#include "isl_lp.h" #include "isl_map.h" #include "isl_map_private.h" #include "isl_mat.h" #include "isl_set.h" #include "isl_seq.h" #include "isl_equalities.h" #include "isl_tab.h" static struct isl_basic_set *uset_convex_hull_wrap_bounded(struct isl_set *set); static void swap_ineq(struct isl_basic_map *bmap, unsigned i, unsigned j) { isl_int *t; if (i != j) { t = bmap->ineq[i]; bmap->ineq[i] = bmap->ineq[j]; bmap->ineq[j] = t; } } /* Return 1 if constraint c is redundant with respect to the constraints * in bmap. If c is a lower [upper] bound in some variable and bmap * does not have a lower [upper] bound in that variable, then c cannot * be redundant and we do not need solve any lp. */ int isl_basic_map_constraint_is_redundant(struct isl_basic_map **bmap, isl_int *c, isl_int *opt_n, isl_int *opt_d) { enum isl_lp_result res; unsigned total; int i, j; if (!bmap) return -1; total = isl_basic_map_total_dim(*bmap); for (i = 0; i < total; ++i) { int sign; if (isl_int_is_zero(c[1+i])) continue; sign = isl_int_sgn(c[1+i]); for (j = 0; j < (*bmap)->n_ineq; ++j) if (sign == isl_int_sgn((*bmap)->ineq[j][1+i])) break; if (j == (*bmap)->n_ineq) break; } if (i < total) return 0; res = isl_basic_map_solve_lp(*bmap, 0, c, (*bmap)->ctx->one, opt_n, opt_d, NULL); if (res == isl_lp_unbounded) return 0; if (res == isl_lp_error) return -1; if (res == isl_lp_empty) { *bmap = isl_basic_map_set_to_empty(*bmap); return 0; } return !isl_int_is_neg(*opt_n); } int isl_basic_set_constraint_is_redundant(struct isl_basic_set **bset, isl_int *c, isl_int *opt_n, isl_int *opt_d) { return isl_basic_map_constraint_is_redundant( (struct isl_basic_map **)bset, c, opt_n, opt_d); } /* Compute the convex hull of a basic map, by removing the redundant * constraints. If the minimal value along the normal of a constraint * is the same if the constraint is removed, then the constraint is redundant. * * Alternatively, we could have intersected the basic map with the * corresponding equality and the checked if the dimension was that * of a facet. */ struct isl_basic_map *isl_basic_map_convex_hull(struct isl_basic_map *bmap) { struct isl_tab *tab; if (!bmap) return NULL; bmap = isl_basic_map_gauss(bmap, NULL); if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) return bmap; if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_NO_REDUNDANT)) return bmap; if (bmap->n_ineq <= 1) return bmap; tab = isl_tab_from_basic_map(bmap); tab = isl_tab_detect_implicit_equalities(tab); tab = isl_tab_detect_redundant(tab); bmap = isl_basic_map_update_from_tab(bmap, tab); isl_tab_free(tab); ISL_F_SET(bmap, ISL_BASIC_MAP_NO_IMPLICIT); ISL_F_SET(bmap, ISL_BASIC_MAP_NO_REDUNDANT); return bmap; } struct isl_basic_set *isl_basic_set_convex_hull(struct isl_basic_set *bset) { return (struct isl_basic_set *) isl_basic_map_convex_hull((struct isl_basic_map *)bset); } /* Check if the set set is bound in the direction of the affine * constraint c and if so, set the constant term such that the * resulting constraint is a bounding constraint for the set. */ static int uset_is_bound(struct isl_set *set, isl_int *c, unsigned len) { int first; int j; isl_int opt; isl_int opt_denom; isl_int_init(opt); isl_int_init(opt_denom); first = 1; for (j = 0; j < set->n; ++j) { enum isl_lp_result res; if (ISL_F_ISSET(set->p[j], ISL_BASIC_SET_EMPTY)) continue; res = isl_basic_set_solve_lp(set->p[j], 0, c, set->ctx->one, &opt, &opt_denom, NULL); if (res == isl_lp_unbounded) break; if (res == isl_lp_error) goto error; if (res == isl_lp_empty) { set->p[j] = isl_basic_set_set_to_empty(set->p[j]); if (!set->p[j]) goto error; continue; } if (!isl_int_is_one(opt_denom)) isl_seq_scale(c, c, opt_denom, len); if (first || isl_int_is_neg(opt)) isl_int_sub(c[0], c[0], opt); first = 0; } isl_int_clear(opt); isl_int_clear(opt_denom); return j >= set->n; error: isl_int_clear(opt); isl_int_clear(opt_denom); return -1; } /* Check if "c" is a direction that is independent of the previously found "n" * bounds in "dirs". * If so, add it to the list, with the negative of the lower bound * in the constant position, i.e., such that c corresponds to a bounding * hyperplane (but not necessarily a facet). * Assumes set "set" is bounded. */ static int is_independent_bound(struct isl_set *set, isl_int *c, struct isl_mat *dirs, int n) { int is_bound; int i = 0; isl_seq_cpy(dirs->row[n]+1, c+1, dirs->n_col-1); if (n != 0) { int pos = isl_seq_first_non_zero(dirs->row[n]+1, dirs->n_col-1); if (pos < 0) return 0; for (i = 0; i < n; ++i) { int pos_i; pos_i = isl_seq_first_non_zero(dirs->row[i]+1, dirs->n_col-1); if (pos_i < pos) continue; if (pos_i > pos) break; isl_seq_elim(dirs->row[n]+1, dirs->row[i]+1, pos, dirs->n_col-1, NULL); pos = isl_seq_first_non_zero(dirs->row[n]+1, dirs->n_col-1); if (pos < 0) return 0; } } is_bound = uset_is_bound(set, dirs->row[n], dirs->n_col); if (is_bound != 1) return is_bound; if (i < n) { int k; isl_int *t = dirs->row[n]; for (k = n; k > i; --k) dirs->row[k] = dirs->row[k-1]; dirs->row[i] = t; } return 1; } /* Compute and return a maximal set of linearly independent bounds * on the set "set", based on the constraints of the basic sets * in "set". */ static struct isl_mat *independent_bounds(struct isl_set *set) { int i, j, n; struct isl_mat *dirs = NULL; unsigned dim = isl_set_n_dim(set); dirs = isl_mat_alloc(set->ctx, dim, 1+dim); if (!dirs) goto error; n = 0; for (i = 0; n < dim && i < set->n; ++i) { int f; struct isl_basic_set *bset = set->p[i]; for (j = 0; n < dim && j < bset->n_eq; ++j) { f = is_independent_bound(set, bset->eq[j], dirs, n); if (f < 0) goto error; if (f) ++n; } for (j = 0; n < dim && j < bset->n_ineq; ++j) { f = is_independent_bound(set, bset->ineq[j], dirs, n); if (f < 0) goto error; if (f) ++n; } } dirs->n_row = n; return dirs; error: isl_mat_free(dirs); return NULL; } struct isl_basic_set *isl_basic_set_set_rational(struct isl_basic_set *bset) { if (!bset) return NULL; if (ISL_F_ISSET(bset, ISL_BASIC_MAP_RATIONAL)) return bset; bset = isl_basic_set_cow(bset); if (!bset) return NULL; ISL_F_SET(bset, ISL_BASIC_MAP_RATIONAL); return isl_basic_set_finalize(bset); } static struct isl_set *isl_set_set_rational(struct isl_set *set) { int i; set = isl_set_cow(set); if (!set) return NULL; for (i = 0; i < set->n; ++i) { set->p[i] = isl_basic_set_set_rational(set->p[i]); if (!set->p[i]) goto error; } return set; error: isl_set_free(set); return NULL; } static struct isl_basic_set *isl_basic_set_add_equality( struct isl_basic_set *bset, isl_int *c) { int i; unsigned dim; if (ISL_F_ISSET(bset, ISL_BASIC_SET_EMPTY)) return bset; isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error); isl_assert(bset->ctx, bset->n_div == 0, goto error); dim = isl_basic_set_n_dim(bset); bset = isl_basic_set_cow(bset); bset = isl_basic_set_extend(bset, 0, dim, 0, 1, 0); i = isl_basic_set_alloc_equality(bset); if (i < 0) goto error; isl_seq_cpy(bset->eq[i], c, 1 + dim); return bset; error: isl_basic_set_free(bset); return NULL; } static struct isl_set *isl_set_add_equality(struct isl_set *set, isl_int *c) { int i; set = isl_set_cow(set); if (!set) return NULL; for (i = 0; i < set->n; ++i) { set->p[i] = isl_basic_set_add_equality(set->p[i], c); if (!set->p[i]) goto error; } return set; error: isl_set_free(set); return NULL; } /* Given a union of basic sets, construct the constraints for wrapping * a facet around one of its ridges. * In particular, if each of n the d-dimensional basic sets i in "set" * contains the origin, satisfies the constraints x_1 >= 0 and x_2 >= 0 * and is defined by the constraints * [ 1 ] * A_i [ x ] >= 0 * * then the resulting set is of dimension n*(1+d) and has as constraints * * [ a_i ] * A_i [ x_i ] >= 0 * * a_i >= 0 * * \sum_i x_{i,1} = 1 */ static struct isl_basic_set *wrap_constraints(struct isl_set *set) { struct isl_basic_set *lp; unsigned n_eq; unsigned n_ineq; int i, j, k; unsigned dim, lp_dim; if (!set) return NULL; dim = 1 + isl_set_n_dim(set); n_eq = 1; n_ineq = set->n; for (i = 0; i < set->n; ++i) { n_eq += set->p[i]->n_eq; n_ineq += set->p[i]->n_ineq; } lp = isl_basic_set_alloc(set->ctx, 0, dim * set->n, 0, n_eq, n_ineq); if (!lp) return NULL; lp_dim = isl_basic_set_n_dim(lp); k = isl_basic_set_alloc_equality(lp); isl_int_set_si(lp->eq[k][0], -1); for (i = 0; i < set->n; ++i) { isl_int_set_si(lp->eq[k][1+dim*i], 0); isl_int_set_si(lp->eq[k][1+dim*i+1], 1); isl_seq_clr(lp->eq[k]+1+dim*i+2, dim-2); } for (i = 0; i < set->n; ++i) { k = isl_basic_set_alloc_inequality(lp); isl_seq_clr(lp->ineq[k], 1+lp_dim); isl_int_set_si(lp->ineq[k][1+dim*i], 1); for (j = 0; j < set->p[i]->n_eq; ++j) { k = isl_basic_set_alloc_equality(lp); isl_seq_clr(lp->eq[k], 1+dim*i); isl_seq_cpy(lp->eq[k]+1+dim*i, set->p[i]->eq[j], dim); isl_seq_clr(lp->eq[k]+1+dim*(i+1), dim*(set->n-i-1)); } for (j = 0; j < set->p[i]->n_ineq; ++j) { k = isl_basic_set_alloc_inequality(lp); isl_seq_clr(lp->ineq[k], 1+dim*i); isl_seq_cpy(lp->ineq[k]+1+dim*i, set->p[i]->ineq[j], dim); isl_seq_clr(lp->ineq[k]+1+dim*(i+1), dim*(set->n-i-1)); } } return lp; } /* Given a facet "facet" of the convex hull of "set" and a facet "ridge" * of that facet, compute the other facet of the convex hull that contains * the ridge. * * We first transform the set such that the facet constraint becomes * * x_1 >= 0 * * I.e., the facet lies in * * x_1 = 0 * * and on that facet, the constraint that defines the ridge is * * x_2 >= 0 * * (This transformation is not strictly needed, all that is needed is * that the ridge contains the origin.) * * Since the ridge contains the origin, the cone of the convex hull * will be of the form * * x_1 >= 0 * x_2 >= a x_1 * * with this second constraint defining the new facet. * The constant a is obtained by settting x_1 in the cone of the * convex hull to 1 and minimizing x_2. * Now, each element in the cone of the convex hull is the sum * of elements in the cones of the basic sets. * If a_i is the dilation factor of basic set i, then the problem * we need to solve is * * min \sum_i x_{i,2} * st * \sum_i x_{i,1} = 1 * a_i >= 0 * [ a_i ] * A [ x_i ] >= 0 * * with * [ 1 ] * A_i [ x_i ] >= 0 * * the constraints of each (transformed) basic set. * If a = n/d, then the constraint defining the new facet (in the transformed * space) is * * -n x_1 + d x_2 >= 0 * * In the original space, we need to take the same combination of the * corresponding constraints "facet" and "ridge". * * Note that a is always finite, since we only apply the wrapping * technique to a union of polytopes. */ static isl_int *wrap_facet(struct isl_set *set, isl_int *facet, isl_int *ridge) { int i; struct isl_mat *T = NULL; struct isl_basic_set *lp = NULL; struct isl_vec *obj; enum isl_lp_result res; isl_int num, den; unsigned dim; set = isl_set_copy(set); dim = 1 + isl_set_n_dim(set); T = isl_mat_alloc(set->ctx, 3, dim); if (!T) goto error; isl_int_set_si(T->row[0][0], 1); isl_seq_clr(T->row[0]+1, dim - 1); isl_seq_cpy(T->row[1], facet, dim); isl_seq_cpy(T->row[2], ridge, dim); T = isl_mat_right_inverse(T); set = isl_set_preimage(set, T); T = NULL; if (!set) goto error; lp = wrap_constraints(set); obj = isl_vec_alloc(set->ctx, 1 + dim*set->n); if (!obj) goto error; isl_int_set_si(obj->block.data[0], 0); for (i = 0; i < set->n; ++i) { isl_seq_clr(obj->block.data + 1 + dim*i, 2); isl_int_set_si(obj->block.data[1 + dim*i+2], 1); isl_seq_clr(obj->block.data + 1 + dim*i+3, dim-3); } isl_int_init(num); isl_int_init(den); res = isl_basic_set_solve_lp(lp, 0, obj->block.data, set->ctx->one, &num, &den, NULL); if (res == isl_lp_ok) { isl_int_neg(num, num); isl_seq_combine(facet, num, facet, den, ridge, dim); } isl_int_clear(num); isl_int_clear(den); isl_vec_free(obj); isl_basic_set_free(lp); isl_set_free(set); isl_assert(set->ctx, res == isl_lp_ok, return NULL); return facet; error: isl_basic_set_free(lp); isl_mat_free(T); isl_set_free(set); return NULL; } /* Given a set of d linearly independent bounding constraints of the * convex hull of "set", compute the constraint of a facet of "set". * * We first compute the intersection with the first bounding hyperplane * and remove the component corresponding to this hyperplane from * other bounds (in homogeneous space). * We then wrap around one of the remaining bounding constraints * and continue the process until all bounding constraints have been * taken into account. * The resulting linear combination of the bounding constraints will * correspond to a facet of the convex hull. */ static struct isl_mat *initial_facet_constraint(struct isl_set *set, struct isl_mat *bounds) { struct isl_set *slice = NULL; struct isl_basic_set *face = NULL; struct isl_mat *m, *U, *Q; int i; unsigned dim = isl_set_n_dim(set); isl_assert(set->ctx, set->n > 0, goto error); isl_assert(set->ctx, bounds->n_row == dim, goto error); while (bounds->n_row > 1) { slice = isl_set_copy(set); slice = isl_set_add_equality(slice, bounds->row[0]); face = isl_set_affine_hull(slice); if (!face) goto error; if (face->n_eq == 1) { isl_basic_set_free(face); break; } m = isl_mat_alloc(set->ctx, 1 + face->n_eq, 1 + dim); if (!m) goto error; isl_int_set_si(m->row[0][0], 1); isl_seq_clr(m->row[0]+1, dim); for (i = 0; i < face->n_eq; ++i) isl_seq_cpy(m->row[1 + i], face->eq[i], 1 + dim); U = isl_mat_right_inverse(m); Q = isl_mat_right_inverse(isl_mat_copy(U)); U = isl_mat_drop_cols(U, 1 + face->n_eq, dim - face->n_eq); Q = isl_mat_drop_rows(Q, 1 + face->n_eq, dim - face->n_eq); U = isl_mat_drop_cols(U, 0, 1); Q = isl_mat_drop_rows(Q, 0, 1); bounds = isl_mat_product(bounds, U); bounds = isl_mat_product(bounds, Q); while (isl_seq_first_non_zero(bounds->row[bounds->n_row-1], bounds->n_col) == -1) { bounds->n_row--; isl_assert(set->ctx, bounds->n_row > 1, goto error); } if (!wrap_facet(set, bounds->row[0], bounds->row[bounds->n_row-1])) goto error; isl_basic_set_free(face); bounds->n_row--; } return bounds; error: isl_basic_set_free(face); isl_mat_free(bounds); return NULL; } /* Given the bounding constraint "c" of a facet of the convex hull of "set", * compute a hyperplane description of the facet, i.e., compute the facets * of the facet. * * We compute an affine transformation that transforms the constraint * * [ 1 ] * c [ x ] = 0 * * to the constraint * * z_1 = 0 * * by computing the right inverse U of a matrix that starts with the rows * * [ 1 0 ] * [ c ] * * Then * [ 1 ] [ 1 ] * [ x ] = U [ z ] * and * [ 1 ] [ 1 ] * [ z ] = Q [ x ] * * with Q = U^{-1} * Since z_1 is zero, we can drop this variable as well as the corresponding * column of U to obtain * * [ 1 ] [ 1 ] * [ x ] = U' [ z' ] * and * [ 1 ] [ 1 ] * [ z' ] = Q' [ x ] * * with Q' equal to Q, but without the corresponding row. * After computing the facets of the facet in the z' space, * we convert them back to the x space through Q. */ static struct isl_basic_set *compute_facet(struct isl_set *set, isl_int *c) { struct isl_mat *m, *U, *Q; struct isl_basic_set *facet = NULL; struct isl_ctx *ctx; unsigned dim; ctx = set->ctx; set = isl_set_copy(set); dim = isl_set_n_dim(set); m = isl_mat_alloc(set->ctx, 2, 1 + dim); if (!m) goto error; isl_int_set_si(m->row[0][0], 1); isl_seq_clr(m->row[0]+1, dim); isl_seq_cpy(m->row[1], c, 1+dim); U = isl_mat_right_inverse(m); Q = isl_mat_right_inverse(isl_mat_copy(U)); U = isl_mat_drop_cols(U, 1, 1); Q = isl_mat_drop_rows(Q, 1, 1); set = isl_set_preimage(set, U); facet = uset_convex_hull_wrap_bounded(set); facet = isl_basic_set_preimage(facet, Q); isl_assert(ctx, facet->n_eq == 0, goto error); return facet; error: isl_basic_set_free(facet); isl_set_free(set); return NULL; } /* Given an initial facet constraint, compute the remaining facets. * We do this by running through all facets found so far and computing * the adjacent facets through wrapping, adding those facets that we * hadn't already found before. * * For each facet we have found so far, we first compute its facets * in the resulting convex hull. That is, we compute the ridges * of the resulting convex hull contained in the facet. * We also compute the corresponding facet in the current approximation * of the convex hull. There is no need to wrap around the ridges * in this facet since that would result in a facet that is already * present in the current approximation. * * This function can still be significantly optimized by checking which of * the facets of the basic sets are also facets of the convex hull and * using all the facets so far to help in constructing the facets of the * facets * and/or * using the technique in section "3.1 Ridge Generation" of * "Extended Convex Hull" by Fukuda et al. */ static struct isl_basic_set *extend(struct isl_basic_set *hull, struct isl_set *set) { int i, j, f; int k; struct isl_basic_set *facet = NULL; struct isl_basic_set *hull_facet = NULL; unsigned dim; isl_assert(set->ctx, set->n > 0, goto error); dim = isl_set_n_dim(set); for (i = 0; i < hull->n_ineq; ++i) { facet = compute_facet(set, hull->ineq[i]); facet = isl_basic_set_add_equality(facet, hull->ineq[i]); facet = isl_basic_set_gauss(facet, NULL); facet = isl_basic_set_normalize_constraints(facet); hull_facet = isl_basic_set_copy(hull); hull_facet = isl_basic_set_add_equality(hull_facet, hull->ineq[i]); hull_facet = isl_basic_set_gauss(hull_facet, NULL); hull_facet = isl_basic_set_normalize_constraints(hull_facet); if (!facet) goto error; hull = isl_basic_set_cow(hull); hull = isl_basic_set_extend_dim(hull, isl_dim_copy(hull->dim), 0, 0, facet->n_ineq); for (j = 0; j < facet->n_ineq; ++j) { for (f = 0; f < hull_facet->n_ineq; ++f) if (isl_seq_eq(facet->ineq[j], hull_facet->ineq[f], 1 + dim)) break; if (f < hull_facet->n_ineq) continue; k = isl_basic_set_alloc_inequality(hull); if (k < 0) goto error; isl_seq_cpy(hull->ineq[k], hull->ineq[i], 1+dim); if (!wrap_facet(set, hull->ineq[k], facet->ineq[j])) goto error; } isl_basic_set_free(hull_facet); isl_basic_set_free(facet); } hull = isl_basic_set_simplify(hull); hull = isl_basic_set_finalize(hull); return hull; error: isl_basic_set_free(hull_facet); isl_basic_set_free(facet); isl_basic_set_free(hull); return NULL; } /* Special case for computing the convex hull of a one dimensional set. * We simply collect the lower and upper bounds of each basic set * and the biggest of those. */ static struct isl_basic_set *convex_hull_1d(struct isl_set *set) { struct isl_mat *c = NULL; isl_int *lower = NULL; isl_int *upper = NULL; int i, j, k; isl_int a, b; struct isl_basic_set *hull; for (i = 0; i < set->n; ++i) { set->p[i] = isl_basic_set_simplify(set->p[i]); if (!set->p[i]) goto error; } set = isl_set_remove_empty_parts(set); if (!set) goto error; isl_assert(set->ctx, set->n > 0, goto error); c = isl_mat_alloc(set->ctx, 2, 2); if (!c) goto error; if (set->p[0]->n_eq > 0) { isl_assert(set->ctx, set->p[0]->n_eq == 1, goto error); lower = c->row[0]; upper = c->row[1]; if (isl_int_is_pos(set->p[0]->eq[0][1])) { isl_seq_cpy(lower, set->p[0]->eq[0], 2); isl_seq_neg(upper, set->p[0]->eq[0], 2); } else { isl_seq_neg(lower, set->p[0]->eq[0], 2); isl_seq_cpy(upper, set->p[0]->eq[0], 2); } } else { for (j = 0; j < set->p[0]->n_ineq; ++j) { if (isl_int_is_pos(set->p[0]->ineq[j][1])) { lower = c->row[0]; isl_seq_cpy(lower, set->p[0]->ineq[j], 2); } else { upper = c->row[1]; isl_seq_cpy(upper, set->p[0]->ineq[j], 2); } } } isl_int_init(a); isl_int_init(b); for (i = 0; i < set->n; ++i) { struct isl_basic_set *bset = set->p[i]; int has_lower = 0; int has_upper = 0; for (j = 0; j < bset->n_eq; ++j) { has_lower = 1; has_upper = 1; if (lower) { isl_int_mul(a, lower[0], bset->eq[j][1]); isl_int_mul(b, lower[1], bset->eq[j][0]); if (isl_int_lt(a, b) && isl_int_is_pos(bset->eq[j][1])) isl_seq_cpy(lower, bset->eq[j], 2); if (isl_int_gt(a, b) && isl_int_is_neg(bset->eq[j][1])) isl_seq_neg(lower, bset->eq[j], 2); } if (upper) { isl_int_mul(a, upper[0], bset->eq[j][1]); isl_int_mul(b, upper[1], bset->eq[j][0]); if (isl_int_lt(a, b) && isl_int_is_pos(bset->eq[j][1])) isl_seq_neg(upper, bset->eq[j], 2); if (isl_int_gt(a, b) && isl_int_is_neg(bset->eq[j][1])) isl_seq_cpy(upper, bset->eq[j], 2); } } for (j = 0; j < bset->n_ineq; ++j) { if (isl_int_is_pos(bset->ineq[j][1])) has_lower = 1; if (isl_int_is_neg(bset->ineq[j][1])) has_upper = 1; if (lower && isl_int_is_pos(bset->ineq[j][1])) { isl_int_mul(a, lower[0], bset->ineq[j][1]); isl_int_mul(b, lower[1], bset->ineq[j][0]); if (isl_int_lt(a, b)) isl_seq_cpy(lower, bset->ineq[j], 2); } if (upper && isl_int_is_neg(bset->ineq[j][1])) { isl_int_mul(a, upper[0], bset->ineq[j][1]); isl_int_mul(b, upper[1], bset->ineq[j][0]); if (isl_int_gt(a, b)) isl_seq_cpy(upper, bset->ineq[j], 2); } } if (!has_lower) lower = NULL; if (!has_upper) upper = NULL; } isl_int_clear(a); isl_int_clear(b); hull = isl_basic_set_alloc(set->ctx, 0, 1, 0, 0, 2); hull = isl_basic_set_set_rational(hull); if (!hull) goto error; if (lower) { k = isl_basic_set_alloc_inequality(hull); isl_seq_cpy(hull->ineq[k], lower, 2); } if (upper) { k = isl_basic_set_alloc_inequality(hull); isl_seq_cpy(hull->ineq[k], upper, 2); } hull = isl_basic_set_finalize(hull); isl_set_free(set); isl_mat_free(c); return hull; error: isl_set_free(set); isl_mat_free(c); return NULL; } /* Project out final n dimensions using Fourier-Motzkin */ static struct isl_set *set_project_out(struct isl_ctx *ctx, struct isl_set *set, unsigned n) { return isl_set_remove_dims(set, isl_set_n_dim(set) - n, n); } static struct isl_basic_set *convex_hull_0d(struct isl_set *set) { struct isl_basic_set *convex_hull; if (!set) return NULL; if (isl_set_is_empty(set)) convex_hull = isl_basic_set_empty(isl_dim_copy(set->dim)); else convex_hull = isl_basic_set_universe(isl_dim_copy(set->dim)); isl_set_free(set); return convex_hull; } /* Compute the convex hull of a pair of basic sets without any parameters or * integer divisions using Fourier-Motzkin elimination. * The convex hull is the set of all points that can be written as * the sum of points from both basic sets (in homogeneous coordinates). * We set up the constraints in a space with dimensions for each of * the three sets and then project out the dimensions corresponding * to the two original basic sets, retaining only those corresponding * to the convex hull. */ static struct isl_basic_set *convex_hull_pair_elim(struct isl_basic_set *bset1, struct isl_basic_set *bset2) { int i, j, k; struct isl_basic_set *bset[2]; struct isl_basic_set *hull = NULL; unsigned dim; if (!bset1 || !bset2) goto error; dim = isl_basic_set_n_dim(bset1); hull = isl_basic_set_alloc(bset1->ctx, 0, 2 + 3 * dim, 0, 1 + dim + bset1->n_eq + bset2->n_eq, 2 + bset1->n_ineq + bset2->n_ineq); bset[0] = bset1; bset[1] = bset2; for (i = 0; i < 2; ++i) { for (j = 0; j < bset[i]->n_eq; ++j) { k = isl_basic_set_alloc_equality(hull); if (k < 0) goto error; isl_seq_clr(hull->eq[k], (i+1) * (1+dim)); isl_seq_clr(hull->eq[k]+(i+2)*(1+dim), (1-i)*(1+dim)); isl_seq_cpy(hull->eq[k]+(i+1)*(1+dim), bset[i]->eq[j], 1+dim); } for (j = 0; j < bset[i]->n_ineq; ++j) { k = isl_basic_set_alloc_inequality(hull); if (k < 0) goto error; isl_seq_clr(hull->ineq[k], (i+1) * (1+dim)); isl_seq_clr(hull->ineq[k]+(i+2)*(1+dim), (1-i)*(1+dim)); isl_seq_cpy(hull->ineq[k]+(i+1)*(1+dim), bset[i]->ineq[j], 1+dim); } k = isl_basic_set_alloc_inequality(hull); if (k < 0) goto error; isl_seq_clr(hull->ineq[k], 1+2+3*dim); isl_int_set_si(hull->ineq[k][(i+1)*(1+dim)], 1); } for (j = 0; j < 1+dim; ++j) { k = isl_basic_set_alloc_equality(hull); if (k < 0) goto error; isl_seq_clr(hull->eq[k], 1+2+3*dim); isl_int_set_si(hull->eq[k][j], -1); isl_int_set_si(hull->eq[k][1+dim+j], 1); isl_int_set_si(hull->eq[k][2*(1+dim)+j], 1); } hull = isl_basic_set_set_rational(hull); hull = isl_basic_set_remove_dims(hull, dim, 2*(1+dim)); hull = isl_basic_set_convex_hull(hull); isl_basic_set_free(bset1); isl_basic_set_free(bset2); return hull; error: isl_basic_set_free(bset1); isl_basic_set_free(bset2); isl_basic_set_free(hull); return NULL; } static int isl_basic_set_is_bounded(struct isl_basic_set *bset) { struct isl_tab *tab; int bounded; tab = isl_tab_from_recession_cone(bset); bounded = isl_tab_cone_is_bounded(tab); isl_tab_free(tab); return bounded; } static int isl_set_is_bounded(struct isl_set *set) { int i; for (i = 0; i < set->n; ++i) { int bounded = isl_basic_set_is_bounded(set->p[i]); if (!bounded || bounded < 0) return bounded; } return 1; } /* Compute the lineality space of the convex hull of bset1 and bset2. * * We first compute the intersection of the recession cone of bset1 * with the negative of the recession cone of bset2 and then compute * the linear hull of the resulting cone. */ static struct isl_basic_set *induced_lineality_space( struct isl_basic_set *bset1, struct isl_basic_set *bset2) { int i, k; struct isl_basic_set *lin = NULL; unsigned dim; if (!bset1 || !bset2) goto error; dim = isl_basic_set_total_dim(bset1); lin = isl_basic_set_alloc_dim(isl_basic_set_get_dim(bset1), 0, bset1->n_eq + bset2->n_eq, bset1->n_ineq + bset2->n_ineq); lin = isl_basic_set_set_rational(lin); if (!lin) goto error; for (i = 0; i < bset1->n_eq; ++i) { k = isl_basic_set_alloc_equality(lin); if (k < 0) goto error; isl_int_set_si(lin->eq[k][0], 0); isl_seq_cpy(lin->eq[k] + 1, bset1->eq[i] + 1, dim); } for (i = 0; i < bset1->n_ineq; ++i) { k = isl_basic_set_alloc_inequality(lin); if (k < 0) goto error; isl_int_set_si(lin->ineq[k][0], 0); isl_seq_cpy(lin->ineq[k] + 1, bset1->ineq[i] + 1, dim); } for (i = 0; i < bset2->n_eq; ++i) { k = isl_basic_set_alloc_equality(lin); if (k < 0) goto error; isl_int_set_si(lin->eq[k][0], 0); isl_seq_neg(lin->eq[k] + 1, bset2->eq[i] + 1, dim); } for (i = 0; i < bset2->n_ineq; ++i) { k = isl_basic_set_alloc_inequality(lin); if (k < 0) goto error; isl_int_set_si(lin->ineq[k][0], 0); isl_seq_neg(lin->ineq[k] + 1, bset2->ineq[i] + 1, dim); } isl_basic_set_free(bset1); isl_basic_set_free(bset2); return isl_basic_set_affine_hull(lin); error: isl_basic_set_free(lin); isl_basic_set_free(bset1); isl_basic_set_free(bset2); return NULL; } static struct isl_basic_set *uset_convex_hull(struct isl_set *set); /* Given a set and a linear space "lin" of dimension n > 0, * project the linear space from the set, compute the convex hull * and then map the set back to the original space. * * Let * * M x = 0 * * describe the linear space. We first compute the Hermite normal * form H = M U of M = H Q, to obtain * * H Q x = 0 * * The last n rows of H will be zero, so the last n variables of x' = Q x * are the one we want to project out. We do this by transforming each * basic set A x >= b to A U x' >= b and then removing the last n dimensions. * After computing the convex hull in x'_1, i.e., A' x'_1 >= b', * we transform the hull back to the original space as A' Q_1 x >= b', * with Q_1 all but the last n rows of Q. */ static struct isl_basic_set *modulo_lineality(struct isl_set *set, struct isl_basic_set *lin) { unsigned total = isl_basic_set_total_dim(lin); unsigned lin_dim; struct isl_basic_set *hull; struct isl_mat *M, *U, *Q; if (!set || !lin) goto error; lin_dim = total - lin->n_eq; M = isl_mat_sub_alloc(set->ctx, lin->eq, 0, lin->n_eq, 1, total); M = isl_mat_left_hermite(M, 0, &U, &Q); if (!M) goto error; isl_mat_free(M); isl_basic_set_free(lin); Q = isl_mat_drop_rows(Q, Q->n_row - lin_dim, lin_dim); U = isl_mat_lin_to_aff(U); Q = isl_mat_lin_to_aff(Q); set = isl_set_preimage(set, U); set = isl_set_remove_dims(set, total - lin_dim, lin_dim); hull = uset_convex_hull(set); hull = isl_basic_set_preimage(hull, Q); return hull; error: isl_basic_set_free(lin); isl_set_free(set); return NULL; } /* Given two polyhedra with as constraints h_{ij} x >= 0 in homegeneous space, * set up an LP for solving * * \sum_j \alpha_{1j} h_{1j} = \sum_j \alpha_{2j} h_{2j} * * \alpha{i0} corresponds to the (implicit) positivity constraint 1 >= 0 * The next \alpha{ij} correspond to the equalities and come in pairs. * The final \alpha{ij} correspond to the inequalities. */ static struct isl_basic_set *valid_direction_lp( struct isl_basic_set *bset1, struct isl_basic_set *bset2) { struct isl_dim *dim; struct isl_basic_set *lp; unsigned d; int n; int i, j, k; if (!bset1 || !bset2) goto error; d = 1 + isl_basic_set_total_dim(bset1); n = 2 + 2 * bset1->n_eq + bset1->n_ineq + 2 * bset2->n_eq + bset2->n_ineq; dim = isl_dim_set_alloc(bset1->ctx, 0, n); lp = isl_basic_set_alloc_dim(dim, 0, d, n); if (!lp) goto error; for (i = 0; i < n; ++i) { k = isl_basic_set_alloc_inequality(lp); if (k < 0) goto error; isl_seq_clr(lp->ineq[k] + 1, n); isl_int_set_si(lp->ineq[k][0], -1); isl_int_set_si(lp->ineq[k][1 + i], 1); } for (i = 0; i < d; ++i) { k = isl_basic_set_alloc_equality(lp); if (k < 0) goto error; n = 0; isl_int_set_si(lp->eq[k][n++], 0); /* positivity constraint 1 >= 0 */ isl_int_set_si(lp->eq[k][n++], i == 0); for (j = 0; j < bset1->n_eq; ++j) { isl_int_set(lp->eq[k][n++], bset1->eq[j][i]); isl_int_neg(lp->eq[k][n++], bset1->eq[j][i]); } for (j = 0; j < bset1->n_ineq; ++j) isl_int_set(lp->eq[k][n++], bset1->ineq[j][i]); /* positivity constraint 1 >= 0 */ isl_int_set_si(lp->eq[k][n++], -(i == 0)); for (j = 0; j < bset2->n_eq; ++j) { isl_int_neg(lp->eq[k][n++], bset2->eq[j][i]); isl_int_set(lp->eq[k][n++], bset2->eq[j][i]); } for (j = 0; j < bset2->n_ineq; ++j) isl_int_neg(lp->eq[k][n++], bset2->ineq[j][i]); } lp = isl_basic_set_gauss(lp, NULL); isl_basic_set_free(bset1); isl_basic_set_free(bset2); return lp; error: isl_basic_set_free(bset1); isl_basic_set_free(bset2); return NULL; } /* Compute a vector s in the homogeneous space such that > 0 * for all rays in the homogeneous space of the two cones that correspond * to the input polyhedra bset1 and bset2. * * We compute s as a vector that satisfies * * s = \sum_j \alpha_{ij} h_{ij} for i = 1,2 (*) * * with h_{ij} the normals of the facets of polyhedron i * (including the "positivity constraint" 1 >= 0) and \alpha_{ij} * strictly positive numbers. For simplicity we impose \alpha_{ij} >= 1. * We first set up an LP with as variables the \alpha{ij}. * In this formulateion, for each polyhedron i, * the first constraint is the positivity constraint, followed by pairs * of variables for the equalities, followed by variables for the inequalities. * We then simply pick a feasible solution and compute s using (*). * * Note that we simply pick any valid direction and make no attempt * to pick a "good" or even the "best" valid direction. */ static struct isl_vec *valid_direction( struct isl_basic_set *bset1, struct isl_basic_set *bset2) { struct isl_basic_set *lp; struct isl_tab *tab; struct isl_vec *sample = NULL; struct isl_vec *dir; unsigned d; int i; int n; if (!bset1 || !bset2) goto error; lp = valid_direction_lp(isl_basic_set_copy(bset1), isl_basic_set_copy(bset2)); tab = isl_tab_from_basic_set(lp); sample = isl_tab_get_sample_value(tab); isl_tab_free(tab); isl_basic_set_free(lp); if (!sample) goto error; d = isl_basic_set_total_dim(bset1); dir = isl_vec_alloc(bset1->ctx, 1 + d); if (!dir) goto error; isl_seq_clr(dir->block.data + 1, dir->size - 1); n = 1; /* positivity constraint 1 >= 0 */ isl_int_set(dir->block.data[0], sample->block.data[n++]); for (i = 0; i < bset1->n_eq; ++i) { isl_int_sub(sample->block.data[n], sample->block.data[n], sample->block.data[n+1]); isl_seq_combine(dir->block.data, bset1->ctx->one, dir->block.data, sample->block.data[n], bset1->eq[i], 1 + d); n += 2; } for (i = 0; i < bset1->n_ineq; ++i) isl_seq_combine(dir->block.data, bset1->ctx->one, dir->block.data, sample->block.data[n++], bset1->ineq[i], 1 + d); isl_vec_free(sample); isl_seq_normalize(bset1->ctx, dir->block.data + 1, dir->size - 1); isl_basic_set_free(bset1); isl_basic_set_free(bset2); return dir; error: isl_vec_free(sample); isl_basic_set_free(bset1); isl_basic_set_free(bset2); return NULL; } /* Given a polyhedron b_i + A_i x >= 0 and a map T = S^{-1}, * compute b_i' + A_i' x' >= 0, with * * [ b_i A_i ] [ y' ] [ y' ] * [ 1 0 ] S^{-1} [ x' ] >= 0 or [ b_i' A_i' ] [ x' ] >= 0 * * In particular, add the "positivity constraint" and then perform * the mapping. */ static struct isl_basic_set *homogeneous_map(struct isl_basic_set *bset, struct isl_mat *T) { int k; if (!bset) goto error; bset = isl_basic_set_extend_constraints(bset, 0, 1); k = isl_basic_set_alloc_inequality(bset); if (k < 0) goto error; isl_seq_clr(bset->ineq[k] + 1, isl_basic_set_total_dim(bset)); isl_int_set_si(bset->ineq[k][0], 1); bset = isl_basic_set_preimage(bset, T); return bset; error: isl_mat_free(T); isl_basic_set_free(bset); return NULL; } /* Compute the convex hull of a pair of basic sets without any parameters or * integer divisions, where the convex hull is known to be pointed, * but the basic sets may be unbounded. * * We turn this problem into the computation of a convex hull of a pair * _bounded_ polyhedra by "changing the direction of the homogeneous * dimension". This idea is due to Matthias Koeppe. * * Consider the cones in homogeneous space that correspond to the * input polyhedra. The rays of these cones are also rays of the * polyhedra if the coordinate that corresponds to the homogeneous * dimension is zero. That is, if the inner product of the rays * with the homogeneous direction is zero. * The cones in the homogeneous space can also be considered to * correspond to other pairs of polyhedra by chosing a different * homogeneous direction. To ensure that both of these polyhedra * are bounded, we need to make sure that all rays of the cones * correspond to vertices and not to rays. * Let s be a direction such that > 0 for all rays r of both cones. * Then using s as a homogeneous direction, we obtain a pair of polytopes. * The vector s is computed in valid_direction. * * Note that we need to consider _all_ rays of the cones and not just * the rays that correspond to rays in the polyhedra. If we were to * only consider those rays and turn them into vertices, then we * may inadvertently turn some vertices into rays. * * The standard homogeneous direction is the unit vector in the 0th coordinate. * We therefore transform the two polyhedra such that the selected * direction is mapped onto this standard direction and then proceed * with the normal computation. * Let S be a non-singular square matrix with s as its first row, * then we want to map the polyhedra to the space * * [ y' ] [ y ] [ y ] [ y' ] * [ x' ] = S [ x ] i.e., [ x ] = S^{-1} [ x' ] * * We take S to be the unimodular completion of s to limit the growth * of the coefficients in the following computations. * * Let b_i + A_i x >= 0 be the constraints of polyhedron i. * We first move to the homogeneous dimension * * b_i y + A_i x >= 0 [ b_i A_i ] [ y ] [ 0 ] * y >= 0 or [ 1 0 ] [ x ] >= [ 0 ] * * Then we change directoin * * [ b_i A_i ] [ y' ] [ y' ] * [ 1 0 ] S^{-1} [ x' ] >= 0 or [ b_i' A_i' ] [ x' ] >= 0 * * Then we compute the convex hull of the polytopes b_i' + A_i' x' >= 0 * resulting in b' + A' x' >= 0, which we then convert back * * [ y ] [ y ] * [ b' A' ] S [ x ] >= 0 or [ b A ] [ x ] >= 0 * * The polyhedron b + A x >= 0 is then the convex hull of the input polyhedra. */ static struct isl_basic_set *convex_hull_pair_pointed( struct isl_basic_set *bset1, struct isl_basic_set *bset2) { struct isl_ctx *ctx = NULL; struct isl_vec *dir = NULL; struct isl_mat *T = NULL; struct isl_mat *T2 = NULL; struct isl_basic_set *hull; struct isl_set *set; if (!bset1 || !bset2) goto error; ctx = bset1->ctx; dir = valid_direction(isl_basic_set_copy(bset1), isl_basic_set_copy(bset2)); if (!dir) goto error; T = isl_mat_alloc(bset1->ctx, dir->size, dir->size); if (!T) goto error; isl_seq_cpy(T->row[0], dir->block.data, dir->size); T = isl_mat_unimodular_complete(T, 1); T2 = isl_mat_right_inverse(isl_mat_copy(T)); bset1 = homogeneous_map(bset1, isl_mat_copy(T2)); bset2 = homogeneous_map(bset2, T2); set = isl_set_alloc_dim(isl_basic_set_get_dim(bset1), 2, 0); set = isl_set_add(set, bset1); set = isl_set_add(set, bset2); hull = uset_convex_hull(set); hull = isl_basic_set_preimage(hull, T); isl_vec_free(dir); return hull; error: isl_vec_free(dir); isl_basic_set_free(bset1); isl_basic_set_free(bset2); return NULL; } /* Compute the convex hull of a pair of basic sets without any parameters or * integer divisions. * * If the convex hull of the two basic sets would have a non-trivial * lineality space, we first project out this lineality space. */ static struct isl_basic_set *convex_hull_pair(struct isl_basic_set *bset1, struct isl_basic_set *bset2) { struct isl_basic_set *lin; if (isl_basic_set_is_bounded(bset1) || isl_basic_set_is_bounded(bset2)) return convex_hull_pair_pointed(bset1, bset2); lin = induced_lineality_space(isl_basic_set_copy(bset1), isl_basic_set_copy(bset2)); if (!lin) goto error; if (isl_basic_set_is_universe(lin)) { isl_basic_set_free(bset1); isl_basic_set_free(bset2); return lin; } if (lin->n_eq < isl_basic_set_total_dim(lin)) { struct isl_set *set; set = isl_set_alloc_dim(isl_basic_set_get_dim(bset1), 2, 0); set = isl_set_add(set, bset1); set = isl_set_add(set, bset2); return modulo_lineality(set, lin); } isl_basic_set_free(lin); return convex_hull_pair_pointed(bset1, bset2); error: isl_basic_set_free(bset1); isl_basic_set_free(bset2); return NULL; } /* Compute the lineality space of a basic set. * We currently do not allow the basic set to have any divs. * We basically just drop the constants and turn every inequality * into an equality. */ struct isl_basic_set *isl_basic_set_lineality_space(struct isl_basic_set *bset) { int i, k; struct isl_basic_set *lin = NULL; unsigned dim; if (!bset) goto error; isl_assert(bset->ctx, bset->n_div == 0, goto error); dim = isl_basic_set_total_dim(bset); lin = isl_basic_set_alloc_dim(isl_basic_set_get_dim(bset), 0, dim, 0); if (!lin) goto error; for (i = 0; i < bset->n_eq; ++i) { k = isl_basic_set_alloc_equality(lin); if (k < 0) goto error; isl_int_set_si(lin->eq[k][0], 0); isl_seq_cpy(lin->eq[k] + 1, bset->eq[i] + 1, dim); } lin = isl_basic_set_gauss(lin, NULL); if (!lin) goto error; for (i = 0; i < bset->n_ineq && lin->n_eq < dim; ++i) { k = isl_basic_set_alloc_equality(lin); if (k < 0) goto error; isl_int_set_si(lin->eq[k][0], 0); isl_seq_cpy(lin->eq[k] + 1, bset->ineq[i] + 1, dim); lin = isl_basic_set_gauss(lin, NULL); if (!lin) goto error; } isl_basic_set_free(bset); return lin; error: isl_basic_set_free(lin); isl_basic_set_free(bset); return NULL; } /* Compute the (linear) hull of the lineality spaces of the basic sets in the * "underlying" set "set". */ static struct isl_basic_set *uset_combined_lineality_space(struct isl_set *set) { int i; struct isl_set *lin = NULL; if (!set) return NULL; if (set->n == 0) { struct isl_dim *dim = isl_set_get_dim(set); isl_set_free(set); return isl_basic_set_empty(dim); } lin = isl_set_alloc_dim(isl_set_get_dim(set), set->n, 0); for (i = 0; i < set->n; ++i) lin = isl_set_add(lin, isl_basic_set_lineality_space(isl_basic_set_copy(set->p[i]))); isl_set_free(set); return isl_set_affine_hull(lin); } /* Compute the convex hull of a set without any parameters or * integer divisions. * In each step, we combined two basic sets until only one * basic set is left. * The input basic sets are assumed not to have a non-trivial * lineality space. If any of the intermediate results has * a non-trivial lineality space, it is projected out. */ static struct isl_basic_set *uset_convex_hull_unbounded(struct isl_set *set) { struct isl_basic_set *convex_hull = NULL; convex_hull = isl_set_copy_basic_set(set); set = isl_set_drop_basic_set(set, convex_hull); if (!set) goto error; while (set->n > 0) { struct isl_basic_set *t; t = isl_set_copy_basic_set(set); if (!t) goto error; set = isl_set_drop_basic_set(set, t); if (!set) goto error; convex_hull = convex_hull_pair(convex_hull, t); if (set->n == 0) break; t = isl_basic_set_lineality_space(isl_basic_set_copy(convex_hull)); if (!t) goto error; if (isl_basic_set_is_universe(t)) { isl_basic_set_free(convex_hull); convex_hull = t; break; } if (t->n_eq < isl_basic_set_total_dim(t)) { set = isl_set_add(set, convex_hull); return modulo_lineality(set, t); } isl_basic_set_free(t); } isl_set_free(set); return convex_hull; error: isl_set_free(set); isl_basic_set_free(convex_hull); return NULL; } /* Compute an initial hull for wrapping containing a single initial * facet by first computing bounds on the set and then using these * bounds to construct an initial facet. * This function is a remnant of an older implementation where the * bounds were also used to check whether the set was bounded. * Since this function will now only be called when we know the * set to be bounded, the initial facet should probably be constructed * by simply using the coordinate directions instead. */ static struct isl_basic_set *initial_hull(struct isl_basic_set *hull, struct isl_set *set) { struct isl_mat *bounds = NULL; unsigned dim; int k; if (!hull) goto error; bounds = independent_bounds(set); if (!bounds) goto error; isl_assert(set->ctx, bounds->n_row == isl_set_n_dim(set), goto error); bounds = initial_facet_constraint(set, bounds); if (!bounds) goto error; k = isl_basic_set_alloc_inequality(hull); if (k < 0) goto error; dim = isl_set_n_dim(set); isl_assert(set->ctx, 1 + dim == bounds->n_col, goto error); isl_seq_cpy(hull->ineq[k], bounds->row[0], bounds->n_col); isl_mat_free(bounds); return hull; error: isl_basic_set_free(hull); isl_mat_free(bounds); return NULL; } struct max_constraint { struct isl_mat *c; int count; int ineq; }; static int max_constraint_equal(const void *entry, const void *val) { struct max_constraint *a = (struct max_constraint *)entry; isl_int *b = (isl_int *)val; return isl_seq_eq(a->c->row[0] + 1, b, a->c->n_col - 1); } static void update_constraint(struct isl_ctx *ctx, struct isl_hash_table *table, isl_int *con, unsigned len, int n, int ineq) { struct isl_hash_table_entry *entry; struct max_constraint *c; uint32_t c_hash; c_hash = isl_seq_get_hash(con + 1, len); entry = isl_hash_table_find(ctx, table, c_hash, max_constraint_equal, con + 1, 0); if (!entry) return; c = entry->data; if (c->count < n) { isl_hash_table_remove(ctx, table, entry); return; } c->count++; if (isl_int_gt(c->c->row[0][0], con[0])) return; if (isl_int_eq(c->c->row[0][0], con[0])) { if (ineq) c->ineq = ineq; return; } c->c = isl_mat_cow(c->c); isl_int_set(c->c->row[0][0], con[0]); c->ineq = ineq; } /* Check whether the constraint hash table "table" constains the constraint * "con". */ static int has_constraint(struct isl_ctx *ctx, struct isl_hash_table *table, isl_int *con, unsigned len, int n) { struct isl_hash_table_entry *entry; struct max_constraint *c; uint32_t c_hash; c_hash = isl_seq_get_hash(con + 1, len); entry = isl_hash_table_find(ctx, table, c_hash, max_constraint_equal, con + 1, 0); if (!entry) return 0; c = entry->data; if (c->count < n) return 0; return isl_int_eq(c->c->row[0][0], con[0]); } /* Check for inequality constraints of a basic set without equalities * such that the same or more stringent copies of the constraint appear * in all of the basic sets. Such constraints are necessarily facet * constraints of the convex hull. * * If the resulting basic set is by chance identical to one of * the basic sets in "set", then we know that this basic set contains * all other basic sets and is therefore the convex hull of set. * In this case we set *is_hull to 1. */ static struct isl_basic_set *common_constraints(struct isl_basic_set *hull, struct isl_set *set, int *is_hull) { int i, j, s, n; int min_constraints; int best; struct max_constraint *constraints = NULL; struct isl_hash_table *table = NULL; unsigned total; *is_hull = 0; for (i = 0; i < set->n; ++i) if (set->p[i]->n_eq == 0) break; if (i >= set->n) return hull; min_constraints = set->p[i]->n_ineq; best = i; for (i = best + 1; i < set->n; ++i) { if (set->p[i]->n_eq != 0) continue; if (set->p[i]->n_ineq >= min_constraints) continue; min_constraints = set->p[i]->n_ineq; best = i; } constraints = isl_calloc_array(hull->ctx, struct max_constraint, min_constraints); if (!constraints) return hull; table = isl_alloc_type(hull->ctx, struct isl_hash_table); if (isl_hash_table_init(hull->ctx, table, min_constraints)) goto error; total = isl_dim_total(set->dim); for (i = 0; i < set->p[best]->n_ineq; ++i) { constraints[i].c = isl_mat_sub_alloc(hull->ctx, set->p[best]->ineq + i, 0, 1, 0, 1 + total); if (!constraints[i].c) goto error; constraints[i].ineq = 1; } for (i = 0; i < min_constraints; ++i) { struct isl_hash_table_entry *entry; uint32_t c_hash; c_hash = isl_seq_get_hash(constraints[i].c->row[0] + 1, total); entry = isl_hash_table_find(hull->ctx, table, c_hash, max_constraint_equal, constraints[i].c->row[0] + 1, 1); if (!entry) goto error; isl_assert(hull->ctx, !entry->data, goto error); entry->data = &constraints[i]; } n = 0; for (s = 0; s < set->n; ++s) { if (s == best) continue; for (i = 0; i < set->p[s]->n_eq; ++i) { isl_int *eq = set->p[s]->eq[i]; for (j = 0; j < 2; ++j) { isl_seq_neg(eq, eq, 1 + total); update_constraint(hull->ctx, table, eq, total, n, 0); } } for (i = 0; i < set->p[s]->n_ineq; ++i) { isl_int *ineq = set->p[s]->ineq[i]; update_constraint(hull->ctx, table, ineq, total, n, set->p[s]->n_eq == 0); } ++n; } for (i = 0; i < min_constraints; ++i) { if (constraints[i].count < n) continue; if (!constraints[i].ineq) continue; j = isl_basic_set_alloc_inequality(hull); if (j < 0) goto error; isl_seq_cpy(hull->ineq[j], constraints[i].c->row[0], 1 + total); } for (s = 0; s < set->n; ++s) { if (set->p[s]->n_eq) continue; if (set->p[s]->n_ineq != hull->n_ineq) continue; for (i = 0; i < set->p[s]->n_ineq; ++i) { isl_int *ineq = set->p[s]->ineq[i]; if (!has_constraint(hull->ctx, table, ineq, total, n)) break; } if (i == set->p[s]->n_ineq) *is_hull = 1; } isl_hash_table_clear(table); for (i = 0; i < min_constraints; ++i) isl_mat_free(constraints[i].c); free(constraints); free(table); return hull; error: isl_hash_table_clear(table); free(table); if (constraints) for (i = 0; i < min_constraints; ++i) isl_mat_free(constraints[i].c); free(constraints); return hull; } /* Create a template for the convex hull of "set" and fill it up * obvious facet constraints, if any. If the result happens to * be the convex hull of "set" then *is_hull is set to 1. */ static struct isl_basic_set *proto_hull(struct isl_set *set, int *is_hull) { struct isl_basic_set *hull; unsigned n_ineq; int i; n_ineq = 1; for (i = 0; i < set->n; ++i) { n_ineq += set->p[i]->n_eq; n_ineq += set->p[i]->n_ineq; } hull = isl_basic_set_alloc_dim(isl_dim_copy(set->dim), 0, 0, n_ineq); hull = isl_basic_set_set_rational(hull); if (!hull) return NULL; return common_constraints(hull, set, is_hull); } static struct isl_basic_set *uset_convex_hull_wrap(struct isl_set *set) { struct isl_basic_set *hull; int is_hull; hull = proto_hull(set, &is_hull); if (hull && !is_hull) { if (hull->n_ineq == 0) hull = initial_hull(hull, set); hull = extend(hull, set); } isl_set_free(set); return hull; } /* Compute the convex hull of a set without any parameters or * integer divisions. Depending on whether the set is bounded, * we pass control to the wrapping based convex hull or * the Fourier-Motzkin elimination based convex hull. * We also handle a few special cases before checking the boundedness. */ static struct isl_basic_set *uset_convex_hull(struct isl_set *set) { struct isl_basic_set *convex_hull = NULL; struct isl_basic_set *lin; if (isl_set_n_dim(set) == 0) return convex_hull_0d(set); set = isl_set_coalesce(set); set = isl_set_set_rational(set); if (!set) goto error; if (!set) return NULL; if (set->n == 1) { convex_hull = isl_basic_set_copy(set->p[0]); isl_set_free(set); return convex_hull; } if (isl_set_n_dim(set) == 1) return convex_hull_1d(set); if (isl_set_is_bounded(set)) return uset_convex_hull_wrap(set); lin = uset_combined_lineality_space(isl_set_copy(set)); if (!lin) goto error; if (isl_basic_set_is_universe(lin)) { isl_set_free(set); return lin; } if (lin->n_eq < isl_basic_set_total_dim(lin)) return modulo_lineality(set, lin); isl_basic_set_free(lin); return uset_convex_hull_unbounded(set); error: isl_set_free(set); isl_basic_set_free(convex_hull); return NULL; } /* This is the core procedure, where "set" is a "pure" set, i.e., * without parameters or divs and where the convex hull of set is * known to be full-dimensional. */ static struct isl_basic_set *uset_convex_hull_wrap_bounded(struct isl_set *set) { struct isl_basic_set *convex_hull = NULL; if (isl_set_n_dim(set) == 0) { convex_hull = isl_basic_set_universe(isl_dim_copy(set->dim)); isl_set_free(set); convex_hull = isl_basic_set_set_rational(convex_hull); return convex_hull; } set = isl_set_set_rational(set); if (!set) goto error; set = isl_set_coalesce(set); if (!set) goto error; if (set->n == 1) { convex_hull = isl_basic_set_copy(set->p[0]); isl_set_free(set); return convex_hull; } if (isl_set_n_dim(set) == 1) return convex_hull_1d(set); return uset_convex_hull_wrap(set); error: isl_set_free(set); return NULL; } /* Compute the convex hull of set "set" with affine hull "affine_hull", * We first remove the equalities (transforming the set), compute the * convex hull of the transformed set and then add the equalities back * (after performing the inverse transformation. */ static struct isl_basic_set *modulo_affine_hull(struct isl_ctx *ctx, struct isl_set *set, struct isl_basic_set *affine_hull) { struct isl_mat *T; struct isl_mat *T2; struct isl_basic_set *dummy; struct isl_basic_set *convex_hull; dummy = isl_basic_set_remove_equalities( isl_basic_set_copy(affine_hull), &T, &T2); if (!dummy) goto error; isl_basic_set_free(dummy); set = isl_set_preimage(set, T); convex_hull = uset_convex_hull(set); convex_hull = isl_basic_set_preimage(convex_hull, T2); convex_hull = isl_basic_set_intersect(convex_hull, affine_hull); return convex_hull; error: isl_basic_set_free(affine_hull); isl_set_free(set); return NULL; } /* Compute the convex hull of a map. * * The implementation was inspired by "Extended Convex Hull" by Fukuda et al., * specifically, the wrapping of facets to obtain new facets. */ struct isl_basic_map *isl_map_convex_hull(struct isl_map *map) { struct isl_basic_set *bset; struct isl_basic_map *model = NULL; struct isl_basic_set *affine_hull = NULL; struct isl_basic_map *convex_hull = NULL; struct isl_set *set = NULL; struct isl_ctx *ctx; if (!map) goto error; ctx = map->ctx; if (map->n == 0) { convex_hull = isl_basic_map_empty_like_map(map); isl_map_free(map); return convex_hull; } map = isl_map_detect_equalities(map); map = isl_map_align_divs(map); model = isl_basic_map_copy(map->p[0]); set = isl_map_underlying_set(map); if (!set) goto error; affine_hull = isl_set_affine_hull(isl_set_copy(set)); if (!affine_hull) goto error; if (affine_hull->n_eq != 0) bset = modulo_affine_hull(ctx, set, affine_hull); else { isl_basic_set_free(affine_hull); bset = uset_convex_hull(set); } convex_hull = isl_basic_map_overlying_set(bset, model); ISL_F_SET(convex_hull, ISL_BASIC_MAP_NO_IMPLICIT); ISL_F_SET(convex_hull, ISL_BASIC_MAP_ALL_EQUALITIES); ISL_F_CLR(convex_hull, ISL_BASIC_MAP_RATIONAL); return convex_hull; error: isl_set_free(set); isl_basic_map_free(model); return NULL; } struct isl_basic_set *isl_set_convex_hull(struct isl_set *set) { return (struct isl_basic_set *) isl_map_convex_hull((struct isl_map *)set); } struct sh_data_entry { struct isl_hash_table *table; struct isl_tab *tab; }; /* Holds the data needed during the simple hull computation. * In particular, * n the number of basic sets in the original set * hull_table a hash table of already computed constraints * in the simple hull * p for each basic set, * table a hash table of the constraints * tab the tableau corresponding to the basic set */ struct sh_data { struct isl_ctx *ctx; unsigned n; struct isl_hash_table *hull_table; struct sh_data_entry p[1]; }; static void sh_data_free(struct sh_data *data) { int i; if (!data) return; isl_hash_table_free(data->ctx, data->hull_table); for (i = 0; i < data->n; ++i) { isl_hash_table_free(data->ctx, data->p[i].table); isl_tab_free(data->p[i].tab); } free(data); } struct ineq_cmp_data { unsigned len; isl_int *p; }; static int has_ineq(const void *entry, const void *val) { isl_int *row = (isl_int *)entry; struct ineq_cmp_data *v = (struct ineq_cmp_data *)val; return isl_seq_eq(row + 1, v->p + 1, v->len) || isl_seq_is_neg(row + 1, v->p + 1, v->len); } static int hash_ineq(struct isl_ctx *ctx, struct isl_hash_table *table, isl_int *ineq, unsigned len) { uint32_t c_hash; struct ineq_cmp_data v; struct isl_hash_table_entry *entry; v.len = len; v.p = ineq; c_hash = isl_seq_get_hash(ineq + 1, len); entry = isl_hash_table_find(ctx, table, c_hash, has_ineq, &v, 1); if (!entry) return - 1; entry->data = ineq; return 0; } /* Fill hash table "table" with the constraints of "bset". * Equalities are added as two inequalities. * The value in the hash table is a pointer to the (in)equality of "bset". */ static int hash_basic_set(struct isl_hash_table *table, struct isl_basic_set *bset) { int i, j; unsigned dim = isl_basic_set_total_dim(bset); for (i = 0; i < bset->n_eq; ++i) { for (j = 0; j < 2; ++j) { isl_seq_neg(bset->eq[i], bset->eq[i], 1 + dim); if (hash_ineq(bset->ctx, table, bset->eq[i], dim) < 0) return -1; } } for (i = 0; i < bset->n_ineq; ++i) { if (hash_ineq(bset->ctx, table, bset->ineq[i], dim) < 0) return -1; } return 0; } static struct sh_data *sh_data_alloc(struct isl_set *set, unsigned n_ineq) { struct sh_data *data; int i; data = isl_calloc(set->ctx, struct sh_data, sizeof(struct sh_data) + (set->n - 1) * sizeof(struct sh_data_entry)); if (!data) return NULL; data->ctx = set->ctx; data->n = set->n; data->hull_table = isl_hash_table_alloc(set->ctx, n_ineq); if (!data->hull_table) goto error; for (i = 0; i < set->n; ++i) { data->p[i].table = isl_hash_table_alloc(set->ctx, 2 * set->p[i]->n_eq + set->p[i]->n_ineq); if (!data->p[i].table) goto error; if (hash_basic_set(data->p[i].table, set->p[i]) < 0) goto error; } return data; error: sh_data_free(data); return NULL; } /* Check if inequality "ineq" is a bound for basic set "j" or if * it can be relaxed (by increasing the constant term) to become * a bound for that basic set. In the latter case, the constant * term is updated. * Return 1 if "ineq" is a bound * 0 if "ineq" may attain arbitrarily small values on basic set "j" * -1 if some error occurred */ static int is_bound(struct sh_data *data, struct isl_set *set, int j, isl_int *ineq) { enum isl_lp_result res; isl_int opt; if (!data->p[j].tab) { data->p[j].tab = isl_tab_from_basic_set(set->p[j]); if (!data->p[j].tab) return -1; } isl_int_init(opt); res = isl_tab_min(data->p[j].tab, ineq, data->ctx->one, &opt, NULL, 0); if (res == isl_lp_ok && isl_int_is_neg(opt)) isl_int_sub(ineq[0], ineq[0], opt); isl_int_clear(opt); return res == isl_lp_ok ? 1 : res == isl_lp_unbounded ? 0 : -1; } /* Check if inequality "ineq" from basic set "i" can be relaxed to * become a bound on the whole set. If so, add the (relaxed) inequality * to "hull". * * We first check if "hull" already contains a translate of the inequality. * If so, we are done. * Then, we check if any of the previous basic sets contains a translate * of the inequality. If so, then we have already considered this * inequality and we are done. * Otherwise, for each basic set other than "i", we check if the inequality * is a bound on the basic set. * For previous basic sets, we know that they do not contain a translate * of the inequality, so we directly call is_bound. * For following basic sets, we first check if a translate of the * inequality appears in its description and if so directly update * the inequality accordingly. */ static struct isl_basic_set *add_bound(struct isl_basic_set *hull, struct sh_data *data, struct isl_set *set, int i, isl_int *ineq) { uint32_t c_hash; struct ineq_cmp_data v; struct isl_hash_table_entry *entry; int j, k; if (!hull) return NULL; v.len = isl_basic_set_total_dim(hull); v.p = ineq; c_hash = isl_seq_get_hash(ineq + 1, v.len); entry = isl_hash_table_find(hull->ctx, data->hull_table, c_hash, has_ineq, &v, 0); if (entry) return hull; for (j = 0; j < i; ++j) { entry = isl_hash_table_find(hull->ctx, data->p[j].table, c_hash, has_ineq, &v, 0); if (entry) break; } if (j < i) return hull; k = isl_basic_set_alloc_inequality(hull); isl_seq_cpy(hull->ineq[k], ineq, 1 + v.len); if (k < 0) goto error; for (j = 0; j < i; ++j) { int bound; bound = is_bound(data, set, j, hull->ineq[k]); if (bound < 0) goto error; if (!bound) break; } if (j < i) { isl_basic_set_free_inequality(hull, 1); return hull; } for (j = i + 1; j < set->n; ++j) { int bound, neg; isl_int *ineq_j; entry = isl_hash_table_find(hull->ctx, data->p[j].table, c_hash, has_ineq, &v, 0); if (entry) { ineq_j = entry->data; neg = isl_seq_is_neg(ineq_j + 1, hull->ineq[k] + 1, v.len); if (neg) isl_int_neg(ineq_j[0], ineq_j[0]); if (isl_int_gt(ineq_j[0], hull->ineq[k][0])) isl_int_set(hull->ineq[k][0], ineq_j[0]); if (neg) isl_int_neg(ineq_j[0], ineq_j[0]); continue; } bound = is_bound(data, set, j, hull->ineq[k]); if (bound < 0) goto error; if (!bound) break; } if (j < set->n) { isl_basic_set_free_inequality(hull, 1); return hull; } entry = isl_hash_table_find(hull->ctx, data->hull_table, c_hash, has_ineq, &v, 1); if (!entry) goto error; entry->data = hull->ineq[k]; return hull; error: isl_basic_set_free(hull); return NULL; } /* Check if any inequality from basic set "i" can be relaxed to * become a bound on the whole set. If so, add the (relaxed) inequality * to "hull". */ static struct isl_basic_set *add_bounds(struct isl_basic_set *bset, struct sh_data *data, struct isl_set *set, int i) { int j, k; unsigned dim = isl_basic_set_total_dim(bset); for (j = 0; j < set->p[i]->n_eq; ++j) { for (k = 0; k < 2; ++k) { isl_seq_neg(set->p[i]->eq[j], set->p[i]->eq[j], 1+dim); add_bound(bset, data, set, i, set->p[i]->eq[j]); } } for (j = 0; j < set->p[i]->n_ineq; ++j) add_bound(bset, data, set, i, set->p[i]->ineq[j]); return bset; } /* Compute a superset of the convex hull of set that is described * by only translates of the constraints in the constituents of set. */ static struct isl_basic_set *uset_simple_hull(struct isl_set *set) { struct sh_data *data = NULL; struct isl_basic_set *hull = NULL; unsigned n_ineq; int i; if (!set) return NULL; n_ineq = 0; for (i = 0; i < set->n; ++i) { if (!set->p[i]) goto error; n_ineq += 2 * set->p[i]->n_eq + set->p[i]->n_ineq; } hull = isl_basic_set_alloc_dim(isl_dim_copy(set->dim), 0, 0, n_ineq); if (!hull) goto error; data = sh_data_alloc(set, n_ineq); if (!data) goto error; for (i = 0; i < set->n; ++i) hull = add_bounds(hull, data, set, i); sh_data_free(data); isl_set_free(set); return hull; error: sh_data_free(data); isl_basic_set_free(hull); isl_set_free(set); return NULL; } /* Compute a superset of the convex hull of map that is described * by only translates of the constraints in the constituents of map. */ struct isl_basic_map *isl_map_simple_hull(struct isl_map *map) { struct isl_set *set = NULL; struct isl_basic_map *model = NULL; struct isl_basic_map *hull; struct isl_basic_map *affine_hull; struct isl_basic_set *bset = NULL; if (!map) return NULL; if (map->n == 0) { hull = isl_basic_map_empty_like_map(map); isl_map_free(map); return hull; } if (map->n == 1) { hull = isl_basic_map_copy(map->p[0]); isl_map_free(map); return hull; } map = isl_map_detect_equalities(map); affine_hull = isl_map_affine_hull(isl_map_copy(map)); map = isl_map_align_divs(map); model = isl_basic_map_copy(map->p[0]); set = isl_map_underlying_set(map); bset = uset_simple_hull(set); hull = isl_basic_map_overlying_set(bset, model); hull = isl_basic_map_intersect(hull, affine_hull); hull = isl_basic_map_convex_hull(hull); ISL_F_SET(hull, ISL_BASIC_MAP_NO_IMPLICIT); ISL_F_SET(hull, ISL_BASIC_MAP_ALL_EQUALITIES); return hull; } struct isl_basic_set *isl_set_simple_hull(struct isl_set *set) { return (struct isl_basic_set *) isl_map_simple_hull((struct isl_map *)set); } /* Given a set "set", return parametric bounds on the dimension "dim". */ static struct isl_basic_set *set_bounds(struct isl_set *set, int dim) { unsigned set_dim = isl_set_dim(set, isl_dim_set); set = isl_set_copy(set); set = isl_set_eliminate_dims(set, dim + 1, set_dim - (dim + 1)); set = isl_set_eliminate_dims(set, 0, dim); return isl_set_convex_hull(set); } /* Computes a "simple hull" and then check if each dimension in the * resulting hull is bounded by a symbolic constant. If not, the * hull is intersected with the corresponding bounds on the whole set. */ struct isl_basic_set *isl_set_bounded_simple_hull(struct isl_set *set) { int i, j; struct isl_basic_set *hull; unsigned nparam, left; int removed_divs = 0; hull = isl_set_simple_hull(isl_set_copy(set)); if (!hull) goto error; nparam = isl_basic_set_dim(hull, isl_dim_param); for (i = 0; i < isl_basic_set_dim(hull, isl_dim_set); ++i) { int lower = 0, upper = 0; struct isl_basic_set *bounds; left = isl_basic_set_total_dim(hull) - nparam - i - 1; for (j = 0; j < hull->n_eq; ++j) { if (isl_int_is_zero(hull->eq[j][1 + nparam + i])) continue; if (isl_seq_first_non_zero(hull->eq[j]+1+nparam+i+1, left) == -1) break; } if (j < hull->n_eq) continue; for (j = 0; j < hull->n_ineq; ++j) { if (isl_int_is_zero(hull->ineq[j][1 + nparam + i])) continue; if (isl_seq_first_non_zero(hull->ineq[j]+1+nparam+i+1, left) != -1 || isl_seq_first_non_zero(hull->ineq[j]+1+nparam, i) != -1) continue; if (isl_int_is_pos(hull->ineq[j][1 + nparam + i])) lower = 1; else upper = 1; if (lower && upper) break; } if (lower && upper) continue; if (!removed_divs) { set = isl_set_remove_divs(set); if (!set) goto error; removed_divs = 1; } bounds = set_bounds(set, i); hull = isl_basic_set_intersect(hull, bounds); if (!hull) goto error; } isl_set_free(set); return hull; error: isl_set_free(set); return NULL; }