blender/intern/opennl/superlu/smyblas2.c
Brecht Van Lommel 4f1c674ee0 Added SuperLU 3.0:
http://crd.lbl.gov/~xiaoye/SuperLU/

This is a library to solve sparse matrix systems (type A*x=B). It is able
to solve large systems very FAST. Only the necessary parts of the library
are included to limit file size and compilation time. This means the example
files, fortran interface, test files, matlab interface, cblas library,
complex number part and build system have been left out. All (gcc) warnings
have been fixed too.

This library will be used for LSCM UV unwrapping. With this library, LSCM
unwrapping can be calculated in a split second, making the unwrapping proces
much more interactive.

Added OpenNL (Open Numerical Libary):
http://www.loria.fr/~levy/OpenNL/

OpenNL is a library to easily construct and solve sparse linear systems. We
use a stripped down version, as an interface to SuperLU.

This library was kindly given to use by Bruno Levy.
2004-07-13 11:42:13 +00:00

226 lines
5.5 KiB
C

/*
* -- SuperLU routine (version 2.0) --
* Univ. of California Berkeley, Xerox Palo Alto Research Center,
* and Lawrence Berkeley National Lab.
* November 15, 1997
*
*/
/*
* File name: smyblas2.c
* Purpose:
* Level 2 BLAS operations: solves and matvec, written in C.
* Note:
* This is only used when the system lacks an efficient BLAS library.
*/
/*
* Solves a dense UNIT lower triangular system. The unit lower
* triangular matrix is stored in a 2D array M(1:nrow,1:ncol).
* The solution will be returned in the rhs vector.
*/
void slsolve ( int ldm, int ncol, float *M, float *rhs )
{
int k;
float x0, x1, x2, x3, x4, x5, x6, x7;
float *M0;
register float *Mki0, *Mki1, *Mki2, *Mki3, *Mki4, *Mki5, *Mki6, *Mki7;
register int firstcol = 0;
M0 = &M[0];
while ( firstcol < ncol - 7 ) { /* Do 8 columns */
Mki0 = M0 + 1;
Mki1 = Mki0 + ldm + 1;
Mki2 = Mki1 + ldm + 1;
Mki3 = Mki2 + ldm + 1;
Mki4 = Mki3 + ldm + 1;
Mki5 = Mki4 + ldm + 1;
Mki6 = Mki5 + ldm + 1;
Mki7 = Mki6 + ldm + 1;
x0 = rhs[firstcol];
x1 = rhs[firstcol+1] - x0 * *Mki0++;
x2 = rhs[firstcol+2] - x0 * *Mki0++ - x1 * *Mki1++;
x3 = rhs[firstcol+3] - x0 * *Mki0++ - x1 * *Mki1++ - x2 * *Mki2++;
x4 = rhs[firstcol+4] - x0 * *Mki0++ - x1 * *Mki1++ - x2 * *Mki2++
- x3 * *Mki3++;
x5 = rhs[firstcol+5] - x0 * *Mki0++ - x1 * *Mki1++ - x2 * *Mki2++
- x3 * *Mki3++ - x4 * *Mki4++;
x6 = rhs[firstcol+6] - x0 * *Mki0++ - x1 * *Mki1++ - x2 * *Mki2++
- x3 * *Mki3++ - x4 * *Mki4++ - x5 * *Mki5++;
x7 = rhs[firstcol+7] - x0 * *Mki0++ - x1 * *Mki1++ - x2 * *Mki2++
- x3 * *Mki3++ - x4 * *Mki4++ - x5 * *Mki5++
- x6 * *Mki6++;
rhs[++firstcol] = x1;
rhs[++firstcol] = x2;
rhs[++firstcol] = x3;
rhs[++firstcol] = x4;
rhs[++firstcol] = x5;
rhs[++firstcol] = x6;
rhs[++firstcol] = x7;
++firstcol;
for (k = firstcol; k < ncol; k++)
rhs[k] = rhs[k] - x0 * *Mki0++ - x1 * *Mki1++
- x2 * *Mki2++ - x3 * *Mki3++
- x4 * *Mki4++ - x5 * *Mki5++
- x6 * *Mki6++ - x7 * *Mki7++;
M0 += 8 * ldm + 8;
}
while ( firstcol < ncol - 3 ) { /* Do 4 columns */
Mki0 = M0 + 1;
Mki1 = Mki0 + ldm + 1;
Mki2 = Mki1 + ldm + 1;
Mki3 = Mki2 + ldm + 1;
x0 = rhs[firstcol];
x1 = rhs[firstcol+1] - x0 * *Mki0++;
x2 = rhs[firstcol+2] - x0 * *Mki0++ - x1 * *Mki1++;
x3 = rhs[firstcol+3] - x0 * *Mki0++ - x1 * *Mki1++ - x2 * *Mki2++;
rhs[++firstcol] = x1;
rhs[++firstcol] = x2;
rhs[++firstcol] = x3;
++firstcol;
for (k = firstcol; k < ncol; k++)
rhs[k] = rhs[k] - x0 * *Mki0++ - x1 * *Mki1++
- x2 * *Mki2++ - x3 * *Mki3++;
M0 += 4 * ldm + 4;
}
if ( firstcol < ncol - 1 ) { /* Do 2 columns */
Mki0 = M0 + 1;
Mki1 = Mki0 + ldm + 1;
x0 = rhs[firstcol];
x1 = rhs[firstcol+1] - x0 * *Mki0++;
rhs[++firstcol] = x1;
++firstcol;
for (k = firstcol; k < ncol; k++)
rhs[k] = rhs[k] - x0 * *Mki0++ - x1 * *Mki1++;
}
}
/*
* Solves a dense upper triangular system. The upper triangular matrix is
* stored in a 2-dim array M(1:ldm,1:ncol). The solution will be returned
* in the rhs vector.
*/
void
susolve ( ldm, ncol, M, rhs )
int ldm; /* in */
int ncol; /* in */
float *M; /* in */
float *rhs; /* modified */
{
float xj;
int jcol, j, irow;
jcol = ncol - 1;
for (j = 0; j < ncol; j++) {
xj = rhs[jcol] / M[jcol + jcol*ldm]; /* M(jcol, jcol) */
rhs[jcol] = xj;
for (irow = 0; irow < jcol; irow++)
rhs[irow] -= xj * M[irow + jcol*ldm]; /* M(irow, jcol) */
jcol--;
}
}
/*
* Performs a dense matrix-vector multiply: Mxvec = Mxvec + M * vec.
* The input matrix is M(1:nrow,1:ncol); The product is returned in Mxvec[].
*/
void smatvec ( ldm, nrow, ncol, M, vec, Mxvec )
int ldm; /* in -- leading dimension of M */
int nrow; /* in */
int ncol; /* in */
float *M; /* in */
float *vec; /* in */
float *Mxvec; /* in/out */
{
float vi0, vi1, vi2, vi3, vi4, vi5, vi6, vi7;
float *M0;
register float *Mki0, *Mki1, *Mki2, *Mki3, *Mki4, *Mki5, *Mki6, *Mki7;
register int firstcol = 0;
int k;
M0 = &M[0];
while ( firstcol < ncol - 7 ) { /* Do 8 columns */
Mki0 = M0;
Mki1 = Mki0 + ldm;
Mki2 = Mki1 + ldm;
Mki3 = Mki2 + ldm;
Mki4 = Mki3 + ldm;
Mki5 = Mki4 + ldm;
Mki6 = Mki5 + ldm;
Mki7 = Mki6 + ldm;
vi0 = vec[firstcol++];
vi1 = vec[firstcol++];
vi2 = vec[firstcol++];
vi3 = vec[firstcol++];
vi4 = vec[firstcol++];
vi5 = vec[firstcol++];
vi6 = vec[firstcol++];
vi7 = vec[firstcol++];
for (k = 0; k < nrow; k++)
Mxvec[k] += vi0 * *Mki0++ + vi1 * *Mki1++
+ vi2 * *Mki2++ + vi3 * *Mki3++
+ vi4 * *Mki4++ + vi5 * *Mki5++
+ vi6 * *Mki6++ + vi7 * *Mki7++;
M0 += 8 * ldm;
}
while ( firstcol < ncol - 3 ) { /* Do 4 columns */
Mki0 = M0;
Mki1 = Mki0 + ldm;
Mki2 = Mki1 + ldm;
Mki3 = Mki2 + ldm;
vi0 = vec[firstcol++];
vi1 = vec[firstcol++];
vi2 = vec[firstcol++];
vi3 = vec[firstcol++];
for (k = 0; k < nrow; k++)
Mxvec[k] += vi0 * *Mki0++ + vi1 * *Mki1++
+ vi2 * *Mki2++ + vi3 * *Mki3++ ;
M0 += 4 * ldm;
}
while ( firstcol < ncol ) { /* Do 1 column */
Mki0 = M0;
vi0 = vec[firstcol++];
for (k = 0; k < nrow; k++)
Mxvec[k] += vi0 * *Mki0++;
M0 += ldm;
}
}