2030 lines
58 KiB
C++
2030 lines
58 KiB
C++
/* Vectorizer
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Copyright (C) 2003-2022 Free Software Foundation, Inc.
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Contributed by Dorit Naishlos <dorit@il.ibm.com>
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This file is part of GCC.
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GCC is free software; you can redistribute it and/or modify it under
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the terms of the GNU General Public License as published by the Free
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Software Foundation; either version 3, or (at your option) any later
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version.
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GCC is distributed in the hope that it will be useful, but WITHOUT ANY
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WARRANTY; without even the implied warranty of MERCHANTABILITY or
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FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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for more details.
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You should have received a copy of the GNU General Public License
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along with GCC; see the file COPYING3. If not see
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<http://www.gnu.org/licenses/>. */
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/* Loop and basic block vectorizer.
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This file contains drivers for the three vectorizers:
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(1) loop vectorizer (inter-iteration parallelism),
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(2) loop-aware SLP (intra-iteration parallelism) (invoked by the loop
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vectorizer)
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(3) BB vectorizer (out-of-loops), aka SLP
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The rest of the vectorizer's code is organized as follows:
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- tree-vect-loop.cc - loop specific parts such as reductions, etc. These are
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used by drivers (1) and (2).
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- tree-vect-loop-manip.cc - vectorizer's loop control-flow utilities, used by
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drivers (1) and (2).
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- tree-vect-slp.cc - BB vectorization specific analysis and transformation,
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used by drivers (2) and (3).
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- tree-vect-stmts.cc - statements analysis and transformation (used by all).
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- tree-vect-data-refs.cc - vectorizer specific data-refs analysis and
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manipulations (used by all).
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- tree-vect-patterns.cc - vectorizable code patterns detector (used by all)
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Here's a poor attempt at illustrating that:
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tree-vectorizer.cc:
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loop_vect() loop_aware_slp() slp_vect()
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| / \ /
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| / \ /
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tree-vect-loop.cc tree-vect-slp.cc
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| \ \ / / |
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| \ \/ / |
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| \ /\ / |
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| \ / \ / |
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tree-vect-stmts.cc tree-vect-data-refs.cc
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\ /
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tree-vect-patterns.cc
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*/
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#include "config.h"
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#include "system.h"
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#include "coretypes.h"
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#include "backend.h"
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#include "tree.h"
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#include "gimple.h"
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#include "predict.h"
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#include "tree-pass.h"
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#include "ssa.h"
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#include "cgraph.h"
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#include "fold-const.h"
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#include "stor-layout.h"
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#include "gimple-iterator.h"
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#include "gimple-walk.h"
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#include "tree-ssa-loop-manip.h"
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#include "tree-ssa-loop-niter.h"
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#include "tree-cfg.h"
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#include "cfgloop.h"
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#include "tree-vectorizer.h"
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#include "tree-ssa-propagate.h"
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#include "dbgcnt.h"
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#include "tree-scalar-evolution.h"
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#include "stringpool.h"
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#include "attribs.h"
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#include "gimple-pretty-print.h"
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#include "opt-problem.h"
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#include "internal-fn.h"
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#include "tree-ssa-sccvn.h"
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/* Loop or bb location, with hotness information. */
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dump_user_location_t vect_location;
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/* auto_purge_vect_location's dtor: reset the vect_location
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global, to avoid stale location_t values that could reference
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GC-ed blocks. */
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auto_purge_vect_location::~auto_purge_vect_location ()
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{
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vect_location = dump_user_location_t ();
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}
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/* Dump a cost entry according to args to F. */
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void
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dump_stmt_cost (FILE *f, int count, enum vect_cost_for_stmt kind,
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stmt_vec_info stmt_info, slp_tree node, tree,
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int misalign, unsigned cost,
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enum vect_cost_model_location where)
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{
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if (stmt_info)
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{
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print_gimple_expr (f, STMT_VINFO_STMT (stmt_info), 0, TDF_SLIM);
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fprintf (f, " ");
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}
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else if (node)
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fprintf (f, "node %p ", (void *)node);
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else
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fprintf (f, "<unknown> ");
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fprintf (f, "%d times ", count);
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const char *ks = "unknown";
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switch (kind)
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{
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case scalar_stmt:
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ks = "scalar_stmt";
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break;
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case scalar_load:
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ks = "scalar_load";
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break;
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case scalar_store:
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ks = "scalar_store";
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break;
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case vector_stmt:
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ks = "vector_stmt";
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break;
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case vector_load:
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ks = "vector_load";
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break;
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case vector_gather_load:
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ks = "vector_gather_load";
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break;
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case unaligned_load:
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ks = "unaligned_load";
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break;
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case unaligned_store:
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ks = "unaligned_store";
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break;
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case vector_store:
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ks = "vector_store";
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break;
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case vector_scatter_store:
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ks = "vector_scatter_store";
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break;
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case vec_to_scalar:
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ks = "vec_to_scalar";
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break;
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case scalar_to_vec:
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ks = "scalar_to_vec";
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break;
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case cond_branch_not_taken:
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ks = "cond_branch_not_taken";
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break;
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case cond_branch_taken:
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ks = "cond_branch_taken";
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break;
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case vec_perm:
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ks = "vec_perm";
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break;
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case vec_promote_demote:
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ks = "vec_promote_demote";
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break;
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case vec_construct:
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ks = "vec_construct";
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break;
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}
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fprintf (f, "%s ", ks);
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if (kind == unaligned_load || kind == unaligned_store)
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fprintf (f, "(misalign %d) ", misalign);
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fprintf (f, "costs %u ", cost);
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const char *ws = "unknown";
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switch (where)
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{
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case vect_prologue:
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ws = "prologue";
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break;
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case vect_body:
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ws = "body";
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break;
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case vect_epilogue:
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ws = "epilogue";
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break;
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}
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fprintf (f, "in %s\n", ws);
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}
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/* For mapping simduid to vectorization factor. */
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class simduid_to_vf : public free_ptr_hash<simduid_to_vf>
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{
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public:
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unsigned int simduid;
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poly_uint64 vf;
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/* hash_table support. */
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static inline hashval_t hash (const simduid_to_vf *);
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static inline int equal (const simduid_to_vf *, const simduid_to_vf *);
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};
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inline hashval_t
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simduid_to_vf::hash (const simduid_to_vf *p)
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{
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return p->simduid;
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}
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inline int
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simduid_to_vf::equal (const simduid_to_vf *p1, const simduid_to_vf *p2)
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{
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return p1->simduid == p2->simduid;
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}
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/* This hash maps the OMP simd array to the corresponding simduid used
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to index into it. Like thus,
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_7 = GOMP_SIMD_LANE (simduid.0)
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...
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...
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D.1737[_7] = stuff;
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This hash maps from the OMP simd array (D.1737[]) to DECL_UID of
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simduid.0. */
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struct simd_array_to_simduid : free_ptr_hash<simd_array_to_simduid>
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{
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tree decl;
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unsigned int simduid;
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/* hash_table support. */
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static inline hashval_t hash (const simd_array_to_simduid *);
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static inline int equal (const simd_array_to_simduid *,
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const simd_array_to_simduid *);
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};
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inline hashval_t
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simd_array_to_simduid::hash (const simd_array_to_simduid *p)
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{
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return DECL_UID (p->decl);
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}
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inline int
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simd_array_to_simduid::equal (const simd_array_to_simduid *p1,
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const simd_array_to_simduid *p2)
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{
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return p1->decl == p2->decl;
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}
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/* Fold IFN_GOMP_SIMD_LANE, IFN_GOMP_SIMD_VF, IFN_GOMP_SIMD_LAST_LANE,
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into their corresponding constants and remove
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IFN_GOMP_SIMD_ORDERED_{START,END}. */
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static void
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adjust_simduid_builtins (hash_table<simduid_to_vf> *htab, function *fun)
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{
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basic_block bb;
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FOR_EACH_BB_FN (bb, fun)
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{
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gimple_stmt_iterator i;
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for (i = gsi_start_bb (bb); !gsi_end_p (i); )
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{
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poly_uint64 vf = 1;
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enum internal_fn ifn;
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gimple *stmt = gsi_stmt (i);
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tree t;
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if (!is_gimple_call (stmt)
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|| !gimple_call_internal_p (stmt))
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{
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gsi_next (&i);
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continue;
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}
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ifn = gimple_call_internal_fn (stmt);
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switch (ifn)
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{
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case IFN_GOMP_SIMD_LANE:
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case IFN_GOMP_SIMD_VF:
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case IFN_GOMP_SIMD_LAST_LANE:
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break;
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case IFN_GOMP_SIMD_ORDERED_START:
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case IFN_GOMP_SIMD_ORDERED_END:
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if (integer_onep (gimple_call_arg (stmt, 0)))
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{
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enum built_in_function bcode
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= (ifn == IFN_GOMP_SIMD_ORDERED_START
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? BUILT_IN_GOMP_ORDERED_START
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: BUILT_IN_GOMP_ORDERED_END);
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gimple *g
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= gimple_build_call (builtin_decl_explicit (bcode), 0);
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gimple_move_vops (g, stmt);
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gsi_replace (&i, g, true);
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continue;
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}
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gsi_remove (&i, true);
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unlink_stmt_vdef (stmt);
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continue;
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default:
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gsi_next (&i);
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continue;
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}
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tree arg = gimple_call_arg (stmt, 0);
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gcc_assert (arg != NULL_TREE);
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gcc_assert (TREE_CODE (arg) == SSA_NAME);
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simduid_to_vf *p = NULL, data;
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data.simduid = DECL_UID (SSA_NAME_VAR (arg));
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/* Need to nullify loop safelen field since it's value is not
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valid after transformation. */
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if (bb->loop_father && bb->loop_father->safelen > 0)
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bb->loop_father->safelen = 0;
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if (htab)
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{
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p = htab->find (&data);
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if (p)
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vf = p->vf;
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}
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switch (ifn)
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{
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case IFN_GOMP_SIMD_VF:
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t = build_int_cst (unsigned_type_node, vf);
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break;
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case IFN_GOMP_SIMD_LANE:
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t = build_int_cst (unsigned_type_node, 0);
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break;
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case IFN_GOMP_SIMD_LAST_LANE:
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t = gimple_call_arg (stmt, 1);
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break;
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default:
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gcc_unreachable ();
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}
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tree lhs = gimple_call_lhs (stmt);
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if (lhs)
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replace_uses_by (lhs, t);
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release_defs (stmt);
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gsi_remove (&i, true);
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}
|
||
}
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||
}
|
||
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||
/* Helper structure for note_simd_array_uses. */
|
||
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||
struct note_simd_array_uses_struct
|
||
{
|
||
hash_table<simd_array_to_simduid> **htab;
|
||
unsigned int simduid;
|
||
};
|
||
|
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/* Callback for note_simd_array_uses, called through walk_gimple_op. */
|
||
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static tree
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note_simd_array_uses_cb (tree *tp, int *walk_subtrees, void *data)
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{
|
||
struct walk_stmt_info *wi = (struct walk_stmt_info *) data;
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struct note_simd_array_uses_struct *ns
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= (struct note_simd_array_uses_struct *) wi->info;
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||
|
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if (TYPE_P (*tp))
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*walk_subtrees = 0;
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else if (VAR_P (*tp)
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&& lookup_attribute ("omp simd array", DECL_ATTRIBUTES (*tp))
|
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&& DECL_CONTEXT (*tp) == current_function_decl)
|
||
{
|
||
simd_array_to_simduid data;
|
||
if (!*ns->htab)
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||
*ns->htab = new hash_table<simd_array_to_simduid> (15);
|
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data.decl = *tp;
|
||
data.simduid = ns->simduid;
|
||
simd_array_to_simduid **slot = (*ns->htab)->find_slot (&data, INSERT);
|
||
if (*slot == NULL)
|
||
{
|
||
simd_array_to_simduid *p = XNEW (simd_array_to_simduid);
|
||
*p = data;
|
||
*slot = p;
|
||
}
|
||
else if ((*slot)->simduid != ns->simduid)
|
||
(*slot)->simduid = -1U;
|
||
*walk_subtrees = 0;
|
||
}
|
||
return NULL_TREE;
|
||
}
|
||
|
||
/* Find "omp simd array" temporaries and map them to corresponding
|
||
simduid. */
|
||
|
||
static void
|
||
note_simd_array_uses (hash_table<simd_array_to_simduid> **htab, function *fun)
|
||
{
|
||
basic_block bb;
|
||
gimple_stmt_iterator gsi;
|
||
struct walk_stmt_info wi;
|
||
struct note_simd_array_uses_struct ns;
|
||
|
||
memset (&wi, 0, sizeof (wi));
|
||
wi.info = &ns;
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||
ns.htab = htab;
|
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|
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FOR_EACH_BB_FN (bb, fun)
|
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for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi))
|
||
{
|
||
gimple *stmt = gsi_stmt (gsi);
|
||
if (!is_gimple_call (stmt) || !gimple_call_internal_p (stmt))
|
||
continue;
|
||
switch (gimple_call_internal_fn (stmt))
|
||
{
|
||
case IFN_GOMP_SIMD_LANE:
|
||
case IFN_GOMP_SIMD_VF:
|
||
case IFN_GOMP_SIMD_LAST_LANE:
|
||
break;
|
||
default:
|
||
continue;
|
||
}
|
||
tree lhs = gimple_call_lhs (stmt);
|
||
if (lhs == NULL_TREE)
|
||
continue;
|
||
imm_use_iterator use_iter;
|
||
gimple *use_stmt;
|
||
ns.simduid = DECL_UID (SSA_NAME_VAR (gimple_call_arg (stmt, 0)));
|
||
FOR_EACH_IMM_USE_STMT (use_stmt, use_iter, lhs)
|
||
if (!is_gimple_debug (use_stmt))
|
||
walk_gimple_op (use_stmt, note_simd_array_uses_cb, &wi);
|
||
}
|
||
}
|
||
|
||
/* Shrink arrays with "omp simd array" attribute to the corresponding
|
||
vectorization factor. */
|
||
|
||
static void
|
||
shrink_simd_arrays
|
||
(hash_table<simd_array_to_simduid> *simd_array_to_simduid_htab,
|
||
hash_table<simduid_to_vf> *simduid_to_vf_htab)
|
||
{
|
||
for (hash_table<simd_array_to_simduid>::iterator iter
|
||
= simd_array_to_simduid_htab->begin ();
|
||
iter != simd_array_to_simduid_htab->end (); ++iter)
|
||
if ((*iter)->simduid != -1U)
|
||
{
|
||
tree decl = (*iter)->decl;
|
||
poly_uint64 vf = 1;
|
||
if (simduid_to_vf_htab)
|
||
{
|
||
simduid_to_vf *p = NULL, data;
|
||
data.simduid = (*iter)->simduid;
|
||
p = simduid_to_vf_htab->find (&data);
|
||
if (p)
|
||
vf = p->vf;
|
||
}
|
||
tree atype
|
||
= build_array_type_nelts (TREE_TYPE (TREE_TYPE (decl)), vf);
|
||
TREE_TYPE (decl) = atype;
|
||
relayout_decl (decl);
|
||
}
|
||
|
||
delete simd_array_to_simduid_htab;
|
||
}
|
||
|
||
/* Initialize the vec_info with kind KIND_IN and target cost data
|
||
TARGET_COST_DATA_IN. */
|
||
|
||
vec_info::vec_info (vec_info::vec_kind kind_in, vec_info_shared *shared_)
|
||
: kind (kind_in),
|
||
shared (shared_),
|
||
stmt_vec_info_ro (false)
|
||
{
|
||
stmt_vec_infos.create (50);
|
||
}
|
||
|
||
vec_info::~vec_info ()
|
||
{
|
||
for (slp_instance &instance : slp_instances)
|
||
vect_free_slp_instance (instance);
|
||
|
||
free_stmt_vec_infos ();
|
||
}
|
||
|
||
vec_info_shared::vec_info_shared ()
|
||
: n_stmts (0),
|
||
datarefs (vNULL),
|
||
datarefs_copy (vNULL),
|
||
ddrs (vNULL)
|
||
{
|
||
}
|
||
|
||
vec_info_shared::~vec_info_shared ()
|
||
{
|
||
free_data_refs (datarefs);
|
||
free_dependence_relations (ddrs);
|
||
datarefs_copy.release ();
|
||
}
|
||
|
||
void
|
||
vec_info_shared::save_datarefs ()
|
||
{
|
||
if (!flag_checking)
|
||
return;
|
||
datarefs_copy.reserve_exact (datarefs.length ());
|
||
for (unsigned i = 0; i < datarefs.length (); ++i)
|
||
datarefs_copy.quick_push (*datarefs[i]);
|
||
}
|
||
|
||
void
|
||
vec_info_shared::check_datarefs ()
|
||
{
|
||
if (!flag_checking)
|
||
return;
|
||
gcc_assert (datarefs.length () == datarefs_copy.length ());
|
||
for (unsigned i = 0; i < datarefs.length (); ++i)
|
||
if (memcmp (&datarefs_copy[i], datarefs[i],
|
||
offsetof (data_reference, alt_indices)) != 0)
|
||
gcc_unreachable ();
|
||
}
|
||
|
||
/* Record that STMT belongs to the vectorizable region. Create and return
|
||
an associated stmt_vec_info. */
|
||
|
||
stmt_vec_info
|
||
vec_info::add_stmt (gimple *stmt)
|
||
{
|
||
stmt_vec_info res = new_stmt_vec_info (stmt);
|
||
set_vinfo_for_stmt (stmt, res);
|
||
return res;
|
||
}
|
||
|
||
/* Record that STMT belongs to the vectorizable region. Create a new
|
||
stmt_vec_info and mark VECINFO as being related and return the new
|
||
stmt_vec_info. */
|
||
|
||
stmt_vec_info
|
||
vec_info::add_pattern_stmt (gimple *stmt, stmt_vec_info stmt_info)
|
||
{
|
||
stmt_vec_info res = new_stmt_vec_info (stmt);
|
||
set_vinfo_for_stmt (stmt, res, false);
|
||
STMT_VINFO_RELATED_STMT (res) = stmt_info;
|
||
return res;
|
||
}
|
||
|
||
/* If STMT has an associated stmt_vec_info, return that vec_info, otherwise
|
||
return null. It is safe to call this function on any statement, even if
|
||
it might not be part of the vectorizable region. */
|
||
|
||
stmt_vec_info
|
||
vec_info::lookup_stmt (gimple *stmt)
|
||
{
|
||
unsigned int uid = gimple_uid (stmt);
|
||
if (uid > 0 && uid - 1 < stmt_vec_infos.length ())
|
||
{
|
||
stmt_vec_info res = stmt_vec_infos[uid - 1];
|
||
if (res && res->stmt == stmt)
|
||
return res;
|
||
}
|
||
return NULL;
|
||
}
|
||
|
||
/* If NAME is an SSA_NAME and its definition has an associated stmt_vec_info,
|
||
return that stmt_vec_info, otherwise return null. It is safe to call
|
||
this on arbitrary operands. */
|
||
|
||
stmt_vec_info
|
||
vec_info::lookup_def (tree name)
|
||
{
|
||
if (TREE_CODE (name) == SSA_NAME
|
||
&& !SSA_NAME_IS_DEFAULT_DEF (name))
|
||
return lookup_stmt (SSA_NAME_DEF_STMT (name));
|
||
return NULL;
|
||
}
|
||
|
||
/* See whether there is a single non-debug statement that uses LHS and
|
||
whether that statement has an associated stmt_vec_info. Return the
|
||
stmt_vec_info if so, otherwise return null. */
|
||
|
||
stmt_vec_info
|
||
vec_info::lookup_single_use (tree lhs)
|
||
{
|
||
use_operand_p dummy;
|
||
gimple *use_stmt;
|
||
if (single_imm_use (lhs, &dummy, &use_stmt))
|
||
return lookup_stmt (use_stmt);
|
||
return NULL;
|
||
}
|
||
|
||
/* Return vectorization information about DR. */
|
||
|
||
dr_vec_info *
|
||
vec_info::lookup_dr (data_reference *dr)
|
||
{
|
||
stmt_vec_info stmt_info = lookup_stmt (DR_STMT (dr));
|
||
/* DR_STMT should never refer to a stmt in a pattern replacement. */
|
||
gcc_checking_assert (!is_pattern_stmt_p (stmt_info));
|
||
return STMT_VINFO_DR_INFO (stmt_info->dr_aux.stmt);
|
||
}
|
||
|
||
/* Record that NEW_STMT_INFO now implements the same data reference
|
||
as OLD_STMT_INFO. */
|
||
|
||
void
|
||
vec_info::move_dr (stmt_vec_info new_stmt_info, stmt_vec_info old_stmt_info)
|
||
{
|
||
gcc_assert (!is_pattern_stmt_p (old_stmt_info));
|
||
STMT_VINFO_DR_INFO (old_stmt_info)->stmt = new_stmt_info;
|
||
new_stmt_info->dr_aux = old_stmt_info->dr_aux;
|
||
STMT_VINFO_DR_WRT_VEC_LOOP (new_stmt_info)
|
||
= STMT_VINFO_DR_WRT_VEC_LOOP (old_stmt_info);
|
||
STMT_VINFO_GATHER_SCATTER_P (new_stmt_info)
|
||
= STMT_VINFO_GATHER_SCATTER_P (old_stmt_info);
|
||
}
|
||
|
||
/* Permanently remove the statement described by STMT_INFO from the
|
||
function. */
|
||
|
||
void
|
||
vec_info::remove_stmt (stmt_vec_info stmt_info)
|
||
{
|
||
gcc_assert (!stmt_info->pattern_stmt_p);
|
||
set_vinfo_for_stmt (stmt_info->stmt, NULL);
|
||
unlink_stmt_vdef (stmt_info->stmt);
|
||
gimple_stmt_iterator si = gsi_for_stmt (stmt_info->stmt);
|
||
gsi_remove (&si, true);
|
||
release_defs (stmt_info->stmt);
|
||
free_stmt_vec_info (stmt_info);
|
||
}
|
||
|
||
/* Replace the statement at GSI by NEW_STMT, both the vectorization
|
||
information and the function itself. STMT_INFO describes the statement
|
||
at GSI. */
|
||
|
||
void
|
||
vec_info::replace_stmt (gimple_stmt_iterator *gsi, stmt_vec_info stmt_info,
|
||
gimple *new_stmt)
|
||
{
|
||
gimple *old_stmt = stmt_info->stmt;
|
||
gcc_assert (!stmt_info->pattern_stmt_p && old_stmt == gsi_stmt (*gsi));
|
||
gimple_set_uid (new_stmt, gimple_uid (old_stmt));
|
||
stmt_info->stmt = new_stmt;
|
||
gsi_replace (gsi, new_stmt, true);
|
||
}
|
||
|
||
/* Insert stmts in SEQ on the VEC_INFO region entry. If CONTEXT is
|
||
not NULL it specifies whether to use the sub-region entry
|
||
determined by it, currently used for loop vectorization to insert
|
||
on the inner loop entry vs. the outer loop entry. */
|
||
|
||
void
|
||
vec_info::insert_seq_on_entry (stmt_vec_info context, gimple_seq seq)
|
||
{
|
||
if (loop_vec_info loop_vinfo = dyn_cast <loop_vec_info> (this))
|
||
{
|
||
class loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
|
||
basic_block new_bb;
|
||
edge pe;
|
||
|
||
if (context && nested_in_vect_loop_p (loop, context))
|
||
loop = loop->inner;
|
||
|
||
pe = loop_preheader_edge (loop);
|
||
new_bb = gsi_insert_seq_on_edge_immediate (pe, seq);
|
||
gcc_assert (!new_bb);
|
||
}
|
||
else
|
||
{
|
||
bb_vec_info bb_vinfo = as_a <bb_vec_info> (this);
|
||
gimple_stmt_iterator gsi_region_begin
|
||
= gsi_after_labels (bb_vinfo->bbs[0]);
|
||
gsi_insert_seq_before (&gsi_region_begin, seq, GSI_SAME_STMT);
|
||
}
|
||
}
|
||
|
||
/* Like insert_seq_on_entry but just inserts the single stmt NEW_STMT. */
|
||
|
||
void
|
||
vec_info::insert_on_entry (stmt_vec_info context, gimple *new_stmt)
|
||
{
|
||
gimple_seq seq = NULL;
|
||
gimple_stmt_iterator gsi = gsi_start (seq);
|
||
gsi_insert_before_without_update (&gsi, new_stmt, GSI_SAME_STMT);
|
||
insert_seq_on_entry (context, seq);
|
||
}
|
||
|
||
/* Create and initialize a new stmt_vec_info struct for STMT. */
|
||
|
||
stmt_vec_info
|
||
vec_info::new_stmt_vec_info (gimple *stmt)
|
||
{
|
||
stmt_vec_info res = XCNEW (class _stmt_vec_info);
|
||
res->stmt = stmt;
|
||
|
||
STMT_VINFO_TYPE (res) = undef_vec_info_type;
|
||
STMT_VINFO_RELEVANT (res) = vect_unused_in_scope;
|
||
STMT_VINFO_VECTORIZABLE (res) = true;
|
||
STMT_VINFO_REDUC_TYPE (res) = TREE_CODE_REDUCTION;
|
||
STMT_VINFO_REDUC_CODE (res) = ERROR_MARK;
|
||
STMT_VINFO_REDUC_FN (res) = IFN_LAST;
|
||
STMT_VINFO_REDUC_IDX (res) = -1;
|
||
STMT_VINFO_SLP_VECT_ONLY (res) = false;
|
||
STMT_VINFO_SLP_VECT_ONLY_PATTERN (res) = false;
|
||
STMT_VINFO_VEC_STMTS (res) = vNULL;
|
||
res->reduc_initial_values = vNULL;
|
||
res->reduc_scalar_results = vNULL;
|
||
|
||
if (is_a <loop_vec_info> (this)
|
||
&& gimple_code (stmt) == GIMPLE_PHI
|
||
&& is_loop_header_bb_p (gimple_bb (stmt)))
|
||
STMT_VINFO_DEF_TYPE (res) = vect_unknown_def_type;
|
||
else
|
||
STMT_VINFO_DEF_TYPE (res) = vect_internal_def;
|
||
|
||
STMT_SLP_TYPE (res) = loop_vect;
|
||
|
||
/* This is really "uninitialized" until vect_compute_data_ref_alignment. */
|
||
res->dr_aux.misalignment = DR_MISALIGNMENT_UNINITIALIZED;
|
||
|
||
return res;
|
||
}
|
||
|
||
/* Associate STMT with INFO. */
|
||
|
||
void
|
||
vec_info::set_vinfo_for_stmt (gimple *stmt, stmt_vec_info info, bool check_ro)
|
||
{
|
||
unsigned int uid = gimple_uid (stmt);
|
||
if (uid == 0)
|
||
{
|
||
gcc_assert (!check_ro || !stmt_vec_info_ro);
|
||
gcc_checking_assert (info);
|
||
uid = stmt_vec_infos.length () + 1;
|
||
gimple_set_uid (stmt, uid);
|
||
stmt_vec_infos.safe_push (info);
|
||
}
|
||
else
|
||
{
|
||
gcc_checking_assert (info == NULL);
|
||
stmt_vec_infos[uid - 1] = info;
|
||
}
|
||
}
|
||
|
||
/* Free the contents of stmt_vec_infos. */
|
||
|
||
void
|
||
vec_info::free_stmt_vec_infos (void)
|
||
{
|
||
for (stmt_vec_info &info : stmt_vec_infos)
|
||
if (info != NULL)
|
||
free_stmt_vec_info (info);
|
||
stmt_vec_infos.release ();
|
||
}
|
||
|
||
/* Free STMT_INFO. */
|
||
|
||
void
|
||
vec_info::free_stmt_vec_info (stmt_vec_info stmt_info)
|
||
{
|
||
if (stmt_info->pattern_stmt_p)
|
||
{
|
||
gimple_set_bb (stmt_info->stmt, NULL);
|
||
tree lhs = gimple_get_lhs (stmt_info->stmt);
|
||
if (lhs && TREE_CODE (lhs) == SSA_NAME)
|
||
release_ssa_name (lhs);
|
||
}
|
||
|
||
stmt_info->reduc_initial_values.release ();
|
||
stmt_info->reduc_scalar_results.release ();
|
||
STMT_VINFO_SIMD_CLONE_INFO (stmt_info).release ();
|
||
STMT_VINFO_VEC_STMTS (stmt_info).release ();
|
||
free (stmt_info);
|
||
}
|
||
|
||
/* Returns true if S1 dominates S2. */
|
||
|
||
bool
|
||
vect_stmt_dominates_stmt_p (gimple *s1, gimple *s2)
|
||
{
|
||
basic_block bb1 = gimple_bb (s1), bb2 = gimple_bb (s2);
|
||
|
||
/* If bb1 is NULL, it should be a GIMPLE_NOP def stmt of an (D)
|
||
SSA_NAME. Assume it lives at the beginning of function and
|
||
thus dominates everything. */
|
||
if (!bb1 || s1 == s2)
|
||
return true;
|
||
|
||
/* If bb2 is NULL, it doesn't dominate any stmt with a bb. */
|
||
if (!bb2)
|
||
return false;
|
||
|
||
if (bb1 != bb2)
|
||
return dominated_by_p (CDI_DOMINATORS, bb2, bb1);
|
||
|
||
/* PHIs in the same basic block are assumed to be
|
||
executed all in parallel, if only one stmt is a PHI,
|
||
it dominates the other stmt in the same basic block. */
|
||
if (gimple_code (s1) == GIMPLE_PHI)
|
||
return true;
|
||
|
||
if (gimple_code (s2) == GIMPLE_PHI)
|
||
return false;
|
||
|
||
/* Inserted vectorized stmts all have UID 0 while the original stmts
|
||
in the IL have UID increasing within a BB. Walk from both sides
|
||
until we find the other stmt or a stmt with UID != 0. */
|
||
gimple_stmt_iterator gsi1 = gsi_for_stmt (s1);
|
||
while (gimple_uid (gsi_stmt (gsi1)) == 0)
|
||
{
|
||
gsi_next (&gsi1);
|
||
if (gsi_end_p (gsi1))
|
||
return false;
|
||
if (gsi_stmt (gsi1) == s2)
|
||
return true;
|
||
}
|
||
if (gimple_uid (gsi_stmt (gsi1)) == -1u)
|
||
return false;
|
||
|
||
gimple_stmt_iterator gsi2 = gsi_for_stmt (s2);
|
||
while (gimple_uid (gsi_stmt (gsi2)) == 0)
|
||
{
|
||
gsi_prev (&gsi2);
|
||
if (gsi_end_p (gsi2))
|
||
return false;
|
||
if (gsi_stmt (gsi2) == s1)
|
||
return true;
|
||
}
|
||
if (gimple_uid (gsi_stmt (gsi2)) == -1u)
|
||
return false;
|
||
|
||
if (gimple_uid (gsi_stmt (gsi1)) <= gimple_uid (gsi_stmt (gsi2)))
|
||
return true;
|
||
return false;
|
||
}
|
||
|
||
/* A helper function to free scev and LOOP niter information, as well as
|
||
clear loop constraint LOOP_C_FINITE. */
|
||
|
||
void
|
||
vect_free_loop_info_assumptions (class loop *loop)
|
||
{
|
||
scev_reset_htab ();
|
||
/* We need to explicitly reset upper bound information since they are
|
||
used even after free_numbers_of_iterations_estimates. */
|
||
loop->any_upper_bound = false;
|
||
loop->any_likely_upper_bound = false;
|
||
free_numbers_of_iterations_estimates (loop);
|
||
loop_constraint_clear (loop, LOOP_C_FINITE);
|
||
}
|
||
|
||
/* If LOOP has been versioned during ifcvt, return the internal call
|
||
guarding it. */
|
||
|
||
gimple *
|
||
vect_loop_vectorized_call (class loop *loop, gcond **cond)
|
||
{
|
||
basic_block bb = loop_preheader_edge (loop)->src;
|
||
gimple *g;
|
||
do
|
||
{
|
||
g = last_stmt (bb);
|
||
if ((g && gimple_code (g) == GIMPLE_COND)
|
||
|| !single_succ_p (bb))
|
||
break;
|
||
if (!single_pred_p (bb))
|
||
break;
|
||
bb = single_pred (bb);
|
||
}
|
||
while (1);
|
||
if (g && gimple_code (g) == GIMPLE_COND)
|
||
{
|
||
if (cond)
|
||
*cond = as_a <gcond *> (g);
|
||
gimple_stmt_iterator gsi = gsi_for_stmt (g);
|
||
gsi_prev (&gsi);
|
||
if (!gsi_end_p (gsi))
|
||
{
|
||
g = gsi_stmt (gsi);
|
||
if (gimple_call_internal_p (g, IFN_LOOP_VECTORIZED)
|
||
&& (tree_to_shwi (gimple_call_arg (g, 0)) == loop->num
|
||
|| tree_to_shwi (gimple_call_arg (g, 1)) == loop->num))
|
||
return g;
|
||
}
|
||
}
|
||
return NULL;
|
||
}
|
||
|
||
/* If LOOP has been versioned during loop distribution, return the gurading
|
||
internal call. */
|
||
|
||
static gimple *
|
||
vect_loop_dist_alias_call (class loop *loop, function *fun)
|
||
{
|
||
basic_block bb;
|
||
basic_block entry;
|
||
class loop *outer, *orig;
|
||
gimple_stmt_iterator gsi;
|
||
gimple *g;
|
||
|
||
if (loop->orig_loop_num == 0)
|
||
return NULL;
|
||
|
||
orig = get_loop (fun, loop->orig_loop_num);
|
||
if (orig == NULL)
|
||
{
|
||
/* The original loop is somehow destroyed. Clear the information. */
|
||
loop->orig_loop_num = 0;
|
||
return NULL;
|
||
}
|
||
|
||
if (loop != orig)
|
||
bb = nearest_common_dominator (CDI_DOMINATORS, loop->header, orig->header);
|
||
else
|
||
bb = loop_preheader_edge (loop)->src;
|
||
|
||
outer = bb->loop_father;
|
||
entry = ENTRY_BLOCK_PTR_FOR_FN (fun);
|
||
|
||
/* Look upward in dominance tree. */
|
||
for (; bb != entry && flow_bb_inside_loop_p (outer, bb);
|
||
bb = get_immediate_dominator (CDI_DOMINATORS, bb))
|
||
{
|
||
g = last_stmt (bb);
|
||
if (g == NULL || gimple_code (g) != GIMPLE_COND)
|
||
continue;
|
||
|
||
gsi = gsi_for_stmt (g);
|
||
gsi_prev (&gsi);
|
||
if (gsi_end_p (gsi))
|
||
continue;
|
||
|
||
g = gsi_stmt (gsi);
|
||
/* The guarding internal function call must have the same distribution
|
||
alias id. */
|
||
if (gimple_call_internal_p (g, IFN_LOOP_DIST_ALIAS)
|
||
&& (tree_to_shwi (gimple_call_arg (g, 0)) == loop->orig_loop_num))
|
||
return g;
|
||
}
|
||
return NULL;
|
||
}
|
||
|
||
/* Set the uids of all the statements in basic blocks inside loop
|
||
represented by LOOP_VINFO. LOOP_VECTORIZED_CALL is the internal
|
||
call guarding the loop which has been if converted. */
|
||
static void
|
||
set_uid_loop_bbs (loop_vec_info loop_vinfo, gimple *loop_vectorized_call,
|
||
function *fun)
|
||
{
|
||
tree arg = gimple_call_arg (loop_vectorized_call, 1);
|
||
basic_block *bbs;
|
||
unsigned int i;
|
||
class loop *scalar_loop = get_loop (fun, tree_to_shwi (arg));
|
||
|
||
LOOP_VINFO_SCALAR_LOOP (loop_vinfo) = scalar_loop;
|
||
gcc_checking_assert (vect_loop_vectorized_call (scalar_loop)
|
||
== loop_vectorized_call);
|
||
/* If we are going to vectorize outer loop, prevent vectorization
|
||
of the inner loop in the scalar loop - either the scalar loop is
|
||
thrown away, so it is a wasted work, or is used only for
|
||
a few iterations. */
|
||
if (scalar_loop->inner)
|
||
{
|
||
gimple *g = vect_loop_vectorized_call (scalar_loop->inner);
|
||
if (g)
|
||
{
|
||
arg = gimple_call_arg (g, 0);
|
||
get_loop (fun, tree_to_shwi (arg))->dont_vectorize = true;
|
||
fold_loop_internal_call (g, boolean_false_node);
|
||
}
|
||
}
|
||
bbs = get_loop_body (scalar_loop);
|
||
for (i = 0; i < scalar_loop->num_nodes; i++)
|
||
{
|
||
basic_block bb = bbs[i];
|
||
gimple_stmt_iterator gsi;
|
||
for (gsi = gsi_start_phis (bb); !gsi_end_p (gsi); gsi_next (&gsi))
|
||
{
|
||
gimple *phi = gsi_stmt (gsi);
|
||
gimple_set_uid (phi, 0);
|
||
}
|
||
for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi))
|
||
{
|
||
gimple *stmt = gsi_stmt (gsi);
|
||
gimple_set_uid (stmt, 0);
|
||
}
|
||
}
|
||
free (bbs);
|
||
}
|
||
|
||
/* Generate vectorized code for LOOP and its epilogues. */
|
||
|
||
static void
|
||
vect_transform_loops (hash_table<simduid_to_vf> *&simduid_to_vf_htab,
|
||
loop_p loop, gimple *loop_vectorized_call,
|
||
function *fun)
|
||
{
|
||
loop_vec_info loop_vinfo = loop_vec_info_for_loop (loop);
|
||
|
||
if (loop_vectorized_call)
|
||
set_uid_loop_bbs (loop_vinfo, loop_vectorized_call, fun);
|
||
|
||
unsigned HOST_WIDE_INT bytes;
|
||
if (dump_enabled_p ())
|
||
{
|
||
if (GET_MODE_SIZE (loop_vinfo->vector_mode).is_constant (&bytes))
|
||
dump_printf_loc (MSG_OPTIMIZED_LOCATIONS, vect_location,
|
||
"loop vectorized using %wu byte vectors\n", bytes);
|
||
else
|
||
dump_printf_loc (MSG_OPTIMIZED_LOCATIONS, vect_location,
|
||
"loop vectorized using variable length vectors\n");
|
||
}
|
||
|
||
loop_p new_loop = vect_transform_loop (loop_vinfo,
|
||
loop_vectorized_call);
|
||
/* Now that the loop has been vectorized, allow it to be unrolled
|
||
etc. */
|
||
loop->force_vectorize = false;
|
||
|
||
if (loop->simduid)
|
||
{
|
||
simduid_to_vf *simduid_to_vf_data = XNEW (simduid_to_vf);
|
||
if (!simduid_to_vf_htab)
|
||
simduid_to_vf_htab = new hash_table<simduid_to_vf> (15);
|
||
simduid_to_vf_data->simduid = DECL_UID (loop->simduid);
|
||
simduid_to_vf_data->vf = loop_vinfo->vectorization_factor;
|
||
*simduid_to_vf_htab->find_slot (simduid_to_vf_data, INSERT)
|
||
= simduid_to_vf_data;
|
||
}
|
||
|
||
/* Epilogue of vectorized loop must be vectorized too. */
|
||
if (new_loop)
|
||
vect_transform_loops (simduid_to_vf_htab, new_loop, NULL, fun);
|
||
}
|
||
|
||
/* Try to vectorize LOOP. */
|
||
|
||
static unsigned
|
||
try_vectorize_loop_1 (hash_table<simduid_to_vf> *&simduid_to_vf_htab,
|
||
unsigned *num_vectorized_loops, loop_p loop,
|
||
gimple *loop_vectorized_call,
|
||
gimple *loop_dist_alias_call,
|
||
function *fun)
|
||
{
|
||
unsigned ret = 0;
|
||
vec_info_shared shared;
|
||
auto_purge_vect_location sentinel;
|
||
vect_location = find_loop_location (loop);
|
||
|
||
if (LOCATION_LOCUS (vect_location.get_location_t ()) != UNKNOWN_LOCATION
|
||
&& dump_enabled_p ())
|
||
dump_printf (MSG_NOTE | MSG_PRIORITY_INTERNALS,
|
||
"\nAnalyzing loop at %s:%d\n",
|
||
LOCATION_FILE (vect_location.get_location_t ()),
|
||
LOCATION_LINE (vect_location.get_location_t ()));
|
||
|
||
/* Try to analyze the loop, retaining an opt_problem if dump_enabled_p. */
|
||
opt_loop_vec_info loop_vinfo = vect_analyze_loop (loop, &shared);
|
||
loop->aux = loop_vinfo;
|
||
|
||
if (!loop_vinfo)
|
||
if (dump_enabled_p ())
|
||
if (opt_problem *problem = loop_vinfo.get_problem ())
|
||
{
|
||
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
|
||
"couldn't vectorize loop\n");
|
||
problem->emit_and_clear ();
|
||
}
|
||
|
||
if (!loop_vinfo || !LOOP_VINFO_VECTORIZABLE_P (loop_vinfo))
|
||
{
|
||
/* Free existing information if loop is analyzed with some
|
||
assumptions. */
|
||
if (loop_constraint_set_p (loop, LOOP_C_FINITE))
|
||
vect_free_loop_info_assumptions (loop);
|
||
|
||
/* If we applied if-conversion then try to vectorize the
|
||
BB of innermost loops.
|
||
??? Ideally BB vectorization would learn to vectorize
|
||
control flow by applying if-conversion on-the-fly, the
|
||
following retains the if-converted loop body even when
|
||
only non-if-converted parts took part in BB vectorization. */
|
||
if (flag_tree_slp_vectorize != 0
|
||
&& loop_vectorized_call
|
||
&& ! loop->inner)
|
||
{
|
||
basic_block bb = loop->header;
|
||
bool require_loop_vectorize = false;
|
||
for (gimple_stmt_iterator gsi = gsi_start_bb (bb);
|
||
!gsi_end_p (gsi); gsi_next (&gsi))
|
||
{
|
||
gimple *stmt = gsi_stmt (gsi);
|
||
gcall *call = dyn_cast <gcall *> (stmt);
|
||
if (call && gimple_call_internal_p (call))
|
||
{
|
||
internal_fn ifn = gimple_call_internal_fn (call);
|
||
if (ifn == IFN_MASK_LOAD || ifn == IFN_MASK_STORE
|
||
/* Don't keep the if-converted parts when the ifn with
|
||
specifc type is not supported by the backend. */
|
||
|| (direct_internal_fn_p (ifn)
|
||
&& !direct_internal_fn_supported_p
|
||
(call, OPTIMIZE_FOR_SPEED)))
|
||
{
|
||
require_loop_vectorize = true;
|
||
break;
|
||
}
|
||
}
|
||
gimple_set_uid (stmt, -1);
|
||
gimple_set_visited (stmt, false);
|
||
}
|
||
if (!require_loop_vectorize)
|
||
{
|
||
tree arg = gimple_call_arg (loop_vectorized_call, 1);
|
||
class loop *scalar_loop = get_loop (fun, tree_to_shwi (arg));
|
||
if (vect_slp_if_converted_bb (bb, scalar_loop))
|
||
{
|
||
fold_loop_internal_call (loop_vectorized_call,
|
||
boolean_true_node);
|
||
loop_vectorized_call = NULL;
|
||
ret |= TODO_cleanup_cfg | TODO_update_ssa_only_virtuals;
|
||
}
|
||
}
|
||
}
|
||
/* If outer loop vectorization fails for LOOP_VECTORIZED guarded
|
||
loop, don't vectorize its inner loop; we'll attempt to
|
||
vectorize LOOP_VECTORIZED guarded inner loop of the scalar
|
||
loop version. */
|
||
if (loop_vectorized_call && loop->inner)
|
||
loop->inner->dont_vectorize = true;
|
||
return ret;
|
||
}
|
||
|
||
if (!dbg_cnt (vect_loop))
|
||
{
|
||
/* Free existing information if loop is analyzed with some
|
||
assumptions. */
|
||
if (loop_constraint_set_p (loop, LOOP_C_FINITE))
|
||
vect_free_loop_info_assumptions (loop);
|
||
return ret;
|
||
}
|
||
|
||
(*num_vectorized_loops)++;
|
||
/* Transform LOOP and its epilogues. */
|
||
vect_transform_loops (simduid_to_vf_htab, loop, loop_vectorized_call, fun);
|
||
|
||
if (loop_vectorized_call)
|
||
{
|
||
fold_loop_internal_call (loop_vectorized_call, boolean_true_node);
|
||
ret |= TODO_cleanup_cfg;
|
||
}
|
||
if (loop_dist_alias_call)
|
||
{
|
||
tree value = gimple_call_arg (loop_dist_alias_call, 1);
|
||
fold_loop_internal_call (loop_dist_alias_call, value);
|
||
ret |= TODO_cleanup_cfg;
|
||
}
|
||
|
||
return ret;
|
||
}
|
||
|
||
/* Try to vectorize LOOP. */
|
||
|
||
static unsigned
|
||
try_vectorize_loop (hash_table<simduid_to_vf> *&simduid_to_vf_htab,
|
||
unsigned *num_vectorized_loops, loop_p loop,
|
||
function *fun)
|
||
{
|
||
if (!((flag_tree_loop_vectorize
|
||
&& optimize_loop_nest_for_speed_p (loop))
|
||
|| loop->force_vectorize))
|
||
return 0;
|
||
|
||
return try_vectorize_loop_1 (simduid_to_vf_htab, num_vectorized_loops, loop,
|
||
vect_loop_vectorized_call (loop),
|
||
vect_loop_dist_alias_call (loop, fun), fun);
|
||
}
|
||
|
||
|
||
/* Loop autovectorization. */
|
||
|
||
namespace {
|
||
|
||
const pass_data pass_data_vectorize =
|
||
{
|
||
GIMPLE_PASS, /* type */
|
||
"vect", /* name */
|
||
OPTGROUP_LOOP | OPTGROUP_VEC, /* optinfo_flags */
|
||
TV_TREE_VECTORIZATION, /* tv_id */
|
||
( PROP_cfg | PROP_ssa ), /* properties_required */
|
||
0, /* properties_provided */
|
||
0, /* properties_destroyed */
|
||
0, /* todo_flags_start */
|
||
0, /* todo_flags_finish */
|
||
};
|
||
|
||
class pass_vectorize : public gimple_opt_pass
|
||
{
|
||
public:
|
||
pass_vectorize (gcc::context *ctxt)
|
||
: gimple_opt_pass (pass_data_vectorize, ctxt)
|
||
{}
|
||
|
||
/* opt_pass methods: */
|
||
virtual bool gate (function *fun)
|
||
{
|
||
return flag_tree_loop_vectorize || fun->has_force_vectorize_loops;
|
||
}
|
||
|
||
virtual unsigned int execute (function *);
|
||
|
||
}; // class pass_vectorize
|
||
|
||
/* Function vectorize_loops.
|
||
|
||
Entry point to loop vectorization phase. */
|
||
|
||
unsigned
|
||
pass_vectorize::execute (function *fun)
|
||
{
|
||
unsigned int i;
|
||
unsigned int num_vectorized_loops = 0;
|
||
unsigned int vect_loops_num;
|
||
hash_table<simduid_to_vf> *simduid_to_vf_htab = NULL;
|
||
hash_table<simd_array_to_simduid> *simd_array_to_simduid_htab = NULL;
|
||
bool any_ifcvt_loops = false;
|
||
unsigned ret = 0;
|
||
|
||
vect_loops_num = number_of_loops (fun);
|
||
|
||
/* Bail out if there are no loops. */
|
||
if (vect_loops_num <= 1)
|
||
return 0;
|
||
|
||
vect_slp_init ();
|
||
|
||
if (fun->has_simduid_loops)
|
||
note_simd_array_uses (&simd_array_to_simduid_htab, fun);
|
||
|
||
/* ----------- Analyze loops. ----------- */
|
||
|
||
/* If some loop was duplicated, it gets bigger number
|
||
than all previously defined loops. This fact allows us to run
|
||
only over initial loops skipping newly generated ones. */
|
||
for (auto loop : loops_list (fun, 0))
|
||
if (loop->dont_vectorize)
|
||
{
|
||
any_ifcvt_loops = true;
|
||
/* If-conversion sometimes versions both the outer loop
|
||
(for the case when outer loop vectorization might be
|
||
desirable) as well as the inner loop in the scalar version
|
||
of the loop. So we have:
|
||
if (LOOP_VECTORIZED (1, 3))
|
||
{
|
||
loop1
|
||
loop2
|
||
}
|
||
else
|
||
loop3 (copy of loop1)
|
||
if (LOOP_VECTORIZED (4, 5))
|
||
loop4 (copy of loop2)
|
||
else
|
||
loop5 (copy of loop4)
|
||
If loops' iteration gives us loop3 first (which has
|
||
dont_vectorize set), make sure to process loop1 before loop4;
|
||
so that we can prevent vectorization of loop4 if loop1
|
||
is successfully vectorized. */
|
||
if (loop->inner)
|
||
{
|
||
gimple *loop_vectorized_call
|
||
= vect_loop_vectorized_call (loop);
|
||
if (loop_vectorized_call
|
||
&& vect_loop_vectorized_call (loop->inner))
|
||
{
|
||
tree arg = gimple_call_arg (loop_vectorized_call, 0);
|
||
class loop *vector_loop
|
||
= get_loop (fun, tree_to_shwi (arg));
|
||
if (vector_loop && vector_loop != loop)
|
||
{
|
||
/* Make sure we don't vectorize it twice. */
|
||
vector_loop->dont_vectorize = true;
|
||
ret |= try_vectorize_loop (simduid_to_vf_htab,
|
||
&num_vectorized_loops,
|
||
vector_loop, fun);
|
||
}
|
||
}
|
||
}
|
||
}
|
||
else
|
||
ret |= try_vectorize_loop (simduid_to_vf_htab, &num_vectorized_loops,
|
||
loop, fun);
|
||
|
||
vect_location = dump_user_location_t ();
|
||
|
||
statistics_counter_event (fun, "Vectorized loops", num_vectorized_loops);
|
||
if (dump_enabled_p ()
|
||
|| (num_vectorized_loops > 0 && dump_enabled_p ()))
|
||
dump_printf_loc (MSG_NOTE, vect_location,
|
||
"vectorized %u loops in function.\n",
|
||
num_vectorized_loops);
|
||
|
||
/* ----------- Finalize. ----------- */
|
||
|
||
if (any_ifcvt_loops)
|
||
for (i = 1; i < number_of_loops (fun); i++)
|
||
{
|
||
class loop *loop = get_loop (fun, i);
|
||
if (loop && loop->dont_vectorize)
|
||
{
|
||
gimple *g = vect_loop_vectorized_call (loop);
|
||
if (g)
|
||
{
|
||
fold_loop_internal_call (g, boolean_false_node);
|
||
ret |= TODO_cleanup_cfg;
|
||
g = NULL;
|
||
}
|
||
else
|
||
g = vect_loop_dist_alias_call (loop, fun);
|
||
|
||
if (g)
|
||
{
|
||
fold_loop_internal_call (g, boolean_false_node);
|
||
ret |= TODO_cleanup_cfg;
|
||
}
|
||
}
|
||
}
|
||
|
||
/* Fold IFN_GOMP_SIMD_{VF,LANE,LAST_LANE,ORDERED_{START,END}} builtins. */
|
||
if (fun->has_simduid_loops)
|
||
{
|
||
adjust_simduid_builtins (simduid_to_vf_htab, fun);
|
||
/* Avoid stale SCEV cache entries for the SIMD_LANE defs. */
|
||
scev_reset ();
|
||
}
|
||
/* Shrink any "omp array simd" temporary arrays to the
|
||
actual vectorization factors. */
|
||
if (simd_array_to_simduid_htab)
|
||
shrink_simd_arrays (simd_array_to_simduid_htab, simduid_to_vf_htab);
|
||
delete simduid_to_vf_htab;
|
||
fun->has_simduid_loops = false;
|
||
|
||
if (num_vectorized_loops > 0)
|
||
{
|
||
/* If we vectorized any loop only virtual SSA form needs to be updated.
|
||
??? Also while we try hard to update loop-closed SSA form we fail
|
||
to properly do this in some corner-cases (see PR56286). */
|
||
rewrite_into_loop_closed_ssa (NULL, TODO_update_ssa_only_virtuals);
|
||
ret |= TODO_cleanup_cfg;
|
||
}
|
||
|
||
for (i = 1; i < number_of_loops (fun); i++)
|
||
{
|
||
loop_vec_info loop_vinfo;
|
||
bool has_mask_store;
|
||
|
||
class loop *loop = get_loop (fun, i);
|
||
if (!loop || !loop->aux)
|
||
continue;
|
||
loop_vinfo = (loop_vec_info) loop->aux;
|
||
has_mask_store = LOOP_VINFO_HAS_MASK_STORE (loop_vinfo);
|
||
delete loop_vinfo;
|
||
if (has_mask_store
|
||
&& targetm.vectorize.empty_mask_is_expensive (IFN_MASK_STORE))
|
||
optimize_mask_stores (loop);
|
||
|
||
auto_bitmap exit_bbs;
|
||
/* Perform local CSE, this esp. helps because we emit code for
|
||
predicates that need to be shared for optimal predicate usage.
|
||
However reassoc will re-order them and prevent CSE from working
|
||
as it should. CSE only the loop body, not the entry. */
|
||
bitmap_set_bit (exit_bbs, single_exit (loop)->dest->index);
|
||
|
||
edge entry = EDGE_PRED (loop_preheader_edge (loop)->src, 0);
|
||
do_rpo_vn (fun, entry, exit_bbs);
|
||
|
||
loop->aux = NULL;
|
||
}
|
||
|
||
vect_slp_fini ();
|
||
|
||
return ret;
|
||
}
|
||
|
||
} // anon namespace
|
||
|
||
gimple_opt_pass *
|
||
make_pass_vectorize (gcc::context *ctxt)
|
||
{
|
||
return new pass_vectorize (ctxt);
|
||
}
|
||
|
||
/* Entry point to the simduid cleanup pass. */
|
||
|
||
namespace {
|
||
|
||
const pass_data pass_data_simduid_cleanup =
|
||
{
|
||
GIMPLE_PASS, /* type */
|
||
"simduid", /* name */
|
||
OPTGROUP_NONE, /* optinfo_flags */
|
||
TV_NONE, /* tv_id */
|
||
( PROP_ssa | PROP_cfg ), /* properties_required */
|
||
0, /* properties_provided */
|
||
0, /* properties_destroyed */
|
||
0, /* todo_flags_start */
|
||
0, /* todo_flags_finish */
|
||
};
|
||
|
||
class pass_simduid_cleanup : public gimple_opt_pass
|
||
{
|
||
public:
|
||
pass_simduid_cleanup (gcc::context *ctxt)
|
||
: gimple_opt_pass (pass_data_simduid_cleanup, ctxt)
|
||
{}
|
||
|
||
/* opt_pass methods: */
|
||
opt_pass * clone () { return new pass_simduid_cleanup (m_ctxt); }
|
||
virtual bool gate (function *fun) { return fun->has_simduid_loops; }
|
||
virtual unsigned int execute (function *);
|
||
|
||
}; // class pass_simduid_cleanup
|
||
|
||
unsigned int
|
||
pass_simduid_cleanup::execute (function *fun)
|
||
{
|
||
hash_table<simd_array_to_simduid> *simd_array_to_simduid_htab = NULL;
|
||
|
||
note_simd_array_uses (&simd_array_to_simduid_htab, fun);
|
||
|
||
/* Fold IFN_GOMP_SIMD_{VF,LANE,LAST_LANE,ORDERED_{START,END}} builtins. */
|
||
adjust_simduid_builtins (NULL, fun);
|
||
|
||
/* Shrink any "omp array simd" temporary arrays to the
|
||
actual vectorization factors. */
|
||
if (simd_array_to_simduid_htab)
|
||
shrink_simd_arrays (simd_array_to_simduid_htab, NULL);
|
||
fun->has_simduid_loops = false;
|
||
return 0;
|
||
}
|
||
|
||
} // anon namespace
|
||
|
||
gimple_opt_pass *
|
||
make_pass_simduid_cleanup (gcc::context *ctxt)
|
||
{
|
||
return new pass_simduid_cleanup (ctxt);
|
||
}
|
||
|
||
|
||
/* Entry point to basic block SLP phase. */
|
||
|
||
namespace {
|
||
|
||
const pass_data pass_data_slp_vectorize =
|
||
{
|
||
GIMPLE_PASS, /* type */
|
||
"slp", /* name */
|
||
OPTGROUP_LOOP | OPTGROUP_VEC, /* optinfo_flags */
|
||
TV_TREE_SLP_VECTORIZATION, /* tv_id */
|
||
( PROP_ssa | PROP_cfg ), /* properties_required */
|
||
0, /* properties_provided */
|
||
0, /* properties_destroyed */
|
||
0, /* todo_flags_start */
|
||
TODO_update_ssa, /* todo_flags_finish */
|
||
};
|
||
|
||
class pass_slp_vectorize : public gimple_opt_pass
|
||
{
|
||
public:
|
||
pass_slp_vectorize (gcc::context *ctxt)
|
||
: gimple_opt_pass (pass_data_slp_vectorize, ctxt)
|
||
{}
|
||
|
||
/* opt_pass methods: */
|
||
opt_pass * clone () { return new pass_slp_vectorize (m_ctxt); }
|
||
virtual bool gate (function *) { return flag_tree_slp_vectorize != 0; }
|
||
virtual unsigned int execute (function *);
|
||
|
||
}; // class pass_slp_vectorize
|
||
|
||
unsigned int
|
||
pass_slp_vectorize::execute (function *fun)
|
||
{
|
||
auto_purge_vect_location sentinel;
|
||
basic_block bb;
|
||
|
||
bool in_loop_pipeline = scev_initialized_p ();
|
||
if (!in_loop_pipeline)
|
||
{
|
||
loop_optimizer_init (LOOPS_NORMAL);
|
||
scev_initialize ();
|
||
}
|
||
|
||
/* Mark all stmts as not belonging to the current region and unvisited. */
|
||
FOR_EACH_BB_FN (bb, fun)
|
||
{
|
||
for (gphi_iterator gsi = gsi_start_phis (bb); !gsi_end_p (gsi);
|
||
gsi_next (&gsi))
|
||
{
|
||
gphi *stmt = gsi.phi ();
|
||
gimple_set_uid (stmt, -1);
|
||
gimple_set_visited (stmt, false);
|
||
}
|
||
for (gimple_stmt_iterator gsi = gsi_start_bb (bb); !gsi_end_p (gsi);
|
||
gsi_next (&gsi))
|
||
{
|
||
gimple *stmt = gsi_stmt (gsi);
|
||
gimple_set_uid (stmt, -1);
|
||
gimple_set_visited (stmt, false);
|
||
}
|
||
}
|
||
|
||
vect_slp_init ();
|
||
|
||
vect_slp_function (fun);
|
||
|
||
vect_slp_fini ();
|
||
|
||
if (!in_loop_pipeline)
|
||
{
|
||
scev_finalize ();
|
||
loop_optimizer_finalize ();
|
||
}
|
||
|
||
return 0;
|
||
}
|
||
|
||
} // anon namespace
|
||
|
||
gimple_opt_pass *
|
||
make_pass_slp_vectorize (gcc::context *ctxt)
|
||
{
|
||
return new pass_slp_vectorize (ctxt);
|
||
}
|
||
|
||
|
||
/* Increase alignment of global arrays to improve vectorization potential.
|
||
TODO:
|
||
- Consider also structs that have an array field.
|
||
- Use ipa analysis to prune arrays that can't be vectorized?
|
||
This should involve global alignment analysis and in the future also
|
||
array padding. */
|
||
|
||
static unsigned get_vec_alignment_for_type (tree);
|
||
static hash_map<tree, unsigned> *type_align_map;
|
||
|
||
/* Return alignment of array's vector type corresponding to scalar type.
|
||
0 if no vector type exists. */
|
||
static unsigned
|
||
get_vec_alignment_for_array_type (tree type)
|
||
{
|
||
gcc_assert (TREE_CODE (type) == ARRAY_TYPE);
|
||
poly_uint64 array_size, vector_size;
|
||
|
||
tree scalar_type = strip_array_types (type);
|
||
tree vectype = get_related_vectype_for_scalar_type (VOIDmode, scalar_type);
|
||
if (!vectype
|
||
|| !poly_int_tree_p (TYPE_SIZE (type), &array_size)
|
||
|| !poly_int_tree_p (TYPE_SIZE (vectype), &vector_size)
|
||
|| maybe_lt (array_size, vector_size))
|
||
return 0;
|
||
|
||
return TYPE_ALIGN (vectype);
|
||
}
|
||
|
||
/* Return alignment of field having maximum alignment of vector type
|
||
corresponding to it's scalar type. For now, we only consider fields whose
|
||
offset is a multiple of it's vector alignment.
|
||
0 if no suitable field is found. */
|
||
static unsigned
|
||
get_vec_alignment_for_record_type (tree type)
|
||
{
|
||
gcc_assert (TREE_CODE (type) == RECORD_TYPE);
|
||
|
||
unsigned max_align = 0, alignment;
|
||
HOST_WIDE_INT offset;
|
||
tree offset_tree;
|
||
|
||
if (TYPE_PACKED (type))
|
||
return 0;
|
||
|
||
unsigned *slot = type_align_map->get (type);
|
||
if (slot)
|
||
return *slot;
|
||
|
||
for (tree field = first_field (type);
|
||
field != NULL_TREE;
|
||
field = DECL_CHAIN (field))
|
||
{
|
||
/* Skip if not FIELD_DECL or if alignment is set by user. */
|
||
if (TREE_CODE (field) != FIELD_DECL
|
||
|| DECL_USER_ALIGN (field)
|
||
|| DECL_ARTIFICIAL (field))
|
||
continue;
|
||
|
||
/* We don't need to process the type further if offset is variable,
|
||
since the offsets of remaining members will also be variable. */
|
||
if (TREE_CODE (DECL_FIELD_OFFSET (field)) != INTEGER_CST
|
||
|| TREE_CODE (DECL_FIELD_BIT_OFFSET (field)) != INTEGER_CST)
|
||
break;
|
||
|
||
/* Similarly stop processing the type if offset_tree
|
||
does not fit in unsigned HOST_WIDE_INT. */
|
||
offset_tree = bit_position (field);
|
||
if (!tree_fits_uhwi_p (offset_tree))
|
||
break;
|
||
|
||
offset = tree_to_uhwi (offset_tree);
|
||
alignment = get_vec_alignment_for_type (TREE_TYPE (field));
|
||
|
||
/* Get maximum alignment of vectorized field/array among those members
|
||
whose offset is multiple of the vector alignment. */
|
||
if (alignment
|
||
&& (offset % alignment == 0)
|
||
&& (alignment > max_align))
|
||
max_align = alignment;
|
||
}
|
||
|
||
type_align_map->put (type, max_align);
|
||
return max_align;
|
||
}
|
||
|
||
/* Return alignment of vector type corresponding to decl's scalar type
|
||
or 0 if it doesn't exist or the vector alignment is lesser than
|
||
decl's alignment. */
|
||
static unsigned
|
||
get_vec_alignment_for_type (tree type)
|
||
{
|
||
if (type == NULL_TREE)
|
||
return 0;
|
||
|
||
gcc_assert (TYPE_P (type));
|
||
|
||
static unsigned alignment = 0;
|
||
switch (TREE_CODE (type))
|
||
{
|
||
case ARRAY_TYPE:
|
||
alignment = get_vec_alignment_for_array_type (type);
|
||
break;
|
||
case RECORD_TYPE:
|
||
alignment = get_vec_alignment_for_record_type (type);
|
||
break;
|
||
default:
|
||
alignment = 0;
|
||
break;
|
||
}
|
||
|
||
return (alignment > TYPE_ALIGN (type)) ? alignment : 0;
|
||
}
|
||
|
||
/* Entry point to increase_alignment pass. */
|
||
static unsigned int
|
||
increase_alignment (void)
|
||
{
|
||
varpool_node *vnode;
|
||
|
||
vect_location = dump_user_location_t ();
|
||
type_align_map = new hash_map<tree, unsigned>;
|
||
|
||
/* Increase the alignment of all global arrays for vectorization. */
|
||
FOR_EACH_DEFINED_VARIABLE (vnode)
|
||
{
|
||
tree decl = vnode->decl;
|
||
unsigned int alignment;
|
||
|
||
if ((decl_in_symtab_p (decl)
|
||
&& !symtab_node::get (decl)->can_increase_alignment_p ())
|
||
|| DECL_USER_ALIGN (decl) || DECL_ARTIFICIAL (decl))
|
||
continue;
|
||
|
||
alignment = get_vec_alignment_for_type (TREE_TYPE (decl));
|
||
if (alignment && vect_can_force_dr_alignment_p (decl, alignment))
|
||
{
|
||
vnode->increase_alignment (alignment);
|
||
if (dump_enabled_p ())
|
||
dump_printf (MSG_NOTE, "Increasing alignment of decl: %T\n", decl);
|
||
}
|
||
}
|
||
|
||
delete type_align_map;
|
||
return 0;
|
||
}
|
||
|
||
|
||
namespace {
|
||
|
||
const pass_data pass_data_ipa_increase_alignment =
|
||
{
|
||
SIMPLE_IPA_PASS, /* type */
|
||
"increase_alignment", /* name */
|
||
OPTGROUP_LOOP | OPTGROUP_VEC, /* optinfo_flags */
|
||
TV_IPA_OPT, /* tv_id */
|
||
0, /* properties_required */
|
||
0, /* properties_provided */
|
||
0, /* properties_destroyed */
|
||
0, /* todo_flags_start */
|
||
0, /* todo_flags_finish */
|
||
};
|
||
|
||
class pass_ipa_increase_alignment : public simple_ipa_opt_pass
|
||
{
|
||
public:
|
||
pass_ipa_increase_alignment (gcc::context *ctxt)
|
||
: simple_ipa_opt_pass (pass_data_ipa_increase_alignment, ctxt)
|
||
{}
|
||
|
||
/* opt_pass methods: */
|
||
virtual bool gate (function *)
|
||
{
|
||
return flag_section_anchors && flag_tree_loop_vectorize;
|
||
}
|
||
|
||
virtual unsigned int execute (function *) { return increase_alignment (); }
|
||
|
||
}; // class pass_ipa_increase_alignment
|
||
|
||
} // anon namespace
|
||
|
||
simple_ipa_opt_pass *
|
||
make_pass_ipa_increase_alignment (gcc::context *ctxt)
|
||
{
|
||
return new pass_ipa_increase_alignment (ctxt);
|
||
}
|
||
|
||
/* If the condition represented by T is a comparison or the SSA name
|
||
result of a comparison, extract the comparison's operands. Represent
|
||
T as NE_EXPR <T, 0> otherwise. */
|
||
|
||
void
|
||
scalar_cond_masked_key::get_cond_ops_from_tree (tree t)
|
||
{
|
||
if (TREE_CODE_CLASS (TREE_CODE (t)) == tcc_comparison)
|
||
{
|
||
this->code = TREE_CODE (t);
|
||
this->op0 = TREE_OPERAND (t, 0);
|
||
this->op1 = TREE_OPERAND (t, 1);
|
||
this->inverted_p = false;
|
||
return;
|
||
}
|
||
|
||
if (TREE_CODE (t) == SSA_NAME)
|
||
if (gassign *stmt = dyn_cast<gassign *> (SSA_NAME_DEF_STMT (t)))
|
||
{
|
||
tree_code code = gimple_assign_rhs_code (stmt);
|
||
if (TREE_CODE_CLASS (code) == tcc_comparison)
|
||
{
|
||
this->code = code;
|
||
this->op0 = gimple_assign_rhs1 (stmt);
|
||
this->op1 = gimple_assign_rhs2 (stmt);
|
||
this->inverted_p = false;
|
||
return;
|
||
}
|
||
else if (code == BIT_NOT_EXPR)
|
||
{
|
||
tree n_op = gimple_assign_rhs1 (stmt);
|
||
if ((stmt = dyn_cast<gassign *> (SSA_NAME_DEF_STMT (n_op))))
|
||
{
|
||
code = gimple_assign_rhs_code (stmt);
|
||
if (TREE_CODE_CLASS (code) == tcc_comparison)
|
||
{
|
||
this->code = code;
|
||
this->op0 = gimple_assign_rhs1 (stmt);
|
||
this->op1 = gimple_assign_rhs2 (stmt);
|
||
this->inverted_p = true;
|
||
return;
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
this->code = NE_EXPR;
|
||
this->op0 = t;
|
||
this->op1 = build_zero_cst (TREE_TYPE (t));
|
||
this->inverted_p = false;
|
||
}
|
||
|
||
/* See the comment above the declaration for details. */
|
||
|
||
unsigned int
|
||
vector_costs::add_stmt_cost (int count, vect_cost_for_stmt kind,
|
||
stmt_vec_info stmt_info, slp_tree,
|
||
tree vectype, int misalign,
|
||
vect_cost_model_location where)
|
||
{
|
||
unsigned int cost
|
||
= builtin_vectorization_cost (kind, vectype, misalign) * count;
|
||
return record_stmt_cost (stmt_info, where, cost);
|
||
}
|
||
|
||
/* See the comment above the declaration for details. */
|
||
|
||
void
|
||
vector_costs::finish_cost (const vector_costs *)
|
||
{
|
||
gcc_assert (!m_finished);
|
||
m_finished = true;
|
||
}
|
||
|
||
/* Record a base cost of COST units against WHERE. If STMT_INFO is
|
||
nonnull, use it to adjust the cost based on execution frequency
|
||
(where appropriate). */
|
||
|
||
unsigned int
|
||
vector_costs::record_stmt_cost (stmt_vec_info stmt_info,
|
||
vect_cost_model_location where,
|
||
unsigned int cost)
|
||
{
|
||
cost = adjust_cost_for_freq (stmt_info, where, cost);
|
||
m_costs[where] += cost;
|
||
return cost;
|
||
}
|
||
|
||
/* COST is the base cost we have calculated for an operation in location WHERE.
|
||
If STMT_INFO is nonnull, use it to adjust the cost based on execution
|
||
frequency (where appropriate). Return the adjusted cost. */
|
||
|
||
unsigned int
|
||
vector_costs::adjust_cost_for_freq (stmt_vec_info stmt_info,
|
||
vect_cost_model_location where,
|
||
unsigned int cost)
|
||
{
|
||
/* Statements in an inner loop relative to the loop being
|
||
vectorized are weighted more heavily. The value here is
|
||
arbitrary and could potentially be improved with analysis. */
|
||
if (where == vect_body
|
||
&& stmt_info
|
||
&& stmt_in_inner_loop_p (m_vinfo, stmt_info))
|
||
{
|
||
loop_vec_info loop_vinfo = as_a<loop_vec_info> (m_vinfo);
|
||
cost *= LOOP_VINFO_INNER_LOOP_COST_FACTOR (loop_vinfo);
|
||
}
|
||
return cost;
|
||
}
|
||
|
||
/* See the comment above the declaration for details. */
|
||
|
||
bool
|
||
vector_costs::better_main_loop_than_p (const vector_costs *other) const
|
||
{
|
||
int diff = compare_inside_loop_cost (other);
|
||
if (diff != 0)
|
||
return diff < 0;
|
||
|
||
/* If there's nothing to choose between the loop bodies, see whether
|
||
there's a difference in the prologue and epilogue costs. */
|
||
diff = compare_outside_loop_cost (other);
|
||
if (diff != 0)
|
||
return diff < 0;
|
||
|
||
return false;
|
||
}
|
||
|
||
|
||
/* See the comment above the declaration for details. */
|
||
|
||
bool
|
||
vector_costs::better_epilogue_loop_than_p (const vector_costs *other,
|
||
loop_vec_info main_loop) const
|
||
{
|
||
loop_vec_info this_loop_vinfo = as_a<loop_vec_info> (this->m_vinfo);
|
||
loop_vec_info other_loop_vinfo = as_a<loop_vec_info> (other->m_vinfo);
|
||
|
||
poly_int64 this_vf = LOOP_VINFO_VECT_FACTOR (this_loop_vinfo);
|
||
poly_int64 other_vf = LOOP_VINFO_VECT_FACTOR (other_loop_vinfo);
|
||
|
||
poly_uint64 main_poly_vf = LOOP_VINFO_VECT_FACTOR (main_loop);
|
||
unsigned HOST_WIDE_INT main_vf;
|
||
unsigned HOST_WIDE_INT other_factor, this_factor, other_cost, this_cost;
|
||
/* If we can determine how many iterations are left for the epilogue
|
||
loop, that is if both the main loop's vectorization factor and number
|
||
of iterations are constant, then we use them to calculate the cost of
|
||
the epilogue loop together with a 'likely value' for the epilogues
|
||
vectorization factor. Otherwise we use the main loop's vectorization
|
||
factor and the maximum poly value for the epilogue's. If the target
|
||
has not provided with a sensible upper bound poly vectorization
|
||
factors are likely to be favored over constant ones. */
|
||
if (main_poly_vf.is_constant (&main_vf)
|
||
&& LOOP_VINFO_NITERS_KNOWN_P (main_loop))
|
||
{
|
||
unsigned HOST_WIDE_INT niters
|
||
= LOOP_VINFO_INT_NITERS (main_loop) % main_vf;
|
||
HOST_WIDE_INT other_likely_vf
|
||
= estimated_poly_value (other_vf, POLY_VALUE_LIKELY);
|
||
HOST_WIDE_INT this_likely_vf
|
||
= estimated_poly_value (this_vf, POLY_VALUE_LIKELY);
|
||
|
||
/* If the epilogue is using partial vectors we account for the
|
||
partial iteration here too. */
|
||
other_factor = niters / other_likely_vf;
|
||
if (LOOP_VINFO_USING_PARTIAL_VECTORS_P (other_loop_vinfo)
|
||
&& niters % other_likely_vf != 0)
|
||
other_factor++;
|
||
|
||
this_factor = niters / this_likely_vf;
|
||
if (LOOP_VINFO_USING_PARTIAL_VECTORS_P (this_loop_vinfo)
|
||
&& niters % this_likely_vf != 0)
|
||
this_factor++;
|
||
}
|
||
else
|
||
{
|
||
unsigned HOST_WIDE_INT main_vf_max
|
||
= estimated_poly_value (main_poly_vf, POLY_VALUE_MAX);
|
||
unsigned HOST_WIDE_INT other_vf_max
|
||
= estimated_poly_value (other_vf, POLY_VALUE_MAX);
|
||
unsigned HOST_WIDE_INT this_vf_max
|
||
= estimated_poly_value (this_vf, POLY_VALUE_MAX);
|
||
|
||
other_factor = CEIL (main_vf_max, other_vf_max);
|
||
this_factor = CEIL (main_vf_max, this_vf_max);
|
||
|
||
/* If the loop is not using partial vectors then it will iterate one
|
||
time less than one that does. It is safe to subtract one here,
|
||
because the main loop's vf is always at least 2x bigger than that
|
||
of an epilogue. */
|
||
if (!LOOP_VINFO_USING_PARTIAL_VECTORS_P (other_loop_vinfo))
|
||
other_factor -= 1;
|
||
if (!LOOP_VINFO_USING_PARTIAL_VECTORS_P (this_loop_vinfo))
|
||
this_factor -= 1;
|
||
}
|
||
|
||
/* Compute the costs by multiplying the inside costs with the factor and
|
||
add the outside costs for a more complete picture. The factor is the
|
||
amount of times we are expecting to iterate this epilogue. */
|
||
other_cost = other->body_cost () * other_factor;
|
||
this_cost = this->body_cost () * this_factor;
|
||
other_cost += other->outside_cost ();
|
||
this_cost += this->outside_cost ();
|
||
return this_cost < other_cost;
|
||
}
|
||
|
||
/* A <=>-style subroutine of better_main_loop_than_p. Check whether we can
|
||
determine the return value of better_main_loop_than_p by comparing the
|
||
inside (loop body) costs of THIS and OTHER. Return:
|
||
|
||
* -1 if better_main_loop_than_p should return true.
|
||
* 1 if better_main_loop_than_p should return false.
|
||
* 0 if we can't decide. */
|
||
|
||
int
|
||
vector_costs::compare_inside_loop_cost (const vector_costs *other) const
|
||
{
|
||
loop_vec_info this_loop_vinfo = as_a<loop_vec_info> (this->m_vinfo);
|
||
loop_vec_info other_loop_vinfo = as_a<loop_vec_info> (other->m_vinfo);
|
||
|
||
struct loop *loop = LOOP_VINFO_LOOP (this_loop_vinfo);
|
||
gcc_assert (LOOP_VINFO_LOOP (other_loop_vinfo) == loop);
|
||
|
||
poly_int64 this_vf = LOOP_VINFO_VECT_FACTOR (this_loop_vinfo);
|
||
poly_int64 other_vf = LOOP_VINFO_VECT_FACTOR (other_loop_vinfo);
|
||
|
||
/* Limit the VFs to what is likely to be the maximum number of iterations,
|
||
to handle cases in which at least one loop_vinfo is fully-masked. */
|
||
HOST_WIDE_INT estimated_max_niter = likely_max_stmt_executions_int (loop);
|
||
if (estimated_max_niter != -1)
|
||
{
|
||
if (known_le (estimated_max_niter, this_vf))
|
||
this_vf = estimated_max_niter;
|
||
if (known_le (estimated_max_niter, other_vf))
|
||
other_vf = estimated_max_niter;
|
||
}
|
||
|
||
/* Check whether the (fractional) cost per scalar iteration is lower or
|
||
higher: this_inside_cost / this_vf vs. other_inside_cost / other_vf. */
|
||
poly_int64 rel_this = this_loop_vinfo->vector_costs->body_cost () * other_vf;
|
||
poly_int64 rel_other
|
||
= other_loop_vinfo->vector_costs->body_cost () * this_vf;
|
||
|
||
HOST_WIDE_INT est_rel_this_min
|
||
= estimated_poly_value (rel_this, POLY_VALUE_MIN);
|
||
HOST_WIDE_INT est_rel_this_max
|
||
= estimated_poly_value (rel_this, POLY_VALUE_MAX);
|
||
|
||
HOST_WIDE_INT est_rel_other_min
|
||
= estimated_poly_value (rel_other, POLY_VALUE_MIN);
|
||
HOST_WIDE_INT est_rel_other_max
|
||
= estimated_poly_value (rel_other, POLY_VALUE_MAX);
|
||
|
||
/* Check first if we can make out an unambigous total order from the minimum
|
||
and maximum estimates. */
|
||
if (est_rel_this_min < est_rel_other_min
|
||
&& est_rel_this_max < est_rel_other_max)
|
||
return -1;
|
||
|
||
if (est_rel_other_min < est_rel_this_min
|
||
&& est_rel_other_max < est_rel_this_max)
|
||
return 1;
|
||
|
||
/* When other_loop_vinfo uses a variable vectorization factor,
|
||
we know that it has a lower cost for at least one runtime VF.
|
||
However, we don't know how likely that VF is.
|
||
|
||
One option would be to compare the costs for the estimated VFs.
|
||
The problem is that that can put too much pressure on the cost
|
||
model. E.g. if the estimated VF is also the lowest possible VF,
|
||
and if other_loop_vinfo is 1 unit worse than this_loop_vinfo
|
||
for the estimated VF, we'd then choose this_loop_vinfo even
|
||
though (a) this_loop_vinfo might not actually be better than
|
||
other_loop_vinfo for that VF and (b) it would be significantly
|
||
worse at larger VFs.
|
||
|
||
Here we go for a hacky compromise: pick this_loop_vinfo if it is
|
||
no more expensive than other_loop_vinfo even after doubling the
|
||
estimated other_loop_vinfo VF. For all but trivial loops, this
|
||
ensures that we only pick this_loop_vinfo if it is significantly
|
||
better than other_loop_vinfo at the estimated VF. */
|
||
if (est_rel_other_min != est_rel_this_min
|
||
|| est_rel_other_max != est_rel_this_max)
|
||
{
|
||
HOST_WIDE_INT est_rel_this_likely
|
||
= estimated_poly_value (rel_this, POLY_VALUE_LIKELY);
|
||
HOST_WIDE_INT est_rel_other_likely
|
||
= estimated_poly_value (rel_other, POLY_VALUE_LIKELY);
|
||
|
||
return est_rel_this_likely * 2 <= est_rel_other_likely ? -1 : 1;
|
||
}
|
||
|
||
return 0;
|
||
}
|
||
|
||
/* A <=>-style subroutine of better_main_loop_than_p, used when there is
|
||
nothing to choose between the inside (loop body) costs of THIS and OTHER.
|
||
Check whether we can determine the return value of better_main_loop_than_p
|
||
by comparing the outside (prologue and epilogue) costs of THIS and OTHER.
|
||
Return:
|
||
|
||
* -1 if better_main_loop_than_p should return true.
|
||
* 1 if better_main_loop_than_p should return false.
|
||
* 0 if we can't decide. */
|
||
|
||
int
|
||
vector_costs::compare_outside_loop_cost (const vector_costs *other) const
|
||
{
|
||
auto this_outside_cost = this->outside_cost ();
|
||
auto other_outside_cost = other->outside_cost ();
|
||
if (this_outside_cost != other_outside_cost)
|
||
return this_outside_cost < other_outside_cost ? -1 : 1;
|
||
|
||
return 0;
|
||
}
|