/* Data References Analysis and Manipulation Utilities for Vectorization.
Copyright (C) 2003-2020 Free Software Foundation, Inc.
Contributed by Dorit Naishlos <dorit@il.ibm.com>
and Ira Rosen <irar@il.ibm.com>
This file is part of GCC.
GCC is free software; you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free
Software Foundation; either version 3, or (at your option) any later
version.
GCC is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
for more details.
You should have received a copy of the GNU General Public License
along with GCC; see the file COPYING3. If not see
<http://www.gnu.org/licenses/>. */
#include "config.h"
#include "system.h"
#include "coretypes.h"
#include "backend.h"
#include "target.h"
#include "rtl.h"
#include "tree.h"
#include "gimple.h"
#include "predict.h"
#include "memmodel.h"
#include "tm_p.h"
#include "ssa.h"
#include "optabs-tree.h"
#include "cgraph.h"
#include "dumpfile.h"
#include "alias.h"
#include "fold-const.h"
#include "stor-layout.h"
#include "tree-eh.h"
#include "gimplify.h"
#include "gimple-iterator.h"
#include "gimplify-me.h"
#include "tree-ssa-loop-ivopts.h"
#include "tree-ssa-loop-manip.h"
#include "tree-ssa-loop.h"
#include "cfgloop.h"
#include "tree-scalar-evolution.h"
#include "tree-vectorizer.h"
#include "expr.h"
#include "builtins.h"
#include "tree-cfg.h"
#include "tree-hash-traits.h"
#include "vec-perm-indices.h"
#include "internal-fn.h"
/* Return true if load- or store-lanes optab OPTAB is implemented for
COUNT vectors of type VECTYPE. NAME is the name of OPTAB. */
static bool
vect_lanes_optab_supported_p (const char *name, convert_optab optab,
tree vectype, unsigned HOST_WIDE_INT count)
{
machine_mode mode, array_mode;
bool limit_p;
mode = TYPE_MODE (vectype);
if (!targetm.array_mode (mode, count).exists (&array_mode))
{
poly_uint64 bits = count * GET_MODE_BITSIZE (mode);
limit_p = !targetm.array_mode_supported_p (mode, count);
if (!int_mode_for_size (bits, limit_p).exists (&array_mode))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"no array mode for %s[%wu]\n",
GET_MODE_NAME (mode), count);
return false;
}
}
if (convert_optab_handler (optab, array_mode, mode) == CODE_FOR_nothing)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"cannot use %s<%s><%s>\n", name,
GET_MODE_NAME (array_mode), GET_MODE_NAME (mode));
return false;
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"can use %s<%s><%s>\n", name, GET_MODE_NAME (array_mode),
GET_MODE_NAME (mode));
return true;
}
/* Return the smallest scalar part of STMT_INFO.
This is used to determine the vectype of the stmt. We generally set the
vectype according to the type of the result (lhs). For stmts whose
result-type is different than the type of the arguments (e.g., demotion,
promotion), vectype will be reset appropriately (later). Note that we have
to visit the smallest datatype in this function, because that determines the
VF. If the smallest datatype in the loop is present only as the rhs of a
promotion operation - we'd miss it.
Such a case, where a variable of this datatype does not appear in the lhs
anywhere in the loop, can only occur if it's an invariant: e.g.:
'int_x = (int) short_inv', which we'd expect to have been optimized away by
invariant motion. However, we cannot rely on invariant motion to always
take invariants out of the loop, and so in the case of promotion we also
have to check the rhs.
LHS_SIZE_UNIT and RHS_SIZE_UNIT contain the sizes of the corresponding
types. */
tree
vect_get_smallest_scalar_type (stmt_vec_info stmt_info,
HOST_WIDE_INT *lhs_size_unit,
HOST_WIDE_INT *rhs_size_unit)
{
tree scalar_type = gimple_expr_type (stmt_info->stmt);
HOST_WIDE_INT lhs, rhs;
/* During the analysis phase, this function is called on arbitrary
statements that might not have scalar results. */
if (!tree_fits_uhwi_p (TYPE_SIZE_UNIT (scalar_type)))
return scalar_type;
lhs = rhs = TREE_INT_CST_LOW (TYPE_SIZE_UNIT (scalar_type));
gassign *assign = dyn_cast <gassign *> (stmt_info->stmt);
if (assign
&& (gimple_assign_cast_p (assign)
|| gimple_assign_rhs_code (assign) == DOT_PROD_EXPR
|| gimple_assign_rhs_code (assign) == WIDEN_SUM_EXPR
|| gimple_assign_rhs_code (assign) == WIDEN_MULT_EXPR
|| gimple_assign_rhs_code (assign) == WIDEN_LSHIFT_EXPR
|| gimple_assign_rhs_code (assign) == FLOAT_EXPR))
{
tree rhs_type = TREE_TYPE (gimple_assign_rhs1 (assign));
rhs = TREE_INT_CST_LOW (TYPE_SIZE_UNIT (rhs_type));
if (rhs < lhs)
scalar_type = rhs_type;
}
else if (gcall *call = dyn_cast <gcall *> (stmt_info->stmt))
{
unsigned int i = 0;
if (gimple_call_internal_p (call))
{
internal_fn ifn = gimple_call_internal_fn (call);
if (internal_load_fn_p (ifn) || internal_store_fn_p (ifn))
/* gimple_expr_type already picked the type of the loaded
or stored data. */
i = ~0U;
else if (internal_fn_mask_index (ifn) == 0)
i = 1;
}
if (i < gimple_call_num_args (call))
{
tree rhs_type = TREE_TYPE (gimple_call_arg (call, i));
if (tree_fits_uhwi_p (TYPE_SIZE_UNIT (rhs_type)))
{
rhs = TREE_INT_CST_LOW (TYPE_SIZE_UNIT (rhs_type));
if (rhs < lhs)
scalar_type = rhs_type;
}
}
}
*lhs_size_unit = lhs;
*rhs_size_unit = rhs;
return scalar_type;
}
/* Insert DDR into LOOP_VINFO list of ddrs that may alias and need to be
tested at run-time. Return TRUE if DDR was successfully inserted.
Return false if versioning is not supported. */
static opt_result
vect_mark_for_runtime_alias_test (ddr_p ddr, loop_vec_info loop_vinfo)
{
class loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
if ((unsigned) param_vect_max_version_for_alias_checks == 0)
return opt_result::failure_at (vect_location,
"will not create alias checks, as"
" --param vect-max-version-for-alias-checks"
" == 0\n");
opt_result res
= runtime_alias_check_p (ddr, loop,
optimize_loop_nest_for_speed_p (loop));
if (!res)
return res;
LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo).safe_push (ddr);
return opt_result::success ();
}
/* Record that loop LOOP_VINFO needs to check that VALUE is nonzero. */
static void
vect_check_nonzero_value (loop_vec_info loop_vinfo, tree value)
{
vec<tree> checks = LOOP_VINFO_CHECK_NONZERO (loop_vinfo);
for (unsigned int i = 0; i < checks.length(); ++i)
if (checks[i] == value)
return;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"need run-time check that %T is nonzero\n",
value);
LOOP_VINFO_CHECK_NONZERO (loop_vinfo).safe_push (value);
}
/* Return true if we know that the order of vectorized DR_INFO_A and
vectorized DR_INFO_B will be the same as the order of DR_INFO_A and
DR_INFO_B. At least one of the accesses is a write. */
static bool
vect_preserves_scalar_order_p (dr_vec_info *dr_info_a, dr_vec_info *dr_info_b)
{
stmt_vec_info stmtinfo_a = dr_info_a->stmt;
stmt_vec_info stmtinfo_b = dr_info_b->stmt;
/* Single statements are always kept in their original order. */
if (!STMT_VINFO_GROUPED_ACCESS (stmtinfo_a)
&& !STMT_VINFO_GROUPED_ACCESS (stmtinfo_b))
return true;
/* STMT_A and STMT_B belong to overlapping groups. All loads in a
SLP group are emitted at the position of the last scalar load and
all loads in an interleaving group are emitted at the position
of the first scalar load.
Stores in a group are emitted at the position of the last scalar store.
Compute that position and check whether the resulting order matches
the current one.
We have not yet decided between SLP and interleaving so we have
to conservatively assume both. */
stmt_vec_info il_a;
stmt_vec_info last_a = il_a = DR_GROUP_FIRST_ELEMENT (stmtinfo_a);
if (last_a)
{
for (stmt_vec_info s = DR_GROUP_NEXT_ELEMENT (last_a); s;
s = DR_GROUP_NEXT_ELEMENT (s))
last_a = get_later_stmt (last_a, s);
if (!DR_IS_WRITE (STMT_VINFO_DATA_REF (stmtinfo_a)))
{
for (stmt_vec_info s = DR_GROUP_NEXT_ELEMENT (il_a); s;
s = DR_GROUP_NEXT_ELEMENT (s))
if (get_later_stmt (il_a, s) == il_a)
il_a = s;
}
else
il_a = last_a;
}
else
last_a = il_a = stmtinfo_a;
stmt_vec_info il_b;
stmt_vec_info last_b = il_b = DR_GROUP_FIRST_ELEMENT (stmtinfo_b);
if (last_b)
{
for (stmt_vec_info s = DR_GROUP_NEXT_ELEMENT (last_b); s;
s = DR_GROUP_NEXT_ELEMENT (s))
last_b = get_later_stmt (last_b, s);
if (!DR_IS_WRITE (STMT_VINFO_DATA_REF (stmtinfo_b)))
{
for (stmt_vec_info s = DR_GROUP_NEXT_ELEMENT (il_b); s;
s = DR_GROUP_NEXT_ELEMENT (s))
if (get_later_stmt (il_b, s) == il_b)
il_b = s;
}
else
il_b = last_b;
}
else
last_b = il_b = stmtinfo_b;
bool a_after_b = (get_later_stmt (stmtinfo_a, stmtinfo_b) == stmtinfo_a);
return (/* SLP */
(get_later_stmt (last_a, last_b) == last_a) == a_after_b
/* Interleaving */
&& (get_later_stmt (il_a, il_b) == il_a) == a_after_b
/* Mixed */
&& (get_later_stmt (il_a, last_b) == il_a) == a_after_b
&& (get_later_stmt (last_a, il_b) == last_a) == a_after_b);
}
/* A subroutine of vect_analyze_data_ref_dependence. Handle
DDR_COULD_BE_INDEPENDENT_P ddr DDR that has a known set of dependence
distances. These distances are conservatively correct but they don't
reflect a guaranteed dependence.
Return true if this function does all the work necessary to avoid
an alias or false if the caller should use the dependence distances
to limit the vectorization factor in the usual way. LOOP_DEPTH is
the depth of the loop described by LOOP_VINFO and the other arguments
are as for vect_analyze_data_ref_dependence. */
static bool
vect_analyze_possibly_independent_ddr (data_dependence_relation *ddr,
loop_vec_info loop_vinfo,
int loop_depth, unsigned int *max_vf)
{
class loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
lambda_vector dist_v;
unsigned int i;
FOR_EACH_VEC_ELT (DDR_DIST_VECTS (ddr), i, dist_v)
{
int dist = dist_v[loop_depth];
if (dist != 0 && !(dist > 0 && DDR_REVERSED_P (ddr)))
{
/* If the user asserted safelen >= DIST consecutive iterations
can be executed concurrently, assume independence.
??? An alternative would be to add the alias check even
in this case, and vectorize the fallback loop with the
maximum VF set to safelen. However, if the user has
explicitly given a length, it's less likely that that
would be a win. */
if (loop->safelen >= 2 && abs_hwi (dist) <= loop->safelen)
{
if ((unsigned int) loop->safelen < *max_vf)
*max_vf = loop->safelen;
LOOP_VINFO_NO_DATA_DEPENDENCIES (loop_vinfo) = false;
continue;
}
/* For dependence distances of 2 or more, we have the option
of limiting VF or checking for an alias at runtime.
Prefer to check at runtime if we can, to avoid limiting
the VF unnecessarily when the bases are in fact independent.
Note that the alias checks will be removed if the VF ends up
being small enough. */
dr_vec_info *dr_info_a = loop_vinfo->lookup_dr (DDR_A (ddr));
dr_vec_info *dr_info_b = loop_vinfo->lookup_dr (DDR_B (ddr));
return (!STMT_VINFO_GATHER_SCATTER_P (dr_info_a->stmt)
&& !STMT_VINFO_GATHER_SCATTER_P (dr_info_b->stmt)
&& vect_mark_for_runtime_alias_test (ddr, loop_vinfo));
}
}
return true;
}
/* Function vect_analyze_data_ref_dependence.
FIXME: I needed to change the sense of the returned flag.
Return FALSE if there (might) exist a dependence between a memory-reference
DRA and a memory-reference DRB. When versioning for alias may check a
dependence at run-time, return TRUE. Adjust *MAX_VF according to
the data dependence. */
static opt_result
vect_analyze_data_ref_dependence (struct data_dependence_relation *ddr,
loop_vec_info loop_vinfo,
unsigned int *max_vf)
{
unsigned int i;
class loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
struct data_reference *dra = DDR_A (ddr);
struct data_reference *drb = DDR_B (ddr);
dr_vec_info *dr_info_a = loop_vinfo->lookup_dr (dra);
dr_vec_info *dr_info_b = loop_vinfo->lookup_dr (drb);
stmt_vec_info stmtinfo_a = dr_info_a->stmt;
stmt_vec_info stmtinfo_b = dr_info_b->stmt;
lambda_vector dist_v;
unsigned int loop_depth;
/* In loop analysis all data references should be vectorizable. */
if (!STMT_VINFO_VECTORIZABLE (stmtinfo_a)
|| !STMT_VINFO_VECTORIZABLE (stmtinfo_b))
gcc_unreachable ();
/* Independent data accesses. */
if (DDR_ARE_DEPENDENT (ddr) == chrec_known)
return opt_result::success ();
if (dra == drb
|| (DR_IS_READ (dra) && DR_IS_READ (drb)))
return opt_result::success ();
/* We do not have to consider dependences between accesses that belong
to the same group, unless the stride could be smaller than the
group size. */
if (DR_GROUP_FIRST_ELEMENT (stmtinfo_a)
&& (DR_GROUP_FIRST_ELEMENT (stmtinfo_a)
== DR_GROUP_FIRST_ELEMENT (stmtinfo_b))
&& !STMT_VINFO_STRIDED_P (stmtinfo_a))
return opt_result::success ();
/* Even if we have an anti-dependence then, as the vectorized loop covers at
least two scalar iterations, there is always also a true dependence.
As the vectorizer does not re-order loads and stores we can ignore
the anti-dependence if TBAA can disambiguate both DRs similar to the
case with known negative distance anti-dependences (positive
distance anti-dependences would violate TBAA constraints). */
if (((DR_IS_READ (dra) && DR_IS_WRITE (drb))
|| (DR_IS_WRITE (dra) && DR_IS_READ (drb)))
&& !alias_sets_conflict_p (get_alias_set (DR_REF (dra)),
get_alias_set (DR_REF (drb))))
return opt_result::success ();
/* Unknown data dependence. */
if (DDR_ARE_DEPENDENT (ddr) == chrec_dont_know)
{
/* If user asserted safelen consecutive iterations can be
executed concurrently, assume independence. */
if (loop->safelen >= 2)
{
if ((unsigned int) loop->safelen < *max_vf)
*max_vf = loop->safelen;
LOOP_VINFO_NO_DATA_DEPENDENCIES (loop_vinfo) = false;
return opt_result::success ();
}
if (STMT_VINFO_GATHER_SCATTER_P (stmtinfo_a)
|| STMT_VINFO_GATHER_SCATTER_P (stmtinfo_b))
return opt_result::failure_at
(stmtinfo_a->stmt,
"versioning for alias not supported for: "
"can't determine dependence between %T and %T\n",
DR_REF (dra), DR_REF (drb));
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, stmtinfo_a->stmt,
"versioning for alias required: "
"can't determine dependence between %T and %T\n",
DR_REF (dra), DR_REF (drb));
/* Add to list of ddrs that need to be tested at run-time. */
return vect_mark_for_runtime_alias_test (ddr, loop_vinfo);
}
/* Known data dependence. */
if (DDR_NUM_DIST_VECTS (ddr) == 0)
{
/* If user asserted safelen consecutive iterations can be
executed concurrently, assume independence. */
if (loop->safelen >= 2)
{
if ((unsigned int) loop->safelen < *max_vf)
*max_vf = loop->safelen;
LOOP_VINFO_NO_DATA_DEPENDENCIES (loop_vinfo) = false;
return opt_result::success ();
}
if (STMT_VINFO_GATHER_SCATTER_P (stmtinfo_a)
|| STMT_VINFO_GATHER_SCATTER_P (stmtinfo_b))
return opt_result::failure_at
(stmtinfo_a->stmt,
"versioning for alias not supported for: "
"bad dist vector for %T and %T\n",
DR_REF (dra), DR_REF (drb));
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, stmtinfo_a->stmt,
"versioning for alias required: "
"bad dist vector for %T and %T\n",
DR_REF (dra), DR_REF (drb));
/* Add to list of ddrs that need to be tested at run-time. */
return vect_mark_for_runtime_alias_test (ddr, loop_vinfo);
}
loop_depth = index_in_loop_nest (loop->num, DDR_LOOP_NEST (ddr));
if (DDR_COULD_BE_INDEPENDENT_P (ddr)
&& vect_analyze_possibly_independent_ddr (ddr, loop_vinfo,
loop_depth, max_vf))
return opt_result::success ();
FOR_EACH_VEC_ELT (DDR_DIST_VECTS (ddr), i, dist_v)
{
int dist = dist_v[loop_depth];
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"dependence distance = %d.\n", dist);
if (dist == 0)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"dependence distance == 0 between %T and %T\n",
DR_REF (dra), DR_REF (drb));
/* When we perform grouped accesses and perform implicit CSE
by detecting equal accesses and doing disambiguation with
runtime alias tests like for
.. = a[i];
.. = a[i+1];
a[i] = ..;
a[i+1] = ..;
*p = ..;
.. = a[i];
.. = a[i+1];
where we will end up loading { a[i], a[i+1] } once, make
sure that inserting group loads before the first load and
stores after the last store will do the right thing.
Similar for groups like
a[i] = ...;
... = a[i];
a[i+1] = ...;
where loads from the group interleave with the store. */
if (!vect_preserves_scalar_order_p (dr_info_a, dr_info_b))
return opt_result::failure_at (stmtinfo_a->stmt,
"READ_WRITE dependence"
" in interleaving.\n");
if (loop->safelen < 2)
{
tree indicator = dr_zero_step_indicator (dra);
if (!indicator || integer_zerop (indicator))
return opt_result::failure_at (stmtinfo_a->stmt,
"access also has a zero step\n");
else if (TREE_CODE (indicator) != INTEGER_CST)
vect_check_nonzero_value (loop_vinfo, indicator);
}
continue;
}
if (dist > 0 && DDR_REVERSED_P (ddr))
{
/* If DDR_REVERSED_P the order of the data-refs in DDR was
reversed (to make distance vector positive), and the actual
distance is negative. */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"dependence distance negative.\n");
/* When doing outer loop vectorization, we need to check if there is
a backward dependence at the inner loop level if the dependence
at the outer loop is reversed. See PR81740. */
if (nested_in_vect_loop_p (loop, stmtinfo_a)
|| nested_in_vect_loop_p (loop, stmtinfo_b))
{
unsigned inner_depth = index_in_loop_nest (loop->inner->num,
DDR_LOOP_NEST (ddr));
if (dist_v[inner_depth] < 0)
return opt_result::failure_at (stmtinfo_a->stmt,
"not vectorized, dependence "
"between data-refs %T and %T\n",
DR_REF (dra), DR_REF (drb));
}
/* Record a negative dependence distance to later limit the
amount of stmt copying / unrolling we can perform.
Only need to handle read-after-write dependence. */
if (DR_IS_READ (drb)
&& (STMT_VINFO_MIN_NEG_DIST (stmtinfo_b) == 0
|| STMT_VINFO_MIN_NEG_DIST (stmtinfo_b) > (unsigned)dist))
STMT_VINFO_MIN_NEG_DIST (stmtinfo_b) = dist;
continue;
}
unsigned int abs_dist = abs (dist);
if (abs_dist >= 2 && abs_dist < *max_vf)
{
/* The dependence distance requires reduction of the maximal
vectorization factor. */
*max_vf = abs_dist;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"adjusting maximal vectorization factor to %i\n",
*max_vf);
}
if (abs_dist >= *max_vf)
{
/* Dependence distance does not create dependence, as far as
vectorization is concerned, in this case. */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"dependence distance >= VF.\n");
continue;
}
return opt_result::failure_at (stmtinfo_a->stmt,
"not vectorized, possible dependence "
"between data-refs %T and %T\n",
DR_REF (dra), DR_REF (drb));
}
return opt_result::success ();
}
/* Function vect_analyze_data_ref_dependences.
Examine all the data references in the loop, and make sure there do not
exist any data dependences between them. Set *MAX_VF according to
the maximum vectorization factor the data dependences allow. */
opt_result
vect_analyze_data_ref_dependences (loop_vec_info loop_vinfo,
unsigned int *max_vf)
{
unsigned int i;
struct data_dependence_relation *ddr;
DUMP_VECT_SCOPE ("vect_analyze_data_ref_dependences");
if (!LOOP_VINFO_DDRS (loop_vinfo).exists ())
{
LOOP_VINFO_DDRS (loop_vinfo)
.create (LOOP_VINFO_DATAREFS (loop_vinfo).length ()
* LOOP_VINFO_DATAREFS (loop_vinfo).length ());
/* We need read-read dependences to compute
STMT_VINFO_SAME_ALIGN_REFS. */
bool res = compute_all_dependences (LOOP_VINFO_DATAREFS (loop_vinfo),
&LOOP_VINFO_DDRS (loop_vinfo),
LOOP_VINFO_LOOP_NEST (loop_vinfo),
true);
gcc_assert (res);
}
LOOP_VINFO_NO_DATA_DEPENDENCIES (loop_vinfo) = true;
/* For epilogues we either have no aliases or alias versioning
was applied to original loop. Therefore we may just get max_vf
using VF of original loop. */
if (LOOP_VINFO_EPILOGUE_P (loop_vinfo))
*max_vf = LOOP_VINFO_ORIG_MAX_VECT_FACTOR (loop_vinfo);
else
FOR_EACH_VEC_ELT (LOOP_VINFO_DDRS (loop_vinfo), i, ddr)
{
opt_result res
= vect_analyze_data_ref_dependence (ddr, loop_vinfo, max_vf);
if (!res)
return res;
}
return opt_result::success ();
}
/* Function vect_slp_analyze_data_ref_dependence.
Return TRUE if there (might) exist a dependence between a memory-reference
DRA and a memory-reference DRB for VINFO. When versioning for alias
may check a dependence at run-time, return FALSE. Adjust *MAX_VF
according to the data dependence. */
static bool
vect_slp_analyze_data_ref_dependence (vec_info *vinfo,
struct data_dependence_relation *ddr)
{
struct data_reference *dra = DDR_A (ddr);
struct data_reference *drb = DDR_B (ddr);
dr_vec_info *dr_info_a = vinfo->lookup_dr (dra);
dr_vec_info *dr_info_b = vinfo->lookup_dr (drb);
/* We need to check dependences of statements marked as unvectorizable
as well, they still can prohibit vectorization. */
/* Independent data accesses. */
if (DDR_ARE_DEPENDENT (ddr) == chrec_known)
return false;
if (dra == drb)
return false;
/* Read-read is OK. */
if (DR_IS_READ (dra) && DR_IS_READ (drb))
return false;
/* If dra and drb are part of the same interleaving chain consider
them independent. */
if (STMT_VINFO_GROUPED_ACCESS (dr_info_a->stmt)
&& (DR_GROUP_FIRST_ELEMENT (dr_info_a->stmt)
== DR_GROUP_FIRST_ELEMENT (dr_info_b->stmt)))
return false;
/* Unknown data dependence. */
if (DDR_ARE_DEPENDENT (ddr) == chrec_dont_know)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"can't determine dependence between %T and %T\n",
DR_REF (dra), DR_REF (drb));
}
else if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"determined dependence between %T and %T\n",
DR_REF (dra), DR_REF (drb));
return true;
}
/* Analyze dependences involved in the transform of SLP NODE. STORES
contain the vector of scalar stores of this instance if we are
disambiguating the loads. */
static bool
vect_slp_analyze_node_dependences (slp_instance instance, slp_tree node,
vec<stmt_vec_info> stores,
stmt_vec_info last_store_info)
{
/* This walks over all stmts involved in the SLP load/store done
in NODE verifying we can sink them up to the last stmt in the
group. */
stmt_vec_info last_access_info = vect_find_last_scalar_stmt_in_slp (node);
vec_info *vinfo = last_access_info->vinfo;
for (unsigned k = 0; k < SLP_INSTANCE_GROUP_SIZE (instance); ++k)
{
stmt_vec_info access_info = SLP_TREE_SCALAR_STMTS (node)[k];
if (access_info == last_access_info)
continue;
data_reference *dr_a = STMT_VINFO_DATA_REF (access_info);
ao_ref ref;
bool ref_initialized_p = false;
for (gimple_stmt_iterator gsi = gsi_for_stmt (access_info->stmt);
gsi_stmt (gsi) != last_access_info->stmt; gsi_next (&gsi))
{
gimple *stmt = gsi_stmt (gsi);
if (! gimple_vuse (stmt)
|| (DR_IS_READ (dr_a) && ! gimple_vdef (stmt)))
continue;
/* If we couldn't record a (single) data reference for this
stmt we have to resort to the alias oracle. */
stmt_vec_info stmt_info = vinfo->lookup_stmt (stmt);
data_reference *dr_b = STMT_VINFO_DATA_REF (stmt_info);
if (!dr_b)
{
/* We are moving a store or sinking a load - this means
we cannot use TBAA for disambiguation. */
if (!ref_initialized_p)
ao_ref_init (&ref, DR_REF (dr_a));
if (stmt_may_clobber_ref_p_1 (stmt, &ref, false)
|| ref_maybe_used_by_stmt_p (stmt, &ref, false))
return false;
continue;
}
bool dependent = false;
/* If we run into a store of this same instance (we've just
marked those) then delay dependence checking until we run
into the last store because this is where it will have
been sunk to (and we verify if we can do that as well). */
if (gimple_visited_p (stmt))
{
if (stmt_info != last_store_info)
continue;
unsigned i;
stmt_vec_info store_info;
FOR_EACH_VEC_ELT (stores, i, store_info)
{
data_reference *store_dr = STMT_VINFO_DATA_REF (store_info);
ddr_p ddr = initialize_data_dependence_relation
(dr_a, store_dr, vNULL);
dependent
= vect_slp_analyze_data_ref_dependence (vinfo, ddr);
free_dependence_relation (ddr);
if (dependent)
break;
}
}
else
{
ddr_p ddr = initialize_data_dependence_relation (dr_a,
dr_b, vNULL);
dependent = vect_slp_analyze_data_ref_dependence (vinfo, ddr);
free_dependence_relation (ddr);
}
if (dependent)
return false;
}
}
return true;
}
/* Function vect_analyze_data_ref_dependences.
Examine all the data references in the basic-block, and make sure there
do not exist any data dependences between them. Set *MAX_VF according to
the maximum vectorization factor the data dependences allow. */
bool
vect_slp_analyze_instance_dependence (slp_instance instance)
{
DUMP_VECT_SCOPE ("vect_slp_analyze_instance_dependence");
/* The stores of this instance are at the root of the SLP tree. */
slp_tree store = SLP_INSTANCE_TREE (instance);
if (! STMT_VINFO_DATA_REF (SLP_TREE_SCALAR_STMTS (store)[0]))
store = NULL;
/* Verify we can sink stores to the vectorized stmt insert location. */
stmt_vec_info last_store_info = NULL;
if (store)
{
if (! vect_slp_analyze_node_dependences (instance, store, vNULL, NULL))
return false;
/* Mark stores in this instance and remember the last one. */
last_store_info = vect_find_last_scalar_stmt_in_slp (store);
for (unsigned k = 0; k < SLP_INSTANCE_GROUP_SIZE (instance); ++k)
gimple_set_visited (SLP_TREE_SCALAR_STMTS (store)[k]->stmt, true);
}
bool res = true;
/* Verify we can sink loads to the vectorized stmt insert location,
special-casing stores of this instance. */
slp_tree load;
unsigned int i;
FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (instance), i, load)
if (! vect_slp_analyze_node_dependences (instance, load,
store
? SLP_TREE_SCALAR_STMTS (store)
: vNULL, last_store_info))
{
res = false;
break;
}
/* Unset the visited flag. */
if (store)
for (unsigned k = 0; k < SLP_INSTANCE_GROUP_SIZE (instance); ++k)
gimple_set_visited (SLP_TREE_SCALAR_STMTS (store)[k]->stmt, false);
return res;
}
/* Record the base alignment guarantee given by DRB, which occurs
in STMT_INFO. */
static void
vect_record_base_alignment (stmt_vec_info stmt_info,
innermost_loop_behavior *drb)
{
vec_info *vinfo = stmt_info->vinfo;
bool existed;
innermost_loop_behavior *&entry
= vinfo->base_alignments.get_or_insert (drb->base_address, &existed);
if (!existed || entry->base_alignment < drb->base_alignment)
{
entry = drb;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"recording new base alignment for %T\n"
" alignment: %d\n"
" misalignment: %d\n"
" based on: %G",
drb->base_address,
drb->base_alignment,
drb->base_misalignment,
stmt_info->stmt);
}
}
/* If the region we're going to vectorize is reached, all unconditional
data references occur at least once. We can therefore pool the base
alignment guarantees from each unconditional reference. Do this by
going through all the data references in VINFO and checking whether
the containing statement makes the reference unconditionally. If so,
record the alignment of the base address in VINFO so that it can be
used for all other references with the same base. */
void
vect_record_base_alignments (vec_info *vinfo)
{
loop_vec_info loop_vinfo = dyn_cast <loop_vec_info> (vinfo);
class loop *loop = loop_vinfo ? LOOP_VINFO_LOOP (loop_vinfo) : NULL;
data_reference *dr;
unsigned int i;
FOR_EACH_VEC_ELT (vinfo->shared->datarefs, i, dr)
{
dr_vec_info *dr_info = vinfo->lookup_dr (dr);
stmt_vec_info stmt_info = dr_info->stmt;
if (!DR_IS_CONDITIONAL_IN_STMT (dr)
&& STMT_VINFO_VECTORIZABLE (stmt_info)
&& !STMT_VINFO_GATHER_SCATTER_P (stmt_info))
{
vect_record_base_alignment (stmt_info, &DR_INNERMOST (dr));
/* If DR is nested in the loop that is being vectorized, we can also
record the alignment of the base wrt the outer loop. */
if (loop && nested_in_vect_loop_p (loop, stmt_info))
vect_record_base_alignment
(stmt_info, &STMT_VINFO_DR_WRT_VEC_LOOP (stmt_info));
}
}
}
/* Return the target alignment for the vectorized form of DR_INFO. */
static poly_uint64
vect_calculate_target_alignment (dr_vec_info *dr_info)
{
tree vectype = STMT_VINFO_VECTYPE (dr_info->stmt);
return targetm.vectorize.preferred_vector_alignment (vectype);
}
/* Function vect_compute_data_ref_alignment
Compute the misalignment of the data reference DR_INFO.
Output:
1. DR_MISALIGNMENT (DR_INFO) is defined.
FOR NOW: No analysis is actually performed. Misalignment is calculated
only for trivial cases. TODO. */
static void
vect_compute_data_ref_alignment (dr_vec_info *dr_info)
{
stmt_vec_info stmt_info = dr_info->stmt;
vec_base_alignments *base_alignments = &stmt_info->vinfo->base_alignments;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
class loop *loop = NULL;
tree ref = DR_REF (dr_info->dr);
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"vect_compute_data_ref_alignment:\n");
if (loop_vinfo)
loop = LOOP_VINFO_LOOP (loop_vinfo);
/* Initialize misalignment to unknown. */
SET_DR_MISALIGNMENT (dr_info, DR_MISALIGNMENT_UNKNOWN);
if (STMT_VINFO_GATHER_SCATTER_P (stmt_info))
return;
innermost_loop_behavior *drb = vect_dr_behavior (dr_info);
bool step_preserves_misalignment_p;
poly_uint64 vector_alignment
= exact_div (vect_calculate_target_alignment (dr_info), BITS_PER_UNIT);
DR_TARGET_ALIGNMENT (dr_info) = vector_alignment;
/* If the main loop has peeled for alignment we have no way of knowing
whether the data accesses in the epilogues are aligned. We can't at
compile time answer the question whether we have entered the main loop or
not. Fixes PR 92351. */
if (loop_vinfo)
{
loop_vec_info orig_loop_vinfo = LOOP_VINFO_ORIG_LOOP_INFO (loop_vinfo);
if (orig_loop_vinfo
&& LOOP_VINFO_PEELING_FOR_ALIGNMENT (orig_loop_vinfo) != 0)
return;
}
unsigned HOST_WIDE_INT vect_align_c;
if (!vector_alignment.is_constant (&vect_align_c))
return;
/* No step for BB vectorization. */
if (!loop)
{
gcc_assert (integer_zerop (drb->step));
step_preserves_misalignment_p = true;
}
/* In case the dataref is in an inner-loop of the loop that is being
vectorized (LOOP), we use the base and misalignment information
relative to the outer-loop (LOOP). This is ok only if the misalignment
stays the same throughout the execution of the inner-loop, which is why
we have to check that the stride of the dataref in the inner-loop evenly
divides by the vector alignment. */
else if (nested_in_vect_loop_p (loop, stmt_info))
{
step_preserves_misalignment_p
= (DR_STEP_ALIGNMENT (dr_info->dr) % vect_align_c) == 0;
if (dump_enabled_p ())
{
if (step_preserves_misalignment_p)
dump_printf_loc (MSG_NOTE, vect_location,
"inner step divides the vector alignment.\n");
else
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"inner step doesn't divide the vector"
" alignment.\n");
}
}
/* Similarly we can only use base and misalignment information relative to
an innermost loop if the misalignment stays the same throughout the
execution of the loop. As above, this is the case if the stride of
the dataref evenly divides by the alignment. */
else
{
poly_uint64 vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
step_preserves_misalignment_p
= multiple_p (DR_STEP_ALIGNMENT (dr_info->dr) * vf, vect_align_c);
if (!step_preserves_misalignment_p && dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"step doesn't divide the vector alignment.\n");
}
unsigned int base_alignment = drb->base_alignment;
unsigned int base_misalignment = drb->base_misalignment;
/* Calculate the maximum of the pooled base address alignment and the
alignment that we can compute for DR itself. */
innermost_loop_behavior **entry = base_alignments->get (drb->base_address);
if (entry && base_alignment < (*entry)->base_alignment)
{
base_alignment = (*entry)->base_alignment;
base_misalignment = (*entry)->base_misalignment;
}
if (drb->offset_alignment < vect_align_c
|| !step_preserves_misalignment_p
/* We need to know whether the step wrt the vectorized loop is
negative when computing the starting misalignment below. */
|| TREE_CODE (drb->step) != INTEGER_CST)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"Unknown alignment for access: %T\n", ref);
return;
}
if (base_alignment < vect_align_c)
{
unsigned int max_alignment;
tree base = get_base_for_alignment (drb->base_address, &max_alignment);
if (max_alignment < vect_align_c
|| !vect_can_force_dr_alignment_p (base,
vect_align_c * BITS_PER_UNIT))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"can't force alignment of ref: %T\n", ref);
return;
}
/* Force the alignment of the decl.
NOTE: This is the only change to the code we make during
the analysis phase, before deciding to vectorize the loop. */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"force alignment of %T\n", ref);
dr_info->base_decl = base;
dr_info->base_misaligned = true;
base_misalignment = 0;
}
poly_int64 misalignment
= base_misalignment + wi::to_poly_offset (drb->init).force_shwi ();
/* If this is a backward running DR then first access in the larger
vectype actually is N-1 elements before the address in the DR.
Adjust misalign accordingly. */
if (tree_int_cst_sgn (drb->step) < 0)
/* PLUS because STEP is negative. */
misalignment += ((TYPE_VECTOR_SUBPARTS (vectype) - 1)
* -TREE_INT_CST_LOW (TYPE_SIZE_UNIT (TREE_TYPE (vectype))));
unsigned int const_misalignment;
if (!known_misalignment (misalignment, vect_align_c, &const_misalignment))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"Non-constant misalignment for access: %T\n", ref);
return;
}
SET_DR_MISALIGNMENT (dr_info, const_misalignment);
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"misalign = %d bytes of ref %T\n",
DR_MISALIGNMENT (dr_info), ref);
return;
}
/* Function vect_update_misalignment_for_peel.
Sets DR_INFO's misalignment
- to 0 if it has the same alignment as DR_PEEL_INFO,
- to the misalignment computed using NPEEL if DR_INFO's salignment is known,
- to -1 (unknown) otherwise.
DR_INFO - the data reference whose misalignment is to be adjusted.
DR_PEEL_INFO - the data reference whose misalignment is being made
zero in the vector loop by the peel.
NPEEL - the number of iterations in the peel loop if the misalignment
of DR_PEEL_INFO is known at compile time. */
static void
vect_update_misalignment_for_peel (dr_vec_info *dr_info,
dr_vec_info *dr_peel_info, int npeel)
{
unsigned int i;
vec<dr_p> same_aligned_drs;
struct data_reference *current_dr;
stmt_vec_info peel_stmt_info = dr_peel_info->stmt;
/* It can be assumed that if dr_info has the same alignment as dr_peel,
it is aligned in the vector loop. */
same_aligned_drs = STMT_VINFO_SAME_ALIGN_REFS (peel_stmt_info);
FOR_EACH_VEC_ELT (same_aligned_drs, i, current_dr)
{
if (current_dr != dr_info->dr)
continue;
gcc_assert (!known_alignment_for_access_p (dr_info)
|| !known_alignment_for_access_p (dr_peel_info)
|| (DR_MISALIGNMENT (dr_info)
== DR_MISALIGNMENT (dr_peel_info)));
SET_DR_MISALIGNMENT (dr_info, 0);
return;
}
unsigned HOST_WIDE_INT alignment;
if (DR_TARGET_ALIGNMENT (dr_info).is_constant (&alignment)
&& known_alignment_for_access_p (dr_info)
&& known_alignment_for_access_p (dr_peel_info))
{
int misal = DR_MISALIGNMENT (dr_info);
misal += npeel * TREE_INT_CST_LOW (DR_STEP (dr_info->dr));
misal &= alignment - 1;
SET_DR_MISALIGNMENT (dr_info, misal);
return;
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "Setting misalignment " \
"to unknown (-1).\n");
SET_DR_MISALIGNMENT (dr_info, DR_MISALIGNMENT_UNKNOWN);
}
/* Function verify_data_ref_alignment
Return TRUE if DR_INFO can be handled with respect to alignment. */
static opt_result
verify_data_ref_alignment (dr_vec_info *dr_info)
{
enum dr_alignment_support supportable_dr_alignment
= vect_supportable_dr_alignment (dr_info, false);
if (!supportable_dr_alignment)
return opt_result::failure_at
(dr_info->stmt->stmt,
DR_IS_READ (dr_info->dr)
? "not vectorized: unsupported unaligned load: %T\n"
: "not vectorized: unsupported unaligned store: %T\n",
DR_REF (dr_info->dr));
if (supportable_dr_alignment != dr_aligned && dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Vectorizing an unaligned access.\n");
return opt_result::success ();
}
/* Function vect_verify_datarefs_alignment
Return TRUE if all data references in the loop can be
handled with respect to alignment. */
opt_result
vect_verify_datarefs_alignment (loop_vec_info vinfo)
{
vec<data_reference_p> datarefs = vinfo->shared->datarefs;
struct data_reference *dr;
unsigned int i;
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
dr_vec_info *dr_info = vinfo->lookup_dr (dr);
stmt_vec_info stmt_info = dr_info->stmt;
if (!STMT_VINFO_RELEVANT_P (stmt_info))
continue;
/* For interleaving, only the alignment of the first access matters. */
if (STMT_VINFO_GROUPED_ACCESS (stmt_info)
&& DR_GROUP_FIRST_ELEMENT (stmt_info) != stmt_info)
continue;
/* Strided accesses perform only component accesses, alignment is
irrelevant for them. */
if (STMT_VINFO_STRIDED_P (stmt_info)
&& !STMT_VINFO_GROUPED_ACCESS (stmt_info))
continue;
opt_result res = verify_data_ref_alignment (dr_info);
if (!res)
return res;
}
return opt_result::success ();
}
/* Given an memory reference EXP return whether its alignment is less
than its size. */
static bool
not_size_aligned (tree exp)
{
if (!tree_fits_uhwi_p (TYPE_SIZE (TREE_TYPE (exp))))
return true;
return (tree_to_uhwi (TYPE_SIZE (TREE_TYPE (exp)))
> get_object_alignment (exp));
}
/* Function vector_alignment_reachable_p
Return true if vector alignment for DR_INFO is reachable by peeling
a few loop iterations. Return false otherwise. */
static bool
vector_alignment_reachable_p (dr_vec_info *dr_info)
{
stmt_vec_info stmt_info = dr_info->stmt;
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
if (STMT_VINFO_GROUPED_ACCESS (stmt_info))
{
/* For interleaved access we peel only if number of iterations in
the prolog loop ({VF - misalignment}), is a multiple of the
number of the interleaved accesses. */
int elem_size, mis_in_elements;
/* FORNOW: handle only known alignment. */
if (!known_alignment_for_access_p (dr_info))
return false;
poly_uint64 nelements = TYPE_VECTOR_SUBPARTS (vectype);
poly_uint64 vector_size = GET_MODE_SIZE (TYPE_MODE (vectype));
elem_size = vector_element_size (vector_size, nelements);
mis_in_elements = DR_MISALIGNMENT (dr_info) / elem_size;
if (!multiple_p (nelements - mis_in_elements, DR_GROUP_SIZE (stmt_info)))
return false;
}
/* If misalignment is known at the compile time then allow peeling
only if natural alignment is reachable through peeling. */
if (known_alignment_for_access_p (dr_info) && !aligned_access_p (dr_info))
{
HOST_WIDE_INT elmsize =
int_cst_value (TYPE_SIZE_UNIT (TREE_TYPE (vectype)));
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"data size = %wd. misalignment = %d.\n", elmsize,
DR_MISALIGNMENT (dr_info));
}
if (DR_MISALIGNMENT (dr_info) % elmsize)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"data size does not divide the misalignment.\n");
return false;
}
}
if (!known_alignment_for_access_p (dr_info))
{
tree type = TREE_TYPE (DR_REF (dr_info->dr));
bool is_packed = not_size_aligned (DR_REF (dr_info->dr));
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"Unknown misalignment, %snaturally aligned\n",
is_packed ? "not " : "");
return targetm.vectorize.vector_alignment_reachable (type, is_packed);
}
return true;
}
/* Calculate the cost of the memory access represented by DR_INFO. */
static void
vect_get_data_access_cost (dr_vec_info *dr_info,
unsigned int *inside_cost,
unsigned int *outside_cost,
stmt_vector_for_cost *body_cost_vec,
stmt_vector_for_cost *prologue_cost_vec)
{
stmt_vec_info stmt_info = dr_info->stmt;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
int ncopies;
if (PURE_SLP_STMT (stmt_info))
ncopies = 1;
else
ncopies = vect_get_num_copies (loop_vinfo, STMT_VINFO_VECTYPE (stmt_info));
if (DR_IS_READ (dr_info->dr))
vect_get_load_cost (stmt_info, ncopies, true, inside_cost, outside_cost,
prologue_cost_vec, body_cost_vec, false);
else
vect_get_store_cost (stmt_info, ncopies, inside_cost, body_cost_vec);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"vect_get_data_access_cost: inside_cost = %d, "
"outside_cost = %d.\n", *inside_cost, *outside_cost);
}
typedef struct _vect_peel_info
{
dr_vec_info *dr_info;
int npeel;
unsigned int count;
} *vect_peel_info;
typedef struct _vect_peel_extended_info
{
struct _vect_peel_info peel_info;
unsigned int inside_cost;
unsigned int outside_cost;
} *vect_peel_extended_info;
/* Peeling hashtable helpers. */
struct peel_info_hasher : free_ptr_hash <_vect_peel_info>
{
static inline hashval_t hash (const _vect_peel_info *);
static inline bool equal (const _vect_peel_info *, const _vect_peel_info *);
};
inline hashval_t
peel_info_hasher::hash (const _vect_peel_info *peel_info)
{
return (hashval_t) peel_info->npeel;
}
inline bool
peel_info_hasher::equal (const _vect_peel_info *a, const _vect_peel_info *b)
{
return (a->npeel == b->npeel);
}
/* Insert DR_INFO into peeling hash table with NPEEL as key. */
static void
vect_peeling_hash_insert (hash_table<peel_info_hasher> *peeling_htab,
loop_vec_info loop_vinfo, dr_vec_info *dr_info,
int npeel)
{
struct _vect_peel_info elem, *slot;
_vect_peel_info **new_slot;
bool supportable_dr_alignment
= vect_supportable_dr_alignment (dr_info, true);
elem.npeel = npeel;
slot = peeling_htab->find (&elem);
if (slot)
slot->count++;
else
{
slot = XNEW (struct _vect_peel_info);
slot->npeel = npeel;
slot->dr_info = dr_info;
slot->count = 1;
new_slot = peeling_htab->find_slot (slot, INSERT);
*new_slot = slot;
}
if (!supportable_dr_alignment
&& unlimited_cost_model (LOOP_VINFO_LOOP (loop_vinfo)))
slot->count += VECT_MAX_COST;
}
/* Traverse peeling hash table to find peeling option that aligns maximum
number of data accesses. */
int
vect_peeling_hash_get_most_frequent (_vect_peel_info **slot,
_vect_peel_extended_info *max)
{
vect_peel_info elem = *slot;
if (elem->count > max->peel_info.count
|| (elem->count == max->peel_info.count
&& max->peel_info.npeel > elem->npeel))
{
max->peel_info.npeel = elem->npeel;
max->peel_info.count = elem->count;
max->peel_info.dr_info = elem->dr_info;
}
return 1;
}
/* Get the costs of peeling NPEEL iterations for LOOP_VINFO, checking
data access costs for all data refs. If UNKNOWN_MISALIGNMENT is true,
we assume DR0_INFO's misalignment will be zero after peeling. */
static void
vect_get_peeling_costs_all_drs (loop_vec_info loop_vinfo,
dr_vec_info *dr0_info,
unsigned int *inside_cost,
unsigned int *outside_cost,
stmt_vector_for_cost *body_cost_vec,
stmt_vector_for_cost *prologue_cost_vec,
unsigned int npeel,
bool unknown_misalignment)
{
vec<data_reference_p> datarefs = LOOP_VINFO_DATAREFS (loop_vinfo);
unsigned i;
data_reference *dr;
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
dr_vec_info *dr_info = loop_vinfo->lookup_dr (dr);
stmt_vec_info stmt_info = dr_info->stmt;
if (!STMT_VINFO_RELEVANT_P (stmt_info))
continue;
/* For interleaving, only the alignment of the first access
matters. */
if (STMT_VINFO_GROUPED_ACCESS (stmt_info)
&& DR_GROUP_FIRST_ELEMENT (stmt_info) != stmt_info)
continue;
/* Strided accesses perform only component accesses, alignment is
irrelevant for them. */
if (STMT_VINFO_STRIDED_P (stmt_info)
&& !STMT_VINFO_GROUPED_ACCESS (stmt_info))
continue;
int save_misalignment;
save_misalignment = DR_MISALIGNMENT (dr_info);
if (npeel == 0)
;
else if (unknown_misalignment && dr_info == dr0_info)
SET_DR_MISALIGNMENT (dr_info, 0);
else
vect_update_misalignment_for_peel (dr_info, dr0_info, npeel);
vect_get_data_access_cost (dr_info, inside_cost, outside_cost,
body_cost_vec, prologue_cost_vec);
SET_DR_MISALIGNMENT (dr_info, save_misalignment);
}
}
/* Traverse peeling hash table and calculate cost for each peeling option.
Find the one with the lowest cost. */
int
vect_peeling_hash_get_lowest_cost (_vect_peel_info **slot,
_vect_peel_extended_info *min)
{
vect_peel_info elem = *slot;
int dummy;
unsigned int inside_cost = 0, outside_cost = 0;
stmt_vec_info stmt_info = elem->dr_info->stmt;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
stmt_vector_for_cost prologue_cost_vec, body_cost_vec,
epilogue_cost_vec;
prologue_cost_vec.create (2);
body_cost_vec.create (2);
epilogue_cost_vec.create (2);
vect_get_peeling_costs_all_drs (loop_vinfo, elem->dr_info, &inside_cost,
&outside_cost, &body_cost_vec,
&prologue_cost_vec, elem->npeel, false);
body_cost_vec.release ();
outside_cost += vect_get_known_peeling_cost
(loop_vinfo, elem->npeel, &dummy,
&LOOP_VINFO_SCALAR_ITERATION_COST (loop_vinfo),
&prologue_cost_vec, &epilogue_cost_vec);
/* Prologue and epilogue costs are added to the target model later.
These costs depend only on the scalar iteration cost, the
number of peeling iterations finally chosen, and the number of
misaligned statements. So discard the information found here. */
prologue_cost_vec.release ();
epilogue_cost_vec.release ();
if (inside_cost < min->inside_cost
|| (inside_cost == min->inside_cost
&& outside_cost < min->outside_cost))
{
min->inside_cost = inside_cost;
min->outside_cost = outside_cost;
min->peel_info.dr_info = elem->dr_info;
min->peel_info.npeel = elem->npeel;
min->peel_info.count = elem->count;
}
return 1;
}
/* Choose best peeling option by traversing peeling hash table and either
choosing an option with the lowest cost (if cost model is enabled) or the
option that aligns as many accesses as possible. */
static struct _vect_peel_extended_info
vect_peeling_hash_choose_best_peeling (hash_table<peel_info_hasher> *peeling_htab,
loop_vec_info loop_vinfo)
{
struct _vect_peel_extended_info res;
res.peel_info.dr_info = NULL;
if (!unlimited_cost_model (LOOP_VINFO_LOOP (loop_vinfo)))
{
res.inside_cost = INT_MAX;
res.outside_cost = INT_MAX;
peeling_htab->traverse <_vect_peel_extended_info *,
vect_peeling_hash_get_lowest_cost> (&res);
}
else
{
res.peel_info.count = 0;
peeling_htab->traverse <_vect_peel_extended_info *,
vect_peeling_hash_get_most_frequent> (&res);
res.inside_cost = 0;
res.outside_cost = 0;
}
return res;
}
/* Return true if the new peeling NPEEL is supported. */
static bool
vect_peeling_supportable (loop_vec_info loop_vinfo, dr_vec_info *dr0_info,
unsigned npeel)
{
unsigned i;
struct data_reference *dr = NULL;
vec<data_reference_p> datarefs = LOOP_VINFO_DATAREFS (loop_vinfo);
enum dr_alignment_support supportable_dr_alignment;
/* Ensure that all data refs can be vectorized after the peel. */
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
int save_misalignment;
if (dr == dr0_info->dr)
continue;
dr_vec_info *dr_info = loop_vinfo->lookup_dr (dr);
stmt_vec_info stmt_info = dr_info->stmt;
/* For interleaving, only the alignment of the first access
matters. */
if (STMT_VINFO_GROUPED_ACCESS (stmt_info)
&& DR_GROUP_FIRST_ELEMENT (stmt_info) != stmt_info)
continue;
/* Strided accesses perform only component accesses, alignment is
irrelevant for them. */
if (STMT_VINFO_STRIDED_P (stmt_info)
&& !STMT_VINFO_GROUPED_ACCESS (stmt_info))
continue;
save_misalignment = DR_MISALIGNMENT (dr_info);
vect_update_misalignment_for_peel (dr_info, dr0_info, npeel);
supportable_dr_alignment
= vect_supportable_dr_alignment (dr_info, false);
SET_DR_MISALIGNMENT (dr_info, save_misalignment);
if (!supportable_dr_alignment)
return false;
}
return true;
}
/* Function vect_enhance_data_refs_alignment
This pass will use loop versioning and loop peeling in order to enhance
the alignment of data references in the loop.
FOR NOW: we assume that whatever versioning/peeling takes place, only the
original loop is to be vectorized. Any other loops that are created by
the transformations performed in this pass - are not supposed to be
vectorized. This restriction will be relaxed.
This pass will require a cost model to guide it whether to apply peeling
or versioning or a combination of the two. For example, the scheme that
intel uses when given a loop with several memory accesses, is as follows:
choose one memory access ('p') which alignment you want to force by doing
peeling. Then, either (1) generate a loop in which 'p' is aligned and all
other accesses are not necessarily aligned, or (2) use loop versioning to
generate one loop in which all accesses are aligned, and another loop in
which only 'p' is necessarily aligned.
("Automatic Intra-Register Vectorization for the Intel Architecture",
Aart J.C. Bik, Milind Girkar, Paul M. Grey and Ximmin Tian, International
Journal of Parallel Programming, Vol. 30, No. 2, April 2002.)
Devising a cost model is the most critical aspect of this work. It will
guide us on which access to peel for, whether to use loop versioning, how
many versions to create, etc. The cost model will probably consist of
generic considerations as well as target specific considerations (on
powerpc for example, misaligned stores are more painful than misaligned
loads).
Here are the general steps involved in alignment enhancements:
-- original loop, before alignment analysis:
for (i=0; i<N; i++){
x = q[i]; # DR_MISALIGNMENT(q) = unknown
p[i] = y; # DR_MISALIGNMENT(p) = unknown
}
-- After vect_compute_data_refs_alignment:
for (i=0; i<N; i++){
x = q[i]; # DR_MISALIGNMENT(q) = 3
p[i] = y; # DR_MISALIGNMENT(p) = unknown
}
-- Possibility 1: we do loop versioning:
if (p is aligned) {
for (i=0; i<N; i++){ # loop 1A
x = q[i]; # DR_MISALIGNMENT(q) = 3
p[i] = y; # DR_MISALIGNMENT(p) = 0
}
}
else {
for (i=0; i<N; i++){ # loop 1B
x = q[i]; # DR_MISALIGNMENT(q) = 3
p[i] = y; # DR_MISALIGNMENT(p) = unaligned
}
}
-- Possibility 2: we do loop peeling:
for (i = 0; i < 3; i++){ # (scalar loop, not to be vectorized).
x = q[i];
p[i] = y;
}
for (i = 3; i < N; i++){ # loop 2A
x = q[i]; # DR_MISALIGNMENT(q) = 0
p[i] = y; # DR_MISALIGNMENT(p) = unknown
}
-- Possibility 3: combination of loop peeling and versioning:
for (i = 0; i < 3; i++){ # (scalar loop, not to be vectorized).
x = q[i];
p[i] = y;
}
if (p is aligned) {
for (i = 3; i<N; i++){ # loop 3A
x = q[i]; # DR_MISALIGNMENT(q) = 0
p[i] = y; # DR_MISALIGNMENT(p) = 0
}
}
else {
for (i = 3; i<N; i++){ # loop 3B
x = q[i]; # DR_MISALIGNMENT(q) = 0
p[i] = y; # DR_MISALIGNMENT(p) = unaligned
}
}
These loops are later passed to loop_transform to be vectorized. The
vectorizer will use the alignment information to guide the transformation
(whether to generate regular loads/stores, or with special handling for
misalignment). */
opt_result
vect_enhance_data_refs_alignment (loop_vec_info loop_vinfo)
{
vec<data_reference_p> datarefs = LOOP_VINFO_DATAREFS (loop_vinfo);
class loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
enum dr_alignment_support supportable_dr_alignment;
dr_vec_info *first_store = NULL;
dr_vec_info *dr0_info = NULL;
struct data_reference *dr;
unsigned int i, j;
bool do_peeling = false;
bool do_versioning = false;
unsigned int npeel = 0;
bool one_misalignment_known = false;
bool one_misalignment_unknown = false;
bool one_dr_unsupportable = false;
dr_vec_info *unsupportable_dr_info = NULL;
poly_uint64 vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
unsigned possible_npeel_number = 1;
tree vectype;
unsigned int mis, same_align_drs_max = 0;
hash_table<peel_info_hasher> peeling_htab (1);
DUMP_VECT_SCOPE ("vect_enhance_data_refs_alignment");
/* Reset data so we can safely be called multiple times. */
LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).truncate (0);
LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) = 0;
/* While cost model enhancements are expected in the future, the high level
view of the code at this time is as follows:
A) If there is a misaligned access then see if peeling to align
this access can make all data references satisfy
vect_supportable_dr_alignment. If so, update data structures
as needed and return true.
B) If peeling wasn't possible and there is a data reference with an
unknown misalignment that does not satisfy vect_supportable_dr_alignment
then see if loop versioning checks can be used to make all data
references satisfy vect_supportable_dr_alignment. If so, update
data structures as needed and return true.
C) If neither peeling nor versioning were successful then return false if
any data reference does not satisfy vect_supportable_dr_alignment.
D) Return true (all data references satisfy vect_supportable_dr_alignment).
Note, Possibility 3 above (which is peeling and versioning together) is not
being done at this time. */
/* (1) Peeling to force alignment. */
/* (1.1) Decide whether to perform peeling, and how many iterations to peel:
Considerations:
+ How many accesses will become aligned due to the peeling
- How many accesses will become unaligned due to the peeling,
and the cost of misaligned accesses.
- The cost of peeling (the extra runtime checks, the increase
in code size). */
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
dr_vec_info *dr_info = loop_vinfo->lookup_dr (dr);
stmt_vec_info stmt_info = dr_info->stmt;
if (!STMT_VINFO_RELEVANT_P (stmt_info))
continue;
/* For interleaving, only the alignment of the first access
matters. */
if (STMT_VINFO_GROUPED_ACCESS (stmt_info)
&& DR_GROUP_FIRST_ELEMENT (stmt_info) != stmt_info)
continue;
/* For scatter-gather or invariant accesses there is nothing
to enhance. */
if (STMT_VINFO_GATHER_SCATTER_P (stmt_info)
|| integer_zerop (DR_STEP (dr)))
continue;
/* Strided accesses perform only component accesses, alignment is
irrelevant for them. */
if (STMT_VINFO_STRIDED_P (stmt_info)
&& !STMT_VINFO_GROUPED_ACCESS (stmt_info))
continue;
supportable_dr_alignment = vect_supportable_dr_alignment (dr_info, true);
do_peeling = vector_alignment_reachable_p (dr_info);
if (do_peeling)
{
if (known_alignment_for_access_p (dr_info))
{
unsigned int npeel_tmp = 0;
bool negative = tree_int_cst_compare (DR_STEP (dr),
size_zero_node) < 0;
vectype = STMT_VINFO_VECTYPE (stmt_info);
/* If known_alignment_for_access_p then we have set
DR_MISALIGNMENT which is only done if we know it at compiler
time, so it is safe to assume target alignment is constant.
*/
unsigned int target_align =
DR_TARGET_ALIGNMENT (dr_info).to_constant ();
unsigned int dr_size = vect_get_scalar_dr_size (dr_info);
mis = (negative
? DR_MISALIGNMENT (dr_info)
: -DR_MISALIGNMENT (dr_info));
if (DR_MISALIGNMENT (dr_info) != 0)
npeel_tmp = (mis & (target_align - 1)) / dr_size;
/* For multiple types, it is possible that the bigger type access
will have more than one peeling option. E.g., a loop with two
types: one of size (vector size / 4), and the other one of
size (vector size / 8). Vectorization factor will 8. If both
accesses are misaligned by 3, the first one needs one scalar
iteration to be aligned, and the second one needs 5. But the
first one will be aligned also by peeling 5 scalar
iterations, and in that case both accesses will be aligned.
Hence, except for the immediate peeling amount, we also want
to try to add full vector size, while we don't exceed
vectorization factor.
We do this automatically for cost model, since we calculate
cost for every peeling option. */
if (unlimited_cost_model (LOOP_VINFO_LOOP (loop_vinfo)))
{
poly_uint64 nscalars = (STMT_SLP_TYPE (stmt_info)
? vf * DR_GROUP_SIZE (stmt_info) : vf);
possible_npeel_number
= vect_get_num_vectors (nscalars, vectype);
/* NPEEL_TMP is 0 when there is no misalignment, but also
allow peeling NELEMENTS. */
if (DR_MISALIGNMENT (dr_info) == 0)
possible_npeel_number++;
}
/* Save info about DR in the hash table. Also include peeling
amounts according to the explanation above. */
for (j = 0; j < possible_npeel_number; j++)
{
vect_peeling_hash_insert (&peeling_htab, loop_vinfo,
dr_info, npeel_tmp);
npeel_tmp += target_align / dr_size;
}
one_misalignment_known = true;
}
else
{
/* If we don't know any misalignment values, we prefer
peeling for data-ref that has the maximum number of data-refs
with the same alignment, unless the target prefers to align
stores over load. */
unsigned same_align_drs
= STMT_VINFO_SAME_ALIGN_REFS (stmt_info).length ();
if (!dr0_info
|| same_align_drs_max < same_align_drs)
{
same_align_drs_max = same_align_drs;
dr0_info = dr_info;
}
/* For data-refs with the same number of related
accesses prefer the one where the misalign
computation will be invariant in the outermost loop. */
else if (same_align_drs_max == same_align_drs)
{
class loop *ivloop0, *ivloop;
ivloop0 = outermost_invariant_loop_for_expr
(loop, DR_BASE_ADDRESS (dr0_info->dr));
ivloop = outermost_invariant_loop_for_expr
(loop, DR_BASE_ADDRESS (dr));
if ((ivloop && !ivloop0)
|| (ivloop && ivloop0
&& flow_loop_nested_p (ivloop, ivloop0)))
dr0_info = dr_info;
}
one_misalignment_unknown = true;
/* Check for data refs with unsupportable alignment that
can be peeled. */
if (!supportable_dr_alignment)
{
one_dr_unsupportable = true;
unsupportable_dr_info = dr_info;
}
if (!first_store && DR_IS_WRITE (dr))
first_store = dr_info;
}
}
else
{
if (!aligned_access_p (dr_info))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"vector alignment may not be reachable\n");
break;
}
}
}
/* Check if we can possibly peel the loop. */
if (!vect_can_advance_ivs_p (loop_vinfo)
|| !slpeel_can_duplicate_loop_p (loop, single_exit (loop))
|| loop->inner)
do_peeling = false;
struct _vect_peel_extended_info peel_for_known_alignment;
struct _vect_peel_extended_info peel_for_unknown_alignment;
struct _vect_peel_extended_info best_peel;
peel_for_unknown_alignment.inside_cost = INT_MAX;
peel_for_unknown_alignment.outside_cost = INT_MAX;
peel_for_unknown_alignment.peel_info.count = 0;
if (do_peeling
&& one_misalignment_unknown)
{
/* Check if the target requires to prefer stores over loads, i.e., if
misaligned stores are more expensive than misaligned loads (taking
drs with same alignment into account). */
unsigned int load_inside_cost = 0;
unsigned int load_outside_cost = 0;
unsigned int store_inside_cost = 0;
unsigned int store_outside_cost = 0;
unsigned int estimated_npeels = vect_vf_for_cost (loop_vinfo) / 2;
stmt_vector_for_cost dummy;
dummy.create (2);
vect_get_peeling_costs_all_drs (loop_vinfo, dr0_info,
&load_inside_cost,
&load_outside_cost,
&dummy, &dummy, estimated_npeels, true);
dummy.release ();
if (first_store)
{
dummy.create (2);
vect_get_peeling_costs_all_drs (loop_vinfo, first_store,
&store_inside_cost,
&store_outside_cost,
&dummy, &dummy,
estimated_npeels, true);
dummy.release ();
}
else
{
store_inside_cost = INT_MAX;
store_outside_cost = INT_MAX;
}
if (load_inside_cost > store_inside_cost
|| (load_inside_cost == store_inside_cost
&& load_outside_cost > store_outside_cost))
{
dr0_info = first_store;
peel_for_unknown_alignment.inside_cost = store_inside_cost;
peel_for_unknown_alignment.outside_cost = store_outside_cost;
}
else
{
peel_for_unknown_alignment.inside_cost = load_inside_cost;
peel_for_unknown_alignment.outside_cost = load_outside_cost;
}
stmt_vector_for_cost prologue_cost_vec, epilogue_cost_vec;
prologue_cost_vec.create (2);
epilogue_cost_vec.create (2);
int dummy2;
peel_for_unknown_alignment.outside_cost += vect_get_known_peeling_cost
(loop_vinfo, estimated_npeels, &dummy2,
&LOOP_VINFO_SCALAR_ITERATION_COST (loop_vinfo),
&prologue_cost_vec, &epilogue_cost_vec);
prologue_cost_vec.release ();
epilogue_cost_vec.release ();
peel_for_unknown_alignment.peel_info.count = 1
+ STMT_VINFO_SAME_ALIGN_REFS (dr0_info->stmt).length ();
}
peel_for_unknown_alignment.peel_info.npeel = 0;
peel_for_unknown_alignment.peel_info.dr_info = dr0_info;
best_peel = peel_for_unknown_alignment;
peel_for_known_alignment.inside_cost = INT_MAX;
peel_for_known_alignment.outside_cost = INT_MAX;
peel_for_known_alignment.peel_info.count = 0;
peel_for_known_alignment.peel_info.dr_info = NULL;
if (do_peeling && one_misalignment_known)
{
/* Peeling is possible, but there is no data access that is not supported
unless aligned. So we try to choose the best possible peeling from
the hash table. */
peel_for_known_alignment = vect_peeling_hash_choose_best_peeling
(&peeling_htab, loop_vinfo);
}
/* Compare costs of peeling for known and unknown alignment. */
if (peel_for_known_alignment.peel_info.dr_info != NULL
&& peel_for_unknown_alignment.inside_cost
>= peel_for_known_alignment.inside_cost)
{
best_peel = peel_for_known_alignment;
/* If the best peeling for known alignment has NPEEL == 0, perform no
peeling at all except if there is an unsupportable dr that we can
align. */
if (best_peel.peel_info.npeel == 0 && !one_dr_unsupportable)
do_peeling = false;
}
/* If there is an unsupportable data ref, prefer this over all choices so far
since we'd have to discard a chosen peeling except when it accidentally
aligned the unsupportable data ref. */
if (one_dr_unsupportable)
dr0_info = unsupportable_dr_info;
else if (do_peeling)
{
/* Calculate the penalty for no peeling, i.e. leaving everything as-is.
TODO: Use nopeel_outside_cost or get rid of it? */
unsigned nopeel_inside_cost = 0;
unsigned nopeel_outside_cost = 0;
stmt_vector_for_cost dummy;
dummy.create (2);
vect_get_peeling_costs_all_drs (loop_vinfo, NULL, &nopeel_inside_cost,
&nopeel_outside_cost, &dummy, &dummy,
0, false);
dummy.release ();
/* Add epilogue costs. As we do not peel for alignment here, no prologue
costs will be recorded. */
stmt_vector_for_cost prologue_cost_vec, epilogue_cost_vec;
prologue_cost_vec.create (2);
epilogue_cost_vec.create (2);
int dummy2;
nopeel_outside_cost += vect_get_known_peeling_cost
(loop_vinfo, 0, &dummy2,
&LOOP_VINFO_SCALAR_ITERATION_COST (loop_vinfo),
&prologue_cost_vec, &epilogue_cost_vec);
prologue_cost_vec.release ();
epilogue_cost_vec.release ();
npeel = best_peel.peel_info.npeel;
dr0_info = best_peel.peel_info.dr_info;
/* If no peeling is not more expensive than the best peeling we
have so far, don't perform any peeling. */
if (nopeel_inside_cost <= best_peel.inside_cost)
do_peeling = false;
}
if (do_peeling)
{
stmt_vec_info stmt_info = dr0_info->stmt;
vectype = STMT_VINFO_VECTYPE (stmt_info);
if (known_alignment_for_access_p (dr0_info))
{
bool negative = tree_int_cst_compare (DR_STEP (dr0_info->dr),
size_zero_node) < 0;
if (!npeel)
{
/* Since it's known at compile time, compute the number of
iterations in the peeled loop (the peeling factor) for use in
updating DR_MISALIGNMENT values. The peeling factor is the
vectorization factor minus the misalignment as an element
count. */
mis = (negative
? DR_MISALIGNMENT (dr0_info)
: -DR_MISALIGNMENT (dr0_info));
/* If known_alignment_for_access_p then we have set
DR_MISALIGNMENT which is only done if we know it at compiler
time, so it is safe to assume target alignment is constant.
*/
unsigned int target_align =
DR_TARGET_ALIGNMENT (dr0_info).to_constant ();
npeel = ((mis & (target_align - 1))
/ vect_get_scalar_dr_size (dr0_info));
}
/* For interleaved data access every iteration accesses all the
members of the group, therefore we divide the number of iterations
by the group size. */
if (STMT_VINFO_GROUPED_ACCESS (stmt_info))
npeel /= DR_GROUP_SIZE (stmt_info);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Try peeling by %d\n", npeel);
}
/* Ensure that all datarefs can be vectorized after the peel. */
if (!vect_peeling_supportable (loop_vinfo, dr0_info, npeel))
do_peeling = false;
/* Check if all datarefs are supportable and log. */
if (do_peeling && known_alignment_for_access_p (dr0_info) && npeel == 0)
{
opt_result stat = vect_verify_datarefs_alignment (loop_vinfo);
if (!stat)
do_peeling = false;
else
return stat;
}
/* Cost model #1 - honor --param vect-max-peeling-for-alignment. */
if (do_peeling)
{
unsigned max_allowed_peel
= param_vect_max_peeling_for_alignment;
if (flag_vect_cost_model == VECT_COST_MODEL_CHEAP)
max_allowed_peel = 0;
if (max_allowed_peel != (unsigned)-1)
{
unsigned max_peel = npeel;
if (max_peel == 0)
{
poly_uint64 target_align = DR_TARGET_ALIGNMENT (dr0_info);
unsigned HOST_WIDE_INT target_align_c;
if (target_align.is_constant (&target_align_c))
max_peel =
target_align_c / vect_get_scalar_dr_size (dr0_info) - 1;
else
{
do_peeling = false;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Disable peeling, max peels set and vector"
" alignment unknown\n");
}
}
if (max_peel > max_allowed_peel)
{
do_peeling = false;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Disable peeling, max peels reached: %d\n", max_peel);
}
}
}
/* Cost model #2 - if peeling may result in a remaining loop not
iterating enough to be vectorized then do not peel. Since this
is a cost heuristic rather than a correctness decision, use the
most likely runtime value for variable vectorization factors. */
if (do_peeling
&& LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
{
unsigned int assumed_vf = vect_vf_for_cost (loop_vinfo);
unsigned int max_peel = npeel == 0 ? assumed_vf - 1 : npeel;
if ((unsigned HOST_WIDE_INT) LOOP_VINFO_INT_NITERS (loop_vinfo)
< assumed_vf + max_peel)
do_peeling = false;
}
if (do_peeling)
{
/* (1.2) Update the DR_MISALIGNMENT of each data reference DR_i.
If the misalignment of DR_i is identical to that of dr0 then set
DR_MISALIGNMENT (DR_i) to zero. If the misalignment of DR_i and
dr0 are known at compile time then increment DR_MISALIGNMENT (DR_i)
by the peeling factor times the element size of DR_i (MOD the
vectorization factor times the size). Otherwise, the
misalignment of DR_i must be set to unknown. */
FOR_EACH_VEC_ELT (datarefs, i, dr)
if (dr != dr0_info->dr)
{
/* Strided accesses perform only component accesses, alignment
is irrelevant for them. */
dr_vec_info *dr_info = loop_vinfo->lookup_dr (dr);
stmt_info = dr_info->stmt;
if (STMT_VINFO_STRIDED_P (stmt_info)
&& !STMT_VINFO_GROUPED_ACCESS (stmt_info))
continue;
vect_update_misalignment_for_peel (dr_info, dr0_info, npeel);
}
LOOP_VINFO_UNALIGNED_DR (loop_vinfo) = dr0_info;
if (npeel)
LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) = npeel;
else
LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo)
= DR_MISALIGNMENT (dr0_info);
SET_DR_MISALIGNMENT (dr0_info, 0);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"Alignment of access forced using peeling.\n");
dump_printf_loc (MSG_NOTE, vect_location,
"Peeling for alignment will be applied.\n");
}
/* The inside-loop cost will be accounted for in vectorizable_load
and vectorizable_store correctly with adjusted alignments.
Drop the body_cst_vec on the floor here. */
opt_result stat = vect_verify_datarefs_alignment (loop_vinfo);
gcc_assert (stat);
return stat;
}
}
/* (2) Versioning to force alignment. */
/* Try versioning if:
1) optimize loop for speed and the cost-model is not cheap
2) there is at least one unsupported misaligned data ref with an unknown
misalignment, and
3) all misaligned data refs with a known misalignment are supported, and
4) the number of runtime alignment checks is within reason. */
do_versioning
= (optimize_loop_nest_for_speed_p (loop)
&& !loop->inner /* FORNOW */
&& flag_vect_cost_model != VECT_COST_MODEL_CHEAP);
if (do_versioning)
{
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
dr_vec_info *dr_info = loop_vinfo->lookup_dr (dr);
stmt_vec_info stmt_info = dr_info->stmt;
/* For interleaving, only the alignment of the first access
matters. */
if (aligned_access_p (dr_info)
|| (STMT_VINFO_GROUPED_ACCESS (stmt_info)
&& DR_GROUP_FIRST_ELEMENT (stmt_info) != stmt_info))
continue;
if (STMT_VINFO_STRIDED_P (stmt_info))
{
/* Strided loads perform only component accesses, alignment is
irrelevant for them. */
if (!STMT_VINFO_GROUPED_ACCESS (stmt_info))
continue;
do_versioning = false;
break;
}
supportable_dr_alignment
= vect_supportable_dr_alignment (dr_info, false);
if (!supportable_dr_alignment)
{
int mask;
tree vectype;
if (known_alignment_for_access_p (dr_info)
|| LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).length ()
>= (unsigned) param_vect_max_version_for_alignment_checks)
{
do_versioning = false;
break;
}
vectype = STMT_VINFO_VECTYPE (stmt_info);
gcc_assert (vectype);
/* At present we don't support versioning for alignment
with variable VF, since there's no guarantee that the
VF is a power of two. We could relax this if we added
a way of enforcing a power-of-two size. */
unsigned HOST_WIDE_INT size;
if (!GET_MODE_SIZE (TYPE_MODE (vectype)).is_constant (&size))
{
do_versioning = false;
break;
}
/* Forcing alignment in the first iteration is no good if
we don't keep it across iterations. For now, just disable
versioning in this case.
?? We could actually unroll the loop to achieve the required
overall step alignment, and forcing the alignment could be
done by doing some iterations of the non-vectorized loop. */
if (!multiple_p (LOOP_VINFO_VECT_FACTOR (loop_vinfo)
* DR_STEP_ALIGNMENT (dr),
DR_TARGET_ALIGNMENT (dr_info)))
{
do_versioning = false;
break;
}
/* The rightmost bits of an aligned address must be zeros.
Construct the mask needed for this test. For example,
GET_MODE_SIZE for the vector mode V4SI is 16 bytes so the
mask must be 15 = 0xf. */
mask = size - 1;
/* FORNOW: use the same mask to test all potentially unaligned
references in the loop. */
if (LOOP_VINFO_PTR_MASK (loop_vinfo)
&& LOOP_VINFO_PTR_MASK (loop_vinfo) != mask)
{
do_versioning = false;
break;
}
LOOP_VINFO_PTR_MASK (loop_vinfo) = mask;
LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).safe_push (stmt_info);
}
}
/* Versioning requires at least one misaligned data reference. */
if (!LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo))
do_versioning = false;
else if (!do_versioning)
LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).truncate (0);
}
if (do_versioning)
{
vec<stmt_vec_info> may_misalign_stmts
= LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo);
stmt_vec_info stmt_info;
/* It can now be assumed that the data references in the statements
in LOOP_VINFO_MAY_MISALIGN_STMTS will be aligned in the version
of the loop being vectorized. */
FOR_EACH_VEC_ELT (may_misalign_stmts, i, stmt_info)
{
dr_vec_info *dr_info = STMT_VINFO_DR_INFO (stmt_info);
SET_DR_MISALIGNMENT (dr_info, 0);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Alignment of access forced using versioning.\n");
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Versioning for alignment will be applied.\n");
/* Peeling and versioning can't be done together at this time. */
gcc_assert (! (do_peeling && do_versioning));
opt_result stat = vect_verify_datarefs_alignment (loop_vinfo);
gcc_assert (stat);
return stat;
}
/* This point is reached if neither peeling nor versioning is being done. */
gcc_assert (! (do_peeling || do_versioning));
opt_result stat = vect_verify_datarefs_alignment (loop_vinfo);
return stat;
}
/* Function vect_find_same_alignment_drs.
Update group and alignment relations in VINFO according to the chosen
vectorization factor. */
static void
vect_find_same_alignment_drs (vec_info *vinfo, data_dependence_relation *ddr)
{
struct data_reference *dra = DDR_A (ddr);
struct data_reference *drb = DDR_B (ddr);
dr_vec_info *dr_info_a = vinfo->lookup_dr (dra);
dr_vec_info *dr_info_b = vinfo->lookup_dr (drb);
stmt_vec_info stmtinfo_a = dr_info_a->stmt;
stmt_vec_info stmtinfo_b = dr_info_b->stmt;
if (DDR_ARE_DEPENDENT (ddr) == chrec_known)
return;
if (dra == drb)
return;
if (STMT_VINFO_GATHER_SCATTER_P (stmtinfo_a)
|| STMT_VINFO_GATHER_SCATTER_P (stmtinfo_b))
return;
if (!operand_equal_p (DR_BASE_ADDRESS (dra), DR_BASE_ADDRESS (drb), 0)
|| !operand_equal_p (DR_OFFSET (dra), DR_OFFSET (drb), 0)
|| !operand_equal_p (DR_STEP (dra), DR_STEP (drb), 0))
return;
/* Two references with distance zero have the same alignment. */
poly_offset_int diff = (wi::to_poly_offset (DR_INIT (dra))
- wi::to_poly_offset (DR_INIT (drb)));
if (maybe_ne (diff, 0))
{
/* Get the wider of the two alignments. */
poly_uint64 align_a =
exact_div (vect_calculate_target_alignment (dr_info_a),
BITS_PER_UNIT);
poly_uint64 align_b =
exact_div (vect_calculate_target_alignment (dr_info_b),
BITS_PER_UNIT);
unsigned HOST_WIDE_INT align_a_c, align_b_c;
if (!align_a.is_constant (&align_a_c)
|| !align_b.is_constant (&align_b_c))
return;
unsigned HOST_WIDE_INT max_align = MAX (align_a_c, align_b_c);
/* Require the gap to be a multiple of the larger vector alignment. */
if (!multiple_p (diff, max_align))
return;
}
STMT_VINFO_SAME_ALIGN_REFS (stmtinfo_a).safe_push (drb);
STMT_VINFO_SAME_ALIGN_REFS (stmtinfo_b).safe_push (dra);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"accesses have the same alignment: %T and %T\n",
DR_REF (dra), DR_REF (drb));
}
/* Function vect_analyze_data_refs_alignment
Analyze the alignment of the data-references in the loop.
Return FALSE if a data reference is found that cannot be vectorized. */
opt_result
vect_analyze_data_refs_alignment (loop_vec_info vinfo)
{
DUMP_VECT_SCOPE ("vect_analyze_data_refs_alignment");
/* Mark groups of data references with same alignment using
data dependence information. */
vec<ddr_p> ddrs = vinfo->shared->ddrs;
struct data_dependence_relation *ddr;
unsigned int i;
FOR_EACH_VEC_ELT (ddrs, i, ddr)
vect_find_same_alignment_drs (vinfo, ddr);
vec<data_reference_p> datarefs = vinfo->shared->datarefs;
struct data_reference *dr;
vect_record_base_alignments (vinfo);
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
dr_vec_info *dr_info = vinfo->lookup_dr (dr);
if (STMT_VINFO_VECTORIZABLE (dr_info->stmt))
vect_compute_data_ref_alignment (dr_info);
}
return opt_result::success ();
}
/* Analyze alignment of DRs of stmts in NODE. */
static bool
vect_slp_analyze_and_verify_node_alignment (slp_tree node)
{
/* We vectorize from the first scalar stmt in the node unless
the node is permuted in which case we start from the first
element in the group. */
stmt_vec_info first_stmt_info = SLP_TREE_SCALAR_STMTS (node)[0];
dr_vec_info *first_dr_info = STMT_VINFO_DR_INFO (first_stmt_info);
if (SLP_TREE_LOAD_PERMUTATION (node).exists ())
first_stmt_info = DR_GROUP_FIRST_ELEMENT (first_stmt_info);
dr_vec_info *dr_info = STMT_VINFO_DR_INFO (first_stmt_info);
vect_compute_data_ref_alignment (dr_info);
/* For creating the data-ref pointer we need alignment of the
first element anyway. */
if (dr_info != first_dr_info)
vect_compute_data_ref_alignment (first_dr_info);
if (! verify_data_ref_alignment (dr_info))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: bad data alignment in basic "
"block.\n");
return false;
}
return true;
}
/* Function vect_slp_analyze_instance_alignment
Analyze the alignment of the data-references in the SLP instance.
Return FALSE if a data reference is found that cannot be vectorized. */
bool
vect_slp_analyze_and_verify_instance_alignment (slp_instance instance)
{
DUMP_VECT_SCOPE ("vect_slp_analyze_and_verify_instance_alignment");
slp_tree node;
unsigned i;
FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (instance), i, node)
if (! vect_slp_analyze_and_verify_node_alignment (node))
return false;
node = SLP_INSTANCE_TREE (instance);
if (STMT_VINFO_DATA_REF (SLP_TREE_SCALAR_STMTS (node)[0])
&& ! vect_slp_analyze_and_verify_node_alignment
(SLP_INSTANCE_TREE (instance)))
return false;
return true;
}
/* Analyze groups of accesses: check that DR_INFO belongs to a group of
accesses of legal size, step, etc. Detect gaps, single element
interleaving, and other special cases. Set grouped access info.
Collect groups of strided stores for further use in SLP analysis.
Worker for vect_analyze_group_access. */
static bool
vect_analyze_group_access_1 (dr_vec_info *dr_info)
{
data_reference *dr = dr_info->dr;
tree step = DR_STEP (dr);
tree scalar_type = TREE_TYPE (DR_REF (dr));
HOST_WIDE_INT type_size = TREE_INT_CST_LOW (TYPE_SIZE_UNIT (scalar_type));
stmt_vec_info stmt_info = dr_info->stmt;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
bb_vec_info bb_vinfo = STMT_VINFO_BB_VINFO (stmt_info);
HOST_WIDE_INT dr_step = -1;
HOST_WIDE_INT groupsize, last_accessed_element = 1;
bool slp_impossible = false;
/* For interleaving, GROUPSIZE is STEP counted in elements, i.e., the
size of the interleaving group (including gaps). */
if (tree_fits_shwi_p (step))
{
dr_step = tree_to_shwi (step);
/* Check that STEP is a multiple of type size. Otherwise there is
a non-element-sized gap at the end of the group which we
cannot represent in DR_GROUP_GAP or DR_GROUP_SIZE.
??? As we can handle non-constant step fine here we should
simply remove uses of DR_GROUP_GAP between the last and first
element and instead rely on DR_STEP. DR_GROUP_SIZE then would
simply not include that gap. */
if ((dr_step % type_size) != 0)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Step %T is not a multiple of the element size"
" for %T\n",
step, DR_REF (dr));
return false;
}
groupsize = absu_hwi (dr_step) / type_size;
}
else
groupsize = 0;
/* Not consecutive access is possible only if it is a part of interleaving. */
if (!DR_GROUP_FIRST_ELEMENT (stmt_info))
{
/* Check if it this DR is a part of interleaving, and is a single
element of the group that is accessed in the loop. */
/* Gaps are supported only for loads. STEP must be a multiple of the type
size. */
if (DR_IS_READ (dr)
&& (dr_step % type_size) == 0
&& groupsize > 0)
{
DR_GROUP_FIRST_ELEMENT (stmt_info) = stmt_info;
DR_GROUP_SIZE (stmt_info) = groupsize;
DR_GROUP_GAP (stmt_info) = groupsize - 1;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Detected single element interleaving %T"
" step %T\n",
DR_REF (dr), step);
return true;
}
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not consecutive access %G", stmt_info->stmt);
if (bb_vinfo)
{
/* Mark the statement as unvectorizable. */
STMT_VINFO_VECTORIZABLE (stmt_info) = false;
return true;
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "using strided accesses\n");
STMT_VINFO_STRIDED_P (stmt_info) = true;
return true;
}
if (DR_GROUP_FIRST_ELEMENT (stmt_info) == stmt_info)
{
/* First stmt in the interleaving chain. Check the chain. */
stmt_vec_info next = DR_GROUP_NEXT_ELEMENT (stmt_info);
struct data_reference *data_ref = dr;
unsigned int count = 1;
tree prev_init = DR_INIT (data_ref);
HOST_WIDE_INT diff, gaps = 0;
/* By construction, all group members have INTEGER_CST DR_INITs. */
while (next)
{
/* We never have the same DR multiple times. */
gcc_assert (tree_int_cst_compare (DR_INIT (data_ref),
DR_INIT (STMT_VINFO_DATA_REF (next))) != 0);
data_ref = STMT_VINFO_DATA_REF (next);
/* All group members have the same STEP by construction. */
gcc_checking_assert (operand_equal_p (DR_STEP (data_ref), step, 0));
/* Check that the distance between two accesses is equal to the type
size. Otherwise, we have gaps. */
diff = (TREE_INT_CST_LOW (DR_INIT (data_ref))
- TREE_INT_CST_LOW (prev_init)) / type_size;
if (diff != 1)
{
/* FORNOW: SLP of accesses with gaps is not supported. */
slp_impossible = true;
if (DR_IS_WRITE (data_ref))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"interleaved store with gaps\n");
return false;
}
gaps += diff - 1;
}
last_accessed_element += diff;
/* Store the gap from the previous member of the group. If there is no
gap in the access, DR_GROUP_GAP is always 1. */
DR_GROUP_GAP (next) = diff;
prev_init = DR_INIT (data_ref);
next = DR_GROUP_NEXT_ELEMENT (next);
/* Count the number of data-refs in the chain. */
count++;
}
if (groupsize == 0)
groupsize = count + gaps;
/* This could be UINT_MAX but as we are generating code in a very
inefficient way we have to cap earlier. See PR78699 for example. */
if (groupsize > 4096)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"group is too large\n");
return false;
}
/* Check that the size of the interleaving is equal to count for stores,
i.e., that there are no gaps. */
if (groupsize != count
&& !DR_IS_READ (dr))
{
groupsize = count;
STMT_VINFO_STRIDED_P (stmt_info) = true;
}
/* If there is a gap after the last load in the group it is the
difference between the groupsize and the last accessed
element.
When there is no gap, this difference should be 0. */
DR_GROUP_GAP (stmt_info) = groupsize - last_accessed_element;
DR_GROUP_SIZE (stmt_info) = groupsize;
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"Detected interleaving ");
if (DR_IS_READ (dr))
dump_printf (MSG_NOTE, "load ");
else if (STMT_VINFO_STRIDED_P (stmt_info))
dump_printf (MSG_NOTE, "strided store ");
else
dump_printf (MSG_NOTE, "store ");
dump_printf (MSG_NOTE, "of size %u\n",
(unsigned)groupsize);
dump_printf_loc (MSG_NOTE, vect_location, "\t%G", stmt_info->stmt);
next = DR_GROUP_NEXT_ELEMENT (stmt_info);
while (next)
{
if (DR_GROUP_GAP (next) != 1)
dump_printf_loc (MSG_NOTE, vect_location,
"\t<gap of %d elements>\n",
DR_GROUP_GAP (next) - 1);
dump_printf_loc (MSG_NOTE, vect_location, "\t%G", next->stmt);
next = DR_GROUP_NEXT_ELEMENT (next);
}
if (DR_GROUP_GAP (stmt_info) != 0)
dump_printf_loc (MSG_NOTE, vect_location,
"\t<gap of %d elements>\n",
DR_GROUP_GAP (stmt_info));
}
/* SLP: create an SLP data structure for every interleaving group of
stores for further analysis in vect_analyse_slp. */
if (DR_IS_WRITE (dr) && !slp_impossible)
{
if (loop_vinfo)
LOOP_VINFO_GROUPED_STORES (loop_vinfo).safe_push (stmt_info);
if (bb_vinfo)
BB_VINFO_GROUPED_STORES (bb_vinfo).safe_push (stmt_info);
}
}
return true;
}
/* Analyze groups of accesses: check that DR_INFO belongs to a group of
accesses of legal size, step, etc. Detect gaps, single element
interleaving, and other special cases. Set grouped access info.
Collect groups of strided stores for further use in SLP analysis. */
static bool
vect_analyze_group_access (dr_vec_info *dr_info)
{
if (!vect_analyze_group_access_1 (dr_info))
{
/* Dissolve the group if present. */
stmt_vec_info stmt_info = DR_GROUP_FIRST_ELEMENT (dr_info->stmt);
while (stmt_info)
{
stmt_vec_info next = DR_GROUP_NEXT_ELEMENT (stmt_info);
DR_GROUP_FIRST_ELEMENT (stmt_info) = NULL;
DR_GROUP_NEXT_ELEMENT (stmt_info) = NULL;
stmt_info = next;
}
return false;
}
return true;
}
/* Analyze the access pattern of the data-reference DR_INFO.
In case of non-consecutive accesses call vect_analyze_group_access() to
analyze groups of accesses. */
static bool
vect_analyze_data_ref_access (dr_vec_info *dr_info)
{
data_reference *dr = dr_info->dr;
tree step = DR_STEP (dr);
tree scalar_type = TREE_TYPE (DR_REF (dr));
stmt_vec_info stmt_info = dr_info->stmt;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
class loop *loop = NULL;
if (STMT_VINFO_GATHER_SCATTER_P (stmt_info))
return true;
if (loop_vinfo)
loop = LOOP_VINFO_LOOP (loop_vinfo);
if (loop_vinfo && !step)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data-ref access in loop\n");
return false;
}
/* Allow loads with zero step in inner-loop vectorization. */
if (loop_vinfo && integer_zerop (step))
{
DR_GROUP_FIRST_ELEMENT (stmt_info) = NULL;
if (!nested_in_vect_loop_p (loop, stmt_info))
return DR_IS_READ (dr);
/* Allow references with zero step for outer loops marked
with pragma omp simd only - it guarantees absence of
loop-carried dependencies between inner loop iterations. */
if (loop->safelen < 2)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"zero step in inner loop of nest\n");
return false;
}
}
if (loop && nested_in_vect_loop_p (loop, stmt_info))
{
/* Interleaved accesses are not yet supported within outer-loop
vectorization for references in the inner-loop. */
DR_GROUP_FIRST_ELEMENT (stmt_info) = NULL;
/* For the rest of the analysis we use the outer-loop step. */
step = STMT_VINFO_DR_STEP (stmt_info);
if (integer_zerop (step))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"zero step in outer loop.\n");
return DR_IS_READ (dr);
}
}
/* Consecutive? */
if (TREE_CODE (step) == INTEGER_CST)
{
HOST_WIDE_INT dr_step = TREE_INT_CST_LOW (step);
if (!tree_int_cst_compare (step, TYPE_SIZE_UNIT (scalar_type))
|| (dr_step < 0
&& !compare_tree_int (TYPE_SIZE_UNIT (scalar_type), -dr_step)))
{
/* Mark that it is not interleaving. */
DR_GROUP_FIRST_ELEMENT (stmt_info) = NULL;
return true;
}
}
if (loop && nested_in_vect_loop_p (loop, stmt_info))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"grouped access in outer loop.\n");
return false;
}
/* Assume this is a DR handled by non-constant strided load case. */
if (TREE_CODE (step) != INTEGER_CST)
return (STMT_VINFO_STRIDED_P (stmt_info)
&& (!STMT_VINFO_GROUPED_ACCESS (stmt_info)
|| vect_analyze_group_access (dr_info)));
/* Not consecutive access - check if it's a part of interleaving group. */
return vect_analyze_group_access (dr_info);
}
/* Compare two data-references DRA and DRB to group them into chunks
suitable for grouping. */
static int
dr_group_sort_cmp (const void *dra_, const void *drb_)
{
data_reference_p dra = *(data_reference_p *)const_cast<void *>(dra_);
data_reference_p drb = *(data_reference_p *)const_cast<void *>(drb_);
int cmp;
/* Stabilize sort. */
if (dra == drb)
return 0;
/* DRs in different loops never belong to the same group. */
loop_p loopa = gimple_bb (DR_STMT (dra))->loop_father;
loop_p loopb = gimple_bb (DR_STMT (drb))->loop_father;
if (loopa != loopb)
return loopa->num < loopb->num ? -1 : 1;
/* Ordering of DRs according to base. */
cmp = data_ref_compare_tree (DR_BASE_ADDRESS (dra),
DR_BASE_ADDRESS (drb));
if (cmp != 0)
return cmp;
/* And according to DR_OFFSET. */
cmp = data_ref_compare_tree (DR_OFFSET (dra), DR_OFFSET (drb));
if (cmp != 0)
return cmp;
/* Put reads before writes. */
if (DR_IS_READ (dra) != DR_IS_READ (drb))
return DR_IS_READ (dra) ? -1 : 1;
/* Then sort after access size. */
cmp = data_ref_compare_tree (TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (dra))),
TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (drb))));
if (cmp != 0)
return cmp;
/* And after step. */
cmp = data_ref_compare_tree (DR_STEP (dra), DR_STEP (drb));
if (cmp != 0)
return cmp;
/* Then sort after DR_INIT. In case of identical DRs sort after stmt UID. */
cmp = data_ref_compare_tree (DR_INIT (dra), DR_INIT (drb));
if (cmp == 0)
return gimple_uid (DR_STMT (dra)) < gimple_uid (DR_STMT (drb)) ? -1 : 1;
return cmp;
}
/* If OP is the result of a conversion, return the unconverted value,
otherwise return null. */
static tree
strip_conversion (tree op)
{
if (TREE_CODE (op) != SSA_NAME)
return NULL_TREE;
gimple *stmt = SSA_NAME_DEF_STMT (op);
if (!is_gimple_assign (stmt)
|| !CONVERT_EXPR_CODE_P (gimple_assign_rhs_code (stmt)))
return NULL_TREE;
return gimple_assign_rhs1 (stmt);
}
/* Return true if vectorizable_* routines can handle statements STMT1_INFO
and STMT2_INFO being in a single group. When ALLOW_SLP_P, masked loads can
be grouped in SLP mode. */
static bool
can_group_stmts_p (stmt_vec_info stmt1_info, stmt_vec_info stmt2_info,
bool allow_slp_p)
{
if (gimple_assign_single_p (stmt1_info->stmt))
return gimple_assign_single_p (stmt2_info->stmt);
gcall *call1 = dyn_cast <gcall *> (stmt1_info->stmt);
if (call1 && gimple_call_internal_p (call1))
{
/* Check for two masked loads or two masked stores. */
gcall *call2 = dyn_cast <gcall *> (stmt2_info->stmt);
if (!call2 || !gimple_call_internal_p (call2))
return false;
internal_fn ifn = gimple_call_internal_fn (call1);
if (ifn != IFN_MASK_LOAD && ifn != IFN_MASK_STORE)
return false;
if (ifn != gimple_call_internal_fn (call2))
return false;
/* Check that the masks are the same. Cope with casts of masks,
like those created by build_mask_conversion. */
tree mask1 = gimple_call_arg (call1, 2);
tree mask2 = gimple_call_arg (call2, 2);
if (!operand_equal_p (mask1, mask2, 0)
&& (ifn == IFN_MASK_STORE || !allow_slp_p))
{
mask1 = strip_conversion (mask1);
if (!mask1)
return false;
mask2 = strip_conversion (mask2);
if (!mask2)
return false;
if (!operand_equal_p (mask1, mask2, 0))
return false;
}
return true;
}
return false;
}
/* Function vect_analyze_data_ref_accesses.
Analyze the access pattern of all the data references in the loop.
FORNOW: the only access pattern that is considered vectorizable is a
simple step 1 (consecutive) access.
FORNOW: handle only arrays and pointer accesses. */
opt_result
vect_analyze_data_ref_accesses (vec_info *vinfo)
{
unsigned int i;
vec<data_reference_p> datarefs = vinfo->shared->datarefs;
struct data_reference *dr;
DUMP_VECT_SCOPE ("vect_analyze_data_ref_accesses");
if (datarefs.is_empty ())
return opt_result::success ();
/* Sort the array of datarefs to make building the interleaving chains
linear. Don't modify the original vector's order, it is needed for
determining what dependencies are reversed. */
vec<data_reference_p> datarefs_copy = datarefs.copy ();
datarefs_copy.qsort (dr_group_sort_cmp);
hash_set<stmt_vec_info> to_fixup;
/* Build the interleaving chains. */
for (i = 0; i < datarefs_copy.length () - 1;)
{
data_reference_p dra = datarefs_copy[i];
dr_vec_info *dr_info_a = vinfo->lookup_dr (dra);
stmt_vec_info stmtinfo_a = dr_info_a->stmt;
stmt_vec_info lastinfo = NULL;
if (!STMT_VINFO_VECTORIZABLE (stmtinfo_a)
|| STMT_VINFO_GATHER_SCATTER_P (stmtinfo_a))
{
++i;
continue;
}
for (i = i + 1; i < datarefs_copy.length (); ++i)
{
data_reference_p drb = datarefs_copy[i];
dr_vec_info *dr_info_b = vinfo->lookup_dr (drb);
stmt_vec_info stmtinfo_b = dr_info_b->stmt;
if (!STMT_VINFO_VECTORIZABLE (stmtinfo_b)
|| STMT_VINFO_GATHER_SCATTER_P (stmtinfo_b))
break;
/* ??? Imperfect sorting (non-compatible types, non-modulo
accesses, same accesses) can lead to a group to be artificially
split here as we don't just skip over those. If it really
matters we can push those to a worklist and re-iterate
over them. The we can just skip ahead to the next DR here. */
/* DRs in a different loop should not be put into the same
interleaving group. */
if (gimple_bb (DR_STMT (dra))->loop_father
!= gimple_bb (DR_STMT (drb))->loop_father)
break;
/* Check that the data-refs have same first location (except init)
and they are both either store or load (not load and store,
not masked loads or stores). */
if (DR_IS_READ (dra) != DR_IS_READ (drb)
|| data_ref_compare_tree (DR_BASE_ADDRESS (dra),
DR_BASE_ADDRESS (drb)) != 0
|| data_ref_compare_tree (DR_OFFSET (dra), DR_OFFSET (drb)) != 0
|| !can_group_stmts_p (stmtinfo_a, stmtinfo_b, true))
break;
/* Check that the data-refs have the same constant size. */
tree sza = TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (dra)));
tree szb = TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (drb)));
if (!tree_fits_uhwi_p (sza)
|| !tree_fits_uhwi_p (szb)
|| !tree_int_cst_equal (sza, szb))
break;
/* Check that the data-refs have the same step. */
if (data_ref_compare_tree (DR_STEP (dra), DR_STEP (drb)) != 0)
break;
/* Check the types are compatible.
??? We don't distinguish this during sorting. */
if (!types_compatible_p (TREE_TYPE (DR_REF (dra)),
TREE_TYPE (DR_REF (drb))))
break;
/* Check that the DR_INITs are compile-time constants. */
if (TREE_CODE (DR_INIT (dra)) != INTEGER_CST
|| TREE_CODE (DR_INIT (drb)) != INTEGER_CST)
break;
/* Different .GOMP_SIMD_LANE calls still give the same lane,
just hold extra information. */
if (STMT_VINFO_SIMD_LANE_ACCESS_P (stmtinfo_a)
&& STMT_VINFO_SIMD_LANE_ACCESS_P (stmtinfo_b)
&& data_ref_compare_tree (DR_INIT (dra), DR_INIT (drb)) == 0)
break;
/* Sorting has ensured that DR_INIT (dra) <= DR_INIT (drb). */
HOST_WIDE_INT init_a = TREE_INT_CST_LOW (DR_INIT (dra));
HOST_WIDE_INT init_b = TREE_INT_CST_LOW (DR_INIT (drb));
HOST_WIDE_INT init_prev
= TREE_INT_CST_LOW (DR_INIT (datarefs_copy[i-1]));
gcc_assert (init_a <= init_b
&& init_a <= init_prev
&& init_prev <= init_b);
/* Do not place the same access in the interleaving chain twice. */
if (init_b == init_prev)
{
gcc_assert (gimple_uid (DR_STMT (datarefs_copy[i-1]))
< gimple_uid (DR_STMT (drb)));
/* Simply link in duplicates and fix up the chain below. */
}
else
{
/* If init_b == init_a + the size of the type * k, we have an
interleaving, and DRA is accessed before DRB. */
HOST_WIDE_INT type_size_a = tree_to_uhwi (sza);
if (type_size_a == 0
|| (init_b - init_a) % type_size_a != 0)
break;
/* If we have a store, the accesses are adjacent. This splits
groups into chunks we support (we don't support vectorization
of stores with gaps). */
if (!DR_IS_READ (dra) && init_b - init_prev != type_size_a)
break;
/* If the step (if not zero or non-constant) is greater than the
difference between data-refs' inits this splits groups into
suitable sizes. */
if (tree_fits_shwi_p (DR_STEP (dra)))
{
HOST_WIDE_INT step = tree_to_shwi (DR_STEP (dra));
if (step != 0 && step <= (init_b - init_a))
break;
}
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
DR_IS_READ (dra)
? "Detected interleaving load %T and %T\n"
: "Detected interleaving store %T and %T\n",
DR_REF (dra), DR_REF (drb));
/* Link the found element into the group list. */
if (!DR_GROUP_FIRST_ELEMENT (stmtinfo_a))
{
DR_GROUP_FIRST_ELEMENT (stmtinfo_a) = stmtinfo_a;
lastinfo = stmtinfo_a;
}
DR_GROUP_FIRST_ELEMENT (stmtinfo_b) = stmtinfo_a;
DR_GROUP_NEXT_ELEMENT (lastinfo) = stmtinfo_b;
lastinfo = stmtinfo_b;
STMT_VINFO_SLP_VECT_ONLY (stmtinfo_a)
= !can_group_stmts_p (stmtinfo_a, stmtinfo_b, false);
if (dump_enabled_p () && STMT_VINFO_SLP_VECT_ONLY (stmtinfo_a))
dump_printf_loc (MSG_NOTE, vect_location,
"Load suitable for SLP vectorization only.\n");
if (init_b == init_prev
&& !to_fixup.add (DR_GROUP_FIRST_ELEMENT (stmtinfo_a))
&& dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Queuing group with duplicate access for fixup\n");
}
}
/* Fixup groups with duplicate entries by splitting it. */
while (1)
{
hash_set<stmt_vec_info>::iterator it = to_fixup.begin ();
if (!(it != to_fixup.end ()))
break;
stmt_vec_info grp = *it;
to_fixup.remove (grp);
/* Find the earliest duplicate group member. */
unsigned first_duplicate = -1u;
stmt_vec_info next, g = grp;
while ((next = DR_GROUP_NEXT_ELEMENT (g)))
{
if (tree_int_cst_equal (DR_INIT (STMT_VINFO_DR_INFO (next)->dr),
DR_INIT (STMT_VINFO_DR_INFO (g)->dr))
&& gimple_uid (STMT_VINFO_STMT (next)) < first_duplicate)
first_duplicate = gimple_uid (STMT_VINFO_STMT (next));
g = next;
}
if (first_duplicate == -1U)
continue;
/* Then move all stmts after the first duplicate to a new group.
Note this is a heuristic but one with the property that *it
is fixed up completely. */
g = grp;
stmt_vec_info newgroup = NULL, ng = grp;
while ((next = DR_GROUP_NEXT_ELEMENT (g)))
{
if (gimple_uid (STMT_VINFO_STMT (next)) >= first_duplicate)
{
DR_GROUP_NEXT_ELEMENT (g) = DR_GROUP_NEXT_ELEMENT (next);
if (!newgroup)
newgroup = next;
else
DR_GROUP_NEXT_ELEMENT (ng) = next;
ng = next;
DR_GROUP_FIRST_ELEMENT (ng) = newgroup;
}
else
g = DR_GROUP_NEXT_ELEMENT (g);
}
DR_GROUP_NEXT_ELEMENT (ng) = NULL;
/* Fixup the new group which still may contain duplicates. */
to_fixup.add (newgroup);
}
FOR_EACH_VEC_ELT (datarefs_copy, i, dr)
{
dr_vec_info *dr_info = vinfo->lookup_dr (dr);
if (STMT_VINFO_VECTORIZABLE (dr_info->stmt)
&& !vect_analyze_data_ref_access (dr_info))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: complicated access pattern.\n");
if (is_a <bb_vec_info> (vinfo))
{
/* Mark the statement as not vectorizable. */
STMT_VINFO_VECTORIZABLE (dr_info->stmt) = false;
continue;
}
else
{
datarefs_copy.release ();
return opt_result::failure_at (dr_info->stmt->stmt,
"not vectorized:"
" complicated access pattern.\n");
}
}
}
datarefs_copy.release ();
return opt_result::success ();
}
/* Function vect_vfa_segment_size.
Input:
DR_INFO: The data reference.
LENGTH_FACTOR: segment length to consider.
Return a value suitable for the dr_with_seg_len::seg_len field.
This is the "distance travelled" by the pointer from the first
iteration in the segment to the last. Note that it does not include
the size of the access; in effect it only describes the first byte. */
static tree
vect_vfa_segment_size (dr_vec_info *dr_info, tree length_factor)
{
length_factor = size_binop (MINUS_EXPR,
fold_convert (sizetype, length_factor),
size_one_node);
return size_binop (MULT_EXPR, fold_convert (sizetype, DR_STEP (dr_info->dr)),
length_factor);
}
/* Return a value that, when added to abs (vect_vfa_segment_size (DR_INFO)),
gives the worst-case number of bytes covered by the segment. */
static unsigned HOST_WIDE_INT
vect_vfa_access_size (dr_vec_info *dr_info)
{
stmt_vec_info stmt_vinfo = dr_info->stmt;
tree ref_type = TREE_TYPE (DR_REF (dr_info->dr));
unsigned HOST_WIDE_INT ref_size = tree_to_uhwi (TYPE_SIZE_UNIT (ref_type));
unsigned HOST_WIDE_INT access_size = ref_size;
if (DR_GROUP_FIRST_ELEMENT (stmt_vinfo))
{
gcc_assert (DR_GROUP_FIRST_ELEMENT (stmt_vinfo) == stmt_vinfo);
access_size *= DR_GROUP_SIZE (stmt_vinfo) - DR_GROUP_GAP (stmt_vinfo);
}
if (STMT_VINFO_VEC_STMT (stmt_vinfo)
&& (vect_supportable_dr_alignment (dr_info, false)
== dr_explicit_realign_optimized))
{
/* We might access a full vector's worth. */
tree vectype = STMT_VINFO_VECTYPE (stmt_vinfo);
access_size += tree_to_uhwi (TYPE_SIZE_UNIT (vectype)) - ref_size;
}
return access_size;
}
/* Get the minimum alignment for all the scalar accesses that DR_INFO
describes. */
static unsigned int
vect_vfa_align (dr_vec_info *dr_info)
{
return dr_alignment (dr_info->dr);
}
/* Function vect_no_alias_p.
Given data references A and B with equal base and offset, see whether
the alias relation can be decided at compilation time. Return 1 if
it can and the references alias, 0 if it can and the references do
not alias, and -1 if we cannot decide at compile time. SEGMENT_LENGTH_A,
SEGMENT_LENGTH_B, ACCESS_SIZE_A and ACCESS_SIZE_B are the equivalent
of dr_with_seg_len::{seg_len,access_size} for A and B. */
static int
vect_compile_time_alias (dr_vec_info *a, dr_vec_info *b,
tree segment_length_a, tree segment_length_b,
unsigned HOST_WIDE_INT access_size_a,
unsigned HOST_WIDE_INT access_size_b)
{
poly_offset_int offset_a = wi::to_poly_offset (DR_INIT (a->dr));
poly_offset_int offset_b = wi::to_poly_offset (DR_INIT (b->dr));
poly_uint64 const_length_a;
poly_uint64 const_length_b;
/* For negative step, we need to adjust address range by TYPE_SIZE_UNIT
bytes, e.g., int a[3] -> a[1] range is [a+4, a+16) instead of
[a, a+12) */
if (tree_int_cst_compare (DR_STEP (a->dr), size_zero_node) < 0)
{
const_length_a = (-wi::to_poly_wide (segment_length_a)).force_uhwi ();
offset_a -= const_length_a;
}
else
const_length_a = tree_to_poly_uint64 (segment_length_a);
if (tree_int_cst_compare (DR_STEP (b->dr), size_zero_node) < 0)
{
const_length_b = (-wi::to_poly_wide (segment_length_b)).force_uhwi ();
offset_b -= const_length_b;
}
else
const_length_b = tree_to_poly_uint64 (segment_length_b);
const_length_a += access_size_a;
const_length_b += access_size_b;
if (ranges_known_overlap_p (offset_a, const_length_a,
offset_b, const_length_b))
return 1;
if (!ranges_maybe_overlap_p (offset_a, const_length_a,
offset_b, const_length_b))
return 0;
return -1;
}
/* Return true if the minimum nonzero dependence distance for loop LOOP_DEPTH
in DDR is >= VF. */
static bool
dependence_distance_ge_vf (data_dependence_relation *ddr,
unsigned int loop_depth, poly_uint64 vf)
{
if (DDR_ARE_DEPENDENT (ddr) != NULL_TREE
|| DDR_NUM_DIST_VECTS (ddr) == 0)
return false;
/* If the dependence is exact, we should have limited the VF instead. */
gcc_checking_assert (DDR_COULD_BE_INDEPENDENT_P (ddr));
unsigned int i;
lambda_vector dist_v;
FOR_EACH_VEC_ELT (DDR_DIST_VECTS (ddr), i, dist_v)
{
HOST_WIDE_INT dist = dist_v[loop_depth];
if (dist != 0
&& !(dist > 0 && DDR_REVERSED_P (ddr))
&& maybe_lt ((unsigned HOST_WIDE_INT) abs_hwi (dist), vf))
return false;
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"dependence distance between %T and %T is >= VF\n",
DR_REF (DDR_A (ddr)), DR_REF (DDR_B (ddr)));
return true;
}
/* Dump LOWER_BOUND using flags DUMP_KIND. Dumps are known to be enabled. */
static void
dump_lower_bound (dump_flags_t dump_kind, const vec_lower_bound &lower_bound)
{
dump_printf (dump_kind, "%s (%T) >= ",
lower_bound.unsigned_p ? "unsigned" : "abs",
lower_bound.expr);
dump_dec (dump_kind, lower_bound.min_value);
}
/* Record that the vectorized loop requires the vec_lower_bound described
by EXPR, UNSIGNED_P and MIN_VALUE. */
static void
vect_check_lower_bound (loop_vec_info loop_vinfo, tree expr, bool unsigned_p,
poly_uint64 min_value)
{
vec<vec_lower_bound> lower_bounds = LOOP_VINFO_LOWER_BOUNDS (loop_vinfo);
for (unsigned int i = 0; i < lower_bounds.length (); ++i)
if (operand_equal_p (lower_bounds[i].expr, expr, 0))
{
unsigned_p &= lower_bounds[i].unsigned_p;
min_value = upper_bound (lower_bounds[i].min_value, min_value);
if (lower_bounds[i].unsigned_p != unsigned_p
|| maybe_lt (lower_bounds[i].min_value, min_value))
{
lower_bounds[i].unsigned_p = unsigned_p;
lower_bounds[i].min_value = min_value;
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"updating run-time check to ");
dump_lower_bound (MSG_NOTE, lower_bounds[i]);
dump_printf (MSG_NOTE, "\n");
}
}
return;
}
vec_lower_bound lower_bound (expr, unsigned_p, min_value);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "need a run-time check that ");
dump_lower_bound (MSG_NOTE, lower_bound);
dump_printf (MSG_NOTE, "\n");
}
LOOP_VINFO_LOWER_BOUNDS (loop_vinfo).safe_push (lower_bound);
}
/* Return true if it's unlikely that the step of the vectorized form of DR_INFO
will span fewer than GAP bytes. */
static bool
vect_small_gap_p (loop_vec_info loop_vinfo, dr_vec_info *dr_info,
poly_int64 gap)
{
stmt_vec_info stmt_info = dr_info->stmt;
HOST_WIDE_INT count
= estimated_poly_value (LOOP_VINFO_VECT_FACTOR (loop_vinfo));
if (DR_GROUP_FIRST_ELEMENT (stmt_info))
count *= DR_GROUP_SIZE (DR_GROUP_FIRST_ELEMENT (stmt_info));
return (estimated_poly_value (gap)
<= count * vect_get_scalar_dr_size (dr_info));
}
/* Return true if we know that there is no alias between DR_INFO_A and
DR_INFO_B when abs (DR_STEP (DR_INFO_A->dr)) >= N for some N.
When returning true, set *LOWER_BOUND_OUT to this N. */
static bool
vectorizable_with_step_bound_p (dr_vec_info *dr_info_a, dr_vec_info *dr_info_b,
poly_uint64 *lower_bound_out)
{
/* Check that there is a constant gap of known sign between DR_A
and DR_B. */
data_reference *dr_a = dr_info_a->dr;
data_reference *dr_b = dr_info_b->dr;
poly_int64 init_a, init_b;
if (!operand_equal_p (DR_BASE_ADDRESS (dr_a), DR_BASE_ADDRESS (dr_b), 0)
|| !operand_equal_p (DR_OFFSET (dr_a), DR_OFFSET (dr_b), 0)
|| !operand_equal_p (DR_STEP (dr_a), DR_STEP (dr_b), 0)
|| !poly_int_tree_p (DR_INIT (dr_a), &init_a)
|| !poly_int_tree_p (DR_INIT (dr_b), &init_b)
|| !ordered_p (init_a, init_b))
return false;
/* Sort DR_A and DR_B by the address they access. */
if (maybe_lt (init_b, init_a))
{
std::swap (init_a, init_b);
std::swap (dr_info_a, dr_info_b);
std::swap (dr_a, dr_b);
}
/* If the two accesses could be dependent within a scalar iteration,
make sure that we'd retain their order. */
if (maybe_gt (init_a + vect_get_scalar_dr_size (dr_info_a), init_b)
&& !vect_preserves_scalar_order_p (dr_info_a, dr_info_b))
return false;
/* There is no alias if abs (DR_STEP) is greater than or equal to
the bytes spanned by the combination of the two accesses. */
*lower_bound_out = init_b + vect_get_scalar_dr_size (dr_info_b) - init_a;
return true;
}
/* Function vect_prune_runtime_alias_test_list.
Prune a list of ddrs to be tested at run-time by versioning for alias.
Merge several alias checks into one if possible.
Return FALSE if resulting list of ddrs is longer then allowed by
PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS, otherwise return TRUE. */
opt_result
vect_prune_runtime_alias_test_list (loop_vec_info loop_vinfo)
{
typedef pair_hash <tree_operand_hash, tree_operand_hash> tree_pair_hash;
hash_set <tree_pair_hash> compared_objects;
vec<ddr_p> may_alias_ddrs = LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo);
vec<dr_with_seg_len_pair_t> &comp_alias_ddrs
= LOOP_VINFO_COMP_ALIAS_DDRS (loop_vinfo);
vec<vec_object_pair> &check_unequal_addrs
= LOOP_VINFO_CHECK_UNEQUAL_ADDRS (loop_vinfo);
poly_uint64 vect_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
tree scalar_loop_iters = LOOP_VINFO_NITERS (loop_vinfo);
ddr_p ddr;
unsigned int i;
tree length_factor;
DUMP_VECT_SCOPE ("vect_prune_runtime_alias_test_list");
/* Step values are irrelevant for aliasing if the number of vector
iterations is equal to the number of scalar iterations (which can
happen for fully-SLP loops). */
bool vf_one_p = known_eq (LOOP_VINFO_VECT_FACTOR (loop_vinfo), 1U);
if (!vf_one_p)
{
/* Convert the checks for nonzero steps into bound tests. */
tree value;
FOR_EACH_VEC_ELT (LOOP_VINFO_CHECK_NONZERO (loop_vinfo), i, value)
vect_check_lower_bound (loop_vinfo, value, true, 1);
}
if (may_alias_ddrs.is_empty ())
return opt_result::success ();
comp_alias_ddrs.create (may_alias_ddrs.length ());
unsigned int loop_depth
= index_in_loop_nest (LOOP_VINFO_LOOP (loop_vinfo)->num,
LOOP_VINFO_LOOP_NEST (loop_vinfo));
/* First, we collect all data ref pairs for aliasing checks. */
FOR_EACH_VEC_ELT (may_alias_ddrs, i, ddr)
{
poly_uint64 lower_bound;
tree segment_length_a, segment_length_b;
unsigned HOST_WIDE_INT access_size_a, access_size_b;
unsigned int align_a, align_b;
/* Ignore the alias if the VF we chose ended up being no greater
than the dependence distance. */
if (dependence_distance_ge_vf (ddr, loop_depth, vect_factor))
continue;
if (DDR_OBJECT_A (ddr))
{
vec_object_pair new_pair (DDR_OBJECT_A (ddr), DDR_OBJECT_B (ddr));
if (!compared_objects.add (new_pair))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"checking that %T and %T"
" have different addresses\n",
new_pair.first, new_pair.second);
LOOP_VINFO_CHECK_UNEQUAL_ADDRS (loop_vinfo).safe_push (new_pair);
}
continue;
}
dr_vec_info *dr_info_a = loop_vinfo->lookup_dr (DDR_A (ddr));
stmt_vec_info stmt_info_a = dr_info_a->stmt;
dr_vec_info *dr_info_b = loop_vinfo->lookup_dr (DDR_B (ddr));
stmt_vec_info stmt_info_b = dr_info_b->stmt;
bool preserves_scalar_order_p
= vect_preserves_scalar_order_p (dr_info_a, dr_info_b);
bool ignore_step_p
= (vf_one_p
&& (preserves_scalar_order_p
|| operand_equal_p (DR_STEP (dr_info_a->dr),
DR_STEP (dr_info_b->dr))));
/* Skip the pair if inter-iteration dependencies are irrelevant
and intra-iteration dependencies are guaranteed to be honored. */
if (ignore_step_p
&& (preserves_scalar_order_p
|| vectorizable_with_step_bound_p (dr_info_a, dr_info_b,
&lower_bound)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"no need for alias check between "
"%T and %T when VF is 1\n",
DR_REF (dr_info_a->dr), DR_REF (dr_info_b->dr));
continue;
}
/* See whether we can handle the alias using a bounds check on
the step, and whether that's likely to be the best approach.
(It might not be, for example, if the minimum step is much larger
than the number of bytes handled by one vector iteration.) */
if (!ignore_step_p
&& TREE_CODE (DR_STEP (dr_info_a->dr)) != INTEGER_CST
&& vectorizable_with_step_bound_p (dr_info_a, dr_info_b,
&lower_bound)
&& (vect_small_gap_p (loop_vinfo, dr_info_a, lower_bound)
|| vect_small_gap_p (loop_vinfo, dr_info_b, lower_bound)))
{
bool unsigned_p = dr_known_forward_stride_p (dr_info_a->dr);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "no alias between "
"%T and %T when the step %T is outside ",
DR_REF (dr_info_a->dr),
DR_REF (dr_info_b->dr),
DR_STEP (dr_info_a->dr));
if (unsigned_p)
dump_printf (MSG_NOTE, "[0");
else
{
dump_printf (MSG_NOTE, "(");
dump_dec (MSG_NOTE, poly_int64 (-lower_bound));
}
dump_printf (MSG_NOTE, ", ");
dump_dec (MSG_NOTE, lower_bound);
dump_printf (MSG_NOTE, ")\n");
}
vect_check_lower_bound (loop_vinfo, DR_STEP (dr_info_a->dr),
unsigned_p, lower_bound);
continue;
}
stmt_vec_info dr_group_first_a = DR_GROUP_FIRST_ELEMENT (stmt_info_a);
if (dr_group_first_a)
{
stmt_info_a = dr_group_first_a;
dr_info_a = STMT_VINFO_DR_INFO (stmt_info_a);
}
stmt_vec_info dr_group_first_b = DR_GROUP_FIRST_ELEMENT (stmt_info_b);
if (dr_group_first_b)
{
stmt_info_b = dr_group_first_b;
dr_info_b = STMT_VINFO_DR_INFO (stmt_info_b);
}
if (ignore_step_p)
{
segment_length_a = size_zero_node;
segment_length_b = size_zero_node;
}
else
{
if (!operand_equal_p (DR_STEP (dr_info_a->dr),
DR_STEP (dr_info_b->dr), 0))
length_factor = scalar_loop_iters;
else
length_factor = size_int (vect_factor);
segment_length_a = vect_vfa_segment_size (dr_info_a, length_factor);
segment_length_b = vect_vfa_segment_size (dr_info_b, length_factor);
}
access_size_a = vect_vfa_access_size (dr_info_a);
access_size_b = vect_vfa_access_size (dr_info_b);
align_a = vect_vfa_align (dr_info_a);
align_b = vect_vfa_align (dr_info_b);
/* See whether the alias is known at compilation time. */
if (operand_equal_p (DR_BASE_ADDRESS (dr_info_a->dr),
DR_BASE_ADDRESS (dr_info_b->dr), 0)
&& operand_equal_p (DR_OFFSET (dr_info_a->dr),
DR_OFFSET (dr_info_b->dr), 0)
&& TREE_CODE (DR_STEP (dr_info_a->dr)) == INTEGER_CST
&& TREE_CODE (DR_STEP (dr_info_b->dr)) == INTEGER_CST
&& poly_int_tree_p (segment_length_a)
&& poly_int_tree_p (segment_length_b))
{
int res = vect_compile_time_alias (dr_info_a, dr_info_b,
segment_length_a,
segment_length_b,
access_size_a,
access_size_b);
if (res >= 0 && dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"can tell at compile time that %T and %T",
DR_REF (dr_info_a->dr), DR_REF (dr_info_b->dr));
if (res == 0)
dump_printf (MSG_NOTE, " do not alias\n");
else
dump_printf (MSG_NOTE, " alias\n");
}
if (res == 0)
continue;
if (res == 1)
return opt_result::failure_at (stmt_info_b->stmt,
"not vectorized:"
" compilation time alias: %G%G",
stmt_info_a->stmt,
stmt_info_b->stmt);
}
dr_with_seg_len dr_a (dr_info_a->dr, segment_length_a,
access_size_a, align_a);
dr_with_seg_len dr_b (dr_info_b->dr, segment_length_b,
access_size_b, align_b);
/* Canonicalize the order to be the one that's needed for accurate
RAW, WAR and WAW flags, in cases where the data references are
well-ordered. The order doesn't really matter otherwise,
but we might as well be consistent. */
if (get_later_stmt (stmt_info_a, stmt_info_b) == stmt_info_a)
std::swap (dr_a, dr_b);
dr_with_seg_len_pair_t dr_with_seg_len_pair
(dr_a, dr_b, (preserves_scalar_order_p
? dr_with_seg_len_pair_t::WELL_ORDERED
: dr_with_seg_len_pair_t::REORDERED));
comp_alias_ddrs.safe_push (dr_with_seg_len_pair);
}
prune_runtime_alias_test_list (&comp_alias_ddrs, vect_factor);
unsigned int count = (comp_alias_ddrs.length ()
+ check_unequal_addrs.length ());
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"improved number of alias checks from %d to %d\n",
may_alias_ddrs.length (), count);
unsigned limit = param_vect_max_version_for_alias_checks;
if (flag_simd_cost_model == VECT_COST_MODEL_CHEAP)
limit = param_vect_max_version_for_alias_checks * 6 / 10;
if (count > limit)
return opt_result::failure_at
(vect_location,
"number of versioning for alias run-time tests exceeds %d "
"(--param vect-max-version-for-alias-checks)\n", limit);
return opt_result::success ();
}
/* Check whether we can use an internal function for a gather load
or scatter store. READ_P is true for loads and false for stores.
MASKED_P is true if the load or store is conditional. MEMORY_TYPE is
the type of the memory elements being loaded or stored. OFFSET_TYPE
is the type of the offset that is being applied to the invariant
base address. SCALE is the amount by which the offset should
be multiplied *after* it has been converted to address width.
Return true if the function is supported, storing the function id in
*IFN_OUT and the vector type for the offset in *OFFSET_VECTYPE_OUT. */
bool
vect_gather_scatter_fn_p (vec_info *vinfo, bool read_p, bool masked_p,
tree vectype, tree memory_type, tree offset_type,
int scale, internal_fn *ifn_out,
tree *offset_vectype_out)
{
unsigned int memory_bits = tree_to_uhwi (TYPE_SIZE (memory_type));
unsigned int element_bits = tree_to_uhwi (TYPE_SIZE (TREE_TYPE (vectype)));
if (element_bits != memory_bits)
/* For now the vector elements must be the same width as the
memory elements. */
return false;
/* Work out which function we need. */
internal_fn ifn;
if (read_p)
ifn = masked_p ? IFN_MASK_GATHER_LOAD : IFN_GATHER_LOAD;
else
ifn = masked_p ? IFN_MASK_SCATTER_STORE : IFN_SCATTER_STORE;
for (;;)
{
tree offset_vectype = get_vectype_for_scalar_type (vinfo, offset_type);
if (!offset_vectype)
return false;
/* Test whether the target supports this combination. */
if (internal_gather_scatter_fn_supported_p (ifn, vectype, memory_type,
offset_vectype, scale))
{
*ifn_out = ifn;
*offset_vectype_out = offset_vectype;
return true;
}
if (TYPE_PRECISION (offset_type) >= POINTER_SIZE
&& TYPE_PRECISION (offset_type) >= element_bits)
return false;
offset_type = build_nonstandard_integer_type
(TYPE_PRECISION (offset_type) * 2, TYPE_UNSIGNED (offset_type));
}
}
/* STMT_INFO is a call to an internal gather load or scatter store function.
Describe the operation in INFO. */
static void
vect_describe_gather_scatter_call (stmt_vec_info stmt_info,
gather_scatter_info *info)
{
gcall *call = as_a <gcall *> (stmt_info->stmt);
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
data_reference *dr = STMT_VINFO_DATA_REF (stmt_info);
info->ifn = gimple_call_internal_fn (call);
info->decl = NULL_TREE;
info->base = gimple_call_arg (call, 0);
info->offset = gimple_call_arg (call, 1);
info->offset_dt = vect_unknown_def_type;
info->offset_vectype = NULL_TREE;
info->scale = TREE_INT_CST_LOW (gimple_call_arg (call, 2));
info->element_type = TREE_TYPE (vectype);
info->memory_type = TREE_TYPE (DR_REF (dr));
}
/* Return true if a non-affine read or write in STMT_INFO is suitable for a
gather load or scatter store. Describe the operation in *INFO if so. */
bool
vect_check_gather_scatter (stmt_vec_info stmt_info, loop_vec_info loop_vinfo,
gather_scatter_info *info)
{
HOST_WIDE_INT scale = 1;
poly_int64 pbitpos, pbitsize;
class loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info);
tree offtype = NULL_TREE;
tree decl = NULL_TREE, base, off;
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
tree memory_type = TREE_TYPE (DR_REF (dr));
machine_mode pmode;
int punsignedp, reversep, pvolatilep = 0;
internal_fn ifn;
tree offset_vectype;
bool masked_p = false;
/* See whether this is already a call to a gather/scatter internal function.
If not, see whether it's a masked load or store. */
gcall *call = dyn_cast <gcall *> (stmt_info->stmt);
if (call && gimple_call_internal_p (call))
{
ifn = gimple_call_internal_fn (call);
if (internal_gather_scatter_fn_p (ifn))
{
vect_describe_gather_scatter_call (stmt_info, info);
return true;
}
masked_p = (ifn == IFN_MASK_LOAD || ifn == IFN_MASK_STORE);
}
/* True if we should aim to use internal functions rather than
built-in functions. */
bool use_ifn_p = (DR_IS_READ (dr)
? supports_vec_gather_load_p ()
: supports_vec_scatter_store_p ());
base = DR_REF (dr);
/* For masked loads/stores, DR_REF (dr) is an artificial MEM_REF,
see if we can use the def stmt of the address. */
if (masked_p
&& TREE_CODE (base) == MEM_REF
&& TREE_CODE (TREE_OPERAND (base, 0)) == SSA_NAME
&& integer_zerop (TREE_OPERAND (base, 1))
&& !expr_invariant_in_loop_p (loop, TREE_OPERAND (base, 0)))
{
gimple *def_stmt = SSA_NAME_DEF_STMT (TREE_OPERAND (base, 0));
if (is_gimple_assign (def_stmt)
&& gimple_assign_rhs_code (def_stmt) == ADDR_EXPR)
base = TREE_OPERAND (gimple_assign_rhs1 (def_stmt), 0);
}
/* The gather and scatter builtins need address of the form
loop_invariant + vector * {1, 2, 4, 8}
or
loop_invariant + sign_extend (vector) * { 1, 2, 4, 8 }.
Unfortunately DR_BASE_ADDRESS/DR_OFFSET can be a mixture
of loop invariants/SSA_NAMEs defined in the loop, with casts,
multiplications and additions in it. To get a vector, we need
a single SSA_NAME that will be defined in the loop and will
contain everything that is not loop invariant and that can be
vectorized. The following code attempts to find such a preexistng
SSA_NAME OFF and put the loop invariants into a tree BASE
that can be gimplified before the loop. */
base = get_inner_reference (base, &pbitsize, &pbitpos, &off, &pmode,
&punsignedp, &reversep, &pvolatilep);
if (reversep)
return false;
poly_int64 pbytepos = exact_div (pbitpos, BITS_PER_UNIT);
if (TREE_CODE (base) == MEM_REF)
{
if (!integer_zerop (TREE_OPERAND (base, 1)))
{
if (off == NULL_TREE)
off = wide_int_to_tree (sizetype, mem_ref_offset (base));
else
off = size_binop (PLUS_EXPR, off,
fold_convert (sizetype, TREE_OPERAND (base, 1)));
}
base = TREE_OPERAND (base, 0);
}
else
base = build_fold_addr_expr (base);
if (off == NULL_TREE)
off = size_zero_node;
/* If base is not loop invariant, either off is 0, then we start with just
the constant offset in the loop invariant BASE and continue with base
as OFF, otherwise give up.
We could handle that case by gimplifying the addition of base + off
into some SSA_NAME and use that as off, but for now punt. */
if (!expr_invariant_in_loop_p (loop, base))
{
if (!integer_zerop (off))
return false;
off = base;
base = size_int (pbytepos);
}
/* Otherwise put base + constant offset into the loop invariant BASE
and continue with OFF. */
else
{
base = fold_convert (sizetype, base);
base = size_binop (PLUS_EXPR, base, size_int (pbytepos));
}
/* OFF at this point may be either a SSA_NAME or some tree expression
from get_inner_reference. Try to peel off loop invariants from it
into BASE as long as possible. */
STRIP_NOPS (off);
while (offtype == NULL_TREE)
{
enum tree_code code;
tree op0, op1, add = NULL_TREE;
if (TREE_CODE (off) == SSA_NAME)
{
gimple *def_stmt = SSA_NAME_DEF_STMT (off);
if (expr_invariant_in_loop_p (loop, off))
return false;
if (gimple_code (def_stmt) != GIMPLE_ASSIGN)
break;
op0 = gimple_assign_rhs1 (def_stmt);
code = gimple_assign_rhs_code (def_stmt);
op1 = gimple_assign_rhs2 (def_stmt);
}
else
{
if (get_gimple_rhs_class (TREE_CODE (off)) == GIMPLE_TERNARY_RHS)
return false;
code = TREE_CODE (off);
extract_ops_from_tree (off, &code, &op0, &op1);
}
switch (code)
{
case POINTER_PLUS_EXPR:
case PLUS_EXPR:
if (expr_invariant_in_loop_p (loop, op0))
{
add = op0;
off = op1;
do_add:
add = fold_convert (sizetype, add);
if (scale != 1)
add = size_binop (MULT_EXPR, add, size_int (scale));
base = size_binop (PLUS_EXPR, base, add);
continue;
}
if (expr_invariant_in_loop_p (loop, op1))
{
add = op1;
off = op0;
goto do_add;
}
break;
case MINUS_EXPR:
if (expr_invariant_in_loop_p (loop, op1))
{
add = fold_convert (sizetype, op1);
add = size_binop (MINUS_EXPR, size_zero_node, add);
off = op0;
goto do_add;
}
break;
case MULT_EXPR:
if (scale == 1 && tree_fits_shwi_p (op1))
{
int new_scale = tree_to_shwi (op1);
/* Only treat this as a scaling operation if the target
supports it for at least some offset type. */
if (use_ifn_p
&& !vect_gather_scatter_fn_p (loop_vinfo, DR_IS_READ (dr),
masked_p, vectype, memory_type,
signed_char_type_node,
new_scale, &ifn,
&offset_vectype)
&& !vect_gather_scatter_fn_p (loop_vinfo, DR_IS_READ (dr),
masked_p, vectype, memory_type,
unsigned_char_type_node,
new_scale, &ifn,
&offset_vectype))
break;
scale = new_scale;
off = op0;
continue;
}
break;
case SSA_NAME:
off = op0;
continue;
CASE_CONVERT:
if (!POINTER_TYPE_P (TREE_TYPE (op0))
&& !INTEGRAL_TYPE_P (TREE_TYPE (op0)))
break;
/* Don't include the conversion if the target is happy with
the current offset type. */
if (use_ifn_p
&& vect_gather_scatter_fn_p (loop_vinfo, DR_IS_READ (dr),
masked_p, vectype, memory_type,
TREE_TYPE (off), scale, &ifn,
&offset_vectype))
break;
if (TYPE_PRECISION (TREE_TYPE (op0))
== TYPE_PRECISION (TREE_TYPE (off)))
{
off = op0;
continue;
}
if (TYPE_PRECISION (TREE_TYPE (op0))
< TYPE_PRECISION (TREE_TYPE (off)))
{
off = op0;
offtype = TREE_TYPE (off);
STRIP_NOPS (off);
continue;
}
break;
default:
break;
}
break;
}
/* If at the end OFF still isn't a SSA_NAME or isn't
defined in the loop, punt. */
if (TREE_CODE (off) != SSA_NAME
|| expr_invariant_in_loop_p (loop, off))
return false;
if (offtype == NULL_TREE)
offtype = TREE_TYPE (off);
if (use_ifn_p)
{
if (!vect_gather_scatter_fn_p (loop_vinfo, DR_IS_READ (dr), masked_p,
vectype, memory_type, offtype, scale,
&ifn, &offset_vectype))
return false;
}
else
{
if (DR_IS_READ (dr))
{
if (targetm.vectorize.builtin_gather)
decl = targetm.vectorize.builtin_gather (vectype, offtype, scale);
}
else
{
if (targetm.vectorize.builtin_scatter)
decl = targetm.vectorize.builtin_scatter (vectype, offtype, scale);
}
if (!decl)
return false;
ifn = IFN_LAST;
/* The offset vector type will be read from DECL when needed. */
offset_vectype = NULL_TREE;
}
info->ifn = ifn;
info->decl = decl;
info->base = base;
info->offset = off;
info->offset_dt = vect_unknown_def_type;
info->offset_vectype = offset_vectype;
info->scale = scale;
info->element_type = TREE_TYPE (vectype);
info->memory_type = memory_type;
return true;
}
/* Find the data references in STMT, analyze them with respect to LOOP and
append them to DATAREFS. Return false if datarefs in this stmt cannot
be handled. */
opt_result
vect_find_stmt_data_reference (loop_p loop, gimple *stmt,
vec<data_reference_p> *datarefs)
{
/* We can ignore clobbers for dataref analysis - they are removed during
loop vectorization and BB vectorization checks dependences with a
stmt walk. */
if (gimple_clobber_p (stmt))
return opt_result::success ();
if (gimple_has_volatile_ops (stmt))
return opt_result::failure_at (stmt, "not vectorized: volatile type: %G",
stmt);
if (stmt_can_throw_internal (cfun, stmt))
return opt_result::failure_at (stmt,
"not vectorized:"
" statement can throw an exception: %G",
stmt);
auto_vec<data_reference_p, 2> refs;
opt_result res = find_data_references_in_stmt (loop, stmt, &refs);
if (!res)
return res;
if (refs.is_empty ())
return opt_result::success ();
if (refs.length () > 1)
return opt_result::failure_at (stmt,
"not vectorized:"
" more than one data ref in stmt: %G", stmt);
if (gcall *call = dyn_cast <gcall *> (stmt))
if (!gimple_call_internal_p (call)
|| (gimple_call_internal_fn (call) != IFN_MASK_LOAD
&& gimple_call_internal_fn (call) != IFN_MASK_STORE))
return opt_result::failure_at (stmt,
"not vectorized: dr in a call %G", stmt);
data_reference_p dr = refs.pop ();
if (TREE_CODE (DR_REF (dr)) == COMPONENT_REF
&& DECL_BIT_FIELD (TREE_OPERAND (DR_REF (dr), 1)))
return opt_result::failure_at (stmt,
"not vectorized:"
" statement is bitfield access %G", stmt);
if (DR_BASE_ADDRESS (dr)
&& TREE_CODE (DR_BASE_ADDRESS (dr)) == INTEGER_CST)
return opt_result::failure_at (stmt,
"not vectorized:"
" base addr of dr is a constant\n");
/* Check whether this may be a SIMD lane access and adjust the
DR to make it easier for us to handle it. */
if (loop
&& loop->simduid
&& (!DR_BASE_ADDRESS (dr)
|| !DR_OFFSET (dr)
|| !DR_INIT (dr)
|| !DR_STEP (dr)))
{
struct data_reference *newdr
= create_data_ref (NULL, loop_containing_stmt (stmt), DR_REF (dr), stmt,
DR_IS_READ (dr), DR_IS_CONDITIONAL_IN_STMT (dr));
if (DR_BASE_ADDRESS (newdr)
&& DR_OFFSET (newdr)
&& DR_INIT (newdr)
&& DR_STEP (newdr)
&& TREE_CODE (DR_INIT (newdr)) == INTEGER_CST
&& integer_zerop (DR_STEP (newdr)))
{
tree base_address = DR_BASE_ADDRESS (newdr);
tree off = DR_OFFSET (newdr);
tree step = ssize_int (1);
if (integer_zerop (off)
&& TREE_CODE (base_address) == POINTER_PLUS_EXPR)
{
off = TREE_OPERAND (base_address, 1);
base_address = TREE_OPERAND (base_address, 0);
}
STRIP_NOPS (off);
if (TREE_CODE (off) == MULT_EXPR
&& tree_fits_uhwi_p (TREE_OPERAND (off, 1)))
{
step = TREE_OPERAND (off, 1);
off = TREE_OPERAND (off, 0);
STRIP_NOPS (off);
}
if (CONVERT_EXPR_P (off)
&& (TYPE_PRECISION (TREE_TYPE (TREE_OPERAND (off, 0)))
< TYPE_PRECISION (TREE_TYPE (off))))
off = TREE_OPERAND (off, 0);
if (TREE_CODE (off) == SSA_NAME)
{
gimple *def = SSA_NAME_DEF_STMT (off);
/* Look through widening conversion. */
if (is_gimple_assign (def)
&& CONVERT_EXPR_CODE_P (gimple_assign_rhs_code (def)))
{
tree rhs1 = gimple_assign_rhs1 (def);
if (TREE_CODE (rhs1) == SSA_NAME
&& INTEGRAL_TYPE_P (TREE_TYPE (rhs1))
&& (TYPE_PRECISION (TREE_TYPE (off))
> TYPE_PRECISION (TREE_TYPE (rhs1))))
def = SSA_NAME_DEF_STMT (rhs1);
}
if (is_gimple_call (def)
&& gimple_call_internal_p (def)
&& (gimple_call_internal_fn (def) == IFN_GOMP_SIMD_LANE))
{
tree arg = gimple_call_arg (def, 0);
tree reft = TREE_TYPE (DR_REF (newdr));
gcc_assert (TREE_CODE (arg) == SSA_NAME);
arg = SSA_NAME_VAR (arg);
if (arg == loop->simduid
/* For now. */
&& tree_int_cst_equal (TYPE_SIZE_UNIT (reft), step))
{
DR_BASE_ADDRESS (newdr) = base_address;
DR_OFFSET (newdr) = ssize_int (0);
DR_STEP (newdr) = step;
DR_OFFSET_ALIGNMENT (newdr) = BIGGEST_ALIGNMENT;
DR_STEP_ALIGNMENT (newdr) = highest_pow2_factor (step);
/* Mark as simd-lane access. */
tree arg2 = gimple_call_arg (def, 1);
newdr->aux = (void *) (-1 - tree_to_uhwi (arg2));
free_data_ref (dr);
datarefs->safe_push (newdr);
return opt_result::success ();
}
}
}
}
free_data_ref (newdr);
}
datarefs->safe_push (dr);
return opt_result::success ();
}
/* Function vect_analyze_data_refs.
Find all the data references in the loop or basic block.
The general structure of the analysis of data refs in the vectorizer is as
follows:
1- vect_analyze_data_refs(loop/bb): call
compute_data_dependences_for_loop/bb to find and analyze all data-refs
in the loop/bb and their dependences.
2- vect_analyze_dependences(): apply dependence testing using ddrs.
3- vect_analyze_drs_alignment(): check that ref_stmt.alignment is ok.
4- vect_analyze_drs_access(): check that ref_stmt.step is ok.
*/
opt_result
vect_analyze_data_refs (vec_info *vinfo, poly_uint64 *min_vf, bool *fatal)
{
class loop *loop = NULL;
unsigned int i;
struct data_reference *dr;
tree scalar_type;
DUMP_VECT_SCOPE ("vect_analyze_data_refs");
if (loop_vec_info loop_vinfo = dyn_cast <loop_vec_info> (vinfo))
loop = LOOP_VINFO_LOOP (loop_vinfo);
/* Go through the data-refs, check that the analysis succeeded. Update
pointer from stmt_vec_info struct to DR and vectype. */
vec<data_reference_p> datarefs = vinfo->shared->datarefs;
FOR_EACH_VEC_ELT (datarefs, i, dr)
{
enum { SG_NONE, GATHER, SCATTER } gatherscatter = SG_NONE;
poly_uint64 vf;
gcc_assert (DR_REF (dr));
stmt_vec_info stmt_info = vinfo->lookup_stmt (DR_STMT (dr));
gcc_assert (!stmt_info->dr_aux.dr);
stmt_info->dr_aux.dr = dr;
stmt_info->dr_aux.stmt = stmt_info;
/* Check that analysis of the data-ref succeeded. */
if (!DR_BASE_ADDRESS (dr) || !DR_OFFSET (dr) || !DR_INIT (dr)
|| !DR_STEP (dr))
{
bool maybe_gather
= DR_IS_READ (dr)
&& !TREE_THIS_VOLATILE (DR_REF (dr))
&& (targetm.vectorize.builtin_gather != NULL
|| supports_vec_gather_load_p ());
bool maybe_scatter
= DR_IS_WRITE (dr)
&& !TREE_THIS_VOLATILE (DR_REF (dr))
&& (targetm.vectorize.builtin_scatter != NULL
|| supports_vec_scatter_store_p ());
/* If target supports vector gather loads or scatter stores,
see if they can't be used. */
if (is_a <loop_vec_info> (vinfo)
&& !nested_in_vect_loop_p (loop, stmt_info))
{
if (maybe_gather || maybe_scatter)
{
if (maybe_gather)
gatherscatter = GATHER;
else
gatherscatter = SCATTER;
}
}
if (gatherscatter == SG_NONE)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: data ref analysis "
"failed %G", stmt_info->stmt);
if (is_a <bb_vec_info> (vinfo))
{
/* In BB vectorization the ref can still participate
in dependence analysis, we just can't vectorize it. */
STMT_VINFO_VECTORIZABLE (stmt_info) = false;
continue;
}
return opt_result::failure_at (stmt_info->stmt,
"not vectorized:"
" data ref analysis failed: %G",
stmt_info->stmt);
}
}
/* See if this was detected as SIMD lane access. */
if (dr->aux == (void *)-1
|| dr->aux == (void *)-2
|| dr->aux == (void *)-3
|| dr->aux == (void *)-4)
{
if (nested_in_vect_loop_p (loop, stmt_info))
return opt_result::failure_at (stmt_info->stmt,
"not vectorized:"
" data ref analysis failed: %G",
stmt_info->stmt);
STMT_VINFO_SIMD_LANE_ACCESS_P (stmt_info)
= -(uintptr_t) dr->aux;
}
tree base = get_base_address (DR_REF (dr));
if (base && VAR_P (base) && DECL_NONALIASED (base))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: base object not addressable "
"for stmt: %G", stmt_info->stmt);
if (is_a <bb_vec_info> (vinfo))
{
/* In BB vectorization the ref can still participate
in dependence analysis, we just can't vectorize it. */
STMT_VINFO_VECTORIZABLE (stmt_info) = false;
continue;
}
return opt_result::failure_at (stmt_info->stmt,
"not vectorized: base object not"
" addressable for stmt: %G",
stmt_info->stmt);
}
if (is_a <loop_vec_info> (vinfo)
&& DR_STEP (dr)
&& TREE_CODE (DR_STEP (dr)) != INTEGER_CST)
{
if (nested_in_vect_loop_p (loop, stmt_info))
return opt_result::failure_at (stmt_info->stmt,
"not vectorized: "
"not suitable for strided load %G",
stmt_info->stmt);
STMT_VINFO_STRIDED_P (stmt_info) = true;
}
/* Update DR field in stmt_vec_info struct. */
/* If the dataref is in an inner-loop of the loop that is considered for
for vectorization, we also want to analyze the access relative to
the outer-loop (DR contains information only relative to the
inner-most enclosing loop). We do that by building a reference to the
first location accessed by the inner-loop, and analyze it relative to
the outer-loop. */
if (loop && nested_in_vect_loop_p (loop, stmt_info))
{
/* Build a reference to the first location accessed by the
inner loop: *(BASE + INIT + OFFSET). By construction,
this address must be invariant in the inner loop, so we
can consider it as being used in the outer loop. */
tree base = unshare_expr (DR_BASE_ADDRESS (dr));
tree offset = unshare_expr (DR_OFFSET (dr));
tree init = unshare_expr (DR_INIT (dr));
tree init_offset = fold_build2 (PLUS_EXPR, TREE_TYPE (offset),
init, offset);
tree init_addr = fold_build_pointer_plus (base, init_offset);
tree init_ref = build_fold_indirect_ref (init_addr);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"analyze in outer loop: %T\n", init_ref);
opt_result res
= dr_analyze_innermost (&STMT_VINFO_DR_WRT_VEC_LOOP (stmt_info),
init_ref, loop, stmt_info->stmt);
if (!res)
/* dr_analyze_innermost already explained the failure. */
return res;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"\touter base_address: %T\n"
"\touter offset from base address: %T\n"
"\touter constant offset from base address: %T\n"
"\touter step: %T\n"
"\touter base alignment: %d\n\n"
"\touter base misalignment: %d\n"
"\touter offset alignment: %d\n"
"\touter step alignment: %d\n",
STMT_VINFO_DR_BASE_ADDRESS (stmt_info),
STMT_VINFO_DR_OFFSET (stmt_info),
STMT_VINFO_DR_INIT (stmt_info),
STMT_VINFO_DR_STEP (stmt_info),
STMT_VINFO_DR_BASE_ALIGNMENT (stmt_info),
STMT_VINFO_DR_BASE_MISALIGNMENT (stmt_info),
STMT_VINFO_DR_OFFSET_ALIGNMENT (stmt_info),
STMT_VINFO_DR_STEP_ALIGNMENT (stmt_info));
}
/* Set vectype for STMT. */
scalar_type = TREE_TYPE (DR_REF (dr));
tree vectype = get_vectype_for_scalar_type (vinfo, scalar_type);
if (!vectype)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: no vectype for stmt: %G",
stmt_info->stmt);
dump_printf (MSG_MISSED_OPTIMIZATION, " scalar_type: ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_DETAILS,
scalar_type);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
if (is_a <bb_vec_info> (vinfo))
{
/* No vector type is fine, the ref can still participate
in dependence analysis, we just can't vectorize it. */
STMT_VINFO_VECTORIZABLE (stmt_info) = false;
continue;
}
if (fatal)
*fatal = false;
return opt_result::failure_at (stmt_info->stmt,
"not vectorized:"
" no vectype for stmt: %G"
" scalar_type: %T\n",
stmt_info->stmt, scalar_type);
}
else
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"got vectype for stmt: %G%T\n",
stmt_info->stmt, vectype);
}
/* Adjust the minimal vectorization factor according to the
vector type. */
vf = TYPE_VECTOR_SUBPARTS (vectype);
*min_vf = upper_bound (*min_vf, vf);
/* Leave the BB vectorizer to pick the vector type later, based on
the final dataref group size and SLP node size. */
if (is_a <loop_vec_info> (vinfo))
STMT_VINFO_VECTYPE (stmt_info) = vectype;
if (gatherscatter != SG_NONE)
{
gather_scatter_info gs_info;
if (!vect_check_gather_scatter (stmt_info,
as_a <loop_vec_info> (vinfo),
&gs_info)
|| !get_vectype_for_scalar_type (vinfo,
TREE_TYPE (gs_info.offset)))
{
if (fatal)
*fatal = false;
return opt_result::failure_at
(stmt_info->stmt,
(gatherscatter == GATHER)
? "not vectorized: not suitable for gather load %G"
: "not vectorized: not suitable for scatter store %G",
stmt_info->stmt);
}
STMT_VINFO_GATHER_SCATTER_P (stmt_info) = gatherscatter;
}
}
/* We used to stop processing and prune the list here. Verify we no
longer need to. */
gcc_assert (i == datarefs.length ());
return opt_result::success ();
}
/* Function vect_get_new_vect_var.
Returns a name for a new variable. The current naming scheme appends the
prefix "vect_" or "vect_p" (depending on the value of VAR_KIND) to
the name of vectorizer generated variables, and appends that to NAME if
provided. */
tree
vect_get_new_vect_var (tree type, enum vect_var_kind var_kind, const char *name)
{
const char *prefix;
tree new_vect_var;
switch (var_kind)
{
case vect_simple_var:
prefix = "vect";
break;
case vect_scalar_var:
prefix = "stmp";
break;
case vect_mask_var:
prefix = "mask";
break;
case vect_pointer_var:
prefix = "vectp";
break;
default:
gcc_unreachable ();
}
if (name)
{
char* tmp = concat (prefix, "_", name, NULL);
new_vect_var = create_tmp_reg (type, tmp);
free (tmp);
}
else
new_vect_var = create_tmp_reg (type, prefix);
return new_vect_var;
}
/* Like vect_get_new_vect_var but return an SSA name. */
tree
vect_get_new_ssa_name (tree type, enum vect_var_kind var_kind, const char *name)
{
const char *prefix;
tree new_vect_var;
switch (var_kind)
{
case vect_simple_var:
prefix = "vect";
break;
case vect_scalar_var:
prefix = "stmp";
break;
case vect_pointer_var:
prefix = "vectp";
break;
default:
gcc_unreachable ();
}
if (name)
{
char* tmp = concat (prefix, "_", name, NULL);
new_vect_var = make_temp_ssa_name (type, NULL, tmp);
free (tmp);
}
else
new_vect_var = make_temp_ssa_name (type, NULL, prefix);
return new_vect_var;
}
/* Duplicate ptr info and set alignment/misaligment on NAME from DR_INFO. */
static void
vect_duplicate_ssa_name_ptr_info (tree name, dr_vec_info *dr_info)
{
duplicate_ssa_name_ptr_info (name, DR_PTR_INFO (dr_info->dr));
int misalign = DR_MISALIGNMENT (dr_info);
if (misalign == DR_MISALIGNMENT_UNKNOWN)
mark_ptr_info_alignment_unknown (SSA_NAME_PTR_INFO (name));
else
set_ptr_info_alignment (SSA_NAME_PTR_INFO (name),
known_alignment (DR_TARGET_ALIGNMENT (dr_info)),
misalign);
}
/* Function vect_create_addr_base_for_vector_ref.
Create an expression that computes the address of the first memory location
that will be accessed for a data reference.
Input:
STMT_INFO: The statement containing the data reference.
NEW_STMT_LIST: Must be initialized to NULL_TREE or a statement list.
OFFSET: Optional. If supplied, it is be added to the initial address.
LOOP: Specify relative to which loop-nest should the address be computed.
For example, when the dataref is in an inner-loop nested in an
outer-loop that is now being vectorized, LOOP can be either the
outer-loop, or the inner-loop. The first memory location accessed
by the following dataref ('in' points to short):
for (i=0; i<N; i++)
for (j=0; j<M; j++)
s += in[i+j]
is as follows:
if LOOP=i_loop: &in (relative to i_loop)
if LOOP=j_loop: &in+i*2B (relative to j_loop)
BYTE_OFFSET: Optional, defaulted to NULL. If supplied, it is added to the
initial address. Unlike OFFSET, which is number of elements to
be added, BYTE_OFFSET is measured in bytes.
Output:
1. Return an SSA_NAME whose value is the address of the memory location of
the first vector of the data reference.
2. If new_stmt_list is not NULL_TREE after return then the caller must insert
these statement(s) which define the returned SSA_NAME.
FORNOW: We are only handling array accesses with step 1. */
tree
vect_create_addr_base_for_vector_ref (stmt_vec_info stmt_info,
gimple_seq *new_stmt_list,
tree offset,
tree byte_offset)
{
dr_vec_info *dr_info = STMT_VINFO_DR_INFO (stmt_info);
struct data_reference *dr = dr_info->dr;
const char *base_name;
tree addr_base;
tree dest;
gimple_seq seq = NULL;
tree vect_ptr_type;
tree step = TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (dr)));
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
innermost_loop_behavior *drb = vect_dr_behavior (dr_info);
tree data_ref_base = unshare_expr (drb->base_address);
tree base_offset = unshare_expr (get_dr_vinfo_offset (dr_info, true));
tree init = unshare_expr (drb->init);
if (loop_vinfo)
base_name = get_name (data_ref_base);
else
{
base_offset = ssize_int (0);
init = ssize_int (0);
base_name = get_name (DR_REF (dr));
}
/* Create base_offset */
base_offset = size_binop (PLUS_EXPR,
fold_convert (sizetype, base_offset),
fold_convert (sizetype, init));
if (offset)
{
offset = fold_build2 (MULT_EXPR, sizetype,
fold_convert (sizetype, offset), step);
base_offset = fold_build2 (PLUS_EXPR, sizetype,
base_offset, offset);
}
if (byte_offset)
{
byte_offset = fold_convert (sizetype, byte_offset);
base_offset = fold_build2 (PLUS_EXPR, sizetype,
base_offset, byte_offset);
}
/* base + base_offset */
if (loop_vinfo)
addr_base = fold_build_pointer_plus (data_ref_base, base_offset);
else
{
addr_base = build1 (ADDR_EXPR,
build_pointer_type (TREE_TYPE (DR_REF (dr))),
unshare_expr (DR_REF (dr)));
}
vect_ptr_type = build_pointer_type (STMT_VINFO_VECTYPE (stmt_info));
dest = vect_get_new_vect_var (vect_ptr_type, vect_pointer_var, base_name);
addr_base = force_gimple_operand (addr_base, &seq, true, dest);
gimple_seq_add_seq (new_stmt_list, seq);
if (DR_PTR_INFO (dr)
&& TREE_CODE (addr_base) == SSA_NAME
/* We should only duplicate pointer info to newly created SSA names. */
&& SSA_NAME_VAR (addr_base) == dest)
{
vect_duplicate_ssa_name_ptr_info (addr_base, dr_info);
if (offset || byte_offset)
mark_ptr_info_alignment_unknown (SSA_NAME_PTR_INFO (addr_base));
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "created %T\n", addr_base);
return addr_base;
}
/* Function vect_create_data_ref_ptr.
Create a new pointer-to-AGGR_TYPE variable (ap), that points to the first
location accessed in the loop by STMT_INFO, along with the def-use update
chain to appropriately advance the pointer through the loop iterations.
Also set aliasing information for the pointer. This pointer is used by
the callers to this function to create a memory reference expression for
vector load/store access.
Input:
1. STMT_INFO: a stmt that references memory. Expected to be of the form
GIMPLE_ASSIGN <name, data-ref> or
GIMPLE_ASSIGN <data-ref, name>.
2. AGGR_TYPE: the type of the reference, which should be either a vector
or an array.
3. AT_LOOP: the loop where the vector memref is to be created.
4. OFFSET (optional): an offset to be added to the initial address accessed
by the data-ref in STMT_INFO.
5. BSI: location where the new stmts are to be placed if there is no loop
6. ONLY_INIT: indicate if ap is to be updated in the loop, or remain
pointing to the initial address.
7. BYTE_OFFSET (optional, defaults to NULL): a byte offset to be added
to the initial address accessed by the data-ref in STMT_INFO. This is
similar to OFFSET, but OFFSET is counted in elements, while BYTE_OFFSET
in bytes.
8. IV_STEP (optional, defaults to NULL): the amount that should be added
to the IV during each iteration of the loop. NULL says to move
by one copy of AGGR_TYPE up or down, depending on the step of the
data reference.
Output:
1. Declare a new ptr to vector_type, and have it point to the base of the
data reference (initial addressed accessed by the data reference).
For example, for vector of type V8HI, the following code is generated:
v8hi *ap;
ap = (v8hi *)initial_address;
if OFFSET is not supplied:
initial_address = &a[init];
if OFFSET is supplied:
initial_address = &a[init + OFFSET];
if BYTE_OFFSET is supplied:
initial_address = &a[init] + BYTE_OFFSET;
Return the initial_address in INITIAL_ADDRESS.
2. If ONLY_INIT is true, just return the initial pointer. Otherwise, also
update the pointer in each iteration of the loop.
Return the increment stmt that updates the pointer in PTR_INCR.
3. Return the pointer. */
tree
vect_create_data_ref_ptr (stmt_vec_info stmt_info, tree aggr_type,
class loop *at_loop, tree offset,
tree *initial_address, gimple_stmt_iterator *gsi,
gimple **ptr_incr, bool only_init,
tree byte_offset, tree iv_step)
{
const char *base_name;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
class loop *loop = NULL;
bool nested_in_vect_loop = false;
class loop *containing_loop = NULL;
tree aggr_ptr_type;
tree aggr_ptr;
tree new_temp;
gimple_seq new_stmt_list = NULL;
edge pe = NULL;
basic_block new_bb;
tree aggr_ptr_init;
dr_vec_info *dr_info = STMT_VINFO_DR_INFO (stmt_info);
struct data_reference *dr = dr_info->dr;
tree aptr;
gimple_stmt_iterator incr_gsi;
bool insert_after;
tree indx_before_incr, indx_after_incr;
gimple *incr;
bb_vec_info bb_vinfo = STMT_VINFO_BB_VINFO (stmt_info);
gcc_assert (iv_step != NULL_TREE
|| TREE_CODE (aggr_type) == ARRAY_TYPE
|| TREE_CODE (aggr_type) == VECTOR_TYPE);
if (loop_vinfo)
{
loop = LOOP_VINFO_LOOP (loop_vinfo);
nested_in_vect_loop = nested_in_vect_loop_p (loop, stmt_info);
containing_loop = (gimple_bb (stmt_info->stmt))->loop_father;
pe = loop_preheader_edge (loop);
}
else
{
gcc_assert (bb_vinfo);
only_init = true;
*ptr_incr = NULL;
}
/* Create an expression for the first address accessed by this load
in LOOP. */
base_name = get_name (DR_BASE_ADDRESS (dr));
if (dump_enabled_p ())
{
tree dr_base_type = TREE_TYPE (DR_BASE_OBJECT (dr));
dump_printf_loc (MSG_NOTE, vect_location,
"create %s-pointer variable to type: %T",
get_tree_code_name (TREE_CODE (aggr_type)),
aggr_type);
if (TREE_CODE (dr_base_type) == ARRAY_TYPE)
dump_printf (MSG_NOTE, " vectorizing an array ref: ");
else if (TREE_CODE (dr_base_type) == VECTOR_TYPE)
dump_printf (MSG_NOTE, " vectorizing a vector ref: ");
else if (TREE_CODE (dr_base_type) == RECORD_TYPE)
dump_printf (MSG_NOTE, " vectorizing a record based array ref: ");
else
dump_printf (MSG_NOTE, " vectorizing a pointer ref: ");
dump_printf (MSG_NOTE, "%T\n", DR_BASE_OBJECT (dr));
}
/* (1) Create the new aggregate-pointer variable.
Vector and array types inherit the alias set of their component
type by default so we need to use a ref-all pointer if the data
reference does not conflict with the created aggregated data
reference because it is not addressable. */
bool need_ref_all = false;
if (!alias_sets_conflict_p (get_alias_set (aggr_type),
get_alias_set (DR_REF (dr))))
need_ref_all = true;
/* Likewise for any of the data references in the stmt group. */
else if (DR_GROUP_SIZE (stmt_info) > 1)
{
stmt_vec_info sinfo = DR_GROUP_FIRST_ELEMENT (stmt_info);
do
{
struct data_reference *sdr = STMT_VINFO_DATA_REF (sinfo);
if (!alias_sets_conflict_p (get_alias_set (aggr_type),
get_alias_set (DR_REF (sdr))))
{
need_ref_all = true;
break;
}
sinfo = DR_GROUP_NEXT_ELEMENT (sinfo);
}
while (sinfo);
}
aggr_ptr_type = build_pointer_type_for_mode (aggr_type, ptr_mode,
need_ref_all);
aggr_ptr = vect_get_new_vect_var (aggr_ptr_type, vect_pointer_var, base_name);
/* Note: If the dataref is in an inner-loop nested in LOOP, and we are
vectorizing LOOP (i.e., outer-loop vectorization), we need to create two
def-use update cycles for the pointer: one relative to the outer-loop
(LOOP), which is what steps (3) and (4) below do. The other is relative
to the inner-loop (which is the inner-most loop containing the dataref),
and this is done be step (5) below.
When vectorizing inner-most loops, the vectorized loop (LOOP) is also the
inner-most loop, and so steps (3),(4) work the same, and step (5) is
redundant. Steps (3),(4) create the following:
vp0 = &base_addr;
LOOP: vp1 = phi(vp0,vp2)
...
...
vp2 = vp1 + step
goto LOOP
If there is an inner-loop nested in loop, then step (5) will also be
applied, and an additional update in the inner-loop will be created:
vp0 = &base_addr;
LOOP: vp1 = phi(vp0,vp2)
...
inner: vp3 = phi(vp1,vp4)
vp4 = vp3 + inner_step
if () goto inner
...
vp2 = vp1 + step
if () goto LOOP */
/* (2) Calculate the initial address of the aggregate-pointer, and set
the aggregate-pointer to point to it before the loop. */
/* Create: (&(base[init_val+offset]+byte_offset) in the loop preheader. */
new_temp = vect_create_addr_base_for_vector_ref (stmt_info, &new_stmt_list,
offset, byte_offset);
if (new_stmt_list)
{
if (pe)
{
new_bb = gsi_insert_seq_on_edge_immediate (pe, new_stmt_list);
gcc_assert (!new_bb);
}
else
gsi_insert_seq_before (gsi, new_stmt_list, GSI_SAME_STMT);
}
*initial_address = new_temp;
aggr_ptr_init = new_temp;
/* (3) Handle the updating of the aggregate-pointer inside the loop.
This is needed when ONLY_INIT is false, and also when AT_LOOP is the
inner-loop nested in LOOP (during outer-loop vectorization). */
/* No update in loop is required. */
if (only_init && (!loop_vinfo || at_loop == loop))
aptr = aggr_ptr_init;
else
{
/* Accesses to invariant addresses should be handled specially
by the caller. */
tree step = vect_dr_behavior (dr_info)->step;
gcc_assert (!integer_zerop (step));
if (iv_step == NULL_TREE)
{
/* The step of the aggregate pointer is the type size,
negated for downward accesses. */
iv_step = TYPE_SIZE_UNIT (aggr_type);
if (tree_int_cst_sgn (step) == -1)
iv_step = fold_build1 (NEGATE_EXPR, TREE_TYPE (iv_step), iv_step);
}
standard_iv_increment_position (loop, &incr_gsi, &insert_after);
create_iv (aggr_ptr_init,
fold_convert (aggr_ptr_type, iv_step),
aggr_ptr, loop, &incr_gsi, insert_after,
&indx_before_incr, &indx_after_incr);
incr = gsi_stmt (incr_gsi);
loop_vinfo->add_stmt (incr);
/* Copy the points-to information if it exists. */
if (DR_PTR_INFO (dr))
{
vect_duplicate_ssa_name_ptr_info (indx_before_incr, dr_info);
vect_duplicate_ssa_name_ptr_info (indx_after_incr, dr_info);
}
if (ptr_incr)
*ptr_incr = incr;
aptr = indx_before_incr;
}
if (!nested_in_vect_loop || only_init)
return aptr;
/* (4) Handle the updating of the aggregate-pointer inside the inner-loop
nested in LOOP, if exists. */
gcc_assert (nested_in_vect_loop);
if (!only_init)
{
standard_iv_increment_position (containing_loop, &incr_gsi,
&insert_after);
create_iv (aptr, fold_convert (aggr_ptr_type, DR_STEP (dr)), aggr_ptr,
containing_loop, &incr_gsi, insert_after, &indx_before_incr,
&indx_after_incr);
incr = gsi_stmt (incr_gsi);
loop_vinfo->add_stmt (incr);
/* Copy the points-to information if it exists. */
if (DR_PTR_INFO (dr))
{
vect_duplicate_ssa_name_ptr_info (indx_before_incr, dr_info);
vect_duplicate_ssa_name_ptr_info (indx_after_incr, dr_info);
}
if (ptr_incr)
*ptr_incr = incr;
return indx_before_incr;
}
else
gcc_unreachable ();
}
/* Function bump_vector_ptr
Increment a pointer (to a vector type) by vector-size. If requested,
i.e. if PTR-INCR is given, then also connect the new increment stmt
to the existing def-use update-chain of the pointer, by modifying
the PTR_INCR as illustrated below:
The pointer def-use update-chain before this function:
DATAREF_PTR = phi (p_0, p_2)
....
PTR_INCR: p_2 = DATAREF_PTR + step
The pointer def-use update-chain after this function:
DATAREF_PTR = phi (p_0, p_2)
....
NEW_DATAREF_PTR = DATAREF_PTR + BUMP
....
PTR_INCR: p_2 = NEW_DATAREF_PTR + step
Input:
DATAREF_PTR - ssa_name of a pointer (to vector type) that is being updated
in the loop.
PTR_INCR - optional. The stmt that updates the pointer in each iteration of
the loop. The increment amount across iterations is expected
to be vector_size.
BSI - location where the new update stmt is to be placed.
STMT_INFO - the original scalar memory-access stmt that is being vectorized.
BUMP - optional. The offset by which to bump the pointer. If not given,
the offset is assumed to be vector_size.
Output: Return NEW_DATAREF_PTR as illustrated above.
*/
tree
bump_vector_ptr (tree dataref_ptr, gimple *ptr_incr, gimple_stmt_iterator *gsi,
stmt_vec_info stmt_info, tree bump)
{
struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info);
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
tree update = TYPE_SIZE_UNIT (vectype);
gassign *incr_stmt;
ssa_op_iter iter;
use_operand_p use_p;
tree new_dataref_ptr;
if (bump)
update = bump;
if (TREE_CODE (dataref_ptr) == SSA_NAME)
new_dataref_ptr = copy_ssa_name (dataref_ptr);
else
new_dataref_ptr = make_ssa_name (TREE_TYPE (dataref_ptr));
incr_stmt = gimple_build_assign (new_dataref_ptr, POINTER_PLUS_EXPR,
dataref_ptr, update);
vect_finish_stmt_generation (stmt_info, incr_stmt, gsi);
/* Copy the points-to information if it exists. */
if (DR_PTR_INFO (dr))
{
duplicate_ssa_name_ptr_info (new_dataref_ptr, DR_PTR_INFO (dr));
mark_ptr_info_alignment_unknown (SSA_NAME_PTR_INFO (new_dataref_ptr));
}
if (!ptr_incr)
return new_dataref_ptr;
/* Update the vector-pointer's cross-iteration increment. */
FOR_EACH_SSA_USE_OPERAND (use_p, ptr_incr, iter, SSA_OP_USE)
{
tree use = USE_FROM_PTR (use_p);
if (use == dataref_ptr)
SET_USE (use_p, new_dataref_ptr);
else
gcc_assert (operand_equal_p (use, update, 0));
}
return new_dataref_ptr;
}
/* Copy memory reference info such as base/clique from the SRC reference
to the DEST MEM_REF. */
void
vect_copy_ref_info (tree dest, tree src)
{
if (TREE_CODE (dest) != MEM_REF)
return;
tree src_base = src;
while (handled_component_p (src_base))
src_base = TREE_OPERAND (src_base, 0);
if (TREE_CODE (src_base) != MEM_REF
&& TREE_CODE (src_base) != TARGET_MEM_REF)
return;
MR_DEPENDENCE_CLIQUE (dest) = MR_DEPENDENCE_CLIQUE (src_base);
MR_DEPENDENCE_BASE (dest) = MR_DEPENDENCE_BASE (src_base);
}
/* Function vect_create_destination_var.
Create a new temporary of type VECTYPE. */
tree
vect_create_destination_var (tree scalar_dest, tree vectype)
{
tree vec_dest;
const char *name;
char *new_name;
tree type;
enum vect_var_kind kind;
kind = vectype
? VECTOR_BOOLEAN_TYPE_P (vectype)
? vect_mask_var
: vect_simple_var
: vect_scalar_var;
type = vectype ? vectype : TREE_TYPE (scalar_dest);
gcc_assert (TREE_CODE (scalar_dest) == SSA_NAME);
name = get_name (scalar_dest);
if (name)
new_name = xasprintf ("%s_%u", name, SSA_NAME_VERSION (scalar_dest));
else
new_name = xasprintf ("_%u", SSA_NAME_VERSION (scalar_dest));
vec_dest = vect_get_new_vect_var (type, kind, new_name);
free (new_name);
return vec_dest;
}
/* Function vect_grouped_store_supported.
Returns TRUE if interleave high and interleave low permutations
are supported, and FALSE otherwise. */
bool
vect_grouped_store_supported (tree vectype, unsigned HOST_WIDE_INT count)
{
machine_mode mode = TYPE_MODE (vectype);
/* vect_permute_store_chain requires the group size to be equal to 3 or
be a power of two. */
if (count != 3 && exact_log2 (count) == -1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"the size of the group of accesses"
" is not a power of 2 or not eqaul to 3\n");
return false;
}
/* Check that the permutation is supported. */
if (VECTOR_MODE_P (mode))
{
unsigned int i;
if (count == 3)
{
unsigned int j0 = 0, j1 = 0, j2 = 0;
unsigned int i, j;
unsigned int nelt;
if (!GET_MODE_NUNITS (mode).is_constant (&nelt))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"cannot handle groups of 3 stores for"
" variable-length vectors\n");
return false;
}
vec_perm_builder sel (nelt, nelt, 1);
sel.quick_grow (nelt);
vec_perm_indices indices;
for (j = 0; j < 3; j++)
{
int nelt0 = ((3 - j) * nelt) % 3;
int nelt1 = ((3 - j) * nelt + 1) % 3;
int nelt2 = ((3 - j) * nelt + 2) % 3;
for (i = 0; i < nelt; i++)
{
if (3 * i + nelt0 < nelt)
sel[3 * i + nelt0] = j0++;
if (3 * i + nelt1 < nelt)
sel[3 * i + nelt1] = nelt + j1++;
if (3 * i + nelt2 < nelt)
sel[3 * i + nelt2] = 0;
}
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (mode, indices))
{
if (dump_enabled_p ())
dump_printf (MSG_MISSED_OPTIMIZATION,
"permutation op not supported by target.\n");
return false;
}
for (i = 0; i < nelt; i++)
{
if (3 * i + nelt0 < nelt)
sel[3 * i + nelt0] = 3 * i + nelt0;
if (3 * i + nelt1 < nelt)
sel[3 * i + nelt1] = 3 * i + nelt1;
if (3 * i + nelt2 < nelt)
sel[3 * i + nelt2] = nelt + j2++;
}
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (mode, indices))
{
if (dump_enabled_p ())
dump_printf (MSG_MISSED_OPTIMIZATION,
"permutation op not supported by target.\n");
return false;
}
}
return true;
}
else
{
/* If length is not equal to 3 then only power of 2 is supported. */
gcc_assert (pow2p_hwi (count));
poly_uint64 nelt = GET_MODE_NUNITS (mode);
/* The encoding has 2 interleaved stepped patterns. */
vec_perm_builder sel (nelt, 2, 3);
sel.quick_grow (6);
for (i = 0; i < 3; i++)
{
sel[i * 2] = i;
sel[i * 2 + 1] = i + nelt;
}
vec_perm_indices indices (sel, 2, nelt);
if (can_vec_perm_const_p (mode, indices))
{
for (i = 0; i < 6; i++)
sel[i] += exact_div (nelt, 2);
indices.new_vector (sel, 2, nelt);
if (can_vec_perm_const_p (mode, indices))
return true;
}
}
}
if (dump_enabled_p ())
dump_printf (MSG_MISSED_OPTIMIZATION,
"permutation op not supported by target.\n");
return false;
}
/* Return TRUE if vec_{mask_}store_lanes is available for COUNT vectors of
type VECTYPE. MASKED_P says whether the masked form is needed. */
bool
vect_store_lanes_supported (tree vectype, unsigned HOST_WIDE_INT count,
bool masked_p)
{
if (masked_p)
return vect_lanes_optab_supported_p ("vec_mask_store_lanes",
vec_mask_store_lanes_optab,
vectype, count);
else
return vect_lanes_optab_supported_p ("vec_store_lanes",
vec_store_lanes_optab,
vectype, count);
}
/* Function vect_permute_store_chain.
Given a chain of interleaved stores in DR_CHAIN of LENGTH that must be
a power of 2 or equal to 3, generate interleave_high/low stmts to reorder
the data correctly for the stores. Return the final references for stores
in RESULT_CHAIN.
E.g., LENGTH is 4 and the scalar type is short, i.e., VF is 8.
The input is 4 vectors each containing 8 elements. We assign a number to
each element, the input sequence is:
1st vec: 0 1 2 3 4 5 6 7
2nd vec: 8 9 10 11 12 13 14 15
3rd vec: 16 17 18 19 20 21 22 23
4th vec: 24 25 26 27 28 29 30 31
The output sequence should be:
1st vec: 0 8 16 24 1 9 17 25
2nd vec: 2 10 18 26 3 11 19 27
3rd vec: 4 12 20 28 5 13 21 30
4th vec: 6 14 22 30 7 15 23 31
i.e., we interleave the contents of the four vectors in their order.
We use interleave_high/low instructions to create such output. The input of
each interleave_high/low operation is two vectors:
1st vec 2nd vec
0 1 2 3 4 5 6 7
the even elements of the result vector are obtained left-to-right from the
high/low elements of the first vector. The odd elements of the result are
obtained left-to-right from the high/low elements of the second vector.
The output of interleave_high will be: 0 4 1 5
and of interleave_low: 2 6 3 7
The permutation is done in log LENGTH stages. In each stage interleave_high
and interleave_low stmts are created for each pair of vectors in DR_CHAIN,
where the first argument is taken from the first half of DR_CHAIN and the
second argument from it's second half.
In our example,
I1: interleave_high (1st vec, 3rd vec)
I2: interleave_low (1st vec, 3rd vec)
I3: interleave_high (2nd vec, 4th vec)
I4: interleave_low (2nd vec, 4th vec)
The output for the first stage is:
I1: 0 16 1 17 2 18 3 19
I2: 4 20 5 21 6 22 7 23
I3: 8 24 9 25 10 26 11 27
I4: 12 28 13 29 14 30 15 31
The output of the second stage, i.e. the final result is:
I1: 0 8 16 24 1 9 17 25
I2: 2 10 18 26 3 11 19 27
I3: 4 12 20 28 5 13 21 30
I4: 6 14 22 30 7 15 23 31. */
void
vect_permute_store_chain (vec<tree> dr_chain,
unsigned int length,
stmt_vec_info stmt_info,
gimple_stmt_iterator *gsi,
vec<tree> *result_chain)
{
tree vect1, vect2, high, low;
gimple *perm_stmt;
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
tree perm_mask_low, perm_mask_high;
tree data_ref;
tree perm3_mask_low, perm3_mask_high;
unsigned int i, j, n, log_length = exact_log2 (length);
result_chain->quick_grow (length);
memcpy (result_chain->address (), dr_chain.address (),
length * sizeof (tree));
if (length == 3)
{
/* vect_grouped_store_supported ensures that this is constant. */
unsigned int nelt = TYPE_VECTOR_SUBPARTS (vectype).to_constant ();
unsigned int j0 = 0, j1 = 0, j2 = 0;
vec_perm_builder sel (nelt, nelt, 1);
sel.quick_grow (nelt);
vec_perm_indices indices;
for (j = 0; j < 3; j++)
{
int nelt0 = ((3 - j) * nelt) % 3;
int nelt1 = ((3 - j) * nelt + 1) % 3;
int nelt2 = ((3 - j) * nelt + 2) % 3;
for (i = 0; i < nelt; i++)
{
if (3 * i + nelt0 < nelt)
sel[3 * i + nelt0] = j0++;
if (3 * i + nelt1 < nelt)
sel[3 * i + nelt1] = nelt + j1++;
if (3 * i + nelt2 < nelt)
sel[3 * i + nelt2] = 0;
}
indices.new_vector (sel, 2, nelt);
perm3_mask_low = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0; i < nelt; i++)
{
if (3 * i + nelt0 < nelt)
sel[3 * i + nelt0] = 3 * i + nelt0;
if (3 * i + nelt1 < nelt)
sel[3 * i + nelt1] = 3 * i + nelt1;
if (3 * i + nelt2 < nelt)
sel[3 * i + nelt2] = nelt + j2++;
}
indices.new_vector (sel, 2, nelt);
perm3_mask_high = vect_gen_perm_mask_checked (vectype, indices);
vect1 = dr_chain[0];
vect2 = dr_chain[1];
/* Create interleaving stmt:
low = VEC_PERM_EXPR <vect1, vect2,
{j, nelt, *, j + 1, nelt + j + 1, *,
j + 2, nelt + j + 2, *, ...}> */
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle3_low");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR, vect1,
vect2, perm3_mask_low);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
vect1 = data_ref;
vect2 = dr_chain[2];
/* Create interleaving stmt:
low = VEC_PERM_EXPR <vect1, vect2,
{0, 1, nelt + j, 3, 4, nelt + j + 1,
6, 7, nelt + j + 2, ...}> */
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle3_high");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR, vect1,
vect2, perm3_mask_high);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[j] = data_ref;
}
}
else
{
/* If length is not equal to 3 then only power of 2 is supported. */
gcc_assert (pow2p_hwi (length));
/* The encoding has 2 interleaved stepped patterns. */
poly_uint64 nelt = TYPE_VECTOR_SUBPARTS (vectype);
vec_perm_builder sel (nelt, 2, 3);
sel.quick_grow (6);
for (i = 0; i < 3; i++)
{
sel[i * 2] = i;
sel[i * 2 + 1] = i + nelt;
}
vec_perm_indices indices (sel, 2, nelt);
perm_mask_high = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0; i < 6; i++)
sel[i] += exact_div (nelt, 2);
indices.new_vector (sel, 2, nelt);
perm_mask_low = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0, n = log_length; i < n; i++)
{
for (j = 0; j < length/2; j++)
{
vect1 = dr_chain[j];
vect2 = dr_chain[j+length/2];
/* Create interleaving stmt:
high = VEC_PERM_EXPR <vect1, vect2, {0, nelt, 1, nelt+1,
...}> */
high = make_temp_ssa_name (vectype, NULL, "vect_inter_high");
perm_stmt = gimple_build_assign (high, VEC_PERM_EXPR, vect1,
vect2, perm_mask_high);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[2*j] = high;
/* Create interleaving stmt:
low = VEC_PERM_EXPR <vect1, vect2,
{nelt/2, nelt*3/2, nelt/2+1, nelt*3/2+1,
...}> */
low = make_temp_ssa_name (vectype, NULL, "vect_inter_low");
perm_stmt = gimple_build_assign (low, VEC_PERM_EXPR, vect1,
vect2, perm_mask_low);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[2*j+1] = low;
}
memcpy (dr_chain.address (), result_chain->address (),
length * sizeof (tree));
}
}
}
/* Function vect_setup_realignment
This function is called when vectorizing an unaligned load using
the dr_explicit_realign[_optimized] scheme.
This function generates the following code at the loop prolog:
p = initial_addr;
x msq_init = *(floor(p)); # prolog load
realignment_token = call target_builtin;
loop:
x msq = phi (msq_init, ---)
The stmts marked with x are generated only for the case of
dr_explicit_realign_optimized.
The code above sets up a new (vector) pointer, pointing to the first
location accessed by STMT_INFO, and a "floor-aligned" load using that
pointer. It also generates code to compute the "realignment-token"
(if the relevant target hook was defined), and creates a phi-node at the
loop-header bb whose arguments are the result of the prolog-load (created
by this function) and the result of a load that takes place in the loop
(to be created by the caller to this function).
For the case of dr_explicit_realign_optimized:
The caller to this function uses the phi-result (msq) to create the
realignment code inside the loop, and sets up the missing phi argument,
as follows:
loop:
msq = phi (msq_init, lsq)
lsq = *(floor(p')); # load in loop
result = realign_load (msq, lsq, realignment_token);
For the case of dr_explicit_realign:
loop:
msq = *(floor(p)); # load in loop
p' = p + (VS-1);
lsq = *(floor(p')); # load in loop
result = realign_load (msq, lsq, realignment_token);
Input:
STMT_INFO - (scalar) load stmt to be vectorized. This load accesses
a memory location that may be unaligned.
BSI - place where new code is to be inserted.
ALIGNMENT_SUPPORT_SCHEME - which of the two misalignment handling schemes
is used.
Output:
REALIGNMENT_TOKEN - the result of a call to the builtin_mask_for_load
target hook, if defined.
Return value - the result of the loop-header phi node. */
tree
vect_setup_realignment (stmt_vec_info stmt_info, gimple_stmt_iterator *gsi,
tree *realignment_token,
enum dr_alignment_support alignment_support_scheme,
tree init_addr,
class loop **at_loop)
{
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
dr_vec_info *dr_info = STMT_VINFO_DR_INFO (stmt_info);
struct data_reference *dr = dr_info->dr;
class loop *loop = NULL;
edge pe = NULL;
tree scalar_dest = gimple_assign_lhs (stmt_info->stmt);
tree vec_dest;
gimple *inc;
tree ptr;
tree data_ref;
basic_block new_bb;
tree msq_init = NULL_TREE;
tree new_temp;
gphi *phi_stmt;
tree msq = NULL_TREE;
gimple_seq stmts = NULL;
bool compute_in_loop = false;
bool nested_in_vect_loop = false;
class loop *containing_loop = (gimple_bb (stmt_info->stmt))->loop_father;
class loop *loop_for_initial_load = NULL;
if (loop_vinfo)
{
loop = LOOP_VINFO_LOOP (loop_vinfo);
nested_in_vect_loop = nested_in_vect_loop_p (loop, stmt_info);
}
gcc_assert (alignment_support_scheme == dr_explicit_realign
|| alignment_support_scheme == dr_explicit_realign_optimized);
/* We need to generate three things:
1. the misalignment computation
2. the extra vector load (for the optimized realignment scheme).
3. the phi node for the two vectors from which the realignment is
done (for the optimized realignment scheme). */
/* 1. Determine where to generate the misalignment computation.
If INIT_ADDR is NULL_TREE, this indicates that the misalignment
calculation will be generated by this function, outside the loop (in the
preheader). Otherwise, INIT_ADDR had already been computed for us by the
caller, inside the loop.
Background: If the misalignment remains fixed throughout the iterations of
the loop, then both realignment schemes are applicable, and also the
misalignment computation can be done outside LOOP. This is because we are
vectorizing LOOP, and so the memory accesses in LOOP advance in steps that
are a multiple of VS (the Vector Size), and therefore the misalignment in
different vectorized LOOP iterations is always the same.
The problem arises only if the memory access is in an inner-loop nested
inside LOOP, which is now being vectorized using outer-loop vectorization.
This is the only case when the misalignment of the memory access may not
remain fixed throughout the iterations of the inner-loop (as explained in
detail in vect_supportable_dr_alignment). In this case, not only is the
optimized realignment scheme not applicable, but also the misalignment
computation (and generation of the realignment token that is passed to
REALIGN_LOAD) have to be done inside the loop.
In short, INIT_ADDR indicates whether we are in a COMPUTE_IN_LOOP mode
or not, which in turn determines if the misalignment is computed inside
the inner-loop, or outside LOOP. */
if (init_addr != NULL_TREE || !loop_vinfo)
{
compute_in_loop = true;
gcc_assert (alignment_support_scheme == dr_explicit_realign);
}
/* 2. Determine where to generate the extra vector load.
For the optimized realignment scheme, instead of generating two vector
loads in each iteration, we generate a single extra vector load in the
preheader of the loop, and in each iteration reuse the result of the
vector load from the previous iteration. In case the memory access is in
an inner-loop nested inside LOOP, which is now being vectorized using
outer-loop vectorization, we need to determine whether this initial vector
load should be generated at the preheader of the inner-loop, or can be
generated at the preheader of LOOP. If the memory access has no evolution
in LOOP, it can be generated in the preheader of LOOP. Otherwise, it has
to be generated inside LOOP (in the preheader of the inner-loop). */
if (nested_in_vect_loop)
{
tree outerloop_step = STMT_VINFO_DR_STEP (stmt_info);
bool invariant_in_outerloop =
(tree_int_cst_compare (outerloop_step, size_zero_node) == 0);
loop_for_initial_load = (invariant_in_outerloop ? loop : loop->inner);
}
else
loop_for_initial_load = loop;
if (at_loop)
*at_loop = loop_for_initial_load;
if (loop_for_initial_load)
pe = loop_preheader_edge (loop_for_initial_load);
/* 3. For the case of the optimized realignment, create the first vector
load at the loop preheader. */
if (alignment_support_scheme == dr_explicit_realign_optimized)
{
/* Create msq_init = *(floor(p1)) in the loop preheader */
gassign *new_stmt;
gcc_assert (!compute_in_loop);
vec_dest = vect_create_destination_var (scalar_dest, vectype);
ptr = vect_create_data_ref_ptr (stmt_info, vectype,
loop_for_initial_load, NULL_TREE,
&init_addr, NULL, &inc, true);
if (TREE_CODE (ptr) == SSA_NAME)
new_temp = copy_ssa_name (ptr);
else
new_temp = make_ssa_name (TREE_TYPE (ptr));
poly_uint64 align = DR_TARGET_ALIGNMENT (dr_info);
tree type = TREE_TYPE (ptr);
new_stmt = gimple_build_assign
(new_temp, BIT_AND_EXPR, ptr,
fold_build2 (MINUS_EXPR, type,
build_int_cst (type, 0),
build_int_cst (type, align)));
new_bb = gsi_insert_on_edge_immediate (pe, new_stmt);
gcc_assert (!new_bb);
data_ref
= build2 (MEM_REF, TREE_TYPE (vec_dest), new_temp,
build_int_cst (reference_alias_ptr_type (DR_REF (dr)), 0));
vect_copy_ref_info (data_ref, DR_REF (dr));
new_stmt = gimple_build_assign (vec_dest, data_ref);
new_temp = make_ssa_name (vec_dest, new_stmt);
gimple_assign_set_lhs (new_stmt, new_temp);
if (pe)
{
new_bb = gsi_insert_on_edge_immediate (pe, new_stmt);
gcc_assert (!new_bb);
}
else
gsi_insert_before (gsi, new_stmt, GSI_SAME_STMT);
msq_init = gimple_assign_lhs (new_stmt);
}
/* 4. Create realignment token using a target builtin, if available.
It is done either inside the containing loop, or before LOOP (as
determined above). */
if (targetm.vectorize.builtin_mask_for_load)
{
gcall *new_stmt;
tree builtin_decl;
/* Compute INIT_ADDR - the initial addressed accessed by this memref. */
if (!init_addr)
{
/* Generate the INIT_ADDR computation outside LOOP. */
init_addr = vect_create_addr_base_for_vector_ref (stmt_info, &stmts,
NULL_TREE);
if (loop)
{
pe = loop_preheader_edge (loop);
new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
gcc_assert (!new_bb);
}
else
gsi_insert_seq_before (gsi, stmts, GSI_SAME_STMT);
}
builtin_decl = targetm.vectorize.builtin_mask_for_load ();
new_stmt = gimple_build_call (builtin_decl, 1, init_addr);
vec_dest =
vect_create_destination_var (scalar_dest,
gimple_call_return_type (new_stmt));
new_temp = make_ssa_name (vec_dest, new_stmt);
gimple_call_set_lhs (new_stmt, new_temp);
if (compute_in_loop)
gsi_insert_before (gsi, new_stmt, GSI_SAME_STMT);
else
{
/* Generate the misalignment computation outside LOOP. */
pe = loop_preheader_edge (loop);
new_bb = gsi_insert_on_edge_immediate (pe, new_stmt);
gcc_assert (!new_bb);
}
*realignment_token = gimple_call_lhs (new_stmt);
/* The result of the CALL_EXPR to this builtin is determined from
the value of the parameter and no global variables are touched
which makes the builtin a "const" function. Requiring the
builtin to have the "const" attribute makes it unnecessary
to call mark_call_clobbered. */
gcc_assert (TREE_READONLY (builtin_decl));
}
if (alignment_support_scheme == dr_explicit_realign)
return msq;
gcc_assert (!compute_in_loop);
gcc_assert (alignment_support_scheme == dr_explicit_realign_optimized);
/* 5. Create msq = phi <msq_init, lsq> in loop */
pe = loop_preheader_edge (containing_loop);
vec_dest = vect_create_destination_var (scalar_dest, vectype);
msq = make_ssa_name (vec_dest);
phi_stmt = create_phi_node (msq, containing_loop->header);
add_phi_arg (phi_stmt, msq_init, pe, UNKNOWN_LOCATION);
return msq;
}
/* Function vect_grouped_load_supported.
COUNT is the size of the load group (the number of statements plus the
number of gaps). SINGLE_ELEMENT_P is true if there is actually
only one statement, with a gap of COUNT - 1.
Returns true if a suitable permute exists. */
bool
vect_grouped_load_supported (tree vectype, bool single_element_p,
unsigned HOST_WIDE_INT count)
{
machine_mode mode = TYPE_MODE (vectype);
/* If this is single-element interleaving with an element distance
that leaves unused vector loads around punt - we at least create
very sub-optimal code in that case (and blow up memory,
see PR65518). */
if (single_element_p && maybe_gt (count, TYPE_VECTOR_SUBPARTS (vectype)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"single-element interleaving not supported "
"for not adjacent vector loads\n");
return false;
}
/* vect_permute_load_chain requires the group size to be equal to 3 or
be a power of two. */
if (count != 3 && exact_log2 (count) == -1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"the size of the group of accesses"
" is not a power of 2 or not equal to 3\n");
return false;
}
/* Check that the permutation is supported. */
if (VECTOR_MODE_P (mode))
{
unsigned int i, j;
if (count == 3)
{
unsigned int nelt;
if (!GET_MODE_NUNITS (mode).is_constant (&nelt))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"cannot handle groups of 3 loads for"
" variable-length vectors\n");
return false;
}
vec_perm_builder sel (nelt, nelt, 1);
sel.quick_grow (nelt);
vec_perm_indices indices;
unsigned int k;
for (k = 0; k < 3; k++)
{
for (i = 0; i < nelt; i++)
if (3 * i + k < 2 * nelt)
sel[i] = 3 * i + k;
else
sel[i] = 0;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (mode, indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shuffle of 3 loads is not supported by"
" target\n");
return false;
}
for (i = 0, j = 0; i < nelt; i++)
if (3 * i + k < 2 * nelt)
sel[i] = i;
else
sel[i] = nelt + ((nelt + k) % 3) + 3 * (j++);
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (mode, indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shuffle of 3 loads is not supported by"
" target\n");
return false;
}
}
return true;
}
else
{
/* If length is not equal to 3 then only power of 2 is supported. */
gcc_assert (pow2p_hwi (count));
poly_uint64 nelt = GET_MODE_NUNITS (mode);
/* The encoding has a single stepped pattern. */
vec_perm_builder sel (nelt, 1, 3);
sel.quick_grow (3);
for (i = 0; i < 3; i++)
sel[i] = i * 2;
vec_perm_indices indices (sel, 2, nelt);
if (can_vec_perm_const_p (mode, indices))
{
for (i = 0; i < 3; i++)
sel[i] = i * 2 + 1;
indices.new_vector (sel, 2, nelt);
if (can_vec_perm_const_p (mode, indices))
return true;
}
}
}
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"extract even/odd not supported by target\n");
return false;
}
/* Return TRUE if vec_{masked_}load_lanes is available for COUNT vectors of
type VECTYPE. MASKED_P says whether the masked form is needed. */
bool
vect_load_lanes_supported (tree vectype, unsigned HOST_WIDE_INT count,
bool masked_p)
{
if (masked_p)
return vect_lanes_optab_supported_p ("vec_mask_load_lanes",
vec_mask_load_lanes_optab,
vectype, count);
else
return vect_lanes_optab_supported_p ("vec_load_lanes",
vec_load_lanes_optab,
vectype, count);
}
/* Function vect_permute_load_chain.
Given a chain of interleaved loads in DR_CHAIN of LENGTH that must be
a power of 2 or equal to 3, generate extract_even/odd stmts to reorder
the input data correctly. Return the final references for loads in
RESULT_CHAIN.
E.g., LENGTH is 4 and the scalar type is short, i.e., VF is 8.
The input is 4 vectors each containing 8 elements. We assign a number to each
element, the input sequence is:
1st vec: 0 1 2 3 4 5 6 7
2nd vec: 8 9 10 11 12 13 14 15
3rd vec: 16 17 18 19 20 21 22 23
4th vec: 24 25 26 27 28 29 30 31
The output sequence should be:
1st vec: 0 4 8 12 16 20 24 28
2nd vec: 1 5 9 13 17 21 25 29
3rd vec: 2 6 10 14 18 22 26 30
4th vec: 3 7 11 15 19 23 27 31
i.e., the first output vector should contain the first elements of each
interleaving group, etc.
We use extract_even/odd instructions to create such output. The input of
each extract_even/odd operation is two vectors
1st vec 2nd vec
0 1 2 3 4 5 6 7
and the output is the vector of extracted even/odd elements. The output of
extract_even will be: 0 2 4 6
and of extract_odd: 1 3 5 7
The permutation is done in log LENGTH stages. In each stage extract_even
and extract_odd stmts are created for each pair of vectors in DR_CHAIN in
their order. In our example,
E1: extract_even (1st vec, 2nd vec)
E2: extract_odd (1st vec, 2nd vec)
E3: extract_even (3rd vec, 4th vec)
E4: extract_odd (3rd vec, 4th vec)
The output for the first stage will be:
E1: 0 2 4 6 8 10 12 14
E2: 1 3 5 7 9 11 13 15
E3: 16 18 20 22 24 26 28 30
E4: 17 19 21 23 25 27 29 31
In order to proceed and create the correct sequence for the next stage (or
for the correct output, if the second stage is the last one, as in our
example), we first put the output of extract_even operation and then the
output of extract_odd in RESULT_CHAIN (which is then copied to DR_CHAIN).
The input for the second stage is:
1st vec (E1): 0 2 4 6 8 10 12 14
2nd vec (E3): 16 18 20 22 24 26 28 30
3rd vec (E2): 1 3 5 7 9 11 13 15
4th vec (E4): 17 19 21 23 25 27 29 31
The output of the second stage:
E1: 0 4 8 12 16 20 24 28
E2: 2 6 10 14 18 22 26 30
E3: 1 5 9 13 17 21 25 29
E4: 3 7 11 15 19 23 27 31
And RESULT_CHAIN after reordering:
1st vec (E1): 0 4 8 12 16 20 24 28
2nd vec (E3): 1 5 9 13 17 21 25 29
3rd vec (E2): 2 6 10 14 18 22 26 30
4th vec (E4): 3 7 11 15 19 23 27 31. */
static void
vect_permute_load_chain (vec<tree> dr_chain,
unsigned int length,
stmt_vec_info stmt_info,
gimple_stmt_iterator *gsi,
vec<tree> *result_chain)
{
tree data_ref, first_vect, second_vect;
tree perm_mask_even, perm_mask_odd;
tree perm3_mask_low, perm3_mask_high;
gimple *perm_stmt;
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
unsigned int i, j, log_length = exact_log2 (length);
result_chain->quick_grow (length);
memcpy (result_chain->address (), dr_chain.address (),
length * sizeof (tree));
if (length == 3)
{
/* vect_grouped_load_supported ensures that this is constant. */
unsigned nelt = TYPE_VECTOR_SUBPARTS (vectype).to_constant ();
unsigned int k;
vec_perm_builder sel (nelt, nelt, 1);
sel.quick_grow (nelt);
vec_perm_indices indices;
for (k = 0; k < 3; k++)
{
for (i = 0; i < nelt; i++)
if (3 * i + k < 2 * nelt)
sel[i] = 3 * i + k;
else
sel[i] = 0;
indices.new_vector (sel, 2, nelt);
perm3_mask_low = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0, j = 0; i < nelt; i++)
if (3 * i + k < 2 * nelt)
sel[i] = i;
else
sel[i] = nelt + ((nelt + k) % 3) + 3 * (j++);
indices.new_vector (sel, 2, nelt);
perm3_mask_high = vect_gen_perm_mask_checked (vectype, indices);
first_vect = dr_chain[0];
second_vect = dr_chain[1];
/* Create interleaving stmt (low part of):
low = VEC_PERM_EXPR <first_vect, second_vect2, {k, 3 + k, 6 + k,
...}> */
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle3_low");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR, first_vect,
second_vect, perm3_mask_low);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
/* Create interleaving stmt (high part of):
high = VEC_PERM_EXPR <first_vect, second_vect2, {k, 3 + k, 6 + k,
...}> */
first_vect = data_ref;
second_vect = dr_chain[2];
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle3_high");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR, first_vect,
second_vect, perm3_mask_high);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[k] = data_ref;
}
}
else
{
/* If length is not equal to 3 then only power of 2 is supported. */
gcc_assert (pow2p_hwi (length));
/* The encoding has a single stepped pattern. */
poly_uint64 nelt = TYPE_VECTOR_SUBPARTS (vectype);
vec_perm_builder sel (nelt, 1, 3);
sel.quick_grow (3);
for (i = 0; i < 3; ++i)
sel[i] = i * 2;
vec_perm_indices indices (sel, 2, nelt);
perm_mask_even = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0; i < 3; ++i)
sel[i] = i * 2 + 1;
indices.new_vector (sel, 2, nelt);
perm_mask_odd = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0; i < log_length; i++)
{
for (j = 0; j < length; j += 2)
{
first_vect = dr_chain[j];
second_vect = dr_chain[j+1];
/* data_ref = permute_even (first_data_ref, second_data_ref); */
data_ref = make_temp_ssa_name (vectype, NULL, "vect_perm_even");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
first_vect, second_vect,
perm_mask_even);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[j/2] = data_ref;
/* data_ref = permute_odd (first_data_ref, second_data_ref); */
data_ref = make_temp_ssa_name (vectype, NULL, "vect_perm_odd");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
first_vect, second_vect,
perm_mask_odd);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[j/2+length/2] = data_ref;
}
memcpy (dr_chain.address (), result_chain->address (),
length * sizeof (tree));
}
}
}
/* Function vect_shift_permute_load_chain.
Given a chain of loads in DR_CHAIN of LENGTH 2 or 3, generate
sequence of stmts to reorder the input data accordingly.
Return the final references for loads in RESULT_CHAIN.
Return true if successed, false otherwise.
E.g., LENGTH is 3 and the scalar type is short, i.e., VF is 8.
The input is 3 vectors each containing 8 elements. We assign a
number to each element, the input sequence is:
1st vec: 0 1 2 3 4 5 6 7
2nd vec: 8 9 10 11 12 13 14 15
3rd vec: 16 17 18 19 20 21 22 23
The output sequence should be:
1st vec: 0 3 6 9 12 15 18 21
2nd vec: 1 4 7 10 13 16 19 22
3rd vec: 2 5 8 11 14 17 20 23
We use 3 shuffle instructions and 3 * 3 - 1 shifts to create such output.
First we shuffle all 3 vectors to get correct elements order:
1st vec: ( 0 3 6) ( 1 4 7) ( 2 5)
2nd vec: ( 8 11 14) ( 9 12 15) (10 13)
3rd vec: (16 19 22) (17 20 23) (18 21)
Next we unite and shift vector 3 times:
1st step:
shift right by 6 the concatenation of:
"1st vec" and "2nd vec"
( 0 3 6) ( 1 4 7) |( 2 5) _ ( 8 11 14) ( 9 12 15)| (10 13)
"2nd vec" and "3rd vec"
( 8 11 14) ( 9 12 15) |(10 13) _ (16 19 22) (17 20 23)| (18 21)
"3rd vec" and "1st vec"
(16 19 22) (17 20 23) |(18 21) _ ( 0 3 6) ( 1 4 7)| ( 2 5)
| New vectors |
So that now new vectors are:
1st vec: ( 2 5) ( 8 11 14) ( 9 12 15)
2nd vec: (10 13) (16 19 22) (17 20 23)
3rd vec: (18 21) ( 0 3 6) ( 1 4 7)
2nd step:
shift right by 5 the concatenation of:
"1st vec" and "3rd vec"
( 2 5) ( 8 11 14) |( 9 12 15) _ (18 21) ( 0 3 6)| ( 1 4 7)
"2nd vec" and "1st vec"
(10 13) (16 19 22) |(17 20 23) _ ( 2 5) ( 8 11 14)| ( 9 12 15)
"3rd vec" and "2nd vec"
(18 21) ( 0 3 6) |( 1 4 7) _ (10 13) (16 19 22)| (17 20 23)
| New vectors |
So that now new vectors are:
1st vec: ( 9 12 15) (18 21) ( 0 3 6)
2nd vec: (17 20 23) ( 2 5) ( 8 11 14)
3rd vec: ( 1 4 7) (10 13) (16 19 22) READY
3rd step:
shift right by 5 the concatenation of:
"1st vec" and "1st vec"
( 9 12 15) (18 21) |( 0 3 6) _ ( 9 12 15) (18 21)| ( 0 3 6)
shift right by 3 the concatenation of:
"2nd vec" and "2nd vec"
(17 20 23) |( 2 5) ( 8 11 14) _ (17 20 23)| ( 2 5) ( 8 11 14)
| New vectors |
So that now all vectors are READY:
1st vec: ( 0 3 6) ( 9 12 15) (18 21)
2nd vec: ( 2 5) ( 8 11 14) (17 20 23)
3rd vec: ( 1 4 7) (10 13) (16 19 22)
This algorithm is faster than one in vect_permute_load_chain if:
1. "shift of a concatination" is faster than general permutation.
This is usually so.
2. The TARGET machine can't execute vector instructions in parallel.
This is because each step of the algorithm depends on previous.
The algorithm in vect_permute_load_chain is much more parallel.
The algorithm is applicable only for LOAD CHAIN LENGTH less than VF.
*/
static bool
vect_shift_permute_load_chain (vec<tree> dr_chain,
unsigned int length,
stmt_vec_info stmt_info,
gimple_stmt_iterator *gsi,
vec<tree> *result_chain)
{
tree vect[3], vect_shift[3], data_ref, first_vect, second_vect;
tree perm2_mask1, perm2_mask2, perm3_mask;
tree select_mask, shift1_mask, shift2_mask, shift3_mask, shift4_mask;
gimple *perm_stmt;
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
unsigned int i;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
unsigned HOST_WIDE_INT nelt, vf;
if (!TYPE_VECTOR_SUBPARTS (vectype).is_constant (&nelt)
|| !LOOP_VINFO_VECT_FACTOR (loop_vinfo).is_constant (&vf))
/* Not supported for variable-length vectors. */
return false;
vec_perm_builder sel (nelt, nelt, 1);
sel.quick_grow (nelt);
result_chain->quick_grow (length);
memcpy (result_chain->address (), dr_chain.address (),
length * sizeof (tree));
if (pow2p_hwi (length) && vf > 4)
{
unsigned int j, log_length = exact_log2 (length);
for (i = 0; i < nelt / 2; ++i)
sel[i] = i * 2;
for (i = 0; i < nelt / 2; ++i)
sel[nelt / 2 + i] = i * 2 + 1;
vec_perm_indices indices (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shuffle of 2 fields structure is not \
supported by target\n");
return false;
}
perm2_mask1 = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0; i < nelt / 2; ++i)
sel[i] = i * 2 + 1;
for (i = 0; i < nelt / 2; ++i)
sel[nelt / 2 + i] = i * 2;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shuffle of 2 fields structure is not \
supported by target\n");
return false;
}
perm2_mask2 = vect_gen_perm_mask_checked (vectype, indices);
/* Generating permutation constant to shift all elements.
For vector length 8 it is {4 5 6 7 8 9 10 11}. */
for (i = 0; i < nelt; i++)
sel[i] = nelt / 2 + i;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shift permutation is not supported by target\n");
return false;
}
shift1_mask = vect_gen_perm_mask_checked (vectype, indices);
/* Generating permutation constant to select vector from 2.
For vector length 8 it is {0 1 2 3 12 13 14 15}. */
for (i = 0; i < nelt / 2; i++)
sel[i] = i;
for (i = nelt / 2; i < nelt; i++)
sel[i] = nelt + i;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"select is not supported by target\n");
return false;
}
select_mask = vect_gen_perm_mask_checked (vectype, indices);
for (i = 0; i < log_length; i++)
{
for (j = 0; j < length; j += 2)
{
first_vect = dr_chain[j];
second_vect = dr_chain[j + 1];
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle2");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
first_vect, first_vect,
perm2_mask1);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
vect[0] = data_ref;
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle2");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
second_vect, second_vect,
perm2_mask2);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
vect[1] = data_ref;
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shift");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
vect[0], vect[1], shift1_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[j/2 + length/2] = data_ref;
data_ref = make_temp_ssa_name (vectype, NULL, "vect_select");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
vect[0], vect[1], select_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[j/2] = data_ref;
}
memcpy (dr_chain.address (), result_chain->address (),
length * sizeof (tree));
}
return true;
}
if (length == 3 && vf > 2)
{
unsigned int k = 0, l = 0;
/* Generating permutation constant to get all elements in rigth order.
For vector length 8 it is {0 3 6 1 4 7 2 5}. */
for (i = 0; i < nelt; i++)
{
if (3 * k + (l % 3) >= nelt)
{
k = 0;
l += (3 - (nelt % 3));
}
sel[i] = 3 * k + (l % 3);
k++;
}
vec_perm_indices indices (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shuffle of 3 fields structure is not \
supported by target\n");
return false;
}
perm3_mask = vect_gen_perm_mask_checked (vectype, indices);
/* Generating permutation constant to shift all elements.
For vector length 8 it is {6 7 8 9 10 11 12 13}. */
for (i = 0; i < nelt; i++)
sel[i] = 2 * (nelt / 3) + (nelt % 3) + i;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shift permutation is not supported by target\n");
return false;
}
shift1_mask = vect_gen_perm_mask_checked (vectype, indices);
/* Generating permutation constant to shift all elements.
For vector length 8 it is {5 6 7 8 9 10 11 12}. */
for (i = 0; i < nelt; i++)
sel[i] = 2 * (nelt / 3) + 1 + i;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shift permutation is not supported by target\n");
return false;
}
shift2_mask = vect_gen_perm_mask_checked (vectype, indices);
/* Generating permutation constant to shift all elements.
For vector length 8 it is {3 4 5 6 7 8 9 10}. */
for (i = 0; i < nelt; i++)
sel[i] = (nelt / 3) + (nelt % 3) / 2 + i;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shift permutation is not supported by target\n");
return false;
}
shift3_mask = vect_gen_perm_mask_checked (vectype, indices);
/* Generating permutation constant to shift all elements.
For vector length 8 it is {5 6 7 8 9 10 11 12}. */
for (i = 0; i < nelt; i++)
sel[i] = 2 * (nelt / 3) + (nelt % 3) / 2 + i;
indices.new_vector (sel, 2, nelt);
if (!can_vec_perm_const_p (TYPE_MODE (vectype), indices))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"shift permutation is not supported by target\n");
return false;
}
shift4_mask = vect_gen_perm_mask_checked (vectype, indices);
for (k = 0; k < 3; k++)
{
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shuffle3");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
dr_chain[k], dr_chain[k],
perm3_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
vect[k] = data_ref;
}
for (k = 0; k < 3; k++)
{
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shift1");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
vect[k % 3], vect[(k + 1) % 3],
shift1_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
vect_shift[k] = data_ref;
}
for (k = 0; k < 3; k++)
{
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shift2");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR,
vect_shift[(4 - k) % 3],
vect_shift[(3 - k) % 3],
shift2_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
vect[k] = data_ref;
}
(*result_chain)[3 - (nelt % 3)] = vect[2];
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shift3");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR, vect[0],
vect[0], shift3_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[nelt % 3] = data_ref;
data_ref = make_temp_ssa_name (vectype, NULL, "vect_shift4");
perm_stmt = gimple_build_assign (data_ref, VEC_PERM_EXPR, vect[1],
vect[1], shift4_mask);
vect_finish_stmt_generation (stmt_info, perm_stmt, gsi);
(*result_chain)[0] = data_ref;
return true;
}
return false;
}
/* Function vect_transform_grouped_load.
Given a chain of input interleaved data-refs (in DR_CHAIN), build statements
to perform their permutation and ascribe the result vectorized statements to
the scalar statements.
*/
void
vect_transform_grouped_load (stmt_vec_info stmt_info, vec<tree> dr_chain,
int size, gimple_stmt_iterator *gsi)
{
machine_mode mode;
vec<tree> result_chain = vNULL;
/* DR_CHAIN contains input data-refs that are a part of the interleaving.
RESULT_CHAIN is the output of vect_permute_load_chain, it contains permuted
vectors, that are ready for vector computation. */
result_chain.create (size);
/* If reassociation width for vector type is 2 or greater target machine can
execute 2 or more vector instructions in parallel. Otherwise try to
get chain for loads group using vect_shift_permute_load_chain. */
mode = TYPE_MODE (STMT_VINFO_VECTYPE (stmt_info));
if (targetm.sched.reassociation_width (VEC_PERM_EXPR, mode) > 1
|| pow2p_hwi (size)
|| !vect_shift_permute_load_chain (dr_chain, size, stmt_info,
gsi, &result_chain))
vect_permute_load_chain (dr_chain, size, stmt_info, gsi, &result_chain);
vect_record_grouped_load_vectors (stmt_info, result_chain);
result_chain.release ();
}
/* RESULT_CHAIN contains the output of a group of grouped loads that were
generated as part of the vectorization of STMT_INFO. Assign the statement
for each vector to the associated scalar statement. */
void
vect_record_grouped_load_vectors (stmt_vec_info stmt_info,
vec<tree> result_chain)
{
vec_info *vinfo = stmt_info->vinfo;
stmt_vec_info first_stmt_info = DR_GROUP_FIRST_ELEMENT (stmt_info);
unsigned int i, gap_count;
tree tmp_data_ref;
/* Put a permuted data-ref in the VECTORIZED_STMT field.
Since we scan the chain starting from it's first node, their order
corresponds the order of data-refs in RESULT_CHAIN. */
stmt_vec_info next_stmt_info = first_stmt_info;
gap_count = 1;
FOR_EACH_VEC_ELT (result_chain, i, tmp_data_ref)
{
if (!next_stmt_info)
break;
/* Skip the gaps. Loads created for the gaps will be removed by dead
code elimination pass later. No need to check for the first stmt in
the group, since it always exists.
DR_GROUP_GAP is the number of steps in elements from the previous
access (if there is no gap DR_GROUP_GAP is 1). We skip loads that
correspond to the gaps. */
if (next_stmt_info != first_stmt_info
&& gap_count < DR_GROUP_GAP (next_stmt_info))
{
gap_count++;
continue;
}
/* ??? The following needs cleanup after the removal of
DR_GROUP_SAME_DR_STMT. */
if (next_stmt_info)
{
stmt_vec_info new_stmt_info = vinfo->lookup_def (tmp_data_ref);
/* We assume that if VEC_STMT is not NULL, this is a case of multiple
copies, and we put the new vector statement in the first available
RELATED_STMT. */
if (!STMT_VINFO_VEC_STMT (next_stmt_info))
STMT_VINFO_VEC_STMT (next_stmt_info) = new_stmt_info;
else
{
stmt_vec_info prev_stmt_info
= STMT_VINFO_VEC_STMT (next_stmt_info);
stmt_vec_info rel_stmt_info
= STMT_VINFO_RELATED_STMT (prev_stmt_info);
while (rel_stmt_info)
{
prev_stmt_info = rel_stmt_info;
rel_stmt_info = STMT_VINFO_RELATED_STMT (rel_stmt_info);
}
STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt_info;
}
next_stmt_info = DR_GROUP_NEXT_ELEMENT (next_stmt_info);
gap_count = 1;
}
}
}
/* Function vect_force_dr_alignment_p.
Returns whether the alignment of a DECL can be forced to be aligned
on ALIGNMENT bit boundary. */
bool
vect_can_force_dr_alignment_p (const_tree decl, poly_uint64 alignment)
{
if (!VAR_P (decl))
return false;
if (decl_in_symtab_p (decl)
&& !symtab_node::get (decl)->can_increase_alignment_p ())
return false;
if (TREE_STATIC (decl))
return (known_le (alignment,
(unsigned HOST_WIDE_INT) MAX_OFILE_ALIGNMENT));
else
return (known_le (alignment, (unsigned HOST_WIDE_INT) MAX_STACK_ALIGNMENT));
}
/* Return whether the data reference DR_INFO is supported with respect to its
alignment.
If CHECK_ALIGNED_ACCESSES is TRUE, check if the access is supported even
it is aligned, i.e., check if it is possible to vectorize it with different
alignment. */
enum dr_alignment_support
vect_supportable_dr_alignment (dr_vec_info *dr_info,
bool check_aligned_accesses)
{
data_reference *dr = dr_info->dr;
stmt_vec_info stmt_info = dr_info->stmt;
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
machine_mode mode = TYPE_MODE (vectype);
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
class loop *vect_loop = NULL;
bool nested_in_vect_loop = false;
if (aligned_access_p (dr_info) && !check_aligned_accesses)
return dr_aligned;
/* For now assume all conditional loads/stores support unaligned
access without any special code. */
if (gcall *stmt = dyn_cast <gcall *> (stmt_info->stmt))
if (gimple_call_internal_p (stmt)
&& (gimple_call_internal_fn (stmt) == IFN_MASK_LOAD
|| gimple_call_internal_fn (stmt) == IFN_MASK_STORE))
return dr_unaligned_supported;
if (loop_vinfo)
{
vect_loop = LOOP_VINFO_LOOP (loop_vinfo);
nested_in_vect_loop = nested_in_vect_loop_p (vect_loop, stmt_info);
}
/* Possibly unaligned access. */
/* We can choose between using the implicit realignment scheme (generating
a misaligned_move stmt) and the explicit realignment scheme (generating
aligned loads with a REALIGN_LOAD). There are two variants to the
explicit realignment scheme: optimized, and unoptimized.
We can optimize the realignment only if the step between consecutive
vector loads is equal to the vector size. Since the vector memory
accesses advance in steps of VS (Vector Size) in the vectorized loop, it
is guaranteed that the misalignment amount remains the same throughout the
execution of the vectorized loop. Therefore, we can create the
"realignment token" (the permutation mask that is passed to REALIGN_LOAD)
at the loop preheader.
However, in the case of outer-loop vectorization, when vectorizing a
memory access in the inner-loop nested within the LOOP that is now being
vectorized, while it is guaranteed that the misalignment of the
vectorized memory access will remain the same in different outer-loop
iterations, it is *not* guaranteed that is will remain the same throughout
the execution of the inner-loop. This is because the inner-loop advances
with the original scalar step (and not in steps of VS). If the inner-loop
step happens to be a multiple of VS, then the misalignment remains fixed
and we can use the optimized realignment scheme. For example:
for (i=0; i<N; i++)
for (j=0; j<M; j++)
s += a[i+j];
When vectorizing the i-loop in the above example, the step between
consecutive vector loads is 1, and so the misalignment does not remain
fixed across the execution of the inner-loop, and the realignment cannot
be optimized (as illustrated in the following pseudo vectorized loop):
for (i=0; i<N; i+=4)
for (j=0; j<M; j++){
vs += vp[i+j]; // misalignment of &vp[i+j] is {0,1,2,3,0,1,2,3,...}
// when j is {0,1,2,3,4,5,6,7,...} respectively.
// (assuming that we start from an aligned address).
}
We therefore have to use the unoptimized realignment scheme:
for (i=0; i<N; i+=4)
for (j=k; j<M; j+=4)
vs += vp[i+j]; // misalignment of &vp[i+j] is always k (assuming
// that the misalignment of the initial address is
// 0).
The loop can then be vectorized as follows:
for (k=0; k<4; k++){
rt = get_realignment_token (&vp[k]);
for (i=0; i<N; i+=4){
v1 = vp[i+k];
for (j=k; j<M; j+=4){
v2 = vp[i+j+VS-1];
va = REALIGN_LOAD <v1,v2,rt>;
vs += va;
v1 = v2;
}
}
} */
if (DR_IS_READ (dr))
{
bool is_packed = false;
tree type = (TREE_TYPE (DR_REF (dr)));
if (optab_handler (vec_realign_load_optab, mode) != CODE_FOR_nothing
&& (!targetm.vectorize.builtin_mask_for_load
|| targetm.vectorize.builtin_mask_for_load ()))
{
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
/* If we are doing SLP then the accesses need not have the
same alignment, instead it depends on the SLP group size. */
if (loop_vinfo
&& STMT_SLP_TYPE (stmt_info)
&& !multiple_p (LOOP_VINFO_VECT_FACTOR (loop_vinfo)
* (DR_GROUP_SIZE
(DR_GROUP_FIRST_ELEMENT (stmt_info))),
TYPE_VECTOR_SUBPARTS (vectype)))
;
else if (!loop_vinfo
|| (nested_in_vect_loop
&& maybe_ne (TREE_INT_CST_LOW (DR_STEP (dr)),
GET_MODE_SIZE (TYPE_MODE (vectype)))))
return dr_explicit_realign;
else
return dr_explicit_realign_optimized;
}
if (!known_alignment_for_access_p (dr_info))
is_packed = not_size_aligned (DR_REF (dr));
if (targetm.vectorize.support_vector_misalignment
(mode, type, DR_MISALIGNMENT (dr_info), is_packed))
/* Can't software pipeline the loads, but can at least do them. */
return dr_unaligned_supported;
}
else
{
bool is_packed = false;
tree type = (TREE_TYPE (DR_REF (dr)));
if (!known_alignment_for_access_p (dr_info))
is_packed = not_size_aligned (DR_REF (dr));
if (targetm.vectorize.support_vector_misalignment
(mode, type, DR_MISALIGNMENT (dr_info), is_packed))
return dr_unaligned_supported;
}
/* Unsupported. */
return dr_unaligned_unsupported;
}