2 * Copyright 2008-2009 Katholieke Universiteit Leuven
3 * Copyright 2010 INRIA Saclay
5 * Use of this software is governed by the MIT license
7 * Written by Sven Verdoolaege, K.U.Leuven, Departement
8 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
9 * and INRIA Saclay - Ile-de-France, Parc Club Orsay Universite,
10 * ZAC des vignes, 4 rue Jacques Monod, 91893 Orsay, France
13 #include <isl_mat_private.h>
15 #include "isl_map_private.h"
16 #include "isl_equalities.h"
18 /* Given a set of modulo constraints
22 * this function computes a particular solution y_0
24 * The input is given as a matrix B = [ c A ] and a vector d.
26 * The output is matrix containing the solution y_0 or
27 * a zero-column matrix if the constraints admit no integer solution.
29 * The given set of constrains is equivalent to
33 * with D = diag d and x a fresh set of variables.
34 * Reducing both c and A modulo d does not change the
35 * value of y in the solution and may lead to smaller coefficients.
36 * Let M = [ D A ] and [ H 0 ] = M U, the Hermite normal form of M.
42 * [ H 0 ] U^{-1} [ y ] = - c
45 * [ B ] = U^{-1} [ y ]
49 * so B may be chosen arbitrarily, e.g., B = 0, and then
52 * U^{-1} [ y ] = [ 0 ]
60 * If any of the coordinates of this y are non-integer
61 * then the constraints admit no integer solution and
62 * a zero-column matrix is returned.
64 static struct isl_mat
*particular_solution(struct isl_mat
*B
, struct isl_vec
*d
)
67 struct isl_mat
*M
= NULL
;
68 struct isl_mat
*C
= NULL
;
69 struct isl_mat
*U
= NULL
;
70 struct isl_mat
*H
= NULL
;
71 struct isl_mat
*cst
= NULL
;
72 struct isl_mat
*T
= NULL
;
74 M
= isl_mat_alloc(B
->ctx
, B
->n_row
, B
->n_row
+ B
->n_col
- 1);
75 C
= isl_mat_alloc(B
->ctx
, 1 + B
->n_row
, 1);
78 isl_int_set_si(C
->row
[0][0], 1);
79 for (i
= 0; i
< B
->n_row
; ++i
) {
80 isl_seq_clr(M
->row
[i
], B
->n_row
);
81 isl_int_set(M
->row
[i
][i
], d
->block
.data
[i
]);
82 isl_int_neg(C
->row
[1 + i
][0], B
->row
[i
][0]);
83 isl_int_fdiv_r(C
->row
[1+i
][0], C
->row
[1+i
][0], M
->row
[i
][i
]);
84 for (j
= 0; j
< B
->n_col
- 1; ++j
)
85 isl_int_fdiv_r(M
->row
[i
][B
->n_row
+ j
],
86 B
->row
[i
][1 + j
], M
->row
[i
][i
]);
88 M
= isl_mat_left_hermite(M
, 0, &U
, NULL
);
91 H
= isl_mat_sub_alloc(M
, 0, B
->n_row
, 0, B
->n_row
);
92 H
= isl_mat_lin_to_aff(H
);
93 C
= isl_mat_inverse_product(H
, C
);
96 for (i
= 0; i
< B
->n_row
; ++i
) {
97 if (!isl_int_is_divisible_by(C
->row
[1+i
][0], C
->row
[0][0]))
99 isl_int_divexact(C
->row
[1+i
][0], C
->row
[1+i
][0], C
->row
[0][0]);
102 cst
= isl_mat_alloc(B
->ctx
, B
->n_row
, 0);
104 cst
= isl_mat_sub_alloc(C
, 1, B
->n_row
, 0, 1);
105 T
= isl_mat_sub_alloc(U
, B
->n_row
, B
->n_col
- 1, 0, B
->n_row
);
106 cst
= isl_mat_product(T
, cst
);
118 /* Compute and return the matrix
120 * U_1^{-1} diag(d_1, 1, ..., 1)
122 * with U_1 the unimodular completion of the first (and only) row of B.
123 * The columns of this matrix generate the lattice that satisfies
124 * the single (linear) modulo constraint.
126 static struct isl_mat
*parameter_compression_1(
127 struct isl_mat
*B
, struct isl_vec
*d
)
131 U
= isl_mat_alloc(B
->ctx
, B
->n_col
- 1, B
->n_col
- 1);
134 isl_seq_cpy(U
->row
[0], B
->row
[0] + 1, B
->n_col
- 1);
135 U
= isl_mat_unimodular_complete(U
, 1);
136 U
= isl_mat_right_inverse(U
);
139 isl_mat_col_mul(U
, 0, d
->block
.data
[0], 0);
140 U
= isl_mat_lin_to_aff(U
);
144 /* Compute a common lattice of solutions to the linear modulo
145 * constraints specified by B and d.
146 * See also the documentation of isl_mat_parameter_compression.
149 * A = [ L_1^{-T} L_2^{-T} ... L_k^{-T} ]
151 * on a common denominator. This denominator D is the lcm of modulos d.
152 * Since L_i = U_i^{-1} diag(d_i, 1, ... 1), we have
153 * L_i^{-T} = U_i^T diag(d_i, 1, ... 1)^{-T} = U_i^T diag(1/d_i, 1, ..., 1).
154 * Putting this on the common denominator, we have
155 * D * L_i^{-T} = U_i^T diag(D/d_i, D, ..., D).
157 static struct isl_mat
*parameter_compression_multi(
158 struct isl_mat
*B
, struct isl_vec
*d
)
162 struct isl_mat
*A
= NULL
, *U
= NULL
;
171 A
= isl_mat_alloc(B
->ctx
, size
, B
->n_row
* size
);
172 U
= isl_mat_alloc(B
->ctx
, size
, size
);
175 for (i
= 0; i
< B
->n_row
; ++i
) {
176 isl_seq_cpy(U
->row
[0], B
->row
[i
] + 1, size
);
177 U
= isl_mat_unimodular_complete(U
, 1);
180 isl_int_divexact(D
, D
, d
->block
.data
[i
]);
181 for (k
= 0; k
< U
->n_col
; ++k
)
182 isl_int_mul(A
->row
[k
][i
*size
+0], D
, U
->row
[0][k
]);
183 isl_int_mul(D
, D
, d
->block
.data
[i
]);
184 for (j
= 1; j
< U
->n_row
; ++j
)
185 for (k
= 0; k
< U
->n_col
; ++k
)
186 isl_int_mul(A
->row
[k
][i
*size
+j
],
189 A
= isl_mat_left_hermite(A
, 0, NULL
, NULL
);
190 T
= isl_mat_sub_alloc(A
, 0, A
->n_row
, 0, A
->n_row
);
191 T
= isl_mat_lin_to_aff(T
);
194 isl_int_set(T
->row
[0][0], D
);
195 T
= isl_mat_right_inverse(T
);
198 isl_assert(T
->ctx
, isl_int_is_one(T
->row
[0][0]), goto error
);
199 T
= isl_mat_transpose(T
);
212 /* Given a set of modulo constraints
216 * this function returns an affine transformation T,
220 * that bijectively maps the integer vectors y' to integer
221 * vectors y that satisfy the modulo constraints.
223 * This function is inspired by Section 2.5.3
224 * of B. Meister, "Stating and Manipulating Periodicity in the Polytope
225 * Model. Applications to Program Analysis and Optimization".
226 * However, the implementation only follows the algorithm of that
227 * section for computing a particular solution and not for computing
228 * a general homogeneous solution. The latter is incomplete and
229 * may remove some valid solutions.
230 * Instead, we use an adaptation of the algorithm in Section 7 of
231 * B. Meister, S. Verdoolaege, "Polynomial Approximations in the Polytope
232 * Model: Bringing the Power of Quasi-Polynomials to the Masses".
234 * The input is given as a matrix B = [ c A ] and a vector d.
235 * Each element of the vector d corresponds to a row in B.
236 * The output is a lower triangular matrix.
237 * If no integer vector y satisfies the given constraints then
238 * a matrix with zero columns is returned.
240 * We first compute a particular solution y_0 to the given set of
241 * modulo constraints in particular_solution. If no such solution
242 * exists, then we return a zero-columned transformation matrix.
243 * Otherwise, we compute the generic solution to
247 * That is we want to compute G such that
251 * with y'' integer, describes the set of solutions.
253 * We first remove the common factors of each row.
254 * In particular if gcd(A_i,d_i) != 1, then we divide the whole
255 * row i (including d_i) by this common factor. If afterwards gcd(A_i) != 1,
256 * then we divide this row of A by the common factor, unless gcd(A_i) = 0.
257 * In the later case, we simply drop the row (in both A and d).
259 * If there are no rows left in A, then G is the identity matrix. Otherwise,
260 * for each row i, we now determine the lattice of integer vectors
261 * that satisfies this row. Let U_i be the unimodular extension of the
262 * row A_i. This unimodular extension exists because gcd(A_i) = 1.
263 * The first component of
267 * needs to be a multiple of d_i. Let y' = diag(d_i, 1, ..., 1) y''.
270 * y = U_i^{-1} diag(d_i, 1, ..., 1) y''
272 * for arbitrary integer vectors y''. That is, y belongs to the lattice
273 * generated by the columns of L_i = U_i^{-1} diag(d_i, 1, ..., 1).
274 * If there is only one row, then G = L_1.
276 * If there is more than one row left, we need to compute the intersection
277 * of the lattices. That is, we need to compute an L such that
279 * L = L_i L_i' for all i
281 * with L_i' some integer matrices. Let A be constructed as follows
283 * A = [ L_1^{-T} L_2^{-T} ... L_k^{-T} ]
285 * and computed the Hermite Normal Form of A = [ H 0 ] U
288 * L_i^{-T} = H U_{1,i}
292 * H^{-T} = L_i U_{1,i}^T
294 * In other words G = L = H^{-T}.
295 * To ensure that G is lower triangular, we compute and use its Hermite
298 * The affine transformation matrix returned is then
303 * as any y = y_0 + G y' with y' integer is a solution to the original
304 * modulo constraints.
306 struct isl_mat
*isl_mat_parameter_compression(
307 struct isl_mat
*B
, struct isl_vec
*d
)
310 struct isl_mat
*cst
= NULL
;
311 struct isl_mat
*T
= NULL
;
316 isl_assert(B
->ctx
, B
->n_row
== d
->size
, goto error
);
317 cst
= particular_solution(B
, d
);
320 if (cst
->n_col
== 0) {
321 T
= isl_mat_alloc(B
->ctx
, B
->n_col
, 0);
328 /* Replace a*g*row = 0 mod g*m by row = 0 mod m */
329 for (i
= 0; i
< B
->n_row
; ++i
) {
330 isl_seq_gcd(B
->row
[i
] + 1, B
->n_col
- 1, &D
);
331 if (isl_int_is_one(D
))
333 if (isl_int_is_zero(D
)) {
334 B
= isl_mat_drop_rows(B
, i
, 1);
338 isl_seq_cpy(d
->block
.data
+i
, d
->block
.data
+i
+1,
347 isl_seq_scale_down(B
->row
[i
] + 1, B
->row
[i
] + 1, D
, B
->n_col
-1);
348 isl_int_gcd(D
, D
, d
->block
.data
[i
]);
352 isl_int_divexact(d
->block
.data
[i
], d
->block
.data
[i
], D
);
356 T
= isl_mat_identity(B
->ctx
, B
->n_col
);
357 else if (B
->n_row
== 1)
358 T
= parameter_compression_1(B
, d
);
360 T
= parameter_compression_multi(B
, d
);
361 T
= isl_mat_left_hermite(T
, 0, NULL
, NULL
);
364 isl_mat_sub_copy(T
->ctx
, T
->row
+ 1, cst
->row
, cst
->n_row
, 0, 0, 1);
378 /* Given a set of equalities
382 * compute and return an affine transformation T,
386 * that bijectively maps the integer vectors y' to integer
387 * vectors y that satisfy the modulo constraints for some value of x.
389 * Let [H 0] be the Hermite Normal Form of A, i.e.,
393 * Then y is a solution of (*) iff
395 * H^-1 B(y) (= - [I 0] Q x)
397 * is an integer vector. Let d be the common denominator of H^-1.
400 * d H^-1 B(y) = 0 mod d
402 * and compute the solution using isl_mat_parameter_compression.
404 __isl_give isl_mat
*isl_mat_parameter_compression_ext(__isl_take isl_mat
*B
,
405 __isl_take isl_mat
*A
)
412 return isl_mat_free(B
);
414 ctx
= isl_mat_get_ctx(A
);
417 A
= isl_mat_left_hermite(A
, 0, NULL
, NULL
);
418 A
= isl_mat_drop_cols(A
, n_row
, n_col
- n_row
);
419 A
= isl_mat_lin_to_aff(A
);
420 A
= isl_mat_right_inverse(A
);
421 d
= isl_vec_alloc(ctx
, n_row
);
423 d
= isl_vec_set(d
, A
->row
[0][0]);
424 A
= isl_mat_drop_rows(A
, 0, 1);
425 A
= isl_mat_drop_cols(A
, 0, 1);
426 B
= isl_mat_product(A
, B
);
428 return isl_mat_parameter_compression(B
, d
);
431 /* Given a set of equalities
435 * this function computes a unimodular transformation from a lower-dimensional
436 * space to the original space that bijectively maps the integer points x'
437 * in the lower-dimensional space to the integer points x in the original
438 * space that satisfy the equalities.
440 * The input is given as a matrix B = [ -c M ] and the output is a
441 * matrix that maps [1 x'] to [1 x].
442 * If T2 is not NULL, then *T2 is set to a matrix mapping [1 x] to [1 x'].
444 * First compute the (left) Hermite normal form of M,
446 * M [U1 U2] = M U = H = [H1 0]
448 * M = H Q = [H1 0] [Q1]
451 * with U, Q unimodular, Q = U^{-1} (and H lower triangular).
452 * Define the transformed variables as
454 * x = [U1 U2] [ x1' ] = [U1 U2] [Q1] x
457 * The equalities then become
459 * H1 x1' - c = 0 or x1' = H1^{-1} c = c'
461 * If any of the c' is non-integer, then the original set has no
462 * integer solutions (since the x' are a unimodular transformation
463 * of the x) and a zero-column matrix is returned.
464 * Otherwise, the transformation is given by
466 * x = U1 H1^{-1} c + U2 x2'
468 * The inverse transformation is simply
472 __isl_give isl_mat
*isl_mat_variable_compression(__isl_take isl_mat
*B
,
473 __isl_give isl_mat
**T2
)
476 struct isl_mat
*H
= NULL
, *C
= NULL
, *H1
, *U
= NULL
, *U1
, *U2
, *TC
;
485 H
= isl_mat_sub_alloc(B
, 0, B
->n_row
, 1, dim
);
486 H
= isl_mat_left_hermite(H
, 0, &U
, T2
);
487 if (!H
|| !U
|| (T2
&& !*T2
))
490 *T2
= isl_mat_drop_rows(*T2
, 0, B
->n_row
);
491 *T2
= isl_mat_lin_to_aff(*T2
);
495 C
= isl_mat_alloc(B
->ctx
, 1+B
->n_row
, 1);
498 isl_int_set_si(C
->row
[0][0], 1);
499 isl_mat_sub_neg(C
->ctx
, C
->row
+1, B
->row
, B
->n_row
, 0, 0, 1);
500 H1
= isl_mat_sub_alloc(H
, 0, H
->n_row
, 0, H
->n_row
);
501 H1
= isl_mat_lin_to_aff(H1
);
502 TC
= isl_mat_inverse_product(H1
, C
);
506 if (!isl_int_is_one(TC
->row
[0][0])) {
507 for (i
= 0; i
< B
->n_row
; ++i
) {
508 if (!isl_int_is_divisible_by(TC
->row
[1+i
][0], TC
->row
[0][0])) {
509 struct isl_ctx
*ctx
= B
->ctx
;
517 return isl_mat_alloc(ctx
, 1 + dim
, 0);
519 isl_seq_scale_down(TC
->row
[1+i
], TC
->row
[1+i
], TC
->row
[0][0], 1);
521 isl_int_set_si(TC
->row
[0][0], 1);
523 U1
= isl_mat_sub_alloc(U
, 0, U
->n_row
, 0, B
->n_row
);
524 U1
= isl_mat_lin_to_aff(U1
);
525 U2
= isl_mat_sub_alloc(U
, 0, U
->n_row
, B
->n_row
, U
->n_row
- B
->n_row
);
526 U2
= isl_mat_lin_to_aff(U2
);
528 TC
= isl_mat_product(U1
, TC
);
529 TC
= isl_mat_aff_direct_sum(TC
, U2
);
545 /* Use the n equalities of bset to unimodularly transform the
546 * variables x such that n transformed variables x1' have a constant value
547 * and rewrite the constraints of bset in terms of the remaining
548 * transformed variables x2'. The matrix pointed to by T maps
549 * the new variables x2' back to the original variables x, while T2
550 * maps the original variables to the new variables.
552 static struct isl_basic_set
*compress_variables(
553 struct isl_basic_set
*bset
, struct isl_mat
**T
, struct isl_mat
**T2
)
555 struct isl_mat
*B
, *TC
;
564 isl_assert(bset
->ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
565 isl_assert(bset
->ctx
, bset
->n_div
== 0, goto error
);
566 dim
= isl_basic_set_n_dim(bset
);
567 isl_assert(bset
->ctx
, bset
->n_eq
<= dim
, goto error
);
571 B
= isl_mat_sub_alloc6(bset
->ctx
, bset
->eq
, 0, bset
->n_eq
, 0, 1 + dim
);
572 TC
= isl_mat_variable_compression(B
, T2
);
575 if (TC
->n_col
== 0) {
581 return isl_basic_set_set_to_empty(bset
);
584 bset
= isl_basic_set_preimage(bset
, T
? isl_mat_copy(TC
) : TC
);
589 isl_basic_set_free(bset
);
593 struct isl_basic_set
*isl_basic_set_remove_equalities(
594 struct isl_basic_set
*bset
, struct isl_mat
**T
, struct isl_mat
**T2
)
602 isl_assert(bset
->ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
603 bset
= isl_basic_set_gauss(bset
, NULL
);
604 if (ISL_F_ISSET(bset
, ISL_BASIC_SET_EMPTY
))
606 bset
= compress_variables(bset
, T
, T2
);
609 isl_basic_set_free(bset
);
614 /* Check if dimension dim belongs to a residue class
615 * i_dim \equiv r mod m
616 * with m != 1 and if so return m in *modulo and r in *residue.
617 * As a special case, when i_dim has a fixed value v, then
618 * *modulo is set to 0 and *residue to v.
620 * If i_dim does not belong to such a residue class, then *modulo
621 * is set to 1 and *residue is set to 0.
623 int isl_basic_set_dim_residue_class(struct isl_basic_set
*bset
,
624 int pos
, isl_int
*modulo
, isl_int
*residue
)
627 struct isl_mat
*H
= NULL
, *U
= NULL
, *C
, *H1
, *U1
;
631 if (!bset
|| !modulo
|| !residue
)
634 if (isl_basic_set_plain_dim_is_fixed(bset
, pos
, residue
)) {
635 isl_int_set_si(*modulo
, 0);
640 total
= isl_basic_set_total_dim(bset
);
641 nparam
= isl_basic_set_n_param(bset
);
642 H
= isl_mat_sub_alloc6(bset
->ctx
, bset
->eq
, 0, bset
->n_eq
, 1, total
);
643 H
= isl_mat_left_hermite(H
, 0, &U
, NULL
);
647 isl_seq_gcd(U
->row
[nparam
+ pos
]+bset
->n_eq
,
648 total
-bset
->n_eq
, modulo
);
649 if (isl_int_is_zero(*modulo
))
650 isl_int_set_si(*modulo
, 1);
651 if (isl_int_is_one(*modulo
)) {
652 isl_int_set_si(*residue
, 0);
658 C
= isl_mat_alloc(bset
->ctx
, 1+bset
->n_eq
, 1);
661 isl_int_set_si(C
->row
[0][0], 1);
662 isl_mat_sub_neg(C
->ctx
, C
->row
+1, bset
->eq
, bset
->n_eq
, 0, 0, 1);
663 H1
= isl_mat_sub_alloc(H
, 0, H
->n_row
, 0, H
->n_row
);
664 H1
= isl_mat_lin_to_aff(H1
);
665 C
= isl_mat_inverse_product(H1
, C
);
667 U1
= isl_mat_sub_alloc(U
, nparam
+pos
, 1, 0, bset
->n_eq
);
668 U1
= isl_mat_lin_to_aff(U1
);
670 C
= isl_mat_product(U1
, C
);
673 if (!isl_int_is_divisible_by(C
->row
[1][0], C
->row
[0][0])) {
674 bset
= isl_basic_set_copy(bset
);
675 bset
= isl_basic_set_set_to_empty(bset
);
676 isl_basic_set_free(bset
);
677 isl_int_set_si(*modulo
, 1);
678 isl_int_set_si(*residue
, 0);
681 isl_int_divexact(*residue
, C
->row
[1][0], C
->row
[0][0]);
682 isl_int_fdiv_r(*residue
, *residue
, *modulo
);
691 /* Check if dimension dim belongs to a residue class
692 * i_dim \equiv r mod m
693 * with m != 1 and if so return m in *modulo and r in *residue.
694 * As a special case, when i_dim has a fixed value v, then
695 * *modulo is set to 0 and *residue to v.
697 * If i_dim does not belong to such a residue class, then *modulo
698 * is set to 1 and *residue is set to 0.
700 int isl_set_dim_residue_class(struct isl_set
*set
,
701 int pos
, isl_int
*modulo
, isl_int
*residue
)
707 if (!set
|| !modulo
|| !residue
)
711 isl_int_set_si(*modulo
, 0);
712 isl_int_set_si(*residue
, 0);
716 if (isl_basic_set_dim_residue_class(set
->p
[0], pos
, modulo
, residue
)<0)
722 if (isl_int_is_one(*modulo
))
728 for (i
= 1; i
< set
->n
; ++i
) {
729 if (isl_basic_set_dim_residue_class(set
->p
[i
], pos
, &m
, &r
) < 0)
731 isl_int_gcd(*modulo
, *modulo
, m
);
732 isl_int_sub(m
, *residue
, r
);
733 isl_int_gcd(*modulo
, *modulo
, m
);
734 if (!isl_int_is_zero(*modulo
))
735 isl_int_fdiv_r(*residue
, *residue
, *modulo
);
736 if (isl_int_is_one(*modulo
))