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/**CFile****************************************************************
FileName [reoSift.c]
PackageName [REO: A specialized DD reordering engine.]
Synopsis [Implementation of the sifting algorihtm.]
Author [Alan Mishchenko]
Affiliation [UC Berkeley]
Date [Ver. 1.0. Started - October 15, 2002.]
Revision [$Id: reoSift.c,v 1.0 2002/15/10 03:00:00 alanmi Exp $]
***********************************************************************/
#include "reo.h"
////////////////////////////////////////////////////////////////////////
/// DECLARATIONS ///
////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////
/// FUNCTION DEFINITIONS ///
////////////////////////////////////////////////////////////////////////
/**Function*************************************************************
Synopsis [Implements the variable sifting algorithm.]
Description [Performs a sequence of adjacent variable swaps known as "sifting".
Uses the cost functions determined by the flag.]
SideEffects []
SeeAlso []
***********************************************************************/
void reoReorderSift( reo_man * p )
{
double CostCurrent; // the cost of the current permutation
double CostLimit; // the maximum increase in cost that can be tolerated
double CostBest; // the best cost
int BestQ; // the best position
int VarCurrent; // the current variable to move
int q; // denotes the current position of the variable
int c; // performs the loops over variables until all of them are sifted
int v; // used for other purposes
assert( p->nSupp > 0 );
// set the current cost depending on the minimization criteria
if ( p->fMinWidth )
CostCurrent = p->nWidthCur;
else if ( p->fMinApl )
CostCurrent = p->nAplCur;
else
CostCurrent = p->nNodesCur;
// find the upper bound on tbe cost growth
CostLimit = 1 + (int)(REO_REORDER_LIMIT * CostCurrent);
// perform sifting for each of p->nSupp variables
for ( c = 0; c < p->nSupp; c++ )
{
// select the current variable to be the one with the largest number of nodes that is not sifted yet
VarCurrent = -1;
CostBest = -1.0;
for ( v = 0; v < p->nSupp; v++ )
{
p->pVarCosts[v] = REO_HIGH_VALUE;
if ( !p->pPlanes[v].fSifted )
{
// VarCurrent = v;
// if ( CostBest < p->pPlanes[v].statsCost )
if ( CostBest < p->pPlanes[v].statsNodes )
{
// CostBest = p->pPlanes[v].statsCost;
CostBest = p->pPlanes[v].statsNodes;
VarCurrent = v;
}
}
}
assert( VarCurrent != -1 );
// mark this variable as sifted
p->pPlanes[VarCurrent].fSifted = 1;
// set the current value
p->pVarCosts[VarCurrent] = CostCurrent;
// set the best cost
CostBest = CostCurrent;
BestQ = VarCurrent;
// determine which way to move the variable first (up or down)
// the rationale is that if we move the shorter way first
// it is more likely that the best position will be found on the longer way
// and the reverse movement (to take the best position) will be faster
if ( VarCurrent < p->nSupp/2 ) // move up first, then down
{
// set the total cost on all levels above the current level
p->pPlanes[0].statsCostAbove = 0;
for ( v = 1; v <= VarCurrent; v++ )
p->pPlanes[v].statsCostAbove = p->pPlanes[v-1].statsCostAbove + p->pPlanes[v-1].statsCost;
// set the total cost on all levels below the current level
p->pPlanes[p->nSupp].statsCostBelow = 0;
for ( v = p->nSupp - 1; v >= VarCurrent; v-- )
p->pPlanes[v].statsCostBelow = p->pPlanes[v+1].statsCostBelow + p->pPlanes[v+1].statsCost;
assert( CostCurrent == p->pPlanes[VarCurrent].statsCostAbove +
p->pPlanes[VarCurrent].statsCost +
p->pPlanes[VarCurrent].statsCostBelow );
// move up
for ( q = VarCurrent-1; q >= 0; q-- )
{
CostCurrent -= reoReorderSwapAdjacentVars( p, q, 1 );
// now q points to the position of this var in the order
p->pVarCosts[q] = CostCurrent;
// update the lower bound (assuming that for level q+1 it is set correctly)
p->pPlanes[q].statsCostBelow = p->pPlanes[q+1].statsCostBelow + p->pPlanes[q+1].statsCost;
// check the upper bound
if ( CostCurrent >= CostLimit )
break;
// check the lower bound
if ( p->pPlanes[q].statsCostBelow + (REO_QUAL_PAR-1)*p->pPlanes[q].statsCostAbove/REO_QUAL_PAR >= CostBest )
break;
// update the best cost
if ( CostBest > CostCurrent )
{
CostBest = CostCurrent;
BestQ = q;
// adjust node limit
CostLimit = ddMin( CostLimit, 1 + (int)(REO_REORDER_LIMIT * CostCurrent) );
}
// when we are reordering for width or APL, it may happen that
// the number of nodes has grown above certain limit,
// in which case we have to resize the data structures
if ( p->fMinWidth || p->fMinApl )
{
if ( p->nNodesCur >= 2 * p->nNodesMaxAlloc )
{
// printf( "Resizing data structures. Old size = %6d. New size = %6d.\n", p->nNodesMaxAlloc, p->nNodesCur );
reoResizeStructures( p, 0, p->nNodesCur, 0 );
}
}
}
// fix the plane index
if ( q == -1 )
q++;
// now p points to the position of this var in the order
// move down
for ( ; q < p->nSupp-1; )
{
CostCurrent -= reoReorderSwapAdjacentVars( p, q, 0 );
q++; // change q to point to the position of this var in the order
// sanity check: the number of nodes on the back pass should be the same
if ( p->pVarCosts[q] != REO_HIGH_VALUE && fabs( p->pVarCosts[q] - CostCurrent ) > REO_COST_EPSILON )
printf("reoReorderSift(): Error! On the backward move, the costs are different.\n");
p->pVarCosts[q] = CostCurrent;
// update the lower bound (assuming that for level q-1 it is set correctly)
p->pPlanes[q].statsCostAbove = p->pPlanes[q-1].statsCostAbove + p->pPlanes[q-1].statsCost;
// check the bounds only if the variable already reached its previous position
if ( q >= BestQ )
{
// check the upper bound
if ( CostCurrent >= CostLimit )
break;
// check the lower bound
if ( p->pPlanes[q].statsCostAbove + (REO_QUAL_PAR-1)*p->pPlanes[q].statsCostBelow/REO_QUAL_PAR >= CostBest )
break;
}
// update the best cost
if ( CostBest >= CostCurrent )
{
CostBest = CostCurrent;
BestQ = q;
// adjust node limit
CostLimit = ddMin( CostLimit, 1 + (int)(REO_REORDER_LIMIT * CostCurrent) );
}
// when we are reordering for width or APL, it may happen that
// the number of nodes has grown above certain limit,
// in which case we have to resize the data structures
if ( p->fMinWidth || p->fMinApl )
{
if ( p->nNodesCur >= 2 * p->nNodesMaxAlloc )
{
// printf( "Resizing data structures. Old size = %6d. New size = %6d.\n", p->nNodesMaxAlloc, p->nNodesCur );
reoResizeStructures( p, 0, p->nNodesCur, 0 );
}
}
}
// move the variable up from the given position (q) to the best position (BestQ)
assert( q >= BestQ );
for ( ; q > BestQ; q-- )
{
CostCurrent -= reoReorderSwapAdjacentVars( p, q-1, 1 );
// sanity check: the number of nodes on the back pass should be the same
if ( fabs( p->pVarCosts[q-1] - CostCurrent ) > REO_COST_EPSILON )
{
printf("reoReorderSift(): Error! On the return move, the costs are different.\n" );
fflush(stdout);
}
}
}
else // move down first, then up
{
// set the current number of nodes on all levels above the given level
p->pPlanes[0].statsCostAbove = 0;
for ( v = 1; v <= VarCurrent; v++ )
p->pPlanes[v].statsCostAbove = p->pPlanes[v-1].statsCostAbove + p->pPlanes[v-1].statsCost;
// set the current number of nodes on all levels below the given level
p->pPlanes[p->nSupp].statsCostBelow = 0;
for ( v = p->nSupp - 1; v >= VarCurrent; v-- )
p->pPlanes[v].statsCostBelow = p->pPlanes[v+1].statsCostBelow + p->pPlanes[v+1].statsCost;
assert( CostCurrent == p->pPlanes[VarCurrent].statsCostAbove +
p->pPlanes[VarCurrent].statsCost +
p->pPlanes[VarCurrent].statsCostBelow );
// move down
for ( q = VarCurrent; q < p->nSupp-1; )
{
CostCurrent -= reoReorderSwapAdjacentVars( p, q, 0 );
q++; // change q to point to the position of this var in the order
p->pVarCosts[q] = CostCurrent;
// update the lower bound (assuming that for level q-1 it is set correctly)
p->pPlanes[q].statsCostAbove = p->pPlanes[q-1].statsCostAbove + p->pPlanes[q-1].statsCost;
// check the upper bound
if ( CostCurrent >= CostLimit )
break;
// check the lower bound
if ( p->pPlanes[q].statsCostAbove + (REO_QUAL_PAR-1)*p->pPlanes[q].statsCostBelow/REO_QUAL_PAR >= CostBest )
break;
// update the best cost
if ( CostBest > CostCurrent )
{
CostBest = CostCurrent;
BestQ = q;
// adjust node limit
CostLimit = ddMin( CostLimit, 1 + (int)(REO_REORDER_LIMIT * CostCurrent) );
}
// when we are reordering for width or APL, it may happen that
// the number of nodes has grown above certain limit,
// in which case we have to resize the data structures
if ( p->fMinWidth || p->fMinApl )
{
if ( p->nNodesCur >= 2 * p->nNodesMaxAlloc )
{
// printf( "Resizing data structures. Old size = %6d. New size = %6d.\n", p->nNodesMaxAlloc, p->nNodesCur );
reoResizeStructures( p, 0, p->nNodesCur, 0 );
}
}
}
// move up
for ( --q; q >= 0; q-- )
{
CostCurrent -= reoReorderSwapAdjacentVars( p, q, 1 );
// now q points to the position of this var in the order
// sanity check: the number of nodes on the back pass should be the same
if ( p->pVarCosts[q] != REO_HIGH_VALUE && fabs( p->pVarCosts[q] - CostCurrent ) > REO_COST_EPSILON )
printf("reoReorderSift(): Error! On the backward move, the costs are different.\n");
p->pVarCosts[q] = CostCurrent;
// update the lower bound (assuming that for level q+1 it is set correctly)
p->pPlanes[q].statsCostBelow = p->pPlanes[q+1].statsCostBelow + p->pPlanes[q+1].statsCost;
// check the bounds only if the variable already reached its previous position
if ( q <= BestQ )
{
// check the upper bound
if ( CostCurrent >= CostLimit )
break;
// check the lower bound
if ( p->pPlanes[q].statsCostBelow + (REO_QUAL_PAR-1)*p->pPlanes[q].statsCostAbove/REO_QUAL_PAR >= CostBest )
break;
}
// update the best cost
if ( CostBest >= CostCurrent )
{
CostBest = CostCurrent;
BestQ = q;
// adjust node limit
CostLimit = ddMin( CostLimit, 1 + (int)(REO_REORDER_LIMIT * CostCurrent) );
}
// when we are reordering for width or APL, it may happen that
// the number of nodes has grown above certain limit,
// in which case we have to resize the data structures
if ( p->fMinWidth || p->fMinApl )
{
if ( p->nNodesCur >= 2 * p->nNodesMaxAlloc )
{
// printf( "Resizing data structures. Old size = %6d. New size = %6d.\n", p->nNodesMaxAlloc, p->nNodesCur );
reoResizeStructures( p, 0, p->nNodesCur, 0 );
}
}
}
// fix the plane index
if ( q == -1 )
q++;
// now q points to the position of this var in the order
// move the variable down from the given position (q) to the best position (BestQ)
assert( q <= BestQ );
for ( ; q < BestQ; q++ )
{
CostCurrent -= reoReorderSwapAdjacentVars( p, q, 0 );
// sanity check: the number of nodes on the back pass should be the same
if ( fabs( p->pVarCosts[q+1] - CostCurrent ) > REO_COST_EPSILON )
{
printf("reoReorderSift(): Error! On the return move, the costs are different.\n" );
fflush(stdout);
}
}
}
assert( fabs( CostBest - CostCurrent ) < REO_COST_EPSILON );
// update the cost
if ( p->fMinWidth )
p->nWidthCur = (int)CostBest;
else if ( p->fMinApl )
p->nAplCur = CostCurrent;
else
p->nNodesCur = (int)CostBest;
}
// remove the sifted attributes if any
for ( v = 0; v < p->nSupp; v++ )
p->pPlanes[v].fSifted = 0;
}
////////////////////////////////////////////////////////////////////////
/// END OF FILE ///
////////////////////////////////////////////////////////////////////////
|
