ierr); 1055 count = 0; 1056 for (i=0; i<a->mbs; i++) { 1057 for (j=0; j<bs; j++) { 1058 for (k=a->i[i]; k<a->i[i+1]; k++) { 1059 for (l=0; l<bs; l++) { 1060 aa[count++] = a->a[bs2*k + l*bs + j]; 1061 } 1062 } 1063 } 1064 } 1065 ierr = PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1066 ierr = PetscFree(aa);CHKERRQ(ierr); 1067 1068 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1069 if (file) { 1070 fprintf(file,"-matload_block_size %d\n",(int)A->bs); 1071 } 1072 PetscFunctionReturn(0); 1073 } 1074 1075 #undef __FUNCT__ 1076 #define __FUNCT__ "MatView_SeqBAIJ_ASCII" 1077 static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer) 1078 { 1079 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1080 PetscErrorCode ierr; 1081 PetscInt i,j,bs = A->bs,k,l,bs2=a->bs2; 1082 PetscViewerFormat format; 1083 1084 PetscFunctionBegin; 1085 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1086 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1087 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1088 } else if (format == PETSC_VIEWER_ASCII_MATLAB) { 1089 Mat aij; 1090 ierr = MatConvert(A,MATSEQAIJ,&aij);CHKERRQ(ierr); 1091 ierr = MatView(aij,viewer);CHKERRQ(ierr); 1092 ierr = MatDestroy(aij);CHKERRQ(ierr); 1093 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1094 PetscFunctionReturn(0); 1095 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1096 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 1097 for (i=0; i<a->mbs; i++) { 1098 for (j=0; j<bs; j++) { 1099 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1100 for (k=a->i[i]; k<a->i[i+1]; k++) { 1101 for (l=0; l<bs; l++) { 1102 #if defined(PETSC_USE_COMPLEX) 1103 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1104 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l, 1105 PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1106 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1107 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l, 1108 PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1109 } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1110 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1111 } 1112 #else 1113 if (a->a[bs2*k + l*bs + j] != 0.0) { 1114 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1115 } 1116 #endif 1117 } 1118 } 1119 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1120 } 1121 } 1122 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 1123 } else { 1124 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 1125 for (i=0; i<a->mbs; i++) { 1126 for (j=0; j<bs; j++) { 1127 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1128 for (k=a->i[i]; k<a->i[i+1]; k++) { 1129 for (l=0; l<bs; l++) { 1130 #if defined(PETSC_USE_COMPLEX) 1131 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) { 1132 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l, 1133 PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1134 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) { 1135 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l, 1136 PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1137 } else { 1138 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1139 } 1140 #else 1141 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1142 #endif 1143 } 1144 } 1145 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1146 } 1147 } 1148 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 1149 } 1150 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1151 PetscFunctionReturn(0); 1152 } 1153 1154 #undef __FUNCT__ 1155 #define __FUNCT__ "MatView_SeqBAIJ_Draw_Zoom" 1156 static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 1157 { 1158 Mat A = (Mat) Aa; 1159 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1160 PetscErrorCode ierr; 1161 PetscInt row,i,j,k,l,mbs=a->mbs,color,bs=A->bs,bs2=a->bs2; 1162 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1163 MatScalar *aa; 1164 PetscViewer viewer; 1165 1166 PetscFunctionBegin; 1167 1168 /* still need to add support for contour plot of nonzeros; see MatView_SeqAIJ_Draw_Zoom()*/ 1169 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1170 1171 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1172 1173 /* loop over matrix elements drawing boxes */ 1174 color = PETSC_DRAW_BLUE; 1175 for (i=0,row=0; i<mbs; i++,row+=bs) { 1176 for (j=a->i[i]; j<a->i[i+1]; j++) { 1177 y_l = A->m - row - 1.0; y_r = y_l + 1.0; 1178 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1179 aa = a->a + j*bs2; 1180 for (k=0; k<bs; k++) { 1181 for (l=0; l<bs; l++) { 1182 if (PetscRealPart(*aa++) >= 0.) continue; 1183 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1184 } 1185 } 1186 } 1187 } 1188 color = PETSC_DRAW_CYAN; 1189 for (i=0,row=0; i<mbs; i++,row+=bs) { 1190 for (j=a->i[i]; j<a->i[i+1]; j++) { 1191 y_l = A->m - row - 1.0; y_r = y_l + 1.0; 1192 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1193 aa = a->a + j*bs2; 1194 for (k=0; k<bs; k++) { 1195 for (l=0; l<bs; l++) { 1196 if (PetscRealPart(*aa++) != 0.) continue; 1197 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1198 } 1199 } 1200 } 1201 } 1202 1203 color = PETSC_DRAW_RED; 1204 for (i=0,row=0; i<mbs; i++,row+=bs) { 1205 for (j=a->i[i]; j<a->i[i+1]; j++) { 1206 y_l = A->m - row - 1.0; y_r = y_l + 1.0; 1207 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1208 aa = a->a + j*bs2; 1209 for (k=0; k<bs; k++) { 1210 for (l=0; l<bs; l++) { 1211 if (PetscRealPart(*aa++) <= 0.) continue; 1212 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1213 } 1214 } 1215 } 1216 } 1217 PetscFunctionReturn(0); 1218 } 1219 1220 #undef __FUNCT__ 1221 #define __FUNCT__ "MatView_SeqBAIJ_Draw" 1222 static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer) 1223 { 1224 PetscErrorCode ierr; 1225 PetscReal xl,yl,xr,yr,w,h; 1226 PetscDraw draw; 1227 PetscTruth isnull; 1228 1229 PetscFunctionBegin; 1230 1231 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1232 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1233 1234 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1235 xr = A->n; yr = A->m; h = yr/10.0; w = xr/10.0; 1236 xr += w; yr += h; xl = -w; yl = -h; 1237 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1238 ierr = PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);CHKERRQ(ierr); 1239 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); 1240 PetscFunctionReturn(0); 1241 } 1242 1243 #undef __FUNCT__ 1244 #define __FUNCT__ "MatView_SeqBAIJ" 1245 PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer) 1246 { 1247 PetscErrorCode ierr; 1248 PetscTruth iascii,isbinary,isdraw; 1249 1250 PetscFunctionBegin; 1251 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1252 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1253 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1254 if (iascii){ 1255 ierr = MatView_SeqBAIJ_ASCII(A,viewer);CHKERRQ(ierr); 1256 } else if (isbinary) { 1257 ierr = MatView_SeqBAIJ_Binary(A,viewer);CHKERRQ(ierr); 1258 } else if (isdraw) { 1259 ierr = MatView_SeqBAIJ_Draw(A,viewer);CHKERRQ(ierr); 1260 } else { 1261 Mat B; 1262 ierr = MatConvert(A,MATSEQAIJ,&B);CHKERRQ(ierr); 1263 ierr = MatView(B,viewer);CHKERRQ(ierr); 1264 ierr = MatDestroy(B);CHKERRQ(ierr); 1265 } 1266 PetscFunctionReturn(0); 1267 } 1268 1269 1270 #undef __FUNCT__ 1271 #define __FUNCT__ "MatGetValues_SeqBAIJ" 1272 PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 1273 { 1274 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1275 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 1276 PetscInt *ai = a->i,*ailen = a->ilen; 1277 PetscInt brow,bcol,ridx,cidx,bs=A->bs,bs2=a->bs2; 1278 MatScalar *ap,*aa = a->a,zero = 0.0; 1279 1280 PetscFunctionBegin; 1281 for (k=0; k<m; k++) { /* loop over rows */ 1282 row = im[k]; brow = row/bs; 1283 if (row < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 1284 if (row >= A->m) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row); 1285 rp = aj + ai[brow] ; ap = aa + bs2*ai[brow] ; 1286 nrow = ailen[brow]; 1287 for (l=0; l<n; l++) { /* loop over columns */ 1288 if (in[l] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); 1289 if (in[l] >= A->n) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]); 1290 col = in[l] ; 1291 bcol = col/bs; 1292 cidx = col%bs; 1293 ridx = row%bs; 1294 high = nrow; 1295 low = 0; /* assume unsorted */ 1296 while (high-low > 5) { 1297 t = (low+high)/2; 1298 if (rp[t] > bcol) high = t; 1299 else low = t; 1300 } 1301 for (i=low; i<high; i++) { 1302 if (rp[i] > bcol) break; 1303 if (rp[i] == bcol) { 1304 *v++ = ap[bs2*i+bs*cidx+ridx]; 1305 goto finished; 1306 } 1307 } 1308 *v++ = zero; 1309 finished:; 1310 } 1311 } 1312 PetscFunctionReturn(0); 1313 } 1314 1315 #if defined(PETSC_USE_MAT_SINGLE) 1316 #undef __FUNCT__ 1317 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ" 1318 PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 1319 { 1320 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)mat->data; 1321 PetscErrorCode ierr; 1322 PetscInt i,N = m*n*b->bs2; 1323 MatScalar *vsingle; 1324 1325 PetscFunctionBegin; 1326 if (N > b->setvalueslen) { 1327 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 1328 ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr); 1329 b->setvalueslen = N; 1330 } 1331 vsingle = b->setvaluescopy; 1332 for (i=0; i<N; i++) { 1333 vsingle[i] = v[i]; 1334 } 1335 ierr = MatSetValuesBlocked_SeqBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 1336 PetscFunctionReturn(0); 1337 } 1338 #endif 1339 1340 1341 #undef __FUNCT__ 1342 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ" 1343 PetscErrorCode MatSetValuesBlocked_SeqBAIJ_MatScalar(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode is) 1344 { 1345 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1346 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,sorted=a->sorted; 1347 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 1348 PetscErrorCode ierr; 1349 PetscInt *aj=a->j,nonew=a->nonew,bs2=a->bs2,bs=A->bs,stepval; 1350 PetscTruth roworiented=a->roworiented; 1351 const MatScalar *value = v; 1352 MatScalar *ap,*aa = a->a,*bap; 1353 1354 PetscFunctionBegin; 1355 if (roworiented) { 1356 stepval = (n-1)*bs; 1357 } else { 1358 stepval = (m-1)*bs; 1359 } 1360 for (k=0; k<m; k++) { /* loop over added rows */ 1361 row = im[k]; 1362 if (row < 0) continue; 1363 #if defined(PETSC_USE_BOPT_g) 1364 if (row >= a->mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1); 1365 #endif 1366 rp = aj + ai[row]; 1367 ap = aa + bs2*ai[row]; 1368 rmax = imax[row]; 1369 nrow = ailen[row]; 1370 low = 0; 1371 for (l=0; l<n; l++) { /* loop over added columns */ 1372 if (in[l] < 0) continue; 1373 #if defined(PETSC_USE_BOPT_g) 1374 if (in[l] >= a->nbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],a->nbs-1); 1375 #endif 1376 col = in[l]; 1377 if (roworiented) { 1378 value = v + k*(stepval+bs)*bs + l*bs; 1379 } else { 1380 value = v + l*(stepval+bs)*bs + k*bs; 1381 } 1382 if (!sorted) low = 0; high = nrow; 1383 while (high-low > 7) { 1384 t = (low+high)/2; 1385 if (rp[t] > col) high = t; 1386 else low = t; 1387 } 1388 for (i=low; i<high; i++) { 1389 if (rp[i] > col) break; 1390 if (rp[i] == col) { 1391 bap = ap + bs2*i; 1392 if (roworiented) { 1393 if (is == ADD_VALUES) { 1394 for (ii=0; ii<bs; ii++,value+=stepval) { 1395 for (jj=ii; jj<bs2; jj+=bs) { 1396 bap[jj] += *value++; 1397 } 1398 } 1399 } else { 1400 for (ii=0; ii<bs; ii++,value+=stepval) { 1401 for (jj=ii; jj<bs2; jj+=bs) { 1402 bap[jj] = *value++; 1403 } 1404 } 1405 } 1406 } else { 1407 if (is == ADD_VALUES) { 1408 for (ii=0; ii<bs; ii++,value+=stepval) { 1409 for (jj=0; jj<bs; jj++) { 1410 *bap++ += *value++; 1411 } 1412 } 1413 } else { 1414 for (ii=0; ii<bs; ii++,value+=stepval) { 1415 for (jj=0; jj<bs; jj++) { 1416 *bap++ = *value++; 1417 } 1418 } 1419 } 1420 } 1421 goto noinsert2; 1422 } 1423 } 1424 if (nonew == 1) goto noinsert2; 1425 else if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1426 if (nrow >= rmax) { 1427 /* there is no extra room in row, therefore enlarge */ 1428 PetscInt new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; 1429 MatScalar *new_a; 1430 1431 if (nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1432 1433 /* malloc new storage space */ 1434 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(PetscInt); 1435 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); 1436 new_j = (PetscInt*)(new_a + bs2*new_nz); 1437 new_i = new_j + new_nz; 1438 1439 /* copy over old data into new slots */ 1440 for (ii=0; ii<row+1; ii++) {new_i[ii] = ai[ii];} 1441 for (ii=row+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} 1442 ierr = PetscMemcpy(new_j,aj,(ai[row]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); 1443 len = (new_nz - CHUNKSIZE - ai[row] - nrow); 1444 ierr = PetscMemcpy(new_j+ai[row]+nrow+CHUNKSIZE,aj+ai[row]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); 1445 ierr = PetscMemcpy(new_a,aa,(ai[row]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); 1446 ierr = PetscMemzero(new_a+bs2*(ai[row]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); 1447 ierr = PetscMemcpy(new_a+bs2*(ai[row]+nrow+CHUNKSIZE),aa+bs2*(ai[row]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); 1448 /* free up old matrix storage */ 1449 ierr = PetscFree(a->a);CHKERRQ(ierr); 1450 if (!a->singlemalloc) { 1451 ierr = PetscFree(a->i);CHKERRQ(ierr); 1452 ierr = PetscFree(a->j);CHKERRQ(ierr); 1453 } 1454 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; 1455 a->singlemalloc = PETSC_TRUE; 1456 1457 rp = aj + ai[row]; ap = aa + bs2*ai[row]; 1458 rmax = imax[row] = imax[row] + CHUNKSIZE; 1459 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); 1460 a->maxnz += bs2*CHUNKSIZE; 1461 a->reallocs++; 1462 a->nz++; 1463 } 1464 N = nrow++ - 1; 1465 /* shift up all the later entries in this row */ 1466 for (ii=N; ii>=i; ii--) { 1467 rp[ii+1] = rp[ii]; 1468 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 1469 } 1470 if (N >= i) { 1471 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1472 } 1473 rp[i] = col; 1474 bap = ap + bs2*i; 1475 if (roworiented) { 1476 for (ii=0; ii<bs; ii++,value+=stepval) { 1477 for (jj=ii; jj<bs2; jj+=bs) { 1478 bap[jj] = *value++; 1479 } 1480 } 1481 } else { 1482 for (ii=0; ii<bs; ii++,value+=stepval) { 1483 for (jj=0; jj<bs; jj++) { 1484 *bap++ = *value++; 1485 } 1486 } 1487 } 1488 noinsert2:; 1489 low = i; 1490 } 1491 ailen[row] = nrow; 1492 } 1493 PetscFunctionReturn(0); 1494 } 1495 1496 #undef __FUNCT__ 1497 #define __FUNCT__ "MatAssemblyEnd_SeqBAIJ" 1498 PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode) 1499 { 1500 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1501 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 1502 PetscInt m = A->m,*ip,N,*ailen = a->ilen; 1503 PetscErrorCode ierr; 1504 PetscInt mbs = a->mbs,bs2 = a->bs2,rmax = 0; 1505 MatScalar *aa = a->a,*ap; 1506 PetscReal ratio=0.6; 1507 1508 PetscFunctionBegin; 1509 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 1510 1511 if (m) rmax = ailen[0]; 1512 for (i=1; i<mbs; i++) { 1513 /* move each row back by the amount of empty slots (fshift) before it*/ 1514 fshift += imax[i-1] - ailen[i-1]; 1515 rmax = PetscMax(rmax,ailen[i]); 1516 if (fshift) { 1517 ip = aj + ai[i]; ap = aa + bs2*ai[i]; 1518 N = ailen[i]; 1519 for (j=0; j<N; j++) { 1520 ip[j-fshift] = ip[j]; 1521 ierr = PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1522 } 1523 } 1524 ai[i] = ai[i-1] + ailen[i-1]; 1525 } 1526 if (mbs) { 1527 fshift += imax[mbs-1] - ailen[mbs-1]; 1528 ai[mbs] = ai[mbs-1] + ailen[mbs-1]; 1529 } 1530 /* reset ilen and imax for each row */ 1531 for (i=0; i<mbs; i++) { 1532 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1533 } 1534 a->nz = ai[mbs]; 1535 1536 /* diagonals may have moved, so kill the diagonal pointers */ 1537 a->idiagvalid = PETSC_FALSE; 1538 if (fshift && a->diag) { 1539 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1540 PetscLogObjectMemory(A,-(mbs+1)*sizeof(PetscInt)); 1541 a->diag = 0; 1542 } 1543 PetscLogInfo(A,"MatAssemblyEnd_SeqBAIJ:Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->n,A->bs,fshift*bs2,a->nz*bs2); 1544 PetscLogInfo(A,"MatAssemblyEnd_SeqBAIJ:Number of mallocs during MatSetValues is %D\n",a->reallocs); 1545 PetscLogInfo(A,"MatAssemblyEnd_SeqBAIJ:Most nonzeros blocks in any row is %D\n",rmax); 1546 a->reallocs = 0; 1547 A->info.nz_unneeded = (PetscReal)fshift*bs2; 1548 1549 /* check for zero rows. If found a large number of nonzero rows, use CompressedRow functions */ 1550 if (!a->compressedrow.checked && a->compressedrow.use){ /* fshift=!samestructure? NO. */ 1551 ierr = Mat_CheckCompressedRow(A,&a->compressedrow,a->i,ratio);CHKERRQ(ierr); 1552 } else if (a->compressedrow.checked && a->compressedrow.use){ 1553 /* mat structure likely has been changed. Do not use compressed row format until a better 1554 flag on changing mat structure is introduced */ 1555 ierr = PetscFree(a->compressedrow.i);CHKERRQ(ierr); 1556 a->compressedrow.use = PETSC_FALSE; 1557 a->compressedrow.rindex = PETSC_NULL; 1558 } 1559 PetscFunctionReturn(0); 1560 } 1561 1562 /* 1563 This function returns an array of flags which indicate the locations of contiguous 1564 blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] 1565 then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)] 1566 Assume: sizes should be long enough to hold all the values. 1567 */ 1568 #undef __FUNCT__ 1569 #define __FUNCT__ "MatZeroRows_SeqBAIJ_Check_Blocks" 1570 static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max) 1571 { 1572 PetscInt i,j,k,row; 1573 PetscTruth flg; 1574 1575 PetscFunctionBegin; 1576 for (i=0,j=0; i<n; j++) { 1577 row = idx[i]; 1578 if (row%bs!=0) { /* Not the begining of a block */ 1579 sizes[j] = 1; 1580 i++; 1581 } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */ 1582 sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */ 1583 i++; 1584 } else { /* Begining of the block, so check if the complete block exists */ 1585 flg = PETSC_TRUE; 1586 for (k=1; k<bs; k++) { 1587 if (row+k != idx[i+k]) { /* break in the block */ 1588 flg = PETSC_FALSE; 1589 break; 1590 } 1591 } 1592 if (flg == PETSC_TRUE) { /* No break in the bs */ 1593 sizes[j] = bs; 1594 i+= bs; 1595 } else { 1596 sizes[j] = 1; 1597 i++; 1598 } 1599 } 1600 } 1601 *bs_max = j; 1602 PetscFunctionReturn(0); 1603 } 1604 1605 #undef __FUNCT__ 1606 #define __FUNCT__ "MatZeroRows_SeqBAIJ" 1607 PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,IS is,const PetscScalar *diag) 1608 { 1609 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 1610 PetscErrorCode ierr; 1611 PetscInt i,j,k,count,is_n,*is_idx,*rows; 1612 PetscInt bs=A->bs,bs2=baij->bs2,*sizes,row,bs_max; 1613 PetscScalar zero = 0.0; 1614 MatScalar *aa; 1615 1616 PetscFunctionBegin; 1617 /* Make a copy of the IS and sort it */ 1618 ierr = ISGetLocalSize(is,&is_n);CHKERRQ(ierr); 1619 ierr = ISGetIndices(is,&is_idx);CHKERRQ(ierr); 1620 1621 /* allocate memory for rows,sizes */ 1622 ierr = PetscMalloc((3*is_n+1)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 1623 sizes = rows + is_n; 1624 1625 /* copy IS values to rows, and sort them */ 1626 for (i=0; i<is_n; i++) { rows[i] = is_idx[i]; } 1627 ierr = PetscSortInt(is_n,rows);CHKERRQ(ierr); 1628 if (baij->keepzeroedrows) { 1629 for (i=0; i<is_n; i++) { sizes[i] = 1; } 1630 bs_max = is_n; 1631 } else { 1632 ierr = MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);CHKERRQ(ierr); 1633 } 1634 ierr = ISRestoreIndices(is,&is_idx);CHKERRQ(ierr); 1635 1636 for (i=0,j=0; i<bs_max; j+=sizes[i],i++) { 1637 row = rows[j]; 1638 if (row < 0 || row > A->m) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row); 1639 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1640 aa = baij->a + baij->i[row/bs]*bs2 + (row%bs); 1641 if (sizes[i] == bs && !baij->keepzeroedrows) { 1642 if (diag) { 1643 if (baij->ilen[row/bs] > 0) { 1644 baij->ilen[row/bs] = 1; 1645 baij->j[baij->i[row/bs]] = row/bs; 1646 ierr = PetscMemzero(aa,count*bs*sizeof(MatScalar));CHKERRQ(ierr); 1647 } 1648 /* Now insert all the diagonal values for this bs */ 1649 for (k=0; k<bs; k++) { 1650 ierr = (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,diag,INSERT_VALUES);CHKERRQ(ierr); 1651 } 1652 } else { /* (!diag) */ 1653 baij->ilen[row/bs] = 0; 1654 } /* end (!diag) */ 1655 } else { /* (sizes[i] != bs) */ 1656 #if defined (PETSC_USE_DEBUG) 1657 if (sizes[i] != 1) SETERRQ(PETSC_ERR_PLIB,"Internal Error. Value should be 1"); 1658 #endif 1659 for (k=0; k<count; k++) { 1660 aa[0] = zero; 1661 aa += bs; 1662 } 1663 if (diag) { 1664 ierr = (*A->ops->setvalues)(A,1,rows+j,1,rows+j,diag,INSERT_VALUES);CHKERRQ(ierr); 1665 } 1666 } 1667 } 1668 1669 ierr = PetscFree(rows);CHKERRQ(ierr); 1670 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1671 PetscFunctionReturn(0); 1672 } 1673 1674 #undef __FUNCT__ 1675 #define __FUNCT__ "MatSetValues_SeqBAIJ" 1676 PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 1677 { 1678 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1679 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,sorted=a->sorted; 1680 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 1681 PetscInt *aj=a->j,nonew=a->nonew,bs=A->bs,brow,bcol; 1682 PetscErrorCode ierr; 1683 PetscInt ridx,cidx,bs2=a->bs2; 1684 PetscTruth roworiented=a->roworiented; 1685 MatScalar *ap,value,*aa=a->a,*bap; 1686 1687 PetscFunctionBegin; 1688 for (k=0; k<m; k++) { /* loop over added rows */ 1689 row = im[k]; brow = row/bs; 1690 if (row < 0) continue; 1691 #if defined(PETSC_USE_BOPT_g) 1692 if (row >= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->m-1); 1693 #endif 1694 rp = aj + ai[brow]; 1695 ap = aa + bs2*ai[brow]; 1696 rmax = imax[brow]; 1697 nrow = ailen[brow]; 1698 low = 0; 1699 for (l=0; l<n; l++) { /* loop over added columns */ 1700 if (in[l] < 0) continue; 1701 #if defined(PETSC_USE_BOPT_g) 1702 if (in[l] >= A->n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->n-1); 1703 #endif 1704 col = in[l]; bcol = col/bs; 1705 ridx = row % bs; cidx = col % bs; 1706 if (roworiented) { 1707 value = v[l + k*n]; 1708 } else { 1709 value = v[k + l*m]; 1710 } 1711 if (!sorted) low = 0; high = nrow; 1712 while (high-low > 7) { 1713 t = (low+high)/2; 1714 if (rp[t] > bcol) high = t; 1715 else low = t; 1716 } 1717 for (i=low; i<high; i++) { 1718 if (rp[i] > bcol) break; 1719 if (rp[i] == bcol) { 1720 bap = ap + bs2*i + bs*cidx + ridx; 1721 if (is == ADD_VALUES) *bap += value; 1722 else *bap = value; 1723 goto noinsert1; 1724 } 1725 } 1726 if (nonew == 1) goto noinsert1; 1727 else if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1728 if (nrow >= rmax) { 1729 /* there is no extra room in row, therefore enlarge */ 1730 PetscInt new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; 1731 MatScalar *new_a; 1732 1733 if (nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1734 1735 /* Malloc new storage space */ 1736 len = new_nz*(sizeof(PetscInt)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(PetscInt); 1737 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); 1738 new_j = (PetscInt*)(new_a + bs2*new_nz); 1739 new_i = new_j + new_nz; 1740 1741 /* copy over old data into new slots */ 1742 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} 1743 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} 1744 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(PetscInt));CHKERRQ(ierr); 1745 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); 1746 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(PetscInt));CHKERRQ(ierr); 1747 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); 1748 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); 1749 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE),aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); 1750 /* free up old matrix storage */ 1751 ierr = PetscFree(a->a);CHKERRQ(ierr); 1752 if (!a->singlemalloc) { 1753 ierr = PetscFree(a->i);CHKERRQ(ierr); 1754 ierr = PetscFree(a->j);CHKERRQ(ierr); 1755 } 1756 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; 1757 a->singlemalloc = PETSC_TRUE; 1758 1759 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; 1760 rmax = imax[brow] = imax[brow] + CHUNKSIZE; 1761 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(PetscInt) + bs2*sizeof(MatScalar))); 1762 a->maxnz += bs2*CHUNKSIZE; 1763 a->reallocs++; 1764 a->nz++; 1765 } 1766 N = nrow++ - 1; 1767 /* shift up all the later entries in this row */ 1768 for (ii=N; ii>=i; ii--) { 1769 rp[ii+1] = rp[ii]; 1770 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 1771 } 1772 if (N>=i) { 1773 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1774 } 1775 rp[i] = bcol; 1776 ap[bs2*i + bs*cidx + ridx] = value; 1777 noinsert1:; 1778 low = i; 1779 } 1780 ailen[brow] = nrow; 1781 } 1782 PetscFunctionReturn(0); 1783 } 1784 1785 1786 #undef __FUNCT__ 1787 #define __FUNCT__ "MatILUFactor_SeqBAIJ" 1788 PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,MatFactorInfo *info) 1789 { 1790 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inA->data; 1791 Mat outA; 1792 PetscErrorCode ierr; 1793 PetscTruth row_identity,col_identity; 1794 1795 PetscFunctionBegin; 1796 if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU"); 1797 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 1798 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 1799 if (!row_identity || !col_identity) { 1800 SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU"); 1801 } 1802 1803 outA = inA; 1804 inA->factor = FACTOR_LU; 1805 1806 if (!a->diag) { 1807 ierr = MatMarkDiagonal_SeqBAIJ(inA);CHKERRQ(ierr); 1808 } 1809 1810 a->row = row; 1811 a->col = col; 1812 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 1813 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 1814 1815 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 1816 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 1817 PetscLogObjectParent(inA,a->icol); 1818 1819 /* 1820 Blocksize 2, 3, 4, 5, 6 and 7 have a special faster factorization/solver 1821 for ILU(0) factorization with natural ordering 1822 */ 1823 if (inA->bs < 8) { 1824 ierr = MatSeqBAIJ_UpdateFactorNumeric_NaturalOrdering(inA);CHKERRQ(ierr); 1825 } else { 1826 if (!a->solve_work) { 1827 ierr = PetscMalloc((inA->m+inA->bs)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 1828 PetscLogObjectMemory(inA,(inA->m+inA->bs)*sizeof(PetscScalar)); 1829 } 1830 } 1831 1832 ierr = MatLUFactorNumeric(inA,&outA);CHKERRQ(ierr); 1833 1834 PetscFunctionReturn(0); 1835 } 1836 #undef __FUNCT__ 1837 #define __FUNCT__ "MatPrintHelp_SeqBAIJ" 1838 PetscErrorCode MatPrintHelp_SeqBAIJ(Mat A) 1839 { 1840 static PetscTruth called = PETSC_FALSE; 1841 MPI_Comm comm = A->comm; 1842 PetscErrorCode ierr; 1843 1844 PetscFunctionBegin; 1845 if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; 1846 ierr = (*PetscHelpPrintf)(comm," Options for MATSEQBAIJ and MATMPIBAIJ matrix formats (the defaults):\n");CHKERRQ(ierr); 1847 ierr = (*PetscHelpPrintf)(comm," -mat_block_size <block_size>\n");CHKERRQ(ierr); 1848 PetscFunctionReturn(0); 1849 } 1850 1851 EXTERN_C_BEGIN 1852 #undef __FUNCT__ 1853 #define __FUNCT__ "MatSeqBAIJSetColumnIndices_SeqBAIJ" 1854 PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices) 1855 { 1856 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ *)mat->data; 1857 PetscInt i,nz,nbs; 1858 1859 PetscFunctionBegin; 1860 nz = baij->maxnz/baij->bs2; 1861 nbs = baij->nbs; 1862 for (i=0; i<nz; i++) { 1863 baij->j[i] = indices[i]; 1864 } 1865 baij->nz = nz; 1866 for (i=0; i<nbs; i++) { 1867 baij->ilen[i] = baij->imax[i]; 1868 } 1869 1870 PetscFunctionReturn(0); 1871 } 1872 EXTERN_C_END 1873 1874 #undef __FUNCT__ 1875 #define __FUNCT__ "MatSeqBAIJSetColumnIndices" 1876 /*@ 1877 MatSeqBAIJSetColumnIndices - Set the column indices for all the rows 1878 in the matrix. 1879 1880 Input Parameters: 1881 + mat - the SeqBAIJ matrix 1882 - indices - the column indices 1883 1884 Level: advanced 1885 1886 Notes: 1887 This can be called if you have precomputed the nonzero structure of the 1888 matrix and want to provide it to the matrix object to improve the performance 1889 of the MatSetValues() operation. 1890 1891 You MUST have set the correct numbers of nonzeros per row in the call to 1892 MatCreateSeqBAIJ(). 1893 1894 MUST be called before any calls to MatSetValues(); 1895 1896 @*/ 1897 PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices) 1898 { 1899 PetscErrorCode ierr,(*f)(Mat,PetscInt *); 1900 1901 PetscFunctionBegin; 1902 PetscValidHeaderSpecific(mat,MAT_COOKIE,1); 1903 PetscValidPointer(indices,2); 1904 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqBAIJSetColumnIndices_C",(void (**)(void))&f);CHKERRQ(ierr); 1905 if (f) { 1906 ierr = (*f)(mat,indices);CHKERRQ(ierr); 1907 } else { 1908 SETERRQ(PETSC_ERR_ARG_WRONG,"Wrong type of matrix to set column indices"); 1909 } 1910 PetscFunctionReturn(0); 1911 } 1912 1913 #undef __FUNCT__ 1914 #define __FUNCT__ "MatGetRowMax_SeqBAIJ" 1915 PetscErrorCode MatGetRowMax_SeqBAIJ(Mat A,Vec v) 1916 { 1917 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1918 PetscErrorCode ierr; 1919 PetscInt i,j,n,row,bs,*ai,*aj,mbs; 1920 PetscReal atmp; 1921 PetscScalar *x,zero = 0.0; 1922 MatScalar *aa; 1923 PetscInt ncols,brow,krow,kcol; 1924 1925 PetscFunctionBegin; 1926 if (A->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 1927 bs = A->bs; 1928 aa = a->a; 1929 ai = a->i; 1930 aj = a->j; 1931 mbs = a->mbs; 1932 1933 ierr = VecSet(&zero,v);CHKERRQ(ierr); 1934 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1935 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1936 if (n != A->m) SETERRQ(PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1937 for (i=0; i<mbs; i++) { 1938 ncols = ai[1] - ai[0]; ai++; 1939 brow = bs*i; 1940 for (j=0; j<ncols; j++){ 1941 /* bcol = bs*(*aj); */ 1942 for (kcol=0; kcol<bs; kcol++){ 1943 for (krow=0; krow<bs; krow++){ 1944 atmp = PetscAbsScalar(*aa); aa++; 1945 row = brow + krow; /* row index */ 1946 /* printf("val[%d,%d]: %g\n",row,bcol+kcol,atmp); */ 1947 if (PetscAbsScalar(x[row]) < atmp) x[row] = atmp; 1948 } 1949 } 1950 aj++; 1951 } 1952 } 1953 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1954 PetscFunctionReturn(0); 1955 } 1956 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatSetUpPreallocation_SeqBAIJ" 1959 PetscErrorCode MatSetUpPreallocation_SeqBAIJ(Mat A) 1960 { 1961 PetscErrorCode ierr; 1962 1963 PetscFunctionBegin; 1964 ierr = MatSeqBAIJSetPreallocation(A,1,PETSC_DEFAULT,0);CHKERRQ(ierr); 1965 PetscFunctionReturn(0); 1966 } 1967 1968 #undef __FUNCT__ 1969 #define __FUNCT__ "MatGetArray_SeqBAIJ" 1970 PetscErrorCode MatGetArray_SeqBAIJ(Mat A,PetscScalar *array[]) 1971 { 1972 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1973 PetscFunctionBegin; 1974 *array = a->a; 1975 PetscFunctionReturn(0); 1976 } 1977 1978 #undef __FUNCT__ 1979 #define __FUNCT__ "MatRestoreArray_SeqBAIJ" 1980 PetscErrorCode MatRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[]) 1981 { 1982 PetscFunctionBegin; 1983 PetscFunctionReturn(0); 1984 } 1985 1986 #include "petscblaslapack.h" 1987 #undef __FUNCT__ 1988 #define __FUNCT__ "MatAXPY_SeqBAIJ" 1989 PetscErrorCode MatAXPY_SeqBAIJ(const PetscScalar *a,Mat X,Mat Y,MatStructure str) 1990 { 1991 Mat_SeqBAIJ *x = (Mat_SeqBAIJ *)X->data,*y = (Mat_SeqBAIJ *)Y->data; 1992 PetscErrorCode ierr; 1993 PetscInt i,bs=Y->bs,j,bs2; 1994 PetscBLASInt one=1,bnz = (PetscBLASInt)x->nz; 1995 1996 PetscFunctionBegin; 1997 if (str == SAME_NONZERO_PATTERN) { 1998 BLaxpy_(&bnz,(PetscScalar*)a,x->a,&one,y->a,&one); 1999 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2000 if (y->xtoy && y->XtoY != X) { 2001 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2002 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 2003 } 2004 if (!y->xtoy) { /* get xtoy */ 2005 ierr = MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);CHKERRQ(ierr); 2006 y->XtoY = X; 2007 } 2008 bs2 = bs*bs; 2009 for (i=0; i<x->nz; i++) { 2010 j = 0; 2011 while (j < bs2){ 2012 y->a[bs2*y->xtoy[i]+j] += (*a)*(x->a[bs2*i+j]); 2013 j++; 2014 } 2015 } 2016 PetscLogInfo(0,"MatAXPY_SeqBAIJ: ratio of nnz(X)/nnz(Y): %D/%D = %g\n",bs2*x->nz,bs2*y->nz,(PetscReal)(bs2*x->nz)/(bs2*y->nz)); 2017 } else { 2018 ierr = MatAXPY_Basic(a,X,Y,str);CHKERRQ(ierr); 2019 } 2020 PetscFunctionReturn(0); 2021 } 2022 2023 /* -------------------------------------------------------------------*/ 2024 static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ, 2025 MatGetRow_SeqBAIJ, 2026 MatRestoreRow_SeqBAIJ, 2027 MatMult_SeqBAIJ_N, 2028 /* 4*/ MatMultAdd_SeqBAIJ_N, 2029 MatMultTranspose_SeqBAIJ, 2030 MatMultTransposeAdd_SeqBAIJ, 2031 MatSolve_SeqBAIJ_N, 2032 0, 2033 0, 2034 /*10*/ 0, 2035 MatLUFactor_SeqBAIJ, 2036 0, 2037 0, 2038 MatTranspose_SeqBAIJ, 2039 /*15*/ MatGetInfo_SeqBAIJ, 2040 MatEqual_SeqBAIJ, 2041 MatGetDiagonal_SeqBAIJ, 2042 MatDiagonalScale_SeqBAIJ, 2043 MatNorm_SeqBAIJ, 2044 /*20*/ 0, 2045 MatAssemblyEnd_SeqBAIJ, 2046 0, 2047 MatSetOption_SeqBAIJ, 2048 MatZeroEntries_SeqBAIJ, 2049 /*25*/ MatZeroRows_SeqBAIJ, 2050 MatLUFactorSymbolic_SeqBAIJ, 2051 MatLUFactorNumeric_SeqBAIJ_N, 2052 0, 2053 0, 2054 /*30*/ MatSetUpPreallocation_SeqBAIJ, 2055 MatILUFactorSymbolic_SeqBAIJ, 2056 0, 2057 MatGetArray_SeqBAIJ, 2058 MatRestoreArray_SeqBAIJ, 2059 /*35*/ MatDuplicate_SeqBAIJ, 2060 0, 2061 0, 2062 MatILUFactor_SeqBAIJ, 2063 0, 2064 /*40*/ MatAXPY_SeqBAIJ, 2065 MatGetSubMatrices_SeqBAIJ, 2066 MatIncreaseOverlap_SeqBAIJ, 2067 MatGetValues_SeqBAIJ, 2068 0, 2069 /*45*/ MatPrintHelp_SeqBAIJ, 2070 MatScale_SeqBAIJ, 2071 0, 2072 0, 2073 0, 2074 /*50*/ 0, 2075 MatGetRowIJ_SeqBAIJ, 2076 MatRestoreRowIJ_SeqBAIJ, 2077 0, 2078 0, 2079 /*55*/ 0, 2080 0, 2081 0, 2082 0, 2083 MatSetValuesBlocked_SeqBAIJ, 2084 /*60*/ MatGetSubMatrix_SeqBAIJ, 2085 MatDestroy_SeqBAIJ, 2086 MatView_SeqBAIJ, 2087 MatGetPetscMaps_Petsc, 2088 0, 2089 /*65*/ 0, 2090 0, 2091 0, 2092 0, 2093 0, 2094 /*70*/ MatGetRowMax_SeqBAIJ, 2095 MatConvert_Basic, 2096 0, 2097 0, 2098 0, 2099 /*75*/ 0, 2100 0, 2101 0, 2102 0, 2103 0, 2104 /*80*/ 0, 2105 0, 2106 0, 2107 0, 2108 MatLoad_SeqBAIJ, 2109 /*85*/ 0, 2110 0, 2111 0, 2112 0, 2113 0, 2114 /*90*/ 0, 2115 0, 2116 0, 2117 0, 2118 0, 2119 /*95*/ 0, 2120 0, 2121 0, 2122 0}; 2123 2124 EXTERN_C_BEGIN 2125 #undef __FUNCT__ 2126 #define __FUNCT__ "MatStoreValues_SeqBAIJ" 2127 PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat) 2128 { 2129 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)mat->data; 2130 PetscInt nz = aij->i[mat->m]*mat->bs*aij->bs2; 2131 PetscErrorCode ierr; 2132 2133 PetscFunctionBegin; 2134 if (aij->nonew != 1) { 2135 SETERRQ(PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 2136 } 2137 2138 /* allocate space for values if not already there */ 2139 if (!aij->saved_values) { 2140 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 2141 } 2142 2143 /* copy values over */ 2144 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2145 PetscFunctionReturn(0); 2146 } 2147 EXTERN_C_END 2148 2149 EXTERN_C_BEGIN 2150 #undef __FUNCT__ 2151 #define __FUNCT__ "MatRetrieveValues_SeqBAIJ" 2152 PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat) 2153 { 2154 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)mat->data; 2155 PetscErrorCode ierr; 2156 PetscInt nz = aij->i[mat->m]*mat->bs*aij->bs2; 2157 2158 PetscFunctionBegin; 2159 if (aij->nonew != 1) { 2160 SETERRQ(PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 2161 } 2162 if (!aij->saved_values) { 2163 SETERRQ(PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2164 } 2165 2166 /* copy values over */ 2167 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2168 PetscFunctionReturn(0); 2169 } 2170 EXTERN_C_END 2171 2172 EXTERN_C_BEGIN 2173 extern PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,const MatType,Mat*); 2174 extern PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat,const MatType,Mat*); 2175 EXTERN_C_END 2176 2177 EXTERN_C_BEGIN 2178 #undef __FUNCT__ 2179 #define __FUNCT__ "MatSeqBAIJSetPreallocation_SeqBAIJ" 2180 PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz) 2181 { 2182 Mat_SeqBAIJ *b; 2183 PetscErrorCode ierr; 2184 PetscInt i,len,mbs,nbs,bs2,newbs = bs; 2185 PetscTruth flg; 2186 2187 PetscFunctionBegin; 2188 2189 B->preallocated = PETSC_TRUE; 2190 ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&newbs,PETSC_NULL);CHKERRQ(ierr); 2191 if (nnz && newbs != bs) { 2192 SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting nnz"); 2193 } 2194 bs = newbs; 2195 2196 mbs = B->m/bs; 2197 nbs = B->n/bs; 2198 bs2 = bs*bs; 2199 2200 if (mbs*bs!=B->m || nbs*bs!=B->n) { 2201 SETERRQ3(PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->m,B->n,bs); 2202 } 2203 2204 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2205 if (nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 2206 if (nnz) { 2207 for (i=0; i<mbs; i++) { 2208 if (nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]); 2209 if (nnz[i] > nbs) SETERRQ3(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],nbs); 2210 } 2211 } 2212 2213 b = (Mat_SeqBAIJ*)B->data; 2214 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_no_unroll",&flg);CHKERRQ(ierr); 2215 B->ops->solve = MatSolve_SeqBAIJ_Update; 2216 B->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_Update; 2217 if (!flg) { 2218 switch (bs) { 2219 case 1: 2220 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_1; 2221 B->ops->mult = MatMult_SeqBAIJ_1; 2222 B->ops->multadd = MatMultAdd_SeqBAIJ_1; 2223 break; 2224 case 2: 2225 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_2; 2226 B->ops->mult = MatMult_SeqBAIJ_2; 2227 B->ops->multadd = MatMultAdd_SeqBAIJ_2; 2228 B->ops->pbrelax = MatPBRelax_SeqBAIJ_2; 2229 break; 2230 case 3: 2231 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_3; 2232 B->ops->mult = MatMult_SeqBAIJ_3; 2233 B->ops->multadd = MatMultAdd_SeqBAIJ_3; 2234 B->ops->pbrelax = MatPBRelax_SeqBAIJ_3; 2235 break; 2236 case 4: 2237 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4; 2238 B->ops->mult = MatMult_SeqBAIJ_4; 2239 B->ops->multadd = MatMultAdd_SeqBAIJ_4; 2240 B->ops->pbrelax = MatPBRelax_SeqBAIJ_4; 2241 break; 2242 case 5: 2243 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_5; 2244 B->ops->mult = MatMult_SeqBAIJ_5; 2245 B->ops->multadd = MatMultAdd_SeqBAIJ_5; 2246 B->ops->pbrelax = MatPBRelax_SeqBAIJ_5; 2247 break; 2248 case 6: 2249 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_6; 2250 B->ops->mult = MatMult_SeqBAIJ_6; 2251 B->ops->multadd = MatMultAdd_SeqBAIJ_6; 2252 break; 2253 case 7: 2254 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_7; 2255 B->ops->mult = MatMult_SeqBAIJ_7; 2256 B->ops->multadd = MatMultAdd_SeqBAIJ_7; 2257 break; 2258 default: 2259 B->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_N; 2260 B->ops->mult = MatMult_SeqBAIJ_N; 2261 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2262 break; 2263 } 2264 } 2265 B->bs = bs; 2266 b->mbs = mbs; 2267 b->nbs = nbs; 2268 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&b->imax);CHKERRQ(ierr); 2269 if (!nnz) { 2270 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2271 else if (nz <= 0) nz = 1; 2272 for (i=0; i<mbs; i++) b->imax[i] = nz; 2273 nz = nz*mbs; 2274 } else { 2275 nz = 0; 2276 for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 2277 } 2278 2279 /* allocate the matrix space */ 2280 len = nz*sizeof(PetscInt) + nz*bs2*sizeof(MatScalar) + (B->m+1)*sizeof(PetscInt); 2281 ierr = PetscMalloc(len,&b->a);CHKERRQ(ierr); 2282 ierr = PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));CHKERRQ(ierr); 2283 b->j = (PetscInt*)(b->a + nz*bs2); 2284 ierr = PetscMemzero(b->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 2285 b->i = b->j + nz; 2286 b->singlemalloc = PETSC_TRUE; 2287 2288 b->i[0] = 0; 2289 for (i=1; i<mbs+1; i++) { 2290 b->i[i] = b->i[i-1] + b->imax[i-1]; 2291 } 2292 2293 /* b->ilen will count nonzeros in each block row so far. */ 2294 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&b->ilen);CHKERRQ(ierr); 2295 PetscLogObjectMemory(B,len+2*(mbs+1)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_SeqBAIJ)); 2296 for (i=0; i<mbs; i++) { b->ilen[i] = 0;} 2297 2298 B->bs = bs; 2299 b->bs2 = bs2; 2300 b->mbs = mbs; 2301 b->nz = 0; 2302 b->maxnz = nz*bs2; 2303 B->info.nz_unneeded = (PetscReal)b->maxnz; 2304 PetscFunctionReturn(0); 2305 } 2306 EXTERN_C_END 2307 2308 /*MC 2309 MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on 2310 block sparse compressed row format. 2311 2312 Options Database Keys: 2313 . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions() 2314 2315 Level: beginner 2316 2317 .seealso: MatCreateSeqBAIJ 2318 M*/ 2319 2320 EXTERN_C_BEGIN 2321 #undef __FUNCT__ 2322 #define __FUNCT__ "MatCreate_SeqBAIJ" 2323 PetscErrorCode MatCreate_SeqBAIJ(Mat B) 2324 { 2325 PetscErrorCode ierr; 2326 PetscMPIInt size; 2327 Mat_SeqBAIJ *b; 2328 2329 PetscFunctionBegin; 2330 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 2331 if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2332 2333 B->m = B->M = PetscMax(B->m,B->M); 2334 B->n = B->N = PetscMax(B->n,B->N); 2335 ierr = PetscNew(Mat_SeqBAIJ,&b);CHKERRQ(ierr); 2336 B->data = (void*)b; 2337 ierr = PetscMemzero(b,sizeof(Mat_SeqBAIJ));CHKERRQ(ierr); 2338 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2339 B->factor = 0; 2340 B->lupivotthreshold = 1.0; 2341 B->mapping = 0; 2342 b->row = 0; 2343 b->col = 0; 2344 b->icol = 0; 2345 b->reallocs = 0; 2346 b->saved_values = 0; 2347 #if defined(PETSC_USE_MAT_SINGLE) 2348 b->setvalueslen = 0; 2349 b->setvaluescopy = PETSC_NULL; 2350 #endif 2351 2352 ierr = PetscMapCreateMPI(B->comm,B->m,B->m,&B->rmap);CHKERRQ(ierr); 2353 ierr = PetscMapCreateMPI(B->comm,B->n,B->n,&B->cmap);CHKERRQ(ierr); 2354 2355 b->sorted = PETSC_FALSE; 2356 b->roworiented = PETSC_TRUE; 2357 b->nonew = 0; 2358 b->diag = 0; 2359 b->solve_work = 0; 2360 b->mult_work = 0; 2361 B->spptr = 0; 2362 B->info.nz_unneeded = (PetscReal)b->maxnz; 2363 b->keepzeroedrows = PETSC_FALSE; 2364 b->xtoy = 0; 2365 b->XtoY = 0; 2366 b->compressedrow.use = PETSC_FALSE; 2367 b->compressedrow.nrows = 0; 2368 b->compressedrow.i = PETSC_NULL; 2369 b->compressedrow.rindex = PETSC_NULL; 2370 b->compressedrow.checked = PETSC_FALSE; 2371 2372 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 2373 "MatStoreValues_SeqBAIJ", 2374 MatStoreValues_SeqBAIJ);CHKERRQ(ierr); 2375 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 2376 "MatRetrieveValues_SeqBAIJ", 2377 MatRetrieveValues_SeqBAIJ);CHKERRQ(ierr); 2378 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqBAIJSetColumnIndices_C", 2379 "MatSeqBAIJSetColumnIndices_SeqBAIJ", 2380 MatSeqBAIJSetColumnIndices_SeqBAIJ);CHKERRQ(ierr); 2381 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqbaij_seqaij_C", 2382 "MatConvert_SeqBAIJ_SeqAIJ", 2383 MatConvert_SeqBAIJ_SeqAIJ);CHKERRQ(ierr); 2384 #if !defined(PETSC_USE_64BIT_INT) 2385 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C", 2386 "MatConvert_SeqBAIJ_SeqSBAIJ", 2387 MatConvert_SeqBAIJ_SeqSBAIJ);CHKERRQ(ierr); 2388 #endif 2389 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqBAIJSetPreallocation_C", 2390 "MatSeqBAIJSetPreallocation_SeqBAIJ", 2391 MatSeqBAIJSetPreallocation_SeqBAIJ);CHKERRQ(ierr); 2392 PetscFunctionReturn(0); 2393 } 2394 EXTERN_C_END 2395 2396 #undef __FUNCT__ 2397 #define __FUNCT__ "MatDuplicate_SeqBAIJ" 2398 PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 2399 { 2400 Mat C; 2401 Mat_SeqBAIJ *c,*a = (Mat_SeqBAIJ*)A->data; 2402 PetscErrorCode ierr; 2403 PetscInt i,len,mbs = a->mbs,nz = a->nz,bs2 = a->bs2; 2404 2405 PetscFunctionBegin; 2406 if (a->i[mbs] != nz) SETERRQ(PETSC_ERR_PLIB,"Corrupt matrix"); 2407 2408 *B = 0; 2409 ierr = MatCreate(A->comm,A->m,A->n,A->m,A->n,&C);CHKERRQ(ierr); 2410 ierr = MatSetType(C,A->type_name);CHKERRQ(ierr); 2411 ierr = PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2412 c = (Mat_SeqBAIJ*)C->data; 2413 2414 C->M = A->M; 2415 C->N = A->N; 2416 C->bs = A->bs; 2417 c->bs2 = a->bs2; 2418 c->mbs = a->mbs; 2419 c->nbs = a->nbs; 2420 2421 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&c->imax);CHKERRQ(ierr); 2422 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&c->ilen);CHKERRQ(ierr); 2423 for (i=0; i<mbs; i++) { 2424 c->imax[i] = a->imax[i]; 2425 c->ilen[i] = a->ilen[i]; 2426 } 2427 2428 /* allocate the matrix space */ 2429 c->singlemalloc = PETSC_TRUE; 2430 len = (mbs+1)*sizeof(PetscInt) + nz*(bs2*sizeof(MatScalar) + sizeof(PetscInt)); 2431 ierr = PetscMalloc(len,&c->a);CHKERRQ(ierr); 2432 c->j = (PetscInt*)(c->a + nz*bs2); 2433 c->i = c->j + nz; 2434 ierr = PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 2435 if (mbs > 0) { 2436 ierr = PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 2437 if (cpvalues == MAT_COPY_VALUES) { 2438 ierr = PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 2439 } else { 2440 ierr = PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 2441 } 2442 } 2443 2444 PetscLogObjectMemory(C,len+2*(mbs+1)*sizeof(PetscInt)+sizeof(struct _p_Mat)+sizeof(Mat_SeqBAIJ)); 2445 c->sorted = a->sorted; 2446 c->roworiented = a->roworiented; 2447 c->nonew = a->nonew; 2448 2449 if (a->diag) { 2450 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 2451 PetscLogObjectMemory(C,(mbs+1)*sizeof(PetscInt)); 2452 for (i=0; i<mbs; i++) { 2453 c->diag[i] = a->diag[i]; 2454 } 2455 } else c->diag = 0; 2456 c->nz = a->nz; 2457 c->maxnz = a->maxnz; 2458 c->solve_work = 0; 2459 c->mult_work = 0; 2460 C->preallocated = PETSC_TRUE; 2461 C->assembled = PETSC_TRUE; 2462 *B = C; 2463 ierr = PetscFListDuplicate(A->qlist,&C->qlist);CHKERRQ(ierr); 2464 PetscFunctionReturn(0); 2465 } 2466 2467 #undef __FUNCT__ 2468 #define __FUNCT__ "MatLoad_SeqBAIJ" 2469 PetscErrorCode MatLoad_SeqBAIJ(PetscViewer viewer,const MatType type,Mat *A) 2470 { 2471 Mat_SeqBAIJ *a; 2472 Mat B; 2473 PetscErrorCode ierr; 2474 PetscInt i,nz,header[4],*rowlengths=0,M,N,bs=1; 2475 PetscInt *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount; 2476 PetscInt kmax,jcount,block,idx,point,nzcountb,extra_rows; 2477 PetscInt *masked,nmask,tmp,bs2,ishift; 2478 PetscMPIInt size; 2479 int fd; 2480 PetscScalar *aa; 2481 MPI_Comm comm = ((PetscObject)viewer)->comm; 2482 2483 PetscFunctionBegin; 2484 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 2485 bs2 = bs*bs; 2486 2487 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2488 if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"view must have one processor"); 2489 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2490 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 2491 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not Mat object"); 2492 M = header[1]; N = header[2]; nz = header[3]; 2493 2494 if (header[3] < 0) { 2495 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ"); 2496 } 2497 2498 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2499 2500 /* 2501 This code adds extra rows to make sure the number of rows is 2502 divisible by the blocksize 2503 */ 2504 mbs = M/bs; 2505 extra_rows = bs - M + bs*(mbs); 2506 if (extra_rows == bs) extra_rows = 0; 2507 else mbs++; 2508 if (extra_rows) { 2509 PetscLogInfo(0,"MatLoad_SeqBAIJ:Padding loaded matrix to match blocksize\n"); 2510 } 2511 2512 /* read in row lengths */ 2513 ierr = PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2514 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2515 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2516 2517 /* read in column indices */ 2518 ierr = PetscMalloc((nz+extra_rows)*sizeof(PetscInt),&jj);CHKERRQ(ierr); 2519 ierr = PetscBinaryRead(fd,jj,nz,PETSC_INT);CHKERRQ(ierr); 2520 for (i=0; i<extra_rows; i++) jj[nz+i] = M+i; 2521 2522 /* loop over row lengths determining block row lengths */ 2523 ierr = PetscMalloc(mbs*sizeof(PetscInt),&browlengths);CHKERRQ(ierr); 2524 ierr = PetscMemzero(browlengths,mbs*sizeof(PetscInt));CHKERRQ(ierr); 2525 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&mask);CHKERRQ(ierr); 2526 ierr = PetscMemzero(mask,mbs*sizeof(PetscInt));CHKERRQ(ierr); 2527 masked = mask + mbs; 2528 rowcount = 0; nzcount = 0; 2529 for (i=0; i<mbs; i++) { 2530 nmask = 0; 2531 for (j=0; j<bs; j++) { 2532 kmax = rowlengths[rowcount]; 2533 for (k=0; k<kmax; k++) { 2534 tmp = jj[nzcount++]/bs; 2535 if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;} 2536 } 2537 rowcount++; 2538 } 2539 browlengths[i] += nmask; 2540 /* zero out the mask elements we set */ 2541 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 2542 } 2543 2544 /* create our matrix */ 2545 ierr = MatCreate(comm,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows,&B); 2546 ierr = MatSetType(B,type);CHKERRQ(ierr); 2547 ierr = MatSeqBAIJSetPreallocation(B,bs,0,browlengths);CHKERRQ(ierr); 2548 a = (Mat_SeqBAIJ*)B->data; 2549 2550 /* set matrix "i" values */ 2551 a->i[0] = 0; 2552 for (i=1; i<= mbs; i++) { 2553 a->i[i] = a->i[i-1] + browlengths[i-1]; 2554 a->ilen[i-1] = browlengths[i-1]; 2555 } 2556 a->nz = 0; 2557 for (i=0; i<mbs; i++) a->nz += browlengths[i]; 2558 2559 /* read in nonzero values */ 2560 ierr = PetscMalloc((nz+extra_rows)*sizeof(PetscScalar),&aa);CHKERRQ(ierr); 2561 ierr = PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);CHKERRQ(ierr); 2562 for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0; 2563 2564 /* set "a" and "j" values into matrix */ 2565 nzcount = 0; jcount = 0; 2566 for (i=0; i<mbs; i++) { 2567 nzcountb = nzcount; 2568 nmask = 0; 2569 for (j=0; j<bs; j++) { 2570 kmax = rowlengths[i*bs+j]; 2571 for (k=0; k<kmax; k++) { 2572 tmp = jj[nzcount++]/bs; 2573 if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;} 2574 } 2575 } 2576 /* sort the masked values */ 2577 ierr = PetscSortInt(nmask,masked);CHKERRQ(ierr); 2578 2579 /* set "j" values into matrix */ 2580 maskcount = 1; 2581 for (j=0; j<nmask; j++) { 2582 a->j[jcount++] = masked[j]; 2583 mask[masked[j]] = maskcount++; 2584 } 2585 /* set "a" values into matrix */ 2586 ishift = bs2*a->i[i]; 2587 for (j=0; j<bs; j++) { 2588 kmax = rowlengths[i*bs+j]; 2589 for (k=0; k<kmax; k++) { 2590 tmp = jj[nzcountb]/bs ; 2591 block = mask[tmp] - 1; 2592 point = jj[nzcountb] - bs*tmp; 2593 idx = ishift + bs2*block + j + bs*point; 2594 a->a[idx] = (MatScalar)aa[nzcountb++]; 2595 } 2596 } 2597 /* zero out the mask elements we set */ 2598 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 2599 } 2600 if (jcount != a->nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix"); 2601 2602 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2603 ierr = PetscFree(browlengths);CHKERRQ(ierr); 2604 ierr = PetscFree(aa);CHKERRQ(ierr); 2605 ierr = PetscFree(jj);CHKERRQ(ierr); 2606 ierr = PetscFree(mask);CHKERRQ(ierr); 2607 2608 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2609 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2610 ierr = MatView_Private(B);CHKERRQ(ierr); 2611 2612 *A = B; 2613 PetscFunctionReturn(0); 2614 } 2615 2616 #undef __FUNCT__ 2617 #define __FUNCT__ "MatCreateSeqBAIJ" 2618 /*@C 2619 MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block 2620 compressed row) format. For good matrix assembly performance the 2621 user should preallocate the matrix storage by setting the parameter nz 2622 (or the array nnz). By setting these parameters accurately, performance 2623 during matrix assembly can be increased by more than a factor of 50. 2624 2625 Collective on MPI_Comm 2626 2627 Input Parameters: 2628 + comm - MPI communicator, set to PETSC_COMM_SELF 2629 . bs - size of block 2630 . m - number of rows 2631 . n - number of columns 2632 . nz - number of nonzero blocks per block row (same for all rows) 2633 - nnz - array containing the number of nonzero blocks in the various block rows 2634 (possibly different for each block row) or PETSC_NULL 2635 2636 Output Parameter: 2637 . A - the matrix 2638 2639 Options Database Keys: 2640 . -mat_no_unroll - uses code that does not unroll the loops in the 2641 block calculations (much slower) 2642 . -mat_block_size - size of the blocks to use 2643 2644 Level: intermediate 2645 2646 Notes: 2647 If the nnz parameter is given then the nz parameter is ignored 2648 2649 A nonzero block is any block that as 1 or more nonzeros in it 2650 2651 The block AIJ format is fully compatible with standard Fortran 77 2652 storage. That is, the stored row and column indices can begin at 2653 either one (as in Fortran) or zero. See the users' manual for details. 2654 2655 Specify the preallocated storage with either nz or nnz (not both). 2656 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2657 allocation. For additional details, see the users manual chapter on 2658 matrices. 2659 2660 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2661 @*/ 2662 PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 2663 { 2664 PetscErrorCode ierr; 2665 2666 PetscFunctionBegin; 2667 ierr = MatCreate(comm,m,n,m,n,A);CHKERRQ(ierr); 2668 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 2669 ierr = MatSeqBAIJSetPreallocation(*A,bs,nz,nnz);CHKERRQ(ierr); 2670 PetscFunctionReturn(0); 2671 } 2672 2673 #undef __FUNCT__ 2674 #define __FUNCT__ "MatSeqBAIJSetPreallocation" 2675 /*@C 2676 MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros 2677 per row in the matrix. For good matrix assembly performance the 2678 user should preallocate the matrix storage by setting the parameter nz 2679 (or the array nnz). By setting these parameters accurately, performance 2680 during matrix assembly can be increased by more than a factor of 50. 2681 2682 Collective on MPI_Comm 2683 2684 Input Parameters: 2685 + A - the matrix 2686 . bs - size of block 2687 . nz - number of block nonzeros per block row (same for all rows) 2688 - nnz - array containing the number of block nonzeros in the various block rows 2689 (possibly different for each block row) or PETSC_NULL 2690 2691 Options Database Keys: 2692 . -mat_no_unroll - uses code that does not unroll the loops in the 2693 block calculations (much slower) 2694 . -mat_block_size - size of the blocks to use 2695 2696 Level: intermediate 2697 2698 Notes: 2699 If the nnz parameter is given then the nz parameter is ignored 2700 2701 The block AIJ format is fully compatible with standard Fortran 77 2702 storage. That is, the stored row and column indices can begin at 2703 either one (as in Fortran) or zero. See the users' manual for details. 2704 2705 Specify the preallocated storage with either nz or nnz (not both). 2706 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2707 allocation. For additional details, see the users manual chapter on 2708 matrices. 2709 2710 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIBAIJ() 2711 @*/ 2712 PetscErrorCode MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[]) 2713 { 2714 PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[]); 2715 2716 PetscFunctionBegin; 2717 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2718 if (f) { 2719 ierr = (*f)(B,bs,nz,nnz);CHKERRQ(ierr); 2720 } 2721 PetscFunctionReturn(0); 2722 } 2723 2724