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"
17 #include <isl_val_private.h>
19 /* Given a set of modulo constraints
23 * this function computes a particular solution y_0
25 * The input is given as a matrix B = [ c A ] and a vector d.
27 * The output is matrix containing the solution y_0 or
28 * a zero-column matrix if the constraints admit no integer solution.
30 * The given set of constrains is equivalent to
34 * with D = diag d and x a fresh set of variables.
35 * Reducing both c and A modulo d does not change the
36 * value of y in the solution and may lead to smaller coefficients.
37 * Let M = [ D A ] and [ H 0 ] = M U, the Hermite normal form of M.
43 * [ H 0 ] U^{-1} [ y ] = - c
46 * [ B ] = U^{-1} [ y ]
50 * so B may be chosen arbitrarily, e.g., B = 0, and then
53 * U^{-1} [ y ] = [ 0 ]
61 * If any of the coordinates of this y are non-integer
62 * then the constraints admit no integer solution and
63 * a zero-column matrix is returned.
65 static struct isl_mat
*particular_solution(struct isl_mat
*B
, struct isl_vec
*d
)
68 struct isl_mat
*M
= NULL
;
69 struct isl_mat
*C
= NULL
;
70 struct isl_mat
*U
= NULL
;
71 struct isl_mat
*H
= NULL
;
72 struct isl_mat
*cst
= NULL
;
73 struct isl_mat
*T
= NULL
;
75 M
= isl_mat_alloc(B
->ctx
, B
->n_row
, B
->n_row
+ B
->n_col
- 1);
76 C
= isl_mat_alloc(B
->ctx
, 1 + B
->n_row
, 1);
79 isl_int_set_si(C
->row
[0][0], 1);
80 for (i
= 0; i
< B
->n_row
; ++i
) {
81 isl_seq_clr(M
->row
[i
], B
->n_row
);
82 isl_int_set(M
->row
[i
][i
], d
->block
.data
[i
]);
83 isl_int_neg(C
->row
[1 + i
][0], B
->row
[i
][0]);
84 isl_int_fdiv_r(C
->row
[1+i
][0], C
->row
[1+i
][0], M
->row
[i
][i
]);
85 for (j
= 0; j
< B
->n_col
- 1; ++j
)
86 isl_int_fdiv_r(M
->row
[i
][B
->n_row
+ j
],
87 B
->row
[i
][1 + j
], M
->row
[i
][i
]);
89 M
= isl_mat_left_hermite(M
, 0, &U
, NULL
);
92 H
= isl_mat_sub_alloc(M
, 0, B
->n_row
, 0, B
->n_row
);
93 H
= isl_mat_lin_to_aff(H
);
94 C
= isl_mat_inverse_product(H
, C
);
97 for (i
= 0; i
< B
->n_row
; ++i
) {
98 if (!isl_int_is_divisible_by(C
->row
[1+i
][0], C
->row
[0][0]))
100 isl_int_divexact(C
->row
[1+i
][0], C
->row
[1+i
][0], C
->row
[0][0]);
103 cst
= isl_mat_alloc(B
->ctx
, B
->n_row
, 0);
105 cst
= isl_mat_sub_alloc(C
, 1, B
->n_row
, 0, 1);
106 T
= isl_mat_sub_alloc(U
, B
->n_row
, B
->n_col
- 1, 0, B
->n_row
);
107 cst
= isl_mat_product(T
, cst
);
119 /* Compute and return the matrix
121 * U_1^{-1} diag(d_1, 1, ..., 1)
123 * with U_1 the unimodular completion of the first (and only) row of B.
124 * The columns of this matrix generate the lattice that satisfies
125 * the single (linear) modulo constraint.
127 static struct isl_mat
*parameter_compression_1(
128 struct isl_mat
*B
, struct isl_vec
*d
)
132 U
= isl_mat_alloc(B
->ctx
, B
->n_col
- 1, B
->n_col
- 1);
135 isl_seq_cpy(U
->row
[0], B
->row
[0] + 1, B
->n_col
- 1);
136 U
= isl_mat_unimodular_complete(U
, 1);
137 U
= isl_mat_right_inverse(U
);
140 isl_mat_col_mul(U
, 0, d
->block
.data
[0], 0);
141 U
= isl_mat_lin_to_aff(U
);
145 /* Compute a common lattice of solutions to the linear modulo
146 * constraints specified by B and d.
147 * See also the documentation of isl_mat_parameter_compression.
150 * A = [ L_1^{-T} L_2^{-T} ... L_k^{-T} ]
152 * on a common denominator. This denominator D is the lcm of modulos d.
153 * Since L_i = U_i^{-1} diag(d_i, 1, ... 1), we have
154 * L_i^{-T} = U_i^T diag(d_i, 1, ... 1)^{-T} = U_i^T diag(1/d_i, 1, ..., 1).
155 * Putting this on the common denominator, we have
156 * D * L_i^{-T} = U_i^T diag(D/d_i, D, ..., D).
158 static struct isl_mat
*parameter_compression_multi(
159 struct isl_mat
*B
, struct isl_vec
*d
)
163 struct isl_mat
*A
= NULL
, *U
= NULL
;
172 A
= isl_mat_alloc(B
->ctx
, size
, B
->n_row
* size
);
173 U
= isl_mat_alloc(B
->ctx
, size
, size
);
176 for (i
= 0; i
< B
->n_row
; ++i
) {
177 isl_seq_cpy(U
->row
[0], B
->row
[i
] + 1, size
);
178 U
= isl_mat_unimodular_complete(U
, 1);
181 isl_int_divexact(D
, D
, d
->block
.data
[i
]);
182 for (k
= 0; k
< U
->n_col
; ++k
)
183 isl_int_mul(A
->row
[k
][i
*size
+0], D
, U
->row
[0][k
]);
184 isl_int_mul(D
, D
, d
->block
.data
[i
]);
185 for (j
= 1; j
< U
->n_row
; ++j
)
186 for (k
= 0; k
< U
->n_col
; ++k
)
187 isl_int_mul(A
->row
[k
][i
*size
+j
],
190 A
= isl_mat_left_hermite(A
, 0, NULL
, NULL
);
191 T
= isl_mat_sub_alloc(A
, 0, A
->n_row
, 0, A
->n_row
);
192 T
= isl_mat_lin_to_aff(T
);
195 isl_int_set(T
->row
[0][0], D
);
196 T
= isl_mat_right_inverse(T
);
199 isl_assert(T
->ctx
, isl_int_is_one(T
->row
[0][0]), goto error
);
200 T
= isl_mat_transpose(T
);
213 /* Given a set of modulo constraints
217 * this function returns an affine transformation T,
221 * that bijectively maps the integer vectors y' to integer
222 * vectors y that satisfy the modulo constraints.
224 * This function is inspired by Section 2.5.3
225 * of B. Meister, "Stating and Manipulating Periodicity in the Polytope
226 * Model. Applications to Program Analysis and Optimization".
227 * However, the implementation only follows the algorithm of that
228 * section for computing a particular solution and not for computing
229 * a general homogeneous solution. The latter is incomplete and
230 * may remove some valid solutions.
231 * Instead, we use an adaptation of the algorithm in Section 7 of
232 * B. Meister, S. Verdoolaege, "Polynomial Approximations in the Polytope
233 * Model: Bringing the Power of Quasi-Polynomials to the Masses".
235 * The input is given as a matrix B = [ c A ] and a vector d.
236 * Each element of the vector d corresponds to a row in B.
237 * The output is a lower triangular matrix.
238 * If no integer vector y satisfies the given constraints then
239 * a matrix with zero columns is returned.
241 * We first compute a particular solution y_0 to the given set of
242 * modulo constraints in particular_solution. If no such solution
243 * exists, then we return a zero-columned transformation matrix.
244 * Otherwise, we compute the generic solution to
248 * That is we want to compute G such that
252 * with y'' integer, describes the set of solutions.
254 * We first remove the common factors of each row.
255 * In particular if gcd(A_i,d_i) != 1, then we divide the whole
256 * row i (including d_i) by this common factor. If afterwards gcd(A_i) != 1,
257 * then we divide this row of A by the common factor, unless gcd(A_i) = 0.
258 * In the later case, we simply drop the row (in both A and d).
260 * If there are no rows left in A, then G is the identity matrix. Otherwise,
261 * for each row i, we now determine the lattice of integer vectors
262 * that satisfies this row. Let U_i be the unimodular extension of the
263 * row A_i. This unimodular extension exists because gcd(A_i) = 1.
264 * The first component of
268 * needs to be a multiple of d_i. Let y' = diag(d_i, 1, ..., 1) y''.
271 * y = U_i^{-1} diag(d_i, 1, ..., 1) y''
273 * for arbitrary integer vectors y''. That is, y belongs to the lattice
274 * generated by the columns of L_i = U_i^{-1} diag(d_i, 1, ..., 1).
275 * If there is only one row, then G = L_1.
277 * If there is more than one row left, we need to compute the intersection
278 * of the lattices. That is, we need to compute an L such that
280 * L = L_i L_i' for all i
282 * with L_i' some integer matrices. Let A be constructed as follows
284 * A = [ L_1^{-T} L_2^{-T} ... L_k^{-T} ]
286 * and computed the Hermite Normal Form of A = [ H 0 ] U
289 * L_i^{-T} = H U_{1,i}
293 * H^{-T} = L_i U_{1,i}^T
295 * In other words G = L = H^{-T}.
296 * To ensure that G is lower triangular, we compute and use its Hermite
299 * The affine transformation matrix returned is then
304 * as any y = y_0 + G y' with y' integer is a solution to the original
305 * modulo constraints.
307 struct isl_mat
*isl_mat_parameter_compression(
308 struct isl_mat
*B
, struct isl_vec
*d
)
311 struct isl_mat
*cst
= NULL
;
312 struct isl_mat
*T
= NULL
;
317 isl_assert(B
->ctx
, B
->n_row
== d
->size
, goto error
);
318 cst
= particular_solution(B
, d
);
321 if (cst
->n_col
== 0) {
322 T
= isl_mat_alloc(B
->ctx
, B
->n_col
, 0);
329 /* Replace a*g*row = 0 mod g*m by row = 0 mod m */
330 for (i
= 0; i
< B
->n_row
; ++i
) {
331 isl_seq_gcd(B
->row
[i
] + 1, B
->n_col
- 1, &D
);
332 if (isl_int_is_one(D
))
334 if (isl_int_is_zero(D
)) {
335 B
= isl_mat_drop_rows(B
, i
, 1);
339 isl_seq_cpy(d
->block
.data
+i
, d
->block
.data
+i
+1,
348 isl_seq_scale_down(B
->row
[i
] + 1, B
->row
[i
] + 1, D
, B
->n_col
-1);
349 isl_int_gcd(D
, D
, d
->block
.data
[i
]);
353 isl_int_divexact(d
->block
.data
[i
], d
->block
.data
[i
], D
);
357 T
= isl_mat_identity(B
->ctx
, B
->n_col
);
358 else if (B
->n_row
== 1)
359 T
= parameter_compression_1(B
, d
);
361 T
= parameter_compression_multi(B
, d
);
362 T
= isl_mat_left_hermite(T
, 0, NULL
, NULL
);
365 isl_mat_sub_copy(T
->ctx
, T
->row
+ 1, cst
->row
, cst
->n_row
, 0, 0, 1);
379 /* Given a set of equalities
383 * compute and return an affine transformation T,
387 * that bijectively maps the integer vectors y' to integer
388 * vectors y that satisfy the modulo constraints for some value of x.
390 * Let [H 0] be the Hermite Normal Form of A, i.e.,
394 * Then y is a solution of (*) iff
396 * H^-1 B(y) (= - [I 0] Q x)
398 * is an integer vector. Let d be the common denominator of H^-1.
401 * d H^-1 B(y) = 0 mod d
403 * and compute the solution using isl_mat_parameter_compression.
405 __isl_give isl_mat
*isl_mat_parameter_compression_ext(__isl_take isl_mat
*B
,
406 __isl_take isl_mat
*A
)
413 return isl_mat_free(B
);
415 ctx
= isl_mat_get_ctx(A
);
418 A
= isl_mat_left_hermite(A
, 0, NULL
, NULL
);
419 A
= isl_mat_drop_cols(A
, n_row
, n_col
- n_row
);
420 A
= isl_mat_lin_to_aff(A
);
421 A
= isl_mat_right_inverse(A
);
422 d
= isl_vec_alloc(ctx
, n_row
);
424 d
= isl_vec_set(d
, A
->row
[0][0]);
425 A
= isl_mat_drop_rows(A
, 0, 1);
426 A
= isl_mat_drop_cols(A
, 0, 1);
427 B
= isl_mat_product(A
, B
);
429 return isl_mat_parameter_compression(B
, d
);
432 /* Given a set of equalities
436 * this function computes a unimodular transformation from a lower-dimensional
437 * space to the original space that bijectively maps the integer points x'
438 * in the lower-dimensional space to the integer points x in the original
439 * space that satisfy the equalities.
441 * The input is given as a matrix B = [ -c M ] and the output is a
442 * matrix that maps [1 x'] to [1 x].
443 * If T2 is not NULL, then *T2 is set to a matrix mapping [1 x] to [1 x'].
445 * First compute the (left) Hermite normal form of M,
447 * M [U1 U2] = M U = H = [H1 0]
449 * M = H Q = [H1 0] [Q1]
452 * with U, Q unimodular, Q = U^{-1} (and H lower triangular).
453 * Define the transformed variables as
455 * x = [U1 U2] [ x1' ] = [U1 U2] [Q1] x
458 * The equalities then become
460 * H1 x1' - c = 0 or x1' = H1^{-1} c = c'
462 * If any of the c' is non-integer, then the original set has no
463 * integer solutions (since the x' are a unimodular transformation
464 * of the x) and a zero-column matrix is returned.
465 * Otherwise, the transformation is given by
467 * x = U1 H1^{-1} c + U2 x2'
469 * The inverse transformation is simply
473 __isl_give isl_mat
*isl_mat_variable_compression(__isl_take isl_mat
*B
,
474 __isl_give isl_mat
**T2
)
477 struct isl_mat
*H
= NULL
, *C
= NULL
, *H1
, *U
= NULL
, *U1
, *U2
, *TC
;
486 H
= isl_mat_sub_alloc(B
, 0, B
->n_row
, 1, dim
);
487 H
= isl_mat_left_hermite(H
, 0, &U
, T2
);
488 if (!H
|| !U
|| (T2
&& !*T2
))
491 *T2
= isl_mat_drop_rows(*T2
, 0, B
->n_row
);
492 *T2
= isl_mat_lin_to_aff(*T2
);
496 C
= isl_mat_alloc(B
->ctx
, 1+B
->n_row
, 1);
499 isl_int_set_si(C
->row
[0][0], 1);
500 isl_mat_sub_neg(C
->ctx
, C
->row
+1, B
->row
, B
->n_row
, 0, 0, 1);
501 H1
= isl_mat_sub_alloc(H
, 0, H
->n_row
, 0, H
->n_row
);
502 H1
= isl_mat_lin_to_aff(H1
);
503 TC
= isl_mat_inverse_product(H1
, C
);
507 if (!isl_int_is_one(TC
->row
[0][0])) {
508 for (i
= 0; i
< B
->n_row
; ++i
) {
509 if (!isl_int_is_divisible_by(TC
->row
[1+i
][0], TC
->row
[0][0])) {
510 struct isl_ctx
*ctx
= B
->ctx
;
518 return isl_mat_alloc(ctx
, 1 + dim
, 0);
520 isl_seq_scale_down(TC
->row
[1+i
], TC
->row
[1+i
], TC
->row
[0][0], 1);
522 isl_int_set_si(TC
->row
[0][0], 1);
524 U1
= isl_mat_sub_alloc(U
, 0, U
->n_row
, 0, B
->n_row
);
525 U1
= isl_mat_lin_to_aff(U1
);
526 U2
= isl_mat_sub_alloc(U
, 0, U
->n_row
, B
->n_row
, U
->n_row
- B
->n_row
);
527 U2
= isl_mat_lin_to_aff(U2
);
529 TC
= isl_mat_product(U1
, TC
);
530 TC
= isl_mat_aff_direct_sum(TC
, U2
);
546 /* Use the n equalities of bset to unimodularly transform the
547 * variables x such that n transformed variables x1' have a constant value
548 * and rewrite the constraints of bset in terms of the remaining
549 * transformed variables x2'. The matrix pointed to by T maps
550 * the new variables x2' back to the original variables x, while T2
551 * maps the original variables to the new variables.
553 static struct isl_basic_set
*compress_variables(
554 struct isl_basic_set
*bset
, struct isl_mat
**T
, struct isl_mat
**T2
)
556 struct isl_mat
*B
, *TC
;
565 isl_assert(bset
->ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
566 isl_assert(bset
->ctx
, bset
->n_div
== 0, goto error
);
567 dim
= isl_basic_set_n_dim(bset
);
568 isl_assert(bset
->ctx
, bset
->n_eq
<= dim
, goto error
);
572 B
= isl_mat_sub_alloc6(bset
->ctx
, bset
->eq
, 0, bset
->n_eq
, 0, 1 + dim
);
573 TC
= isl_mat_variable_compression(B
, T2
);
576 if (TC
->n_col
== 0) {
582 return isl_basic_set_set_to_empty(bset
);
585 bset
= isl_basic_set_preimage(bset
, T
? isl_mat_copy(TC
) : TC
);
590 isl_basic_set_free(bset
);
594 struct isl_basic_set
*isl_basic_set_remove_equalities(
595 struct isl_basic_set
*bset
, struct isl_mat
**T
, struct isl_mat
**T2
)
603 isl_assert(bset
->ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
604 bset
= isl_basic_set_gauss(bset
, NULL
);
605 if (ISL_F_ISSET(bset
, ISL_BASIC_SET_EMPTY
))
607 bset
= compress_variables(bset
, T
, T2
);
610 isl_basic_set_free(bset
);
615 /* Check if dimension dim belongs to a residue class
616 * i_dim \equiv r mod m
617 * with m != 1 and if so return m in *modulo and r in *residue.
618 * As a special case, when i_dim has a fixed value v, then
619 * *modulo is set to 0 and *residue to v.
621 * If i_dim does not belong to such a residue class, then *modulo
622 * is set to 1 and *residue is set to 0.
624 int isl_basic_set_dim_residue_class(struct isl_basic_set
*bset
,
625 int pos
, isl_int
*modulo
, isl_int
*residue
)
628 struct isl_mat
*H
= NULL
, *U
= NULL
, *C
, *H1
, *U1
;
632 if (!bset
|| !modulo
|| !residue
)
635 if (isl_basic_set_plain_dim_is_fixed(bset
, pos
, residue
)) {
636 isl_int_set_si(*modulo
, 0);
641 total
= isl_basic_set_total_dim(bset
);
642 nparam
= isl_basic_set_n_param(bset
);
643 H
= isl_mat_sub_alloc6(bset
->ctx
, bset
->eq
, 0, bset
->n_eq
, 1, total
);
644 H
= isl_mat_left_hermite(H
, 0, &U
, NULL
);
648 isl_seq_gcd(U
->row
[nparam
+ pos
]+bset
->n_eq
,
649 total
-bset
->n_eq
, modulo
);
650 if (isl_int_is_zero(*modulo
))
651 isl_int_set_si(*modulo
, 1);
652 if (isl_int_is_one(*modulo
)) {
653 isl_int_set_si(*residue
, 0);
659 C
= isl_mat_alloc(bset
->ctx
, 1+bset
->n_eq
, 1);
662 isl_int_set_si(C
->row
[0][0], 1);
663 isl_mat_sub_neg(C
->ctx
, C
->row
+1, bset
->eq
, bset
->n_eq
, 0, 0, 1);
664 H1
= isl_mat_sub_alloc(H
, 0, H
->n_row
, 0, H
->n_row
);
665 H1
= isl_mat_lin_to_aff(H1
);
666 C
= isl_mat_inverse_product(H1
, C
);
668 U1
= isl_mat_sub_alloc(U
, nparam
+pos
, 1, 0, bset
->n_eq
);
669 U1
= isl_mat_lin_to_aff(U1
);
671 C
= isl_mat_product(U1
, C
);
674 if (!isl_int_is_divisible_by(C
->row
[1][0], C
->row
[0][0])) {
675 bset
= isl_basic_set_copy(bset
);
676 bset
= isl_basic_set_set_to_empty(bset
);
677 isl_basic_set_free(bset
);
678 isl_int_set_si(*modulo
, 1);
679 isl_int_set_si(*residue
, 0);
682 isl_int_divexact(*residue
, C
->row
[1][0], C
->row
[0][0]);
683 isl_int_fdiv_r(*residue
, *residue
, *modulo
);
692 /* Check if dimension dim belongs to a residue class
693 * i_dim \equiv r mod m
694 * with m != 1 and if so return m in *modulo and r in *residue.
695 * As a special case, when i_dim has a fixed value v, then
696 * *modulo is set to 0 and *residue to v.
698 * If i_dim does not belong to such a residue class, then *modulo
699 * is set to 1 and *residue is set to 0.
701 int isl_set_dim_residue_class(struct isl_set
*set
,
702 int pos
, isl_int
*modulo
, isl_int
*residue
)
708 if (!set
|| !modulo
|| !residue
)
712 isl_int_set_si(*modulo
, 0);
713 isl_int_set_si(*residue
, 0);
717 if (isl_basic_set_dim_residue_class(set
->p
[0], pos
, modulo
, residue
)<0)
723 if (isl_int_is_one(*modulo
))
729 for (i
= 1; i
< set
->n
; ++i
) {
730 if (isl_basic_set_dim_residue_class(set
->p
[i
], pos
, &m
, &r
) < 0)
732 isl_int_gcd(*modulo
, *modulo
, m
);
733 isl_int_sub(m
, *residue
, r
);
734 isl_int_gcd(*modulo
, *modulo
, m
);
735 if (!isl_int_is_zero(*modulo
))
736 isl_int_fdiv_r(*residue
, *residue
, *modulo
);
737 if (isl_int_is_one(*modulo
))
751 /* Check if dimension "dim" belongs to a residue class
752 * i_dim \equiv r mod m
753 * with m != 1 and if so return m in *modulo and r in *residue.
754 * As a special case, when i_dim has a fixed value v, then
755 * *modulo is set to 0 and *residue to v.
757 * If i_dim does not belong to such a residue class, then *modulo
758 * is set to 1 and *residue is set to 0.
760 int isl_set_dim_residue_class_val(__isl_keep isl_set
*set
,
761 int pos
, __isl_give isl_val
**modulo
, __isl_give isl_val
**residue
)
767 *modulo
= isl_val_alloc(isl_set_get_ctx(set
));
768 *residue
= isl_val_alloc(isl_set_get_ctx(set
));
769 if (!*modulo
|| !*residue
)
771 if (isl_set_dim_residue_class(set
, pos
,
772 &(*modulo
)->n
, &(*residue
)->n
) < 0)
774 isl_int_set_si((*modulo
)->d
, 1);
775 isl_int_set_si((*residue
)->d
, 1);
778 isl_val_free(*modulo
);
779 isl_val_free(*residue
);