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SparseLU: remove the "snode" path which appears to bring nearly zero speedup
This commit is contained in:
Gael Guennebaud
parent
ac8c694f3e
commit
90fcaf11cf
@ -455,64 +455,6 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
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int i, k, jj;
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int i, k, jj;
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for (jcol = 0; jcol < n; )
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for (jcol = 0; jcol < n; )
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{
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{
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if (relax_end(jcol) != IND_EMPTY)
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{ // Starting a relaxed node from jcol
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kcol = relax_end(jcol); // End index of the relaxed snode
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// Factorize the relaxed supernode(jcol:kcol)
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// First, determine the union of the row structure of the snode
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info = SparseLUBase<Scalar,Index>::LU_snode_dfs(jcol, kcol, m_mat, xprune, marker, m_glu);
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if ( info )
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{
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std::cerr << "MEMORY ALLOCATION FAILED IN SNODE_DFS() \n";
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m_info = NumericalIssue;
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m_factorizationIsOk = false;
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return;
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}
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nextu = m_glu.xusub(jcol); //starting location of column jcol in ucol
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nextlu = m_glu.xlusup(jcol); //Starting location of column jcol in lusup (rectangular supernodes)
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jsupno = m_glu.supno(jcol); // Supernode number which column jcol belongs to
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fsupc = m_glu.xsup(jsupno); //First column number of the current supernode
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int lda = m_glu.xusub(fsupc+1) - m_glu.xusub(fsupc);
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lda = m_glu.xlsub(fsupc+1)-m_glu.xlsub(fsupc);
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new_next = nextlu + lda * (kcol - jcol + 1);
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int mem;
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while (new_next > m_glu.nzlumax )
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{
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mem = SparseLUBase<Scalar,Index>::LUMemXpand(m_glu.lusup, m_glu.nzlumax, nextlu, LUSUP, m_glu.num_expansions);
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if (mem)
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{
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std::cerr << "MEMORY ALLOCATION FAILED FOR L FACTOR \n";
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m_factorizationIsOk = false;
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return;
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}
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}
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// Now, left-looking factorize each column within the snode
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for (icol = jcol; icol<=kcol; icol++){
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m_glu.xusub(icol+1) = nextu;
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// Scatter into SPA dense(*)
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for (typename MatrixType::InnerIterator it(m_mat, icol); it; ++it)
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dense(it.row()) = it.value();
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// Numeric update within the snode
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SparseLUBase<Scalar,Index>::LU_snode_bmod(icol, fsupc, dense, m_glu);
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// Eliminate the current column
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info = SparseLUBase<Scalar,Index>::LU_pivotL(icol, m_diagpivotthresh, m_perm_r.indices(), iperm_c.indices(), pivrow, m_glu);
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if ( info )
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{
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m_info = NumericalIssue;
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std::cerr<< "THE MATRIX IS STRUCTURALLY SINGULAR ... ZERO COLUMN AT " << info <<std::endl;
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m_factorizationIsOk = false;
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return;
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}
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}
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jcol = icol; // The last column te be eliminated
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}
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else
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{ // Work on one panel of panel_size columns
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// Adjust panel size so that a panel won't overlap with the next relaxed snode.
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// Adjust panel size so that a panel won't overlap with the next relaxed snode.
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int panel_size = m_perfv.panel_size; // upper bound on panel width
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int panel_size = m_perfv.panel_size; // upper bound on panel width
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for (k = jcol + 1; k < (std::min)(jcol+panel_size, n); k++)
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for (k = jcol + 1; k < (std::min)(jcol+panel_size, n); k++)
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@ -592,7 +534,6 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
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}
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}
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} // end SparseLU within the panel
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} // end SparseLU within the panel
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jcol += panel_size; // Move to the next panel
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jcol += panel_size; // Move to the next panel
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} // end else
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} // end for -- end elimination
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} // end for -- end elimination
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// Count the number of nonzeros in factors
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// Count the number of nonzeros in factors
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@ -628,4 +569,5 @@ struct solve_retval<SparseLU<_MatrixType,Derived>, Rhs>
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} // end namespace internal
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} // end namespace internal
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} // End namespace Eigen
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} // End namespace Eigen
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#endif
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#endif
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@ -57,8 +57,6 @@ struct SparseLUBase
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#include "SparseLU_Memory.h"
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#include "SparseLU_Memory.h"
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#include "SparseLU_heap_relax_snode.h"
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#include "SparseLU_heap_relax_snode.h"
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#include "SparseLU_relax_snode.h"
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#include "SparseLU_relax_snode.h"
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#include "SparseLU_snode_dfs.h"
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#include "SparseLU_snode_bmod.h"
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#include "SparseLU_pivotL.h"
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#include "SparseLU_pivotL.h"
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#include "SparseLU_panel_dfs.h"
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#include "SparseLU_panel_dfs.h"
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#include "SparseLU_kernel_bmod.h"
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#include "SparseLU_kernel_bmod.h"
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@ -1,84 +0,0 @@
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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/*
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* NOTE: This file is the modified version of [s,d,c,z]snode_bmod.c file in SuperLU
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* -- SuperLU routine (version 3.0) --
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* Univ. of California Berkeley, Xerox Palo Alto Research Center,
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* and Lawrence Berkeley National Lab.
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* October 15, 2003
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*
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* Copyright (c) 1994 by Xerox Corporation. All rights reserved.
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*
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* THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
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* EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
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*
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* Permission is hereby granted to use or copy this program for any
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* purpose, provided the above notices are retained on all copies.
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* Permission to modify the code and to distribute modified code is
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* granted, provided the above notices are retained, and a notice that
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* the code was modified is included with the above copyright notice.
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*/
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#ifndef SPARSELU_SNODE_BMOD_H
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#define SPARSELU_SNODE_BMOD_H
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template <typename Scalar, typename Index>
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int SparseLUBase<Scalar,Index>::LU_snode_bmod (const int jcol, const int fsupc, ScalarVector& dense, GlobalLU_t& glu)
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{
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/* lsub : Compressed row subscripts of ( rectangular supernodes )
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* xlsub : xlsub[j] is the starting location of the j-th column in lsub(*)
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* lusup : Numerical values of the rectangular supernodes
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* xlusup[j] is the starting location of the j-th column in lusup(*)
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*/
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int nextlu = glu.xlusup(jcol); // Starting location of the next column to add
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int irow, isub;
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// Process the supernodal portion of L\U[*,jcol]
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for (isub = glu.xlsub(fsupc); isub < glu.xlsub(fsupc+1); isub++)
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{
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irow = glu.lsub(isub);
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glu.lusup(nextlu) = dense(irow);
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dense(irow) = 0;
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++nextlu;
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}
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// Make sure the leading dimension is a multiple of the underlying packet size
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// so that fast fully aligned kernels can be enabled:
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{
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Index lda = nextlu-glu.xlusup(jcol);
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int offset = internal::first_multiple<Index>(lda, internal::packet_traits<Scalar>::size) - lda;
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if(offset)
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{
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glu.lusup.segment(nextlu,offset).setZero();
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nextlu += offset;
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}
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}
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glu.xlusup(jcol + 1) = nextlu; // Initialize xlusup for next column ( jcol+1 )
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if (fsupc < jcol ){
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int luptr = glu.xlusup(fsupc); // points to the first column of the supernode
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int nsupr = glu.xlsub(fsupc + 1) -glu.xlsub(fsupc); //Number of rows in the supernode
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int nsupc = jcol - fsupc; // Number of columns in the supernodal portion of L\U[*,jcol]
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int ufirst = glu.xlusup(jcol); // points to the beginning of column jcol in supernode L\U(jsupno)
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int lda = glu.xlusup(jcol+1) - ufirst;
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int nrow = nsupr - nsupc; // Number of rows in the off-diagonal blocks
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// Solve the triangular system for U(fsupc:jcol, jcol) with L(fspuc:jcol, fsupc:jcol)
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Map<Matrix<Scalar,Dynamic,Dynamic>,0,OuterStride<> > A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
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VectorBlock<ScalarVector> u(glu.lusup, ufirst, nsupc);
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u = A.template triangularView<UnitLower>().solve(u); // Call the Eigen dense triangular solve interface
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// Update the trailing part of the column jcol U(jcol:jcol+nrow, jcol) using L(jcol:jcol+nrow, fsupc:jcol) and U(fsupc:jcol)
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new (&A) Map<Matrix<Scalar,Dynamic,Dynamic>,0,OuterStride<> > ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
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VectorBlock<ScalarVector> l(glu.lusup, ufirst+nsupc, nrow);
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l.noalias() -= A * u;
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}
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return 0;
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}
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#endif
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@ -1,95 +0,0 @@
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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/*
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* NOTE: This file is the modified version of [s,d,c,z]snode_dfs.c file in SuperLU
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* -- SuperLU routine (version 2.0) --
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* Univ. of California Berkeley, Xerox Palo Alto Research Center,
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* and Lawrence Berkeley National Lab.
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* November 15, 1997
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*
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* Copyright (c) 1994 by Xerox Corporation. All rights reserved.
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*
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* THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
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* EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
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*
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* Permission is hereby granted to use or copy this program for any
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* purpose, provided the above notices are retained on all copies.
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* Permission to modify the code and to distribute modified code is
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* granted, provided the above notices are retained, and a notice that
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* the code was modified is included with the above copyright notice.
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*/
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#ifndef SPARSELU_SNODE_DFS_H
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#define SPARSELU_SNODE_DFS_H
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/**
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* \brief Determine the union of the row structures of those columns within the relaxed snode.
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* NOTE: The relaxed snodes are leaves of the supernodal etree, therefore,
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* the portion outside the rectangular supernode must be zero.
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*
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* \param jcol start of the supernode
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* \param kcol end of the supernode
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* \param asub Row indices
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* \param colptr Pointer to the beginning of each column
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* \param xprune (out) The pruned tree ??
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* \param marker (in/out) working vector
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* \return 0 on success, > 0 size of the memory when memory allocation failed
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*/
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template <typename Scalar, typename Index>
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int SparseLUBase<Scalar,Index>::LU_snode_dfs(const int jcol, const int kcol,const MatrixType& mat, IndexVector& xprune, IndexVector& marker, GlobalLU_t& glu)
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{
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int mem;
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Index nsuper = ++glu.supno(jcol); // Next available supernode number
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int nextl = glu.xlsub(jcol); //Index of the starting location of the jcol-th column in lsub
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int krow,kmark;
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for (int i = jcol; i <=kcol; i++)
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{
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// For each nonzero in A(*,i)
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for (typename MatrixType::InnerIterator it(mat, i); it; ++it)
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{
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krow = it.row();
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kmark = marker(krow);
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if ( kmark != kcol )
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{
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// First time to visit krow
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marker(krow) = kcol;
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glu.lsub(nextl++) = krow;
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if( nextl >= glu.nzlmax )
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{
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mem = LUMemXpand<IndexVector>(glu.lsub, glu.nzlmax, nextl, LSUB, glu.num_expansions);
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if (mem) return mem; // Memory expansion failed... Return the memory allocated so far
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}
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}
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}
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glu.supno(i) = nsuper;
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}
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// If supernode > 1, then make a copy of the subscripts for pruning
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if (jcol < kcol)
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{
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Index new_next = nextl + (nextl - glu.xlsub(jcol));
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while (new_next > glu.nzlmax)
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{
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mem = LUMemXpand<IndexVector>(glu.lsub, glu.nzlmax, nextl, LSUB, glu.num_expansions);
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if (mem) return mem; // Memory expansion failed... Return the memory allocated so far
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}
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Index ifrom, ito = nextl;
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for (ifrom = glu.xlsub(jcol); ifrom < nextl;)
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glu.lsub(ito++) = glu.lsub(ifrom++);
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for (int i = jcol+1; i <=kcol; i++) glu.xlsub(i) = nextl;
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nextl = ito;
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}
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glu.xsup(nsuper+1) = kcol + 1; // Start of next available supernode
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glu.supno(kcol+1) = nsuper;
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xprune(kcol) = nextl;
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glu.xlsub(kcol+1) = nextl;
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return 0;
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}
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#endif
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