Actual source code: relax.h
petsc-3.9.4 2018-09-11
2: /*
3: This is included by sbaij.c to generate unsigned short and regular versions of these two functions
4: */
6: /* We cut-and-past below from aij.h to make a "no_function" version of PetscSparseDensePlusDot().
7: * This is necessary because the USESHORT case cannot use the inlined functions that may be employed. */
9: #if defined(PETSC_KERNEL_USE_UNROLL_4)
10: #define PetscSparseDensePlusDot_no_function(sum,r,xv,xi,nnz) { \
11: if (nnz > 0) { \
12: PetscInt nnz2=nnz,rem=nnz&0x3; \
13: switch (rem) { \
14: case 3: sum += *xv++ *r[*xi++]; \
15: case 2: sum += *xv++ *r[*xi++]; \
16: case 1: sum += *xv++ *r[*xi++]; \
17: nnz2 -= rem;} \
18: while (nnz2 > 0) { \
19: sum += xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + \
20: xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
21: xv += 4; xi += 4; nnz2 -= 4; \
22: } \
23: xv -= nnz; xi -= nnz; \
24: } \
25: }
27: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
28: #define PetscSparseDensePlusDot_no_function(sum,r,xv,xi,nnz) { \
29: PetscInt __i,__i1,__i2; \
30: for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
31: sum += (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
32: if (nnz & 0x1) sum += xv[__i] * r[xi[__i]];}
34: #else
35: #define PetscSparseDensePlusDot_no_function(sum,r,xv,xi,nnz) { \
36: PetscInt __i; \
37: for (__i=0; __i<nnz; __i++) sum += xv[__i] * r[xi[__i]];}
38: #endif
41: #if defined(USESHORT)
42: PetscErrorCode MatMult_SeqSBAIJ_1_Hermitian_ushort(Mat A,Vec xx,Vec zz)
43: #else
44: PetscErrorCode MatMult_SeqSBAIJ_1_Hermitian(Mat A,Vec xx,Vec zz)
45: #endif
46: {
47: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
48: const PetscScalar *x;
49: PetscScalar *z,x1,sum;
50: const MatScalar *v;
51: MatScalar vj;
52: PetscErrorCode ierr;
53: PetscInt mbs=a->mbs,i,j,nz;
54: const PetscInt *ai=a->i;
55: #if defined(USESHORT)
56: const unsigned short *ib=a->jshort;
57: unsigned short ibt;
58: #else
59: const PetscInt *ib=a->j;
60: PetscInt ibt;
61: #endif
62: PetscInt nonzerorow = 0,jmin;
65: VecSet(zz,0.0);
66: VecGetArrayRead(xx,&x);
67: VecGetArray(zz,&z);
69: v = a->a;
70: for (i=0; i<mbs; i++) {
71: nz = ai[i+1] - ai[i]; /* length of i_th row of A */
72: if (!nz) continue; /* Move to the next row if the current row is empty */
73: nonzerorow++;
74: x1 = x[i];
75: sum = 0.0;
76: jmin = 0;
77: if (ib[0] == i) {
78: sum = v[0]*x1; /* diagonal term */
79: jmin++;
80: }
81: for (j=jmin; j<nz; j++) {
82: ibt = ib[j];
83: vj = v[j];
84: sum += vj * x[ibt]; /* (strict upper triangular part of A)*x */
85: z[ibt] += PetscConj(v[j]) * x1; /* (strict lower triangular part of A)*x */
86: }
87: z[i] += sum;
88: v += nz;
89: ib += nz;
90: }
92: VecRestoreArrayRead(xx,&x);
93: VecRestoreArray(zz,&z);
94: PetscLogFlops(2.0*(2.0*a->nz - nonzerorow) - nonzerorow);
95: return(0);
96: }
98: #if defined(USESHORT)
99: PetscErrorCode MatMult_SeqSBAIJ_1_ushort(Mat A,Vec xx,Vec zz)
100: #else
101: PetscErrorCode MatMult_SeqSBAIJ_1(Mat A,Vec xx,Vec zz)
102: #endif
103: {
104: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
105: const PetscScalar *x;
106: PetscScalar *z,x1,sum;
107: const MatScalar *v;
108: MatScalar vj;
109: PetscErrorCode ierr;
110: PetscInt mbs=a->mbs,i,j,nz;
111: const PetscInt *ai=a->i;
112: #if defined(USESHORT)
113: const unsigned short *ib=a->jshort;
114: unsigned short ibt;
115: #else
116: const PetscInt *ib=a->j;
117: PetscInt ibt;
118: #endif
119: PetscInt nonzerorow=0,jmin;
122: VecSet(zz,0.0);
123: VecGetArrayRead(xx,&x);
124: VecGetArray(zz,&z);
126: v = a->a;
127: for (i=0; i<mbs; i++) {
128: nz = ai[i+1] - ai[i]; /* length of i_th row of A */
129: if (!nz) continue; /* Move to the next row if the current row is empty */
130: nonzerorow++;
131: sum = 0.0;
132: jmin = 0;
133: x1 = x[i];
134: if (ib[0] == i) {
135: sum = v[0]*x1; /* diagonal term */
136: jmin++;
137: }
138: PetscPrefetchBlock(ib+nz,nz,0,PETSC_PREFETCH_HINT_NTA); /* Indices for the next row (assumes same size as this one) */
139: PetscPrefetchBlock(v+nz,nz,0,PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
140: for (j=jmin; j<nz; j++) {
141: ibt = ib[j];
142: vj = v[j];
143: z[ibt] += vj * x1; /* (strict lower triangular part of A)*x */
144: sum += vj * x[ibt]; /* (strict upper triangular part of A)*x */
145: }
146: z[i] += sum;
147: v += nz;
148: ib += nz;
149: }
151: VecRestoreArrayRead(xx,&x);
152: VecRestoreArray(zz,&z);
153: PetscLogFlops(2.0*(2.0*a->nz - nonzerorow) - nonzerorow);
154: return(0);
155: }
157: #if defined(USESHORT)
158: PetscErrorCode MatSOR_SeqSBAIJ_ushort(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
159: #else
160: PetscErrorCode MatSOR_SeqSBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
161: #endif
162: {
163: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
164: const MatScalar *aa=a->a,*v,*v1,*aidiag;
165: PetscScalar *x,*t,sum;
166: const PetscScalar *b;
167: MatScalar tmp;
168: PetscErrorCode ierr;
169: PetscInt m =a->mbs,bs=A->rmap->bs,j;
170: const PetscInt *ai=a->i;
171: #if defined(USESHORT)
172: const unsigned short *aj=a->jshort,*vj,*vj1;
173: #else
174: const PetscInt *aj=a->j,*vj,*vj1;
175: #endif
176: PetscInt nz,nz1,i;
179: if (fshift == -1.0) fshift = 0.0; /* negative fshift indicates do not error on zero diagonal; this code never errors on zero diagonal */
180: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
182: its = its*lits;
183: if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
185: if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");
187: VecGetArray(xx,&x);
188: VecGetArrayRead(bb,&b);
190: if (!a->idiagvalid) {
191: if (!a->idiag) {
192: PetscMalloc1(m,&a->idiag);
193: }
194: for (i=0; i<a->mbs; i++) a->idiag[i] = 1.0/a->a[a->i[i]];
195: a->idiagvalid = PETSC_TRUE;
196: }
198: if (!a->sor_work) {
199: PetscMalloc1(m,&a->sor_work);
200: }
201: t = a->sor_work;
203: aidiag = a->idiag;
205: if (flag == SOR_APPLY_UPPER) {
206: /* apply (U + D/omega) to the vector */
207: PetscScalar d;
208: for (i=0; i<m; i++) {
209: d = fshift + aa[ai[i]];
210: nz = ai[i+1] - ai[i] - 1;
211: vj = aj + ai[i] + 1;
212: v = aa + ai[i] + 1;
213: sum = b[i]*d/omega;
214: #ifdef USESHORT
215: PetscSparseDensePlusDot_no_function(sum,b,v,vj,nz);
216: #else
217: PetscSparseDensePlusDot(sum,b,v,vj,nz);
218: #endif
219: x[i] = sum;
220: }
221: PetscLogFlops(a->nz);
222: }
224: if (flag & SOR_ZERO_INITIAL_GUESS) {
225: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
226: PetscMemcpy(t,b,m*sizeof(PetscScalar));
228: v = aa + 1;
229: vj = aj + 1;
230: for (i=0; i<m; i++) {
231: nz = ai[i+1] - ai[i] - 1;
232: tmp = -(x[i] = omega*t[i]*aidiag[i]);
233: for (j=0; j<nz; j++) t[vj[j]] += tmp*v[j];
234: v += nz + 1;
235: vj += nz + 1;
236: }
237: PetscLogFlops(2*a->nz);
238: }
240: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
241: int nz2;
242: if (!(flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP)) {
243: #if defined(PETSC_USE_BACKWARD_LOOP)
244: v = aa + ai[m] - 1;
245: vj = aj + ai[m] - 1;
246: for (i=m-1; i>=0; i--) {
247: sum = b[i];
248: nz = ai[i+1] - ai[i] - 1;
249: {PetscInt __i;for (__i=0; __i<nz; __i++) sum -= v[-__i] * x[vj[-__i]];}
250: #else
251: v = aa + ai[m-1] + 1;
252: vj = aj + ai[m-1] + 1;
253: nz = 0;
254: for (i=m-1; i>=0; i--) {
255: sum = b[i];
256: nz2 = ai[i] - ai[PetscMax(i-1,0)] - 1; /* avoid referencing ai[-1], nonsense nz2 is okay on last iteration */
257: PETSC_Prefetch(v-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
258: PETSC_Prefetch(vj-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
259: PetscSparseDenseMinusDot(sum,x,v,vj,nz);
260: nz = nz2;
261: #endif
262: x[i] = omega*sum*aidiag[i];
263: v -= nz + 1;
264: vj -= nz + 1;
265: }
266: PetscLogFlops(2*a->nz);
267: } else {
268: v = aa + ai[m-1] + 1;
269: vj = aj + ai[m-1] + 1;
270: nz = 0;
271: for (i=m-1; i>=0; i--) {
272: sum = t[i];
273: nz2 = ai[i] - ai[PetscMax(i-1,0)] - 1; /* avoid referencing ai[-1], nonsense nz2 is okay on last iteration */
274: PETSC_Prefetch(v-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
275: PETSC_Prefetch(vj-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
276: PetscSparseDenseMinusDot(sum,x,v,vj,nz);
277: x[i] = (1-omega)*x[i] + omega*sum*aidiag[i];
278: nz = nz2;
279: v -= nz + 1;
280: vj -= nz + 1;
281: }
282: PetscLogFlops(2*a->nz);
283: }
284: }
285: its--;
286: }
288: while (its--) {
289: /*
290: forward sweep:
291: for i=0,...,m-1:
292: sum[i] = (b[i] - U(i,:)x)/d[i];
293: x[i] = (1-omega)x[i] + omega*sum[i];
294: b = b - x[i]*U^T(i,:);
296: */
297: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
298: PetscMemcpy(t,b,m*sizeof(PetscScalar));
300: for (i=0; i<m; i++) {
301: v = aa + ai[i] + 1; v1=v;
302: vj = aj + ai[i] + 1; vj1=vj;
303: nz = ai[i+1] - ai[i] - 1; nz1=nz;
304: sum = t[i];
305: while (nz1--) sum -= (*v1++)*x[*vj1++];
306: x[i] = (1-omega)*x[i] + omega*sum*aidiag[i];
307: while (nz--) t[*vj++] -= x[i]*(*v++);
308: }
309: PetscLogFlops(4.0*a->nz);
310: }
312: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
313: /*
314: backward sweep:
315: b = b - x[i]*U^T(i,:), i=0,...,n-2
316: for i=m-1,...,0:
317: sum[i] = (b[i] - U(i,:)x)/d[i];
318: x[i] = (1-omega)x[i] + omega*sum[i];
319: */
320: /* if there was a forward sweep done above then I thing the next two for loops are not needed */
321: PetscMemcpy(t,b,m*sizeof(PetscScalar));
323: for (i=0; i<m-1; i++) { /* update rhs */
324: v = aa + ai[i] + 1;
325: vj = aj + ai[i] + 1;
326: nz = ai[i+1] - ai[i] - 1;
327: while (nz--) t[*vj++] -= x[i]*(*v++);
328: }
329: PetscLogFlops(2.0*(a->nz - m));
330: for (i=m-1; i>=0; i--) {
331: v = aa + ai[i] + 1;
332: vj = aj + ai[i] + 1;
333: nz = ai[i+1] - ai[i] - 1;
334: sum = t[i];
335: while (nz--) sum -= x[*vj++]*(*v++);
336: x[i] = (1-omega)*x[i] + omega*sum*aidiag[i];
337: }
338: PetscLogFlops(2.0*(a->nz + m));
339: }
340: }
342: VecRestoreArray(xx,&x);
343: VecRestoreArrayRead(bb,&b);
344: return(0);
345: }