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Memory management

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Desire NUENTSA
2012-06-07 19:06:22 +02:00
parent 268ba3b521
commit f091879d77
7 changed files with 206 additions and 194 deletions
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72
Eigen/src/SparseLU/SparseLU.h
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@@ -48,7 +48,8 @@ class SparseLU
typedef SparseMatrix<Scalar,ColMajor,Index> NCMatrix;
typedef SuperNodalMatrix<Scalar, Index> SCMatrix;
typedef GlobalLU_t<Scalar, Index> Eigen_GlobalLU_t;
typedef Matrix<Scalar,Dynamic,1> VectorType;
typedef Matrix<Scalar,Dynamic,1> ScalarVector;
typedef Matrix<Index,Dynamic,1> IndexVector;
typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
public:
SparseLU():m_isInitialized(true),m_symmetricmode(false),m_fact(DOFACT),m_diagpivotthresh(1.0)
@@ -93,15 +94,15 @@ class SparseLU
fact_t m_fact;
NCMatrix m_mat; // The input (permuted ) matrix
SCMatrix m_Lstore; // The lower triangular matrix (supernodal)
NCMatrix m_Ustore; //The upper triangular matrix
NCMatrix m_Ustore; // The upper triangular matrix
PermutationType m_perm_c; // Column permutation
PermutationType m_iperm_c; // Column permutation
PermutationType m_perm_r ; // Row permutation
PermutationType m_iperm_r ; // Inverse row permutation
VectorXi m_etree; // Column elimination tree
IndexVector m_etree; // Column elimination tree
Scalar *m_work; //
Index *m_iwork; //
ScalarVector m_work; //
IndexVector m_iwork; //
static Eigen_GlobalLU_t m_Glu; // persistent data to facilitate multiple factors
// should be defined as a class member
// SuperLU/SparseLU options
@@ -158,7 +159,7 @@ void SparseLU::analyzePattern(const MatrixType& mat)
// In symmetric mode, do not do postorder here
if (m_symmetricmode == false) {
VectorXi post, iwork;
IndexVector post, iwork;
// Post order etree
post = internal::TreePostorder(m_mat.cols(), m_etree);
@@ -209,20 +210,20 @@ void SparseLU::factorize(const MatrixType& matrix)
int maxpanel = m_panel_size * m;
// Set up pointers for integer working arrays
Map<VectorXi> segrep(m_iwork, m); //
Map<VectorXi> parent(&segrep(0) + m, m); //
Map<VectorXi> xplore(&parent(0) + m, m); //
Map<VectorXi> repfnz(&xplore(0) + m, maxpanel); //
Map<VectorXi> panel_lsub(&repfnz(0) + maxpanel, maxpanel);//
Map<VectorXi> xprune(&panel_lsub(0) + maxpanel, n); //
Map<VectorXi> marker(&xprune(0)+n, m * LU_NO_MARKER); //
Map<IndexVector> segrep(&m_iwork(0), m); //
Map<IndexVector> parent(&segrep(0) + m, m); //
Map<IndexVector> xplore(&parent(0) + m, m); //
Map<IndexVector> repfnz(&xplore(0) + m, maxpanel); //
Map<IndexVector> panel_lsub(&repfnz(0) + maxpanel, maxpanel);//
Map<IndexVector> xprune(&panel_lsub(0) + maxpanel, n); //
Map<IndexVector> marker(&xprune(0)+n, m * LU_NO_MARKER); //
repfnz.setConstant(-1);
panel_lsub.setConstant(-1);
// Set up pointers for scalar working arrays
VectorType dense(maxpanel);
ScalarVector dense(maxpanel);
dense.setZero();
VectorType tempv(LU_NUM_TEMPV(m,m_panel_size,m_maxsuper,m_rowblk);
ScalarVector tempv(LU_NUM_TEMPV(m,m_panel_size,m_maxsuper,m_rowblk);
tempv.setZero();
// Setup Permutation vectors
@@ -234,7 +235,7 @@ void SparseLU::factorize(const MatrixType& matrix)
iperm_c = m_perm_c.inverse();
// Identify initial relaxed snodes
VectorXi relax_end(n);
IndexVector relax_end(n);
if ( m_symmetricmode = true )
LU_heap_relax_snode(n, m_etree, m_relax, marker, relax_end);
else
@@ -243,11 +244,12 @@ void SparseLU::factorize(const MatrixType& matrix)
m_perm_r.setConstant(-1);
marker.setConstant(-1);
VectorXi& xsup = m_Glu.xsup;
VectorXi& supno = m_GLu.supno;
VectorXi& xlsub = m_Glu.xlsub;
VectorXi& xlusup = m_GLu.xlusup;
VectorXi& xusub = m_Glu.xusub;
IndexVector& xsup = m_Glu.xsup;
IndexVector& supno = m_GLu.supno;
IndexVector& xlsub = m_Glu.xlsub;
IndexVector& xlusup = m_GLu.xlusup;
IndexVector& xusub = m_Glu.xusub;
Index& nzlumax = m_Glu.nzlumax;
supno(0) = IND_EMPTY;
xsup(0) = xlsub(0) = xusub(0) = xlusup(0);
@@ -259,7 +261,7 @@ void SparseLU::factorize(const MatrixType& matrix)
// (b) panel_size contiguous columns, <panel_size> defined by the user
register int jcol,kcol;
int min_mn = std::min(m,n);
VectorXi panel_histo(n);
IndexVector panel_histo(n);
Index nextu, nextlu, jsupno, fsupc, new_next;
int pivrow; // Pivotal row number in the original row matrix
int nseg1; // Number of segments in U-column above panel row jcol
@@ -274,7 +276,7 @@ void SparseLU::factorize(const MatrixType& matrix)
// Factorize the relaxed supernode(jcol:kcol)
// First, determine the union of the row structure of the snode
info = LU_snode_dfs(jcol, kcol, m_mat.innerIndexPtr(), m_mat.outerIndexPtr(), xprune, marker);
if ( !info )
if ( info )
{
m_info = NumericalIssue;
m_factorizationIsOk = false;
@@ -288,8 +290,12 @@ void SparseLU::factorize(const MatrixType& matrix)
nzlumax = m_Glu.nzlumax;
while (new_next > nzlumax )
{
m_Glu.lusup = LUMemXpand<Scalar>(jcol, nextlu, LUSUP, nzlumax);
m_GLu.nzlumax = nzlumax;
mem = LUMemXpand<Scalar>(lusup, nzlumax, nextlu, LUSUP, m_Glu);
if (mem)
{
m_factorizationIsOk = false;
return;
}
}
// Now, left-looking factorize each column within the snode
for (icol = jcol; icol<=kcol; icol++){
@@ -303,7 +309,7 @@ void SparseLU::factorize(const MatrixType& matrix)
// Eliminate the current column
info = LU_pivotL(icol, m_diagpivotthresh, m_perm_r, m_iperm_c, pivrow, m_Glu);
if ( !info )
if ( info )
{
m_info = NumericalIssue;
m_factorizationIsOk = false;
@@ -341,8 +347,8 @@ void SparseLU::factorize(const MatrixType& matrix)
nseg = nseg1; // begin after all the panel segments
//Depth-first-search for the current column
VectorBlock<VectorXi> panel_lsubk(panel_lsub, k, m); //FIXME
VectorBlock<VectorXi> repfnz_k(repfnz, k, m); //FIXME
VectorBlock<IndexVector> panel_lsubk(panel_lsub, k, m); //FIXME
VectorBlock<IndexVector> repfnz_k(repfnz, k, m); //FIXME
info = LU_column_dfs(m, jj, perm_r, nseg, panel_lsub(k), segrep, repfnz_k, xprune, marker, parent, xplore, m_Glu);
if ( !info )
{
@@ -351,10 +357,10 @@ void SparseLU::factorize(const MatrixType& matrix)
return;
}
// Numeric updates to this column
VectorBlock<VectorXi> dense_k(dense, k, m); //FIXME
VectorBlock<VectorXi> segrep_k(segrep, nseg1, m) // FIXME Check the length
VectorBlock<IndexVector> dense_k(dense, k, m); //FIXME
VectorBlock<IndexVector> segrep_k(segrep, nseg1, m) // FIXME Check the length
info = LU_column_bmod(jj, (nseg - nseg1), dense_k, tempv, segrep_k, repfnz_k, jcol, m_Glu);
if ( !info )
if ( info )
{
m_info = NumericalIssue;
m_factorizationIsOk = false;
@@ -364,7 +370,7 @@ void SparseLU::factorize(const MatrixType& matrix)
// Copy the U-segments to ucol(*)
//FIXME Check that repfnz_k, dense_k... have stored references to modified columns
info = LU_copy_to_col(jj, nseg, segrep, repfnz_k, perm_r, dense_k, m_Glu);
if ( !info )
if ( info )
{
m_info = NumericalIssue;
m_factorizationIsOk = false;
@@ -373,7 +379,7 @@ void SparseLU::factorize(const MatrixType& matrix)
// Form the L-segment
info = LU_pivotL(jj, m_diagpivotthresh, m_perm_r, iperm_c, pivrow, m_Glu);
if ( !info )
if ( info )
{
m_info = NumericalIssue;
m_factorizationIsOk = false;