From 4812c90424dfc40d26725244723887a2d16ddfd9 Mon Sep 17 00:00:00 2001 From: Alan Mishchenko Date: Mon, 1 Oct 2007 08:01:00 -0700 Subject: Version abc71001 --- src/bdd/cudd/cuddGenetic.c | 921 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 921 insertions(+) create mode 100644 src/bdd/cudd/cuddGenetic.c (limited to 'src/bdd/cudd/cuddGenetic.c') diff --git a/src/bdd/cudd/cuddGenetic.c b/src/bdd/cudd/cuddGenetic.c new file mode 100644 index 00000000..9fe03dad --- /dev/null +++ b/src/bdd/cudd/cuddGenetic.c @@ -0,0 +1,921 @@ +/**CFile*********************************************************************** + + FileName [cuddGenetic.c] + + PackageName [cudd] + + Synopsis [Genetic algorithm for variable reordering.] + + Description [Internal procedures included in this file: + + Static procedures included in this module: + + + The genetic algorithm implemented here is as follows. We start with + the current DD order. We sift this order and use this as the + reference DD. We only keep 1 DD around for the entire process and + simply rearrange the order of this DD, storing the various orders + and their corresponding DD sizes. We generate more random orders to + build an initial population. This initial population is 3 times the + number of variables, with a maximum of 120. Each random order is + built (from the reference DD) and its size stored. Each random + order is also sifted to keep the DD sizes fairly small. Then a + crossover is performed between two orders (picked randomly) and the + two resulting DDs are built and sifted. For each new order, if its + size is smaller than any DD in the population, it is inserted into + the population and the DD with the largest number of nodes is thrown + out. The crossover process happens up to 50 times, and at this point + the DD in the population with the smallest size is chosen as the + result. This DD must then be built from the reference DD.] + + SeeAlso [] + + Author [Curt Musfeldt, Alan Shuler, Fabio Somenzi] + + Copyright [This file was created at the University of Colorado at + Boulder. The University of Colorado at Boulder makes no warranty + about the suitability of this software for any purpose. It is + presented on an AS IS basis.] + +******************************************************************************/ + +#include "util_hack.h" +#include "cuddInt.h" + +/*---------------------------------------------------------------------------*/ +/* Constant declarations */ +/*---------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* Stucture declarations */ +/*---------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* Type declarations */ +/*---------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* Variable declarations */ +/*---------------------------------------------------------------------------*/ + +#ifndef lint +static char rcsid[] DD_UNUSED = "$Id: cuddGenetic.c,v 1.1.1.1 2003/02/24 22:23:52 wjiang Exp $"; +#endif + +static int popsize; /* the size of the population */ +static int numvars; /* the number of input variables in the ckt. */ +/* storedd stores the population orders and sizes. This table has two +** extra rows and one extras column. The two extra rows are used for the +** offspring produced by a crossover. Each row stores one order and its +** size. The order is stored by storing the indices of variables in the +** order in which they appear in the order. The table is in reality a +** one-dimensional array which is accessed via a macro to give the illusion +** it is a two-dimensional structure. +*/ +static int *storedd; +static st_table *computed; /* hash table to identify existing orders */ +static int *repeat; /* how many times an order is present */ +static int large; /* stores the index of the population with + ** the largest number of nodes in the DD */ +static int result; +static int cross; /* the number of crossovers to perform */ + +/*---------------------------------------------------------------------------*/ +/* Macro declarations */ +/*---------------------------------------------------------------------------*/ + +/* macro used to access the population table as if it were a +** two-dimensional structure. +*/ +#define STOREDD(i,j) storedd[(i)*(numvars+1)+(j)] + + +/**AutomaticStart*************************************************************/ + +/*---------------------------------------------------------------------------*/ +/* Static function prototypes */ +/*---------------------------------------------------------------------------*/ + +static int make_random ARGS((DdManager *table, int lower)); +static int sift_up ARGS((DdManager *table, int x, int x_low)); +static int build_dd ARGS((DdManager *table, int num, int lower, int upper)); +static int largest ARGS(()); +static int rand_int ARGS((int a)); +static int array_hash ARGS((char *array, int modulus)); +static int array_compare ARGS((const char *array1, const char *array2)); +static int find_best ARGS(()); +static double find_average_fitness ARGS(()); +static int PMX ARGS((int maxvar)); +static int roulette ARGS((int *p1, int *p2)); + +/**AutomaticEnd***************************************************************/ + + +/*---------------------------------------------------------------------------*/ +/* Definition of exported functions */ +/*---------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* Definition of internal functions */ +/*---------------------------------------------------------------------------*/ + + +/**Function******************************************************************** + + Synopsis [Genetic algorithm for DD reordering.] + + Description [Genetic algorithm for DD reordering. + The two children of a crossover will be stored in + storedd[popsize] and storedd[popsize+1] --- the last two slots in the + storedd array. (This will make comparisons and replacement easy.) + Returns 1 in case of success; 0 otherwise.] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +int +cuddGa( + DdManager * table /* manager */, + int lower /* lowest level to be reordered */, + int upper /* highest level to be reorderded */) +{ + int i,n,m; /* dummy/loop vars */ + int index; + double average_fitness; + int small; /* index of smallest DD in population */ + + /* Do an initial sifting to produce at least one reasonable individual. */ + if (!cuddSifting(table,lower,upper)) return(0); + + /* Get the initial values. */ + numvars = upper - lower + 1; /* number of variables to be reordered */ + if (table->populationSize == 0) { + popsize = 3 * numvars; /* population size is 3 times # of vars */ + if (popsize > 120) { + popsize = 120; /* Maximum population size is 120 */ + } + } else { + popsize = table->populationSize; /* user specified value */ + } + if (popsize < 4) popsize = 4; /* enforce minimum population size */ + + /* Allocate population table. */ + storedd = ALLOC(int,(popsize+2)*(numvars+1)); + if (storedd == NULL) { + table->errorCode = CUDD_MEMORY_OUT; + return(0); + } + + /* Initialize the computed table. This table is made up of two data + ** structures: A hash table with the key given by the order, which says + ** if a given order is present in the population; and the repeat + ** vector, which says how many copies of a given order are stored in + ** the population table. If there are multiple copies of an order, only + ** one has a repeat count greater than 1. This copy is the one pointed + ** by the computed table. + */ + repeat = ALLOC(int,popsize); + if (repeat == NULL) { + table->errorCode = CUDD_MEMORY_OUT; + FREE(storedd); + return(0); + } + for (i = 0; i < popsize; i++) { + repeat[i] = 0; + } + computed = st_init_table(array_compare,array_hash); + if (computed == NULL) { + table->errorCode = CUDD_MEMORY_OUT; + FREE(storedd); + FREE(repeat); + return(0); + } + + /* Copy the current DD and its size to the population table. */ + for (i = 0; i < numvars; i++) { + STOREDD(0,i) = table->invperm[i+lower]; /* order of initial DD */ + } + STOREDD(0,numvars) = table->keys - table->isolated; /* size of initial DD */ + + /* Store the initial order in the computed table. */ + if (st_insert(computed,(char *)storedd,(char *) 0) == ST_OUT_OF_MEM) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + repeat[0]++; + + /* Insert the reverse order as second element of the population. */ + for (i = 0; i < numvars; i++) { + STOREDD(1,numvars-1-i) = table->invperm[i+lower]; /* reverse order */ + } + + /* Now create the random orders. make_random fills the population + ** table with random permutations. The successive loop builds and sifts + ** the DDs for the reverse order and each random permutation, and stores + ** the results in the computed table. + */ + if (!make_random(table,lower)) { + table->errorCode = CUDD_MEMORY_OUT; + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + for (i = 1; i < popsize; i++) { + result = build_dd(table,i,lower,upper); /* build and sift order */ + if (!result) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + if (st_lookup(computed,(char *)&STOREDD(i,0),(char **)&index)) { + repeat[index]++; + } else { + if (st_insert(computed,(char *)&STOREDD(i,0),(char *)(long)i) == + ST_OUT_OF_MEM) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + repeat[i]++; + } + } + +#if 0 +#ifdef DD_STATS + /* Print the initial population. */ + (void) fprintf(table->out,"Initial population after sifting\n"); + for (m = 0; m < popsize; m++) { + for (i = 0; i < numvars; i++) { + (void) fprintf(table->out," %2d",STOREDD(m,i)); + } + (void) fprintf(table->out," : %3d (%d)\n", + STOREDD(m,numvars),repeat[m]); + } +#endif +#endif + + small = find_best(); + average_fitness = find_average_fitness(); +#ifdef DD_STATS + (void) fprintf(table->out,"\nInitial population: best fitness = %d, average fitness %8.3f",STOREDD(small,numvars),average_fitness); +#endif + + /* Decide how many crossovers should be tried. */ + if (table->numberXovers == 0) { + cross = 3*numvars; + if (cross > 60) { /* do a maximum of 50 crossovers */ + cross = 60; + } + } else { + cross = table->numberXovers; /* use user specified value */ + } + + /* Perform the crossovers to get the best order. */ + for (m = 0; m < cross; m++) { + if (!PMX(table->size)) { /* perform one crossover */ + table->errorCode = CUDD_MEMORY_OUT; + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + /* The offsprings are left in the last two entries of the + ** population table. These are now considered in turn. + */ + for (i = popsize; i <= popsize+1; i++) { + result = build_dd(table,i,lower,upper); /* build and sift child */ + if (!result) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + large = largest(); /* find the largest DD in population */ + + /* If the new child is smaller than the largest DD in the current + ** population, enter it into the population in place of the + ** largest DD. + */ + if (STOREDD(i,numvars) < STOREDD(large,numvars)) { + /* Look up the largest DD in the computed table. + ** Decrease its repetition count. If the repetition count + ** goes to 0, remove the largest DD from the computed table. + */ + result = st_lookup(computed,(char *)&STOREDD(large,0),(char + **)&index); + if (!result) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + repeat[index]--; + if (repeat[index] == 0) { + int *pointer = &STOREDD(index,0); + result = st_delete(computed, (char **)&pointer,NULL); + if (!result) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + } + /* Copy the new individual to the entry of the + ** population table just made available and update the + ** computed table. + */ + for (n = 0; n <= numvars; n++) { + STOREDD(large,n) = STOREDD(i,n); + } + if (st_lookup(computed,(char *)&STOREDD(large,0),(char + **)&index)) { + repeat[index]++; + } else { + if (st_insert(computed,(char *)&STOREDD(large,0), + (char *)(long)large) == ST_OUT_OF_MEM) { + FREE(storedd); + FREE(repeat); + st_free_table(computed); + return(0); + } + repeat[large]++; + } + } + } + } + + /* Find the smallest DD in the population and build it; + ** that will be the result. + */ + small = find_best(); + + /* Print stats on the final population. */ +#ifdef DD_STATS + average_fitness = find_average_fitness(); + (void) fprintf(table->out,"\nFinal population: best fitness = %d, average fitness %8.3f",STOREDD(small,numvars),average_fitness); +#endif + + /* Clean up, build the result DD, and return. */ + st_free_table(computed); + computed = NULL; + result = build_dd(table,small,lower,upper); + FREE(storedd); + FREE(repeat); + return(result); + +} /* end of cuddGa */ + + +/*---------------------------------------------------------------------------*/ +/* Definition of static functions */ +/*---------------------------------------------------------------------------*/ + +/**Function******************************************************************** + + Synopsis [Generates the random sequences for the initial population.] + + Description [Generates the random sequences for the initial population. + The sequences are permutations of the indices between lower and + upper in the current order.] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +make_random( + DdManager * table, + int lower) +{ + int i,j; /* loop variables */ + int *used; /* is a number already in a permutation */ + int next; /* next random number without repetitions */ + + used = ALLOC(int,numvars); + if (used == NULL) { + table->errorCode = CUDD_MEMORY_OUT; + return(0); + } +#if 0 +#ifdef DD_STATS + (void) fprintf(table->out,"Initial population before sifting\n"); + for (i = 0; i < 2; i++) { + for (j = 0; j < numvars; j++) { + (void) fprintf(table->out," %2d",STOREDD(i,j)); + } + (void) fprintf(table->out,"\n"); + } +#endif +#endif + for (i = 2; i < popsize; i++) { + for (j = 0; j < numvars; j++) { + used[j] = 0; + } + /* Generate a permutation of {0...numvars-1} and use it to + ** permute the variables in the layesr from lower to upper. + */ + for (j = 0; j < numvars; j++) { + do { + next = rand_int(numvars-1); + } while (used[next] != 0); + used[next] = 1; + STOREDD(i,j) = table->invperm[next+lower]; + } +#if 0 +#ifdef DD_STATS + /* Print the order just generated. */ + for (j = 0; j < numvars; j++) { + (void) fprintf(table->out," %2d",STOREDD(i,j)); + } + (void) fprintf(table->out,"\n"); +#endif +#endif + } + FREE(used); + return(1); + +} /* end of make_random */ + + +/**Function******************************************************************** + + Synopsis [Moves one variable up.] + + Description [Takes a variable from position x and sifts it up to + position x_low; x_low should be less than x. Returns 1 if successful; + 0 otherwise] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +sift_up( + DdManager * table, + int x, + int x_low) +{ + int y; + int size; + + y = cuddNextLow(table,x); + while (y >= x_low) { + size = cuddSwapInPlace(table,y,x); + if (size == 0) { + return(0); + } + x = y; + y = cuddNextLow(table,x); + } + return(1); + +} /* end of sift_up */ + + +/**Function******************************************************************** + + Synopsis [Builds a DD from a given order.] + + Description [Builds a DD from a given order. This procedure also + sifts the final order and inserts into the array the size in nodes + of the result. Returns 1 if successful; 0 otherwise.] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +build_dd( + DdManager * table, + int num /* the index of the individual to be built */, + int lower, + int upper) +{ + int i,j; /* loop vars */ + int position; + int index; + int limit; /* how large the DD for this order can grow */ + int size; + + /* Check the computed table. If the order already exists, it + ** suffices to copy the size from the existing entry. + */ + if (computed && st_lookup(computed,(char *)&STOREDD(num,0),(char **)&index)) { + STOREDD(num,numvars) = STOREDD(index,numvars); +#ifdef DD_STATS + (void) fprintf(table->out,"\nCache hit for index %d", index); +#endif + return(1); + } + + /* Stop if the DD grows 20 times larges than the reference size. */ + limit = 20 * STOREDD(0,numvars); + + /* Sift up the variables so as to build the desired permutation. + ** First the variable that has to be on top is sifted to the top. + ** Then the variable that has to occupy the secon position is sifted + ** up to the second position, and so on. + */ + for (j = 0; j < numvars; j++) { + i = STOREDD(num,j); + position = table->perm[i]; + result = sift_up(table,position,j+lower); + if (!result) return(0); + size = table->keys - table->isolated; + if (size > limit) break; + } + + /* Sift the DD just built. */ +#ifdef DD_STATS + (void) fprintf(table->out,"\n"); +#endif + result = cuddSifting(table,lower,upper); + if (!result) return(0); + + /* Copy order and size to table. */ + for (j = 0; j < numvars; j++) { + STOREDD(num,j) = table->invperm[lower+j]; + } + STOREDD(num,numvars) = table->keys - table->isolated; /* size of new DD */ + return(1); + +} /* end of build_dd */ + + +/**Function******************************************************************** + + Synopsis [Finds the largest DD in the population.] + + Description [Finds the largest DD in the population. If an order is + repeated, it avoids choosing the copy that is in the computed table + (it has repeat[i] > 1).] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +largest( + ) +{ + int i; /* loop var */ + int big; /* temporary holder to return result */ + + big = 0; + while (repeat[big] > 1) big++; + for (i = big + 1; i < popsize; i++) { + if (STOREDD(i,numvars) >= STOREDD(big,numvars) && repeat[i] <= 1) { + big = i; + } + } + return(big); + +} /* end of largest */ + + +/**Function******************************************************************** + + Synopsis [Generates a random number between 0 and the integer a.] + + Description [] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +rand_int( + int a) +{ + return(Cudd_Random() % (a+1)); + +} /* end of rand_int */ + + +/**Function******************************************************************** + + Synopsis [Hash function for the computed table.] + + Description [Hash function for the computed table. Returns the bucket + number.] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +array_hash( + char * array, + int modulus) +{ + int val = 0; + int i; + int *intarray; + + intarray = (int *) array; + + for (i = 0; i < numvars; i++) { + val = val * 997 + intarray[i]; + } + + return ((val < 0) ? -val : val) % modulus; + +} /* end of array_hash */ + + +/**Function******************************************************************** + + Synopsis [Comparison function for the computed table.] + + Description [Comparison function for the computed table. Returns 0 if + the two arrays are equal; 1 otherwise.] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +array_compare( + const char * array1, + const char * array2) +{ + int i; + int *intarray1, *intarray2; + + intarray1 = (int *) array1; + intarray2 = (int *) array2; + + for (i = 0; i < numvars; i++) { + if (intarray1[i] != intarray2[i]) return(1); + } + return(0); + +} /* end of array_compare */ + + +/**Function******************************************************************** + + Synopsis [Returns the index of the fittest individual.] + + Description [] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +find_best( + ) +{ + int i,small; + + small = 0; + for (i = 1; i < popsize; i++) { + if (STOREDD(i,numvars) < STOREDD(small,numvars)) { + small = i; + } + } + return(small); + +} /* end of find_best */ + + +/**Function******************************************************************** + + Synopsis [Returns the average fitness of the population.] + + Description [] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static double +find_average_fitness( + ) +{ + int i; + int total_fitness = 0; + double average_fitness; + + for (i = 0; i < popsize; i++) { + total_fitness += STOREDD(i,numvars); + } + average_fitness = (double) total_fitness / (double) popsize; + return(average_fitness); + +} /* end of find_average_fitness */ + + +/**Function******************************************************************** + + Synopsis [Performs the crossover between two parents.] + + Description [Performs the crossover between two randomly chosen + parents, and creates two children, x1 and x2. Uses the Partially + Matched Crossover operator.] + + SideEffects [None] + + SeeAlso [] + +******************************************************************************/ +static int +PMX( + int maxvar) +{ + int cut1,cut2; /* the two cut positions (random) */ + int mom,dad; /* the two randomly chosen parents */ + int *inv1; /* inverse permutations for repair algo */ + int *inv2; + int i; /* loop vars */ + int u,v; /* aux vars */ + + inv1 = ALLOC(int,maxvar); + if (inv1 == NULL) { + return(0); + } + inv2 = ALLOC(int,maxvar); + if (inv2 == NULL) { + FREE(inv1); + return(0); + } + + /* Choose two orders from the population using roulette wheel. */ + if (!roulette(&mom,&dad)) { + FREE(inv1); + FREE(inv2); + return(0); + } + + /* Choose two random cut positions. A cut in position i means that + ** the cut immediately precedes position i. If cut1 < cut2, we + ** exchange the middle of the two orderings; otherwise, we + ** exchange the beginnings and the ends. + */ + cut1 = rand_int(numvars-1); + do { + cut2 = rand_int(numvars-1); + } while (cut1 == cut2); + +#if 0 + /* Print out the parents. */ + (void) fprintf(table->out, + "Crossover of %d (mom) and %d (dad) between %d and %d\n", + mom,dad,cut1,cut2); + for (i = 0; i < numvars; i++) { + if (i == cut1 || i == cut2) (void) fprintf(table->out,"|"); + (void) fprintf(table->out,"%2d ",STOREDD(mom,i)); + } + (void) fprintf(table->out,"\n"); + for (i = 0; i < numvars; i++) { + if (i == cut1 || i == cut2) (void) fprintf(table->out,"|"); + (void) fprintf(table->out,"%2d ",STOREDD(dad,i)); + } + (void) fprintf(table->out,"\n"); +#endif + + /* Initialize the inverse permutations: -1 means yet undetermined. */ + for (i = 0; i < maxvar; i++) { + inv1[i] = -1; + inv2[i] = -1; + } + + /* Copy the portions whithin the cuts. */ + for (i = cut1; i != cut2; i = (i == numvars-1) ? 0 : i+1) { + STOREDD(popsize,i) = STOREDD(dad,i); + inv1[STOREDD(popsize,i)] = i; + STOREDD(popsize+1,i) = STOREDD(mom,i); + inv2[STOREDD(popsize+1,i)] = i; + } + + /* Now apply the repair algorithm outside the cuts. */ + for (i = cut2; i != cut1; i = (i == numvars-1 ) ? 0 : i+1) { + v = i; + do { + u = STOREDD(mom,v); + v = inv1[u]; + } while (v != -1); + STOREDD(popsize,i) = u; + inv1[u] = i; + v = i; + do { + u = STOREDD(dad,v); + v = inv2[u]; + } while (v != -1); + STOREDD(popsize+1,i) = u; + inv2[u] = i; + } + +#if 0 + /* Print the results of crossover. */ + for (i = 0; i < numvars; i++) { + if (i == cut1 || i == cut2) (void) fprintf(table->out,"|"); + (void) fprintf(table->out,"%2d ",STOREDD(popsize,i)); + } + (void) fprintf(table->out,"\n"); + for (i = 0; i < numvars; i++) { + if (i == cut1 || i == cut2) (void) fprintf(table->out,"|"); + (void) fprintf(table->out,"%2d ",STOREDD(popsize+1,i)); + } + (void) fprintf(table->out,"\n"); +#endif + + FREE(inv1); + FREE(inv2); + return(1); + +} /* end of PMX */ + + +/**Function******************************************************************** + + Synopsis [Selects two parents with the roulette wheel method.] + + Description [Selects two distinct parents with the roulette wheel method.] + + SideEffects [The indices of the selected parents are returned as side + effects.] + + SeeAlso [] + +******************************************************************************/ +static int +roulette( + int * p1, + int * p2) +{ + double *wheel; + double spin; + int i; + + wheel = ALLOC(double,popsize); + if (wheel == NULL) { + return(0); + } + + /* The fitness of an individual is the reciprocal of its size. */ + wheel[0] = 1.0 / (double) STOREDD(0,numvars); + + for (i = 1; i < popsize; i++) { + wheel[i] = wheel[i-1] + 1.0 / (double) STOREDD(i,numvars); + } + + /* Get a random number between 0 and wheel[popsize-1] (that is, + ** the sum of all fitness values. 2147483561 is the largest number + ** returned by Cudd_Random. + */ + spin = wheel[numvars-1] * (double) Cudd_Random() / 2147483561.0; + + /* Find the lucky element by scanning the wheel. */ + for (i = 0; i < popsize; i++) { + if (spin <= wheel[i]) break; + } + *p1 = i; + + /* Repeat the process for the second parent, making sure it is + ** distinct from the first. + */ + do { + spin = wheel[popsize-1] * (double) Cudd_Random() / 2147483561.0; + for (i = 0; i < popsize; i++) { + if (spin <= wheel[i]) break; + } + } while (i == *p1); + *p2 = i; + + FREE(wheel); + return(1); + +} /* end of roulette */ + -- cgit v1.2.3