2871 lines
88 KiB
C
2871 lines
88 KiB
C
/* Loop transformation code generation
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Copyright (C) 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010
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Free Software Foundation, Inc.
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Contributed by Daniel Berlin <dberlin@dberlin.org>
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This file is part of GCC.
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GCC is free software; you can redistribute it and/or modify it under
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the terms of the GNU General Public License as published by the Free
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Software Foundation; either version 3, or (at your option) any later
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version.
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GCC is distributed in the hope that it will be useful, but WITHOUT ANY
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WARRANTY; without even the implied warranty of MERCHANTABILITY or
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FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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for more details.
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You should have received a copy of the GNU General Public License
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along with GCC; see the file COPYING3. If not see
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<http://www.gnu.org/licenses/>. */
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#include "config.h"
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#include "system.h"
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#include "coretypes.h"
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#include "tm.h"
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#include "ggc.h"
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#include "tree.h"
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#include "target.h"
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#include "rtl.h"
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#include "basic-block.h"
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#include "diagnostic.h"
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#include "obstack.h"
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#include "tree-flow.h"
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#include "tree-dump.h"
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#include "timevar.h"
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#include "cfgloop.h"
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#include "expr.h"
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#include "optabs.h"
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#include "tree-chrec.h"
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#include "tree-data-ref.h"
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#include "tree-pass.h"
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#include "tree-scalar-evolution.h"
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#include "vec.h"
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#include "lambda.h"
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#include "vecprim.h"
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#include "pointer-set.h"
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/* This loop nest code generation is based on non-singular matrix
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math.
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A little terminology and a general sketch of the algorithm. See "A singular
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loop transformation framework based on non-singular matrices" by Wei Li and
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Keshav Pingali for formal proofs that the various statements below are
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correct.
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A loop iteration space represents the points traversed by the loop. A point in the
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iteration space can be represented by a vector of size <loop depth>. You can
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therefore represent the iteration space as an integral combinations of a set
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of basis vectors.
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A loop iteration space is dense if every integer point between the loop
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bounds is a point in the iteration space. Every loop with a step of 1
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therefore has a dense iteration space.
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for i = 1 to 3, step 1 is a dense iteration space.
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A loop iteration space is sparse if it is not dense. That is, the iteration
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space skips integer points that are within the loop bounds.
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for i = 1 to 3, step 2 is a sparse iteration space, because the integer point
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2 is skipped.
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Dense source spaces are easy to transform, because they don't skip any
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points to begin with. Thus we can compute the exact bounds of the target
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space using min/max and floor/ceil.
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For a dense source space, we take the transformation matrix, decompose it
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into a lower triangular part (H) and a unimodular part (U).
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We then compute the auxiliary space from the unimodular part (source loop
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nest . U = auxiliary space) , which has two important properties:
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1. It traverses the iterations in the same lexicographic order as the source
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space.
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2. It is a dense space when the source is a dense space (even if the target
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space is going to be sparse).
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Given the auxiliary space, we use the lower triangular part to compute the
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bounds in the target space by simple matrix multiplication.
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The gaps in the target space (IE the new loop step sizes) will be the
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diagonals of the H matrix.
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Sparse source spaces require another step, because you can't directly compute
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the exact bounds of the auxiliary and target space from the sparse space.
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Rather than try to come up with a separate algorithm to handle sparse source
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spaces directly, we just find a legal transformation matrix that gives you
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the sparse source space, from a dense space, and then transform the dense
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space.
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For a regular sparse space, you can represent the source space as an integer
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lattice, and the base space of that lattice will always be dense. Thus, we
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effectively use the lattice to figure out the transformation from the lattice
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base space, to the sparse iteration space (IE what transform was applied to
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the dense space to make it sparse). We then compose this transform with the
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transformation matrix specified by the user (since our matrix transformations
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are closed under composition, this is okay). We can then use the base space
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(which is dense) plus the composed transformation matrix, to compute the rest
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of the transform using the dense space algorithm above.
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In other words, our sparse source space (B) is decomposed into a dense base
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space (A), and a matrix (L) that transforms A into B, such that A.L = B.
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We then compute the composition of L and the user transformation matrix (T),
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so that T is now a transform from A to the result, instead of from B to the
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result.
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IE A.(LT) = result instead of B.T = result
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Since A is now a dense source space, we can use the dense source space
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algorithm above to compute the result of applying transform (LT) to A.
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Fourier-Motzkin elimination is used to compute the bounds of the base space
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of the lattice. */
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static bool perfect_nestify (struct loop *, VEC(tree,heap) *,
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VEC(tree,heap) *, VEC(int,heap) *,
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VEC(tree,heap) *);
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/* Lattice stuff that is internal to the code generation algorithm. */
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typedef struct lambda_lattice_s
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{
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/* Lattice base matrix. */
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lambda_matrix base;
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/* Lattice dimension. */
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int dimension;
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/* Origin vector for the coefficients. */
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lambda_vector origin;
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/* Origin matrix for the invariants. */
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lambda_matrix origin_invariants;
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/* Number of invariants. */
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int invariants;
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} *lambda_lattice;
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#define LATTICE_BASE(T) ((T)->base)
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#define LATTICE_DIMENSION(T) ((T)->dimension)
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#define LATTICE_ORIGIN(T) ((T)->origin)
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#define LATTICE_ORIGIN_INVARIANTS(T) ((T)->origin_invariants)
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#define LATTICE_INVARIANTS(T) ((T)->invariants)
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static bool lle_equal (lambda_linear_expression, lambda_linear_expression,
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int, int);
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static lambda_lattice lambda_lattice_new (int, int, struct obstack *);
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static lambda_lattice lambda_lattice_compute_base (lambda_loopnest,
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struct obstack *);
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static bool can_convert_to_perfect_nest (struct loop *);
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/* Create a new lambda loop in LAMBDA_OBSTACK. */
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static lambda_loop
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lambda_loop_new (struct obstack * lambda_obstack)
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{
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lambda_loop result = (lambda_loop)
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obstack_alloc (lambda_obstack, sizeof (struct lambda_loop_s));
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memset (result, 0, sizeof (struct lambda_loop_s));
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return result;
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}
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/* Create a new lambda body vector. */
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lambda_body_vector
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lambda_body_vector_new (int size, struct obstack * lambda_obstack)
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{
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lambda_body_vector ret;
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ret = (lambda_body_vector) obstack_alloc (lambda_obstack,
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sizeof (*ret));
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LBV_COEFFICIENTS (ret) = lambda_vector_new (size);
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LBV_SIZE (ret) = size;
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LBV_DENOMINATOR (ret) = 1;
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return ret;
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}
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/* Compute the new coefficients for the vector based on the
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*inverse* of the transformation matrix. */
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lambda_body_vector
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lambda_body_vector_compute_new (lambda_trans_matrix transform,
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lambda_body_vector vect,
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struct obstack * lambda_obstack)
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{
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lambda_body_vector temp;
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int depth;
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/* Make sure the matrix is square. */
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gcc_assert (LTM_ROWSIZE (transform) == LTM_COLSIZE (transform));
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depth = LTM_ROWSIZE (transform);
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temp = lambda_body_vector_new (depth, lambda_obstack);
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LBV_DENOMINATOR (temp) =
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LBV_DENOMINATOR (vect) * LTM_DENOMINATOR (transform);
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lambda_vector_matrix_mult (LBV_COEFFICIENTS (vect), depth,
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LTM_MATRIX (transform), depth,
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LBV_COEFFICIENTS (temp));
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LBV_SIZE (temp) = LBV_SIZE (vect);
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return temp;
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}
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/* Print out a lambda body vector. */
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void
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print_lambda_body_vector (FILE * outfile, lambda_body_vector body)
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{
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print_lambda_vector (outfile, LBV_COEFFICIENTS (body), LBV_SIZE (body));
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}
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/* Return TRUE if two linear expressions are equal. */
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static bool
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lle_equal (lambda_linear_expression lle1, lambda_linear_expression lle2,
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int depth, int invariants)
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{
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int i;
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if (lle1 == NULL || lle2 == NULL)
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return false;
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if (LLE_CONSTANT (lle1) != LLE_CONSTANT (lle2))
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return false;
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if (LLE_DENOMINATOR (lle1) != LLE_DENOMINATOR (lle2))
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return false;
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for (i = 0; i < depth; i++)
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if (LLE_COEFFICIENTS (lle1)[i] != LLE_COEFFICIENTS (lle2)[i])
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return false;
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for (i = 0; i < invariants; i++)
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if (LLE_INVARIANT_COEFFICIENTS (lle1)[i] !=
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LLE_INVARIANT_COEFFICIENTS (lle2)[i])
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return false;
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return true;
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}
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/* Create a new linear expression with dimension DIM, and total number
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of invariants INVARIANTS. */
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lambda_linear_expression
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lambda_linear_expression_new (int dim, int invariants,
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struct obstack * lambda_obstack)
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{
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lambda_linear_expression ret;
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ret = (lambda_linear_expression)obstack_alloc (lambda_obstack,
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sizeof (*ret));
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LLE_COEFFICIENTS (ret) = lambda_vector_new (dim);
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LLE_CONSTANT (ret) = 0;
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LLE_INVARIANT_COEFFICIENTS (ret) = lambda_vector_new (invariants);
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LLE_DENOMINATOR (ret) = 1;
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LLE_NEXT (ret) = NULL;
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return ret;
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}
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/* Print out a linear expression EXPR, with SIZE coefficients, to OUTFILE.
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The starting letter used for variable names is START. */
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static void
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print_linear_expression (FILE * outfile, lambda_vector expr, int size,
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char start)
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{
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int i;
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bool first = true;
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for (i = 0; i < size; i++)
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{
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if (expr[i] != 0)
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{
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if (first)
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{
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if (expr[i] < 0)
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fprintf (outfile, "-");
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first = false;
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}
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else if (expr[i] > 0)
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fprintf (outfile, " + ");
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else
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fprintf (outfile, " - ");
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if (abs (expr[i]) == 1)
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fprintf (outfile, "%c", start + i);
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else
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fprintf (outfile, "%d%c", abs (expr[i]), start + i);
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}
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}
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}
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/* Print out a lambda linear expression structure, EXPR, to OUTFILE. The
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depth/number of coefficients is given by DEPTH, the number of invariants is
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given by INVARIANTS, and the character to start variable names with is given
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by START. */
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void
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print_lambda_linear_expression (FILE * outfile,
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lambda_linear_expression expr,
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int depth, int invariants, char start)
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{
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fprintf (outfile, "\tLinear expression: ");
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print_linear_expression (outfile, LLE_COEFFICIENTS (expr), depth, start);
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fprintf (outfile, " constant: %d ", LLE_CONSTANT (expr));
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fprintf (outfile, " invariants: ");
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print_linear_expression (outfile, LLE_INVARIANT_COEFFICIENTS (expr),
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invariants, 'A');
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fprintf (outfile, " denominator: %d\n", LLE_DENOMINATOR (expr));
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}
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/* Print a lambda loop structure LOOP to OUTFILE. The depth/number of
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coefficients is given by DEPTH, the number of invariants is
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given by INVARIANTS, and the character to start variable names with is given
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by START. */
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void
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print_lambda_loop (FILE * outfile, lambda_loop loop, int depth,
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int invariants, char start)
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{
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int step;
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lambda_linear_expression expr;
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gcc_assert (loop);
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expr = LL_LINEAR_OFFSET (loop);
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step = LL_STEP (loop);
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fprintf (outfile, " step size = %d \n", step);
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if (expr)
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{
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fprintf (outfile, " linear offset: \n");
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print_lambda_linear_expression (outfile, expr, depth, invariants,
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start);
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}
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fprintf (outfile, " lower bound: \n");
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for (expr = LL_LOWER_BOUND (loop); expr != NULL; expr = LLE_NEXT (expr))
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print_lambda_linear_expression (outfile, expr, depth, invariants, start);
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fprintf (outfile, " upper bound: \n");
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for (expr = LL_UPPER_BOUND (loop); expr != NULL; expr = LLE_NEXT (expr))
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print_lambda_linear_expression (outfile, expr, depth, invariants, start);
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}
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/* Create a new loop nest structure with DEPTH loops, and INVARIANTS as the
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number of invariants. */
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lambda_loopnest
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lambda_loopnest_new (int depth, int invariants,
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struct obstack * lambda_obstack)
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{
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lambda_loopnest ret;
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ret = (lambda_loopnest)obstack_alloc (lambda_obstack, sizeof (*ret));
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LN_LOOPS (ret) = (lambda_loop *)
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obstack_alloc (lambda_obstack, depth * sizeof(LN_LOOPS(ret)));
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LN_DEPTH (ret) = depth;
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LN_INVARIANTS (ret) = invariants;
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return ret;
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}
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/* Print a lambda loopnest structure, NEST, to OUTFILE. The starting
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character to use for loop names is given by START. */
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void
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print_lambda_loopnest (FILE * outfile, lambda_loopnest nest, char start)
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{
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int i;
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for (i = 0; i < LN_DEPTH (nest); i++)
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{
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fprintf (outfile, "Loop %c\n", start + i);
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print_lambda_loop (outfile, LN_LOOPS (nest)[i], LN_DEPTH (nest),
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LN_INVARIANTS (nest), 'i');
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fprintf (outfile, "\n");
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}
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}
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/* Allocate a new lattice structure of DEPTH x DEPTH, with INVARIANTS number
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of invariants. */
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static lambda_lattice
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lambda_lattice_new (int depth, int invariants, struct obstack * lambda_obstack)
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{
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lambda_lattice ret
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= (lambda_lattice)obstack_alloc (lambda_obstack, sizeof (*ret));
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LATTICE_BASE (ret) = lambda_matrix_new (depth, depth, lambda_obstack);
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LATTICE_ORIGIN (ret) = lambda_vector_new (depth);
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LATTICE_ORIGIN_INVARIANTS (ret) = lambda_matrix_new (depth, invariants,
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lambda_obstack);
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LATTICE_DIMENSION (ret) = depth;
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LATTICE_INVARIANTS (ret) = invariants;
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return ret;
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}
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/* Compute the lattice base for NEST. The lattice base is essentially a
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non-singular transform from a dense base space to a sparse iteration space.
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We use it so that we don't have to specially handle the case of a sparse
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iteration space in other parts of the algorithm. As a result, this routine
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only does something interesting (IE produce a matrix that isn't the
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identity matrix) if NEST is a sparse space. */
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static lambda_lattice
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lambda_lattice_compute_base (lambda_loopnest nest,
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struct obstack * lambda_obstack)
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{
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lambda_lattice ret;
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int depth, invariants;
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lambda_matrix base;
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int i, j, step;
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lambda_loop loop;
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lambda_linear_expression expression;
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depth = LN_DEPTH (nest);
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invariants = LN_INVARIANTS (nest);
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ret = lambda_lattice_new (depth, invariants, lambda_obstack);
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base = LATTICE_BASE (ret);
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for (i = 0; i < depth; i++)
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{
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loop = LN_LOOPS (nest)[i];
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gcc_assert (loop);
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step = LL_STEP (loop);
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/* If we have a step of 1, then the base is one, and the
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origin and invariant coefficients are 0. */
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if (step == 1)
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{
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for (j = 0; j < depth; j++)
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base[i][j] = 0;
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base[i][i] = 1;
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LATTICE_ORIGIN (ret)[i] = 0;
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for (j = 0; j < invariants; j++)
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LATTICE_ORIGIN_INVARIANTS (ret)[i][j] = 0;
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}
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else
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{
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/* Otherwise, we need the lower bound expression (which must
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be an affine function) to determine the base. */
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expression = LL_LOWER_BOUND (loop);
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gcc_assert (expression && !LLE_NEXT (expression)
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&& LLE_DENOMINATOR (expression) == 1);
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/* The lower triangular portion of the base is going to be the
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coefficient times the step */
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for (j = 0; j < i; j++)
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base[i][j] = LLE_COEFFICIENTS (expression)[j]
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* LL_STEP (LN_LOOPS (nest)[j]);
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base[i][i] = step;
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for (j = i + 1; j < depth; j++)
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base[i][j] = 0;
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/* Origin for this loop is the constant of the lower bound
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expression. */
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LATTICE_ORIGIN (ret)[i] = LLE_CONSTANT (expression);
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/* Coefficient for the invariants are equal to the invariant
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coefficients in the expression. */
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for (j = 0; j < invariants; j++)
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LATTICE_ORIGIN_INVARIANTS (ret)[i][j] =
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LLE_INVARIANT_COEFFICIENTS (expression)[j];
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}
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}
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return ret;
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}
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/* Compute the least common multiple of two numbers A and B . */
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int
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least_common_multiple (int a, int b)
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{
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return (abs (a) * abs (b) / gcd (a, b));
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}
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/* Perform Fourier-Motzkin elimination to calculate the bounds of the
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auxiliary nest.
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Fourier-Motzkin is a way of reducing systems of linear inequalities so that
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it is easy to calculate the answer and bounds.
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A sketch of how it works:
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Given a system of linear inequalities, ai * xj >= bk, you can always
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rewrite the constraints so they are all of the form
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a <= x, or x <= b, or x >= constant for some x in x1 ... xj (and some b
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in b1 ... bk, and some a in a1...ai)
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You can then eliminate this x from the non-constant inequalities by
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rewriting these as a <= b, x >= constant, and delete the x variable.
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You can then repeat this for any remaining x variables, and then we have
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an easy to use variable <= constant (or no variables at all) form that we
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can construct our bounds from.
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In our case, each time we eliminate, we construct part of the bound from
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the ith variable, then delete the ith variable.
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Remember the constant are in our vector a, our coefficient matrix is A,
|
|
and our invariant coefficient matrix is B.
|
|
|
|
SIZE is the size of the matrices being passed.
|
|
DEPTH is the loop nest depth.
|
|
INVARIANTS is the number of loop invariants.
|
|
A, B, and a are the coefficient matrix, invariant coefficient, and a
|
|
vector of constants, respectively. */
|
|
|
|
static lambda_loopnest
|
|
compute_nest_using_fourier_motzkin (int size,
|
|
int depth,
|
|
int invariants,
|
|
lambda_matrix A,
|
|
lambda_matrix B,
|
|
lambda_vector a,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
|
|
int multiple, f1, f2;
|
|
int i, j, k;
|
|
lambda_linear_expression expression;
|
|
lambda_loop loop;
|
|
lambda_loopnest auxillary_nest;
|
|
lambda_matrix swapmatrix, A1, B1;
|
|
lambda_vector swapvector, a1;
|
|
int newsize;
|
|
|
|
A1 = lambda_matrix_new (128, depth, lambda_obstack);
|
|
B1 = lambda_matrix_new (128, invariants, lambda_obstack);
|
|
a1 = lambda_vector_new (128);
|
|
|
|
auxillary_nest = lambda_loopnest_new (depth, invariants, lambda_obstack);
|
|
|
|
for (i = depth - 1; i >= 0; i--)
|
|
{
|
|
loop = lambda_loop_new (lambda_obstack);
|
|
LN_LOOPS (auxillary_nest)[i] = loop;
|
|
LL_STEP (loop) = 1;
|
|
|
|
for (j = 0; j < size; j++)
|
|
{
|
|
if (A[j][i] < 0)
|
|
{
|
|
/* Any linear expression in the matrix with a coefficient less
|
|
than 0 becomes part of the new lower bound. */
|
|
expression = lambda_linear_expression_new (depth, invariants,
|
|
lambda_obstack);
|
|
|
|
for (k = 0; k < i; k++)
|
|
LLE_COEFFICIENTS (expression)[k] = A[j][k];
|
|
|
|
for (k = 0; k < invariants; k++)
|
|
LLE_INVARIANT_COEFFICIENTS (expression)[k] = -1 * B[j][k];
|
|
|
|
LLE_DENOMINATOR (expression) = -1 * A[j][i];
|
|
LLE_CONSTANT (expression) = -1 * a[j];
|
|
|
|
/* Ignore if identical to the existing lower bound. */
|
|
if (!lle_equal (LL_LOWER_BOUND (loop),
|
|
expression, depth, invariants))
|
|
{
|
|
LLE_NEXT (expression) = LL_LOWER_BOUND (loop);
|
|
LL_LOWER_BOUND (loop) = expression;
|
|
}
|
|
|
|
}
|
|
else if (A[j][i] > 0)
|
|
{
|
|
/* Any linear expression with a coefficient greater than 0
|
|
becomes part of the new upper bound. */
|
|
expression = lambda_linear_expression_new (depth, invariants,
|
|
lambda_obstack);
|
|
for (k = 0; k < i; k++)
|
|
LLE_COEFFICIENTS (expression)[k] = -1 * A[j][k];
|
|
|
|
for (k = 0; k < invariants; k++)
|
|
LLE_INVARIANT_COEFFICIENTS (expression)[k] = B[j][k];
|
|
|
|
LLE_DENOMINATOR (expression) = A[j][i];
|
|
LLE_CONSTANT (expression) = a[j];
|
|
|
|
/* Ignore if identical to the existing upper bound. */
|
|
if (!lle_equal (LL_UPPER_BOUND (loop),
|
|
expression, depth, invariants))
|
|
{
|
|
LLE_NEXT (expression) = LL_UPPER_BOUND (loop);
|
|
LL_UPPER_BOUND (loop) = expression;
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
/* This portion creates a new system of linear inequalities by deleting
|
|
the i'th variable, reducing the system by one variable. */
|
|
newsize = 0;
|
|
for (j = 0; j < size; j++)
|
|
{
|
|
/* If the coefficient for the i'th variable is 0, then we can just
|
|
eliminate the variable straightaway. Otherwise, we have to
|
|
multiply through by the coefficients we are eliminating. */
|
|
if (A[j][i] == 0)
|
|
{
|
|
lambda_vector_copy (A[j], A1[newsize], depth);
|
|
lambda_vector_copy (B[j], B1[newsize], invariants);
|
|
a1[newsize] = a[j];
|
|
newsize++;
|
|
}
|
|
else if (A[j][i] > 0)
|
|
{
|
|
for (k = 0; k < size; k++)
|
|
{
|
|
if (A[k][i] < 0)
|
|
{
|
|
multiple = least_common_multiple (A[j][i], A[k][i]);
|
|
f1 = multiple / A[j][i];
|
|
f2 = -1 * multiple / A[k][i];
|
|
|
|
lambda_vector_add_mc (A[j], f1, A[k], f2,
|
|
A1[newsize], depth);
|
|
lambda_vector_add_mc (B[j], f1, B[k], f2,
|
|
B1[newsize], invariants);
|
|
a1[newsize] = f1 * a[j] + f2 * a[k];
|
|
newsize++;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
swapmatrix = A;
|
|
A = A1;
|
|
A1 = swapmatrix;
|
|
|
|
swapmatrix = B;
|
|
B = B1;
|
|
B1 = swapmatrix;
|
|
|
|
swapvector = a;
|
|
a = a1;
|
|
a1 = swapvector;
|
|
|
|
size = newsize;
|
|
}
|
|
|
|
return auxillary_nest;
|
|
}
|
|
|
|
/* Compute the loop bounds for the auxiliary space NEST.
|
|
Input system used is Ax <= b. TRANS is the unimodular transformation.
|
|
Given the original nest, this function will
|
|
1. Convert the nest into matrix form, which consists of a matrix for the
|
|
coefficients, a matrix for the
|
|
invariant coefficients, and a vector for the constants.
|
|
2. Use the matrix form to calculate the lattice base for the nest (which is
|
|
a dense space)
|
|
3. Compose the dense space transform with the user specified transform, to
|
|
get a transform we can easily calculate transformed bounds for.
|
|
4. Multiply the composed transformation matrix times the matrix form of the
|
|
loop.
|
|
5. Transform the newly created matrix (from step 4) back into a loop nest
|
|
using Fourier-Motzkin elimination to figure out the bounds. */
|
|
|
|
static lambda_loopnest
|
|
lambda_compute_auxillary_space (lambda_loopnest nest,
|
|
lambda_trans_matrix trans,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
lambda_matrix A, B, A1, B1;
|
|
lambda_vector a, a1;
|
|
lambda_matrix invertedtrans;
|
|
int depth, invariants, size;
|
|
int i, j;
|
|
lambda_loop loop;
|
|
lambda_linear_expression expression;
|
|
lambda_lattice lattice;
|
|
|
|
depth = LN_DEPTH (nest);
|
|
invariants = LN_INVARIANTS (nest);
|
|
|
|
/* Unfortunately, we can't know the number of constraints we'll have
|
|
ahead of time, but this should be enough even in ridiculous loop nest
|
|
cases. We must not go over this limit. */
|
|
A = lambda_matrix_new (128, depth, lambda_obstack);
|
|
B = lambda_matrix_new (128, invariants, lambda_obstack);
|
|
a = lambda_vector_new (128);
|
|
|
|
A1 = lambda_matrix_new (128, depth, lambda_obstack);
|
|
B1 = lambda_matrix_new (128, invariants, lambda_obstack);
|
|
a1 = lambda_vector_new (128);
|
|
|
|
/* Store the bounds in the equation matrix A, constant vector a, and
|
|
invariant matrix B, so that we have Ax <= a + B.
|
|
This requires a little equation rearranging so that everything is on the
|
|
correct side of the inequality. */
|
|
size = 0;
|
|
for (i = 0; i < depth; i++)
|
|
{
|
|
loop = LN_LOOPS (nest)[i];
|
|
|
|
/* First we do the lower bound. */
|
|
if (LL_STEP (loop) > 0)
|
|
expression = LL_LOWER_BOUND (loop);
|
|
else
|
|
expression = LL_UPPER_BOUND (loop);
|
|
|
|
for (; expression != NULL; expression = LLE_NEXT (expression))
|
|
{
|
|
/* Fill in the coefficient. */
|
|
for (j = 0; j < i; j++)
|
|
A[size][j] = LLE_COEFFICIENTS (expression)[j];
|
|
|
|
/* And the invariant coefficient. */
|
|
for (j = 0; j < invariants; j++)
|
|
B[size][j] = LLE_INVARIANT_COEFFICIENTS (expression)[j];
|
|
|
|
/* And the constant. */
|
|
a[size] = LLE_CONSTANT (expression);
|
|
|
|
/* Convert (2x+3y+2+b)/4 <= z to 2x+3y-4z <= -2-b. IE put all
|
|
constants and single variables on */
|
|
A[size][i] = -1 * LLE_DENOMINATOR (expression);
|
|
a[size] *= -1;
|
|
for (j = 0; j < invariants; j++)
|
|
B[size][j] *= -1;
|
|
|
|
size++;
|
|
/* Need to increase matrix sizes above. */
|
|
gcc_assert (size <= 127);
|
|
|
|
}
|
|
|
|
/* Then do the exact same thing for the upper bounds. */
|
|
if (LL_STEP (loop) > 0)
|
|
expression = LL_UPPER_BOUND (loop);
|
|
else
|
|
expression = LL_LOWER_BOUND (loop);
|
|
|
|
for (; expression != NULL; expression = LLE_NEXT (expression))
|
|
{
|
|
/* Fill in the coefficient. */
|
|
for (j = 0; j < i; j++)
|
|
A[size][j] = LLE_COEFFICIENTS (expression)[j];
|
|
|
|
/* And the invariant coefficient. */
|
|
for (j = 0; j < invariants; j++)
|
|
B[size][j] = LLE_INVARIANT_COEFFICIENTS (expression)[j];
|
|
|
|
/* And the constant. */
|
|
a[size] = LLE_CONSTANT (expression);
|
|
|
|
/* Convert z <= (2x+3y+2+b)/4 to -2x-3y+4z <= 2+b. */
|
|
for (j = 0; j < i; j++)
|
|
A[size][j] *= -1;
|
|
A[size][i] = LLE_DENOMINATOR (expression);
|
|
size++;
|
|
/* Need to increase matrix sizes above. */
|
|
gcc_assert (size <= 127);
|
|
|
|
}
|
|
}
|
|
|
|
/* Compute the lattice base x = base * y + origin, where y is the
|
|
base space. */
|
|
lattice = lambda_lattice_compute_base (nest, lambda_obstack);
|
|
|
|
/* Ax <= a + B then becomes ALy <= a+B - A*origin. L is the lattice base */
|
|
|
|
/* A1 = A * L */
|
|
lambda_matrix_mult (A, LATTICE_BASE (lattice), A1, size, depth, depth);
|
|
|
|
/* a1 = a - A * origin constant. */
|
|
lambda_matrix_vector_mult (A, size, depth, LATTICE_ORIGIN (lattice), a1);
|
|
lambda_vector_add_mc (a, 1, a1, -1, a1, size);
|
|
|
|
/* B1 = B - A * origin invariant. */
|
|
lambda_matrix_mult (A, LATTICE_ORIGIN_INVARIANTS (lattice), B1, size, depth,
|
|
invariants);
|
|
lambda_matrix_add_mc (B, 1, B1, -1, B1, size, invariants);
|
|
|
|
/* Now compute the auxiliary space bounds by first inverting U, multiplying
|
|
it by A1, then performing Fourier-Motzkin. */
|
|
|
|
invertedtrans = lambda_matrix_new (depth, depth, lambda_obstack);
|
|
|
|
/* Compute the inverse of U. */
|
|
lambda_matrix_inverse (LTM_MATRIX (trans),
|
|
invertedtrans, depth, lambda_obstack);
|
|
|
|
/* A = A1 inv(U). */
|
|
lambda_matrix_mult (A1, invertedtrans, A, size, depth, depth);
|
|
|
|
return compute_nest_using_fourier_motzkin (size, depth, invariants,
|
|
A, B1, a1, lambda_obstack);
|
|
}
|
|
|
|
/* Compute the loop bounds for the target space, using the bounds of
|
|
the auxiliary nest AUXILLARY_NEST, and the triangular matrix H.
|
|
The target space loop bounds are computed by multiplying the triangular
|
|
matrix H by the auxiliary nest, to get the new loop bounds. The sign of
|
|
the loop steps (positive or negative) is then used to swap the bounds if
|
|
the loop counts downwards.
|
|
Return the target loopnest. */
|
|
|
|
static lambda_loopnest
|
|
lambda_compute_target_space (lambda_loopnest auxillary_nest,
|
|
lambda_trans_matrix H, lambda_vector stepsigns,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
lambda_matrix inverse, H1;
|
|
int determinant, i, j;
|
|
int gcd1, gcd2;
|
|
int factor;
|
|
|
|
lambda_loopnest target_nest;
|
|
int depth, invariants;
|
|
lambda_matrix target;
|
|
|
|
lambda_loop auxillary_loop, target_loop;
|
|
lambda_linear_expression expression, auxillary_expr, target_expr, tmp_expr;
|
|
|
|
depth = LN_DEPTH (auxillary_nest);
|
|
invariants = LN_INVARIANTS (auxillary_nest);
|
|
|
|
inverse = lambda_matrix_new (depth, depth, lambda_obstack);
|
|
determinant = lambda_matrix_inverse (LTM_MATRIX (H), inverse, depth,
|
|
lambda_obstack);
|
|
|
|
/* H1 is H excluding its diagonal. */
|
|
H1 = lambda_matrix_new (depth, depth, lambda_obstack);
|
|
lambda_matrix_copy (LTM_MATRIX (H), H1, depth, depth);
|
|
|
|
for (i = 0; i < depth; i++)
|
|
H1[i][i] = 0;
|
|
|
|
/* Computes the linear offsets of the loop bounds. */
|
|
target = lambda_matrix_new (depth, depth, lambda_obstack);
|
|
lambda_matrix_mult (H1, inverse, target, depth, depth, depth);
|
|
|
|
target_nest = lambda_loopnest_new (depth, invariants, lambda_obstack);
|
|
|
|
for (i = 0; i < depth; i++)
|
|
{
|
|
|
|
/* Get a new loop structure. */
|
|
target_loop = lambda_loop_new (lambda_obstack);
|
|
LN_LOOPS (target_nest)[i] = target_loop;
|
|
|
|
/* Computes the gcd of the coefficients of the linear part. */
|
|
gcd1 = lambda_vector_gcd (target[i], i);
|
|
|
|
/* Include the denominator in the GCD. */
|
|
gcd1 = gcd (gcd1, determinant);
|
|
|
|
/* Now divide through by the gcd. */
|
|
for (j = 0; j < i; j++)
|
|
target[i][j] = target[i][j] / gcd1;
|
|
|
|
expression = lambda_linear_expression_new (depth, invariants,
|
|
lambda_obstack);
|
|
lambda_vector_copy (target[i], LLE_COEFFICIENTS (expression), depth);
|
|
LLE_DENOMINATOR (expression) = determinant / gcd1;
|
|
LLE_CONSTANT (expression) = 0;
|
|
lambda_vector_clear (LLE_INVARIANT_COEFFICIENTS (expression),
|
|
invariants);
|
|
LL_LINEAR_OFFSET (target_loop) = expression;
|
|
}
|
|
|
|
/* For each loop, compute the new bounds from H. */
|
|
for (i = 0; i < depth; i++)
|
|
{
|
|
auxillary_loop = LN_LOOPS (auxillary_nest)[i];
|
|
target_loop = LN_LOOPS (target_nest)[i];
|
|
LL_STEP (target_loop) = LTM_MATRIX (H)[i][i];
|
|
factor = LTM_MATRIX (H)[i][i];
|
|
|
|
/* First we do the lower bound. */
|
|
auxillary_expr = LL_LOWER_BOUND (auxillary_loop);
|
|
|
|
for (; auxillary_expr != NULL;
|
|
auxillary_expr = LLE_NEXT (auxillary_expr))
|
|
{
|
|
target_expr = lambda_linear_expression_new (depth, invariants,
|
|
lambda_obstack);
|
|
lambda_vector_matrix_mult (LLE_COEFFICIENTS (auxillary_expr),
|
|
depth, inverse, depth,
|
|
LLE_COEFFICIENTS (target_expr));
|
|
lambda_vector_mult_const (LLE_COEFFICIENTS (target_expr),
|
|
LLE_COEFFICIENTS (target_expr), depth,
|
|
factor);
|
|
|
|
LLE_CONSTANT (target_expr) = LLE_CONSTANT (auxillary_expr) * factor;
|
|
lambda_vector_copy (LLE_INVARIANT_COEFFICIENTS (auxillary_expr),
|
|
LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
invariants);
|
|
lambda_vector_mult_const (LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
invariants, factor);
|
|
LLE_DENOMINATOR (target_expr) = LLE_DENOMINATOR (auxillary_expr);
|
|
|
|
if (!lambda_vector_zerop (LLE_COEFFICIENTS (target_expr), depth))
|
|
{
|
|
LLE_CONSTANT (target_expr) = LLE_CONSTANT (target_expr)
|
|
* determinant;
|
|
lambda_vector_mult_const (LLE_INVARIANT_COEFFICIENTS
|
|
(target_expr),
|
|
LLE_INVARIANT_COEFFICIENTS
|
|
(target_expr), invariants,
|
|
determinant);
|
|
LLE_DENOMINATOR (target_expr) =
|
|
LLE_DENOMINATOR (target_expr) * determinant;
|
|
}
|
|
/* Find the gcd and divide by it here, rather than doing it
|
|
at the tree level. */
|
|
gcd1 = lambda_vector_gcd (LLE_COEFFICIENTS (target_expr), depth);
|
|
gcd2 = lambda_vector_gcd (LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
invariants);
|
|
gcd1 = gcd (gcd1, gcd2);
|
|
gcd1 = gcd (gcd1, LLE_CONSTANT (target_expr));
|
|
gcd1 = gcd (gcd1, LLE_DENOMINATOR (target_expr));
|
|
for (j = 0; j < depth; j++)
|
|
LLE_COEFFICIENTS (target_expr)[j] /= gcd1;
|
|
for (j = 0; j < invariants; j++)
|
|
LLE_INVARIANT_COEFFICIENTS (target_expr)[j] /= gcd1;
|
|
LLE_CONSTANT (target_expr) /= gcd1;
|
|
LLE_DENOMINATOR (target_expr) /= gcd1;
|
|
/* Ignore if identical to existing bound. */
|
|
if (!lle_equal (LL_LOWER_BOUND (target_loop), target_expr, depth,
|
|
invariants))
|
|
{
|
|
LLE_NEXT (target_expr) = LL_LOWER_BOUND (target_loop);
|
|
LL_LOWER_BOUND (target_loop) = target_expr;
|
|
}
|
|
}
|
|
/* Now do the upper bound. */
|
|
auxillary_expr = LL_UPPER_BOUND (auxillary_loop);
|
|
|
|
for (; auxillary_expr != NULL;
|
|
auxillary_expr = LLE_NEXT (auxillary_expr))
|
|
{
|
|
target_expr = lambda_linear_expression_new (depth, invariants,
|
|
lambda_obstack);
|
|
lambda_vector_matrix_mult (LLE_COEFFICIENTS (auxillary_expr),
|
|
depth, inverse, depth,
|
|
LLE_COEFFICIENTS (target_expr));
|
|
lambda_vector_mult_const (LLE_COEFFICIENTS (target_expr),
|
|
LLE_COEFFICIENTS (target_expr), depth,
|
|
factor);
|
|
LLE_CONSTANT (target_expr) = LLE_CONSTANT (auxillary_expr) * factor;
|
|
lambda_vector_copy (LLE_INVARIANT_COEFFICIENTS (auxillary_expr),
|
|
LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
invariants);
|
|
lambda_vector_mult_const (LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
invariants, factor);
|
|
LLE_DENOMINATOR (target_expr) = LLE_DENOMINATOR (auxillary_expr);
|
|
|
|
if (!lambda_vector_zerop (LLE_COEFFICIENTS (target_expr), depth))
|
|
{
|
|
LLE_CONSTANT (target_expr) = LLE_CONSTANT (target_expr)
|
|
* determinant;
|
|
lambda_vector_mult_const (LLE_INVARIANT_COEFFICIENTS
|
|
(target_expr),
|
|
LLE_INVARIANT_COEFFICIENTS
|
|
(target_expr), invariants,
|
|
determinant);
|
|
LLE_DENOMINATOR (target_expr) =
|
|
LLE_DENOMINATOR (target_expr) * determinant;
|
|
}
|
|
/* Find the gcd and divide by it here, instead of at the
|
|
tree level. */
|
|
gcd1 = lambda_vector_gcd (LLE_COEFFICIENTS (target_expr), depth);
|
|
gcd2 = lambda_vector_gcd (LLE_INVARIANT_COEFFICIENTS (target_expr),
|
|
invariants);
|
|
gcd1 = gcd (gcd1, gcd2);
|
|
gcd1 = gcd (gcd1, LLE_CONSTANT (target_expr));
|
|
gcd1 = gcd (gcd1, LLE_DENOMINATOR (target_expr));
|
|
for (j = 0; j < depth; j++)
|
|
LLE_COEFFICIENTS (target_expr)[j] /= gcd1;
|
|
for (j = 0; j < invariants; j++)
|
|
LLE_INVARIANT_COEFFICIENTS (target_expr)[j] /= gcd1;
|
|
LLE_CONSTANT (target_expr) /= gcd1;
|
|
LLE_DENOMINATOR (target_expr) /= gcd1;
|
|
/* Ignore if equal to existing bound. */
|
|
if (!lle_equal (LL_UPPER_BOUND (target_loop), target_expr, depth,
|
|
invariants))
|
|
{
|
|
LLE_NEXT (target_expr) = LL_UPPER_BOUND (target_loop);
|
|
LL_UPPER_BOUND (target_loop) = target_expr;
|
|
}
|
|
}
|
|
}
|
|
for (i = 0; i < depth; i++)
|
|
{
|
|
target_loop = LN_LOOPS (target_nest)[i];
|
|
/* If necessary, exchange the upper and lower bounds and negate
|
|
the step size. */
|
|
if (stepsigns[i] < 0)
|
|
{
|
|
LL_STEP (target_loop) *= -1;
|
|
tmp_expr = LL_LOWER_BOUND (target_loop);
|
|
LL_LOWER_BOUND (target_loop) = LL_UPPER_BOUND (target_loop);
|
|
LL_UPPER_BOUND (target_loop) = tmp_expr;
|
|
}
|
|
}
|
|
return target_nest;
|
|
}
|
|
|
|
/* Compute the step signs of TRANS, using TRANS and stepsigns. Return the new
|
|
result. */
|
|
|
|
static lambda_vector
|
|
lambda_compute_step_signs (lambda_trans_matrix trans,
|
|
lambda_vector stepsigns,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
lambda_matrix matrix, H;
|
|
int size;
|
|
lambda_vector newsteps;
|
|
int i, j, factor, minimum_column;
|
|
int temp;
|
|
|
|
matrix = LTM_MATRIX (trans);
|
|
size = LTM_ROWSIZE (trans);
|
|
H = lambda_matrix_new (size, size, lambda_obstack);
|
|
|
|
newsteps = lambda_vector_new (size);
|
|
lambda_vector_copy (stepsigns, newsteps, size);
|
|
|
|
lambda_matrix_copy (matrix, H, size, size);
|
|
|
|
for (j = 0; j < size; j++)
|
|
{
|
|
lambda_vector row;
|
|
row = H[j];
|
|
for (i = j; i < size; i++)
|
|
if (row[i] < 0)
|
|
lambda_matrix_col_negate (H, size, i);
|
|
while (lambda_vector_first_nz (row, size, j + 1) < size)
|
|
{
|
|
minimum_column = lambda_vector_min_nz (row, size, j);
|
|
lambda_matrix_col_exchange (H, size, j, minimum_column);
|
|
|
|
temp = newsteps[j];
|
|
newsteps[j] = newsteps[minimum_column];
|
|
newsteps[minimum_column] = temp;
|
|
|
|
for (i = j + 1; i < size; i++)
|
|
{
|
|
factor = row[i] / row[j];
|
|
lambda_matrix_col_add (H, size, j, i, -1 * factor);
|
|
}
|
|
}
|
|
}
|
|
return newsteps;
|
|
}
|
|
|
|
/* Transform NEST according to TRANS, and return the new loopnest.
|
|
This involves
|
|
1. Computing a lattice base for the transformation
|
|
2. Composing the dense base with the specified transformation (TRANS)
|
|
3. Decomposing the combined transformation into a lower triangular portion,
|
|
and a unimodular portion.
|
|
4. Computing the auxiliary nest using the unimodular portion.
|
|
5. Computing the target nest using the auxiliary nest and the lower
|
|
triangular portion. */
|
|
|
|
lambda_loopnest
|
|
lambda_loopnest_transform (lambda_loopnest nest, lambda_trans_matrix trans,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
lambda_loopnest auxillary_nest, target_nest;
|
|
|
|
int depth, invariants;
|
|
int i, j;
|
|
lambda_lattice lattice;
|
|
lambda_trans_matrix trans1, H, U;
|
|
lambda_loop loop;
|
|
lambda_linear_expression expression;
|
|
lambda_vector origin;
|
|
lambda_matrix origin_invariants;
|
|
lambda_vector stepsigns;
|
|
int f;
|
|
|
|
depth = LN_DEPTH (nest);
|
|
invariants = LN_INVARIANTS (nest);
|
|
|
|
/* Keep track of the signs of the loop steps. */
|
|
stepsigns = lambda_vector_new (depth);
|
|
for (i = 0; i < depth; i++)
|
|
{
|
|
if (LL_STEP (LN_LOOPS (nest)[i]) > 0)
|
|
stepsigns[i] = 1;
|
|
else
|
|
stepsigns[i] = -1;
|
|
}
|
|
|
|
/* Compute the lattice base. */
|
|
lattice = lambda_lattice_compute_base (nest, lambda_obstack);
|
|
trans1 = lambda_trans_matrix_new (depth, depth, lambda_obstack);
|
|
|
|
/* Multiply the transformation matrix by the lattice base. */
|
|
|
|
lambda_matrix_mult (LTM_MATRIX (trans), LATTICE_BASE (lattice),
|
|
LTM_MATRIX (trans1), depth, depth, depth);
|
|
|
|
/* Compute the Hermite normal form for the new transformation matrix. */
|
|
H = lambda_trans_matrix_new (depth, depth, lambda_obstack);
|
|
U = lambda_trans_matrix_new (depth, depth, lambda_obstack);
|
|
lambda_matrix_hermite (LTM_MATRIX (trans1), depth, LTM_MATRIX (H),
|
|
LTM_MATRIX (U));
|
|
|
|
/* Compute the auxiliary loop nest's space from the unimodular
|
|
portion. */
|
|
auxillary_nest = lambda_compute_auxillary_space (nest, U,
|
|
lambda_obstack);
|
|
|
|
/* Compute the loop step signs from the old step signs and the
|
|
transformation matrix. */
|
|
stepsigns = lambda_compute_step_signs (trans1, stepsigns,
|
|
lambda_obstack);
|
|
|
|
/* Compute the target loop nest space from the auxiliary nest and
|
|
the lower triangular matrix H. */
|
|
target_nest = lambda_compute_target_space (auxillary_nest, H, stepsigns,
|
|
lambda_obstack);
|
|
origin = lambda_vector_new (depth);
|
|
origin_invariants = lambda_matrix_new (depth, invariants, lambda_obstack);
|
|
lambda_matrix_vector_mult (LTM_MATRIX (trans), depth, depth,
|
|
LATTICE_ORIGIN (lattice), origin);
|
|
lambda_matrix_mult (LTM_MATRIX (trans), LATTICE_ORIGIN_INVARIANTS (lattice),
|
|
origin_invariants, depth, depth, invariants);
|
|
|
|
for (i = 0; i < depth; i++)
|
|
{
|
|
loop = LN_LOOPS (target_nest)[i];
|
|
expression = LL_LINEAR_OFFSET (loop);
|
|
if (lambda_vector_zerop (LLE_COEFFICIENTS (expression), depth))
|
|
f = 1;
|
|
else
|
|
f = LLE_DENOMINATOR (expression);
|
|
|
|
LLE_CONSTANT (expression) += f * origin[i];
|
|
|
|
for (j = 0; j < invariants; j++)
|
|
LLE_INVARIANT_COEFFICIENTS (expression)[j] +=
|
|
f * origin_invariants[i][j];
|
|
}
|
|
|
|
return target_nest;
|
|
|
|
}
|
|
|
|
/* Convert a gcc tree expression EXPR to a lambda linear expression, and
|
|
return the new expression. DEPTH is the depth of the loopnest.
|
|
OUTERINDUCTIONVARS is an array of the induction variables for outer loops
|
|
in this nest. INVARIANTS is the array of invariants for the loop. EXTRA
|
|
is the amount we have to add/subtract from the expression because of the
|
|
type of comparison it is used in. */
|
|
|
|
static lambda_linear_expression
|
|
gcc_tree_to_linear_expression (int depth, tree expr,
|
|
VEC(tree,heap) *outerinductionvars,
|
|
VEC(tree,heap) *invariants, int extra,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
lambda_linear_expression lle = NULL;
|
|
switch (TREE_CODE (expr))
|
|
{
|
|
case INTEGER_CST:
|
|
{
|
|
lle = lambda_linear_expression_new (depth, 2 * depth, lambda_obstack);
|
|
LLE_CONSTANT (lle) = TREE_INT_CST_LOW (expr);
|
|
if (extra != 0)
|
|
LLE_CONSTANT (lle) += extra;
|
|
|
|
LLE_DENOMINATOR (lle) = 1;
|
|
}
|
|
break;
|
|
case SSA_NAME:
|
|
{
|
|
tree iv, invar;
|
|
size_t i;
|
|
for (i = 0; VEC_iterate (tree, outerinductionvars, i, iv); i++)
|
|
if (iv != NULL)
|
|
{
|
|
if (SSA_NAME_VAR (iv) == SSA_NAME_VAR (expr))
|
|
{
|
|
lle = lambda_linear_expression_new (depth, 2 * depth,
|
|
lambda_obstack);
|
|
LLE_COEFFICIENTS (lle)[i] = 1;
|
|
if (extra != 0)
|
|
LLE_CONSTANT (lle) = extra;
|
|
|
|
LLE_DENOMINATOR (lle) = 1;
|
|
}
|
|
}
|
|
for (i = 0; VEC_iterate (tree, invariants, i, invar); i++)
|
|
if (invar != NULL)
|
|
{
|
|
if (SSA_NAME_VAR (invar) == SSA_NAME_VAR (expr))
|
|
{
|
|
lle = lambda_linear_expression_new (depth, 2 * depth,
|
|
lambda_obstack);
|
|
LLE_INVARIANT_COEFFICIENTS (lle)[i] = 1;
|
|
if (extra != 0)
|
|
LLE_CONSTANT (lle) = extra;
|
|
LLE_DENOMINATOR (lle) = 1;
|
|
}
|
|
}
|
|
}
|
|
break;
|
|
default:
|
|
return NULL;
|
|
}
|
|
|
|
return lle;
|
|
}
|
|
|
|
/* Return the depth of the loopnest NEST */
|
|
|
|
static int
|
|
depth_of_nest (struct loop *nest)
|
|
{
|
|
size_t depth = 0;
|
|
while (nest)
|
|
{
|
|
depth++;
|
|
nest = nest->inner;
|
|
}
|
|
return depth;
|
|
}
|
|
|
|
|
|
/* Return true if OP is invariant in LOOP and all outer loops. */
|
|
|
|
static bool
|
|
invariant_in_loop_and_outer_loops (struct loop *loop, tree op)
|
|
{
|
|
if (is_gimple_min_invariant (op))
|
|
return true;
|
|
if (loop_depth (loop) == 0)
|
|
return true;
|
|
if (!expr_invariant_in_loop_p (loop, op))
|
|
return false;
|
|
if (!invariant_in_loop_and_outer_loops (loop_outer (loop), op))
|
|
return false;
|
|
return true;
|
|
}
|
|
|
|
/* Generate a lambda loop from a gcc loop LOOP. Return the new lambda loop,
|
|
or NULL if it could not be converted.
|
|
DEPTH is the depth of the loop.
|
|
INVARIANTS is a pointer to the array of loop invariants.
|
|
The induction variable for this loop should be stored in the parameter
|
|
OURINDUCTIONVAR.
|
|
OUTERINDUCTIONVARS is an array of induction variables for outer loops. */
|
|
|
|
static lambda_loop
|
|
gcc_loop_to_lambda_loop (struct loop *loop, int depth,
|
|
VEC(tree,heap) ** invariants,
|
|
tree * ourinductionvar,
|
|
VEC(tree,heap) * outerinductionvars,
|
|
VEC(tree,heap) ** lboundvars,
|
|
VEC(tree,heap) ** uboundvars,
|
|
VEC(int,heap) ** steps,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
gimple phi;
|
|
gimple exit_cond;
|
|
tree access_fn, inductionvar;
|
|
tree step;
|
|
lambda_loop lloop = NULL;
|
|
lambda_linear_expression lbound, ubound;
|
|
tree test_lhs, test_rhs;
|
|
int stepint;
|
|
int extra = 0;
|
|
tree lboundvar, uboundvar, uboundresult;
|
|
|
|
/* Find out induction var and exit condition. */
|
|
inductionvar = find_induction_var_from_exit_cond (loop);
|
|
exit_cond = get_loop_exit_condition (loop);
|
|
|
|
if (inductionvar == NULL || exit_cond == NULL)
|
|
{
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot determine exit condition or induction variable for loop.\n");
|
|
return NULL;
|
|
}
|
|
|
|
if (SSA_NAME_DEF_STMT (inductionvar) == NULL)
|
|
{
|
|
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot find PHI node for induction variable\n");
|
|
|
|
return NULL;
|
|
}
|
|
|
|
phi = SSA_NAME_DEF_STMT (inductionvar);
|
|
if (gimple_code (phi) != GIMPLE_PHI)
|
|
{
|
|
tree op = SINGLE_SSA_TREE_OPERAND (phi, SSA_OP_USE);
|
|
if (!op)
|
|
{
|
|
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot find PHI node for induction variable\n");
|
|
|
|
return NULL;
|
|
}
|
|
|
|
phi = SSA_NAME_DEF_STMT (op);
|
|
if (gimple_code (phi) != GIMPLE_PHI)
|
|
{
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot find PHI node for induction variable\n");
|
|
return NULL;
|
|
}
|
|
}
|
|
|
|
/* The induction variable name/version we want to put in the array is the
|
|
result of the induction variable phi node. */
|
|
*ourinductionvar = PHI_RESULT (phi);
|
|
access_fn = instantiate_parameters
|
|
(loop, analyze_scalar_evolution (loop, PHI_RESULT (phi)));
|
|
if (access_fn == chrec_dont_know)
|
|
{
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Access function for induction variable phi is unknown\n");
|
|
|
|
return NULL;
|
|
}
|
|
|
|
step = evolution_part_in_loop_num (access_fn, loop->num);
|
|
if (!step || step == chrec_dont_know)
|
|
{
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot determine step of loop.\n");
|
|
|
|
return NULL;
|
|
}
|
|
if (TREE_CODE (step) != INTEGER_CST)
|
|
{
|
|
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Step of loop is not integer.\n");
|
|
return NULL;
|
|
}
|
|
|
|
stepint = TREE_INT_CST_LOW (step);
|
|
|
|
/* Only want phis for induction vars, which will have two
|
|
arguments. */
|
|
if (gimple_phi_num_args (phi) != 2)
|
|
{
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: PHI node for induction variable has >2 arguments\n");
|
|
return NULL;
|
|
}
|
|
|
|
/* Another induction variable check. One argument's source should be
|
|
in the loop, one outside the loop. */
|
|
if (flow_bb_inside_loop_p (loop, gimple_phi_arg_edge (phi, 0)->src)
|
|
&& flow_bb_inside_loop_p (loop, gimple_phi_arg_edge (phi, 1)->src))
|
|
{
|
|
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: PHI edges both inside loop, or both outside loop.\n");
|
|
|
|
return NULL;
|
|
}
|
|
|
|
if (flow_bb_inside_loop_p (loop, gimple_phi_arg_edge (phi, 0)->src))
|
|
{
|
|
lboundvar = PHI_ARG_DEF (phi, 1);
|
|
lbound = gcc_tree_to_linear_expression (depth, lboundvar,
|
|
outerinductionvars, *invariants,
|
|
0, lambda_obstack);
|
|
}
|
|
else
|
|
{
|
|
lboundvar = PHI_ARG_DEF (phi, 0);
|
|
lbound = gcc_tree_to_linear_expression (depth, lboundvar,
|
|
outerinductionvars, *invariants,
|
|
0, lambda_obstack);
|
|
}
|
|
|
|
if (!lbound)
|
|
{
|
|
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot convert lower bound to linear expression\n");
|
|
|
|
return NULL;
|
|
}
|
|
/* One part of the test may be a loop invariant tree. */
|
|
VEC_reserve (tree, heap, *invariants, 1);
|
|
test_lhs = gimple_cond_lhs (exit_cond);
|
|
test_rhs = gimple_cond_rhs (exit_cond);
|
|
|
|
if (TREE_CODE (test_rhs) == SSA_NAME
|
|
&& invariant_in_loop_and_outer_loops (loop, test_rhs))
|
|
VEC_quick_push (tree, *invariants, test_rhs);
|
|
else if (TREE_CODE (test_lhs) == SSA_NAME
|
|
&& invariant_in_loop_and_outer_loops (loop, test_lhs))
|
|
VEC_quick_push (tree, *invariants, test_lhs);
|
|
|
|
/* The non-induction variable part of the test is the upper bound variable.
|
|
*/
|
|
if (test_lhs == inductionvar)
|
|
uboundvar = test_rhs;
|
|
else
|
|
uboundvar = test_lhs;
|
|
|
|
/* We only size the vectors assuming we have, at max, 2 times as many
|
|
invariants as we do loops (one for each bound).
|
|
This is just an arbitrary number, but it has to be matched against the
|
|
code below. */
|
|
gcc_assert (VEC_length (tree, *invariants) <= (unsigned int) (2 * depth));
|
|
|
|
|
|
/* We might have some leftover. */
|
|
if (gimple_cond_code (exit_cond) == LT_EXPR)
|
|
extra = -1 * stepint;
|
|
else if (gimple_cond_code (exit_cond) == NE_EXPR)
|
|
extra = -1 * stepint;
|
|
else if (gimple_cond_code (exit_cond) == GT_EXPR)
|
|
extra = -1 * stepint;
|
|
else if (gimple_cond_code (exit_cond) == EQ_EXPR)
|
|
extra = 1 * stepint;
|
|
|
|
ubound = gcc_tree_to_linear_expression (depth, uboundvar,
|
|
outerinductionvars,
|
|
*invariants, extra, lambda_obstack);
|
|
uboundresult = build2 (PLUS_EXPR, TREE_TYPE (uboundvar), uboundvar,
|
|
build_int_cst (TREE_TYPE (uboundvar), extra));
|
|
VEC_safe_push (tree, heap, *uboundvars, uboundresult);
|
|
VEC_safe_push (tree, heap, *lboundvars, lboundvar);
|
|
VEC_safe_push (int, heap, *steps, stepint);
|
|
if (!ubound)
|
|
{
|
|
if (dump_file && (dump_flags & TDF_DETAILS))
|
|
fprintf (dump_file,
|
|
"Unable to convert loop: Cannot convert upper bound to linear expression\n");
|
|
return NULL;
|
|
}
|
|
|
|
lloop = lambda_loop_new (lambda_obstack);
|
|
LL_STEP (lloop) = stepint;
|
|
LL_LOWER_BOUND (lloop) = lbound;
|
|
LL_UPPER_BOUND (lloop) = ubound;
|
|
return lloop;
|
|
}
|
|
|
|
/* Given a LOOP, find the induction variable it is testing against in the exit
|
|
condition. Return the induction variable if found, NULL otherwise. */
|
|
|
|
tree
|
|
find_induction_var_from_exit_cond (struct loop *loop)
|
|
{
|
|
gimple expr = get_loop_exit_condition (loop);
|
|
tree ivarop;
|
|
tree test_lhs, test_rhs;
|
|
if (expr == NULL)
|
|
return NULL_TREE;
|
|
if (gimple_code (expr) != GIMPLE_COND)
|
|
return NULL_TREE;
|
|
test_lhs = gimple_cond_lhs (expr);
|
|
test_rhs = gimple_cond_rhs (expr);
|
|
|
|
/* Find the side that is invariant in this loop. The ivar must be the other
|
|
side. */
|
|
|
|
if (expr_invariant_in_loop_p (loop, test_lhs))
|
|
ivarop = test_rhs;
|
|
else if (expr_invariant_in_loop_p (loop, test_rhs))
|
|
ivarop = test_lhs;
|
|
else
|
|
return NULL_TREE;
|
|
|
|
if (TREE_CODE (ivarop) != SSA_NAME)
|
|
return NULL_TREE;
|
|
return ivarop;
|
|
}
|
|
|
|
DEF_VEC_P(lambda_loop);
|
|
DEF_VEC_ALLOC_P(lambda_loop,heap);
|
|
|
|
/* Generate a lambda loopnest from a gcc loopnest LOOP_NEST.
|
|
Return the new loop nest.
|
|
INDUCTIONVARS is a pointer to an array of induction variables for the
|
|
loopnest that will be filled in during this process.
|
|
INVARIANTS is a pointer to an array of invariants that will be filled in
|
|
during this process. */
|
|
|
|
lambda_loopnest
|
|
gcc_loopnest_to_lambda_loopnest (struct loop *loop_nest,
|
|
VEC(tree,heap) **inductionvars,
|
|
VEC(tree,heap) **invariants,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
lambda_loopnest ret = NULL;
|
|
struct loop *temp = loop_nest;
|
|
int depth = depth_of_nest (loop_nest);
|
|
size_t i;
|
|
VEC(lambda_loop,heap) *loops = NULL;
|
|
VEC(tree,heap) *uboundvars = NULL;
|
|
VEC(tree,heap) *lboundvars = NULL;
|
|
VEC(int,heap) *steps = NULL;
|
|
lambda_loop newloop;
|
|
tree inductionvar = NULL;
|
|
bool perfect_nest = perfect_nest_p (loop_nest);
|
|
|
|
if (!perfect_nest && !can_convert_to_perfect_nest (loop_nest))
|
|
goto fail;
|
|
|
|
while (temp)
|
|
{
|
|
newloop = gcc_loop_to_lambda_loop (temp, depth, invariants,
|
|
&inductionvar, *inductionvars,
|
|
&lboundvars, &uboundvars,
|
|
&steps, lambda_obstack);
|
|
if (!newloop)
|
|
goto fail;
|
|
|
|
VEC_safe_push (tree, heap, *inductionvars, inductionvar);
|
|
VEC_safe_push (lambda_loop, heap, loops, newloop);
|
|
temp = temp->inner;
|
|
}
|
|
|
|
if (!perfect_nest)
|
|
{
|
|
if (!perfect_nestify (loop_nest, lboundvars, uboundvars, steps,
|
|
*inductionvars))
|
|
{
|
|
if (dump_file)
|
|
fprintf (dump_file,
|
|
"Not a perfect loop nest and couldn't convert to one.\n");
|
|
goto fail;
|
|
}
|
|
else if (dump_file)
|
|
fprintf (dump_file,
|
|
"Successfully converted loop nest to perfect loop nest.\n");
|
|
}
|
|
|
|
ret = lambda_loopnest_new (depth, 2 * depth, lambda_obstack);
|
|
|
|
for (i = 0; VEC_iterate (lambda_loop, loops, i, newloop); i++)
|
|
LN_LOOPS (ret)[i] = newloop;
|
|
|
|
fail:
|
|
VEC_free (lambda_loop, heap, loops);
|
|
VEC_free (tree, heap, uboundvars);
|
|
VEC_free (tree, heap, lboundvars);
|
|
VEC_free (int, heap, steps);
|
|
|
|
return ret;
|
|
}
|
|
|
|
/* Convert a lambda body vector LBV to a gcc tree, and return the new tree.
|
|
STMTS_TO_INSERT is a pointer to a tree where the statements we need to be
|
|
inserted for us are stored. INDUCTION_VARS is the array of induction
|
|
variables for the loop this LBV is from. TYPE is the tree type to use for
|
|
the variables and trees involved. */
|
|
|
|
static tree
|
|
lbv_to_gcc_expression (lambda_body_vector lbv,
|
|
tree type, VEC(tree,heap) *induction_vars,
|
|
gimple_seq *stmts_to_insert)
|
|
{
|
|
int k;
|
|
tree resvar;
|
|
tree expr = build_linear_expr (type, LBV_COEFFICIENTS (lbv), induction_vars);
|
|
|
|
k = LBV_DENOMINATOR (lbv);
|
|
gcc_assert (k != 0);
|
|
if (k != 1)
|
|
expr = fold_build2 (CEIL_DIV_EXPR, type, expr, build_int_cst (type, k));
|
|
|
|
resvar = create_tmp_var (type, "lbvtmp");
|
|
add_referenced_var (resvar);
|
|
return force_gimple_operand (fold (expr), stmts_to_insert, true, resvar);
|
|
}
|
|
|
|
/* Convert a linear expression from coefficient and constant form to a
|
|
gcc tree.
|
|
Return the tree that represents the final value of the expression.
|
|
LLE is the linear expression to convert.
|
|
OFFSET is the linear offset to apply to the expression.
|
|
TYPE is the tree type to use for the variables and math.
|
|
INDUCTION_VARS is a vector of induction variables for the loops.
|
|
INVARIANTS is a vector of the loop nest invariants.
|
|
WRAP specifies what tree code to wrap the results in, if there is more than
|
|
one (it is either MAX_EXPR, or MIN_EXPR).
|
|
STMTS_TO_INSERT Is a pointer to the statement list we fill in with
|
|
statements that need to be inserted for the linear expression. */
|
|
|
|
static tree
|
|
lle_to_gcc_expression (lambda_linear_expression lle,
|
|
lambda_linear_expression offset,
|
|
tree type,
|
|
VEC(tree,heap) *induction_vars,
|
|
VEC(tree,heap) *invariants,
|
|
enum tree_code wrap, gimple_seq *stmts_to_insert)
|
|
{
|
|
int k;
|
|
tree resvar;
|
|
tree expr = NULL_TREE;
|
|
VEC(tree,heap) *results = NULL;
|
|
|
|
gcc_assert (wrap == MAX_EXPR || wrap == MIN_EXPR);
|
|
|
|
/* Build up the linear expressions. */
|
|
for (; lle != NULL; lle = LLE_NEXT (lle))
|
|
{
|
|
expr = build_linear_expr (type, LLE_COEFFICIENTS (lle), induction_vars);
|
|
expr = fold_build2 (PLUS_EXPR, type, expr,
|
|
build_linear_expr (type,
|
|
LLE_INVARIANT_COEFFICIENTS (lle),
|
|
invariants));
|
|
|
|
k = LLE_CONSTANT (lle);
|
|
if (k)
|
|
expr = fold_build2 (PLUS_EXPR, type, expr, build_int_cst (type, k));
|
|
|
|
k = LLE_CONSTANT (offset);
|
|
if (k)
|
|
expr = fold_build2 (PLUS_EXPR, type, expr, build_int_cst (type, k));
|
|
|
|
k = LLE_DENOMINATOR (lle);
|
|
if (k != 1)
|
|
expr = fold_build2 (wrap == MAX_EXPR ? CEIL_DIV_EXPR : FLOOR_DIV_EXPR,
|
|
type, expr, build_int_cst (type, k));
|
|
|
|
expr = fold (expr);
|
|
VEC_safe_push (tree, heap, results, expr);
|
|
}
|
|
|
|
gcc_assert (expr);
|
|
|
|
/* We may need to wrap the results in a MAX_EXPR or MIN_EXPR. */
|
|
if (VEC_length (tree, results) > 1)
|
|
{
|
|
size_t i;
|
|
tree op;
|
|
|
|
expr = VEC_index (tree, results, 0);
|
|
for (i = 1; VEC_iterate (tree, results, i, op); i++)
|
|
expr = fold_build2 (wrap, type, expr, op);
|
|
}
|
|
|
|
VEC_free (tree, heap, results);
|
|
|
|
resvar = create_tmp_var (type, "lletmp");
|
|
add_referenced_var (resvar);
|
|
return force_gimple_operand (fold (expr), stmts_to_insert, true, resvar);
|
|
}
|
|
|
|
/* Remove the induction variable defined at IV_STMT. */
|
|
|
|
void
|
|
remove_iv (gimple iv_stmt)
|
|
{
|
|
gimple_stmt_iterator si = gsi_for_stmt (iv_stmt);
|
|
|
|
if (gimple_code (iv_stmt) == GIMPLE_PHI)
|
|
{
|
|
unsigned i;
|
|
|
|
for (i = 0; i < gimple_phi_num_args (iv_stmt); i++)
|
|
{
|
|
gimple stmt;
|
|
imm_use_iterator imm_iter;
|
|
tree arg = gimple_phi_arg_def (iv_stmt, i);
|
|
bool used = false;
|
|
|
|
if (TREE_CODE (arg) != SSA_NAME)
|
|
continue;
|
|
|
|
FOR_EACH_IMM_USE_STMT (stmt, imm_iter, arg)
|
|
if (stmt != iv_stmt && !is_gimple_debug (stmt))
|
|
used = true;
|
|
|
|
if (!used)
|
|
remove_iv (SSA_NAME_DEF_STMT (arg));
|
|
}
|
|
|
|
remove_phi_node (&si, true);
|
|
}
|
|
else
|
|
{
|
|
gsi_remove (&si, true);
|
|
release_defs (iv_stmt);
|
|
}
|
|
}
|
|
|
|
/* Transform a lambda loopnest NEW_LOOPNEST, which had TRANSFORM applied to
|
|
it, back into gcc code. This changes the
|
|
loops, their induction variables, and their bodies, so that they
|
|
match the transformed loopnest.
|
|
OLD_LOOPNEST is the loopnest before we've replaced it with the new
|
|
loopnest.
|
|
OLD_IVS is a vector of induction variables from the old loopnest.
|
|
INVARIANTS is a vector of loop invariants from the old loopnest.
|
|
NEW_LOOPNEST is the new lambda loopnest to replace OLD_LOOPNEST with.
|
|
TRANSFORM is the matrix transform that was applied to OLD_LOOPNEST to get
|
|
NEW_LOOPNEST. */
|
|
|
|
void
|
|
lambda_loopnest_to_gcc_loopnest (struct loop *old_loopnest,
|
|
VEC(tree,heap) *old_ivs,
|
|
VEC(tree,heap) *invariants,
|
|
VEC(gimple,heap) **remove_ivs,
|
|
lambda_loopnest new_loopnest,
|
|
lambda_trans_matrix transform,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
struct loop *temp;
|
|
size_t i = 0;
|
|
unsigned j;
|
|
size_t depth = 0;
|
|
VEC(tree,heap) *new_ivs = NULL;
|
|
tree oldiv;
|
|
gimple_stmt_iterator bsi;
|
|
|
|
transform = lambda_trans_matrix_inverse (transform, lambda_obstack);
|
|
|
|
if (dump_file)
|
|
{
|
|
fprintf (dump_file, "Inverse of transformation matrix:\n");
|
|
print_lambda_trans_matrix (dump_file, transform);
|
|
}
|
|
depth = depth_of_nest (old_loopnest);
|
|
temp = old_loopnest;
|
|
|
|
while (temp)
|
|
{
|
|
lambda_loop newloop;
|
|
basic_block bb;
|
|
edge exit;
|
|
tree ivvar, ivvarinced;
|
|
gimple exitcond;
|
|
gimple_seq stmts;
|
|
enum tree_code testtype;
|
|
tree newupperbound, newlowerbound;
|
|
lambda_linear_expression offset;
|
|
tree type;
|
|
bool insert_after;
|
|
gimple inc_stmt;
|
|
|
|
oldiv = VEC_index (tree, old_ivs, i);
|
|
type = TREE_TYPE (oldiv);
|
|
|
|
/* First, build the new induction variable temporary */
|
|
|
|
ivvar = create_tmp_var (type, "lnivtmp");
|
|
add_referenced_var (ivvar);
|
|
|
|
VEC_safe_push (tree, heap, new_ivs, ivvar);
|
|
|
|
newloop = LN_LOOPS (new_loopnest)[i];
|
|
|
|
/* Linear offset is a bit tricky to handle. Punt on the unhandled
|
|
cases for now. */
|
|
offset = LL_LINEAR_OFFSET (newloop);
|
|
|
|
gcc_assert (LLE_DENOMINATOR (offset) == 1 &&
|
|
lambda_vector_zerop (LLE_COEFFICIENTS (offset), depth));
|
|
|
|
/* Now build the new lower bounds, and insert the statements
|
|
necessary to generate it on the loop preheader. */
|
|
stmts = NULL;
|
|
newlowerbound = lle_to_gcc_expression (LL_LOWER_BOUND (newloop),
|
|
LL_LINEAR_OFFSET (newloop),
|
|
type,
|
|
new_ivs,
|
|
invariants, MAX_EXPR, &stmts);
|
|
|
|
if (stmts)
|
|
{
|
|
gsi_insert_seq_on_edge (loop_preheader_edge (temp), stmts);
|
|
gsi_commit_edge_inserts ();
|
|
}
|
|
/* Build the new upper bound and insert its statements in the
|
|
basic block of the exit condition */
|
|
stmts = NULL;
|
|
newupperbound = lle_to_gcc_expression (LL_UPPER_BOUND (newloop),
|
|
LL_LINEAR_OFFSET (newloop),
|
|
type,
|
|
new_ivs,
|
|
invariants, MIN_EXPR, &stmts);
|
|
exit = single_exit (temp);
|
|
exitcond = get_loop_exit_condition (temp);
|
|
bb = gimple_bb (exitcond);
|
|
bsi = gsi_after_labels (bb);
|
|
if (stmts)
|
|
gsi_insert_seq_before (&bsi, stmts, GSI_NEW_STMT);
|
|
|
|
/* Create the new iv. */
|
|
|
|
standard_iv_increment_position (temp, &bsi, &insert_after);
|
|
create_iv (newlowerbound,
|
|
build_int_cst (type, LL_STEP (newloop)),
|
|
ivvar, temp, &bsi, insert_after, &ivvar,
|
|
NULL);
|
|
|
|
/* Unfortunately, the incremented ivvar that create_iv inserted may not
|
|
dominate the block containing the exit condition.
|
|
So we simply create our own incremented iv to use in the new exit
|
|
test, and let redundancy elimination sort it out. */
|
|
inc_stmt = gimple_build_assign_with_ops (PLUS_EXPR, SSA_NAME_VAR (ivvar),
|
|
ivvar,
|
|
build_int_cst (type, LL_STEP (newloop)));
|
|
|
|
ivvarinced = make_ssa_name (SSA_NAME_VAR (ivvar), inc_stmt);
|
|
gimple_assign_set_lhs (inc_stmt, ivvarinced);
|
|
bsi = gsi_for_stmt (exitcond);
|
|
gsi_insert_before (&bsi, inc_stmt, GSI_SAME_STMT);
|
|
|
|
/* Replace the exit condition with the new upper bound
|
|
comparison. */
|
|
|
|
testtype = LL_STEP (newloop) >= 0 ? LE_EXPR : GE_EXPR;
|
|
|
|
/* We want to build a conditional where true means exit the loop, and
|
|
false means continue the loop.
|
|
So swap the testtype if this isn't the way things are.*/
|
|
|
|
if (exit->flags & EDGE_FALSE_VALUE)
|
|
testtype = swap_tree_comparison (testtype);
|
|
|
|
gimple_cond_set_condition (exitcond, testtype, newupperbound, ivvarinced);
|
|
update_stmt (exitcond);
|
|
VEC_replace (tree, new_ivs, i, ivvar);
|
|
|
|
i++;
|
|
temp = temp->inner;
|
|
}
|
|
|
|
/* Rewrite uses of the old ivs so that they are now specified in terms of
|
|
the new ivs. */
|
|
|
|
for (i = 0; VEC_iterate (tree, old_ivs, i, oldiv); i++)
|
|
{
|
|
imm_use_iterator imm_iter;
|
|
use_operand_p use_p;
|
|
tree oldiv_def;
|
|
gimple oldiv_stmt = SSA_NAME_DEF_STMT (oldiv);
|
|
gimple stmt;
|
|
|
|
if (gimple_code (oldiv_stmt) == GIMPLE_PHI)
|
|
oldiv_def = PHI_RESULT (oldiv_stmt);
|
|
else
|
|
oldiv_def = SINGLE_SSA_TREE_OPERAND (oldiv_stmt, SSA_OP_DEF);
|
|
gcc_assert (oldiv_def != NULL_TREE);
|
|
|
|
FOR_EACH_IMM_USE_STMT (stmt, imm_iter, oldiv_def)
|
|
{
|
|
tree newiv;
|
|
gimple_seq stmts;
|
|
lambda_body_vector lbv, newlbv;
|
|
|
|
if (is_gimple_debug (stmt))
|
|
continue;
|
|
|
|
/* Compute the new expression for the induction
|
|
variable. */
|
|
depth = VEC_length (tree, new_ivs);
|
|
lbv = lambda_body_vector_new (depth, lambda_obstack);
|
|
LBV_COEFFICIENTS (lbv)[i] = 1;
|
|
|
|
newlbv = lambda_body_vector_compute_new (transform, lbv,
|
|
lambda_obstack);
|
|
|
|
stmts = NULL;
|
|
newiv = lbv_to_gcc_expression (newlbv, TREE_TYPE (oldiv),
|
|
new_ivs, &stmts);
|
|
|
|
if (stmts && gimple_code (stmt) != GIMPLE_PHI)
|
|
{
|
|
bsi = gsi_for_stmt (stmt);
|
|
gsi_insert_seq_before (&bsi, stmts, GSI_SAME_STMT);
|
|
}
|
|
|
|
FOR_EACH_IMM_USE_ON_STMT (use_p, imm_iter)
|
|
propagate_value (use_p, newiv);
|
|
|
|
if (stmts && gimple_code (stmt) == GIMPLE_PHI)
|
|
for (j = 0; j < gimple_phi_num_args (stmt); j++)
|
|
if (gimple_phi_arg_def (stmt, j) == newiv)
|
|
gsi_insert_seq_on_edge (gimple_phi_arg_edge (stmt, j), stmts);
|
|
|
|
update_stmt (stmt);
|
|
}
|
|
|
|
/* Remove the now unused induction variable. */
|
|
VEC_safe_push (gimple, heap, *remove_ivs, oldiv_stmt);
|
|
}
|
|
VEC_free (tree, heap, new_ivs);
|
|
}
|
|
|
|
/* Return TRUE if this is not interesting statement from the perspective of
|
|
determining if we have a perfect loop nest. */
|
|
|
|
static bool
|
|
not_interesting_stmt (gimple stmt)
|
|
{
|
|
/* Note that COND_EXPR's aren't interesting because if they were exiting the
|
|
loop, we would have already failed the number of exits tests. */
|
|
if (gimple_code (stmt) == GIMPLE_LABEL
|
|
|| gimple_code (stmt) == GIMPLE_GOTO
|
|
|| gimple_code (stmt) == GIMPLE_COND
|
|
|| is_gimple_debug (stmt))
|
|
return true;
|
|
return false;
|
|
}
|
|
|
|
/* Return TRUE if PHI uses DEF for it's in-the-loop edge for LOOP. */
|
|
|
|
static bool
|
|
phi_loop_edge_uses_def (struct loop *loop, gimple phi, tree def)
|
|
{
|
|
unsigned i;
|
|
for (i = 0; i < gimple_phi_num_args (phi); i++)
|
|
if (flow_bb_inside_loop_p (loop, gimple_phi_arg_edge (phi, i)->src))
|
|
if (PHI_ARG_DEF (phi, i) == def)
|
|
return true;
|
|
return false;
|
|
}
|
|
|
|
/* Return TRUE if STMT is a use of PHI_RESULT. */
|
|
|
|
static bool
|
|
stmt_uses_phi_result (gimple stmt, tree phi_result)
|
|
{
|
|
tree use = SINGLE_SSA_TREE_OPERAND (stmt, SSA_OP_USE);
|
|
|
|
/* This is conservatively true, because we only want SIMPLE bumpers
|
|
of the form x +- constant for our pass. */
|
|
return (use == phi_result);
|
|
}
|
|
|
|
/* STMT is a bumper stmt for LOOP if the version it defines is used in the
|
|
in-loop-edge in a phi node, and the operand it uses is the result of that
|
|
phi node.
|
|
I.E. i_29 = i_3 + 1
|
|
i_3 = PHI (0, i_29); */
|
|
|
|
static bool
|
|
stmt_is_bumper_for_loop (struct loop *loop, gimple stmt)
|
|
{
|
|
gimple use;
|
|
tree def;
|
|
imm_use_iterator iter;
|
|
use_operand_p use_p;
|
|
|
|
def = SINGLE_SSA_TREE_OPERAND (stmt, SSA_OP_DEF);
|
|
if (!def)
|
|
return false;
|
|
|
|
FOR_EACH_IMM_USE_FAST (use_p, iter, def)
|
|
{
|
|
use = USE_STMT (use_p);
|
|
if (gimple_code (use) == GIMPLE_PHI)
|
|
{
|
|
if (phi_loop_edge_uses_def (loop, use, def))
|
|
if (stmt_uses_phi_result (stmt, PHI_RESULT (use)))
|
|
return true;
|
|
}
|
|
}
|
|
return false;
|
|
}
|
|
|
|
|
|
/* Return true if LOOP is a perfect loop nest.
|
|
Perfect loop nests are those loop nests where all code occurs in the
|
|
innermost loop body.
|
|
If S is a program statement, then
|
|
|
|
i.e.
|
|
DO I = 1, 20
|
|
S1
|
|
DO J = 1, 20
|
|
...
|
|
END DO
|
|
END DO
|
|
is not a perfect loop nest because of S1.
|
|
|
|
DO I = 1, 20
|
|
DO J = 1, 20
|
|
S1
|
|
...
|
|
END DO
|
|
END DO
|
|
is a perfect loop nest.
|
|
|
|
Since we don't have high level loops anymore, we basically have to walk our
|
|
statements and ignore those that are there because the loop needs them (IE
|
|
the induction variable increment, and jump back to the top of the loop). */
|
|
|
|
bool
|
|
perfect_nest_p (struct loop *loop)
|
|
{
|
|
basic_block *bbs;
|
|
size_t i;
|
|
gimple exit_cond;
|
|
|
|
/* Loops at depth 0 are perfect nests. */
|
|
if (!loop->inner)
|
|
return true;
|
|
|
|
bbs = get_loop_body (loop);
|
|
exit_cond = get_loop_exit_condition (loop);
|
|
|
|
for (i = 0; i < loop->num_nodes; i++)
|
|
{
|
|
if (bbs[i]->loop_father == loop)
|
|
{
|
|
gimple_stmt_iterator bsi;
|
|
|
|
for (bsi = gsi_start_bb (bbs[i]); !gsi_end_p (bsi); gsi_next (&bsi))
|
|
{
|
|
gimple stmt = gsi_stmt (bsi);
|
|
|
|
if (gimple_code (stmt) == GIMPLE_COND
|
|
&& exit_cond != stmt)
|
|
goto non_perfectly_nested;
|
|
|
|
if (stmt == exit_cond
|
|
|| not_interesting_stmt (stmt)
|
|
|| stmt_is_bumper_for_loop (loop, stmt))
|
|
continue;
|
|
|
|
non_perfectly_nested:
|
|
free (bbs);
|
|
return false;
|
|
}
|
|
}
|
|
}
|
|
|
|
free (bbs);
|
|
|
|
return perfect_nest_p (loop->inner);
|
|
}
|
|
|
|
/* Replace the USES of X in STMT, or uses with the same step as X with Y.
|
|
YINIT is the initial value of Y, REPLACEMENTS is a hash table to
|
|
avoid creating duplicate temporaries and FIRSTBSI is statement
|
|
iterator where new temporaries should be inserted at the beginning
|
|
of body basic block. */
|
|
|
|
static void
|
|
replace_uses_equiv_to_x_with_y (struct loop *loop, gimple stmt, tree x,
|
|
int xstep, tree y, tree yinit,
|
|
htab_t replacements,
|
|
gimple_stmt_iterator *firstbsi)
|
|
{
|
|
ssa_op_iter iter;
|
|
use_operand_p use_p;
|
|
|
|
FOR_EACH_SSA_USE_OPERAND (use_p, stmt, iter, SSA_OP_USE)
|
|
{
|
|
tree use = USE_FROM_PTR (use_p);
|
|
tree step = NULL_TREE;
|
|
tree scev, init, val, var;
|
|
gimple setstmt;
|
|
struct tree_map *h, in;
|
|
void **loc;
|
|
|
|
/* Replace uses of X with Y right away. */
|
|
if (use == x)
|
|
{
|
|
SET_USE (use_p, y);
|
|
continue;
|
|
}
|
|
|
|
scev = instantiate_parameters (loop,
|
|
analyze_scalar_evolution (loop, use));
|
|
|
|
if (scev == NULL || scev == chrec_dont_know)
|
|
continue;
|
|
|
|
step = evolution_part_in_loop_num (scev, loop->num);
|
|
if (step == NULL
|
|
|| step == chrec_dont_know
|
|
|| TREE_CODE (step) != INTEGER_CST
|
|
|| int_cst_value (step) != xstep)
|
|
continue;
|
|
|
|
/* Use REPLACEMENTS hash table to cache already created
|
|
temporaries. */
|
|
in.hash = htab_hash_pointer (use);
|
|
in.base.from = use;
|
|
h = (struct tree_map *) htab_find_with_hash (replacements, &in, in.hash);
|
|
if (h != NULL)
|
|
{
|
|
SET_USE (use_p, h->to);
|
|
continue;
|
|
}
|
|
|
|
/* USE which has the same step as X should be replaced
|
|
with a temporary set to Y + YINIT - INIT. */
|
|
init = initial_condition_in_loop_num (scev, loop->num);
|
|
gcc_assert (init != NULL && init != chrec_dont_know);
|
|
if (TREE_TYPE (use) == TREE_TYPE (y))
|
|
{
|
|
val = fold_build2 (MINUS_EXPR, TREE_TYPE (y), init, yinit);
|
|
val = fold_build2 (PLUS_EXPR, TREE_TYPE (y), y, val);
|
|
if (val == y)
|
|
{
|
|
/* If X has the same type as USE, the same step
|
|
and same initial value, it can be replaced by Y. */
|
|
SET_USE (use_p, y);
|
|
continue;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
val = fold_build2 (MINUS_EXPR, TREE_TYPE (y), y, yinit);
|
|
val = fold_convert (TREE_TYPE (use), val);
|
|
val = fold_build2 (PLUS_EXPR, TREE_TYPE (use), val, init);
|
|
}
|
|
|
|
/* Create a temporary variable and insert it at the beginning
|
|
of the loop body basic block, right after the PHI node
|
|
which sets Y. */
|
|
var = create_tmp_var (TREE_TYPE (use), "perfecttmp");
|
|
add_referenced_var (var);
|
|
val = force_gimple_operand_gsi (firstbsi, val, false, NULL,
|
|
true, GSI_SAME_STMT);
|
|
setstmt = gimple_build_assign (var, val);
|
|
var = make_ssa_name (var, setstmt);
|
|
gimple_assign_set_lhs (setstmt, var);
|
|
gsi_insert_before (firstbsi, setstmt, GSI_SAME_STMT);
|
|
update_stmt (setstmt);
|
|
SET_USE (use_p, var);
|
|
h = GGC_NEW (struct tree_map);
|
|
h->hash = in.hash;
|
|
h->base.from = use;
|
|
h->to = var;
|
|
loc = htab_find_slot_with_hash (replacements, h, in.hash, INSERT);
|
|
gcc_assert ((*(struct tree_map **)loc) == NULL);
|
|
*(struct tree_map **) loc = h;
|
|
}
|
|
}
|
|
|
|
/* Return true if STMT is an exit PHI for LOOP */
|
|
|
|
static bool
|
|
exit_phi_for_loop_p (struct loop *loop, gimple stmt)
|
|
{
|
|
if (gimple_code (stmt) != GIMPLE_PHI
|
|
|| gimple_phi_num_args (stmt) != 1
|
|
|| gimple_bb (stmt) != single_exit (loop)->dest)
|
|
return false;
|
|
|
|
return true;
|
|
}
|
|
|
|
/* Return true if STMT can be put back into the loop INNER, by
|
|
copying it to the beginning of that loop and changing the uses. */
|
|
|
|
static bool
|
|
can_put_in_inner_loop (struct loop *inner, gimple stmt)
|
|
{
|
|
imm_use_iterator imm_iter;
|
|
use_operand_p use_p;
|
|
|
|
gcc_assert (is_gimple_assign (stmt));
|
|
if (gimple_vuse (stmt)
|
|
|| !stmt_invariant_in_loop_p (inner, stmt))
|
|
return false;
|
|
|
|
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, gimple_assign_lhs (stmt))
|
|
{
|
|
if (!exit_phi_for_loop_p (inner, USE_STMT (use_p)))
|
|
{
|
|
basic_block immbb = gimple_bb (USE_STMT (use_p));
|
|
|
|
if (!flow_bb_inside_loop_p (inner, immbb))
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
/* Return true if STMT can be put *after* the inner loop of LOOP. */
|
|
|
|
static bool
|
|
can_put_after_inner_loop (struct loop *loop, gimple stmt)
|
|
{
|
|
imm_use_iterator imm_iter;
|
|
use_operand_p use_p;
|
|
|
|
if (gimple_vuse (stmt))
|
|
return false;
|
|
|
|
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, gimple_assign_lhs (stmt))
|
|
{
|
|
if (!exit_phi_for_loop_p (loop, USE_STMT (use_p)))
|
|
{
|
|
basic_block immbb = gimple_bb (USE_STMT (use_p));
|
|
|
|
if (!dominated_by_p (CDI_DOMINATORS,
|
|
immbb,
|
|
loop->inner->header)
|
|
&& !can_put_in_inner_loop (loop->inner, stmt))
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
/* Return true when the induction variable IV is simple enough to be
|
|
re-synthesized. */
|
|
|
|
static bool
|
|
can_duplicate_iv (tree iv, struct loop *loop)
|
|
{
|
|
tree scev = instantiate_parameters
|
|
(loop, analyze_scalar_evolution (loop, iv));
|
|
|
|
if (!automatically_generated_chrec_p (scev))
|
|
{
|
|
tree step = evolution_part_in_loop_num (scev, loop->num);
|
|
|
|
if (step && step != chrec_dont_know && TREE_CODE (step) == INTEGER_CST)
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
/* If this is a scalar operation that can be put back into the inner
|
|
loop, or after the inner loop, through copying, then do so. This
|
|
works on the theory that any amount of scalar code we have to
|
|
reduplicate into or after the loops is less expensive that the win
|
|
we get from rearranging the memory walk the loop is doing so that
|
|
it has better cache behavior. */
|
|
|
|
static bool
|
|
cannot_convert_modify_to_perfect_nest (gimple stmt, struct loop *loop)
|
|
{
|
|
use_operand_p use_a, use_b;
|
|
imm_use_iterator imm_iter;
|
|
ssa_op_iter op_iter, op_iter1;
|
|
tree op0 = gimple_assign_lhs (stmt);
|
|
|
|
/* The statement should not define a variable used in the inner
|
|
loop. */
|
|
if (TREE_CODE (op0) == SSA_NAME
|
|
&& !can_duplicate_iv (op0, loop))
|
|
FOR_EACH_IMM_USE_FAST (use_a, imm_iter, op0)
|
|
if (gimple_bb (USE_STMT (use_a))->loop_father == loop->inner)
|
|
return true;
|
|
|
|
FOR_EACH_SSA_USE_OPERAND (use_a, stmt, op_iter, SSA_OP_USE)
|
|
{
|
|
gimple node;
|
|
tree op = USE_FROM_PTR (use_a);
|
|
|
|
/* The variables should not be used in both loops. */
|
|
if (!can_duplicate_iv (op, loop))
|
|
FOR_EACH_IMM_USE_FAST (use_b, imm_iter, op)
|
|
if (gimple_bb (USE_STMT (use_b))->loop_father == loop->inner)
|
|
return true;
|
|
|
|
/* The statement should not use the value of a scalar that was
|
|
modified in the loop. */
|
|
node = SSA_NAME_DEF_STMT (op);
|
|
if (gimple_code (node) == GIMPLE_PHI)
|
|
FOR_EACH_PHI_ARG (use_b, node, op_iter1, SSA_OP_USE)
|
|
{
|
|
tree arg = USE_FROM_PTR (use_b);
|
|
|
|
if (TREE_CODE (arg) == SSA_NAME)
|
|
{
|
|
gimple arg_stmt = SSA_NAME_DEF_STMT (arg);
|
|
|
|
if (gimple_bb (arg_stmt)
|
|
&& (gimple_bb (arg_stmt)->loop_father == loop->inner))
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
/* Return true when BB contains statements that can harm the transform
|
|
to a perfect loop nest. */
|
|
|
|
static bool
|
|
cannot_convert_bb_to_perfect_nest (basic_block bb, struct loop *loop)
|
|
{
|
|
gimple_stmt_iterator bsi;
|
|
gimple exit_condition = get_loop_exit_condition (loop);
|
|
|
|
for (bsi = gsi_start_bb (bb); !gsi_end_p (bsi); gsi_next (&bsi))
|
|
{
|
|
gimple stmt = gsi_stmt (bsi);
|
|
|
|
if (stmt == exit_condition
|
|
|| not_interesting_stmt (stmt)
|
|
|| stmt_is_bumper_for_loop (loop, stmt))
|
|
continue;
|
|
|
|
if (is_gimple_assign (stmt))
|
|
{
|
|
if (cannot_convert_modify_to_perfect_nest (stmt, loop))
|
|
return true;
|
|
|
|
if (can_duplicate_iv (gimple_assign_lhs (stmt), loop))
|
|
continue;
|
|
|
|
if (can_put_in_inner_loop (loop->inner, stmt)
|
|
|| can_put_after_inner_loop (loop, stmt))
|
|
continue;
|
|
}
|
|
|
|
/* If the bb of a statement we care about isn't dominated by the
|
|
header of the inner loop, then we can't handle this case
|
|
right now. This test ensures that the statement comes
|
|
completely *after* the inner loop. */
|
|
if (!dominated_by_p (CDI_DOMINATORS,
|
|
gimple_bb (stmt),
|
|
loop->inner->header))
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
|
|
/* Return TRUE if LOOP is an imperfect nest that we can convert to a
|
|
perfect one. At the moment, we only handle imperfect nests of
|
|
depth 2, where all of the statements occur after the inner loop. */
|
|
|
|
static bool
|
|
can_convert_to_perfect_nest (struct loop *loop)
|
|
{
|
|
basic_block *bbs;
|
|
size_t i;
|
|
gimple_stmt_iterator si;
|
|
|
|
/* Can't handle triply nested+ loops yet. */
|
|
if (!loop->inner || loop->inner->inner)
|
|
return false;
|
|
|
|
bbs = get_loop_body (loop);
|
|
for (i = 0; i < loop->num_nodes; i++)
|
|
if (bbs[i]->loop_father == loop
|
|
&& cannot_convert_bb_to_perfect_nest (bbs[i], loop))
|
|
goto fail;
|
|
|
|
/* We also need to make sure the loop exit only has simple copy phis in it,
|
|
otherwise we don't know how to transform it into a perfect nest. */
|
|
for (si = gsi_start_phis (single_exit (loop)->dest);
|
|
!gsi_end_p (si);
|
|
gsi_next (&si))
|
|
if (gimple_phi_num_args (gsi_stmt (si)) != 1)
|
|
goto fail;
|
|
|
|
free (bbs);
|
|
return true;
|
|
|
|
fail:
|
|
free (bbs);
|
|
return false;
|
|
}
|
|
|
|
|
|
DEF_VEC_I(source_location);
|
|
DEF_VEC_ALLOC_I(source_location,heap);
|
|
|
|
/* Transform the loop nest into a perfect nest, if possible.
|
|
LOOP is the loop nest to transform into a perfect nest
|
|
LBOUNDS are the lower bounds for the loops to transform
|
|
UBOUNDS are the upper bounds for the loops to transform
|
|
STEPS is the STEPS for the loops to transform.
|
|
LOOPIVS is the induction variables for the loops to transform.
|
|
|
|
Basically, for the case of
|
|
|
|
FOR (i = 0; i < 50; i++)
|
|
{
|
|
FOR (j =0; j < 50; j++)
|
|
{
|
|
<whatever>
|
|
}
|
|
<some code>
|
|
}
|
|
|
|
This function will transform it into a perfect loop nest by splitting the
|
|
outer loop into two loops, like so:
|
|
|
|
FOR (i = 0; i < 50; i++)
|
|
{
|
|
FOR (j = 0; j < 50; j++)
|
|
{
|
|
<whatever>
|
|
}
|
|
}
|
|
|
|
FOR (i = 0; i < 50; i ++)
|
|
{
|
|
<some code>
|
|
}
|
|
|
|
Return FALSE if we can't make this loop into a perfect nest. */
|
|
|
|
static bool
|
|
perfect_nestify (struct loop *loop,
|
|
VEC(tree,heap) *lbounds,
|
|
VEC(tree,heap) *ubounds,
|
|
VEC(int,heap) *steps,
|
|
VEC(tree,heap) *loopivs)
|
|
{
|
|
basic_block *bbs;
|
|
gimple exit_condition;
|
|
gimple cond_stmt;
|
|
basic_block preheaderbb, headerbb, bodybb, latchbb, olddest;
|
|
int i;
|
|
gimple_stmt_iterator bsi, firstbsi;
|
|
bool insert_after;
|
|
edge e;
|
|
struct loop *newloop;
|
|
gimple phi;
|
|
tree uboundvar;
|
|
gimple stmt;
|
|
tree oldivvar, ivvar, ivvarinced;
|
|
VEC(tree,heap) *phis = NULL;
|
|
VEC(source_location,heap) *locations = NULL;
|
|
htab_t replacements = NULL;
|
|
|
|
/* Create the new loop. */
|
|
olddest = single_exit (loop)->dest;
|
|
preheaderbb = split_edge (single_exit (loop));
|
|
headerbb = create_empty_bb (EXIT_BLOCK_PTR->prev_bb);
|
|
|
|
/* Push the exit phi nodes that we are moving. */
|
|
for (bsi = gsi_start_phis (olddest); !gsi_end_p (bsi); gsi_next (&bsi))
|
|
{
|
|
phi = gsi_stmt (bsi);
|
|
VEC_reserve (tree, heap, phis, 2);
|
|
VEC_reserve (source_location, heap, locations, 1);
|
|
VEC_quick_push (tree, phis, PHI_RESULT (phi));
|
|
VEC_quick_push (tree, phis, PHI_ARG_DEF (phi, 0));
|
|
VEC_quick_push (source_location, locations,
|
|
gimple_phi_arg_location (phi, 0));
|
|
}
|
|
e = redirect_edge_and_branch (single_succ_edge (preheaderbb), headerbb);
|
|
|
|
/* Remove the exit phis from the old basic block. */
|
|
for (bsi = gsi_start_phis (olddest); !gsi_end_p (bsi); )
|
|
remove_phi_node (&bsi, false);
|
|
|
|
/* and add them back to the new basic block. */
|
|
while (VEC_length (tree, phis) != 0)
|
|
{
|
|
tree def;
|
|
tree phiname;
|
|
source_location locus;
|
|
def = VEC_pop (tree, phis);
|
|
phiname = VEC_pop (tree, phis);
|
|
locus = VEC_pop (source_location, locations);
|
|
phi = create_phi_node (phiname, preheaderbb);
|
|
add_phi_arg (phi, def, single_pred_edge (preheaderbb), locus);
|
|
}
|
|
flush_pending_stmts (e);
|
|
VEC_free (tree, heap, phis);
|
|
|
|
bodybb = create_empty_bb (EXIT_BLOCK_PTR->prev_bb);
|
|
latchbb = create_empty_bb (EXIT_BLOCK_PTR->prev_bb);
|
|
make_edge (headerbb, bodybb, EDGE_FALLTHRU);
|
|
cond_stmt = gimple_build_cond (NE_EXPR, integer_one_node, integer_zero_node,
|
|
NULL_TREE, NULL_TREE);
|
|
bsi = gsi_start_bb (bodybb);
|
|
gsi_insert_after (&bsi, cond_stmt, GSI_NEW_STMT);
|
|
e = make_edge (bodybb, olddest, EDGE_FALSE_VALUE);
|
|
make_edge (bodybb, latchbb, EDGE_TRUE_VALUE);
|
|
make_edge (latchbb, headerbb, EDGE_FALLTHRU);
|
|
|
|
/* Update the loop structures. */
|
|
newloop = duplicate_loop (loop, olddest->loop_father);
|
|
newloop->header = headerbb;
|
|
newloop->latch = latchbb;
|
|
add_bb_to_loop (latchbb, newloop);
|
|
add_bb_to_loop (bodybb, newloop);
|
|
add_bb_to_loop (headerbb, newloop);
|
|
set_immediate_dominator (CDI_DOMINATORS, bodybb, headerbb);
|
|
set_immediate_dominator (CDI_DOMINATORS, headerbb, preheaderbb);
|
|
set_immediate_dominator (CDI_DOMINATORS, preheaderbb,
|
|
single_exit (loop)->src);
|
|
set_immediate_dominator (CDI_DOMINATORS, latchbb, bodybb);
|
|
set_immediate_dominator (CDI_DOMINATORS, olddest,
|
|
recompute_dominator (CDI_DOMINATORS, olddest));
|
|
/* Create the new iv. */
|
|
oldivvar = VEC_index (tree, loopivs, 0);
|
|
ivvar = create_tmp_var (TREE_TYPE (oldivvar), "perfectiv");
|
|
add_referenced_var (ivvar);
|
|
standard_iv_increment_position (newloop, &bsi, &insert_after);
|
|
create_iv (VEC_index (tree, lbounds, 0),
|
|
build_int_cst (TREE_TYPE (oldivvar), VEC_index (int, steps, 0)),
|
|
ivvar, newloop, &bsi, insert_after, &ivvar, &ivvarinced);
|
|
|
|
/* Create the new upper bound. This may be not just a variable, so we copy
|
|
it to one just in case. */
|
|
|
|
exit_condition = get_loop_exit_condition (newloop);
|
|
uboundvar = create_tmp_var (TREE_TYPE (VEC_index (tree, ubounds, 0)),
|
|
"uboundvar");
|
|
add_referenced_var (uboundvar);
|
|
stmt = gimple_build_assign (uboundvar, VEC_index (tree, ubounds, 0));
|
|
uboundvar = make_ssa_name (uboundvar, stmt);
|
|
gimple_assign_set_lhs (stmt, uboundvar);
|
|
|
|
if (insert_after)
|
|
gsi_insert_after (&bsi, stmt, GSI_SAME_STMT);
|
|
else
|
|
gsi_insert_before (&bsi, stmt, GSI_SAME_STMT);
|
|
update_stmt (stmt);
|
|
gimple_cond_set_condition (exit_condition, GE_EXPR, uboundvar, ivvarinced);
|
|
update_stmt (exit_condition);
|
|
replacements = htab_create_ggc (20, tree_map_hash,
|
|
tree_map_eq, NULL);
|
|
bbs = get_loop_body_in_dom_order (loop);
|
|
/* Now move the statements, and replace the induction variable in the moved
|
|
statements with the correct loop induction variable. */
|
|
oldivvar = VEC_index (tree, loopivs, 0);
|
|
firstbsi = gsi_start_bb (bodybb);
|
|
for (i = loop->num_nodes - 1; i >= 0 ; i--)
|
|
{
|
|
gimple_stmt_iterator tobsi = gsi_last_bb (bodybb);
|
|
if (bbs[i]->loop_father == loop)
|
|
{
|
|
/* If this is true, we are *before* the inner loop.
|
|
If this isn't true, we are *after* it.
|
|
|
|
The only time can_convert_to_perfect_nest returns true when we
|
|
have statements before the inner loop is if they can be moved
|
|
into the inner loop.
|
|
|
|
The only time can_convert_to_perfect_nest returns true when we
|
|
have statements after the inner loop is if they can be moved into
|
|
the new split loop. */
|
|
|
|
if (dominated_by_p (CDI_DOMINATORS, loop->inner->header, bbs[i]))
|
|
{
|
|
gimple_stmt_iterator header_bsi
|
|
= gsi_after_labels (loop->inner->header);
|
|
|
|
for (bsi = gsi_start_bb (bbs[i]); !gsi_end_p (bsi);)
|
|
{
|
|
gimple stmt = gsi_stmt (bsi);
|
|
|
|
if (stmt == exit_condition
|
|
|| not_interesting_stmt (stmt)
|
|
|| stmt_is_bumper_for_loop (loop, stmt))
|
|
{
|
|
gsi_next (&bsi);
|
|
continue;
|
|
}
|
|
|
|
gsi_move_before (&bsi, &header_bsi);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* Note that the bsi only needs to be explicitly incremented
|
|
when we don't move something, since it is automatically
|
|
incremented when we do. */
|
|
for (bsi = gsi_start_bb (bbs[i]); !gsi_end_p (bsi);)
|
|
{
|
|
gimple stmt = gsi_stmt (bsi);
|
|
|
|
if (stmt == exit_condition
|
|
|| not_interesting_stmt (stmt)
|
|
|| stmt_is_bumper_for_loop (loop, stmt))
|
|
{
|
|
gsi_next (&bsi);
|
|
continue;
|
|
}
|
|
|
|
replace_uses_equiv_to_x_with_y
|
|
(loop, stmt, oldivvar, VEC_index (int, steps, 0), ivvar,
|
|
VEC_index (tree, lbounds, 0), replacements, &firstbsi);
|
|
|
|
gsi_move_before (&bsi, &tobsi);
|
|
|
|
/* If the statement has any virtual operands, they may
|
|
need to be rewired because the original loop may
|
|
still reference them. */
|
|
if (gimple_vuse (stmt))
|
|
mark_sym_for_renaming (gimple_vop (cfun));
|
|
}
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
free (bbs);
|
|
htab_delete (replacements);
|
|
return perfect_nest_p (loop);
|
|
}
|
|
|
|
/* Return true if TRANS is a legal transformation matrix that respects
|
|
the dependence vectors in DISTS and DIRS. The conservative answer
|
|
is false.
|
|
|
|
"Wolfe proves that a unimodular transformation represented by the
|
|
matrix T is legal when applied to a loop nest with a set of
|
|
lexicographically non-negative distance vectors RDG if and only if
|
|
for each vector d in RDG, (T.d >= 0) is lexicographically positive.
|
|
i.e.: if and only if it transforms the lexicographically positive
|
|
distance vectors to lexicographically positive vectors. Note that
|
|
a unimodular matrix must transform the zero vector (and only it) to
|
|
the zero vector." S.Muchnick. */
|
|
|
|
bool
|
|
lambda_transform_legal_p (lambda_trans_matrix trans,
|
|
int nb_loops,
|
|
VEC (ddr_p, heap) *dependence_relations)
|
|
{
|
|
unsigned int i, j;
|
|
lambda_vector distres;
|
|
struct data_dependence_relation *ddr;
|
|
|
|
gcc_assert (LTM_COLSIZE (trans) == nb_loops
|
|
&& LTM_ROWSIZE (trans) == nb_loops);
|
|
|
|
/* When there are no dependences, the transformation is correct. */
|
|
if (VEC_length (ddr_p, dependence_relations) == 0)
|
|
return true;
|
|
|
|
ddr = VEC_index (ddr_p, dependence_relations, 0);
|
|
if (ddr == NULL)
|
|
return true;
|
|
|
|
/* When there is an unknown relation in the dependence_relations, we
|
|
know that it is no worth looking at this loop nest: give up. */
|
|
if (DDR_ARE_DEPENDENT (ddr) == chrec_dont_know)
|
|
return false;
|
|
|
|
distres = lambda_vector_new (nb_loops);
|
|
|
|
/* For each distance vector in the dependence graph. */
|
|
for (i = 0; VEC_iterate (ddr_p, dependence_relations, i, ddr); i++)
|
|
{
|
|
/* Don't care about relations for which we know that there is no
|
|
dependence, nor about read-read (aka. output-dependences):
|
|
these data accesses can happen in any order. */
|
|
if (DDR_ARE_DEPENDENT (ddr) == chrec_known
|
|
|| (DR_IS_READ (DDR_A (ddr)) && DR_IS_READ (DDR_B (ddr))))
|
|
continue;
|
|
|
|
/* Conservatively answer: "this transformation is not valid". */
|
|
if (DDR_ARE_DEPENDENT (ddr) == chrec_dont_know)
|
|
return false;
|
|
|
|
/* If the dependence could not be captured by a distance vector,
|
|
conservatively answer that the transform is not valid. */
|
|
if (DDR_NUM_DIST_VECTS (ddr) == 0)
|
|
return false;
|
|
|
|
/* Compute trans.dist_vect */
|
|
for (j = 0; j < DDR_NUM_DIST_VECTS (ddr); j++)
|
|
{
|
|
lambda_matrix_vector_mult (LTM_MATRIX (trans), nb_loops, nb_loops,
|
|
DDR_DIST_VECT (ddr, j), distres);
|
|
|
|
if (!lambda_vector_lexico_pos (distres, nb_loops))
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
|
|
/* Collects parameters from affine function ACCESS_FUNCTION, and push
|
|
them in PARAMETERS. */
|
|
|
|
static void
|
|
lambda_collect_parameters_from_af (tree access_function,
|
|
struct pointer_set_t *param_set,
|
|
VEC (tree, heap) **parameters)
|
|
{
|
|
if (access_function == NULL)
|
|
return;
|
|
|
|
if (TREE_CODE (access_function) == SSA_NAME
|
|
&& pointer_set_contains (param_set, access_function) == 0)
|
|
{
|
|
pointer_set_insert (param_set, access_function);
|
|
VEC_safe_push (tree, heap, *parameters, access_function);
|
|
}
|
|
else
|
|
{
|
|
int i, num_operands = tree_operand_length (access_function);
|
|
|
|
for (i = 0; i < num_operands; i++)
|
|
lambda_collect_parameters_from_af (TREE_OPERAND (access_function, i),
|
|
param_set, parameters);
|
|
}
|
|
}
|
|
|
|
/* Collects parameters from DATAREFS, and push them in PARAMETERS. */
|
|
|
|
void
|
|
lambda_collect_parameters (VEC (data_reference_p, heap) *datarefs,
|
|
VEC (tree, heap) **parameters)
|
|
{
|
|
unsigned i, j;
|
|
struct pointer_set_t *parameter_set = pointer_set_create ();
|
|
data_reference_p data_reference;
|
|
|
|
for (i = 0; VEC_iterate (data_reference_p, datarefs, i, data_reference); i++)
|
|
for (j = 0; j < DR_NUM_DIMENSIONS (data_reference); j++)
|
|
lambda_collect_parameters_from_af (DR_ACCESS_FN (data_reference, j),
|
|
parameter_set, parameters);
|
|
pointer_set_destroy (parameter_set);
|
|
}
|
|
|
|
/* Translates BASE_EXPR to vector CY. AM is needed for inferring
|
|
indexing positions in the data access vector. CST is the analyzed
|
|
integer constant. */
|
|
|
|
static bool
|
|
av_for_af_base (tree base_expr, lambda_vector cy, struct access_matrix *am,
|
|
int cst)
|
|
{
|
|
bool result = true;
|
|
|
|
switch (TREE_CODE (base_expr))
|
|
{
|
|
case INTEGER_CST:
|
|
/* Constant part. */
|
|
cy[AM_CONST_COLUMN_INDEX (am)] += int_cst_value (base_expr) * cst;
|
|
return true;
|
|
|
|
case SSA_NAME:
|
|
{
|
|
int param_index =
|
|
access_matrix_get_index_for_parameter (base_expr, am);
|
|
|
|
if (param_index >= 0)
|
|
{
|
|
cy[param_index] = cst + cy[param_index];
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
case PLUS_EXPR:
|
|
return av_for_af_base (TREE_OPERAND (base_expr, 0), cy, am, cst)
|
|
&& av_for_af_base (TREE_OPERAND (base_expr, 1), cy, am, cst);
|
|
|
|
case MINUS_EXPR:
|
|
return av_for_af_base (TREE_OPERAND (base_expr, 0), cy, am, cst)
|
|
&& av_for_af_base (TREE_OPERAND (base_expr, 1), cy, am, -1 * cst);
|
|
|
|
case MULT_EXPR:
|
|
if (TREE_CODE (TREE_OPERAND (base_expr, 0)) == INTEGER_CST)
|
|
result = av_for_af_base (TREE_OPERAND (base_expr, 1),
|
|
cy, am, cst *
|
|
int_cst_value (TREE_OPERAND (base_expr, 0)));
|
|
else if (TREE_CODE (TREE_OPERAND (base_expr, 1)) == INTEGER_CST)
|
|
result = av_for_af_base (TREE_OPERAND (base_expr, 0),
|
|
cy, am, cst *
|
|
int_cst_value (TREE_OPERAND (base_expr, 1)));
|
|
else
|
|
result = false;
|
|
|
|
return result;
|
|
|
|
case NEGATE_EXPR:
|
|
return av_for_af_base (TREE_OPERAND (base_expr, 0), cy, am, -1 * cst);
|
|
|
|
default:
|
|
return false;
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
/* Translates ACCESS_FUN to vector CY. AM is needed for inferring
|
|
indexing positions in the data access vector. */
|
|
|
|
static bool
|
|
av_for_af (tree access_fun, lambda_vector cy, struct access_matrix *am)
|
|
{
|
|
switch (TREE_CODE (access_fun))
|
|
{
|
|
case POLYNOMIAL_CHREC:
|
|
{
|
|
tree left = CHREC_LEFT (access_fun);
|
|
tree right = CHREC_RIGHT (access_fun);
|
|
unsigned var;
|
|
|
|
if (TREE_CODE (right) != INTEGER_CST)
|
|
return false;
|
|
|
|
var = am_vector_index_for_loop (am, CHREC_VARIABLE (access_fun));
|
|
cy[var] = int_cst_value (right);
|
|
|
|
if (TREE_CODE (left) == POLYNOMIAL_CHREC)
|
|
return av_for_af (left, cy, am);
|
|
else
|
|
return av_for_af_base (left, cy, am, 1);
|
|
}
|
|
|
|
case INTEGER_CST:
|
|
/* Constant part. */
|
|
return av_for_af_base (access_fun, cy, am, 1);
|
|
|
|
default:
|
|
return false;
|
|
}
|
|
}
|
|
|
|
/* Initializes the access matrix for DATA_REFERENCE. */
|
|
|
|
static bool
|
|
build_access_matrix (data_reference_p data_reference,
|
|
VEC (tree, heap) *parameters,
|
|
VEC (loop_p, heap) *nest,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
struct access_matrix *am = (struct access_matrix *)
|
|
obstack_alloc(lambda_obstack, sizeof (struct access_matrix));
|
|
unsigned i, ndim = DR_NUM_DIMENSIONS (data_reference);
|
|
unsigned nivs = VEC_length (loop_p, nest);
|
|
unsigned lambda_nb_columns;
|
|
|
|
AM_LOOP_NEST (am) = nest;
|
|
AM_NB_INDUCTION_VARS (am) = nivs;
|
|
AM_PARAMETERS (am) = parameters;
|
|
|
|
lambda_nb_columns = AM_NB_COLUMNS (am);
|
|
AM_MATRIX (am) = VEC_alloc (lambda_vector, gc, ndim);
|
|
|
|
for (i = 0; i < ndim; i++)
|
|
{
|
|
lambda_vector access_vector = lambda_vector_new (lambda_nb_columns);
|
|
tree access_function = DR_ACCESS_FN (data_reference, i);
|
|
|
|
if (!av_for_af (access_function, access_vector, am))
|
|
return false;
|
|
|
|
VEC_quick_push (lambda_vector, AM_MATRIX (am), access_vector);
|
|
}
|
|
|
|
DR_ACCESS_MATRIX (data_reference) = am;
|
|
return true;
|
|
}
|
|
|
|
/* Returns false when one of the access matrices cannot be built. */
|
|
|
|
bool
|
|
lambda_compute_access_matrices (VEC (data_reference_p, heap) *datarefs,
|
|
VEC (tree, heap) *parameters,
|
|
VEC (loop_p, heap) *nest,
|
|
struct obstack * lambda_obstack)
|
|
{
|
|
data_reference_p dataref;
|
|
unsigned ix;
|
|
|
|
for (ix = 0; VEC_iterate (data_reference_p, datarefs, ix, dataref); ix++)
|
|
if (!build_access_matrix (dataref, parameters, nest, lambda_obstack))
|
|
return false;
|
|
|
|
return true;
|
|
}
|