Module: ppl/ppl Branch: pip Commit: 8fcb1702a990a056b5ae539d6a47260dd00ff08c URL: http://www.cs.unipr.it/git/gitweb.cgi?p=ppl/ppl.git;a=commit;h=8fcb1702a990a...
Author: François Galea francois.galea@uvsq.fr Date: Fri Nov 20 09:58:38 2009 +0100
Optimized the solver main loop using PPL_DIRTY_TEMP_COEFFICIENT's.
---
src/PIP_Tree.cc | 40 ++++++++++++++++++++++++---------------- 1 files changed, 24 insertions(+), 16 deletions(-)
diff --git a/src/PIP_Tree.cc b/src/PIP_Tree.cc index e868427..b6f065d 100644 --- a/src/PIP_Tree.cc +++ b/src/PIP_Tree.cc @@ -1409,10 +1409,10 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, << std::endl; #endif dimension_type k; - Coefficient z(0); - Coefficient sij, cij, cij_; - Coefficient c; - Row &row = tableau.s[i_]; + const Row& row = tableau.s[i_]; + PPL_DIRTY_TEMP_COEFFICIENT(sij); + PPL_DIRTY_TEMP_COEFFICIENT(cij); + PPL_DIRTY_TEMP_COEFFICIENT(cij_); /* Look for a positive S_ij such as the j^th column/S_ij is lexico-minimal */ @@ -1461,6 +1461,7 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, #endif
/* ** Perform pivot operation ** */ + PPL_DIRTY_TEMP_COEFFICIENT(c);
/* update basis */ dimension_type var_j = var_column[j_]; @@ -1481,8 +1482,10 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, prt.swap(tableau.t[i_]); sign[i_] = ZERO; /* save current denominator corresponding to sij */ - Coefficient sij_denom = tableau.get_denominator(); + PPL_DIRTY_TEMP_COEFFICIENT(sij_denom); + sij_denom = tableau.get_denominator(); /* Compute columns s[*][j] : s[k][j] -= s[k][j_] * prs[j] / sij */ + PPL_DIRTY_TEMP_COEFFICIENT(scale_factor); for (j=0; j<num_vars; ++j) { if (j==j_) continue; @@ -1491,11 +1494,12 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, // if element j of pivot row is zero, nothing to do for this column continue; for (k=0; k<num_rows; ++k) { - Coefficient mult = prsj * tableau.s[k][j_]; + PPL_DIRTY_TEMP_COEFFICIENT(mult); + mult = prsj * tableau.s[k][j_]; if (mult % sij != 0) { // Must scale matrix to stay in integer case gcd_assign(gcd, mult, sij); - Coefficient scale_factor = sij/gcd; + scale_factor = sij/gcd; tableau.scale(scale_factor); mult *= scale_factor; } @@ -1510,11 +1514,11 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, // if element j of pivot row is zero, nothing to do for this column continue; for (k=0; k<num_rows; ++k) { - Coefficient c = prtj * tableau.s[k][j_]; + c = prtj * tableau.s[k][j_]; if (c % sij != 0) { // Must scale matrix to stay in integer case gcd_assign(gcd, c, sij); - Coefficient scale_factor = sij/gcd; + scale_factor = sij/gcd; tableau.scale(scale_factor); c *= scale_factor; } @@ -1550,11 +1554,12 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, // Update column only if pivot != 1 for (k=0; k<num_rows; ++k) { Coefficient& c = tableau.s[k][j_]; - Coefficient numerator = c * sij_denom; + PPL_DIRTY_TEMP_COEFFICIENT(numerator); + numerator = c * sij_denom; if (numerator % sij != 0) { - Coefficient gcd; + PPL_DIRTY_TEMP_COEFFICIENT(gcd); gcd_assign(gcd, numerator, sij); - Coefficient scale_factor = sij/gcd; + scale_factor = sij/gcd; tableau.scale(scale_factor); numerator *= scale_factor; } @@ -1567,7 +1572,8 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, /* Otherwise, we have found a row i__ with mixed parameter sign. */ else if (i__ != n_a_d) { dimension_type neg = n_a_d; - Coefficient ns, score; + PPL_DIRTY_TEMP_COEFFICIENT(ns); + PPL_DIRTY_TEMP_COEFFICIENT(score);
/* Look for a constraint with mixed parameter sign with no positive * variable coefficients */ @@ -1613,8 +1619,9 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, #endif } else { /* Heuristically choose "best" pivoting row. */ - Coefficient score; - Coefficient best = 0; + PPL_DIRTY_TEMP_COEFFICIENT(score); + PPL_DIRTY_TEMP_COEFFICIENT(best); + best = 0; dimension_type best_i = n_a_d; for (i = i__; i < num_rows; ++i) { if (sign[i] != MIXED) @@ -1762,7 +1769,8 @@ PIP_Solution_Node::solve(PIP_Tree_Node*& parent_ref, the "deepest" cut */ PPL_DIRTY_TEMP_COEFFICIENT(score); PPL_DIRTY_TEMP_COEFFICIENT(score2); - Coefficient best_score = 0; + PPL_DIRTY_TEMP_COEFFICIENT(best_score); + best_score = 0; dimension_type best_i = n_a_d; dimension_type best_pcount = n_a_d; dimension_type pcount;