Actual source code: baij.c
petsc-3.5.2 2014-09-08
2: /*
3: Defines the basic matrix operations for the BAIJ (compressed row)
4: matrix storage format.
5: */
6: #include <../src/mat/impls/baij/seq/baij.h> /*I "petscmat.h" I*/
7: #include <petscblaslapack.h>
8: #include <petsc-private/kernels/blockinvert.h>
9: #include <petsc-private/kernels/blockmatmult.h>
13: PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A,const PetscScalar **values)
14: {
15: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*) A->data;
17: PetscInt *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs,ipvt[5],bs2 = bs*bs,*v_pivots;
18: MatScalar *v = a->a,*odiag,*diag,*mdiag,work[25],*v_work;
19: PetscReal shift = 0.0;
22: if (a->idiagvalid) {
23: if (values) *values = a->idiag;
24: return(0);
25: }
26: MatMarkDiagonal_SeqBAIJ(A);
27: diag_offset = a->diag;
28: if (!a->idiag) {
29: PetscMalloc1(2*bs2*mbs,&a->idiag);
30: PetscLogObjectMemory((PetscObject)A,2*bs2*mbs*sizeof(PetscScalar));
31: }
32: diag = a->idiag;
33: mdiag = a->idiag+bs2*mbs;
34: if (values) *values = a->idiag;
35: /* factor and invert each block */
36: switch (bs) {
37: case 1:
38: for (i=0; i<mbs; i++) {
39: odiag = v + 1*diag_offset[i];
40: diag[0] = odiag[0];
41: mdiag[0] = odiag[0];
42: diag[0] = (PetscScalar)1.0 / (diag[0] + shift);
43: diag += 1;
44: mdiag += 1;
45: }
46: break;
47: case 2:
48: for (i=0; i<mbs; i++) {
49: odiag = v + 4*diag_offset[i];
50: diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
51: mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3];
52: PetscKernel_A_gets_inverse_A_2(diag,shift);
53: diag += 4;
54: mdiag += 4;
55: }
56: break;
57: case 3:
58: for (i=0; i<mbs; i++) {
59: odiag = v + 9*diag_offset[i];
60: diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
61: diag[4] = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7];
62: diag[8] = odiag[8];
63: mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3];
64: mdiag[4] = odiag[4]; mdiag[5] = odiag[5]; mdiag[6] = odiag[6]; mdiag[7] = odiag[7];
65: mdiag[8] = odiag[8];
66: PetscKernel_A_gets_inverse_A_3(diag,shift);
67: diag += 9;
68: mdiag += 9;
69: }
70: break;
71: case 4:
72: for (i=0; i<mbs; i++) {
73: odiag = v + 16*diag_offset[i];
74: PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));
75: PetscMemcpy(mdiag,odiag,16*sizeof(PetscScalar));
76: PetscKernel_A_gets_inverse_A_4(diag,shift);
77: diag += 16;
78: mdiag += 16;
79: }
80: break;
81: case 5:
82: for (i=0; i<mbs; i++) {
83: odiag = v + 25*diag_offset[i];
84: PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));
85: PetscMemcpy(mdiag,odiag,25*sizeof(PetscScalar));
86: PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);
87: diag += 25;
88: mdiag += 25;
89: }
90: break;
91: case 6:
92: for (i=0; i<mbs; i++) {
93: odiag = v + 36*diag_offset[i];
94: PetscMemcpy(diag,odiag,36*sizeof(PetscScalar));
95: PetscMemcpy(mdiag,odiag,36*sizeof(PetscScalar));
96: PetscKernel_A_gets_inverse_A_6(diag,shift);
97: diag += 36;
98: mdiag += 36;
99: }
100: break;
101: case 7:
102: for (i=0; i<mbs; i++) {
103: odiag = v + 49*diag_offset[i];
104: PetscMemcpy(diag,odiag,49*sizeof(PetscScalar));
105: PetscMemcpy(mdiag,odiag,49*sizeof(PetscScalar));
106: PetscKernel_A_gets_inverse_A_7(diag,shift);
107: diag += 49;
108: mdiag += 49;
109: }
110: break;
111: default:
112: PetscMalloc2(bs,&v_work,bs,&v_pivots);
113: for (i=0; i<mbs; i++) {
114: odiag = v + bs2*diag_offset[i];
115: PetscMemcpy(diag,odiag,bs2*sizeof(PetscScalar));
116: PetscMemcpy(mdiag,odiag,bs2*sizeof(PetscScalar));
117: PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);
118: diag += bs2;
119: mdiag += bs2;
120: }
121: PetscFree2(v_work,v_pivots);
122: }
123: a->idiagvalid = PETSC_TRUE;
124: return(0);
125: }
129: PetscErrorCode MatSOR_SeqBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
130: {
131: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
132: PetscScalar *x,*work,*w,*workt,*t;
133: const MatScalar *v,*aa = a->a, *idiag;
134: const PetscScalar *b,*xb;
135: PetscScalar s[7], xw[7]={0}; /* avoid some compilers thinking xw is uninitialized */
136: PetscErrorCode ierr;
137: PetscInt m = a->mbs,i,i2,nz,bs = A->rmap->bs,bs2 = bs*bs,k,j,idx,it;
138: const PetscInt *diag,*ai = a->i,*aj = a->j,*vi;
141: its = its*lits;
142: if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
143: if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
144: if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
145: if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
146: if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");
148: if (!a->idiagvalid) {MatInvertBlockDiagonal(A,NULL);}
150: if (!m) return(0);
151: diag = a->diag;
152: idiag = a->idiag;
153: k = PetscMax(A->rmap->n,A->cmap->n);
154: if (!a->mult_work) {
155: PetscMalloc1((2*k+1),&a->mult_work);
156: }
157: work = a->mult_work;
158: t = work + k+1;
159: if (!a->sor_work) {
160: PetscMalloc1(bs,&a->sor_work);
161: }
162: w = a->sor_work;
164: VecGetArray(xx,&x);
165: VecGetArrayRead(bb,&b);
167: if (flag & SOR_ZERO_INITIAL_GUESS) {
168: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
169: switch (bs) {
170: case 1:
171: PetscKernel_v_gets_A_times_w_1(x,idiag,b);
172: t[0] = b[0];
173: i2 = 1;
174: idiag += 1;
175: for (i=1; i<m; i++) {
176: v = aa + ai[i];
177: vi = aj + ai[i];
178: nz = diag[i] - ai[i];
179: s[0] = b[i2];
180: for (j=0; j<nz; j++) {
181: xw[0] = x[vi[j]];
182: PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
183: }
184: t[i2] = s[0];
185: PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
186: x[i2] = xw[0];
187: idiag += 1;
188: i2 += 1;
189: }
190: break;
191: case 2:
192: PetscKernel_v_gets_A_times_w_2(x,idiag,b);
193: t[0] = b[0]; t[1] = b[1];
194: i2 = 2;
195: idiag += 4;
196: for (i=1; i<m; i++) {
197: v = aa + 4*ai[i];
198: vi = aj + ai[i];
199: nz = diag[i] - ai[i];
200: s[0] = b[i2]; s[1] = b[i2+1];
201: for (j=0; j<nz; j++) {
202: idx = 2*vi[j];
203: it = 4*j;
204: xw[0] = x[idx]; xw[1] = x[1+idx];
205: PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
206: }
207: t[i2] = s[0]; t[i2+1] = s[1];
208: PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
209: x[i2] = xw[0]; x[i2+1] = xw[1];
210: idiag += 4;
211: i2 += 2;
212: }
213: break;
214: case 3:
215: PetscKernel_v_gets_A_times_w_3(x,idiag,b);
216: t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
217: i2 = 3;
218: idiag += 9;
219: for (i=1; i<m; i++) {
220: v = aa + 9*ai[i];
221: vi = aj + ai[i];
222: nz = diag[i] - ai[i];
223: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
224: while (nz--) {
225: idx = 3*(*vi++);
226: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
227: PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
228: v += 9;
229: }
230: t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
231: PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
232: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
233: idiag += 9;
234: i2 += 3;
235: }
236: break;
237: case 4:
238: PetscKernel_v_gets_A_times_w_4(x,idiag,b);
239: t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3];
240: i2 = 4;
241: idiag += 16;
242: for (i=1; i<m; i++) {
243: v = aa + 16*ai[i];
244: vi = aj + ai[i];
245: nz = diag[i] - ai[i];
246: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
247: while (nz--) {
248: idx = 4*(*vi++);
249: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
250: PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
251: v += 16;
252: }
253: t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3];
254: PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
255: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
256: idiag += 16;
257: i2 += 4;
258: }
259: break;
260: case 5:
261: PetscKernel_v_gets_A_times_w_5(x,idiag,b);
262: t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4];
263: i2 = 5;
264: idiag += 25;
265: for (i=1; i<m; i++) {
266: v = aa + 25*ai[i];
267: vi = aj + ai[i];
268: nz = diag[i] - ai[i];
269: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
270: while (nz--) {
271: idx = 5*(*vi++);
272: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
273: PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
274: v += 25;
275: }
276: t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4];
277: PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
278: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
279: idiag += 25;
280: i2 += 5;
281: }
282: break;
283: case 6:
284: PetscKernel_v_gets_A_times_w_6(x,idiag,b);
285: t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5];
286: i2 = 6;
287: idiag += 36;
288: for (i=1; i<m; i++) {
289: v = aa + 36*ai[i];
290: vi = aj + ai[i];
291: nz = diag[i] - ai[i];
292: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5];
293: while (nz--) {
294: idx = 6*(*vi++);
295: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
296: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
297: PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
298: v += 36;
299: }
300: t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
301: t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5];
302: PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
303: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5];
304: idiag += 36;
305: i2 += 6;
306: }
307: break;
308: case 7:
309: PetscKernel_v_gets_A_times_w_7(x,idiag,b);
310: t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
311: t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6];
312: i2 = 7;
313: idiag += 49;
314: for (i=1; i<m; i++) {
315: v = aa + 49*ai[i];
316: vi = aj + ai[i];
317: nz = diag[i] - ai[i];
318: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
319: s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
320: while (nz--) {
321: idx = 7*(*vi++);
322: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
323: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
324: PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
325: v += 49;
326: }
327: t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
328: t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6];
329: PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
330: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
331: x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
332: idiag += 49;
333: i2 += 7;
334: }
335: break;
336: default:
337: PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x);
338: PetscMemcpy(t,b,bs*sizeof(PetscScalar));
339: i2 = bs;
340: idiag += bs2;
341: for (i=1; i<m; i++) {
342: v = aa + bs2*ai[i];
343: vi = aj + ai[i];
344: nz = diag[i] - ai[i];
346: PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
347: /* copy all rows of x that are needed into contiguous space */
348: workt = work;
349: for (j=0; j<nz; j++) {
350: PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
351: workt += bs;
352: }
353: PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
354: PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));
355: PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);
357: idiag += bs2;
358: i2 += bs;
359: }
360: break;
361: }
362: /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
363: PetscLogFlops(1.0*bs2*a->nz);
364: xb = t;
365: }
366: else xb = b;
367: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
368: idiag = a->idiag+bs2*(a->mbs-1);
369: i2 = bs * (m-1);
370: switch (bs) {
371: case 1:
372: s[0] = xb[i2];
373: PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
374: x[i2] = xw[0];
375: i2 -= 1;
376: for (i=m-2; i>=0; i--) {
377: v = aa + (diag[i]+1);
378: vi = aj + diag[i] + 1;
379: nz = ai[i+1] - diag[i] - 1;
380: s[0] = xb[i2];
381: for (j=0; j<nz; j++) {
382: xw[0] = x[vi[j]];
383: PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
384: }
385: PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
386: x[i2] = xw[0];
387: idiag -= 1;
388: i2 -= 1;
389: }
390: break;
391: case 2:
392: s[0] = xb[i2]; s[1] = xb[i2+1];
393: PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
394: x[i2] = xw[0]; x[i2+1] = xw[1];
395: i2 -= 2;
396: idiag -= 4;
397: for (i=m-2; i>=0; i--) {
398: v = aa + 4*(diag[i] + 1);
399: vi = aj + diag[i] + 1;
400: nz = ai[i+1] - diag[i] - 1;
401: s[0] = xb[i2]; s[1] = xb[i2+1];
402: for (j=0; j<nz; j++) {
403: idx = 2*vi[j];
404: it = 4*j;
405: xw[0] = x[idx]; xw[1] = x[1+idx];
406: PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
407: }
408: PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
409: x[i2] = xw[0]; x[i2+1] = xw[1];
410: idiag -= 4;
411: i2 -= 2;
412: }
413: break;
414: case 3:
415: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
416: PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
417: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
418: i2 -= 3;
419: idiag -= 9;
420: for (i=m-2; i>=0; i--) {
421: v = aa + 9*(diag[i]+1);
422: vi = aj + diag[i] + 1;
423: nz = ai[i+1] - diag[i] - 1;
424: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
425: while (nz--) {
426: idx = 3*(*vi++);
427: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
428: PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
429: v += 9;
430: }
431: PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
432: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
433: idiag -= 9;
434: i2 -= 3;
435: }
436: break;
437: case 4:
438: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
439: PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
440: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
441: i2 -= 4;
442: idiag -= 16;
443: for (i=m-2; i>=0; i--) {
444: v = aa + 16*(diag[i]+1);
445: vi = aj + diag[i] + 1;
446: nz = ai[i+1] - diag[i] - 1;
447: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
448: while (nz--) {
449: idx = 4*(*vi++);
450: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
451: PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
452: v += 16;
453: }
454: PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
455: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
456: idiag -= 16;
457: i2 -= 4;
458: }
459: break;
460: case 5:
461: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
462: PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
463: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
464: i2 -= 5;
465: idiag -= 25;
466: for (i=m-2; i>=0; i--) {
467: v = aa + 25*(diag[i]+1);
468: vi = aj + diag[i] + 1;
469: nz = ai[i+1] - diag[i] - 1;
470: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
471: while (nz--) {
472: idx = 5*(*vi++);
473: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
474: PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
475: v += 25;
476: }
477: PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
478: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
479: idiag -= 25;
480: i2 -= 5;
481: }
482: break;
483: case 6:
484: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5];
485: PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
486: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5];
487: i2 -= 6;
488: idiag -= 36;
489: for (i=m-2; i>=0; i--) {
490: v = aa + 36*(diag[i]+1);
491: vi = aj + diag[i] + 1;
492: nz = ai[i+1] - diag[i] - 1;
493: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5];
494: while (nz--) {
495: idx = 6*(*vi++);
496: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
497: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
498: PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
499: v += 36;
500: }
501: PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
502: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5];
503: idiag -= 36;
504: i2 -= 6;
505: }
506: break;
507: case 7:
508: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
509: s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
510: PetscKernel_v_gets_A_times_w_7(x,idiag,b);
511: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
512: x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
513: i2 -= 7;
514: idiag -= 49;
515: for (i=m-2; i>=0; i--) {
516: v = aa + 49*(diag[i]+1);
517: vi = aj + diag[i] + 1;
518: nz = ai[i+1] - diag[i] - 1;
519: s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
520: s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
521: while (nz--) {
522: idx = 7*(*vi++);
523: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
524: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
525: PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
526: v += 49;
527: }
528: PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
529: x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
530: x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
531: idiag -= 49;
532: i2 -= 7;
533: }
534: break;
535: default:
536: PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
537: PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);
538: i2 -= bs;
539: idiag -= bs2;
540: for (i=m-2; i>=0; i--) {
541: v = aa + bs2*(diag[i]+1);
542: vi = aj + diag[i] + 1;
543: nz = ai[i+1] - diag[i] - 1;
545: PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
546: /* copy all rows of x that are needed into contiguous space */
547: workt = work;
548: for (j=0; j<nz; j++) {
549: PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
550: workt += bs;
551: }
552: PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
553: PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);
555: idiag -= bs2;
556: i2 -= bs;
557: }
558: break;
559: }
560: PetscLogFlops(1.0*bs2*(a->nz));
561: }
562: its--;
563: }
564: while (its--) {
565: if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
566: idiag = a->idiag;
567: i2 = 0;
568: switch (bs) {
569: case 1:
570: for (i=0; i<m; i++) {
571: v = aa + ai[i];
572: vi = aj + ai[i];
573: nz = ai[i+1] - ai[i];
574: s[0] = b[i2];
575: for (j=0; j<nz; j++) {
576: xw[0] = x[vi[j]];
577: PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
578: }
579: PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
580: x[i2] += xw[0];
581: idiag += 1;
582: i2 += 1;
583: }
584: break;
585: case 2:
586: for (i=0; i<m; i++) {
587: v = aa + 4*ai[i];
588: vi = aj + ai[i];
589: nz = ai[i+1] - ai[i];
590: s[0] = b[i2]; s[1] = b[i2+1];
591: for (j=0; j<nz; j++) {
592: idx = 2*vi[j];
593: it = 4*j;
594: xw[0] = x[idx]; xw[1] = x[1+idx];
595: PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
596: }
597: PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
598: x[i2] += xw[0]; x[i2+1] += xw[1];
599: idiag += 4;
600: i2 += 2;
601: }
602: break;
603: case 3:
604: for (i=0; i<m; i++) {
605: v = aa + 9*ai[i];
606: vi = aj + ai[i];
607: nz = ai[i+1] - ai[i];
608: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
609: while (nz--) {
610: idx = 3*(*vi++);
611: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
612: PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
613: v += 9;
614: }
615: PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
616: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
617: idiag += 9;
618: i2 += 3;
619: }
620: break;
621: case 4:
622: for (i=0; i<m; i++) {
623: v = aa + 16*ai[i];
624: vi = aj + ai[i];
625: nz = ai[i+1] - ai[i];
626: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
627: while (nz--) {
628: idx = 4*(*vi++);
629: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
630: PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
631: v += 16;
632: }
633: PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
634: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
635: idiag += 16;
636: i2 += 4;
637: }
638: break;
639: case 5:
640: for (i=0; i<m; i++) {
641: v = aa + 25*ai[i];
642: vi = aj + ai[i];
643: nz = ai[i+1] - ai[i];
644: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
645: while (nz--) {
646: idx = 5*(*vi++);
647: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
648: PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
649: v += 25;
650: }
651: PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
652: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
653: idiag += 25;
654: i2 += 5;
655: }
656: break;
657: case 6:
658: for (i=0; i<m; i++) {
659: v = aa + 36*ai[i];
660: vi = aj + ai[i];
661: nz = ai[i+1] - ai[i];
662: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5];
663: while (nz--) {
664: idx = 6*(*vi++);
665: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
666: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
667: PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
668: v += 36;
669: }
670: PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
671: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
672: x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
673: idiag += 36;
674: i2 += 6;
675: }
676: break;
677: case 7:
678: for (i=0; i<m; i++) {
679: v = aa + 49*ai[i];
680: vi = aj + ai[i];
681: nz = ai[i+1] - ai[i];
682: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
683: s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
684: while (nz--) {
685: idx = 7*(*vi++);
686: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
687: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
688: PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
689: v += 49;
690: }
691: PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
692: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
693: x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
694: idiag += 49;
695: i2 += 7;
696: }
697: break;
698: default:
699: for (i=0; i<m; i++) {
700: v = aa + bs2*ai[i];
701: vi = aj + ai[i];
702: nz = ai[i+1] - ai[i];
704: PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
705: /* copy all rows of x that are needed into contiguous space */
706: workt = work;
707: for (j=0; j<nz; j++) {
708: PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
709: workt += bs;
710: }
711: PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
712: PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);
714: idiag += bs2;
715: i2 += bs;
716: }
717: break;
718: }
719: PetscLogFlops(2.0*bs2*a->nz);
720: }
721: if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
722: idiag = a->idiag+bs2*(a->mbs-1);
723: i2 = bs * (m-1);
724: switch (bs) {
725: case 1:
726: for (i=m-1; i>=0; i--) {
727: v = aa + ai[i];
728: vi = aj + ai[i];
729: nz = ai[i+1] - ai[i];
730: s[0] = b[i2];
731: for (j=0; j<nz; j++) {
732: xw[0] = x[vi[j]];
733: PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
734: }
735: PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
736: x[i2] += xw[0];
737: idiag -= 1;
738: i2 -= 1;
739: }
740: break;
741: case 2:
742: for (i=m-1; i>=0; i--) {
743: v = aa + 4*ai[i];
744: vi = aj + ai[i];
745: nz = ai[i+1] - ai[i];
746: s[0] = b[i2]; s[1] = b[i2+1];
747: for (j=0; j<nz; j++) {
748: idx = 2*vi[j];
749: it = 4*j;
750: xw[0] = x[idx]; xw[1] = x[1+idx];
751: PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
752: }
753: PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
754: x[i2] += xw[0]; x[i2+1] += xw[1];
755: idiag -= 4;
756: i2 -= 2;
757: }
758: break;
759: case 3:
760: for (i=m-1; i>=0; i--) {
761: v = aa + 9*ai[i];
762: vi = aj + ai[i];
763: nz = ai[i+1] - ai[i];
764: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
765: while (nz--) {
766: idx = 3*(*vi++);
767: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
768: PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
769: v += 9;
770: }
771: PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
772: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
773: idiag -= 9;
774: i2 -= 3;
775: }
776: break;
777: case 4:
778: for (i=m-1; i>=0; i--) {
779: v = aa + 16*ai[i];
780: vi = aj + ai[i];
781: nz = ai[i+1] - ai[i];
782: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
783: while (nz--) {
784: idx = 4*(*vi++);
785: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
786: PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
787: v += 16;
788: }
789: PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
790: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
791: idiag -= 16;
792: i2 -= 4;
793: }
794: break;
795: case 5:
796: for (i=m-1; i>=0; i--) {
797: v = aa + 25*ai[i];
798: vi = aj + ai[i];
799: nz = ai[i+1] - ai[i];
800: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
801: while (nz--) {
802: idx = 5*(*vi++);
803: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
804: PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
805: v += 25;
806: }
807: PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
808: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
809: idiag -= 25;
810: i2 -= 5;
811: }
812: break;
813: case 6:
814: for (i=m-1; i>=0; i--) {
815: v = aa + 36*ai[i];
816: vi = aj + ai[i];
817: nz = ai[i+1] - ai[i];
818: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5];
819: while (nz--) {
820: idx = 6*(*vi++);
821: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
822: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
823: PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
824: v += 36;
825: }
826: PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
827: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
828: x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
829: idiag -= 36;
830: i2 -= 6;
831: }
832: break;
833: case 7:
834: for (i=m-1; i>=0; i--) {
835: v = aa + 49*ai[i];
836: vi = aj + ai[i];
837: nz = ai[i+1] - ai[i];
838: s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
839: s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
840: while (nz--) {
841: idx = 7*(*vi++);
842: xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
843: xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
844: PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
845: v += 49;
846: }
847: PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
848: x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
849: x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
850: idiag -= 49;
851: i2 -= 7;
852: }
853: break;
854: default:
855: for (i=m-1; i>=0; i--) {
856: v = aa + bs2*ai[i];
857: vi = aj + ai[i];
858: nz = ai[i+1] - ai[i];
860: PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
861: /* copy all rows of x that are needed into contiguous space */
862: workt = work;
863: for (j=0; j<nz; j++) {
864: PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
865: workt += bs;
866: }
867: PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
868: PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);
870: idiag -= bs2;
871: i2 -= bs;
872: }
873: break;
874: }
875: PetscLogFlops(2.0*bs2*(a->nz));
876: }
877: }
878: VecRestoreArray(xx,&x);
879: VecRestoreArrayRead(bb,&b);
880: return(0);
881: }
884: /*
885: Special version for direct calls from Fortran (Used in PETSc-fun3d)
886: */
887: #if defined(PETSC_HAVE_FORTRAN_CAPS)
888: #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4
889: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
890: #define matsetvaluesblocked4_ matsetvaluesblocked4
891: #endif
895: PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[])
896: {
897: Mat A = *AA;
898: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
899: PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn;
900: PetscInt *ai =a->i,*ailen=a->ilen;
901: PetscInt *aj =a->j,stepval,lastcol = -1;
902: const PetscScalar *value = v;
903: MatScalar *ap,*aa = a->a,*bap;
906: if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4");
907: stepval = (n-1)*4;
908: for (k=0; k<m; k++) { /* loop over added rows */
909: row = im[k];
910: rp = aj + ai[row];
911: ap = aa + 16*ai[row];
912: nrow = ailen[row];
913: low = 0;
914: high = nrow;
915: for (l=0; l<n; l++) { /* loop over added columns */
916: col = in[l];
917: if (col <= lastcol) low = 0;
918: else high = nrow;
919: lastcol = col;
920: value = v + k*(stepval+4 + l)*4;
921: while (high-low > 7) {
922: t = (low+high)/2;
923: if (rp[t] > col) high = t;
924: else low = t;
925: }
926: for (i=low; i<high; i++) {
927: if (rp[i] > col) break;
928: if (rp[i] == col) {
929: bap = ap + 16*i;
930: for (ii=0; ii<4; ii++,value+=stepval) {
931: for (jj=ii; jj<16; jj+=4) {
932: bap[jj] += *value++;
933: }
934: }
935: goto noinsert2;
936: }
937: }
938: N = nrow++ - 1;
939: high++; /* added new column index thus must search to one higher than before */
940: /* shift up all the later entries in this row */
941: for (ii=N; ii>=i; ii--) {
942: rp[ii+1] = rp[ii];
943: PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
944: }
945: if (N >= i) {
946: PetscMemzero(ap+16*i,16*sizeof(MatScalar));
947: }
948: rp[i] = col;
949: bap = ap + 16*i;
950: for (ii=0; ii<4; ii++,value+=stepval) {
951: for (jj=ii; jj<16; jj+=4) {
952: bap[jj] = *value++;
953: }
954: }
955: noinsert2:;
956: low = i;
957: }
958: ailen[row] = nrow;
959: }
960: PetscFunctionReturnVoid();
961: }
963: #if defined(PETSC_HAVE_FORTRAN_CAPS)
964: #define matsetvalues4_ MATSETVALUES4
965: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
966: #define matsetvalues4_ matsetvalues4
967: #endif
971: PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v)
972: {
973: Mat A = *AA;
974: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
975: PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm;
976: PetscInt *ai=a->i,*ailen=a->ilen;
977: PetscInt *aj=a->j,brow,bcol;
978: PetscInt ridx,cidx,lastcol = -1;
979: MatScalar *ap,value,*aa=a->a,*bap;
982: for (k=0; k<m; k++) { /* loop over added rows */
983: row = im[k]; brow = row/4;
984: rp = aj + ai[brow];
985: ap = aa + 16*ai[brow];
986: nrow = ailen[brow];
987: low = 0;
988: high = nrow;
989: for (l=0; l<n; l++) { /* loop over added columns */
990: col = in[l]; bcol = col/4;
991: ridx = row % 4; cidx = col % 4;
992: value = v[l + k*n];
993: if (col <= lastcol) low = 0;
994: else high = nrow;
995: lastcol = col;
996: while (high-low > 7) {
997: t = (low+high)/2;
998: if (rp[t] > bcol) high = t;
999: else low = t;
1000: }
1001: for (i=low; i<high; i++) {
1002: if (rp[i] > bcol) break;
1003: if (rp[i] == bcol) {
1004: bap = ap + 16*i + 4*cidx + ridx;
1005: *bap += value;
1006: goto noinsert1;
1007: }
1008: }
1009: N = nrow++ - 1;
1010: high++; /* added new column thus must search to one higher than before */
1011: /* shift up all the later entries in this row */
1012: for (ii=N; ii>=i; ii--) {
1013: rp[ii+1] = rp[ii];
1014: PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
1015: }
1016: if (N>=i) {
1017: PetscMemzero(ap+16*i,16*sizeof(MatScalar));
1018: }
1019: rp[i] = bcol;
1020: ap[16*i + 4*cidx + ridx] = value;
1021: noinsert1:;
1022: low = i;
1023: }
1024: ailen[brow] = nrow;
1025: }
1026: PetscFunctionReturnVoid();
1027: }
1029: /*
1030: Checks for missing diagonals
1031: */
1034: PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool *missing,PetscInt *d)
1035: {
1036: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1038: PetscInt *diag,*ii = a->i,i;
1041: MatMarkDiagonal_SeqBAIJ(A);
1042: *missing = PETSC_FALSE;
1043: if (A->rmap->n > 0 && !ii) {
1044: *missing = PETSC_TRUE;
1045: if (d) *d = 0;
1046: PetscInfo(A,"Matrix has no entries therefore is missing diagonal");
1047: } else {
1048: diag = a->diag;
1049: for (i=0; i<a->mbs; i++) {
1050: if (diag[i] >= ii[i+1]) {
1051: *missing = PETSC_TRUE;
1052: if (d) *d = i;
1053: PetscInfo1(A,"Matrix is missing block diagonal number %D",i);
1054: break;
1055: }
1056: }
1057: }
1058: return(0);
1059: }
1063: PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A)
1064: {
1065: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1067: PetscInt i,j,m = a->mbs;
1070: if (!a->diag) {
1071: PetscMalloc1(m,&a->diag);
1072: PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));
1073: a->free_diag = PETSC_TRUE;
1074: }
1075: for (i=0; i<m; i++) {
1076: a->diag[i] = a->i[i+1];
1077: for (j=a->i[i]; j<a->i[i+1]; j++) {
1078: if (a->j[j] == i) {
1079: a->diag[i] = j;
1080: break;
1081: }
1082: }
1083: }
1084: return(0);
1085: }
1090: static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool *done)
1091: {
1092: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1094: PetscInt i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt;
1095: PetscInt **ia = (PetscInt**)inia,**ja = (PetscInt**)inja;
1098: *nn = n;
1099: if (!ia) return(0);
1100: if (symmetric) {
1101: MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,0,0,&tia,&tja);
1102: nz = tia[n];
1103: } else {
1104: tia = a->i; tja = a->j;
1105: }
1107: if (!blockcompressed && bs > 1) {
1108: (*nn) *= bs;
1109: /* malloc & create the natural set of indices */
1110: PetscMalloc1((n+1)*bs,ia);
1111: if (n) {
1112: (*ia)[0] = 0;
1113: for (j=1; j<bs; j++) {
1114: (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1];
1115: }
1116: }
1118: for (i=1; i<n; i++) {
1119: (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1];
1120: for (j=1; j<bs; j++) {
1121: (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1];
1122: }
1123: }
1124: if (n) {
1125: (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1];
1126: }
1128: if (inja) {
1129: PetscMalloc1(nz*bs*bs,ja);
1130: cnt = 0;
1131: for (i=0; i<n; i++) {
1132: for (j=0; j<bs; j++) {
1133: for (k=tia[i]; k<tia[i+1]; k++) {
1134: for (l=0; l<bs; l++) {
1135: (*ja)[cnt++] = bs*tja[k] + l;
1136: }
1137: }
1138: }
1139: }
1140: }
1142: if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
1143: PetscFree(tia);
1144: PetscFree(tja);
1145: }
1146: } else if (oshift == 1) {
1147: if (symmetric) {
1148: nz = tia[A->rmap->n/bs];
1149: /* add 1 to i and j indices */
1150: for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1;
1151: *ia = tia;
1152: if (ja) {
1153: for (i=0; i<nz; i++) tja[i] = tja[i] + 1;
1154: *ja = tja;
1155: }
1156: } else {
1157: nz = a->i[A->rmap->n/bs];
1158: /* malloc space and add 1 to i and j indices */
1159: PetscMalloc1((A->rmap->n/bs+1),ia);
1160: for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1;
1161: if (ja) {
1162: PetscMalloc1(nz,ja);
1163: for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1;
1164: }
1165: }
1166: } else {
1167: *ia = tia;
1168: if (ja) *ja = tja;
1169: }
1170: return(0);
1171: }
1175: static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done)
1176: {
1180: if (!ia) return(0);
1181: if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
1182: PetscFree(*ia);
1183: if (ja) {PetscFree(*ja);}
1184: }
1185: return(0);
1186: }
1190: PetscErrorCode MatDestroy_SeqBAIJ(Mat A)
1191: {
1192: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1196: #if defined(PETSC_USE_LOG)
1197: PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz);
1198: #endif
1199: MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
1200: ISDestroy(&a->row);
1201: ISDestroy(&a->col);
1202: if (a->free_diag) {PetscFree(a->diag);}
1203: PetscFree(a->idiag);
1204: if (a->free_imax_ilen) {PetscFree2(a->imax,a->ilen);}
1205: PetscFree(a->solve_work);
1206: PetscFree(a->mult_work);
1207: PetscFree(a->sor_work);
1208: ISDestroy(&a->icol);
1209: PetscFree(a->saved_values);
1210: PetscFree(a->xtoy);
1211: PetscFree2(a->compressedrow.i,a->compressedrow.rindex);
1213: MatDestroy(&a->sbaijMat);
1214: MatDestroy(&a->parent);
1215: PetscFree(A->data);
1217: PetscObjectChangeTypeName((PetscObject)A,0);
1218: PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);
1219: PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);
1220: PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);
1221: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);
1222: PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);
1223: PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);
1224: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);
1225: PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);
1226: PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);
1227: PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);
1228: return(0);
1229: }
1233: PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg)
1234: {
1235: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1239: switch (op) {
1240: case MAT_ROW_ORIENTED:
1241: a->roworiented = flg;
1242: break;
1243: case MAT_KEEP_NONZERO_PATTERN:
1244: a->keepnonzeropattern = flg;
1245: break;
1246: case MAT_NEW_NONZERO_LOCATIONS:
1247: a->nonew = (flg ? 0 : 1);
1248: break;
1249: case MAT_NEW_NONZERO_LOCATION_ERR:
1250: a->nonew = (flg ? -1 : 0);
1251: break;
1252: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1253: a->nonew = (flg ? -2 : 0);
1254: break;
1255: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1256: a->nounused = (flg ? -1 : 0);
1257: break;
1258: case MAT_NEW_DIAGONALS:
1259: case MAT_IGNORE_OFF_PROC_ENTRIES:
1260: case MAT_USE_HASH_TABLE:
1261: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1262: break;
1263: case MAT_SPD:
1264: case MAT_SYMMETRIC:
1265: case MAT_STRUCTURALLY_SYMMETRIC:
1266: case MAT_HERMITIAN:
1267: case MAT_SYMMETRY_ETERNAL:
1268: /* These options are handled directly by MatSetOption() */
1269: break;
1270: default:
1271: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1272: }
1273: return(0);
1274: }
1276: /* used for both SeqBAIJ and SeqSBAIJ matrices */
1279: PetscErrorCode MatGetRow_SeqBAIJ_private(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v,PetscInt *ai,PetscInt *aj,PetscScalar *aa)
1280: {
1282: PetscInt itmp,i,j,k,M,bn,bp,*idx_i,bs,bs2;
1283: MatScalar *aa_i;
1284: PetscScalar *v_i;
1287: bs = A->rmap->bs;
1288: bs2 = bs*bs;
1289: if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row);
1291: bn = row/bs; /* Block number */
1292: bp = row % bs; /* Block Position */
1293: M = ai[bn+1] - ai[bn];
1294: *nz = bs*M;
1296: if (v) {
1297: *v = 0;
1298: if (*nz) {
1299: PetscMalloc1((*nz),v);
1300: for (i=0; i<M; i++) { /* for each block in the block row */
1301: v_i = *v + i*bs;
1302: aa_i = aa + bs2*(ai[bn] + i);
1303: for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j];
1304: }
1305: }
1306: }
1308: if (idx) {
1309: *idx = 0;
1310: if (*nz) {
1311: PetscMalloc1((*nz),idx);
1312: for (i=0; i<M; i++) { /* for each block in the block row */
1313: idx_i = *idx + i*bs;
1314: itmp = bs*aj[ai[bn] + i];
1315: for (j=0; j<bs; j++) idx_i[j] = itmp++;
1316: }
1317: }
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:
1330: MatGetRow_SeqBAIJ_private(A,row,nz,idx,v,a->i,a->j,a->a);
1331: return(0);
1332: }
1336: PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1337: {
1341: if (idx) {PetscFree(*idx);}
1342: if (v) {PetscFree(*v);}
1343: return(0);
1344: }
1346: extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
1350: PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B)
1351: {
1352: Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data;
1353: Mat C;
1355: PetscInt i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col;
1356: PetscInt *rows,*cols,bs2=a->bs2;
1357: MatScalar *array;
1360: if (reuse == MAT_REUSE_MATRIX && A == *B && mbs != nbs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1361: if (reuse == MAT_INITIAL_MATRIX || A == *B) {
1362: PetscCalloc1((1+nbs),&col);
1364: for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1;
1365: MatCreate(PetscObjectComm((PetscObject)A),&C);
1366: MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);
1367: MatSetType(C,((PetscObject)A)->type_name);
1368: MatSeqBAIJSetPreallocation_SeqBAIJ(C,bs,0,col);
1369: PetscFree(col);
1370: } else {
1371: C = *B;
1372: }
1374: array = a->a;
1375: PetscMalloc2(bs,&rows,bs,&cols);
1376: for (i=0; i<mbs; i++) {
1377: cols[0] = i*bs;
1378: for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1;
1379: len = ai[i+1] - ai[i];
1380: for (j=0; j<len; j++) {
1381: rows[0] = (*aj++)*bs;
1382: for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1;
1383: MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);
1384: array += bs2;
1385: }
1386: }
1387: PetscFree2(rows,cols);
1389: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
1390: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
1392: if (reuse == MAT_INITIAL_MATRIX || *B != A) {
1393: *B = C;
1394: } else {
1395: MatHeaderMerge(A,C);
1396: }
1397: return(0);
1398: }
1402: PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f)
1403: {
1405: Mat Btrans;
1408: *f = PETSC_FALSE;
1409: MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);
1410: MatEqual_SeqBAIJ(B,Btrans,f);
1411: MatDestroy(&Btrans);
1412: return(0);
1413: }
1417: static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer)
1418: {
1419: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1421: PetscInt i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2;
1422: int fd;
1423: PetscScalar *aa;
1424: FILE *file;
1427: PetscViewerBinaryGetDescriptor(viewer,&fd);
1428: PetscMalloc1((4+A->rmap->N),&col_lens);
1429: col_lens[0] = MAT_FILE_CLASSID;
1431: col_lens[1] = A->rmap->N;
1432: col_lens[2] = A->cmap->n;
1433: col_lens[3] = a->nz*bs2;
1435: /* store lengths of each row and write (including header) to file */
1436: count = 0;
1437: for (i=0; i<a->mbs; i++) {
1438: for (j=0; j<bs; j++) {
1439: col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]);
1440: }
1441: }
1442: PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);
1443: PetscFree(col_lens);
1445: /* store column indices (zero start index) */
1446: PetscMalloc1((a->nz+1)*bs2,&jj);
1447: count = 0;
1448: for (i=0; i<a->mbs; i++) {
1449: for (j=0; j<bs; j++) {
1450: for (k=a->i[i]; k<a->i[i+1]; k++) {
1451: for (l=0; l<bs; l++) {
1452: jj[count++] = bs*a->j[k] + l;
1453: }
1454: }
1455: }
1456: }
1457: PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);
1458: PetscFree(jj);
1460: /* store nonzero values */
1461: PetscMalloc1((a->nz+1)*bs2,&aa);
1462: count = 0;
1463: for (i=0; i<a->mbs; i++) {
1464: for (j=0; j<bs; j++) {
1465: for (k=a->i[i]; k<a->i[i+1]; k++) {
1466: for (l=0; l<bs; l++) {
1467: aa[count++] = a->a[bs2*k + l*bs + j];
1468: }
1469: }
1470: }
1471: }
1472: PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);
1473: PetscFree(aa);
1475: PetscViewerBinaryGetInfoPointer(viewer,&file);
1476: if (file) {
1477: fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs);
1478: }
1479: return(0);
1480: }
1484: static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer)
1485: {
1486: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1487: PetscErrorCode ierr;
1488: PetscInt i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
1489: PetscViewerFormat format;
1492: PetscViewerGetFormat(viewer,&format);
1493: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1494: PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);
1495: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
1496: Mat aij;
1497: MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
1498: MatView(aij,viewer);
1499: MatDestroy(&aij);
1500: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1501: return(0);
1502: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
1503: PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1504: for (i=0; i<a->mbs; i++) {
1505: for (j=0; j<bs; j++) {
1506: PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
1507: for (k=a->i[i]; k<a->i[i+1]; k++) {
1508: for (l=0; l<bs; l++) {
1509: #if defined(PETSC_USE_COMPLEX)
1510: if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1511: PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l,
1512: (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1513: } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1514: PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l,
1515: (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1516: } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1517: PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
1518: }
1519: #else
1520: if (a->a[bs2*k + l*bs + j] != 0.0) {
1521: PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
1522: }
1523: #endif
1524: }
1525: }
1526: PetscViewerASCIIPrintf(viewer,"\n");
1527: }
1528: }
1529: PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1530: } else {
1531: PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1532: for (i=0; i<a->mbs; i++) {
1533: for (j=0; j<bs; j++) {
1534: PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
1535: for (k=a->i[i]; k<a->i[i+1]; k++) {
1536: for (l=0; l<bs; l++) {
1537: #if defined(PETSC_USE_COMPLEX)
1538: if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
1539: PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l,
1540: (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1541: } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
1542: PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l,
1543: (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1544: } else {
1545: PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
1546: }
1547: #else
1548: PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
1549: #endif
1550: }
1551: }
1552: PetscViewerASCIIPrintf(viewer,"\n");
1553: }
1554: }
1555: PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1556: }
1557: PetscViewerFlush(viewer);
1558: return(0);
1559: }
1561: #include <petscdraw.h>
1564: static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
1565: {
1566: Mat A = (Mat) Aa;
1567: Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data;
1568: PetscErrorCode ierr;
1569: PetscInt row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
1570: PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r;
1571: MatScalar *aa;
1572: PetscViewer viewer;
1573: PetscViewerFormat format;
1576: PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
1577: PetscViewerGetFormat(viewer,&format);
1579: PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);
1581: /* loop over matrix elements drawing boxes */
1583: if (format != PETSC_VIEWER_DRAW_CONTOUR) {
1584: color = PETSC_DRAW_BLUE;
1585: for (i=0,row=0; i<mbs; i++,row+=bs) {
1586: for (j=a->i[i]; j<a->i[i+1]; j++) {
1587: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1588: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1589: aa = a->a + j*bs2;
1590: for (k=0; k<bs; k++) {
1591: for (l=0; l<bs; l++) {
1592: if (PetscRealPart(*aa++) >= 0.) continue;
1593: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1594: }
1595: }
1596: }
1597: }
1598: color = PETSC_DRAW_CYAN;
1599: for (i=0,row=0; i<mbs; i++,row+=bs) {
1600: for (j=a->i[i]; j<a->i[i+1]; j++) {
1601: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1602: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1603: aa = a->a + j*bs2;
1604: for (k=0; k<bs; k++) {
1605: for (l=0; l<bs; l++) {
1606: if (PetscRealPart(*aa++) != 0.) continue;
1607: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1608: }
1609: }
1610: }
1611: }
1612: color = PETSC_DRAW_RED;
1613: for (i=0,row=0; i<mbs; i++,row+=bs) {
1614: for (j=a->i[i]; j<a->i[i+1]; j++) {
1615: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1616: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1617: aa = a->a + j*bs2;
1618: for (k=0; k<bs; k++) {
1619: for (l=0; l<bs; l++) {
1620: if (PetscRealPart(*aa++) <= 0.) continue;
1621: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1622: }
1623: }
1624: }
1625: }
1626: } else {
1627: /* use contour shading to indicate magnitude of values */
1628: /* first determine max of all nonzero values */
1629: PetscDraw popup;
1630: PetscReal scale,maxv = 0.0;
1632: for (i=0; i<a->nz*a->bs2; i++) {
1633: if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]);
1634: }
1635: scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv;
1636: PetscDrawGetPopup(draw,&popup);
1637: if (popup) {
1638: PetscDrawScalePopup(popup,0.0,maxv);
1639: }
1640: for (i=0,row=0; i<mbs; i++,row+=bs) {
1641: for (j=a->i[i]; j<a->i[i+1]; j++) {
1642: y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1643: x_l = a->j[j]*bs; x_r = x_l + 1.0;
1644: aa = a->a + j*bs2;
1645: for (k=0; k<bs; k++) {
1646: for (l=0; l<bs; l++) {
1647: color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(*aa++));
1648: PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1649: }
1650: }
1651: }
1652: }
1653: }
1654: return(0);
1655: }
1659: static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer)
1660: {
1662: PetscReal xl,yl,xr,yr,w,h;
1663: PetscDraw draw;
1664: PetscBool isnull;
1667: PetscViewerDrawGetDraw(viewer,0,&draw);
1668: PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
1670: PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
1671: xr = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
1672: xr += w; yr += h; xl = -w; yl = -h;
1673: PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
1674: PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);
1675: PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
1676: return(0);
1677: }
1681: PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer)
1682: {
1684: PetscBool iascii,isbinary,isdraw;
1687: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1688: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1689: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1690: if (iascii) {
1691: MatView_SeqBAIJ_ASCII(A,viewer);
1692: } else if (isbinary) {
1693: MatView_SeqBAIJ_Binary(A,viewer);
1694: } else if (isdraw) {
1695: MatView_SeqBAIJ_Draw(A,viewer);
1696: } else {
1697: Mat B;
1698: MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
1699: MatView(B,viewer);
1700: MatDestroy(&B);
1701: }
1702: return(0);
1703: }
1708: PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
1709: {
1710: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1711: PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
1712: PetscInt *ai = a->i,*ailen = a->ilen;
1713: PetscInt brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
1714: MatScalar *ap,*aa = a->a;
1717: for (k=0; k<m; k++) { /* loop over rows */
1718: row = im[k]; brow = row/bs;
1719: if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
1720: if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row);
1721: rp = aj + ai[brow]; ap = aa + bs2*ai[brow];
1722: nrow = ailen[brow];
1723: for (l=0; l<n; l++) { /* loop over columns */
1724: if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
1725: if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]);
1726: col = in[l];
1727: bcol = col/bs;
1728: cidx = col%bs;
1729: ridx = row%bs;
1730: high = nrow;
1731: low = 0; /* assume unsorted */
1732: while (high-low > 5) {
1733: t = (low+high)/2;
1734: if (rp[t] > bcol) high = t;
1735: else low = t;
1736: }
1737: for (i=low; i<high; i++) {
1738: if (rp[i] > bcol) break;
1739: if (rp[i] == bcol) {
1740: *v++ = ap[bs2*i+bs*cidx+ridx];
1741: goto finished;
1742: }
1743: }
1744: *v++ = 0.0;
1745: finished:;
1746: }
1747: }
1748: return(0);
1749: }
1753: PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
1754: {
1755: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1756: PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
1757: PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen;
1758: PetscErrorCode ierr;
1759: PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
1760: PetscBool roworiented=a->roworiented;
1761: const PetscScalar *value = v;
1762: MatScalar *ap,*aa = a->a,*bap;
1765: if (roworiented) {
1766: stepval = (n-1)*bs;
1767: } else {
1768: stepval = (m-1)*bs;
1769: }
1770: for (k=0; k<m; k++) { /* loop over added rows */
1771: row = im[k];
1772: if (row < 0) continue;
1773: #if defined(PETSC_USE_DEBUG)
1774: if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1);
1775: #endif
1776: rp = aj + ai[row];
1777: ap = aa + bs2*ai[row];
1778: rmax = imax[row];
1779: nrow = ailen[row];
1780: low = 0;
1781: high = nrow;
1782: for (l=0; l<n; l++) { /* loop over added columns */
1783: if (in[l] < 0) continue;
1784: #if defined(PETSC_USE_DEBUG)
1785: if (in[l] >= a->nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],a->nbs-1);
1786: #endif
1787: col = in[l];
1788: if (roworiented) {
1789: value = v + (k*(stepval+bs) + l)*bs;
1790: } else {
1791: value = v + (l*(stepval+bs) + k)*bs;
1792: }
1793: if (col <= lastcol) low = 0;
1794: else high = nrow;
1795: lastcol = col;
1796: while (high-low > 7) {
1797: t = (low+high)/2;
1798: if (rp[t] > col) high = t;
1799: else low = t;
1800: }
1801: for (i=low; i<high; i++) {
1802: if (rp[i] > col) break;
1803: if (rp[i] == col) {
1804: bap = ap + bs2*i;
1805: if (roworiented) {
1806: if (is == ADD_VALUES) {
1807: for (ii=0; ii<bs; ii++,value+=stepval) {
1808: for (jj=ii; jj<bs2; jj+=bs) {
1809: bap[jj] += *value++;
1810: }
1811: }
1812: } else {
1813: for (ii=0; ii<bs; ii++,value+=stepval) {
1814: for (jj=ii; jj<bs2; jj+=bs) {
1815: bap[jj] = *value++;
1816: }
1817: }
1818: }
1819: } else {
1820: if (is == ADD_VALUES) {
1821: for (ii=0; ii<bs; ii++,value+=bs+stepval) {
1822: for (jj=0; jj<bs; jj++) {
1823: bap[jj] += value[jj];
1824: }
1825: bap += bs;
1826: }
1827: } else {
1828: for (ii=0; ii<bs; ii++,value+=bs+stepval) {
1829: for (jj=0; jj<bs; jj++) {
1830: bap[jj] = value[jj];
1831: }
1832: bap += bs;
1833: }
1834: }
1835: }
1836: goto noinsert2;
1837: }
1838: }
1839: if (nonew == 1) goto noinsert2;
1840: if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
1841: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
1842: N = nrow++ - 1; high++;
1843: /* shift up all the later entries in this row */
1844: for (ii=N; ii>=i; ii--) {
1845: rp[ii+1] = rp[ii];
1846: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
1847: }
1848: if (N >= i) {
1849: PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
1850: }
1851: rp[i] = col;
1852: bap = ap + bs2*i;
1853: if (roworiented) {
1854: for (ii=0; ii<bs; ii++,value+=stepval) {
1855: for (jj=ii; jj<bs2; jj+=bs) {
1856: bap[jj] = *value++;
1857: }
1858: }
1859: } else {
1860: for (ii=0; ii<bs; ii++,value+=stepval) {
1861: for (jj=0; jj<bs; jj++) {
1862: *bap++ = *value++;
1863: }
1864: }
1865: }
1866: noinsert2:;
1867: low = i;
1868: }
1869: ailen[row] = nrow;
1870: }
1871: return(0);
1872: }
1876: PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode)
1877: {
1878: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1879: PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
1880: PetscInt m = A->rmap->N,*ip,N,*ailen = a->ilen;
1882: PetscInt mbs = a->mbs,bs2 = a->bs2,rmax = 0;
1883: MatScalar *aa = a->a,*ap;
1884: PetscReal ratio=0.6;
1887: if (mode == MAT_FLUSH_ASSEMBLY) return(0);
1889: if (m) rmax = ailen[0];
1890: for (i=1; i<mbs; i++) {
1891: /* move each row back by the amount of empty slots (fshift) before it*/
1892: fshift += imax[i-1] - ailen[i-1];
1893: rmax = PetscMax(rmax,ailen[i]);
1894: if (fshift) {
1895: ip = aj + ai[i]; ap = aa + bs2*ai[i];
1896: N = ailen[i];
1897: for (j=0; j<N; j++) {
1898: ip[j-fshift] = ip[j];
1900: PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));
1901: }
1902: }
1903: ai[i] = ai[i-1] + ailen[i-1];
1904: }
1905: if (mbs) {
1906: fshift += imax[mbs-1] - ailen[mbs-1];
1907: ai[mbs] = ai[mbs-1] + ailen[mbs-1];
1908: }
1910: /* reset ilen and imax for each row */
1911: a->nonzerorowcnt = 0;
1912: for (i=0; i<mbs; i++) {
1913: ailen[i] = imax[i] = ai[i+1] - ai[i];
1914: a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0);
1915: }
1916: a->nz = ai[mbs];
1918: /* diagonals may have moved, so kill the diagonal pointers */
1919: a->idiagvalid = PETSC_FALSE;
1920: if (fshift && a->diag) {
1921: PetscFree(a->diag);
1922: PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));
1923: a->diag = 0;
1924: }
1925: if (fshift && a->nounused == -1) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2);
1926: 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);
1927: PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);
1928: PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);
1930: A->info.mallocs += a->reallocs;
1931: a->reallocs = 0;
1932: A->info.nz_unneeded = (PetscReal)fshift*bs2;
1934: MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,mbs,ratio);
1935: return(0);
1936: }
1938: /*
1939: This function returns an array of flags which indicate the locations of contiguous
1940: blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9]
1941: then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)]
1942: Assume: sizes should be long enough to hold all the values.
1943: */
1946: static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
1947: {
1948: PetscInt i,j,k,row;
1949: PetscBool flg;
1952: for (i=0,j=0; i<n; j++) {
1953: row = idx[i];
1954: if (row%bs!=0) { /* Not the begining of a block */
1955: sizes[j] = 1;
1956: i++;
1957: } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */
1958: sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */
1959: i++;
1960: } else { /* Begining of the block, so check if the complete block exists */
1961: flg = PETSC_TRUE;
1962: for (k=1; k<bs; k++) {
1963: if (row+k != idx[i+k]) { /* break in the block */
1964: flg = PETSC_FALSE;
1965: break;
1966: }
1967: }
1968: if (flg) { /* No break in the bs */
1969: sizes[j] = bs;
1970: i += bs;
1971: } else {
1972: sizes[j] = 1;
1973: i++;
1974: }
1975: }
1976: }
1977: *bs_max = j;
1978: return(0);
1979: }
1983: PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
1984: {
1985: Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data;
1986: PetscErrorCode ierr;
1987: PetscInt i,j,k,count,*rows;
1988: PetscInt bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max;
1989: PetscScalar zero = 0.0;
1990: MatScalar *aa;
1991: const PetscScalar *xx;
1992: PetscScalar *bb;
1995: /* fix right hand side if needed */
1996: if (x && b) {
1997: VecGetArrayRead(x,&xx);
1998: VecGetArray(b,&bb);
1999: for (i=0; i<is_n; i++) {
2000: bb[is_idx[i]] = diag*xx[is_idx[i]];
2001: }
2002: VecRestoreArrayRead(x,&xx);
2003: VecRestoreArray(b,&bb);
2004: }
2006: /* Make a copy of the IS and sort it */
2007: /* allocate memory for rows,sizes */
2008: PetscMalloc2(is_n,&rows,2*is_n,&sizes);
2010: /* copy IS values to rows, and sort them */
2011: for (i=0; i<is_n; i++) rows[i] = is_idx[i];
2012: PetscSortInt(is_n,rows);
2014: if (baij->keepnonzeropattern) {
2015: for (i=0; i<is_n; i++) sizes[i] = 1;
2016: bs_max = is_n;
2017: } else {
2018: MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);
2019: A->nonzerostate++;
2020: }
2022: for (i=0,j=0; i<bs_max; j+=sizes[i],i++) {
2023: row = rows[j];
2024: if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row);
2025: count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
2026: aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
2027: if (sizes[i] == bs && !baij->keepnonzeropattern) {
2028: if (diag != (PetscScalar)0.0) {
2029: if (baij->ilen[row/bs] > 0) {
2030: baij->ilen[row/bs] = 1;
2031: baij->j[baij->i[row/bs]] = row/bs;
2033: PetscMemzero(aa,count*bs*sizeof(MatScalar));
2034: }
2035: /* Now insert all the diagonal values for this bs */
2036: for (k=0; k<bs; k++) {
2037: (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);
2038: }
2039: } else { /* (diag == 0.0) */
2040: baij->ilen[row/bs] = 0;
2041: } /* end (diag == 0.0) */
2042: } else { /* (sizes[i] != bs) */
2043: #if defined(PETSC_USE_DEBUG)
2044: if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1");
2045: #endif
2046: for (k=0; k<count; k++) {
2047: aa[0] = zero;
2048: aa += bs;
2049: }
2050: if (diag != (PetscScalar)0.0) {
2051: (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);
2052: }
2053: }
2054: }
2056: PetscFree2(rows,sizes);
2057: MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
2058: return(0);
2059: }
2063: PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
2064: {
2065: Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data;
2066: PetscErrorCode ierr;
2067: PetscInt i,j,k,count;
2068: PetscInt bs =A->rmap->bs,bs2=baij->bs2,row,col;
2069: PetscScalar zero = 0.0;
2070: MatScalar *aa;
2071: const PetscScalar *xx;
2072: PetscScalar *bb;
2073: PetscBool *zeroed,vecs = PETSC_FALSE;
2076: /* fix right hand side if needed */
2077: if (x && b) {
2078: VecGetArrayRead(x,&xx);
2079: VecGetArray(b,&bb);
2080: vecs = PETSC_TRUE;
2081: }
2083: /* zero the columns */
2084: PetscCalloc1(A->rmap->n,&zeroed);
2085: for (i=0; i<is_n; i++) {
2086: if (is_idx[i] < 0 || is_idx[i] >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",is_idx[i]);
2087: zeroed[is_idx[i]] = PETSC_TRUE;
2088: }
2089: for (i=0; i<A->rmap->N; i++) {
2090: if (!zeroed[i]) {
2091: row = i/bs;
2092: for (j=baij->i[row]; j<baij->i[row+1]; j++) {
2093: for (k=0; k<bs; k++) {
2094: col = bs*baij->j[j] + k;
2095: if (zeroed[col]) {
2096: aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
2097: if (vecs) bb[i] -= aa[0]*xx[col];
2098: aa[0] = 0.0;
2099: }
2100: }
2101: }
2102: } else if (vecs) bb[i] = diag*xx[i];
2103: }
2104: PetscFree(zeroed);
2105: if (vecs) {
2106: VecRestoreArrayRead(x,&xx);
2107: VecRestoreArray(b,&bb);
2108: }
2110: /* zero the rows */
2111: for (i=0; i<is_n; i++) {
2112: row = is_idx[i];
2113: count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
2114: aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
2115: for (k=0; k<count; k++) {
2116: aa[0] = zero;
2117: aa += bs;
2118: }
2119: if (diag != (PetscScalar)0.0) {
2120: (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);
2121: }
2122: }
2123: MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
2124: return(0);
2125: }
2129: PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
2130: {
2131: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2132: PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
2133: PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen;
2134: PetscInt *aj =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
2136: PetscInt ridx,cidx,bs2=a->bs2;
2137: PetscBool roworiented=a->roworiented;
2138: MatScalar *ap,value,*aa=a->a,*bap;
2141: for (k=0; k<m; k++) { /* loop over added rows */
2142: row = im[k];
2143: brow = row/bs;
2144: if (row < 0) continue;
2145: #if defined(PETSC_USE_DEBUG)
2146: if (row >= A->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
2147: #endif
2148: rp = aj + ai[brow];
2149: ap = aa + bs2*ai[brow];
2150: rmax = imax[brow];
2151: nrow = ailen[brow];
2152: low = 0;
2153: high = nrow;
2154: for (l=0; l<n; l++) { /* loop over added columns */
2155: if (in[l] < 0) continue;
2156: #if defined(PETSC_USE_DEBUG)
2157: if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1);
2158: #endif
2159: col = in[l]; bcol = col/bs;
2160: ridx = row % bs; cidx = col % bs;
2161: if (roworiented) {
2162: value = v[l + k*n];
2163: } else {
2164: value = v[k + l*m];
2165: }
2166: if (col <= lastcol) low = 0; else high = nrow;
2167: lastcol = col;
2168: while (high-low > 7) {
2169: t = (low+high)/2;
2170: if (rp[t] > bcol) high = t;
2171: else low = t;
2172: }
2173: for (i=low; i<high; i++) {
2174: if (rp[i] > bcol) break;
2175: if (rp[i] == bcol) {
2176: bap = ap + bs2*i + bs*cidx + ridx;
2177: if (is == ADD_VALUES) *bap += value;
2178: else *bap = value;
2179: goto noinsert1;
2180: }
2181: }
2182: if (nonew == 1) goto noinsert1;
2183: if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
2184: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
2185: N = nrow++ - 1; high++;
2186: /* shift up all the later entries in this row */
2187: for (ii=N; ii>=i; ii--) {
2188: rp[ii+1] = rp[ii];
2189: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
2190: }
2191: if (N>=i) {
2192: PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
2193: }
2194: rp[i] = bcol;
2195: ap[bs2*i + bs*cidx + ridx] = value;
2196: a->nz++;
2197: A->nonzerostate++;
2198: noinsert1:;
2199: low = i;
2200: }
2201: ailen[brow] = nrow;
2202: }
2203: return(0);
2204: }
2208: PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info)
2209: {
2210: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inA->data;
2211: Mat outA;
2213: PetscBool row_identity,col_identity;
2216: if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU");
2217: ISIdentity(row,&row_identity);
2218: ISIdentity(col,&col_identity);
2219: if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU");
2221: outA = inA;
2222: inA->factortype = MAT_FACTOR_LU;
2224: MatMarkDiagonal_SeqBAIJ(inA);
2226: PetscObjectReference((PetscObject)row);
2227: ISDestroy(&a->row);
2228: a->row = row;
2229: PetscObjectReference((PetscObject)col);
2230: ISDestroy(&a->col);
2231: a->col = col;
2233: /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */
2234: ISDestroy(&a->icol);
2235: ISInvertPermutation(col,PETSC_DECIDE,&a->icol);
2236: PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);
2238: MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));
2239: if (!a->solve_work) {
2240: PetscMalloc1((inA->rmap->N+inA->rmap->bs),&a->solve_work);
2241: PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
2242: }
2243: MatLUFactorNumeric(outA,inA,info);
2244: return(0);
2245: }
2249: PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices)
2250: {
2251: Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data;
2252: PetscInt i,nz,mbs;
2255: nz = baij->maxnz;
2256: mbs = baij->mbs;
2257: for (i=0; i<nz; i++) {
2258: baij->j[i] = indices[i];
2259: }
2260: baij->nz = nz;
2261: for (i=0; i<mbs; i++) {
2262: baij->ilen[i] = baij->imax[i];
2263: }
2264: return(0);
2265: }
2269: /*@
2270: MatSeqBAIJSetColumnIndices - Set the column indices for all the rows
2271: in the matrix.
2273: Input Parameters:
2274: + mat - the SeqBAIJ matrix
2275: - indices - the column indices
2277: Level: advanced
2279: Notes:
2280: This can be called if you have precomputed the nonzero structure of the
2281: matrix and want to provide it to the matrix object to improve the performance
2282: of the MatSetValues() operation.
2284: You MUST have set the correct numbers of nonzeros per row in the call to
2285: MatCreateSeqBAIJ(), and the columns indices MUST be sorted.
2287: MUST be called before any calls to MatSetValues();
2289: @*/
2290: PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices)
2291: {
2297: PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));
2298: return(0);
2299: }
2303: PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[])
2304: {
2305: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2307: PetscInt i,j,n,row,bs,*ai,*aj,mbs;
2308: PetscReal atmp;
2309: PetscScalar *x,zero = 0.0;
2310: MatScalar *aa;
2311: PetscInt ncols,brow,krow,kcol;
2314: if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
2315: bs = A->rmap->bs;
2316: aa = a->a;
2317: ai = a->i;
2318: aj = a->j;
2319: mbs = a->mbs;
2321: VecSet(v,zero);
2322: VecGetArray(v,&x);
2323: VecGetLocalSize(v,&n);
2324: if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
2325: for (i=0; i<mbs; i++) {
2326: ncols = ai[1] - ai[0]; ai++;
2327: brow = bs*i;
2328: for (j=0; j<ncols; j++) {
2329: for (kcol=0; kcol<bs; kcol++) {
2330: for (krow=0; krow<bs; krow++) {
2331: atmp = PetscAbsScalar(*aa);aa++;
2332: row = brow + krow; /* row index */
2333: if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;}
2334: }
2335: }
2336: aj++;
2337: }
2338: }
2339: VecRestoreArray(v,&x);
2340: return(0);
2341: }
2345: PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str)
2346: {
2350: /* If the two matrices have the same copy implementation, use fast copy. */
2351: if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
2352: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2353: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)B->data;
2354: PetscInt ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs;
2356: if (a->i[ambs] != b->i[bmbs]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzero blocks in matrices A %D and B %D are different",a->i[ambs],b->i[bmbs]);
2357: if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs);
2358: PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));
2359: } else {
2360: MatCopy_Basic(A,B,str);
2361: }
2362: return(0);
2363: }
2367: PetscErrorCode MatSetUp_SeqBAIJ(Mat A)
2368: {
2372: MatSeqBAIJSetPreallocation_SeqBAIJ(A,A->rmap->bs,PETSC_DEFAULT,0);
2373: return(0);
2374: }
2378: PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[])
2379: {
2380: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2383: *array = a->a;
2384: return(0);
2385: }
2389: PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[])
2390: {
2392: return(0);
2393: }
2397: PetscErrorCode MatAXPYGetPreallocation_SeqBAIJ(Mat Y,Mat X,PetscInt *nnz)
2398: {
2399: PetscInt bs = Y->rmap->bs,mbs = Y->rmap->N/bs;
2400: Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data;
2401: Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data;
2405: /* Set the number of nonzeros in the new matrix */
2406: MatAXPYGetPreallocation_SeqX_private(mbs,x->i,x->j,y->i,y->j,nnz);
2407: return(0);
2408: }
2412: PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2413: {
2414: Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data;
2416: PetscInt i,bs=Y->rmap->bs,j,bs2=bs*bs;
2417: PetscBLASInt one=1;
2420: if (str == SAME_NONZERO_PATTERN) {
2421: PetscScalar alpha = a;
2422: PetscBLASInt bnz;
2423: PetscBLASIntCast(x->nz*bs2,&bnz);
2424: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2425: PetscObjectStateIncrease((PetscObject)Y);
2426: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2427: if (y->xtoy && y->XtoY != X) {
2428: PetscFree(y->xtoy);
2429: MatDestroy(&y->XtoY);
2430: }
2431: if (!y->xtoy) { /* get xtoy */
2432: MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);
2433: y->XtoY = X;
2434: PetscObjectReference((PetscObject)X);
2435: }
2436: for (i=0; i<x->nz; i++) {
2437: j = 0;
2438: while (j < bs2) {
2439: y->a[bs2*y->xtoy[i]+j] += a*(x->a[bs2*i+j]);
2440: j++;
2441: }
2442: }
2443: PetscObjectStateIncrease((PetscObject)Y);
2444: PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %D/%D = %g\n",bs2*x->nz,bs2*y->nz,(double)((PetscReal)(bs2*x->nz)/(bs2*y->nz)));
2445: } else {
2446: Mat B;
2447: PetscInt *nnz;
2448: if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
2449: PetscMalloc1(Y->rmap->N,&nnz);
2450: MatCreate(PetscObjectComm((PetscObject)Y),&B);
2451: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2452: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2453: MatSetBlockSizesFromMats(B,Y,Y);
2454: MatSetType(B,(MatType) ((PetscObject)Y)->type_name);
2455: MatAXPYGetPreallocation_SeqBAIJ(Y,X,nnz);
2456: MatSeqBAIJSetPreallocation(B,bs,0,nnz);
2457: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2458: MatHeaderReplace(Y,B);
2459: PetscFree(nnz);
2460: }
2461: return(0);
2462: }
2466: PetscErrorCode MatRealPart_SeqBAIJ(Mat A)
2467: {
2468: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2469: PetscInt i,nz = a->bs2*a->i[a->mbs];
2470: MatScalar *aa = a->a;
2473: for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
2474: return(0);
2475: }
2479: PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A)
2480: {
2481: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2482: PetscInt i,nz = a->bs2*a->i[a->mbs];
2483: MatScalar *aa = a->a;
2486: for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
2487: return(0);
2488: }
2492: /*
2493: Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code
2494: */
2495: PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done)
2496: {
2497: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2499: PetscInt bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs;
2500: PetscInt nz = a->i[m],row,*jj,mr,col;
2503: *nn = n;
2504: if (!ia) return(0);
2505: if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices");
2506: else {
2507: PetscCalloc1((n+1),&collengths);
2508: PetscMalloc1((n+1),&cia);
2509: PetscMalloc1((nz+1),&cja);
2510: jj = a->j;
2511: for (i=0; i<nz; i++) {
2512: collengths[jj[i]]++;
2513: }
2514: cia[0] = oshift;
2515: for (i=0; i<n; i++) {
2516: cia[i+1] = cia[i] + collengths[i];
2517: }
2518: PetscMemzero(collengths,n*sizeof(PetscInt));
2519: jj = a->j;
2520: for (row=0; row<m; row++) {
2521: mr = a->i[row+1] - a->i[row];
2522: for (i=0; i<mr; i++) {
2523: col = *jj++;
2525: cja[cia[col] + collengths[col]++ - oshift] = row + oshift;
2526: }
2527: }
2528: PetscFree(collengths);
2529: *ia = cia; *ja = cja;
2530: }
2531: return(0);
2532: }
2536: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done)
2537: {
2541: if (!ia) return(0);
2542: PetscFree(*ia);
2543: PetscFree(*ja);
2544: return(0);
2545: }
2547: /*
2548: MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from
2549: MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output
2550: spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate()
2551: */
2554: PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done)
2555: {
2556: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2558: PetscInt i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs;
2559: PetscInt nz = a->i[m],row,*jj,mr,col;
2560: PetscInt *cspidx;
2563: *nn = n;
2564: if (!ia) return(0);
2566: PetscCalloc1((n+1),&collengths);
2567: PetscMalloc1((n+1),&cia);
2568: PetscMalloc1((nz+1),&cja);
2569: PetscMalloc1((nz+1),&cspidx);
2570: jj = a->j;
2571: for (i=0; i<nz; i++) {
2572: collengths[jj[i]]++;
2573: }
2574: cia[0] = oshift;
2575: for (i=0; i<n; i++) {
2576: cia[i+1] = cia[i] + collengths[i];
2577: }
2578: PetscMemzero(collengths,n*sizeof(PetscInt));
2579: jj = a->j;
2580: for (row=0; row<m; row++) {
2581: mr = a->i[row+1] - a->i[row];
2582: for (i=0; i<mr; i++) {
2583: col = *jj++;
2584: cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */
2585: cja[cia[col] + collengths[col]++ - oshift] = row + oshift;
2586: }
2587: }
2588: PetscFree(collengths);
2589: *ia = cia; *ja = cja;
2590: *spidx = cspidx;
2591: return(0);
2592: }
2596: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done)
2597: {
2601: MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);
2602: PetscFree(*spidx);
2603: return(0);
2604: }
2606: /* -------------------------------------------------------------------*/
2607: static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ,
2608: MatGetRow_SeqBAIJ,
2609: MatRestoreRow_SeqBAIJ,
2610: MatMult_SeqBAIJ_N,
2611: /* 4*/ MatMultAdd_SeqBAIJ_N,
2612: MatMultTranspose_SeqBAIJ,
2613: MatMultTransposeAdd_SeqBAIJ,
2614: 0,
2615: 0,
2616: 0,
2617: /* 10*/ 0,
2618: MatLUFactor_SeqBAIJ,
2619: 0,
2620: 0,
2621: MatTranspose_SeqBAIJ,
2622: /* 15*/ MatGetInfo_SeqBAIJ,
2623: MatEqual_SeqBAIJ,
2624: MatGetDiagonal_SeqBAIJ,
2625: MatDiagonalScale_SeqBAIJ,
2626: MatNorm_SeqBAIJ,
2627: /* 20*/ 0,
2628: MatAssemblyEnd_SeqBAIJ,
2629: MatSetOption_SeqBAIJ,
2630: MatZeroEntries_SeqBAIJ,
2631: /* 24*/ MatZeroRows_SeqBAIJ,
2632: 0,
2633: 0,
2634: 0,
2635: 0,
2636: /* 29*/ MatSetUp_SeqBAIJ,
2637: 0,
2638: 0,
2639: 0,
2640: 0,
2641: /* 34*/ MatDuplicate_SeqBAIJ,
2642: 0,
2643: 0,
2644: MatILUFactor_SeqBAIJ,
2645: 0,
2646: /* 39*/ MatAXPY_SeqBAIJ,
2647: MatGetSubMatrices_SeqBAIJ,
2648: MatIncreaseOverlap_SeqBAIJ,
2649: MatGetValues_SeqBAIJ,
2650: MatCopy_SeqBAIJ,
2651: /* 44*/ 0,
2652: MatScale_SeqBAIJ,
2653: 0,
2654: 0,
2655: MatZeroRowsColumns_SeqBAIJ,
2656: /* 49*/ 0,
2657: MatGetRowIJ_SeqBAIJ,
2658: MatRestoreRowIJ_SeqBAIJ,
2659: MatGetColumnIJ_SeqBAIJ,
2660: MatRestoreColumnIJ_SeqBAIJ,
2661: /* 54*/ MatFDColoringCreate_SeqXAIJ,
2662: 0,
2663: 0,
2664: 0,
2665: MatSetValuesBlocked_SeqBAIJ,
2666: /* 59*/ MatGetSubMatrix_SeqBAIJ,
2667: MatDestroy_SeqBAIJ,
2668: MatView_SeqBAIJ,
2669: 0,
2670: 0,
2671: /* 64*/ 0,
2672: 0,
2673: 0,
2674: 0,
2675: 0,
2676: /* 69*/ MatGetRowMaxAbs_SeqBAIJ,
2677: 0,
2678: MatConvert_Basic,
2679: 0,
2680: 0,
2681: /* 74*/ 0,
2682: MatFDColoringApply_BAIJ,
2683: 0,
2684: 0,
2685: 0,
2686: /* 79*/ 0,
2687: 0,
2688: 0,
2689: 0,
2690: MatLoad_SeqBAIJ,
2691: /* 84*/ 0,
2692: 0,
2693: 0,
2694: 0,
2695: 0,
2696: /* 89*/ 0,
2697: 0,
2698: 0,
2699: 0,
2700: 0,
2701: /* 94*/ 0,
2702: 0,
2703: 0,
2704: 0,
2705: 0,
2706: /* 99*/ 0,
2707: 0,
2708: 0,
2709: 0,
2710: 0,
2711: /*104*/ 0,
2712: MatRealPart_SeqBAIJ,
2713: MatImaginaryPart_SeqBAIJ,
2714: 0,
2715: 0,
2716: /*109*/ 0,
2717: 0,
2718: 0,
2719: 0,
2720: MatMissingDiagonal_SeqBAIJ,
2721: /*114*/ 0,
2722: 0,
2723: 0,
2724: 0,
2725: 0,
2726: /*119*/ 0,
2727: 0,
2728: MatMultHermitianTranspose_SeqBAIJ,
2729: MatMultHermitianTransposeAdd_SeqBAIJ,
2730: 0,
2731: /*124*/ 0,
2732: 0,
2733: MatInvertBlockDiagonal_SeqBAIJ,
2734: 0,
2735: 0,
2736: /*129*/ 0,
2737: 0,
2738: 0,
2739: 0,
2740: 0,
2741: /*134*/ 0,
2742: 0,
2743: 0,
2744: 0,
2745: 0,
2746: /*139*/ 0,
2747: 0,
2748: 0,
2749: MatFDColoringSetUp_SeqXAIJ
2750: };
2754: PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat)
2755: {
2756: Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data;
2757: PetscInt nz = aij->i[aij->mbs]*aij->bs2;
2761: if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
2763: /* allocate space for values if not already there */
2764: if (!aij->saved_values) {
2765: PetscMalloc1((nz+1),&aij->saved_values);
2766: PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));
2767: }
2769: /* copy values over */
2770: PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));
2771: return(0);
2772: }
2776: PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat)
2777: {
2778: Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data;
2780: PetscInt nz = aij->i[aij->mbs]*aij->bs2;
2783: if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
2784: if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");
2786: /* copy values over */
2787: PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));
2788: return(0);
2789: }
2791: PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*);
2792: PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*);
2796: PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
2797: {
2798: Mat_SeqBAIJ *b;
2800: PetscInt i,mbs,nbs,bs2;
2801: PetscBool flg,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE;
2804: if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
2805: if (nz == MAT_SKIP_ALLOCATION) {
2806: skipallocation = PETSC_TRUE;
2807: nz = 0;
2808: }
2810: MatSetBlockSize(B,PetscAbs(bs));
2811: PetscLayoutSetUp(B->rmap);
2812: PetscLayoutSetUp(B->cmap);
2813: PetscLayoutGetBlockSize(B->rmap,&bs);
2815: B->preallocated = PETSC_TRUE;
2817: mbs = B->rmap->n/bs;
2818: nbs = B->cmap->n/bs;
2819: bs2 = bs*bs;
2821: if (mbs*bs!=B->rmap->n || nbs*bs!=B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->rmap->N,B->cmap->n,bs);
2823: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
2824: if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz);
2825: if (nnz) {
2826: for (i=0; i<mbs; i++) {
2827: if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]);
2828: if (nnz[i] > nbs) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],nbs);
2829: }
2830: }
2832: b = (Mat_SeqBAIJ*)B->data;
2833: PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");
2834: PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,PETSC_FALSE,&flg,NULL);
2835: PetscOptionsEnd();
2837: if (!flg) {
2838: switch (bs) {
2839: case 1:
2840: B->ops->mult = MatMult_SeqBAIJ_1;
2841: B->ops->multadd = MatMultAdd_SeqBAIJ_1;
2842: break;
2843: case 2:
2844: B->ops->mult = MatMult_SeqBAIJ_2;
2845: B->ops->multadd = MatMultAdd_SeqBAIJ_2;
2846: break;
2847: case 3:
2848: B->ops->mult = MatMult_SeqBAIJ_3;
2849: B->ops->multadd = MatMultAdd_SeqBAIJ_3;
2850: break;
2851: case 4:
2852: B->ops->mult = MatMult_SeqBAIJ_4;
2853: B->ops->multadd = MatMultAdd_SeqBAIJ_4;
2854: break;
2855: case 5:
2856: B->ops->mult = MatMult_SeqBAIJ_5;
2857: B->ops->multadd = MatMultAdd_SeqBAIJ_5;
2858: break;
2859: case 6:
2860: B->ops->mult = MatMult_SeqBAIJ_6;
2861: B->ops->multadd = MatMultAdd_SeqBAIJ_6;
2862: break;
2863: case 7:
2864: B->ops->mult = MatMult_SeqBAIJ_7;
2865: B->ops->multadd = MatMultAdd_SeqBAIJ_7;
2866: break;
2867: case 15:
2868: B->ops->mult = MatMult_SeqBAIJ_15_ver1;
2869: B->ops->multadd = MatMultAdd_SeqBAIJ_N;
2870: break;
2871: default:
2872: B->ops->mult = MatMult_SeqBAIJ_N;
2873: B->ops->multadd = MatMultAdd_SeqBAIJ_N;
2874: break;
2875: }
2876: }
2877: B->ops->sor = MatSOR_SeqBAIJ;
2878: b->mbs = mbs;
2879: b->nbs = nbs;
2880: if (!skipallocation) {
2881: if (!b->imax) {
2882: PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);
2883: PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));
2885: b->free_imax_ilen = PETSC_TRUE;
2886: }
2887: /* b->ilen will count nonzeros in each block row so far. */
2888: for (i=0; i<mbs; i++) b->ilen[i] = 0;
2889: if (!nnz) {
2890: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
2891: else if (nz < 0) nz = 1;
2892: for (i=0; i<mbs; i++) b->imax[i] = nz;
2893: nz = nz*mbs;
2894: } else {
2895: nz = 0;
2896: for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];}
2897: }
2899: /* allocate the matrix space */
2900: MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
2901: PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);
2902: PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
2903: PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));
2904: PetscMemzero(b->j,nz*sizeof(PetscInt));
2906: b->singlemalloc = PETSC_TRUE;
2907: b->i[0] = 0;
2908: for (i=1; i<mbs+1; i++) {
2909: b->i[i] = b->i[i-1] + b->imax[i-1];
2910: }
2911: b->free_a = PETSC_TRUE;
2912: b->free_ij = PETSC_TRUE;
2913: #if defined(PETSC_THREADCOMM_ACTIVE)
2914: MatZeroEntries_SeqBAIJ(B);
2915: #endif
2916: } else {
2917: b->free_a = PETSC_FALSE;
2918: b->free_ij = PETSC_FALSE;
2919: }
2921: b->bs2 = bs2;
2922: b->mbs = mbs;
2923: b->nz = 0;
2924: b->maxnz = nz;
2925: B->info.nz_unneeded = (PetscReal)b->maxnz*bs2;
2926: if (realalloc) {MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);}
2927: return(0);
2928: }
2932: PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2933: {
2934: PetscInt i,m,nz,nz_max=0,*nnz;
2935: PetscScalar *values=0;
2936: PetscBool roworiented = ((Mat_SeqBAIJ*)B->data)->roworiented;
2940: if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2941: PetscLayoutSetBlockSize(B->rmap,bs);
2942: PetscLayoutSetBlockSize(B->cmap,bs);
2943: PetscLayoutSetUp(B->rmap);
2944: PetscLayoutSetUp(B->cmap);
2945: PetscLayoutGetBlockSize(B->rmap,&bs);
2946: m = B->rmap->n/bs;
2948: if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]);
2949: PetscMalloc1((m+1), &nnz);
2950: for (i=0; i<m; i++) {
2951: nz = ii[i+1]- ii[i];
2952: if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz);
2953: nz_max = PetscMax(nz_max, nz);
2954: nnz[i] = nz;
2955: }
2956: MatSeqBAIJSetPreallocation(B,bs,0,nnz);
2957: PetscFree(nnz);
2959: values = (PetscScalar*)V;
2960: if (!values) {
2961: PetscCalloc1(bs*bs*(nz_max+1),&values);
2962: }
2963: for (i=0; i<m; i++) {
2964: PetscInt ncols = ii[i+1] - ii[i];
2965: const PetscInt *icols = jj + ii[i];
2966: const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2967: if (!roworiented) {
2968: MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);
2969: } else {
2970: PetscInt j;
2971: for (j=0; j<ncols; j++) {
2972: const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2973: MatSetValuesBlocked_SeqBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);
2974: }
2975: }
2976: }
2977: if (!V) { PetscFree(values); }
2978: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2979: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2980: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2981: return(0);
2982: }
2984: PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_petsc(Mat,MatFactorType,Mat*);
2985: PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_bstrm(Mat,MatFactorType,Mat*);
2986: #if defined(PETSC_HAVE_MUMPS)
2987: PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*);
2988: #endif
2989: extern PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat,MatFactorType,PetscBool*);
2991: /*MC
2992: MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on
2993: block sparse compressed row format.
2995: Options Database Keys:
2996: . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions()
2998: Level: beginner
3000: .seealso: MatCreateSeqBAIJ()
3001: M*/
3003: PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*);
3007: PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B)
3008: {
3010: PetscMPIInt size;
3011: Mat_SeqBAIJ *b;
3014: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
3015: if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1");
3017: PetscNewLog(B,&b);
3018: B->data = (void*)b;
3019: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
3021: b->row = 0;
3022: b->col = 0;
3023: b->icol = 0;
3024: b->reallocs = 0;
3025: b->saved_values = 0;
3027: b->roworiented = PETSC_TRUE;
3028: b->nonew = 0;
3029: b->diag = 0;
3030: b->solve_work = 0;
3031: b->mult_work = 0;
3032: B->spptr = 0;
3033: B->info.nz_unneeded = (PetscReal)b->maxnz*b->bs2;
3034: b->keepnonzeropattern = PETSC_FALSE;
3035: b->xtoy = 0;
3036: b->XtoY = 0;
3038: PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqbaij_petsc);
3039: PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqbaij_petsc);
3040: PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bstrm_C",MatGetFactor_seqbaij_bstrm);
3041: #if defined(PETSC_HAVE_MUMPS)
3042: PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C", MatGetFactor_baij_mumps);
3043: #endif
3044: PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);
3045: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);
3046: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);
3047: PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);
3048: PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);
3049: PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);
3050: PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);
3051: PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);
3052: PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqbstrm_C",MatConvert_SeqBAIJ_SeqBSTRM);
3053: PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);
3054: PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);
3055: return(0);
3056: }
3060: PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace)
3061: {
3062: Mat_SeqBAIJ *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data;
3064: PetscInt i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2;
3067: if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix");
3069: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
3070: c->imax = a->imax;
3071: c->ilen = a->ilen;
3072: c->free_imax_ilen = PETSC_FALSE;
3073: } else {
3074: PetscMalloc2(mbs,&c->imax,mbs,&c->ilen);
3075: PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));
3076: for (i=0; i<mbs; i++) {
3077: c->imax[i] = a->imax[i];
3078: c->ilen[i] = a->ilen[i];
3079: }
3080: c->free_imax_ilen = PETSC_TRUE;
3081: }
3083: /* allocate the matrix space */
3084: if (mallocmatspace) {
3085: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
3086: PetscCalloc1(bs2*nz,&c->a);
3087: PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));
3089: c->i = a->i;
3090: c->j = a->j;
3091: c->singlemalloc = PETSC_FALSE;
3092: c->free_a = PETSC_TRUE;
3093: c->free_ij = PETSC_FALSE;
3094: c->parent = A;
3095: C->preallocated = PETSC_TRUE;
3096: C->assembled = PETSC_TRUE;
3098: PetscObjectReference((PetscObject)A);
3099: MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3100: MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3101: } else {
3102: PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);
3103: PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));
3105: c->singlemalloc = PETSC_TRUE;
3106: c->free_a = PETSC_TRUE;
3107: c->free_ij = PETSC_TRUE;
3109: PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));
3110: if (mbs > 0) {
3111: PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));
3112: if (cpvalues == MAT_COPY_VALUES) {
3113: PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));
3114: } else {
3115: PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));
3116: }
3117: }
3118: C->preallocated = PETSC_TRUE;
3119: C->assembled = PETSC_TRUE;
3120: }
3121: }
3123: c->roworiented = a->roworiented;
3124: c->nonew = a->nonew;
3126: PetscLayoutReference(A->rmap,&C->rmap);
3127: PetscLayoutReference(A->cmap,&C->cmap);
3129: c->bs2 = a->bs2;
3130: c->mbs = a->mbs;
3131: c->nbs = a->nbs;
3133: if (a->diag) {
3134: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
3135: c->diag = a->diag;
3136: c->free_diag = PETSC_FALSE;
3137: } else {
3138: PetscMalloc1((mbs+1),&c->diag);
3139: PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));
3140: for (i=0; i<mbs; i++) c->diag[i] = a->diag[i];
3141: c->free_diag = PETSC_TRUE;
3142: }
3143: } else c->diag = 0;
3145: c->nz = a->nz;
3146: c->maxnz = a->nz; /* Since we allocate exactly the right amount */
3147: c->solve_work = 0;
3148: c->mult_work = 0;
3150: c->compressedrow.use = a->compressedrow.use;
3151: c->compressedrow.nrows = a->compressedrow.nrows;
3152: if (a->compressedrow.use) {
3153: i = a->compressedrow.nrows;
3154: PetscMalloc2(i+1,&c->compressedrow.i,i+1,&c->compressedrow.rindex);
3155: PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));
3156: PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));
3157: PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));
3158: } else {
3159: c->compressedrow.use = PETSC_FALSE;
3160: c->compressedrow.i = NULL;
3161: c->compressedrow.rindex = NULL;
3162: }
3163: C->nonzerostate = A->nonzerostate;
3165: PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
3166: PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));
3167: return(0);
3168: }
3172: PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
3173: {
3177: MatCreate(PetscObjectComm((PetscObject)A),B);
3178: MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
3179: MatSetType(*B,MATSEQBAIJ);
3180: MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);
3181: return(0);
3182: }
3186: PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer)
3187: {
3188: Mat_SeqBAIJ *a;
3190: PetscInt i,nz,header[4],*rowlengths=0,M,N,bs=1;
3191: PetscInt *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount;
3192: PetscInt kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols;
3193: PetscInt *masked,nmask,tmp,bs2,ishift;
3194: PetscMPIInt size;
3195: int fd;
3196: PetscScalar *aa;
3197: MPI_Comm comm;
3200: PetscObjectGetComm((PetscObject)viewer,&comm);
3201: PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");
3202: PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
3203: PetscOptionsEnd();
3204: bs2 = bs*bs;
3206: MPI_Comm_size(comm,&size);
3207: if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor");
3208: PetscViewerBinaryGetDescriptor(viewer,&fd);
3209: PetscBinaryRead(fd,header,4,PETSC_INT);
3210: if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object");
3211: M = header[1]; N = header[2]; nz = header[3];
3213: if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ");
3214: if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");
3216: /*
3217: This code adds extra rows to make sure the number of rows is
3218: divisible by the blocksize
3219: */
3220: mbs = M/bs;
3221: extra_rows = bs - M + bs*(mbs);
3222: if (extra_rows == bs) extra_rows = 0;
3223: else mbs++;
3224: if (extra_rows) {
3225: PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
3226: }
3228: /* Set global sizes if not already set */
3229: if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
3230: MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);
3231: } else { /* Check if the matrix global sizes are correct */
3232: MatGetSize(newmat,&rows,&cols);
3233: if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */
3234: MatGetLocalSize(newmat,&rows,&cols);
3235: }
3236: if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,rows,cols);
3237: }
3239: /* read in row lengths */
3240: PetscMalloc1((M+extra_rows),&rowlengths);
3241: PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
3242: for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
3244: /* read in column indices */
3245: PetscMalloc1((nz+extra_rows),&jj);
3246: PetscBinaryRead(fd,jj,nz,PETSC_INT);
3247: for (i=0; i<extra_rows; i++) jj[nz+i] = M+i;
3249: /* loop over row lengths determining block row lengths */
3250: PetscCalloc1(mbs,&browlengths);
3251: PetscMalloc2(mbs,&mask,mbs,&masked);
3252: PetscMemzero(mask,mbs*sizeof(PetscInt));
3253: rowcount = 0;
3254: nzcount = 0;
3255: for (i=0; i<mbs; i++) {
3256: nmask = 0;
3257: for (j=0; j<bs; j++) {
3258: kmax = rowlengths[rowcount];
3259: for (k=0; k<kmax; k++) {
3260: tmp = jj[nzcount++]/bs;
3261: if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;}
3262: }
3263: rowcount++;
3264: }
3265: browlengths[i] += nmask;
3266: /* zero out the mask elements we set */
3267: for (j=0; j<nmask; j++) mask[masked[j]] = 0;
3268: }
3270: /* Do preallocation */
3271: MatSeqBAIJSetPreallocation_SeqBAIJ(newmat,bs,0,browlengths);
3272: a = (Mat_SeqBAIJ*)newmat->data;
3274: /* set matrix "i" values */
3275: a->i[0] = 0;
3276: for (i=1; i<= mbs; i++) {
3277: a->i[i] = a->i[i-1] + browlengths[i-1];
3278: a->ilen[i-1] = browlengths[i-1];
3279: }
3280: a->nz = 0;
3281: for (i=0; i<mbs; i++) a->nz += browlengths[i];
3283: /* read in nonzero values */
3284: PetscMalloc1((nz+extra_rows),&aa);
3285: PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);
3286: for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0;
3288: /* set "a" and "j" values into matrix */
3289: nzcount = 0; jcount = 0;
3290: for (i=0; i<mbs; i++) {
3291: nzcountb = nzcount;
3292: nmask = 0;
3293: for (j=0; j<bs; j++) {
3294: kmax = rowlengths[i*bs+j];
3295: for (k=0; k<kmax; k++) {
3296: tmp = jj[nzcount++]/bs;
3297: if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;}
3298: }
3299: }
3300: /* sort the masked values */
3301: PetscSortInt(nmask,masked);
3303: /* set "j" values into matrix */
3304: maskcount = 1;
3305: for (j=0; j<nmask; j++) {
3306: a->j[jcount++] = masked[j];
3307: mask[masked[j]] = maskcount++;
3308: }
3309: /* set "a" values into matrix */
3310: ishift = bs2*a->i[i];
3311: for (j=0; j<bs; j++) {
3312: kmax = rowlengths[i*bs+j];
3313: for (k=0; k<kmax; k++) {
3314: tmp = jj[nzcountb]/bs;
3315: block = mask[tmp] - 1;
3316: point = jj[nzcountb] - bs*tmp;
3317: idx = ishift + bs2*block + j + bs*point;
3318: a->a[idx] = (MatScalar)aa[nzcountb++];
3319: }
3320: }
3321: /* zero out the mask elements we set */
3322: for (j=0; j<nmask; j++) mask[masked[j]] = 0;
3323: }
3324: if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix");
3326: PetscFree(rowlengths);
3327: PetscFree(browlengths);
3328: PetscFree(aa);
3329: PetscFree(jj);
3330: PetscFree2(mask,masked);
3332: MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
3333: MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
3334: return(0);
3335: }
3339: /*@C
3340: MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block
3341: compressed row) format. For good matrix assembly performance the
3342: user should preallocate the matrix storage by setting the parameter nz
3343: (or the array nnz). By setting these parameters accurately, performance
3344: during matrix assembly can be increased by more than a factor of 50.
3346: Collective on MPI_Comm
3348: Input Parameters:
3349: + comm - MPI communicator, set to PETSC_COMM_SELF
3350: . bs - size of block
3351: . m - number of rows
3352: . n - number of columns
3353: . nz - number of nonzero blocks per block row (same for all rows)
3354: - nnz - array containing the number of nonzero blocks in the various block rows
3355: (possibly different for each block row) or NULL
3357: Output Parameter:
3358: . A - the matrix
3360: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3361: MatXXXXSetPreallocation() paradgm instead of this routine directly.
3362: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
3364: Options Database Keys:
3365: . -mat_no_unroll - uses code that does not unroll the loops in the
3366: block calculations (much slower)
3367: . -mat_block_size - size of the blocks to use
3369: Level: intermediate
3371: Notes:
3372: The number of rows and columns must be divisible by blocksize.
3374: If the nnz parameter is given then the nz parameter is ignored
3376: A nonzero block is any block that as 1 or more nonzeros in it
3378: The block AIJ format is fully compatible with standard Fortran 77
3379: storage. That is, the stored row and column indices can begin at
3380: either one (as in Fortran) or zero. See the users' manual for details.
3382: Specify the preallocated storage with either nz or nnz (not both).
3383: Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
3384: allocation. See Users-Manual: ch_mat for details.
3385: matrices.
3387: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ()
3388: @*/
3389: PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
3390: {
3394: MatCreate(comm,A);
3395: MatSetSizes(*A,m,n,m,n);
3396: MatSetType(*A,MATSEQBAIJ);
3397: MatSeqBAIJSetPreallocation_SeqBAIJ(*A,bs,nz,(PetscInt*)nnz);
3398: return(0);
3399: }
3403: /*@C
3404: MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros
3405: per row in the matrix. For good matrix assembly performance the
3406: user should preallocate the matrix storage by setting the parameter nz
3407: (or the array nnz). By setting these parameters accurately, performance
3408: during matrix assembly can be increased by more than a factor of 50.
3410: Collective on MPI_Comm
3412: Input Parameters:
3413: + B - the matrix
3414: . bs - size of block
3415: . nz - number of block nonzeros per block row (same for all rows)
3416: - nnz - array containing the number of block nonzeros in the various block rows
3417: (possibly different for each block row) or NULL
3419: Options Database Keys:
3420: . -mat_no_unroll - uses code that does not unroll the loops in the
3421: block calculations (much slower)
3422: . -mat_block_size - size of the blocks to use
3424: Level: intermediate
3426: Notes:
3427: If the nnz parameter is given then the nz parameter is ignored
3429: You can call MatGetInfo() to get information on how effective the preallocation was;
3430: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3431: You can also run with the option -info and look for messages with the string
3432: malloc in them to see if additional memory allocation was needed.
3434: The block AIJ format is fully compatible with standard Fortran 77
3435: storage. That is, the stored row and column indices can begin at
3436: either one (as in Fortran) or zero. See the users' manual for details.
3438: Specify the preallocated storage with either nz or nnz (not both).
3439: Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
3440: allocation. See Users-Manual: ch_mat for details.
3442: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo()
3443: @*/
3444: PetscErrorCode MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
3445: {
3452: PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));
3453: return(0);
3454: }
3458: /*@C
3459: MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format
3460: (the default sequential PETSc format).
3462: Collective on MPI_Comm
3464: Input Parameters:
3465: + B - the matrix
3466: . i - the indices into j for the start of each local row (starts with zero)
3467: . j - the column indices for each local row (starts with zero) these must be sorted for each row
3468: - v - optional values in the matrix
3470: Level: developer
3472: Notes:
3473: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs
3474: may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
3475: over rows within a block and the last index is over columns within a block row. Fortran programs will likely set
3476: MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
3477: block column and the second index is over columns within a block.
3479: .keywords: matrix, aij, compressed row, sparse
3481: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ
3482: @*/
3483: PetscErrorCode MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3484: {
3491: PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3492: return(0);
3493: }
3498: /*@
3499: MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user.
3501: Collective on MPI_Comm
3503: Input Parameters:
3504: + comm - must be an MPI communicator of size 1
3505: . bs - size of block
3506: . m - number of rows
3507: . n - number of columns
3508: . i - row indices
3509: . j - column indices
3510: - a - matrix values
3512: Output Parameter:
3513: . mat - the matrix
3515: Level: advanced
3517: Notes:
3518: The i, j, and a arrays are not copied by this routine, the user must free these arrays
3519: once the matrix is destroyed
3521: You cannot set new nonzero locations into this matrix, that will generate an error.
3523: The i and j indices are 0 based
3525: When block size is greater than 1 the matrix values must be stored using the BAIJ storage format (see the BAIJ code to determine this).
3527: The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
3528: the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
3529: block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory
3530: with column-major ordering within blocks.
3532: .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ()
3534: @*/
3535: PetscErrorCode MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat)
3536: {
3538: PetscInt ii;
3539: Mat_SeqBAIJ *baij;
3542: if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs);
3543: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3545: MatCreate(comm,mat);
3546: MatSetSizes(*mat,m,n,m,n);
3547: MatSetType(*mat,MATSEQBAIJ);
3548: MatSeqBAIJSetPreallocation_SeqBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);
3549: baij = (Mat_SeqBAIJ*)(*mat)->data;
3550: PetscMalloc2(m,&baij->imax,m,&baij->ilen);
3551: PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));
3553: baij->i = i;
3554: baij->j = j;
3555: baij->a = a;
3557: baij->singlemalloc = PETSC_FALSE;
3558: baij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
3559: baij->free_a = PETSC_FALSE;
3560: baij->free_ij = PETSC_FALSE;
3562: for (ii=0; ii<m; ii++) {
3563: baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii];
3564: #if defined(PETSC_USE_DEBUG)
3565: if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]);
3566: #endif
3567: }
3568: #if defined(PETSC_USE_DEBUG)
3569: for (ii=0; ii<baij->i[m]; ii++) {
3570: if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]);
3571: if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]);
3572: }
3573: #endif
3575: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3576: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3577: return(0);
3578: }