Actual source code: baijfact12.c
1: /*$Id: baijfact12.c,v 1.17 2001/08/31 16:22:11 bsmith Exp $*/
2: /*
3: Factorization code for BAIJ format.
4: */
5: #include src/mat/impls/baij/seq/baij.h
6: #include src/vec/vecimpl.h
7: #include src/inline/ilu.h
9: int MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering(Mat A,Mat *B)
10: {
11: /*
12: Default Version for when blocks are 4 by 4 Using natural ordering
13: */
14: Mat C = *B;
15: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ*)C->data;
16: int ierr,i,j,n = a->mbs,*bi = b->i,*bj = b->j;
17: int *ajtmpold,*ajtmp,nz,row;
18: int *diag_offset = b->diag,*ai=a->i,*aj=a->j,*pj;
19: MatScalar *pv,*v,*rtmp,*pc,*w,*x;
20: MatScalar p1,p2,p3,p4,m1,m2,m3,m4,m5,m6,m7,m8,m9,x1,x2,x3,x4;
21: MatScalar p5,p6,p7,p8,p9,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16;
22: MatScalar p10,p11,p12,p13,p14,p15,p16,m10,m11,m12;
23: MatScalar m13,m14,m15,m16;
24: MatScalar *ba = b->a,*aa = a->a;
25: PetscTruth pivotinblocks = b->pivotinblocks;
28: PetscMalloc(16*(n+1)*sizeof(MatScalar),&rtmp);
30: for (i=0; i<n; i++) {
31: nz = bi[i+1] - bi[i];
32: ajtmp = bj + bi[i];
33: for (j=0; j<nz; j++) {
34: x = rtmp+16*ajtmp[j];
35: x[0] = x[1] = x[2] = x[3] = x[4] = x[5] = x[6] = x[7] = x[8] = x[9] = 0.0;
36: x[10] = x[11] = x[12] = x[13] = x[14] = x[15] = 0.0;
37: }
38: /* load in initial (unfactored row) */
39: nz = ai[i+1] - ai[i];
40: ajtmpold = aj + ai[i];
41: v = aa + 16*ai[i];
42: for (j=0; j<nz; j++) {
43: x = rtmp+16*ajtmpold[j];
44: x[0] = v[0]; x[1] = v[1]; x[2] = v[2]; x[3] = v[3];
45: x[4] = v[4]; x[5] = v[5]; x[6] = v[6]; x[7] = v[7]; x[8] = v[8];
46: x[9] = v[9]; x[10] = v[10]; x[11] = v[11]; x[12] = v[12]; x[13] = v[13];
47: x[14] = v[14]; x[15] = v[15];
48: v += 16;
49: }
50: row = *ajtmp++;
51: while (row < i) {
52: pc = rtmp + 16*row;
53: p1 = pc[0]; p2 = pc[1]; p3 = pc[2]; p4 = pc[3];
54: p5 = pc[4]; p6 = pc[5]; p7 = pc[6]; p8 = pc[7]; p9 = pc[8];
55: p10 = pc[9]; p11 = pc[10]; p12 = pc[11]; p13 = pc[12]; p14 = pc[13];
56: p15 = pc[14]; p16 = pc[15];
57: if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0 || p5 != 0.0 ||
58: p6 != 0.0 || p7 != 0.0 || p8 != 0.0 || p9 != 0.0 || p10 != 0.0 ||
59: p11 != 0.0 || p12 != 0.0 || p13 != 0.0 || p14 != 0.0 || p15 != 0.0
60: || p16 != 0.0) {
61: pv = ba + 16*diag_offset[row];
62: pj = bj + diag_offset[row] + 1;
63: x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
64: x5 = pv[4]; x6 = pv[5]; x7 = pv[6]; x8 = pv[7]; x9 = pv[8];
65: x10 = pv[9]; x11 = pv[10]; x12 = pv[11]; x13 = pv[12]; x14 = pv[13];
66: x15 = pv[14]; x16 = pv[15];
67: pc[0] = m1 = p1*x1 + p5*x2 + p9*x3 + p13*x4;
68: pc[1] = m2 = p2*x1 + p6*x2 + p10*x3 + p14*x4;
69: pc[2] = m3 = p3*x1 + p7*x2 + p11*x3 + p15*x4;
70: pc[3] = m4 = p4*x1 + p8*x2 + p12*x3 + p16*x4;
72: pc[4] = m5 = p1*x5 + p5*x6 + p9*x7 + p13*x8;
73: pc[5] = m6 = p2*x5 + p6*x6 + p10*x7 + p14*x8;
74: pc[6] = m7 = p3*x5 + p7*x6 + p11*x7 + p15*x8;
75: pc[7] = m8 = p4*x5 + p8*x6 + p12*x7 + p16*x8;
77: pc[8] = m9 = p1*x9 + p5*x10 + p9*x11 + p13*x12;
78: pc[9] = m10 = p2*x9 + p6*x10 + p10*x11 + p14*x12;
79: pc[10] = m11 = p3*x9 + p7*x10 + p11*x11 + p15*x12;
80: pc[11] = m12 = p4*x9 + p8*x10 + p12*x11 + p16*x12;
82: pc[12] = m13 = p1*x13 + p5*x14 + p9*x15 + p13*x16;
83: pc[13] = m14 = p2*x13 + p6*x14 + p10*x15 + p14*x16;
84: pc[14] = m15 = p3*x13 + p7*x14 + p11*x15 + p15*x16;
85: pc[15] = m16 = p4*x13 + p8*x14 + p12*x15 + p16*x16;
86: nz = bi[row+1] - diag_offset[row] - 1;
87: pv += 16;
88: for (j=0; j<nz; j++) {
89: x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
90: x5 = pv[4]; x6 = pv[5]; x7 = pv[6]; x8 = pv[7]; x9 = pv[8];
91: x10 = pv[9]; x11 = pv[10]; x12 = pv[11]; x13 = pv[12];
92: x14 = pv[13]; x15 = pv[14]; x16 = pv[15];
93: x = rtmp + 16*pj[j];
94: x[0] -= m1*x1 + m5*x2 + m9*x3 + m13*x4;
95: x[1] -= m2*x1 + m6*x2 + m10*x3 + m14*x4;
96: x[2] -= m3*x1 + m7*x2 + m11*x3 + m15*x4;
97: x[3] -= m4*x1 + m8*x2 + m12*x3 + m16*x4;
99: x[4] -= m1*x5 + m5*x6 + m9*x7 + m13*x8;
100: x[5] -= m2*x5 + m6*x6 + m10*x7 + m14*x8;
101: x[6] -= m3*x5 + m7*x6 + m11*x7 + m15*x8;
102: x[7] -= m4*x5 + m8*x6 + m12*x7 + m16*x8;
104: x[8] -= m1*x9 + m5*x10 + m9*x11 + m13*x12;
105: x[9] -= m2*x9 + m6*x10 + m10*x11 + m14*x12;
106: x[10] -= m3*x9 + m7*x10 + m11*x11 + m15*x12;
107: x[11] -= m4*x9 + m8*x10 + m12*x11 + m16*x12;
109: x[12] -= m1*x13 + m5*x14 + m9*x15 + m13*x16;
110: x[13] -= m2*x13 + m6*x14 + m10*x15 + m14*x16;
111: x[14] -= m3*x13 + m7*x14 + m11*x15 + m15*x16;
112: x[15] -= m4*x13 + m8*x14 + m12*x15 + m16*x16;
114: pv += 16;
115: }
116: PetscLogFlops(128*nz+112);
117: }
118: row = *ajtmp++;
119: }
120: /* finished row so stick it into b->a */
121: pv = ba + 16*bi[i];
122: pj = bj + bi[i];
123: nz = bi[i+1] - bi[i];
124: for (j=0; j<nz; j++) {
125: x = rtmp+16*pj[j];
126: pv[0] = x[0]; pv[1] = x[1]; pv[2] = x[2]; pv[3] = x[3];
127: pv[4] = x[4]; pv[5] = x[5]; pv[6] = x[6]; pv[7] = x[7]; pv[8] = x[8];
128: pv[9] = x[9]; pv[10] = x[10]; pv[11] = x[11]; pv[12] = x[12];
129: pv[13] = x[13]; pv[14] = x[14]; pv[15] = x[15];
130: pv += 16;
131: }
132: /* invert diagonal block */
133: w = ba + 16*diag_offset[i];
134: if (pivotinblocks) {
135: Kernel_A_gets_inverse_A_4(w);
136: } else {
137: Kernel_A_gets_inverse_A_4_nopivot(w);
138: }
139: }
141: PetscFree(rtmp);
142: C->factor = FACTOR_LU;
143: C->assembled = PETSC_TRUE;
144: PetscLogFlops(1.3333*64*b->mbs); /* from inverting diagonal blocks */
145: return(0);
146: }
149: #if defined(PETSC_HAVE_SSE)
151: #include PETSC_HAVE_SSE
153: /* SSE Version for when blocks are 4 by 4 Using natural ordering */
154: int MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering_SSE(Mat A,Mat *B)
155: {
156: Mat C = *B;
157: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ*)C->data;
158: int ierr,i,j,n = a->mbs,*bi = b->i,*bj = b->j;
159: int *ajtmpold,*ajtmp,nz,row;
160: int *diag_offset = b->diag,*ai=a->i,*aj=a->j,*pj;
161: MatScalar *pv,*v,*rtmp,*pc,*w,*x;
162: MatScalar *ba = b->a,*aa = a->a;
163: int nonzero=0;
166: SSE_SCOPE_BEGIN;
168: PetscMalloc(16*(n+1)*sizeof(MatScalar),&rtmp);
169: for (i=0; i<n; i++) {
170: nz = bi[i+1] - bi[i];
171: ajtmp = bj + bi[i];
172: /* zero out the 4x4 block accumulators */
173: /* zero out one register */
174: XOR_PS(XMM7,XMM7);
175: for (j=0; j<nz; j++) {
176: x = rtmp+16*ajtmp[j];
177: SSE_INLINE_BEGIN_1(x)
178: /* Copy zero register to memory locations */
179: /* Note: on future SSE architectures, STORE might be more efficient than STOREL/H */
180: SSE_STOREL_PS(SSE_ARG_1,FLOAT_0,XMM7)
181: SSE_STOREH_PS(SSE_ARG_1,FLOAT_2,XMM7)
182: SSE_STOREL_PS(SSE_ARG_1,FLOAT_4,XMM7)
183: SSE_STOREH_PS(SSE_ARG_1,FLOAT_6,XMM7)
184: SSE_STOREL_PS(SSE_ARG_1,FLOAT_8,XMM7)
185: SSE_STOREH_PS(SSE_ARG_1,FLOAT_10,XMM7)
186: SSE_STOREL_PS(SSE_ARG_1,FLOAT_12,XMM7)
187: SSE_STOREH_PS(SSE_ARG_1,FLOAT_14,XMM7)
188: SSE_INLINE_END_1;
189: }
190: /* load in initial (unfactored row) */
191: nz = ai[i+1] - ai[i];
192: ajtmpold = aj + ai[i];
193: v = aa + 16*ai[i];
194: for (j=0; j<nz; j++) {
195: x = rtmp+16*ajtmpold[j];
196: /* Copy v block into x block */
197: SSE_INLINE_BEGIN_2(v,x)
198: /* Note: on future SSE architectures, STORE might be more efficient than STOREL/H */
199: SSE_LOADL_PS(SSE_ARG_1,FLOAT_0,XMM0)
200: SSE_STOREL_PS(SSE_ARG_2,FLOAT_0,XMM0)
202: SSE_LOADH_PS(SSE_ARG_1,FLOAT_2,XMM1)
203: SSE_STOREH_PS(SSE_ARG_2,FLOAT_2,XMM1)
205: SSE_LOADL_PS(SSE_ARG_1,FLOAT_4,XMM2)
206: SSE_STOREL_PS(SSE_ARG_2,FLOAT_4,XMM2)
208: SSE_LOADH_PS(SSE_ARG_1,FLOAT_6,XMM3)
209: SSE_STOREH_PS(SSE_ARG_2,FLOAT_6,XMM3)
211: SSE_LOADL_PS(SSE_ARG_1,FLOAT_8,XMM4)
212: SSE_STOREL_PS(SSE_ARG_2,FLOAT_8,XMM4)
214: SSE_LOADH_PS(SSE_ARG_1,FLOAT_10,XMM5)
215: SSE_STOREH_PS(SSE_ARG_2,FLOAT_10,XMM5)
217: SSE_LOADL_PS(SSE_ARG_1,FLOAT_12,XMM6)
218: SSE_STOREL_PS(SSE_ARG_2,FLOAT_12,XMM6)
220: SSE_LOADH_PS(SSE_ARG_1,FLOAT_14,XMM0)
221: SSE_STOREH_PS(SSE_ARG_2,FLOAT_14,XMM0)
222: SSE_INLINE_END_2;
224: v += 16;
225: }
226: row = *ajtmp++;
227: while (row < i) {
228: pc = rtmp + 16*row;
229: SSE_INLINE_BEGIN_1(pc)
230: /* Load block from lower triangle */
231: /* Note: on future SSE architectures, STORE might be more efficient than STOREL/H */
232: SSE_LOADL_PS(SSE_ARG_1,FLOAT_0,XMM0)
233: SSE_LOADH_PS(SSE_ARG_1,FLOAT_2,XMM0)
235: SSE_LOADL_PS(SSE_ARG_1,FLOAT_4,XMM1)
236: SSE_LOADH_PS(SSE_ARG_1,FLOAT_6,XMM1)
238: SSE_LOADL_PS(SSE_ARG_1,FLOAT_8,XMM2)
239: SSE_LOADH_PS(SSE_ARG_1,FLOAT_10,XMM2)
241: SSE_LOADL_PS(SSE_ARG_1,FLOAT_12,XMM3)
242: SSE_LOADH_PS(SSE_ARG_1,FLOAT_14,XMM3)
244: /* Compare block to zero block */
246: SSE_COPY_PS(XMM4,XMM7)
247: SSE_CMPNEQ_PS(XMM4,XMM0)
249: SSE_COPY_PS(XMM5,XMM7)
250: SSE_CMPNEQ_PS(XMM5,XMM1)
252: SSE_COPY_PS(XMM6,XMM7)
253: SSE_CMPNEQ_PS(XMM6,XMM2)
255: SSE_CMPNEQ_PS(XMM7,XMM3)
257: /* Reduce the comparisons to one SSE register */
258: SSE_OR_PS(XMM6,XMM7)
259: SSE_OR_PS(XMM5,XMM4)
260: SSE_OR_PS(XMM5,XMM6)
261: SSE_INLINE_END_1;
263: /* Reduce the one SSE register to an integer register for branching */
264: /* Note: Since nonzero is an int, there is no INLINE block version of this call */
265: MOVEMASK(nonzero,XMM5);
267: /* If block is nonzero ... */
268: if (nonzero) {
269: pv = ba + 16*diag_offset[row];
270: PREFETCH_L1(&pv[16]);
271: pj = bj + diag_offset[row] + 1;
273: /* Form Multiplier, one column at a time (Matrix-Matrix Product) */
274: /* L_ij^(k+1) = L_ij^(k)*inv(L_jj^(k)) */
275: /* but the diagonal was inverted already */
276: /* and, L_ij^(k) is already loaded into registers XMM0-XMM3 columnwise */
278: SSE_INLINE_BEGIN_2(pv,pc)
279: /* Column 0, product is accumulated in XMM4 */
280: SSE_LOAD_SS(SSE_ARG_1,FLOAT_0,XMM4)
281: SSE_SHUFFLE(XMM4,XMM4,0x00)
282: SSE_MULT_PS(XMM4,XMM0)
284: SSE_LOAD_SS(SSE_ARG_1,FLOAT_1,XMM5)
285: SSE_SHUFFLE(XMM5,XMM5,0x00)
286: SSE_MULT_PS(XMM5,XMM1)
287: SSE_ADD_PS(XMM4,XMM5)
289: SSE_LOAD_SS(SSE_ARG_1,FLOAT_2,XMM6)
290: SSE_SHUFFLE(XMM6,XMM6,0x00)
291: SSE_MULT_PS(XMM6,XMM2)
292: SSE_ADD_PS(XMM4,XMM6)
294: SSE_LOAD_SS(SSE_ARG_1,FLOAT_3,XMM7)
295: SSE_SHUFFLE(XMM7,XMM7,0x00)
296: SSE_MULT_PS(XMM7,XMM3)
297: SSE_ADD_PS(XMM4,XMM7)
299: SSE_STOREL_PS(SSE_ARG_2,FLOAT_0,XMM4)
300: SSE_STOREH_PS(SSE_ARG_2,FLOAT_2,XMM4)
302: /* Column 1, product is accumulated in XMM5 */
303: SSE_LOAD_SS(SSE_ARG_1,FLOAT_4,XMM5)
304: SSE_SHUFFLE(XMM5,XMM5,0x00)
305: SSE_MULT_PS(XMM5,XMM0)
307: SSE_LOAD_SS(SSE_ARG_1,FLOAT_5,XMM6)
308: SSE_SHUFFLE(XMM6,XMM6,0x00)
309: SSE_MULT_PS(XMM6,XMM1)
310: SSE_ADD_PS(XMM5,XMM6)
312: SSE_LOAD_SS(SSE_ARG_1,FLOAT_6,XMM7)
313: SSE_SHUFFLE(XMM7,XMM7,0x00)
314: SSE_MULT_PS(XMM7,XMM2)
315: SSE_ADD_PS(XMM5,XMM7)
317: SSE_LOAD_SS(SSE_ARG_1,FLOAT_7,XMM6)
318: SSE_SHUFFLE(XMM6,XMM6,0x00)
319: SSE_MULT_PS(XMM6,XMM3)
320: SSE_ADD_PS(XMM5,XMM6)
322: SSE_STOREL_PS(SSE_ARG_2,FLOAT_4,XMM5)
323: SSE_STOREH_PS(SSE_ARG_2,FLOAT_6,XMM5)
325: SSE_PREFETCH_L1(SSE_ARG_1,FLOAT_24)
327: /* Column 2, product is accumulated in XMM6 */
328: SSE_LOAD_SS(SSE_ARG_1,FLOAT_8,XMM6)
329: SSE_SHUFFLE(XMM6,XMM6,0x00)
330: SSE_MULT_PS(XMM6,XMM0)
332: SSE_LOAD_SS(SSE_ARG_1,FLOAT_9,XMM7)
333: SSE_SHUFFLE(XMM7,XMM7,0x00)
334: SSE_MULT_PS(XMM7,XMM1)
335: SSE_ADD_PS(XMM6,XMM7)
337: SSE_LOAD_SS(SSE_ARG_1,FLOAT_10,XMM7)
338: SSE_SHUFFLE(XMM7,XMM7,0x00)
339: SSE_MULT_PS(XMM7,XMM2)
340: SSE_ADD_PS(XMM6,XMM7)
342: SSE_LOAD_SS(SSE_ARG_1,FLOAT_11,XMM7)
343: SSE_SHUFFLE(XMM7,XMM7,0x00)
344: SSE_MULT_PS(XMM7,XMM3)
345: SSE_ADD_PS(XMM6,XMM7)
346:
347: SSE_STOREL_PS(SSE_ARG_2,FLOAT_8,XMM6)
348: SSE_STOREH_PS(SSE_ARG_2,FLOAT_10,XMM6)
350: /* Note: For the last column, we no longer need to preserve XMM0->XMM3 */
351: /* Column 3, product is accumulated in XMM0 */
352: SSE_LOAD_SS(SSE_ARG_1,FLOAT_12,XMM7)
353: SSE_SHUFFLE(XMM7,XMM7,0x00)
354: SSE_MULT_PS(XMM0,XMM7)
356: SSE_LOAD_SS(SSE_ARG_1,FLOAT_13,XMM7)
357: SSE_SHUFFLE(XMM7,XMM7,0x00)
358: SSE_MULT_PS(XMM1,XMM7)
359: SSE_ADD_PS(XMM0,XMM1)
361: SSE_LOAD_SS(SSE_ARG_1,FLOAT_14,XMM1)
362: SSE_SHUFFLE(XMM1,XMM1,0x00)
363: SSE_MULT_PS(XMM1,XMM2)
364: SSE_ADD_PS(XMM0,XMM1)
366: SSE_LOAD_SS(SSE_ARG_1,FLOAT_15,XMM7)
367: SSE_SHUFFLE(XMM7,XMM7,0x00)
368: SSE_MULT_PS(XMM3,XMM7)
369: SSE_ADD_PS(XMM0,XMM3)
371: SSE_STOREL_PS(SSE_ARG_2,FLOAT_12,XMM0)
372: SSE_STOREH_PS(SSE_ARG_2,FLOAT_14,XMM0)
374: /* Simplify Bookkeeping -- Completely Unnecessary Instructions */
375: /* This is code to be maintained and read by humans afterall. */
376: /* Copy Multiplier Col 3 into XMM3 */
377: SSE_COPY_PS(XMM3,XMM0)
378: /* Copy Multiplier Col 2 into XMM2 */
379: SSE_COPY_PS(XMM2,XMM6)
380: /* Copy Multiplier Col 1 into XMM1 */
381: SSE_COPY_PS(XMM1,XMM5)
382: /* Copy Multiplier Col 0 into XMM0 */
383: SSE_COPY_PS(XMM0,XMM4)
384: SSE_INLINE_END_2;
386: /* Update the row: */
387: nz = bi[row+1] - diag_offset[row] - 1;
388: pv += 16;
389: for (j=0; j<nz; j++) {
390: PREFETCH_L1(&pv[16]);
391: x = rtmp + 16*pj[j];
393: /* X:=X-M*PV, One column at a time */
394: /* Note: M is already loaded columnwise into registers XMM0-XMM3 */
395: SSE_INLINE_BEGIN_2(x,pv)
396: /* Load First Column of X*/
397: SSE_LOADL_PS(SSE_ARG_1,FLOAT_0,XMM4)
398: SSE_LOADH_PS(SSE_ARG_1,FLOAT_2,XMM4)
400: /* Matrix-Vector Product: */
401: SSE_LOAD_SS(SSE_ARG_2,FLOAT_0,XMM5)
402: SSE_SHUFFLE(XMM5,XMM5,0x00)
403: SSE_MULT_PS(XMM5,XMM0)
404: SSE_SUB_PS(XMM4,XMM5)
406: SSE_LOAD_SS(SSE_ARG_2,FLOAT_1,XMM6)
407: SSE_SHUFFLE(XMM6,XMM6,0x00)
408: SSE_MULT_PS(XMM6,XMM1)
409: SSE_SUB_PS(XMM4,XMM6)
411: SSE_LOAD_SS(SSE_ARG_2,FLOAT_2,XMM7)
412: SSE_SHUFFLE(XMM7,XMM7,0x00)
413: SSE_MULT_PS(XMM7,XMM2)
414: SSE_SUB_PS(XMM4,XMM7)
416: SSE_LOAD_SS(SSE_ARG_2,FLOAT_3,XMM5)
417: SSE_SHUFFLE(XMM5,XMM5,0x00)
418: SSE_MULT_PS(XMM5,XMM3)
419: SSE_SUB_PS(XMM4,XMM5)
421: SSE_STOREL_PS(SSE_ARG_1,FLOAT_0,XMM4)
422: SSE_STOREH_PS(SSE_ARG_1,FLOAT_2,XMM4)
424: /* Second Column */
425: SSE_LOADL_PS(SSE_ARG_1,FLOAT_4,XMM5)
426: SSE_LOADH_PS(SSE_ARG_1,FLOAT_6,XMM5)
428: /* Matrix-Vector Product: */
429: SSE_LOAD_SS(SSE_ARG_2,FLOAT_4,XMM6)
430: SSE_SHUFFLE(XMM6,XMM6,0x00)
431: SSE_MULT_PS(XMM6,XMM0)
432: SSE_SUB_PS(XMM5,XMM6)
434: SSE_LOAD_SS(SSE_ARG_2,FLOAT_5,XMM7)
435: SSE_SHUFFLE(XMM7,XMM7,0x00)
436: SSE_MULT_PS(XMM7,XMM1)
437: SSE_SUB_PS(XMM5,XMM7)
439: SSE_LOAD_SS(SSE_ARG_2,FLOAT_6,XMM4)
440: SSE_SHUFFLE(XMM4,XMM4,0x00)
441: SSE_MULT_PS(XMM4,XMM2)
442: SSE_SUB_PS(XMM5,XMM4)
444: SSE_LOAD_SS(SSE_ARG_2,FLOAT_7,XMM6)
445: SSE_SHUFFLE(XMM6,XMM6,0x00)
446: SSE_MULT_PS(XMM6,XMM3)
447: SSE_SUB_PS(XMM5,XMM6)
448:
449: SSE_STOREL_PS(SSE_ARG_1,FLOAT_4,XMM5)
450: SSE_STOREH_PS(SSE_ARG_1,FLOAT_6,XMM5)
452: SSE_PREFETCH_L1(SSE_ARG_2,FLOAT_24)
454: /* Third Column */
455: SSE_LOADL_PS(SSE_ARG_1,FLOAT_8,XMM6)
456: SSE_LOADH_PS(SSE_ARG_1,FLOAT_10,XMM6)
458: /* Matrix-Vector Product: */
459: SSE_LOAD_SS(SSE_ARG_2,FLOAT_8,XMM7)
460: SSE_SHUFFLE(XMM7,XMM7,0x00)
461: SSE_MULT_PS(XMM7,XMM0)
462: SSE_SUB_PS(XMM6,XMM7)
464: SSE_LOAD_SS(SSE_ARG_2,FLOAT_9,XMM4)
465: SSE_SHUFFLE(XMM4,XMM4,0x00)
466: SSE_MULT_PS(XMM4,XMM1)
467: SSE_SUB_PS(XMM6,XMM4)
469: SSE_LOAD_SS(SSE_ARG_2,FLOAT_10,XMM5)
470: SSE_SHUFFLE(XMM5,XMM5,0x00)
471: SSE_MULT_PS(XMM5,XMM2)
472: SSE_SUB_PS(XMM6,XMM5)
474: SSE_LOAD_SS(SSE_ARG_2,FLOAT_11,XMM7)
475: SSE_SHUFFLE(XMM7,XMM7,0x00)
476: SSE_MULT_PS(XMM7,XMM3)
477: SSE_SUB_PS(XMM6,XMM7)
478:
479: SSE_STOREL_PS(SSE_ARG_1,FLOAT_8,XMM6)
480: SSE_STOREH_PS(SSE_ARG_1,FLOAT_10,XMM6)
481:
482: /* Fourth Column */
483: SSE_LOADL_PS(SSE_ARG_1,FLOAT_12,XMM4)
484: SSE_LOADH_PS(SSE_ARG_1,FLOAT_14,XMM4)
486: /* Matrix-Vector Product: */
487: SSE_LOAD_SS(SSE_ARG_2,FLOAT_12,XMM5)
488: SSE_SHUFFLE(XMM5,XMM5,0x00)
489: SSE_MULT_PS(XMM5,XMM0)
490: SSE_SUB_PS(XMM4,XMM5)
492: SSE_LOAD_SS(SSE_ARG_2,FLOAT_13,XMM6)
493: SSE_SHUFFLE(XMM6,XMM6,0x00)
494: SSE_MULT_PS(XMM6,XMM1)
495: SSE_SUB_PS(XMM4,XMM6)
497: SSE_LOAD_SS(SSE_ARG_2,FLOAT_14,XMM7)
498: SSE_SHUFFLE(XMM7,XMM7,0x00)
499: SSE_MULT_PS(XMM7,XMM2)
500: SSE_SUB_PS(XMM4,XMM7)
502: SSE_LOAD_SS(SSE_ARG_2,FLOAT_15,XMM5)
503: SSE_SHUFFLE(XMM5,XMM5,0x00)
504: SSE_MULT_PS(XMM5,XMM3)
505: SSE_SUB_PS(XMM4,XMM5)
506:
507: SSE_STOREL_PS(SSE_ARG_1,FLOAT_12,XMM4)
508: SSE_STOREH_PS(SSE_ARG_1,FLOAT_14,XMM4)
509: SSE_INLINE_END_2;
510: pv += 16;
511: }
512: PetscLogFlops(128*nz+112);
513: }
514: row = *ajtmp++;
515: }
516: /* finished row so stick it into b->a */
517: pv = ba + 16*bi[i];
518: pj = bj + bi[i];
519: nz = bi[i+1] - bi[i];
521: /* Copy x block back into pv block */
522: for (j=0; j<nz; j++) {
523: x = rtmp+16*pj[j];
525: SSE_INLINE_BEGIN_2(x,pv)
526: /* Note: on future SSE architectures, STORE might be more efficient than STOREL/H */
527: SSE_LOADL_PS(SSE_ARG_1,FLOAT_0,XMM1)
528: SSE_STOREL_PS(SSE_ARG_2,FLOAT_0,XMM1)
530: SSE_LOADH_PS(SSE_ARG_1,FLOAT_2,XMM2)
531: SSE_STOREH_PS(SSE_ARG_2,FLOAT_2,XMM2)
533: SSE_LOADL_PS(SSE_ARG_1,FLOAT_4,XMM3)
534: SSE_STOREL_PS(SSE_ARG_2,FLOAT_4,XMM3)
536: SSE_LOADH_PS(SSE_ARG_1,FLOAT_6,XMM4)
537: SSE_STOREH_PS(SSE_ARG_2,FLOAT_6,XMM4)
539: SSE_LOADL_PS(SSE_ARG_1,FLOAT_8,XMM5)
540: SSE_STOREL_PS(SSE_ARG_2,FLOAT_8,XMM5)
542: SSE_LOADH_PS(SSE_ARG_1,FLOAT_10,XMM6)
543: SSE_STOREH_PS(SSE_ARG_2,FLOAT_10,XMM6)
545: SSE_LOADL_PS(SSE_ARG_1,FLOAT_12,XMM7)
546: SSE_STOREL_PS(SSE_ARG_2,FLOAT_12,XMM7)
548: SSE_LOADH_PS(SSE_ARG_1,FLOAT_14,XMM0)
549: SSE_STOREH_PS(SSE_ARG_2,FLOAT_14,XMM0)
550: SSE_INLINE_END_2;
551: pv += 16;
552: }
553: /* invert diagonal block */
554: w = ba + 16*diag_offset[i];
555: Kernel_A_gets_inverse_A_4_SSE(w);
556: /* Note: Using Kramer's rule, flop count below might be infairly high or low? */
557: }
559: PetscFree(rtmp);
560: C->factor = FACTOR_LU;
561: C->assembled = PETSC_TRUE;
562: PetscLogFlops(1.3333*64*b->mbs);
563: /* Flop Count from inverting diagonal blocks */
564: SSE_SCOPE_END;
565: return(0);
566: }
568: #endif