Actual source code: baij.c
1: #define PETSCMAT_DLL
3: /*
4: Defines the basic matrix operations for the BAIJ (compressed row)
5: matrix storage format.
6: */
7: #include ../src/mat/impls/baij/seq/baij.h
8: #include ../src/inline/spops.h
9: #include petscsys.h
11: #include ../src/inline/ilu.h
15: /*@
16: MatSeqBAIJInvertBlockDiagonal - Inverts the block diagonal entries.
18: Collective on Mat
20: Input Parameters:
21: . mat - the matrix
23: Level: advanced
24: @*/
25: PetscErrorCode MatSeqBAIJInvertBlockDiagonal(Mat mat)
26: {
27: PetscErrorCode ierr,(*f)(Mat);
31: if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix");
32: if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
34: PetscObjectQueryFunction((PetscObject)mat,"MatSeqBAIJInvertBlockDiagonal_C",(void (**)(void))&f);
35: if (f) {
36: (*f)(mat);
37: } else {
38: SETERRQ(PETSC_ERR_SUP,"Currently only implemented for SeqBAIJ.");
39: }
40: return(0);
41: }
46: PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A)
47: {
48: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*) A->data;
50: PetscInt *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs;
51: MatScalar *v = a->a,*odiag,*diag,*mdiag;
52: PetscReal shift = 0.0;
55: if (a->idiagvalid) return(0);
56: MatMarkDiagonal_SeqBAIJ(A);
57: diag_offset = a->diag;
58: if (!a->idiag) {
59: PetscMalloc(2*bs*bs*mbs*sizeof(PetscScalar),&a->idiag);
60: }
61: diag = a->idiag;
62: mdiag = a->idiag+bs*bs*mbs;
63: /* factor and invert each block */
64: switch (bs){
65: case 2:
66: for (i=0; i<mbs; i++) {
67: odiag = v + 4*diag_offset[i];
68: diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
69: mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3];
70: Kernel_A_gets_inverse_A_2(diag,shift);
71: diag += 4;
72: mdiag += 4;
73: }
74: break;
75: case 3:
76: for (i=0; i<mbs; i++) {
77: odiag = v + 9*diag_offset[i];
78: diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
79: diag[4] = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7];
80: diag[8] = odiag[8];
81: mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3];
82: mdiag[4] = odiag[4]; mdiag[5] = odiag[5]; mdiag[6] = odiag[6]; mdiag[7] = odiag[7];
83: mdiag[8] = odiag[8];
84: Kernel_A_gets_inverse_A_3(diag,shift);
85: diag += 9;
86: mdiag += 9;
87: }
88: break;
89: case 4:
90: for (i=0; i<mbs; i++) {
91: odiag = v + 16*diag_offset[i];
92: PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));
93: PetscMemcpy(mdiag,odiag,16*sizeof(PetscScalar));
94: Kernel_A_gets_inverse_A_4(diag,shift);
95: diag += 16;
96: mdiag += 16;
97: }
98: break;
99: case 5:
100: for (i=0; i<mbs; i++) {
101: odiag = v + 25*diag_offset[i];
102: PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));
103: PetscMemcpy(mdiag,odiag,25*sizeof(PetscScalar));
104: Kernel_A_gets_inverse_A_5(diag,shift);
105: diag += 25;
106: mdiag += 25;
107: }
108: break;
109: default:
110: SETERRQ1(PETSC_ERR_SUP,"not supported for block size %D",bs);
111: }
112: a->idiagvalid = PETSC_TRUE;
113: return(0);
114: }
119: PetscErrorCode MatPBRelax_SeqBAIJ_1(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
120: {
121: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
122: PetscScalar *x,x1,s1;
123: const PetscScalar *b;
124: const MatScalar *aa = a->a, *idiag,*mdiag,*v;
125: PetscErrorCode ierr;
126: PetscInt m = a->mbs,i,i2,nz,idx;
127: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
130: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
131: its = its*lits;
132: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
133: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
134: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
135: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
136: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
138: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
140: diag = a->diag;
141: idiag = a->idiag;
142: VecGetArray(xx,&x);
143: VecGetArray(bb,(PetscScalar**)&b);
145: if (flag & SOR_ZERO_INITIAL_GUESS) {
146: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
147: x[0] = b[0]*idiag[0];
148: i2 = 1;
149: idiag += 1;
150: for (i=1; i<m; i++) {
151: v = aa + ai[i];
152: vi = aj + ai[i];
153: nz = diag[i] - ai[i];
154: s1 = b[i2];
155: while (nz--) {
156: idx = (*vi++);
157: x1 = x[idx];
158: s1 -= v[0]*x1;
159: v += 1;
160: }
161: x[i2] = idiag[0]*s1;
162: idiag += 1;
163: i2 += 1;
164: }
165: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
166: PetscLogFlops(a->nz);
167: }
168: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
169: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
170: i2 = 0;
171: mdiag = a->idiag+a->mbs;
172: for (i=0; i<m; i++) {
173: x1 = x[i2];
174: x[i2] = mdiag[0]*x1;
175: mdiag += 1;
176: i2 += 1;
177: }
178: PetscLogFlops(m);
179: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
180: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
181: }
182: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
183: idiag = a->idiag+a->mbs - 1;
184: i2 = m - 1;
185: x1 = x[i2];
186: x[i2] = idiag[0]*x1;
187: idiag -= 1;
188: i2 -= 1;
189: for (i=m-2; i>=0; i--) {
190: v = aa + (diag[i]+1);
191: vi = aj + diag[i] + 1;
192: nz = ai[i+1] - diag[i] - 1;
193: s1 = x[i2];
194: while (nz--) {
195: idx = (*vi++);
196: x1 = x[idx];
197: s1 -= v[0]*x1;
198: v += 1;
199: }
200: x[i2] = idiag[0]*s1;
201: idiag -= 2;
202: i2 -= 1;
203: }
204: PetscLogFlops(a->nz);
205: }
206: } else {
207: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
208: }
209: VecRestoreArray(xx,&x);
210: VecRestoreArray(bb,(PetscScalar**)&b);
211: return(0);
212: }
216: PetscErrorCode MatPBRelax_SeqBAIJ_2(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
217: {
218: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
219: PetscScalar *x,x1,x2,s1,s2;
220: const PetscScalar *b;
221: const MatScalar *v,*aa = a->a, *idiag,*mdiag;
222: PetscErrorCode ierr;
223: PetscInt m = a->mbs,i,i2,nz,idx;
224: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
227: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
228: its = its*lits;
229: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
230: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
231: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
232: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
233: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
235: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
237: diag = a->diag;
238: idiag = a->idiag;
239: VecGetArray(xx,&x);
240: VecGetArray(bb,(PetscScalar**)&b);
242: if (flag & SOR_ZERO_INITIAL_GUESS) {
243: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
244: x[0] = b[0]*idiag[0] + b[1]*idiag[2];
245: x[1] = b[0]*idiag[1] + b[1]*idiag[3];
246: i2 = 2;
247: idiag += 4;
248: for (i=1; i<m; i++) {
249: v = aa + 4*ai[i];
250: vi = aj + ai[i];
251: nz = diag[i] - ai[i];
252: s1 = b[i2]; s2 = b[i2+1];
253: while (nz--) {
254: idx = 2*(*vi++);
255: x1 = x[idx]; x2 = x[1+idx];
256: s1 -= v[0]*x1 + v[2]*x2;
257: s2 -= v[1]*x1 + v[3]*x2;
258: v += 4;
259: }
260: x[i2] = idiag[0]*s1 + idiag[2]*s2;
261: x[i2+1] = idiag[1]*s1 + idiag[3]*s2;
262: idiag += 4;
263: i2 += 2;
264: }
265: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
266: PetscLogFlops(4*(a->nz));
267: }
268: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
269: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
270: i2 = 0;
271: mdiag = a->idiag+4*a->mbs;
272: for (i=0; i<m; i++) {
273: x1 = x[i2]; x2 = x[i2+1];
274: x[i2] = mdiag[0]*x1 + mdiag[2]*x2;
275: x[i2+1] = mdiag[1]*x1 + mdiag[3]*x2;
276: mdiag += 4;
277: i2 += 2;
278: }
279: PetscLogFlops(6*m);
280: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
281: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
282: }
283: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
284: idiag = a->idiag+4*a->mbs - 4;
285: i2 = 2*m - 2;
286: x1 = x[i2]; x2 = x[i2+1];
287: x[i2] = idiag[0]*x1 + idiag[2]*x2;
288: x[i2+1] = idiag[1]*x1 + idiag[3]*x2;
289: idiag -= 4;
290: i2 -= 2;
291: for (i=m-2; i>=0; i--) {
292: v = aa + 4*(diag[i]+1);
293: vi = aj + diag[i] + 1;
294: nz = ai[i+1] - diag[i] - 1;
295: s1 = x[i2]; s2 = x[i2+1];
296: while (nz--) {
297: idx = 2*(*vi++);
298: x1 = x[idx]; x2 = x[1+idx];
299: s1 -= v[0]*x1 + v[2]*x2;
300: s2 -= v[1]*x1 + v[3]*x2;
301: v += 4;
302: }
303: x[i2] = idiag[0]*s1 + idiag[2]*s2;
304: x[i2+1] = idiag[1]*s1 + idiag[3]*s2;
305: idiag -= 4;
306: i2 -= 2;
307: }
308: PetscLogFlops(4*(a->nz));
309: }
310: } else {
311: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
312: }
313: VecRestoreArray(xx,&x);
314: VecRestoreArray(bb,(PetscScalar**)&b);
315: return(0);
316: }
320: PetscErrorCode MatPBRelax_SeqBAIJ_3(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
321: {
322: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
323: PetscScalar *x,x1,x2,x3,s1,s2,s3;
324: const MatScalar *v,*aa = a->a, *idiag,*mdiag;
325: const PetscScalar *b;
326: PetscErrorCode ierr;
327: PetscInt m = a->mbs,i,i2,nz,idx;
328: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
331: its = its*lits;
332: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
333: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
334: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
335: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
336: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
337: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
339: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
341: diag = a->diag;
342: idiag = a->idiag;
343: VecGetArray(xx,&x);
344: VecGetArray(bb,(PetscScalar**)&b);
346: if (flag & SOR_ZERO_INITIAL_GUESS) {
347: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
348: x[0] = b[0]*idiag[0] + b[1]*idiag[3] + b[2]*idiag[6];
349: x[1] = b[0]*idiag[1] + b[1]*idiag[4] + b[2]*idiag[7];
350: x[2] = b[0]*idiag[2] + b[1]*idiag[5] + b[2]*idiag[8];
351: i2 = 3;
352: idiag += 9;
353: for (i=1; i<m; i++) {
354: v = aa + 9*ai[i];
355: vi = aj + ai[i];
356: nz = diag[i] - ai[i];
357: s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2];
358: while (nz--) {
359: idx = 3*(*vi++);
360: x1 = x[idx]; x2 = x[1+idx];x3 = x[2+idx];
361: s1 -= v[0]*x1 + v[3]*x2 + v[6]*x3;
362: s2 -= v[1]*x1 + v[4]*x2 + v[7]*x3;
363: s3 -= v[2]*x1 + v[5]*x2 + v[8]*x3;
364: v += 9;
365: }
366: x[i2] = idiag[0]*s1 + idiag[3]*s2 + idiag[6]*s3;
367: x[i2+1] = idiag[1]*s1 + idiag[4]*s2 + idiag[7]*s3;
368: x[i2+2] = idiag[2]*s1 + idiag[5]*s2 + idiag[8]*s3;
369: idiag += 9;
370: i2 += 3;
371: }
372: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
373: PetscLogFlops(9*(a->nz));
374: }
375: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
376: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
377: i2 = 0;
378: mdiag = a->idiag+9*a->mbs;
379: for (i=0; i<m; i++) {
380: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2];
381: x[i2] = mdiag[0]*x1 + mdiag[3]*x2 + mdiag[6]*x3;
382: x[i2+1] = mdiag[1]*x1 + mdiag[4]*x2 + mdiag[7]*x3;
383: x[i2+2] = mdiag[2]*x1 + mdiag[5]*x2 + mdiag[8]*x3;
384: mdiag += 9;
385: i2 += 3;
386: }
387: PetscLogFlops(15*m);
388: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
389: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
390: }
391: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
392: idiag = a->idiag+9*a->mbs - 9;
393: i2 = 3*m - 3;
394: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2];
395: x[i2] = idiag[0]*x1 + idiag[3]*x2 + idiag[6]*x3;
396: x[i2+1] = idiag[1]*x1 + idiag[4]*x2 + idiag[7]*x3;
397: x[i2+2] = idiag[2]*x1 + idiag[5]*x2 + idiag[8]*x3;
398: idiag -= 9;
399: i2 -= 3;
400: for (i=m-2; i>=0; i--) {
401: v = aa + 9*(diag[i]+1);
402: vi = aj + diag[i] + 1;
403: nz = ai[i+1] - diag[i] - 1;
404: s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2];
405: while (nz--) {
406: idx = 3*(*vi++);
407: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx];
408: s1 -= v[0]*x1 + v[3]*x2 + v[6]*x3;
409: s2 -= v[1]*x1 + v[4]*x2 + v[7]*x3;
410: s3 -= v[2]*x1 + v[5]*x2 + v[8]*x3;
411: v += 9;
412: }
413: x[i2] = idiag[0]*s1 + idiag[3]*s2 + idiag[6]*s3;
414: x[i2+1] = idiag[1]*s1 + idiag[4]*s2 + idiag[7]*s3;
415: x[i2+2] = idiag[2]*s1 + idiag[5]*s2 + idiag[8]*s3;
416: idiag -= 9;
417: i2 -= 3;
418: }
419: PetscLogFlops(9*(a->nz));
420: }
421: } else {
422: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
423: }
424: VecRestoreArray(xx,&x);
425: VecRestoreArray(bb,(PetscScalar**)&b);
426: return(0);
427: }
431: PetscErrorCode MatPBRelax_SeqBAIJ_4(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
432: {
433: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
434: PetscScalar *x,x1,x2,x3,x4,s1,s2,s3,s4;
435: const MatScalar *v,*aa = a->a, *idiag,*mdiag;
436: const PetscScalar *b;
437: PetscErrorCode ierr;
438: PetscInt m = a->mbs,i,i2,nz,idx;
439: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
442: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
443: its = its*lits;
444: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
445: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
446: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
447: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
448: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
450: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
452: diag = a->diag;
453: idiag = a->idiag;
454: VecGetArray(xx,&x);
455: VecGetArray(bb,(PetscScalar**)&b);
457: if (flag & SOR_ZERO_INITIAL_GUESS) {
458: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
459: x[0] = b[0]*idiag[0] + b[1]*idiag[4] + b[2]*idiag[8] + b[3]*idiag[12];
460: x[1] = b[0]*idiag[1] + b[1]*idiag[5] + b[2]*idiag[9] + b[3]*idiag[13];
461: x[2] = b[0]*idiag[2] + b[1]*idiag[6] + b[2]*idiag[10] + b[3]*idiag[14];
462: x[3] = b[0]*idiag[3] + b[1]*idiag[7] + b[2]*idiag[11] + b[3]*idiag[15];
463: i2 = 4;
464: idiag += 16;
465: for (i=1; i<m; i++) {
466: v = aa + 16*ai[i];
467: vi = aj + ai[i];
468: nz = diag[i] - ai[i];
469: s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; s4 = b[i2+3];
470: while (nz--) {
471: idx = 4*(*vi++);
472: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx];
473: s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3 + v[12]*x4;
474: s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3 + v[13]*x4;
475: s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
476: s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;
477: v += 16;
478: }
479: x[i2] = idiag[0]*s1 + idiag[4]*s2 + idiag[8]*s3 + idiag[12]*s4;
480: x[i2+1] = idiag[1]*s1 + idiag[5]*s2 + idiag[9]*s3 + idiag[13]*s4;
481: x[i2+2] = idiag[2]*s1 + idiag[6]*s2 + idiag[10]*s3 + idiag[14]*s4;
482: x[i2+3] = idiag[3]*s1 + idiag[7]*s2 + idiag[11]*s3 + idiag[15]*s4;
483: idiag += 16;
484: i2 += 4;
485: }
486: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
487: PetscLogFlops(16*(a->nz));
488: }
489: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
490: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
491: i2 = 0;
492: mdiag = a->idiag+16*a->mbs;
493: for (i=0; i<m; i++) {
494: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3];
495: x[i2] = mdiag[0]*x1 + mdiag[4]*x2 + mdiag[8]*x3 + mdiag[12]*x4;
496: x[i2+1] = mdiag[1]*x1 + mdiag[5]*x2 + mdiag[9]*x3 + mdiag[13]*x4;
497: x[i2+2] = mdiag[2]*x1 + mdiag[6]*x2 + mdiag[10]*x3 + mdiag[14]*x4;
498: x[i2+3] = mdiag[3]*x1 + mdiag[7]*x2 + mdiag[11]*x3 + mdiag[15]*x4;
499: mdiag += 16;
500: i2 += 4;
501: }
502: PetscLogFlops(28*m);
503: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
504: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
505: }
506: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
507: idiag = a->idiag+16*a->mbs - 16;
508: i2 = 4*m - 4;
509: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3];
510: x[i2] = idiag[0]*x1 + idiag[4]*x2 + idiag[8]*x3 + idiag[12]*x4;
511: x[i2+1] = idiag[1]*x1 + idiag[5]*x2 + idiag[9]*x3 + idiag[13]*x4;
512: x[i2+2] = idiag[2]*x1 + idiag[6]*x2 + idiag[10]*x3 + idiag[14]*x4;
513: x[i2+3] = idiag[3]*x1 + idiag[7]*x2 + idiag[11]*x3 + idiag[15]*x4;
514: idiag -= 16;
515: i2 -= 4;
516: for (i=m-2; i>=0; i--) {
517: v = aa + 16*(diag[i]+1);
518: vi = aj + diag[i] + 1;
519: nz = ai[i+1] - diag[i] - 1;
520: s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; s4 = x[i2+3];
521: while (nz--) {
522: idx = 4*(*vi++);
523: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx];
524: s1 -= v[0]*x1 + v[4]*x2 + v[8]*x3 + v[12]*x4;
525: s2 -= v[1]*x1 + v[5]*x2 + v[9]*x3 + v[13]*x4;
526: s3 -= v[2]*x1 + v[6]*x2 + v[10]*x3 + v[14]*x4;
527: s4 -= v[3]*x1 + v[7]*x2 + v[11]*x3 + v[15]*x4;
528: v += 16;
529: }
530: x[i2] = idiag[0]*s1 + idiag[4]*s2 + idiag[8]*s3 + idiag[12]*s4;
531: x[i2+1] = idiag[1]*s1 + idiag[5]*s2 + idiag[9]*s3 + idiag[13]*s4;
532: x[i2+2] = idiag[2]*s1 + idiag[6]*s2 + idiag[10]*s3 + idiag[14]*s4;
533: x[i2+3] = idiag[3]*s1 + idiag[7]*s2 + idiag[11]*s3 + idiag[15]*s4;
534: idiag -= 16;
535: i2 -= 4;
536: }
537: PetscLogFlops(16*(a->nz));
538: }
539: } else {
540: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
541: }
542: VecRestoreArray(xx,&x);
543: VecRestoreArray(bb,(PetscScalar**)&b);
544: return(0);
545: }
549: PetscErrorCode MatPBRelax_SeqBAIJ_5(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
550: {
551: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
552: PetscScalar *x,x1,x2,x3,x4,x5,s1,s2,s3,s4,s5;
553: const MatScalar *v,*aa = a->a, *idiag,*mdiag;
554: const PetscScalar *b;
555: PetscErrorCode ierr;
556: PetscInt m = a->mbs,i,i2,nz,idx;
557: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
560: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
561: its = its*lits;
562: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
563: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
564: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
565: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
566: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
568: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
570: diag = a->diag;
571: idiag = a->idiag;
572: VecGetArray(xx,&x);
573: VecGetArray(bb,(PetscScalar**)&b);
575: if (flag & SOR_ZERO_INITIAL_GUESS) {
576: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
577: x[0] = b[0]*idiag[0] + b[1]*idiag[5] + b[2]*idiag[10] + b[3]*idiag[15] + b[4]*idiag[20];
578: x[1] = b[0]*idiag[1] + b[1]*idiag[6] + b[2]*idiag[11] + b[3]*idiag[16] + b[4]*idiag[21];
579: x[2] = b[0]*idiag[2] + b[1]*idiag[7] + b[2]*idiag[12] + b[3]*idiag[17] + b[4]*idiag[22];
580: x[3] = b[0]*idiag[3] + b[1]*idiag[8] + b[2]*idiag[13] + b[3]*idiag[18] + b[4]*idiag[23];
581: x[4] = b[0]*idiag[4] + b[1]*idiag[9] + b[2]*idiag[14] + b[3]*idiag[19] + b[4]*idiag[24];
582: i2 = 5;
583: idiag += 25;
584: for (i=1; i<m; i++) {
585: v = aa + 25*ai[i];
586: vi = aj + ai[i];
587: nz = diag[i] - ai[i];
588: s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; s4 = b[i2+3]; s5 = b[i2+4];
589: while (nz--) {
590: idx = 5*(*vi++);
591: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx];
592: s1 -= v[0]*x1 + v[5]*x2 + v[10]*x3 + v[15]*x4 + v[20]*x5;
593: s2 -= v[1]*x1 + v[6]*x2 + v[11]*x3 + v[16]*x4 + v[21]*x5;
594: s3 -= v[2]*x1 + v[7]*x2 + v[12]*x3 + v[17]*x4 + v[22]*x5;
595: s4 -= v[3]*x1 + v[8]*x2 + v[13]*x3 + v[18]*x4 + v[23]*x5;
596: s5 -= v[4]*x1 + v[9]*x2 + v[14]*x3 + v[19]*x4 + v[24]*x5;
597: v += 25;
598: }
599: x[i2] = idiag[0]*s1 + idiag[5]*s2 + idiag[10]*s3 + idiag[15]*s4 + idiag[20]*s5;
600: x[i2+1] = idiag[1]*s1 + idiag[6]*s2 + idiag[11]*s3 + idiag[16]*s4 + idiag[21]*s5;
601: x[i2+2] = idiag[2]*s1 + idiag[7]*s2 + idiag[12]*s3 + idiag[17]*s4 + idiag[22]*s5;
602: x[i2+3] = idiag[3]*s1 + idiag[8]*s2 + idiag[13]*s3 + idiag[18]*s4 + idiag[23]*s5;
603: x[i2+4] = idiag[4]*s1 + idiag[9]*s2 + idiag[14]*s3 + idiag[19]*s4 + idiag[24]*s5;
604: idiag += 25;
605: i2 += 5;
606: }
607: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
608: PetscLogFlops(25*(a->nz));
609: }
610: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
611: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
612: i2 = 0;
613: mdiag = a->idiag+25*a->mbs;
614: for (i=0; i<m; i++) {
615: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4];
616: x[i2] = mdiag[0]*x1 + mdiag[5]*x2 + mdiag[10]*x3 + mdiag[15]*x4 + mdiag[20]*x5;
617: x[i2+1] = mdiag[1]*x1 + mdiag[6]*x2 + mdiag[11]*x3 + mdiag[16]*x4 + mdiag[21]*x5;
618: x[i2+2] = mdiag[2]*x1 + mdiag[7]*x2 + mdiag[12]*x3 + mdiag[17]*x4 + mdiag[22]*x5;
619: x[i2+3] = mdiag[3]*x1 + mdiag[8]*x2 + mdiag[13]*x3 + mdiag[18]*x4 + mdiag[23]*x5;
620: x[i2+4] = mdiag[4]*x1 + mdiag[9]*x2 + mdiag[14]*x3 + mdiag[19]*x4 + mdiag[24]*x5;
621: mdiag += 25;
622: i2 += 5;
623: }
624: PetscLogFlops(45*m);
625: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
626: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
627: }
628: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
629: idiag = a->idiag+25*a->mbs - 25;
630: i2 = 5*m - 5;
631: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4];
632: x[i2] = idiag[0]*x1 + idiag[5]*x2 + idiag[10]*x3 + idiag[15]*x4 + idiag[20]*x5;
633: x[i2+1] = idiag[1]*x1 + idiag[6]*x2 + idiag[11]*x3 + idiag[16]*x4 + idiag[21]*x5;
634: x[i2+2] = idiag[2]*x1 + idiag[7]*x2 + idiag[12]*x3 + idiag[17]*x4 + idiag[22]*x5;
635: x[i2+3] = idiag[3]*x1 + idiag[8]*x2 + idiag[13]*x3 + idiag[18]*x4 + idiag[23]*x5;
636: x[i2+4] = idiag[4]*x1 + idiag[9]*x2 + idiag[14]*x3 + idiag[19]*x4 + idiag[24]*x5;
637: idiag -= 25;
638: i2 -= 5;
639: for (i=m-2; i>=0; i--) {
640: v = aa + 25*(diag[i]+1);
641: vi = aj + diag[i] + 1;
642: nz = ai[i+1] - diag[i] - 1;
643: s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; s4 = x[i2+3]; s5 = x[i2+4];
644: while (nz--) {
645: idx = 5*(*vi++);
646: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx];
647: s1 -= v[0]*x1 + v[5]*x2 + v[10]*x3 + v[15]*x4 + v[20]*x5;
648: s2 -= v[1]*x1 + v[6]*x2 + v[11]*x3 + v[16]*x4 + v[21]*x5;
649: s3 -= v[2]*x1 + v[7]*x2 + v[12]*x3 + v[17]*x4 + v[22]*x5;
650: s4 -= v[3]*x1 + v[8]*x2 + v[13]*x3 + v[18]*x4 + v[23]*x5;
651: s5 -= v[4]*x1 + v[9]*x2 + v[14]*x3 + v[19]*x4 + v[24]*x5;
652: v += 25;
653: }
654: x[i2] = idiag[0]*s1 + idiag[5]*s2 + idiag[10]*s3 + idiag[15]*s4 + idiag[20]*s5;
655: x[i2+1] = idiag[1]*s1 + idiag[6]*s2 + idiag[11]*s3 + idiag[16]*s4 + idiag[21]*s5;
656: x[i2+2] = idiag[2]*s1 + idiag[7]*s2 + idiag[12]*s3 + idiag[17]*s4 + idiag[22]*s5;
657: x[i2+3] = idiag[3]*s1 + idiag[8]*s2 + idiag[13]*s3 + idiag[18]*s4 + idiag[23]*s5;
658: x[i2+4] = idiag[4]*s1 + idiag[9]*s2 + idiag[14]*s3 + idiag[19]*s4 + idiag[24]*s5;
659: idiag -= 25;
660: i2 -= 5;
661: }
662: PetscLogFlops(25*(a->nz));
663: }
664: } else {
665: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
666: }
667: VecRestoreArray(xx,&x);
668: VecRestoreArray(bb,(PetscScalar**)&b);
669: return(0);
670: }
674: PetscErrorCode MatPBRelax_SeqBAIJ_6(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
675: {
676: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
677: PetscScalar *x,x1,x2,x3,x4,x5,x6,s1,s2,s3,s4,s5,s6;
678: const MatScalar *v,*aa = a->a, *idiag,*mdiag;
679: const PetscScalar *b;
680: PetscErrorCode ierr;
681: PetscInt m = a->mbs,i,i2,nz,idx;
682: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
685: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
686: its = its*lits;
687: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
688: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
689: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
690: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
691: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
693: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
695: diag = a->diag;
696: idiag = a->idiag;
697: VecGetArray(xx,&x);
698: VecGetArray(bb,(PetscScalar**)&b);
700: if (flag & SOR_ZERO_INITIAL_GUESS) {
701: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
702: x[0] = b[0]*idiag[0] + b[1]*idiag[6] + b[2]*idiag[12] + b[3]*idiag[18] + b[4]*idiag[24] + b[5]*idiag[30];
703: x[1] = b[0]*idiag[1] + b[1]*idiag[7] + b[2]*idiag[13] + b[3]*idiag[19] + b[4]*idiag[25] + b[5]*idiag[31];
704: x[2] = b[0]*idiag[2] + b[1]*idiag[8] + b[2]*idiag[14] + b[3]*idiag[20] + b[4]*idiag[26] + b[5]*idiag[32];
705: x[3] = b[0]*idiag[3] + b[1]*idiag[9] + b[2]*idiag[15] + b[3]*idiag[21] + b[4]*idiag[27] + b[5]*idiag[33];
706: x[4] = b[0]*idiag[4] + b[1]*idiag[10] + b[2]*idiag[16] + b[3]*idiag[22] + b[4]*idiag[28] + b[5]*idiag[34];
707: x[5] = b[0]*idiag[5] + b[1]*idiag[11] + b[2]*idiag[17] + b[3]*idiag[23] + b[4]*idiag[29] + b[5]*idiag[35];
708: i2 = 6;
709: idiag += 36;
710: for (i=1; i<m; i++) {
711: v = aa + 36*ai[i];
712: vi = aj + ai[i];
713: nz = diag[i] - ai[i];
714: s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; s4 = b[i2+3]; s5 = b[i2+4]; s6 = b[i2+5];
715: while (nz--) {
716: idx = 6*(*vi++);
717: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx]; x6 = x[5+idx];
718: s1 -= v[0]*x1 + v[6]*x2 + v[12]*x3 + v[18]*x4 + v[24]*x5 + v[30]*x6;
719: s2 -= v[1]*x1 + v[7]*x2 + v[13]*x3 + v[19]*x4 + v[25]*x5 + v[31]*x6;
720: s3 -= v[2]*x1 + v[8]*x2 + v[14]*x3 + v[20]*x4 + v[26]*x5 + v[32]*x6;
721: s4 -= v[3]*x1 + v[9]*x2 + v[15]*x3 + v[21]*x4 + v[27]*x5 + v[33]*x6;
722: s5 -= v[4]*x1 + v[10]*x2 + v[16]*x3 + v[22]*x4 + v[28]*x5 + v[34]*x6;
723: s6 -= v[5]*x1 + v[11]*x2 + v[17]*x3 + v[23]*x4 + v[29]*x5 + v[35]*x6;
724: v += 36;
725: }
726: x[i2] = idiag[0]*s1 + idiag[6]*s2 + idiag[12]*s3 + idiag[18]*s4 + idiag[24]*s5 + idiag[30]*s6;
727: x[i2+1] = idiag[1]*s1 + idiag[7]*s2 + idiag[13]*s3 + idiag[19]*s4 + idiag[25]*s5 + idiag[31]*s6;
728: x[i2+2] = idiag[2]*s1 + idiag[8]*s2 + idiag[14]*s3 + idiag[20]*s4 + idiag[26]*s5 + idiag[32]*s6;
729: x[i2+3] = idiag[3]*s1 + idiag[9]*s2 + idiag[15]*s3 + idiag[21]*s4 + idiag[27]*s5 + idiag[33]*s6;
730: x[i2+4] = idiag[4]*s1 + idiag[10]*s2 + idiag[16]*s3 + idiag[22]*s4 + idiag[28]*s5 + idiag[34]*s6;
731: x[i2+5] = idiag[5]*s1 + idiag[11]*s2 + idiag[17]*s3 + idiag[23]*s4 + idiag[29]*s5 + idiag[35]*s6;
732: idiag += 36;
733: i2 += 6;
734: }
735: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
736: PetscLogFlops(36*(a->nz));
737: }
738: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
739: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
740: i2 = 0;
741: mdiag = a->idiag+36*a->mbs;
742: for (i=0; i<m; i++) {
743: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4]; x6 = x[i2+5];
744: x[i2] = mdiag[0]*x1 + mdiag[6]*x2 + mdiag[12]*x3 + mdiag[18]*x4 + mdiag[24]*x5 + mdiag[30]*x6;
745: x[i2+1] = mdiag[1]*x1 + mdiag[7]*x2 + mdiag[13]*x3 + mdiag[19]*x4 + mdiag[25]*x5 + mdiag[31]*x6;
746: x[i2+2] = mdiag[2]*x1 + mdiag[8]*x2 + mdiag[14]*x3 + mdiag[20]*x4 + mdiag[26]*x5 + mdiag[32]*x6;
747: x[i2+3] = mdiag[3]*x1 + mdiag[9]*x2 + mdiag[15]*x3 + mdiag[21]*x4 + mdiag[27]*x5 + mdiag[33]*x6;
748: x[i2+4] = mdiag[4]*x1 + mdiag[10]*x2 + mdiag[16]*x3 + mdiag[22]*x4 + mdiag[28]*x5 + mdiag[34]*x6;
749: x[i2+5] = mdiag[5]*x1 + mdiag[11]*x2 + mdiag[17]*x3 + mdiag[23]*x4 + mdiag[29]*x5 + mdiag[35]*x6;
750: mdiag += 36;
751: i2 += 6;
752: }
753: PetscLogFlops(60*m);
754: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
755: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
756: }
757: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
758: idiag = a->idiag+36*a->mbs - 36;
759: i2 = 6*m - 6;
760: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4]; x6 = x[i2+5];
761: x[i2] = idiag[0]*x1 + idiag[6]*x2 + idiag[12]*x3 + idiag[18]*x4 + idiag[24]*x5 + idiag[30]*x6;
762: x[i2+1] = idiag[1]*x1 + idiag[7]*x2 + idiag[13]*x3 + idiag[19]*x4 + idiag[25]*x5 + idiag[31]*x6;
763: x[i2+2] = idiag[2]*x1 + idiag[8]*x2 + idiag[14]*x3 + idiag[20]*x4 + idiag[26]*x5 + idiag[32]*x6;
764: x[i2+3] = idiag[3]*x1 + idiag[9]*x2 + idiag[15]*x3 + idiag[21]*x4 + idiag[27]*x5 + idiag[33]*x6;
765: x[i2+4] = idiag[4]*x1 + idiag[10]*x2 + idiag[16]*x3 + idiag[22]*x4 + idiag[28]*x5 + idiag[34]*x6;
766: x[i2+5] = idiag[5]*x1 + idiag[11]*x2 + idiag[17]*x3 + idiag[23]*x4 + idiag[29]*x5 + idiag[35]*x6;
767: idiag -= 36;
768: i2 -= 6;
769: for (i=m-2; i>=0; i--) {
770: v = aa + 36*(diag[i]+1);
771: vi = aj + diag[i] + 1;
772: nz = ai[i+1] - diag[i] - 1;
773: s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; s4 = x[i2+3]; s5 = x[i2+4]; s6 = x[i2+5];
774: while (nz--) {
775: idx = 6*(*vi++);
776: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx]; x6 = x[5+idx];
777: s1 -= v[0]*x1 + v[6]*x2 + v[12]*x3 + v[18]*x4 + v[24]*x5 + v[30]*x6;
778: s2 -= v[1]*x1 + v[7]*x2 + v[13]*x3 + v[19]*x4 + v[25]*x5 + v[31]*x6;
779: s3 -= v[2]*x1 + v[8]*x2 + v[14]*x3 + v[20]*x4 + v[26]*x5 + v[32]*x6;
780: s4 -= v[3]*x1 + v[9]*x2 + v[15]*x3 + v[21]*x4 + v[27]*x5 + v[33]*x6;
781: s5 -= v[4]*x1 + v[10]*x2 + v[16]*x3 + v[22]*x4 + v[28]*x5 + v[34]*x6;
782: s6 -= v[5]*x1 + v[11]*x2 + v[17]*x3 + v[23]*x4 + v[29]*x5 + v[35]*x6;
783: v += 36;
784: }
785: x[i2] = idiag[0]*s1 + idiag[6]*s2 + idiag[12]*s3 + idiag[18]*s4 + idiag[24]*s5 + idiag[30]*s6;
786: x[i2+1] = idiag[1]*s1 + idiag[7]*s2 + idiag[13]*s3 + idiag[19]*s4 + idiag[25]*s5 + idiag[31]*s6;
787: x[i2+2] = idiag[2]*s1 + idiag[8]*s2 + idiag[14]*s3 + idiag[20]*s4 + idiag[26]*s5 + idiag[32]*s6;
788: x[i2+3] = idiag[3]*s1 + idiag[9]*s2 + idiag[15]*s3 + idiag[21]*s4 + idiag[27]*s5 + idiag[33]*s6;
789: x[i2+4] = idiag[4]*s1 + idiag[10]*s2 + idiag[16]*s3 + idiag[22]*s4 + idiag[28]*s5 + idiag[34]*s6;
790: x[i2+5] = idiag[5]*s1 + idiag[11]*s2 + idiag[17]*s3 + idiag[23]*s4 + idiag[29]*s5 + idiag[35]*s6;
791: idiag -= 36;
792: i2 -= 6;
793: }
794: PetscLogFlops(36*(a->nz));
795: }
796: } else {
797: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
798: }
799: VecRestoreArray(xx,&x);
800: VecRestoreArray(bb,(PetscScalar**)&b);
801: return(0);
802: }
806: PetscErrorCode MatPBRelax_SeqBAIJ_7(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
807: {
808: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
809: PetscScalar *x,x1,x2,x3,x4,x5,x6,x7,s1,s2,s3,s4,s5,s6,s7;
810: const MatScalar *v,*aa = a->a, *idiag,*mdiag;
811: const PetscScalar *b;
812: PetscErrorCode ierr;
813: PetscInt m = a->mbs,i,i2,nz,idx;
814: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
817: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");
818: its = its*lits;
819: if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
820: if (fshift) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
821: if (omega != 1.0) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
822: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
823: if (its > 1) SETERRQ(PETSC_ERR_SUP,"Sorry, no support yet for multiple point block SOR iterations");
825: if (!a->idiagvalid){MatInvertBlockDiagonal_SeqBAIJ(A);}
827: diag = a->diag;
828: idiag = a->idiag;
829: VecGetArray(xx,&x);
830: VecGetArray(bb,(PetscScalar**)&b);
832: if (flag & SOR_ZERO_INITIAL_GUESS) {
833: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
834: x[0] = b[0]*idiag[0] + b[1]*idiag[7] + b[2]*idiag[14] + b[3]*idiag[21] + b[4]*idiag[28] + b[5]*idiag[35] + b[6]*idiag[42];
835: x[1] = b[0]*idiag[1] + b[1]*idiag[8] + b[2]*idiag[15] + b[3]*idiag[22] + b[4]*idiag[29] + b[5]*idiag[36] + b[6]*idiag[43];
836: x[2] = b[0]*idiag[2] + b[1]*idiag[9] + b[2]*idiag[16] + b[3]*idiag[23] + b[4]*idiag[30] + b[5]*idiag[37] + b[6]*idiag[44];
837: x[3] = b[0]*idiag[3] + b[1]*idiag[10] + b[2]*idiag[17] + b[3]*idiag[24] + b[4]*idiag[31] + b[5]*idiag[38] + b[6]*idiag[45];
838: x[4] = b[0]*idiag[4] + b[1]*idiag[11] + b[2]*idiag[18] + b[3]*idiag[25] + b[4]*idiag[32] + b[5]*idiag[39] + b[6]*idiag[46];
839: x[5] = b[0]*idiag[5] + b[1]*idiag[12] + b[2]*idiag[19] + b[3]*idiag[26] + b[4]*idiag[33] + b[5]*idiag[40] + b[6]*idiag[47];
840: x[6] = b[0]*idiag[6] + b[1]*idiag[13] + b[2]*idiag[20] + b[3]*idiag[27] + b[4]*idiag[34] + b[5]*idiag[41] + b[6]*idiag[48];
841: i2 = 7;
842: idiag += 49;
843: for (i=1; i<m; i++) {
844: v = aa + 49*ai[i];
845: vi = aj + ai[i];
846: nz = diag[i] - ai[i];
847: s1 = b[i2]; s2 = b[i2+1]; s3 = b[i2+2]; s4 = b[i2+3]; s5 = b[i2+4]; s6 = b[i2+5]; s7 = b[i2+6];
848: while (nz--) {
849: idx = 7*(*vi++);
850: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx]; x6 = x[5+idx]; x7 = x[6+idx];
851: s1 -= v[0]*x1 + v[7]*x2 + v[14]*x3 + v[21]*x4 + v[28]*x5 + v[35]*x6 + v[42]*x7;
852: s2 -= v[1]*x1 + v[8]*x2 + v[15]*x3 + v[22]*x4 + v[29]*x5 + v[36]*x6 + v[43]*x7;
853: s3 -= v[2]*x1 + v[9]*x2 + v[16]*x3 + v[23]*x4 + v[30]*x5 + v[37]*x6 + v[44]*x7;
854: s4 -= v[3]*x1 + v[10]*x2 + v[17]*x3 + v[24]*x4 + v[31]*x5 + v[38]*x6 + v[45]*x7;
855: s5 -= v[4]*x1 + v[11]*x2 + v[18]*x3 + v[25]*x4 + v[32]*x5 + v[39]*x6 + v[46]*x7;
856: s6 -= v[5]*x1 + v[12]*x2 + v[19]*x3 + v[26]*x4 + v[33]*x5 + v[40]*x6 + v[47]*x7;
857: s7 -= v[6]*x1 + v[13]*x2 + v[20]*x3 + v[27]*x4 + v[34]*x5 + v[41]*x6 + v[48]*x7;
858: v += 49;
859: }
860: x[i2] = idiag[0]*s1 + idiag[7]*s2 + idiag[14]*s3 + idiag[21]*s4 + idiag[28]*s5 + idiag[35]*s6 + idiag[42]*s7;
861: x[i2+1] = idiag[1]*s1 + idiag[8]*s2 + idiag[15]*s3 + idiag[22]*s4 + idiag[29]*s5 + idiag[36]*s6 + idiag[43]*s7;
862: x[i2+2] = idiag[2]*s1 + idiag[9]*s2 + idiag[16]*s3 + idiag[23]*s4 + idiag[30]*s5 + idiag[37]*s6 + idiag[44]*s7;
863: x[i2+3] = idiag[3]*s1 + idiag[10]*s2 + idiag[17]*s3 + idiag[24]*s4 + idiag[31]*s5 + idiag[38]*s6 + idiag[45]*s7;
864: x[i2+4] = idiag[4]*s1 + idiag[11]*s2 + idiag[18]*s3 + idiag[25]*s4 + idiag[32]*s5 + idiag[39]*s6 + idiag[46]*s7;
865: x[i2+5] = idiag[5]*s1 + idiag[12]*s2 + idiag[19]*s3 + idiag[26]*s4 + idiag[33]*s5 + idiag[40]*s6 + idiag[47]*s7;
866: x[i2+6] = idiag[6]*s1 + idiag[13]*s2 + idiag[20]*s3 + idiag[27]*s4 + idiag[34]*s5 + idiag[41]*s6 + idiag[48]*s7;
867: idiag += 49;
868: i2 += 7;
869: }
870: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
871: PetscLogFlops(49*(a->nz));
872: }
873: if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) &&
874: (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) {
875: i2 = 0;
876: mdiag = a->idiag+49*a->mbs;
877: for (i=0; i<m; i++) {
878: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4]; x6 = x[i2+5]; x7 = x[i2+6];
879: x[i2] = mdiag[0]*x1 + mdiag[7]*x2 + mdiag[14]*x3 + mdiag[21]*x4 + mdiag[28]*x5 + mdiag[35]*x6 + mdiag[35]*x7;
880: x[i2+1] = mdiag[1]*x1 + mdiag[8]*x2 + mdiag[15]*x3 + mdiag[22]*x4 + mdiag[29]*x5 + mdiag[36]*x6 + mdiag[36]*x7;
881: x[i2+2] = mdiag[2]*x1 + mdiag[9]*x2 + mdiag[16]*x3 + mdiag[23]*x4 + mdiag[30]*x5 + mdiag[37]*x6 + mdiag[37]*x7;
882: x[i2+3] = mdiag[3]*x1 + mdiag[10]*x2 + mdiag[17]*x3 + mdiag[24]*x4 + mdiag[31]*x5 + mdiag[38]*x6 + mdiag[38]*x7;
883: x[i2+4] = mdiag[4]*x1 + mdiag[11]*x2 + mdiag[18]*x3 + mdiag[25]*x4 + mdiag[32]*x5 + mdiag[39]*x6 + mdiag[39]*x7;
884: x[i2+5] = mdiag[5]*x1 + mdiag[12]*x2 + mdiag[19]*x3 + mdiag[26]*x4 + mdiag[33]*x5 + mdiag[40]*x6 + mdiag[40]*x7;
885: x[i2+6] = mdiag[6]*x1 + mdiag[13]*x2 + mdiag[20]*x3 + mdiag[27]*x4 + mdiag[34]*x5 + mdiag[41]*x6 + mdiag[41]*x7;
886: mdiag += 36;
887: i2 += 6;
888: }
889: PetscLogFlops(93*m);
890: } else if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
891: PetscMemcpy(x,b,A->rmap->N*sizeof(PetscScalar));
892: }
893: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
894: idiag = a->idiag+49*a->mbs - 49;
895: i2 = 7*m - 7;
896: x1 = x[i2]; x2 = x[i2+1]; x3 = x[i2+2]; x4 = x[i2+3]; x5 = x[i2+4]; x6 = x[i2+5]; x7 = x[i2+6];
897: x[i2] = idiag[0]*x1 + idiag[7]*x2 + idiag[14]*x3 + idiag[21]*x4 + idiag[28]*x5 + idiag[35]*x6 + idiag[42]*x7;
898: x[i2+1] = idiag[1]*x1 + idiag[8]*x2 + idiag[15]*x3 + idiag[22]*x4 + idiag[29]*x5 + idiag[36]*x6 + idiag[43]*x7;
899: x[i2+2] = idiag[2]*x1 + idiag[9]*x2 + idiag[16]*x3 + idiag[23]*x4 + idiag[30]*x5 + idiag[37]*x6 + idiag[44]*x7;
900: x[i2+3] = idiag[3]*x1 + idiag[10]*x2 + idiag[17]*x3 + idiag[24]*x4 + idiag[31]*x5 + idiag[38]*x6 + idiag[45]*x7;
901: x[i2+4] = idiag[4]*x1 + idiag[11]*x2 + idiag[18]*x3 + idiag[25]*x4 + idiag[32]*x5 + idiag[39]*x6 + idiag[46]*x7;
902: x[i2+5] = idiag[5]*x1 + idiag[12]*x2 + idiag[19]*x3 + idiag[26]*x4 + idiag[33]*x5 + idiag[40]*x6 + idiag[47]*x7;
903: x[i2+6] = idiag[6]*x1 + idiag[13]*x2 + idiag[20]*x3 + idiag[27]*x4 + idiag[34]*x5 + idiag[41]*x6 + idiag[48]*x7;
904: idiag -= 49;
905: i2 -= 7;
906: for (i=m-2; i>=0; i--) {
907: v = aa + 49*(diag[i]+1);
908: vi = aj + diag[i] + 1;
909: nz = ai[i+1] - diag[i] - 1;
910: s1 = x[i2]; s2 = x[i2+1]; s3 = x[i2+2]; s4 = x[i2+3]; s5 = x[i2+4]; s6 = x[i2+5]; s7 = x[i2+6];
911: while (nz--) {
912: idx = 7*(*vi++);
913: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx]; x6 = x[5+idx]; x7 = x[6+idx];
914: s1 -= v[0]*x1 + v[7]*x2 + v[14]*x3 + v[21]*x4 + v[28]*x5 + v[35]*x6 + v[42]*x7;
915: s2 -= v[1]*x1 + v[8]*x2 + v[15]*x3 + v[22]*x4 + v[29]*x5 + v[36]*x6 + v[43]*x7;
916: s3 -= v[2]*x1 + v[9]*x2 + v[16]*x3 + v[23]*x4 + v[30]*x5 + v[37]*x6 + v[44]*x7;
917: s4 -= v[3]*x1 + v[10]*x2 + v[17]*x3 + v[24]*x4 + v[31]*x5 + v[38]*x6 + v[45]*x7;
918: s5 -= v[4]*x1 + v[11]*x2 + v[18]*x3 + v[25]*x4 + v[32]*x5 + v[39]*x6 + v[46]*x7;
919: s6 -= v[5]*x1 + v[12]*x2 + v[19]*x3 + v[26]*x4 + v[33]*x5 + v[40]*x6 + v[47]*x7;
920: s7 -= v[6]*x1 + v[13]*x2 + v[20]*x3 + v[27]*x4 + v[34]*x5 + v[41]*x6 + v[48]*x7;
921: v += 49;
922: }
923: x[i2] = idiag[0]*s1 + idiag[7]*s2 + idiag[14]*s3 + idiag[21]*s4 + idiag[28]*s5 + idiag[35]*s6 + idiag[42]*s7;
924: x[i2+1] = idiag[1]*s1 + idiag[8]*s2 + idiag[15]*s3 + idiag[22]*s4 + idiag[29]*s5 + idiag[36]*s6 + idiag[43]*s7;
925: x[i2+2] = idiag[2]*s1 + idiag[9]*s2 + idiag[16]*s3 + idiag[23]*s4 + idiag[30]*s5 + idiag[37]*s6 + idiag[44]*s7;
926: x[i2+3] = idiag[3]*s1 + idiag[10]*s2 + idiag[17]*s3 + idiag[24]*s4 + idiag[31]*s5 + idiag[38]*s6 + idiag[45]*s7;
927: x[i2+4] = idiag[4]*s1 + idiag[11]*s2 + idiag[18]*s3 + idiag[25]*s4 + idiag[32]*s5 + idiag[39]*s6 + idiag[46]*s7;
928: x[i2+5] = idiag[5]*s1 + idiag[12]*s2 + idiag[19]*s3 + idiag[26]*s4 + idiag[33]*s5 + idiag[40]*s6 + idiag[47]*s7;
929: x[i2+6] = idiag[6]*s1 + idiag[13]*s2 + idiag[20]*s3 + idiag[27]*s4 + idiag[34]*s5 + idiag[41]*s6 + idiag[48]*s7;
930: idiag -= 49;
931: i2 -= 7;
932: }
933: PetscLogFlops(49*(a->nz));
934: }
935: } else {
936: SETERRQ(PETSC_ERR_SUP,"Only supports point block SOR with zero initial guess");
937: }
938: VecRestoreArray(xx,&x);
939: VecRestoreArray(bb,(PetscScalar**)&b);
940: return(0);
941: }
943: /*
944: Special version for direct calls from Fortran (Used in PETSc-fun3d)
945: */
946: #if defined(PETSC_HAVE_FORTRAN_CAPS)
947: #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4
948: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
949: #define matsetvaluesblocked4_ matsetvaluesblocked4
950: #endif
955: void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[])
956: {
957: Mat A = *AA;
958: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
959: PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn;
960: PetscInt *ai=a->i,*ailen=a->ilen;
961: PetscInt *aj=a->j,stepval,lastcol = -1;
962: const PetscScalar *value = v;
963: MatScalar *ap,*aa = a->a,*bap;
966: if (A->rmap->bs != 4) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4");
967: stepval = (n-1)*4;
968: for (k=0; k<m; k++) { /* loop over added rows */
969: row = im[k];
970: rp = aj + ai[row];
971: ap = aa + 16*ai[row];
972: nrow = ailen[row];
973: low = 0;
974: high = nrow;
975: for (l=0; l<n; l++) { /* loop over added columns */
976: col = in[l];
977: if (col <= lastcol) low = 0; else high = nrow;
978: lastcol = col;
979: value = v + k*(stepval+4 + l)*4;
980: while (high-low > 7) {
981: t = (low+high)/2;
982: if (rp[t] > col) high = t;
983: else low = t;
984: }
985: for (i=low; i<high; i++) {
986: if (rp[i] > col) break;
987: if (rp[i] == col) {
988: bap = ap + 16*i;
989: for (ii=0; ii<4; ii++,value+=stepval) {
990: for (jj=ii; jj<16; jj+=4) {
991: bap[jj] += *value++;
992: }
993: }
994: goto noinsert2;
995: }
996: }
997: N = nrow++ - 1;
998: high++; /* added new column index thus must search to one higher than before */
999: /* shift up all the later entries in this row */
1000: for (ii=N; ii>=i; ii--) {
1001: rp[ii+1] = rp[ii];
1002: PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
1003: }
1004: if (N >= i) {
1005: PetscMemzero(ap+16*i,16*sizeof(MatScalar));
1006: }
1007: rp[i] = col;
1008: bap = ap + 16*i;
1009: for (ii=0; ii<4; ii++,value+=stepval) {
1010: for (jj=ii; jj<16; jj+=4) {
1011: bap[jj] = *value++;
1012: }
1013: }
1014: noinsert2:;
1015: low = i;
1016: }
1017: ailen[row] = nrow;
1018: }
1019: PetscFunctionReturnVoid();
1020: }
1023: #if defined(PETSC_HAVE_FORTRAN_CAPS)
1024: #define matsetvalues4_ MATSETVALUES4
1025: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
1026: #define matsetvalues4_ matsetvalues4
1027: #endif
1032: void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v)
1033: {
1034: Mat A = *AA;
1035: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1036: PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm;
1037: PetscInt *ai=a->i,*ailen=a->ilen;
1038: PetscInt *aj=a->j,brow,bcol;
1039: PetscInt ridx,cidx,lastcol = -1;
1040: MatScalar *ap,value,*aa=a->a,*bap;
1041:
1043: for (k=0; k<m; k++) { /* loop over added rows */
1044: row = im[k]; brow = row/4;
1045: rp = aj + ai[brow];
1046: ap = aa + 16*ai[brow];
1047: nrow = ailen[brow];
1048: low = 0;
1049: high = nrow;
1050: for (l=0; l<n; l++) { /* loop over added columns */
1051: col = in[l]; bcol = col/4;
1052: ridx = row % 4; cidx = col % 4;
1053: value = v[l + k*n];
1054: if (col <= lastcol) low = 0; else high = nrow;
1055: lastcol = col;
1056: while (high-low > 7) {
1057: t = (low+high)/2;
1058: if (rp[t] > bcol) high = t;
1059: else low = t;
1060: }
1061: for (i=low; i<high; i++) {
1062: if (rp[i] > bcol) break;
1063: if (rp[i] == bcol) {
1064: bap = ap + 16*i + 4*cidx + ridx;
1065: *bap += value;
1066: goto noinsert1;
1067: }
1068: }
1069: N = nrow++ - 1;
1070: high++; /* added new column thus must search to one higher than before */
1071: /* shift up all the later entries in this row */
1072: for (ii=N; ii>=i; ii--) {
1073: rp[ii+1] = rp[ii];
1074: PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
1075: }
1076: if (N>=i) {
1077: PetscMemzero(ap+16*i,16*sizeof(MatScalar));
1078: }
1079: rp[i] = bcol;
1080: ap[16*i + 4*cidx + ridx] = value;
1081: noinsert1:;
1082: low = i;
1083: }
1084: ailen[brow] = nrow;
1085: }
1086: PetscFunctionReturnVoid();
1087: }
1090: /*
1091: Checks for missing diagonals
1092: */
1095: PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscTruth *missing,PetscInt *d)
1096: {
1097: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1099: PetscInt *diag,*jj = a->j,i;
1102: MatMarkDiagonal_SeqBAIJ(A);
1103: *missing = PETSC_FALSE;
1104: diag = a->diag;
1105: for (i=0; i<a->mbs; i++) {
1106: if (jj[diag[i]] != i) {
1107: *missing = PETSC_TRUE;
1108: if (d) *d = i;
1109: }
1110: }
1111: return(0);
1112: }
1116: PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A)
1117: {
1118: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1120: PetscInt i,j,m = a->mbs;
1123: if (!a->diag) {
1124: PetscMalloc(m*sizeof(PetscInt),&a->diag);
1125: }
1126: for (i=0; i<m; i++) {
1127: a->diag[i] = a->i[i+1];
1128: for (j=a->i[i]; j<a->i[i+1]; j++) {
1129: if (a->j[j] == i) {
1130: a->diag[i] = j;
1131: break;
1132: }
1133: }
1134: }
1135: return(0);
1136: }
1139: EXTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt,PetscInt*,PetscInt*,PetscInt,PetscInt,PetscInt**,PetscInt**);
1143: static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth blockcompressed,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done)
1144: {
1145: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1147: PetscInt i,j,n = a->mbs,nz = a->i[n],bs = A->rmap->bs,nbs = 1,k,l,cnt;
1148: PetscInt *tia, *tja;
1151: *nn = n;
1152: if (!ia) return(0);
1153: if (symmetric) {
1154: MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,0,0,&tia,&tja);
1155: } else {
1156: tia = a->i; tja = a->j;
1157: }
1158:
1159: if (!blockcompressed && bs > 1) {
1160: (*nn) *= bs;
1161: nbs = bs;
1162: /* malloc & create the natural set of indices */
1163: PetscMalloc((n+1)*bs*sizeof(PetscInt),ia);
1164: if (n) {
1165: (*ia)[0] = 0;
1166: for (j=1; j<bs; j++) {
1167: (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1];
1168: }
1169: }
1171: for (i=1; i<n; i++) {
1172: (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1];
1173: for (j=1; j<bs; j++) {
1174: (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1];
1175: }
1176: }
1177: if (n) {
1178: (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1];
1179: }
1181: if (ja) {
1182: PetscMalloc(nz*bs*bs*sizeof(PetscInt),ja);
1183: cnt = 0;
1184: for (i=0; i<n; i++) {
1185: for (j=0; j<bs; j++) {
1186: for (k=tia[i]; k<tia[i+1]; k++) {
1187: for (l=0; l<bs; l++) {
1188: (*ja)[cnt++] = bs*tja[k] + l;
1189: }
1190: }
1191: }
1192: }
1193: }
1195: n *= bs;
1196: nz *= bs*bs;
1197: if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
1198: PetscFree(tia);
1199: PetscFree(tja);
1200: }
1201: } else {
1202: *ia = tia;
1203: if (ja) *ja = tja;
1204: }
1205: if (oshift == 1) {
1206: for (i=0; i<n+nbs; i++) (*ia)[i]++;
1207: if (ja) for (i=0; i<nz; i++) (*ja)[i]++;
1208: }
1209: return(0);
1210: }
1214: static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth blockcompressed,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done)
1215: {
1216: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1218: PetscInt i,n = a->mbs,nz = a->i[n];
1221: if (!ia) return(0);
1222: if (!blockcompressed && A->rmap->bs > 1) {
1223: PetscFree(*ia);
1224: if (ja) {PetscFree(*ja);}
1225: } else if (symmetric) {
1226: PetscFree(*ia);
1227: if (ja) {PetscFree(*ja);}
1228: } else if (oshift == 1) { /* blockcompressed */
1229: for (i=0; i<n+1; i++) a->i[i]--;
1230: if (ja) {for (i=0; i<nz; i++) a->j[i]--;}
1231: }
1232: return(0);
1233: }
1237: PetscErrorCode MatDestroy_SeqBAIJ(Mat A)
1238: {
1239: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1243: #if defined(PETSC_USE_LOG)
1244: PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz);
1245: #endif
1246: MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
1247: if (a->row) {
1248: ISDestroy(a->row);
1249: }
1250: if (a->col) {
1251: ISDestroy(a->col);
1252: }
1253: PetscFree(a->diag);
1254: PetscFree(a->idiag);
1255: PetscFree2(a->imax,a->ilen);
1256: PetscFree(a->solve_work);
1257: PetscFree(a->mult_work);
1258: if (a->icol) {ISDestroy(a->icol);}
1259: PetscFree(a->saved_values);
1260: PetscFree(a->xtoy);
1261: if (a->compressedrow.use){PetscFree(a->compressedrow.i);}
1263: if (a->sbaijMat) {MatDestroy(a->sbaijMat);}
1264: PetscFree(a);
1266: PetscObjectChangeTypeName((PetscObject)A,0);
1267: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJInvertBlockDiagonal_C","",PETSC_NULL);
1268: PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C","",PETSC_NULL);
1269: PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C","",PETSC_NULL);
1270: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C","",PETSC_NULL);
1271: PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C","",PETSC_NULL);
1272: PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C","",PETSC_NULL);
1273: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C","",PETSC_NULL);
1274: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C","",PETSC_NULL);
1275: return(0);
1276: }
1280: PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscTruth flg)
1281: {
1282: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1286: switch (op) {
1287: case MAT_ROW_ORIENTED:
1288: a->roworiented = flg;
1289: break;
1290: case MAT_KEEP_ZEROED_ROWS:
1291: a->keepzeroedrows = flg;
1292: break;
1293: case MAT_NEW_NONZERO_LOCATIONS:
1294: a->nonew = (flg ? 0 : 1);
1295: break;
1296: case MAT_NEW_NONZERO_LOCATION_ERR:
1297: a->nonew = (flg ? -1 : 0);
1298: break;
1299: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1300: a->nonew = (flg ? -2 : 0);
1301: break;
1302: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1303: a->nounused = (flg ? -1 : 0);
1304: break;
1305: case MAT_NEW_DIAGONALS:
1306: case MAT_IGNORE_OFF_PROC_ENTRIES:
1307: case MAT_USE_HASH_TABLE:
1308: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1309: break;
1310: case MAT_SYMMETRIC:
1311: case MAT_STRUCTURALLY_SYMMETRIC:
1312: case MAT_HERMITIAN:
1313: case MAT_SYMMETRY_ETERNAL:
1314: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1315: break;
1316: default:
1317: SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op);
1318: }
1319: return(0);
1320: }
1324: PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1325: {
1326: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1328: PetscInt itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*idx_i,bs2;
1329: MatScalar *aa,*aa_i;
1330: PetscScalar *v_i;
1333: bs = A->rmap->bs;
1334: ai = a->i;
1335: aj = a->j;
1336: aa = a->a;
1337: bs2 = a->bs2;
1338:
1339: if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row);
1340:
1341: bn = row/bs; /* Block number */
1342: bp = row % bs; /* Block Position */
1343: M = ai[bn+1] - ai[bn];
1344: *nz = bs*M;
1345:
1346: if (v) {
1347: *v = 0;
1348: if (*nz) {
1349: PetscMalloc((*nz)*sizeof(PetscScalar),v);
1350: for (i=0; i<M; i++) { /* for each block in the block row */
1351: v_i = *v + i*bs;
1352: aa_i = aa + bs2*(ai[bn] + i);
1353: for (j=bp,k=0; j<bs2; j+=bs,k++) {v_i[k] = aa_i[j];}
1354: }
1355: }
1356: }
1358: if (idx) {
1359: *idx = 0;
1360: if (*nz) {
1361: PetscMalloc((*nz)*sizeof(PetscInt),idx);
1362: for (i=0; i<M; i++) { /* for each block in the block row */
1363: idx_i = *idx + i*bs;
1364: itmp = bs*aj[ai[bn] + i];
1365: for (j=0; j<bs; j++) {idx_i[j] = itmp++;}
1366: }
1367: }
1368: }
1369: return(0);
1370: }
1374: PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1375: {
1379: if (idx) {PetscFree(*idx);}
1380: if (v) {PetscFree(*v);}
1381: return(0);
1382: }
1386: PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B)
1387: {
1388: Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data;
1389: Mat C;
1391: PetscInt i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col;
1392: PetscInt *rows,*cols,bs2=a->bs2;
1393: MatScalar *array;
1396: if (reuse == MAT_REUSE_MATRIX && A == *B && mbs != nbs) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1397: if (reuse == MAT_INITIAL_MATRIX || A == *B) {
1398: PetscMalloc((1+nbs)*sizeof(PetscInt),&col);
1399: PetscMemzero(col,(1+nbs)*sizeof(PetscInt));
1401: for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1;
1402: MatCreate(((PetscObject)A)->comm,&C);
1403: MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);
1404: MatSetType(C,((PetscObject)A)->type_name);
1405: MatSeqBAIJSetPreallocation_SeqBAIJ(C,bs,PETSC_NULL,col);
1406: PetscFree(col);
1407: } else {
1408: C = *B;
1409: }
1411: array = a->a;
1412: PetscMalloc(2*bs*sizeof(PetscInt),&rows);
1413: cols = rows + bs;
1414: for (i=0; i<mbs; i++) {
1415: cols[0] = i*bs;
1416: for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1;
1417: len = ai[i+1] - ai[i];
1418: for (j=0; j<len; j++) {
1419: rows[0] = (*aj++)*bs;
1420: for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1;
1421: MatSetValues(C,bs,rows,bs,cols,array,INSERT_VALUES);
1422: array += bs2;
1423: }
1424: }
1425: PetscFree(rows);
1426:
1427: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
1428: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
1429:
1430: if (reuse == MAT_INITIAL_MATRIX || *B != A) {
1431: *B = C;
1432: } else {
1433: MatHeaderCopy(A,C);
1434: }
1435: return(0);
1436: }
1440: static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer)
1441: {
1442: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1444: PetscInt i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2;
1445: int fd;
1446: PetscScalar *aa;
1447: FILE *file;
1450: PetscViewerBinaryGetDescriptor(viewer,&fd);
1451: PetscMalloc((4+A->rmap->N)*sizeof(PetscInt),&col_lens);
1452: col_lens[0] = MAT_FILE_COOKIE;
1454: col_lens[1] = A->rmap->N;
1455: col_lens[2] = A->cmap->n;
1456: col_lens[3] = a->nz*bs2;
1458: /* store lengths of each row and write (including header) to file */
1459: count = 0;
1460: for (i=0; i<a->mbs; i++) {
1461: for (j=0; j<bs; j++) {
1462: col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]);
1463: }
1464: }
1465: PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);
1466: PetscFree(col_lens);
1468: /* store column indices (zero start index) */
1469: PetscMalloc((a->nz+1)*bs2*sizeof(PetscInt),&jj);
1470: count = 0;
1471: for (i=0; i<a->mbs; i++) {
1472: for (j=0; j<bs; j++) {
1473: for (k=a->i[i]; k<a->i[i+1]; k++) {
1474: for (l=0; l<bs; l++) {
1475: jj[count++] = bs*a->j[k] + l;
1476: }
1477: }
1478: }
1479: }
1480: PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);
1481: PetscFree(jj);
1483: /* store nonzero values */
1484: PetscMalloc((a->nz+1)*bs2*sizeof(PetscScalar),&aa);
1485: count = 0;
1486: for (i=0; i<a->mbs; i++) {
1487: for (j=0; j<bs; j++) {
1488: for (k=a->i[i]; k<a->i[i+1]; k++) {
1489: for (l=0; l<bs; l++) {
1490: aa[count++] = a->a[bs2*k + l*bs + j];
1491: }
1492: }
1493: }
1494: }
1495: PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);
1496: PetscFree(aa);
1498: PetscViewerBinaryGetInfoPointer(viewer,&file);
1499: if (file) {
1500: fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs);
1501: }
1502: return(0);
1503: }
1507: static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer)
1508: {
1509: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1510: PetscErrorCode ierr;
1511: PetscInt i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
1512: PetscViewerFormat format;
1515: PetscViewerGetFormat(viewer,&format);
1516: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1517: PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);
1518: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
1519: Mat aij;
1520: MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
1521: MatView(aij,viewer);
1522: MatDestroy(aij);
1523: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1524: return(0);
1525: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
1526: PetscViewerASCIIUseTabs(viewer,PETSC_NO);
1527: for (i=0; i<a->mbs; i++) {
1528: for (j=0; j<bs; j++) {
1529: PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
1530: for (k=a->i[i]; k<a->i[i+1]; k++) {
1531: for (l=0; l<bs; l++) {
1532: #if defined(PETSC_USE_COMPLEX)
1533: if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1534: PetscViewerASCIIPrintf(viewer," (%D, %G + %Gi) ",bs*a->j[k]+l,
1535: PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1536: } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1537: PetscViewerASCIIPrintf(viewer," (%D, %G - %Gi) ",bs*a->j[k]+l,
1538: PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1539: } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1540: PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));
1541: }
1542: #else
1543: if (a->a[bs2*k + l*bs + j] != 0.0) {
1544: PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);
1545: }
1546: #endif
1547: }
1548: }
1549: PetscViewerASCIIPrintf(viewer,"\n");
1550: }
1551: }
1552: PetscViewerASCIIUseTabs(viewer,PETSC_YES);
1553: } else {
1554: PetscViewerASCIIUseTabs(viewer,PETSC_NO);
1555: for (i=0; i<a->mbs; i++) {
1556: for (j=0; j<bs; j++) {
1557: PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
1558: for (k=a->i[i]; k<a->i[i+1]; k++) {
1559: for (l=0; l<bs; l++) {
1560: #if defined(PETSC_USE_COMPLEX)
1561: if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
1562: PetscViewerASCIIPrintf(viewer," (%D, %G + %G i) ",bs*a->j[k]+l,
1563: PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1564: } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
1565: PetscViewerASCIIPrintf(viewer," (%D, %G - %G i) ",bs*a->j[k]+l,
1566: PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1567: } else {
1568: PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));
1569: }
1570: #else
1571: PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);
1572: #endif
1573: }
1574: }
1575: PetscViewerASCIIPrintf(viewer,"\n");
1576: }
1577: }
1578: PetscViewerASCIIUseTabs(viewer,PETSC_YES);
1579: }
1580: PetscViewerFlush(viewer);
1581: return(0);
1582: }
1586: static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
1587: {
1588: Mat A = (Mat) Aa;
1589: Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data;
1591: PetscInt row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
1592: PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r;
1593: MatScalar *aa;
1594: PetscViewer viewer;
1598: /* still need to add support for contour plot of nonzeros; see MatView_SeqAIJ_Draw_Zoom()*/
1599: PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
1601: PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);
1603: /* loop over matrix elements drawing boxes */
1604: color = PETSC_DRAW_BLUE;
1605: for (i=0,row=0; i<mbs; i++,row+=bs) {
1606: for (j=a->i[i]; j<a->i[i+1]; j++) {
1607: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1608: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1609: aa = a->a + j*bs2;
1610: for (k=0; k<bs; k++) {
1611: for (l=0; l<bs; l++) {
1612: if (PetscRealPart(*aa++) >= 0.) continue;
1613: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1614: }
1615: }
1616: }
1617: }
1618: color = PETSC_DRAW_CYAN;
1619: for (i=0,row=0; i<mbs; i++,row+=bs) {
1620: for (j=a->i[i]; j<a->i[i+1]; j++) {
1621: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1622: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1623: aa = a->a + j*bs2;
1624: for (k=0; k<bs; k++) {
1625: for (l=0; l<bs; l++) {
1626: if (PetscRealPart(*aa++) != 0.) continue;
1627: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1628: }
1629: }
1630: }
1631: }
1633: color = PETSC_DRAW_RED;
1634: for (i=0,row=0; i<mbs; i++,row+=bs) {
1635: for (j=a->i[i]; j<a->i[i+1]; j++) {
1636: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1637: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1638: aa = a->a + j*bs2;
1639: for (k=0; k<bs; k++) {
1640: for (l=0; l<bs; l++) {
1641: if (PetscRealPart(*aa++) <= 0.) continue;
1642: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1643: }
1644: }
1645: }
1646: }
1647: return(0);
1648: }
1652: static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer)
1653: {
1655: PetscReal xl,yl,xr,yr,w,h;
1656: PetscDraw draw;
1657: PetscTruth isnull;
1661: PetscViewerDrawGetDraw(viewer,0,&draw);
1662: PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
1664: PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
1665: xr = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
1666: xr += w; yr += h; xl = -w; yl = -h;
1667: PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
1668: PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);
1669: PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);
1670: return(0);
1671: }
1675: PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer)
1676: {
1678: PetscTruth iascii,isbinary,isdraw;
1681: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
1682: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
1683: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
1684: if (iascii){
1685: MatView_SeqBAIJ_ASCII(A,viewer);
1686: } else if (isbinary) {
1687: MatView_SeqBAIJ_Binary(A,viewer);
1688: } else if (isdraw) {
1689: MatView_SeqBAIJ_Draw(A,viewer);
1690: } else {
1691: Mat B;
1692: MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
1693: MatView(B,viewer);
1694: MatDestroy(B);
1695: }
1696: return(0);
1697: }
1702: PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
1703: {
1704: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1705: PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
1706: PetscInt *ai = a->i,*ailen = a->ilen;
1707: PetscInt brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
1708: MatScalar *ap,*aa = a->a;
1711: for (k=0; k<m; k++) { /* loop over rows */
1712: row = im[k]; brow = row/bs;
1713: if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
1714: if (row >= A->rmap->N) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row);
1715: rp = aj + ai[brow] ; ap = aa + bs2*ai[brow] ;
1716: nrow = ailen[brow];
1717: for (l=0; l<n; l++) { /* loop over columns */
1718: if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
1719: if (in[l] >= A->cmap->n) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]);
1720: col = in[l] ;
1721: bcol = col/bs;
1722: cidx = col%bs;
1723: ridx = row%bs;
1724: high = nrow;
1725: low = 0; /* assume unsorted */
1726: while (high-low > 5) {
1727: t = (low+high)/2;
1728: if (rp[t] > bcol) high = t;
1729: else low = t;
1730: }
1731: for (i=low; i<high; i++) {
1732: if (rp[i] > bcol) break;
1733: if (rp[i] == bcol) {
1734: *v++ = ap[bs2*i+bs*cidx+ridx];
1735: goto finished;
1736: }
1737: }
1738: *v++ = 0.0;
1739: finished:;
1740: }
1741: }
1742: return(0);
1743: }
1745: #define CHUNKSIZE 10
1748: PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
1749: {
1750: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1751: PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
1752: PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen;
1753: PetscErrorCode ierr;
1754: PetscInt *aj=a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
1755: PetscTruth roworiented=a->roworiented;
1756: const PetscScalar *value = v;
1757: MatScalar *ap,*aa = a->a,*bap;
1760: if (roworiented) {
1761: stepval = (n-1)*bs;
1762: } else {
1763: stepval = (m-1)*bs;
1764: }
1765: for (k=0; k<m; k++) { /* loop over added rows */
1766: row = im[k];
1767: if (row < 0) continue;
1768: #if defined(PETSC_USE_DEBUG)
1769: if (row >= a->mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1);
1770: #endif
1771: rp = aj + ai[row];
1772: ap = aa + bs2*ai[row];
1773: rmax = imax[row];
1774: nrow = ailen[row];
1775: low = 0;
1776: high = nrow;
1777: for (l=0; l<n; l++) { /* loop over added columns */
1778: if (in[l] < 0) continue;
1779: #if defined(PETSC_USE_DEBUG)
1780: if (in[l] >= a->nbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],a->nbs-1);
1781: #endif
1782: col = in[l];
1783: if (roworiented) {
1784: value = v + k*(stepval+bs)*bs + l*bs;
1785: } else {
1786: value = v + l*(stepval+bs)*bs + k*bs;
1787: }
1788: if (col <= lastcol) low = 0; else high = nrow;
1789: lastcol = col;
1790: while (high-low > 7) {
1791: t = (low+high)/2;
1792: if (rp[t] > col) high = t;
1793: else low = t;
1794: }
1795: for (i=low; i<high; i++) {
1796: if (rp[i] > col) break;
1797: if (rp[i] == col) {
1798: bap = ap + bs2*i;
1799: if (roworiented) {
1800: if (is == ADD_VALUES) {
1801: for (ii=0; ii<bs; ii++,value+=stepval) {
1802: for (jj=ii; jj<bs2; jj+=bs) {
1803: bap[jj] += *value++;
1804: }
1805: }
1806: } else {
1807: for (ii=0; ii<bs; ii++,value+=stepval) {
1808: for (jj=ii; jj<bs2; jj+=bs) {
1809: bap[jj] = *value++;
1810: }
1811: }
1812: }
1813: } else {
1814: if (is == ADD_VALUES) {
1815: for (ii=0; ii<bs; ii++,value+=stepval) {
1816: for (jj=0; jj<bs; jj++) {
1817: *bap++ += *value++;
1818: }
1819: }
1820: } else {
1821: for (ii=0; ii<bs; ii++,value+=stepval) {
1822: for (jj=0; jj<bs; jj++) {
1823: *bap++ = *value++;
1824: }
1825: }
1826: }
1827: }
1828: goto noinsert2;
1829: }
1830: }
1831: if (nonew == 1) goto noinsert2;
1832: if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
1833: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
1834: N = nrow++ - 1; high++;
1835: /* shift up all the later entries in this row */
1836: for (ii=N; ii>=i; ii--) {
1837: rp[ii+1] = rp[ii];
1838: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
1839: }
1840: if (N >= i) {
1841: PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
1842: }
1843: rp[i] = col;
1844: bap = ap + bs2*i;
1845: if (roworiented) {
1846: for (ii=0; ii<bs; ii++,value+=stepval) {
1847: for (jj=ii; jj<bs2; jj+=bs) {
1848: bap[jj] = *value++;
1849: }
1850: }
1851: } else {
1852: for (ii=0; ii<bs; ii++,value+=stepval) {
1853: for (jj=0; jj<bs; jj++) {
1854: *bap++ = *value++;
1855: }
1856: }
1857: }
1858: noinsert2:;
1859: low = i;
1860: }
1861: ailen[row] = nrow;
1862: }
1863: return(0);
1864: }
1868: PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode)
1869: {
1870: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1871: PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
1872: PetscInt m = A->rmap->N,*ip,N,*ailen = a->ilen;
1874: PetscInt mbs = a->mbs,bs2 = a->bs2,rmax = 0;
1875: MatScalar *aa = a->a,*ap;
1876: PetscReal ratio=0.6;
1879: if (mode == MAT_FLUSH_ASSEMBLY) return(0);
1881: if (m) rmax = ailen[0];
1882: for (i=1; i<mbs; i++) {
1883: /* move each row back by the amount of empty slots (fshift) before it*/
1884: fshift += imax[i-1] - ailen[i-1];
1885: rmax = PetscMax(rmax,ailen[i]);
1886: if (fshift) {
1887: ip = aj + ai[i]; ap = aa + bs2*ai[i];
1888: N = ailen[i];
1889: for (j=0; j<N; j++) {
1890: ip[j-fshift] = ip[j];
1891: PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));
1892: }
1893: }
1894: ai[i] = ai[i-1] + ailen[i-1];
1895: }
1896: if (mbs) {
1897: fshift += imax[mbs-1] - ailen[mbs-1];
1898: ai[mbs] = ai[mbs-1] + ailen[mbs-1];
1899: }
1900: /* reset ilen and imax for each row */
1901: for (i=0; i<mbs; i++) {
1902: ailen[i] = imax[i] = ai[i+1] - ai[i];
1903: }
1904: a->nz = ai[mbs];
1906: /* diagonals may have moved, so kill the diagonal pointers */
1907: a->idiagvalid = PETSC_FALSE;
1908: if (fshift && a->diag) {
1909: PetscFree(a->diag);
1910: PetscLogObjectMemory(A,-(mbs+1)*sizeof(PetscInt));
1911: a->diag = 0;
1912: }
1913: if (fshift && a->nounused == -1) {
1914: SETERRQ4(PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2);
1915: }
1916: PetscInfo5(A,"Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->cmap->n,A->rmap->bs,fshift*bs2,a->nz*bs2);
1917: PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);
1918: PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);
1919: a->reallocs = 0;
1920: A->info.nz_unneeded = (PetscReal)fshift*bs2;
1922: /* check for zero rows. If found a large number of zero rows, use CompressedRow functions */
1923: if (a->compressedrow.use){
1924: Mat_CheckCompressedRow(A,&a->compressedrow,a->i,mbs,ratio);
1925: }
1927: A->same_nonzero = PETSC_TRUE;
1928: return(0);
1929: }
1931: /*
1932: This function returns an array of flags which indicate the locations of contiguous
1933: blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9]
1934: then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)]
1935: Assume: sizes should be long enough to hold all the values.
1936: */
1939: static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
1940: {
1941: PetscInt i,j,k,row;
1942: PetscTruth flg;
1945: for (i=0,j=0; i<n; j++) {
1946: row = idx[i];
1947: if (row%bs!=0) { /* Not the begining of a block */
1948: sizes[j] = 1;
1949: i++;
1950: } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */
1951: sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */
1952: i++;
1953: } else { /* Begining of the block, so check if the complete block exists */
1954: flg = PETSC_TRUE;
1955: for (k=1; k<bs; k++) {
1956: if (row+k != idx[i+k]) { /* break in the block */
1957: flg = PETSC_FALSE;
1958: break;
1959: }
1960: }
1961: if (flg) { /* No break in the bs */
1962: sizes[j] = bs;
1963: i+= bs;
1964: } else {
1965: sizes[j] = 1;
1966: i++;
1967: }
1968: }
1969: }
1970: *bs_max = j;
1971: return(0);
1972: }
1973:
1976: PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag)
1977: {
1978: Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data;
1980: PetscInt i,j,k,count,*rows;
1981: PetscInt bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max;
1982: PetscScalar zero = 0.0;
1983: MatScalar *aa;
1986: /* Make a copy of the IS and sort it */
1987: /* allocate memory for rows,sizes */
1988: PetscMalloc((3*is_n+1)*sizeof(PetscInt),&rows);
1989: sizes = rows + is_n;
1991: /* copy IS values to rows, and sort them */
1992: for (i=0; i<is_n; i++) { rows[i] = is_idx[i]; }
1993: PetscSortInt(is_n,rows);
1994: if (baij->keepzeroedrows) {
1995: for (i=0; i<is_n; i++) { sizes[i] = 1; }
1996: bs_max = is_n;
1997: A->same_nonzero = PETSC_TRUE;
1998: } else {
1999: MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);
2000: A->same_nonzero = PETSC_FALSE;
2001: }
2003: for (i=0,j=0; i<bs_max; j+=sizes[i],i++) {
2004: row = rows[j];
2005: if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row);
2006: count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
2007: aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
2008: if (sizes[i] == bs && !baij->keepzeroedrows) {
2009: if (diag != 0.0) {
2010: if (baij->ilen[row/bs] > 0) {
2011: baij->ilen[row/bs] = 1;
2012: baij->j[baij->i[row/bs]] = row/bs;
2013: PetscMemzero(aa,count*bs*sizeof(MatScalar));
2014: }
2015: /* Now insert all the diagonal values for this bs */
2016: for (k=0; k<bs; k++) {
2017: (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);
2018: }
2019: } else { /* (diag == 0.0) */
2020: baij->ilen[row/bs] = 0;
2021: } /* end (diag == 0.0) */
2022: } else { /* (sizes[i] != bs) */
2023: #if defined (PETSC_USE_DEBUG)
2024: if (sizes[i] != 1) SETERRQ(PETSC_ERR_PLIB,"Internal Error. Value should be 1");
2025: #endif
2026: for (k=0; k<count; k++) {
2027: aa[0] = zero;
2028: aa += bs;
2029: }
2030: if (diag != 0.0) {
2031: (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);
2032: }
2033: }
2034: }
2036: PetscFree(rows);
2037: MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
2038: return(0);
2039: }
2043: PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
2044: {
2045: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2046: PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
2047: PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen;
2048: PetscInt *aj=a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
2050: PetscInt ridx,cidx,bs2=a->bs2;
2051: PetscTruth roworiented=a->roworiented;
2052: MatScalar *ap,value,*aa=a->a,*bap;
2055: for (k=0; k<m; k++) { /* loop over added rows */
2056: row = im[k];
2057: brow = row/bs;
2058: if (row < 0) continue;
2059: #if defined(PETSC_USE_DEBUG)
2060: if (row >= A->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
2061: #endif
2062: rp = aj + ai[brow];
2063: ap = aa + bs2*ai[brow];
2064: rmax = imax[brow];
2065: nrow = ailen[brow];
2066: low = 0;
2067: high = nrow;
2068: for (l=0; l<n; l++) { /* loop over added columns */
2069: if (in[l] < 0) continue;
2070: #if defined(PETSC_USE_DEBUG)
2071: if (in[l] >= A->cmap->n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1);
2072: #endif
2073: col = in[l]; bcol = col/bs;
2074: ridx = row % bs; cidx = col % bs;
2075: if (roworiented) {
2076: value = v[l + k*n];
2077: } else {
2078: value = v[k + l*m];
2079: }
2080: if (col <= lastcol) low = 0; else high = nrow;
2081: lastcol = col;
2082: while (high-low > 7) {
2083: t = (low+high)/2;
2084: if (rp[t] > bcol) high = t;
2085: else low = t;
2086: }
2087: for (i=low; i<high; i++) {
2088: if (rp[i] > bcol) break;
2089: if (rp[i] == bcol) {
2090: bap = ap + bs2*i + bs*cidx + ridx;
2091: if (is == ADD_VALUES) *bap += value;
2092: else *bap = value;
2093: goto noinsert1;
2094: }
2095: }
2096: if (nonew == 1) goto noinsert1;
2097: if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
2098: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
2099: N = nrow++ - 1; high++;
2100: /* shift up all the later entries in this row */
2101: for (ii=N; ii>=i; ii--) {
2102: rp[ii+1] = rp[ii];
2103: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
2104: }
2105: if (N>=i) {
2106: PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
2107: }
2108: rp[i] = bcol;
2109: ap[bs2*i + bs*cidx + ridx] = value;
2110: a->nz++;
2111: noinsert1:;
2112: low = i;
2113: }
2114: ailen[brow] = nrow;
2115: }
2116: A->same_nonzero = PETSC_FALSE;
2117: return(0);
2118: }
2120: EXTERN PetscErrorCode MatSeqBAIJSetNumericFactorization(Mat,PetscTruth);
2124: PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info)
2125: {
2126: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inA->data;
2127: Mat outA;
2129: PetscTruth row_identity,col_identity;
2132: if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU");
2133: ISIdentity(row,&row_identity);
2134: ISIdentity(col,&col_identity);
2135: if (!row_identity || !col_identity) {
2136: SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU");
2137: }
2139: outA = inA;
2140: inA->factor = MAT_FACTOR_LU;
2142: MatMarkDiagonal_SeqBAIJ(inA);
2144: PetscObjectReference((PetscObject)row);
2145: if (a->row) { ISDestroy(a->row); }
2146: a->row = row;
2147: PetscObjectReference((PetscObject)col);
2148: if (a->col) { ISDestroy(a->col); }
2149: a->col = col;
2150:
2151: /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */
2152: ISInvertPermutation(col,PETSC_DECIDE,&a->icol);
2153: PetscLogObjectParent(inA,a->icol);
2154:
2155: MatSeqBAIJSetNumericFactorization(inA,(PetscTruth)(row_identity && col_identity));
2156: if (!a->solve_work) {
2157: PetscMalloc((inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar),&a->solve_work);
2158: PetscLogObjectMemory(inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
2159: }
2160: MatLUFactorNumeric(outA,inA,info);
2162: return(0);
2163: }
2168: PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices)
2169: {
2170: Mat_SeqBAIJ *baij = (Mat_SeqBAIJ *)mat->data;
2171: PetscInt i,nz,nbs;
2174: nz = baij->maxnz/baij->bs2;
2175: nbs = baij->nbs;
2176: for (i=0; i<nz; i++) {
2177: baij->j[i] = indices[i];
2178: }
2179: baij->nz = nz;
2180: for (i=0; i<nbs; i++) {
2181: baij->ilen[i] = baij->imax[i];
2182: }
2184: return(0);
2185: }
2190: /*@
2191: MatSeqBAIJSetColumnIndices - Set the column indices for all the rows
2192: in the matrix.
2194: Input Parameters:
2195: + mat - the SeqBAIJ matrix
2196: - indices - the column indices
2198: Level: advanced
2200: Notes:
2201: This can be called if you have precomputed the nonzero structure of the
2202: matrix and want to provide it to the matrix object to improve the performance
2203: of the MatSetValues() operation.
2205: You MUST have set the correct numbers of nonzeros per row in the call to
2206: MatCreateSeqBAIJ(), and the columns indices MUST be sorted.
2208: MUST be called before any calls to MatSetValues();
2210: @*/
2211: PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices)
2212: {
2213: PetscErrorCode ierr,(*f)(Mat,PetscInt *);
2218: PetscObjectQueryFunction((PetscObject)mat,"MatSeqBAIJSetColumnIndices_C",(void (**)(void))&f);
2219: if (f) {
2220: (*f)(mat,indices);
2221: } else {
2222: SETERRQ(PETSC_ERR_ARG_WRONG,"Wrong type of matrix to set column indices");
2223: }
2224: return(0);
2225: }
2229: PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[])
2230: {
2231: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2233: PetscInt i,j,n,row,bs,*ai,*aj,mbs;
2234: PetscReal atmp;
2235: PetscScalar *x,zero = 0.0;
2236: MatScalar *aa;
2237: PetscInt ncols,brow,krow,kcol;
2240: if (A->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
2241: bs = A->rmap->bs;
2242: aa = a->a;
2243: ai = a->i;
2244: aj = a->j;
2245: mbs = a->mbs;
2247: VecSet(v,zero);
2248: VecGetArray(v,&x);
2249: VecGetLocalSize(v,&n);
2250: if (n != A->rmap->N) SETERRQ(PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
2251: for (i=0; i<mbs; i++) {
2252: ncols = ai[1] - ai[0]; ai++;
2253: brow = bs*i;
2254: for (j=0; j<ncols; j++){
2255: for (kcol=0; kcol<bs; kcol++){
2256: for (krow=0; krow<bs; krow++){
2257: atmp = PetscAbsScalar(*aa);aa++;
2258: row = brow + krow; /* row index */
2259: /* printf("val[%d,%d]: %G\n",row,bcol+kcol,atmp); */
2260: if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;}
2261: }
2262: }
2263: aj++;
2264: }
2265: }
2266: VecRestoreArray(v,&x);
2267: return(0);
2268: }
2272: PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str)
2273: {
2277: /* If the two matrices have the same copy implementation, use fast copy. */
2278: if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
2279: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2280: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)B->data;
2282: if (a->i[A->rmap->N] != b->i[B->rmap->N]) {
2283: SETERRQ(PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different");
2284: }
2285: PetscMemcpy(b->a,a->a,(a->i[A->rmap->N])*sizeof(PetscScalar));
2286: } else {
2287: MatCopy_Basic(A,B,str);
2288: }
2289: return(0);
2290: }
2294: PetscErrorCode MatSetUpPreallocation_SeqBAIJ(Mat A)
2295: {
2299: MatSeqBAIJSetPreallocation_SeqBAIJ(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0);
2300: return(0);
2301: }
2305: PetscErrorCode MatGetArray_SeqBAIJ(Mat A,PetscScalar *array[])
2306: {
2307: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2309: *array = a->a;
2310: return(0);
2311: }
2315: PetscErrorCode MatRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[])
2316: {
2318: return(0);
2319: }
2321: #include petscblaslapack.h
2324: PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2325: {
2326: Mat_SeqBAIJ *x = (Mat_SeqBAIJ *)X->data,*y = (Mat_SeqBAIJ *)Y->data;
2328: PetscInt i,bs=Y->rmap->bs,j,bs2;
2329: PetscBLASInt one=1,bnz = PetscBLASIntCast(x->nz);
2332: if (str == SAME_NONZERO_PATTERN) {
2333: PetscScalar alpha = a;
2334: BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one);
2335: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2336: if (y->xtoy && y->XtoY != X) {
2337: PetscFree(y->xtoy);
2338: MatDestroy(y->XtoY);
2339: }
2340: if (!y->xtoy) { /* get xtoy */
2341: MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);
2342: y->XtoY = X;
2343: PetscObjectReference((PetscObject)X);
2344: }
2345: bs2 = bs*bs;
2346: for (i=0; i<x->nz; i++) {
2347: j = 0;
2348: while (j < bs2){
2349: y->a[bs2*y->xtoy[i]+j] += a*(x->a[bs2*i+j]);
2350: j++;
2351: }
2352: }
2353: PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %D/%D = %G\n",bs2*x->nz,bs2*y->nz,(PetscReal)(bs2*x->nz)/(bs2*y->nz));
2354: } else {
2355: MatAXPY_Basic(Y,a,X,str);
2356: }
2357: return(0);
2358: }
2362: PetscErrorCode MatRealPart_SeqBAIJ(Mat A)
2363: {
2364: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2365: PetscInt i,nz = a->bs2*a->i[a->mbs];
2366: MatScalar *aa = a->a;
2369: for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
2370: return(0);
2371: }
2375: PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A)
2376: {
2377: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2378: PetscInt i,nz = a->bs2*a->i[a->mbs];
2379: MatScalar *aa = a->a;
2382: for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
2383: return(0);
2384: }
2387: /* -------------------------------------------------------------------*/
2388: static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ,
2389: MatGetRow_SeqBAIJ,
2390: MatRestoreRow_SeqBAIJ,
2391: MatMult_SeqBAIJ_N,
2392: /* 4*/ MatMultAdd_SeqBAIJ_N,
2393: MatMultTranspose_SeqBAIJ,
2394: MatMultTransposeAdd_SeqBAIJ,
2395: 0,
2396: 0,
2397: 0,
2398: /*10*/ 0,
2399: MatLUFactor_SeqBAIJ,
2400: 0,
2401: 0,
2402: MatTranspose_SeqBAIJ,
2403: /*15*/ MatGetInfo_SeqBAIJ,
2404: MatEqual_SeqBAIJ,
2405: MatGetDiagonal_SeqBAIJ,
2406: MatDiagonalScale_SeqBAIJ,
2407: MatNorm_SeqBAIJ,
2408: /*20*/ 0,
2409: MatAssemblyEnd_SeqBAIJ,
2410: 0,
2411: MatSetOption_SeqBAIJ,
2412: MatZeroEntries_SeqBAIJ,
2413: /*25*/ MatZeroRows_SeqBAIJ,
2414: 0,
2415: 0,
2416: 0,
2417: 0,
2418: /*30*/ MatSetUpPreallocation_SeqBAIJ,
2419: 0,
2420: 0,
2421: MatGetArray_SeqBAIJ,
2422: MatRestoreArray_SeqBAIJ,
2423: /*35*/ MatDuplicate_SeqBAIJ,
2424: 0,
2425: 0,
2426: MatILUFactor_SeqBAIJ,
2427: 0,
2428: /*40*/ MatAXPY_SeqBAIJ,
2429: MatGetSubMatrices_SeqBAIJ,
2430: MatIncreaseOverlap_SeqBAIJ,
2431: MatGetValues_SeqBAIJ,
2432: MatCopy_SeqBAIJ,
2433: /*45*/ 0,
2434: MatScale_SeqBAIJ,
2435: 0,
2436: 0,
2437: 0,
2438: /*50*/ 0,
2439: MatGetRowIJ_SeqBAIJ,
2440: MatRestoreRowIJ_SeqBAIJ,
2441: 0,
2442: 0,
2443: /*55*/ 0,
2444: 0,
2445: 0,
2446: 0,
2447: MatSetValuesBlocked_SeqBAIJ,
2448: /*60*/ MatGetSubMatrix_SeqBAIJ,
2449: MatDestroy_SeqBAIJ,
2450: MatView_SeqBAIJ,
2451: 0,
2452: 0,
2453: /*65*/ 0,
2454: 0,
2455: 0,
2456: 0,
2457: 0,
2458: /*70*/ MatGetRowMaxAbs_SeqBAIJ,
2459: 0,
2460: MatConvert_Basic,
2461: 0,
2462: 0,
2463: /*75*/ 0,
2464: 0,
2465: 0,
2466: 0,
2467: 0,
2468: /*80*/ 0,
2469: 0,
2470: 0,
2471: 0,
2472: MatLoad_SeqBAIJ,
2473: /*85*/ 0,
2474: 0,
2475: 0,
2476: 0,
2477: 0,
2478: /*90*/ 0,
2479: 0,
2480: 0,
2481: 0,
2482: 0,
2483: /*95*/ 0,
2484: 0,
2485: 0,
2486: 0,
2487: 0,
2488: /*100*/0,
2489: 0,
2490: 0,
2491: 0,
2492: 0,
2493: /*105*/0,
2494: MatRealPart_SeqBAIJ,
2495: MatImaginaryPart_SeqBAIJ,
2496: 0,
2497: 0,
2498: /*110*/0,
2499: 0,
2500: 0,
2501: 0,
2502: MatMissingDiagonal_SeqBAIJ
2503: /*115*/
2504: };
2509: PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat)
2510: {
2511: Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)mat->data;
2512: PetscInt nz = aij->i[mat->rmap->N]*mat->rmap->bs*aij->bs2;
2516: if (aij->nonew != 1) {
2517: SETERRQ(PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
2518: }
2520: /* allocate space for values if not already there */
2521: if (!aij->saved_values) {
2522: PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);
2523: }
2525: /* copy values over */
2526: PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));
2527: return(0);
2528: }
2534: PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat)
2535: {
2536: Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)mat->data;
2538: PetscInt nz = aij->i[mat->rmap->N]*mat->rmap->bs*aij->bs2;
2541: if (aij->nonew != 1) {
2542: SETERRQ(PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
2543: }
2544: if (!aij->saved_values) {
2545: SETERRQ(PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");
2546: }
2548: /* copy values over */
2549: PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));
2550: return(0);
2551: }
2562: PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
2563: {
2564: Mat_SeqBAIJ *b;
2566: PetscInt i,mbs,nbs,bs2,newbs = PetscAbs(bs);
2567: PetscTruth flg,skipallocation = PETSC_FALSE;
2571: if (nz == MAT_SKIP_ALLOCATION) {
2572: skipallocation = PETSC_TRUE;
2573: nz = 0;
2574: }
2576: if (bs < 0) {
2577: PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Block options for SEQBAIJ matrix 1","Mat");
2578: PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatSeqBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);
2579: PetscOptionsEnd();
2580: bs = PetscAbs(bs);
2581: }
2582: if (nnz && newbs != bs) {
2583: SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting nnz");
2584: }
2585: bs = newbs;
2587: PetscMapSetBlockSize(B->rmap,bs);
2588: PetscMapSetBlockSize(B->cmap,bs);
2589: PetscMapSetUp(B->rmap);
2590: PetscMapSetUp(B->cmap);
2592: B->preallocated = PETSC_TRUE;
2594: mbs = B->rmap->n/bs;
2595: nbs = B->cmap->n/bs;
2596: bs2 = bs*bs;
2598: if (mbs*bs!=B->rmap->n || nbs*bs!=B->cmap->n) {
2599: SETERRQ3(PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->rmap->N,B->cmap->n,bs);
2600: }
2602: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
2603: if (nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz);
2604: if (nnz) {
2605: for (i=0; i<mbs; i++) {
2606: if (nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]);
2607: 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);
2608: }
2609: }
2611: b = (Mat_SeqBAIJ*)B->data;
2612: PetscOptionsBegin(((PetscObject)B)->comm,PETSC_NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");
2613: PetscOptionsTruth("-mat_no_unroll","Do not optimize for block size (slow)",PETSC_NULL,PETSC_FALSE,&flg,PETSC_NULL);
2614: PetscOptionsEnd();
2616: if (!flg) {
2617: switch (bs) {
2618: case 1:
2619: B->ops->mult = MatMult_SeqBAIJ_1;
2620: B->ops->multadd = MatMultAdd_SeqBAIJ_1;
2621: B->ops->pbrelax = MatPBRelax_SeqBAIJ_1;
2622: break;
2623: case 2:
2624: B->ops->mult = MatMult_SeqBAIJ_2;
2625: B->ops->multadd = MatMultAdd_SeqBAIJ_2;
2626: B->ops->pbrelax = MatPBRelax_SeqBAIJ_2;
2627: break;
2628: case 3:
2629: B->ops->mult = MatMult_SeqBAIJ_3;
2630: B->ops->multadd = MatMultAdd_SeqBAIJ_3;
2631: B->ops->pbrelax = MatPBRelax_SeqBAIJ_3;
2632: break;
2633: case 4:
2634: B->ops->mult = MatMult_SeqBAIJ_4;
2635: B->ops->multadd = MatMultAdd_SeqBAIJ_4;
2636: B->ops->pbrelax = MatPBRelax_SeqBAIJ_4;
2637: break;
2638: case 5:
2639: B->ops->mult = MatMult_SeqBAIJ_5;
2640: B->ops->multadd = MatMultAdd_SeqBAIJ_5;
2641: B->ops->pbrelax = MatPBRelax_SeqBAIJ_5;
2642: break;
2643: case 6:
2644: B->ops->mult = MatMult_SeqBAIJ_6;
2645: B->ops->multadd = MatMultAdd_SeqBAIJ_6;
2646: B->ops->pbrelax = MatPBRelax_SeqBAIJ_6;
2647: break;
2648: case 7:
2649: B->ops->mult = MatMult_SeqBAIJ_7;
2650: B->ops->multadd = MatMultAdd_SeqBAIJ_7;
2651: B->ops->pbrelax = MatPBRelax_SeqBAIJ_7;
2652: break;
2653: default:
2654: B->ops->mult = MatMult_SeqBAIJ_N;
2655: B->ops->multadd = MatMultAdd_SeqBAIJ_N;
2656: break;
2657: }
2658: }
2659: B->rmap->bs = bs;
2660: b->mbs = mbs;
2661: b->nbs = nbs;
2662: if (!skipallocation) {
2663: if (!b->imax) {
2664: PetscMalloc2(mbs,PetscInt,&b->imax,mbs,PetscInt,&b->ilen);
2665: }
2666: /* b->ilen will count nonzeros in each block row so far. */
2667: for (i=0; i<mbs; i++) { b->ilen[i] = 0;}
2668: if (!nnz) {
2669: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
2670: else if (nz <= 0) nz = 1;
2671: for (i=0; i<mbs; i++) b->imax[i] = nz;
2672: nz = nz*mbs;
2673: } else {
2674: nz = 0;
2675: for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];}
2676: }
2678: /* allocate the matrix space */
2679: MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
2680: PetscMalloc3(bs2*nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->N+1,PetscInt,&b->i);
2681: PetscLogObjectMemory(B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
2682: PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));
2683: PetscMemzero(b->j,nz*sizeof(PetscInt));
2684: b->singlemalloc = PETSC_TRUE;
2685: b->i[0] = 0;
2686: for (i=1; i<mbs+1; i++) {
2687: b->i[i] = b->i[i-1] + b->imax[i-1];
2688: }
2689: b->free_a = PETSC_TRUE;
2690: b->free_ij = PETSC_TRUE;
2691: } else {
2692: b->free_a = PETSC_FALSE;
2693: b->free_ij = PETSC_FALSE;
2694: }
2696: B->rmap->bs = bs;
2697: b->bs2 = bs2;
2698: b->mbs = mbs;
2699: b->nz = 0;
2700: b->maxnz = nz*bs2;
2701: B->info.nz_unneeded = (PetscReal)b->maxnz;
2702: return(0);
2703: }
2709: PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2710: {
2711: PetscInt i,m,nz,nz_max=0,*nnz;
2712: PetscScalar *values=0;
2717: if (bs < 1) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2719: PetscMapSetBlockSize(B->rmap,bs);
2720: PetscMapSetBlockSize(B->cmap,bs);
2721: PetscMapSetUp(B->rmap);
2722: PetscMapSetUp(B->cmap);
2723: m = B->rmap->n/bs;
2725: if (ii[0] != 0) { SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]); }
2726: PetscMalloc((m+1) * sizeof(PetscInt), &nnz);
2727: for(i=0; i<m; i++) {
2728: nz = ii[i+1]- ii[i];
2729: if (nz < 0) { SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz); }
2730: nz_max = PetscMax(nz_max, nz);
2731: nnz[i] = nz;
2732: }
2733: MatSeqBAIJSetPreallocation(B,bs,0,nnz);
2734: PetscFree(nnz);
2736: values = (PetscScalar*)V;
2737: if (!values) {
2738: PetscMalloc(bs*bs*(nz_max+1)*sizeof(PetscScalar),&values);
2739: PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2740: }
2741: for (i=0; i<m; i++) {
2742: PetscInt ncols = ii[i+1] - ii[i];
2743: const PetscInt *icols = jj + ii[i];
2744: const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2745: MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);
2746: }
2747: if (!V) { PetscFree(values); }
2748: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2749: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2751: return(0);
2752: }
2761: /*MC
2762: MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on
2763: block sparse compressed row format.
2765: Options Database Keys:
2766: . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions()
2768: Level: beginner
2770: .seealso: MatCreateSeqBAIJ()
2771: M*/
2777: PetscErrorCode MatCreate_SeqBAIJ(Mat B)
2778: {
2780: PetscMPIInt size;
2781: Mat_SeqBAIJ *b;
2784: MPI_Comm_size(((PetscObject)B)->comm,&size);
2785: if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"Comm must be of size 1");
2787: PetscNewLog(B,Mat_SeqBAIJ,&b);
2788: B->data = (void*)b;
2789: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
2790: B->mapping = 0;
2791: b->row = 0;
2792: b->col = 0;
2793: b->icol = 0;
2794: b->reallocs = 0;
2795: b->saved_values = 0;
2797: b->roworiented = PETSC_TRUE;
2798: b->nonew = 0;
2799: b->diag = 0;
2800: b->solve_work = 0;
2801: b->mult_work = 0;
2802: B->spptr = 0;
2803: B->info.nz_unneeded = (PetscReal)b->maxnz;
2804: b->keepzeroedrows = PETSC_FALSE;
2805: b->xtoy = 0;
2806: b->XtoY = 0;
2807: b->compressedrow.use = PETSC_FALSE;
2808: b->compressedrow.nrows = 0;
2809: b->compressedrow.i = PETSC_NULL;
2810: b->compressedrow.rindex = PETSC_NULL;
2811: b->compressedrow.checked = PETSC_FALSE;
2812: B->same_nonzero = PETSC_FALSE;
2814: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactorAvailable_seqbaij_petsc_C",
2815: "MatGetFactorAvailable_seqbaij_petsc",
2816: MatGetFactorAvailable_seqbaij_petsc);
2817: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_seqbaij_petsc_C",
2818: "MatGetFactor_seqbaij_petsc",
2819: MatGetFactor_seqbaij_petsc);
2820: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqBAIJInvertBlockDiagonal_C",
2821: "MatInvertBlockDiagonal_SeqBAIJ",
2822: MatInvertBlockDiagonal_SeqBAIJ);
2823: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C",
2824: "MatStoreValues_SeqBAIJ",
2825: MatStoreValues_SeqBAIJ);
2826: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C",
2827: "MatRetrieveValues_SeqBAIJ",
2828: MatRetrieveValues_SeqBAIJ);
2829: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",
2830: "MatSeqBAIJSetColumnIndices_SeqBAIJ",
2831: MatSeqBAIJSetColumnIndices_SeqBAIJ);
2832: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqbaij_seqaij_C",
2833: "MatConvert_SeqBAIJ_SeqAIJ",
2834: MatConvert_SeqBAIJ_SeqAIJ);
2835: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",
2836: "MatConvert_SeqBAIJ_SeqSBAIJ",
2837: MatConvert_SeqBAIJ_SeqSBAIJ);
2838: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqBAIJSetPreallocation_C",
2839: "MatSeqBAIJSetPreallocation_SeqBAIJ",
2840: MatSeqBAIJSetPreallocation_SeqBAIJ);
2841: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",
2842: "MatSeqBAIJSetPreallocationCSR_SeqBAIJ",
2843: MatSeqBAIJSetPreallocationCSR_SeqBAIJ);
2844: PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);
2845: return(0);
2846: }
2851: PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues)
2852: {
2853: Mat_SeqBAIJ *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data;
2855: PetscInt i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2;
2858: if (a->i[mbs] != nz) SETERRQ(PETSC_ERR_PLIB,"Corrupt matrix");
2860: PetscMalloc2(mbs,PetscInt,&c->imax,mbs,PetscInt,&c->ilen);
2861: for (i=0; i<mbs; i++) {
2862: c->imax[i] = a->imax[i];
2863: c->ilen[i] = a->ilen[i];
2864: }
2866: /* allocate the matrix space */
2867: PetscMalloc3(bs2*nz,PetscScalar,&c->a,nz,PetscInt,&c->j,mbs+1,PetscInt,&c->i);
2868: c->singlemalloc = PETSC_TRUE;
2869: PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));
2870: if (mbs > 0) {
2871: PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));
2872: if (cpvalues == MAT_COPY_VALUES) {
2873: PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));
2874: } else {
2875: PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));
2876: }
2877: }
2878: c->roworiented = a->roworiented;
2879: c->nonew = a->nonew;
2880: PetscMapCopy(((PetscObject)A)->comm,A->rmap,C->rmap);
2881: PetscMapCopy(((PetscObject)A)->comm,A->cmap,C->cmap);
2882: c->bs2 = a->bs2;
2883: c->mbs = a->mbs;
2884: c->nbs = a->nbs;
2886: if (a->diag) {
2887: PetscMalloc((mbs+1)*sizeof(PetscInt),&c->diag);
2888: PetscLogObjectMemory(C,(mbs+1)*sizeof(PetscInt));
2889: for (i=0; i<mbs; i++) {
2890: c->diag[i] = a->diag[i];
2891: }
2892: } else c->diag = 0;
2893: c->nz = a->nz;
2894: c->maxnz = a->maxnz;
2895: c->solve_work = 0;
2896: c->mult_work = 0;
2897: c->free_a = PETSC_TRUE;
2898: c->free_ij = PETSC_TRUE;
2899: C->preallocated = PETSC_TRUE;
2900: C->assembled = PETSC_TRUE;
2902: c->compressedrow.use = a->compressedrow.use;
2903: c->compressedrow.nrows = a->compressedrow.nrows;
2904: c->compressedrow.checked = a->compressedrow.checked;
2905: if ( a->compressedrow.checked && a->compressedrow.use){
2906: i = a->compressedrow.nrows;
2907: PetscMalloc((2*i+1)*sizeof(PetscInt),&c->compressedrow.i);
2908: c->compressedrow.rindex = c->compressedrow.i + i + 1;
2909: PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));
2910: PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));
2911: } else {
2912: c->compressedrow.use = PETSC_FALSE;
2913: c->compressedrow.i = PETSC_NULL;
2914: c->compressedrow.rindex = PETSC_NULL;
2915: }
2916: C->same_nonzero = A->same_nonzero;
2917: PetscFListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
2918: return(0);
2919: }
2923: PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
2924: {
2928: MatCreate(((PetscObject)A)->comm,B);
2929: MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
2930: MatSetType(*B,MATSEQBAIJ);
2931: MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues);
2932: return(0);
2933: }
2937: PetscErrorCode MatLoad_SeqBAIJ(PetscViewer viewer, const MatType type,Mat *A)
2938: {
2939: Mat_SeqBAIJ *a;
2940: Mat B;
2942: PetscInt i,nz,header[4],*rowlengths=0,M,N,bs=1;
2943: PetscInt *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount;
2944: PetscInt kmax,jcount,block,idx,point,nzcountb,extra_rows;
2945: PetscInt *masked,nmask,tmp,bs2,ishift;
2946: PetscMPIInt size;
2947: int fd;
2948: PetscScalar *aa;
2949: MPI_Comm comm = ((PetscObject)viewer)->comm;
2952: PetscOptionsBegin(comm,PETSC_NULL,"Options for loading SEQBAIJ matrix","Mat");
2953: PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);
2954: PetscOptionsEnd();
2955: bs2 = bs*bs;
2957: MPI_Comm_size(comm,&size);
2958: if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"view must have one processor");
2959: PetscViewerBinaryGetDescriptor(viewer,&fd);
2960: PetscBinaryRead(fd,header,4,PETSC_INT);
2961: if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not Mat object");
2962: M = header[1]; N = header[2]; nz = header[3];
2964: if (header[3] < 0) {
2965: SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ");
2966: }
2968: if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices");
2970: /*
2971: This code adds extra rows to make sure the number of rows is
2972: divisible by the blocksize
2973: */
2974: mbs = M/bs;
2975: extra_rows = bs - M + bs*(mbs);
2976: if (extra_rows == bs) extra_rows = 0;
2977: else mbs++;
2978: if (extra_rows) {
2979: PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2980: }
2982: /* read in row lengths */
2983: PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);
2984: PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
2985: for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2987: /* read in column indices */
2988: PetscMalloc((nz+extra_rows)*sizeof(PetscInt),&jj);
2989: PetscBinaryRead(fd,jj,nz,PETSC_INT);
2990: for (i=0; i<extra_rows; i++) jj[nz+i] = M+i;
2992: /* loop over row lengths determining block row lengths */
2993: PetscMalloc(mbs*sizeof(PetscInt),&browlengths);
2994: PetscMemzero(browlengths,mbs*sizeof(PetscInt));
2995: PetscMalloc(2*mbs*sizeof(PetscInt),&mask);
2996: PetscMemzero(mask,mbs*sizeof(PetscInt));
2997: masked = mask + mbs;
2998: rowcount = 0; nzcount = 0;
2999: for (i=0; i<mbs; i++) {
3000: nmask = 0;
3001: for (j=0; j<bs; j++) {
3002: kmax = rowlengths[rowcount];
3003: for (k=0; k<kmax; k++) {
3004: tmp = jj[nzcount++]/bs;
3005: if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;}
3006: }
3007: rowcount++;
3008: }
3009: browlengths[i] += nmask;
3010: /* zero out the mask elements we set */
3011: for (j=0; j<nmask; j++) mask[masked[j]] = 0;
3012: }
3014: /* create our matrix */
3015: MatCreate(comm,&B);
3016: MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);
3017: MatSetType(B,type);
3018: MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,0,browlengths);
3019: a = (Mat_SeqBAIJ*)B->data;
3021: /* set matrix "i" values */
3022: a->i[0] = 0;
3023: for (i=1; i<= mbs; i++) {
3024: a->i[i] = a->i[i-1] + browlengths[i-1];
3025: a->ilen[i-1] = browlengths[i-1];
3026: }
3027: a->nz = 0;
3028: for (i=0; i<mbs; i++) a->nz += browlengths[i];
3030: /* read in nonzero values */
3031: PetscMalloc((nz+extra_rows)*sizeof(PetscScalar),&aa);
3032: PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);
3033: for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0;
3035: /* set "a" and "j" values into matrix */
3036: nzcount = 0; jcount = 0;
3037: for (i=0; i<mbs; i++) {
3038: nzcountb = nzcount;
3039: nmask = 0;
3040: for (j=0; j<bs; j++) {
3041: kmax = rowlengths[i*bs+j];
3042: for (k=0; k<kmax; k++) {
3043: tmp = jj[nzcount++]/bs;
3044: if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;}
3045: }
3046: }
3047: /* sort the masked values */
3048: PetscSortInt(nmask,masked);
3050: /* set "j" values into matrix */
3051: maskcount = 1;
3052: for (j=0; j<nmask; j++) {
3053: a->j[jcount++] = masked[j];
3054: mask[masked[j]] = maskcount++;
3055: }
3056: /* set "a" values into matrix */
3057: ishift = bs2*a->i[i];
3058: for (j=0; j<bs; j++) {
3059: kmax = rowlengths[i*bs+j];
3060: for (k=0; k<kmax; k++) {
3061: tmp = jj[nzcountb]/bs ;
3062: block = mask[tmp] - 1;
3063: point = jj[nzcountb] - bs*tmp;
3064: idx = ishift + bs2*block + j + bs*point;
3065: a->a[idx] = (MatScalar)aa[nzcountb++];
3066: }
3067: }
3068: /* zero out the mask elements we set */
3069: for (j=0; j<nmask; j++) mask[masked[j]] = 0;
3070: }
3071: if (jcount != a->nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix");
3073: PetscFree(rowlengths);
3074: PetscFree(browlengths);
3075: PetscFree(aa);
3076: PetscFree(jj);
3077: PetscFree(mask);
3079: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3080: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3081: MatView_Private(B);
3083: *A = B;
3084: return(0);
3085: }
3089: /*@C
3090: MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block
3091: compressed row) format. For good matrix assembly performance the
3092: user should preallocate the matrix storage by setting the parameter nz
3093: (or the array nnz). By setting these parameters accurately, performance
3094: during matrix assembly can be increased by more than a factor of 50.
3096: Collective on MPI_Comm
3098: Input Parameters:
3099: + comm - MPI communicator, set to PETSC_COMM_SELF
3100: . bs - size of block
3101: . m - number of rows
3102: . n - number of columns
3103: . nz - number of nonzero blocks per block row (same for all rows)
3104: - nnz - array containing the number of nonzero blocks in the various block rows
3105: (possibly different for each block row) or PETSC_NULL
3107: Output Parameter:
3108: . A - the matrix
3110: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3111: MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely
3112: true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles.
3113: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
3115: Options Database Keys:
3116: . -mat_no_unroll - uses code that does not unroll the loops in the
3117: block calculations (much slower)
3118: . -mat_block_size - size of the blocks to use
3120: Level: intermediate
3122: Notes:
3123: The number of rows and columns must be divisible by blocksize.
3125: If the nnz parameter is given then the nz parameter is ignored
3127: A nonzero block is any block that as 1 or more nonzeros in it
3129: The block AIJ format is fully compatible with standard Fortran 77
3130: storage. That is, the stored row and column indices can begin at
3131: either one (as in Fortran) or zero. See the users' manual for details.
3133: Specify the preallocated storage with either nz or nnz (not both).
3134: Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory
3135: allocation. For additional details, see the users manual chapter on
3136: matrices.
3138: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIBAIJ()
3139: @*/
3140: PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
3141: {
3143:
3145: MatCreate(comm,A);
3146: MatSetSizes(*A,m,n,m,n);
3147: MatSetType(*A,MATSEQBAIJ);
3148: MatSeqBAIJSetPreallocation_SeqBAIJ(*A,bs,nz,(PetscInt*)nnz);
3149: return(0);
3150: }
3154: /*@C
3155: MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros
3156: per row in the matrix. For good matrix assembly performance the
3157: user should preallocate the matrix storage by setting the parameter nz
3158: (or the array nnz). By setting these parameters accurately, performance
3159: during matrix assembly can be increased by more than a factor of 50.
3161: Collective on MPI_Comm
3163: Input Parameters:
3164: + A - the matrix
3165: . bs - size of block
3166: . nz - number of block nonzeros per block row (same for all rows)
3167: - nnz - array containing the number of block nonzeros in the various block rows
3168: (possibly different for each block row) or PETSC_NULL
3170: Options Database Keys:
3171: . -mat_no_unroll - uses code that does not unroll the loops in the
3172: block calculations (much slower)
3173: . -mat_block_size - size of the blocks to use
3175: Level: intermediate
3177: Notes:
3178: If the nnz parameter is given then the nz parameter is ignored
3180: You can call MatGetInfo() to get information on how effective the preallocation was;
3181: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3182: You can also run with the option -info and look for messages with the string
3183: malloc in them to see if additional memory allocation was needed.
3185: The block AIJ format is fully compatible with standard Fortran 77
3186: storage. That is, the stored row and column indices can begin at
3187: either one (as in Fortran) or zero. See the users' manual for details.
3189: Specify the preallocated storage with either nz or nnz (not both).
3190: Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory
3191: allocation. For additional details, see the users manual chapter on
3192: matrices.
3194: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatGetInfo()
3195: @*/
3196: PetscErrorCode MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
3197: {
3198: PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[]);
3201: PetscObjectQueryFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",(void (**)(void))&f);
3202: if (f) {
3203: (*f)(B,bs,nz,nnz);
3204: }
3205: return(0);
3206: }
3210: /*@C
3211: MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format
3212: (the default sequential PETSc format).
3214: Collective on MPI_Comm
3216: Input Parameters:
3217: + A - the matrix
3218: . i - the indices into j for the start of each local row (starts with zero)
3219: . j - the column indices for each local row (starts with zero) these must be sorted for each row
3220: - v - optional values in the matrix
3222: Level: developer
3224: .keywords: matrix, aij, compressed row, sparse
3226: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ
3227: @*/
3228: PetscErrorCode MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3229: {
3230: PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]);
3233: PetscObjectQueryFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",(void (**)(void))&f);
3234: if (f) {
3235: (*f)(B,bs,i,j,v);
3236: }
3237: return(0);
3238: }
3243: /*@
3244: MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements
3245: (upper triangular entries in CSR format) provided by the user.
3247: Collective on MPI_Comm
3249: Input Parameters:
3250: + comm - must be an MPI communicator of size 1
3251: . bs - size of block
3252: . m - number of rows
3253: . n - number of columns
3254: . i - row indices
3255: . j - column indices
3256: - a - matrix values
3258: Output Parameter:
3259: . mat - the matrix
3261: Level: intermediate
3263: Notes:
3264: The i, j, and a arrays are not copied by this routine, the user must free these arrays
3265: once the matrix is destroyed
3267: You cannot set new nonzero locations into this matrix, that will generate an error.
3269: The i and j indices are 0 based
3271: .seealso: MatCreate(), MatCreateMPIBAIJ(), MatCreateSeqBAIJ()
3273: @*/
3274: PetscErrorCode MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt* i,PetscInt*j,PetscScalar *a,Mat *mat)
3275: {
3277: PetscInt ii;
3278: Mat_SeqBAIJ *baij;
3281: if (bs != 1) SETERRQ1(PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs);
3282: if (i[0]) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3283:
3284: MatCreate(comm,mat);
3285: MatSetSizes(*mat,m,n,m,n);
3286: MatSetType(*mat,MATSEQBAIJ);
3287: MatSeqBAIJSetPreallocation_SeqBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);
3288: baij = (Mat_SeqBAIJ*)(*mat)->data;
3289: PetscMalloc2(m,PetscInt,&baij->imax,m,PetscInt,&baij->ilen);
3291: baij->i = i;
3292: baij->j = j;
3293: baij->a = a;
3294: baij->singlemalloc = PETSC_FALSE;
3295: baij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
3296: baij->free_a = PETSC_FALSE;
3297: baij->free_ij = PETSC_FALSE;
3299: for (ii=0; ii<m; ii++) {
3300: baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii];
3301: #if defined(PETSC_USE_DEBUG)
3302: if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]);
3303: #endif
3304: }
3305: #if defined(PETSC_USE_DEBUG)
3306: for (ii=0; ii<baij->i[m]; ii++) {
3307: if (j[ii] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]);
3308: if (j[ii] > n - 1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]);
3309: }
3310: #endif
3312: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3313: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3314: return(0);
3315: }