1 2 /* 3 This is included by sbaij.c to generate unsigned short and regular versions of these two functions 4 */ 5 #undef __FUNCT__ 6 #if defined(USESHORT) 7 #define __FUNCT__ "MatMult_SeqSBAIJ_1_Hermitian_ushort" 8 PetscErrorCode MatMult_SeqSBAIJ_1_Hermitian_ushort(Mat A,Vec xx,Vec zz) 9 #else 10 #define __FUNCT__ "MatMult_SeqSBAIJ_1_Hermitian" 11 PetscErrorCode MatMult_SeqSBAIJ_1_Hermitian(Mat A,Vec xx,Vec zz) 12 #endif 13 { 14 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 15 const PetscScalar *x; 16 PetscScalar *z,x1,sum; 17 const MatScalar *v; 18 MatScalar vj; 19 PetscErrorCode ierr; 20 PetscInt mbs=a->mbs,i,j,nz; 21 const PetscInt *ai=a->i; 22 #if defined(USESHORT) 23 const unsigned short *ib=a->jshort; 24 unsigned short ibt; 25 #else 26 const PetscInt *ib=a->j; 27 PetscInt ibt; 28 #endif 29 PetscInt nonzerorow = 0,jmin; 30 31 PetscFunctionBegin; 32 ierr = VecSet(zz,0.0);CHKERRQ(ierr); 33 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 34 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 35 36 v = a->a; 37 for (i=0; i<mbs; i++) { 38 nz = ai[i+1] - ai[i]; /* length of i_th row of A */ 39 if (!nz) continue; /* Move to the next row if the current row is empty */ 40 nonzerorow++; 41 x1 = x[i]; 42 sum = 0.0; 43 jmin = 0; 44 if (ib[0] == i) { 45 sum = v[0]*x1; /* diagonal term */ 46 jmin++; 47 } 48 for (j=jmin; j<nz; j++) { 49 ibt = ib[j]; 50 vj = v[j]; 51 sum += vj * x[ibt]; /* (strict upper triangular part of A)*x */ 52 z[ibt] += PetscConj(v[j]) * x1; /* (strict lower triangular part of A)*x */ 53 } 54 z[i] += sum; 55 v += nz; 56 ib += nz; 57 } 58 59 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 60 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 61 ierr = PetscLogFlops(2.0*(2.0*a->nz - nonzerorow) - nonzerorow);CHKERRQ(ierr); 62 PetscFunctionReturn(0); 63 } 64 65 #undef __FUNCT__ 66 #if defined(USESHORT) 67 #define __FUNCT__ "MatMult_SeqSBAIJ_1_ushort" 68 PetscErrorCode MatMult_SeqSBAIJ_1_ushort(Mat A,Vec xx,Vec zz) 69 #else 70 #define __FUNCT__ "MatMult_SeqSBAIJ_1" 71 PetscErrorCode MatMult_SeqSBAIJ_1(Mat A,Vec xx,Vec zz) 72 #endif 73 { 74 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 75 const PetscScalar *x; 76 PetscScalar *z,x1,sum; 77 const MatScalar *v; 78 MatScalar vj; 79 PetscErrorCode ierr; 80 PetscInt mbs=a->mbs,i,j,nz; 81 const PetscInt *ai=a->i; 82 #if defined(USESHORT) 83 const unsigned short *ib=a->jshort; 84 unsigned short ibt; 85 #else 86 const PetscInt *ib=a->j; 87 PetscInt ibt; 88 #endif 89 PetscInt nonzerorow=0,jmin; 90 91 PetscFunctionBegin; 92 ierr = VecSet(zz,0.0);CHKERRQ(ierr); 93 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 94 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 95 96 v = a->a; 97 for (i=0; i<mbs; i++) { 98 nz = ai[i+1] - ai[i]; /* length of i_th row of A */ 99 if (!nz) continue; /* Move to the next row if the current row is empty */ 100 nonzerorow++; 101 sum = 0.0; 102 jmin = 0; 103 x1 = x[i]; 104 if (ib[0] == i) { 105 sum = v[0]*x1; /* diagonal term */ 106 jmin++; 107 } 108 PetscPrefetchBlock(ib+nz,nz,0,PETSC_PREFETCH_HINT_NTA); /* Indices for the next row (assumes same size as this one) */ 109 PetscPrefetchBlock(v+nz,nz,0,PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */ 110 for (j=jmin; j<nz; j++) { 111 ibt = ib[j]; 112 vj = v[j]; 113 z[ibt] += vj * x1; /* (strict lower triangular part of A)*x */ 114 sum += vj * x[ibt]; /* (strict upper triangular part of A)*x */ 115 } 116 z[i] += sum; 117 v += nz; 118 ib += nz; 119 } 120 121 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 122 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 123 ierr = PetscLogFlops(2.0*(2.0*a->nz - nonzerorow) - nonzerorow);CHKERRQ(ierr); 124 PetscFunctionReturn(0); 125 } 126 127 #undef __FUNCT__ 128 #if defined(USESHORT) 129 #define __FUNCT__ "MatSOR_SeqSBAIJ_ushort" 130 PetscErrorCode MatSOR_SeqSBAIJ_ushort(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 131 #else 132 #define __FUNCT__ "MatSOR_SeqSBAIJ" 133 PetscErrorCode MatSOR_SeqSBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 134 #endif 135 { 136 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 137 const MatScalar *aa=a->a,*v,*v1,*aidiag; 138 PetscScalar *x,*t,sum; 139 const PetscScalar *b; 140 MatScalar tmp; 141 PetscErrorCode ierr; 142 PetscInt m =a->mbs,bs=A->rmap->bs,j; 143 const PetscInt *ai=a->i; 144 #if defined(USESHORT) 145 const unsigned short *aj=a->jshort,*vj,*vj1; 146 #else 147 const PetscInt *aj=a->j,*vj,*vj1; 148 #endif 149 PetscInt nz,nz1,i; 150 151 PetscFunctionBegin; 152 if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat"); 153 154 its = its*lits; 155 if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 156 157 if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); 158 159 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 160 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 161 162 if (!a->idiagvalid) { 163 if (!a->idiag) { 164 ierr = PetscMalloc1(m,&a->idiag);CHKERRQ(ierr); 165 } 166 for (i=0; i<a->mbs; i++) a->idiag[i] = 1.0/a->a[a->i[i]]; 167 a->idiagvalid = PETSC_TRUE; 168 } 169 170 if (!a->sor_work) { 171 ierr = PetscMalloc1(m,&a->sor_work);CHKERRQ(ierr); 172 } 173 t = a->sor_work; 174 175 aidiag = a->idiag; 176 177 if (flag == SOR_APPLY_UPPER) { 178 /* apply (U + D/omega) to the vector */ 179 PetscScalar d; 180 for (i=0; i<m; i++) { 181 d = fshift + aa[ai[i]]; 182 nz = ai[i+1] - ai[i] - 1; 183 vj = aj + ai[i] + 1; 184 v = aa + ai[i] + 1; 185 sum = b[i]*d/omega; 186 PetscSparseDensePlusDot(sum,b,v,vj,nz); 187 x[i] = sum; 188 } 189 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 190 } 191 192 if (flag & SOR_ZERO_INITIAL_GUESS) { 193 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 194 ierr = PetscMemcpy(t,b,m*sizeof(PetscScalar));CHKERRQ(ierr); 195 196 v = aa + 1; 197 vj = aj + 1; 198 for (i=0; i<m; i++) { 199 nz = ai[i+1] - ai[i] - 1; 200 tmp = -(x[i] = omega*t[i]*aidiag[i]); 201 for (j=0; j<nz; j++) t[vj[j]] += tmp*v[j]; 202 v += nz + 1; 203 vj += nz + 1; 204 } 205 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 206 } 207 208 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 209 int nz2; 210 if (!(flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP)) { 211 #if defined(PETSC_USE_BACKWARD_LOOP) 212 v = aa + ai[m] - 1; 213 vj = aj + ai[m] - 1; 214 for (i=m-1; i>=0; i--) { 215 sum = b[i]; 216 nz = ai[i+1] - ai[i] - 1; 217 {PetscInt __i;for (__i=0; __i<nz; __i++) sum -= v[-__i] * x[vj[-__i]];} 218 #else 219 v = aa + ai[m-1] + 1; 220 vj = aj + ai[m-1] + 1; 221 nz = 0; 222 for (i=m-1; i>=0; i--) { 223 sum = b[i]; 224 nz2 = ai[i] - ai[PetscMax(i-1,0)] - 1; /* avoid referencing ai[-1], nonsense nz2 is okay on last iteration */ 225 PETSC_Prefetch(v-nz2-1,0,PETSC_PREFETCH_HINT_NTA); 226 PETSC_Prefetch(vj-nz2-1,0,PETSC_PREFETCH_HINT_NTA); 227 PetscSparseDenseMinusDot(sum,x,v,vj,nz); 228 nz = nz2; 229 #endif 230 x[i] = omega*sum*aidiag[i]; 231 v -= nz + 1; 232 vj -= nz + 1; 233 } 234 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 235 } else { 236 v = aa + ai[m-1] + 1; 237 vj = aj + ai[m-1] + 1; 238 nz = 0; 239 for (i=m-1; i>=0; i--) { 240 sum = t[i]; 241 nz2 = ai[i] - ai[PetscMax(i-1,0)] - 1; /* avoid referencing ai[-1], nonsense nz2 is okay on last iteration */ 242 PETSC_Prefetch(v-nz2-1,0,PETSC_PREFETCH_HINT_NTA); 243 PETSC_Prefetch(vj-nz2-1,0,PETSC_PREFETCH_HINT_NTA); 244 PetscSparseDenseMinusDot(sum,x,v,vj,nz); 245 x[i] = (1-omega)*x[i] + omega*sum*aidiag[i]; 246 nz = nz2; 247 v -= nz + 1; 248 vj -= nz + 1; 249 } 250 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 251 } 252 } 253 its--; 254 } 255 256 while (its--) { 257 /* 258 forward sweep: 259 for i=0,...,m-1: 260 sum[i] = (b[i] - U(i,:)x)/d[i]; 261 x[i] = (1-omega)x[i] + omega*sum[i]; 262 b = b - x[i]*U^T(i,:); 263 264 */ 265 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 266 ierr = PetscMemcpy(t,b,m*sizeof(PetscScalar));CHKERRQ(ierr); 267 268 for (i=0; i<m; i++) { 269 v = aa + ai[i] + 1; v1=v; 270 vj = aj + ai[i] + 1; vj1=vj; 271 nz = ai[i+1] - ai[i] - 1; nz1=nz; 272 sum = t[i]; 273 while (nz1--) sum -= (*v1++)*x[*vj1++]; 274 x[i] = (1-omega)*x[i] + omega*sum*aidiag[i]; 275 while (nz--) t[*vj++] -= x[i]*(*v++); 276 } 277 ierr = PetscLogFlops(4.0*a->nz);CHKERRQ(ierr); 278 } 279 280 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 281 /* 282 backward sweep: 283 b = b - x[i]*U^T(i,:), i=0,...,n-2 284 for i=m-1,...,0: 285 sum[i] = (b[i] - U(i,:)x)/d[i]; 286 x[i] = (1-omega)x[i] + omega*sum[i]; 287 */ 288 /* if there was a forward sweep done above then I thing the next two for loops are not needed */ 289 ierr = PetscMemcpy(t,b,m*sizeof(PetscScalar));CHKERRQ(ierr); 290 291 for (i=0; i<m-1; i++) { /* update rhs */ 292 v = aa + ai[i] + 1; 293 vj = aj + ai[i] + 1; 294 nz = ai[i+1] - ai[i] - 1; 295 while (nz--) t[*vj++] -= x[i]*(*v++); 296 } 297 ierr = PetscLogFlops(2.0*(a->nz - m));CHKERRQ(ierr); 298 for (i=m-1; i>=0; i--) { 299 v = aa + ai[i] + 1; 300 vj = aj + ai[i] + 1; 301 nz = ai[i+1] - ai[i] - 1; 302 sum = t[i]; 303 while (nz--) sum -= x[*vj++]*(*v++); 304 x[i] = (1-omega)*x[i] + omega*sum*aidiag[i]; 305 } 306 ierr = PetscLogFlops(2.0*(a->nz + m));CHKERRQ(ierr); 307 } 308 } 309 310 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 311 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 312 PetscFunctionReturn(0); 313 } 314