mirror of
https://github.com/autc04/Retro68.git
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3217 lines
89 KiB
C
3217 lines
89 KiB
C
/* Branch prediction routines for the GNU compiler.
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Copyright (C) 2000-2015 Free Software Foundation, Inc.
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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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/* References:
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[1] "Branch Prediction for Free"
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Ball and Larus; PLDI '93.
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[2] "Static Branch Frequency and Program Profile Analysis"
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Wu and Larus; MICRO-27.
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[3] "Corpus-based Static Branch Prediction"
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Calder, Grunwald, Lindsay, Martin, Mozer, and Zorn; PLDI '95. */
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#include "config.h"
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#include "system.h"
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#include "coretypes.h"
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#include "tm.h"
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#include "hash-set.h"
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#include "machmode.h"
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#include "vec.h"
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#include "double-int.h"
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#include "input.h"
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#include "alias.h"
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#include "symtab.h"
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#include "wide-int.h"
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#include "inchash.h"
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#include "tree.h"
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#include "fold-const.h"
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#include "calls.h"
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#include "rtl.h"
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#include "tm_p.h"
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#include "hard-reg-set.h"
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#include "predict.h"
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#include "function.h"
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#include "dominance.h"
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#include "cfg.h"
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#include "cfganal.h"
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#include "basic-block.h"
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#include "insn-config.h"
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#include "regs.h"
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#include "flags.h"
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#include "profile.h"
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#include "except.h"
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#include "diagnostic-core.h"
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#include "recog.h"
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#include "hashtab.h"
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#include "statistics.h"
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#include "real.h"
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#include "fixed-value.h"
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#include "expmed.h"
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#include "dojump.h"
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#include "explow.h"
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#include "emit-rtl.h"
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#include "varasm.h"
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#include "stmt.h"
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#include "expr.h"
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#include "coverage.h"
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#include "sreal.h"
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#include "params.h"
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#include "target.h"
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#include "cfgloop.h"
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#include "hash-map.h"
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#include "tree-ssa-alias.h"
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#include "internal-fn.h"
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#include "gimple-expr.h"
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#include "is-a.h"
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#include "gimple.h"
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#include "gimple-iterator.h"
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#include "gimple-ssa.h"
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#include "plugin-api.h"
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#include "ipa-ref.h"
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#include "cgraph.h"
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#include "tree-cfg.h"
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#include "tree-phinodes.h"
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#include "ssa-iterators.h"
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#include "tree-ssa-loop-niter.h"
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#include "tree-ssa-loop.h"
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#include "tree-pass.h"
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#include "tree-scalar-evolution.h"
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/* real constants: 0, 1, 1-1/REG_BR_PROB_BASE, REG_BR_PROB_BASE,
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1/REG_BR_PROB_BASE, 0.5, BB_FREQ_MAX. */
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static sreal real_almost_one, real_br_prob_base,
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real_inv_br_prob_base, real_one_half, real_bb_freq_max;
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static void combine_predictions_for_insn (rtx_insn *, basic_block);
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static void dump_prediction (FILE *, enum br_predictor, int, basic_block, int);
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static void predict_paths_leading_to (basic_block, enum br_predictor, enum prediction);
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static void predict_paths_leading_to_edge (edge, enum br_predictor, enum prediction);
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static bool can_predict_insn_p (const rtx_insn *);
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/* Information we hold about each branch predictor.
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Filled using information from predict.def. */
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struct predictor_info
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{
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const char *const name; /* Name used in the debugging dumps. */
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const int hitrate; /* Expected hitrate used by
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predict_insn_def call. */
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const int flags;
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};
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/* Use given predictor without Dempster-Shaffer theory if it matches
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using first_match heuristics. */
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#define PRED_FLAG_FIRST_MATCH 1
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/* Recompute hitrate in percent to our representation. */
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#define HITRATE(VAL) ((int) ((VAL) * REG_BR_PROB_BASE + 50) / 100)
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#define DEF_PREDICTOR(ENUM, NAME, HITRATE, FLAGS) {NAME, HITRATE, FLAGS},
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static const struct predictor_info predictor_info[]= {
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#include "predict.def"
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/* Upper bound on predictors. */
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{NULL, 0, 0}
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};
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#undef DEF_PREDICTOR
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/* Return TRUE if frequency FREQ is considered to be hot. */
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static inline bool
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maybe_hot_frequency_p (struct function *fun, int freq)
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{
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struct cgraph_node *node = cgraph_node::get (fun->decl);
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if (!profile_info
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|| !opt_for_fn (fun->decl, flag_branch_probabilities))
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{
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if (node->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED)
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return false;
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if (node->frequency == NODE_FREQUENCY_HOT)
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return true;
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}
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if (profile_status_for_fn (fun) == PROFILE_ABSENT)
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return true;
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if (node->frequency == NODE_FREQUENCY_EXECUTED_ONCE
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&& freq < (ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency * 2 / 3))
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return false;
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if (PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION) == 0)
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return false;
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if (freq < (ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency
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/ PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION)))
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return false;
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return true;
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}
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static gcov_type min_count = -1;
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/* Determine the threshold for hot BB counts. */
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gcov_type
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get_hot_bb_threshold ()
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{
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gcov_working_set_t *ws;
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if (min_count == -1)
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{
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ws = find_working_set (PARAM_VALUE (HOT_BB_COUNT_WS_PERMILLE));
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gcc_assert (ws);
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min_count = ws->min_counter;
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}
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return min_count;
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}
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/* Set the threshold for hot BB counts. */
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void
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set_hot_bb_threshold (gcov_type min)
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{
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min_count = min;
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}
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/* Return TRUE if frequency FREQ is considered to be hot. */
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bool
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maybe_hot_count_p (struct function *fun, gcov_type count)
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{
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if (fun && profile_status_for_fn (fun) != PROFILE_READ)
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return true;
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/* Code executed at most once is not hot. */
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if (profile_info->runs >= count)
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return false;
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return (count >= get_hot_bb_threshold ());
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}
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/* Return true in case BB can be CPU intensive and should be optimized
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for maximal performance. */
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bool
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maybe_hot_bb_p (struct function *fun, const_basic_block bb)
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{
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gcc_checking_assert (fun);
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if (profile_status_for_fn (fun) == PROFILE_READ)
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return maybe_hot_count_p (fun, bb->count);
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return maybe_hot_frequency_p (fun, bb->frequency);
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}
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/* Return true in case BB can be CPU intensive and should be optimized
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for maximal performance. */
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bool
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maybe_hot_edge_p (edge e)
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{
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if (profile_status_for_fn (cfun) == PROFILE_READ)
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return maybe_hot_count_p (cfun, e->count);
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return maybe_hot_frequency_p (cfun, EDGE_FREQUENCY (e));
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}
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/* Return true if profile COUNT and FREQUENCY, or function FUN static
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node frequency reflects never being executed. */
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static bool
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probably_never_executed (struct function *fun,
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gcov_type count, int frequency)
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{
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gcc_checking_assert (fun);
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if (profile_status_for_fn (fun) == PROFILE_READ)
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{
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int unlikely_count_fraction = PARAM_VALUE (UNLIKELY_BB_COUNT_FRACTION);
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if (count * unlikely_count_fraction >= profile_info->runs)
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return false;
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if (!frequency)
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return true;
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if (!ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency)
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return false;
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if (ENTRY_BLOCK_PTR_FOR_FN (fun)->count)
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{
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gcov_type computed_count;
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/* Check for possibility of overflow, in which case entry bb count
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is large enough to do the division first without losing much
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precision. */
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if (ENTRY_BLOCK_PTR_FOR_FN (fun)->count < REG_BR_PROB_BASE *
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REG_BR_PROB_BASE)
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{
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gcov_type scaled_count
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= frequency * ENTRY_BLOCK_PTR_FOR_FN (fun)->count *
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unlikely_count_fraction;
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computed_count = RDIV (scaled_count,
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ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency);
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}
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else
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{
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computed_count = RDIV (ENTRY_BLOCK_PTR_FOR_FN (fun)->count,
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ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency);
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computed_count *= frequency * unlikely_count_fraction;
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}
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if (computed_count >= profile_info->runs)
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return false;
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}
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return true;
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}
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if ((!profile_info || !(opt_for_fn (fun->decl, flag_branch_probabilities)))
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&& (cgraph_node::get (fun->decl)->frequency
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== NODE_FREQUENCY_UNLIKELY_EXECUTED))
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return true;
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return false;
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}
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/* Return true in case BB is probably never executed. */
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bool
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probably_never_executed_bb_p (struct function *fun, const_basic_block bb)
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{
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return probably_never_executed (fun, bb->count, bb->frequency);
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}
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/* Return true in case edge E is probably never executed. */
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bool
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probably_never_executed_edge_p (struct function *fun, edge e)
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{
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return probably_never_executed (fun, e->count, EDGE_FREQUENCY (e));
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}
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/* Return true when current function should always be optimized for size. */
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bool
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optimize_function_for_size_p (struct function *fun)
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{
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if (!fun || !fun->decl)
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return optimize_size;
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cgraph_node *n = cgraph_node::get (fun->decl);
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return n && n->optimize_for_size_p ();
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}
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/* Return true when current function should always be optimized for speed. */
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bool
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optimize_function_for_speed_p (struct function *fun)
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{
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return !optimize_function_for_size_p (fun);
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}
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/* Return TRUE when BB should be optimized for size. */
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bool
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optimize_bb_for_size_p (const_basic_block bb)
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{
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return (optimize_function_for_size_p (cfun)
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|| (bb && !maybe_hot_bb_p (cfun, bb)));
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}
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/* Return TRUE when BB should be optimized for speed. */
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bool
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optimize_bb_for_speed_p (const_basic_block bb)
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{
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return !optimize_bb_for_size_p (bb);
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}
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/* Return TRUE when BB should be optimized for size. */
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bool
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optimize_edge_for_size_p (edge e)
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{
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return optimize_function_for_size_p (cfun) || !maybe_hot_edge_p (e);
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}
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/* Return TRUE when BB should be optimized for speed. */
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bool
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optimize_edge_for_speed_p (edge e)
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{
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return !optimize_edge_for_size_p (e);
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}
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/* Return TRUE when BB should be optimized for size. */
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bool
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optimize_insn_for_size_p (void)
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{
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return optimize_function_for_size_p (cfun) || !crtl->maybe_hot_insn_p;
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}
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/* Return TRUE when BB should be optimized for speed. */
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bool
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optimize_insn_for_speed_p (void)
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{
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return !optimize_insn_for_size_p ();
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}
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/* Return TRUE when LOOP should be optimized for size. */
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bool
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optimize_loop_for_size_p (struct loop *loop)
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{
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return optimize_bb_for_size_p (loop->header);
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}
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/* Return TRUE when LOOP should be optimized for speed. */
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bool
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optimize_loop_for_speed_p (struct loop *loop)
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{
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return optimize_bb_for_speed_p (loop->header);
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}
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/* Return TRUE when LOOP nest should be optimized for speed. */
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bool
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optimize_loop_nest_for_speed_p (struct loop *loop)
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{
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struct loop *l = loop;
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if (optimize_loop_for_speed_p (loop))
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return true;
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l = loop->inner;
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while (l && l != loop)
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{
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if (optimize_loop_for_speed_p (l))
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return true;
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if (l->inner)
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l = l->inner;
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else if (l->next)
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l = l->next;
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else
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{
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while (l != loop && !l->next)
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l = loop_outer (l);
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if (l != loop)
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l = l->next;
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}
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}
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return false;
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}
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/* Return TRUE when LOOP nest should be optimized for size. */
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bool
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optimize_loop_nest_for_size_p (struct loop *loop)
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{
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return !optimize_loop_nest_for_speed_p (loop);
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}
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/* Return true when edge E is likely to be well predictable by branch
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predictor. */
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bool
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predictable_edge_p (edge e)
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{
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if (profile_status_for_fn (cfun) == PROFILE_ABSENT)
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return false;
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if ((e->probability
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<= PARAM_VALUE (PARAM_PREDICTABLE_BRANCH_OUTCOME) * REG_BR_PROB_BASE / 100)
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|| (REG_BR_PROB_BASE - e->probability
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<= PARAM_VALUE (PARAM_PREDICTABLE_BRANCH_OUTCOME) * REG_BR_PROB_BASE / 100))
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return true;
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return false;
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}
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/* Set RTL expansion for BB profile. */
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void
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rtl_profile_for_bb (basic_block bb)
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{
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crtl->maybe_hot_insn_p = maybe_hot_bb_p (cfun, bb);
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}
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/* Set RTL expansion for edge profile. */
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void
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rtl_profile_for_edge (edge e)
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{
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crtl->maybe_hot_insn_p = maybe_hot_edge_p (e);
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}
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/* Set RTL expansion to default mode (i.e. when profile info is not known). */
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void
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default_rtl_profile (void)
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{
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crtl->maybe_hot_insn_p = true;
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}
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/* Return true if the one of outgoing edges is already predicted by
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PREDICTOR. */
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bool
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rtl_predicted_by_p (const_basic_block bb, enum br_predictor predictor)
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{
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rtx note;
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if (!INSN_P (BB_END (bb)))
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return false;
|
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for (note = REG_NOTES (BB_END (bb)); note; note = XEXP (note, 1))
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if (REG_NOTE_KIND (note) == REG_BR_PRED
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&& INTVAL (XEXP (XEXP (note, 0), 0)) == (int)predictor)
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return true;
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return false;
|
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}
|
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|
||
/* Structure representing predictions in tree level. */
|
||
|
||
struct edge_prediction {
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||
struct edge_prediction *ep_next;
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||
edge ep_edge;
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enum br_predictor ep_predictor;
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int ep_probability;
|
||
};
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|
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/* This map contains for a basic block the list of predictions for the
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||
outgoing edges. */
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||
|
||
static hash_map<const_basic_block, edge_prediction *> *bb_predictions;
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||
|
||
/* Return true if the one of outgoing edges is already predicted by
|
||
PREDICTOR. */
|
||
|
||
bool
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||
gimple_predicted_by_p (const_basic_block bb, enum br_predictor predictor)
|
||
{
|
||
struct edge_prediction *i;
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||
edge_prediction **preds = bb_predictions->get (bb);
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||
|
||
if (!preds)
|
||
return false;
|
||
|
||
for (i = *preds; i; i = i->ep_next)
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||
if (i->ep_predictor == predictor)
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||
return true;
|
||
return false;
|
||
}
|
||
|
||
/* Return true when the probability of edge is reliable.
|
||
|
||
The profile guessing code is good at predicting branch outcome (ie.
|
||
taken/not taken), that is predicted right slightly over 75% of time.
|
||
It is however notoriously poor on predicting the probability itself.
|
||
In general the profile appear a lot flatter (with probabilities closer
|
||
to 50%) than the reality so it is bad idea to use it to drive optimization
|
||
such as those disabling dynamic branch prediction for well predictable
|
||
branches.
|
||
|
||
There are two exceptions - edges leading to noreturn edges and edges
|
||
predicted by number of iterations heuristics are predicted well. This macro
|
||
should be able to distinguish those, but at the moment it simply check for
|
||
noreturn heuristic that is only one giving probability over 99% or bellow
|
||
1%. In future we might want to propagate reliability information across the
|
||
CFG if we find this information useful on multiple places. */
|
||
static bool
|
||
probability_reliable_p (int prob)
|
||
{
|
||
return (profile_status_for_fn (cfun) == PROFILE_READ
|
||
|| (profile_status_for_fn (cfun) == PROFILE_GUESSED
|
||
&& (prob <= HITRATE (1) || prob >= HITRATE (99))));
|
||
}
|
||
|
||
/* Same predicate as above, working on edges. */
|
||
bool
|
||
edge_probability_reliable_p (const_edge e)
|
||
{
|
||
return probability_reliable_p (e->probability);
|
||
}
|
||
|
||
/* Same predicate as edge_probability_reliable_p, working on notes. */
|
||
bool
|
||
br_prob_note_reliable_p (const_rtx note)
|
||
{
|
||
gcc_assert (REG_NOTE_KIND (note) == REG_BR_PROB);
|
||
return probability_reliable_p (XINT (note, 0));
|
||
}
|
||
|
||
static void
|
||
predict_insn (rtx_insn *insn, enum br_predictor predictor, int probability)
|
||
{
|
||
gcc_assert (any_condjump_p (insn));
|
||
if (!flag_guess_branch_prob)
|
||
return;
|
||
|
||
add_reg_note (insn, REG_BR_PRED,
|
||
gen_rtx_CONCAT (VOIDmode,
|
||
GEN_INT ((int) predictor),
|
||
GEN_INT ((int) probability)));
|
||
}
|
||
|
||
/* Predict insn by given predictor. */
|
||
|
||
void
|
||
predict_insn_def (rtx_insn *insn, enum br_predictor predictor,
|
||
enum prediction taken)
|
||
{
|
||
int probability = predictor_info[(int) predictor].hitrate;
|
||
|
||
if (taken != TAKEN)
|
||
probability = REG_BR_PROB_BASE - probability;
|
||
|
||
predict_insn (insn, predictor, probability);
|
||
}
|
||
|
||
/* Predict edge E with given probability if possible. */
|
||
|
||
void
|
||
rtl_predict_edge (edge e, enum br_predictor predictor, int probability)
|
||
{
|
||
rtx_insn *last_insn;
|
||
last_insn = BB_END (e->src);
|
||
|
||
/* We can store the branch prediction information only about
|
||
conditional jumps. */
|
||
if (!any_condjump_p (last_insn))
|
||
return;
|
||
|
||
/* We always store probability of branching. */
|
||
if (e->flags & EDGE_FALLTHRU)
|
||
probability = REG_BR_PROB_BASE - probability;
|
||
|
||
predict_insn (last_insn, predictor, probability);
|
||
}
|
||
|
||
/* Predict edge E with the given PROBABILITY. */
|
||
void
|
||
gimple_predict_edge (edge e, enum br_predictor predictor, int probability)
|
||
{
|
||
gcc_assert (profile_status_for_fn (cfun) != PROFILE_GUESSED);
|
||
if ((e->src != ENTRY_BLOCK_PTR_FOR_FN (cfun) && EDGE_COUNT (e->src->succs) >
|
||
1)
|
||
&& flag_guess_branch_prob && optimize)
|
||
{
|
||
struct edge_prediction *i = XNEW (struct edge_prediction);
|
||
edge_prediction *&preds = bb_predictions->get_or_insert (e->src);
|
||
|
||
i->ep_next = preds;
|
||
preds = i;
|
||
i->ep_probability = probability;
|
||
i->ep_predictor = predictor;
|
||
i->ep_edge = e;
|
||
}
|
||
}
|
||
|
||
/* Remove all predictions on given basic block that are attached
|
||
to edge E. */
|
||
void
|
||
remove_predictions_associated_with_edge (edge e)
|
||
{
|
||
if (!bb_predictions)
|
||
return;
|
||
|
||
edge_prediction **preds = bb_predictions->get (e->src);
|
||
|
||
if (preds)
|
||
{
|
||
struct edge_prediction **prediction = preds;
|
||
struct edge_prediction *next;
|
||
|
||
while (*prediction)
|
||
{
|
||
if ((*prediction)->ep_edge == e)
|
||
{
|
||
next = (*prediction)->ep_next;
|
||
free (*prediction);
|
||
*prediction = next;
|
||
}
|
||
else
|
||
prediction = &((*prediction)->ep_next);
|
||
}
|
||
}
|
||
}
|
||
|
||
/* Clears the list of predictions stored for BB. */
|
||
|
||
static void
|
||
clear_bb_predictions (basic_block bb)
|
||
{
|
||
edge_prediction **preds = bb_predictions->get (bb);
|
||
struct edge_prediction *pred, *next;
|
||
|
||
if (!preds)
|
||
return;
|
||
|
||
for (pred = *preds; pred; pred = next)
|
||
{
|
||
next = pred->ep_next;
|
||
free (pred);
|
||
}
|
||
*preds = NULL;
|
||
}
|
||
|
||
/* Return true when we can store prediction on insn INSN.
|
||
At the moment we represent predictions only on conditional
|
||
jumps, not at computed jump or other complicated cases. */
|
||
static bool
|
||
can_predict_insn_p (const rtx_insn *insn)
|
||
{
|
||
return (JUMP_P (insn)
|
||
&& any_condjump_p (insn)
|
||
&& EDGE_COUNT (BLOCK_FOR_INSN (insn)->succs) >= 2);
|
||
}
|
||
|
||
/* Predict edge E by given predictor if possible. */
|
||
|
||
void
|
||
predict_edge_def (edge e, enum br_predictor predictor,
|
||
enum prediction taken)
|
||
{
|
||
int probability = predictor_info[(int) predictor].hitrate;
|
||
|
||
if (taken != TAKEN)
|
||
probability = REG_BR_PROB_BASE - probability;
|
||
|
||
predict_edge (e, predictor, probability);
|
||
}
|
||
|
||
/* Invert all branch predictions or probability notes in the INSN. This needs
|
||
to be done each time we invert the condition used by the jump. */
|
||
|
||
void
|
||
invert_br_probabilities (rtx insn)
|
||
{
|
||
rtx note;
|
||
|
||
for (note = REG_NOTES (insn); note; note = XEXP (note, 1))
|
||
if (REG_NOTE_KIND (note) == REG_BR_PROB)
|
||
XINT (note, 0) = REG_BR_PROB_BASE - XINT (note, 0);
|
||
else if (REG_NOTE_KIND (note) == REG_BR_PRED)
|
||
XEXP (XEXP (note, 0), 1)
|
||
= GEN_INT (REG_BR_PROB_BASE - INTVAL (XEXP (XEXP (note, 0), 1)));
|
||
}
|
||
|
||
/* Dump information about the branch prediction to the output file. */
|
||
|
||
static void
|
||
dump_prediction (FILE *file, enum br_predictor predictor, int probability,
|
||
basic_block bb, int used)
|
||
{
|
||
edge e;
|
||
edge_iterator ei;
|
||
|
||
if (!file)
|
||
return;
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
if (! (e->flags & EDGE_FALLTHRU))
|
||
break;
|
||
|
||
fprintf (file, " %s heuristics%s: %.1f%%",
|
||
predictor_info[predictor].name,
|
||
used ? "" : " (ignored)", probability * 100.0 / REG_BR_PROB_BASE);
|
||
|
||
if (bb->count)
|
||
{
|
||
fprintf (file, " exec %"PRId64, bb->count);
|
||
if (e)
|
||
{
|
||
fprintf (file, " hit %"PRId64, e->count);
|
||
fprintf (file, " (%.1f%%)", e->count * 100.0 / bb->count);
|
||
}
|
||
}
|
||
|
||
fprintf (file, "\n");
|
||
}
|
||
|
||
/* We can not predict the probabilities of outgoing edges of bb. Set them
|
||
evenly and hope for the best. */
|
||
static void
|
||
set_even_probabilities (basic_block bb)
|
||
{
|
||
int nedges = 0;
|
||
edge e;
|
||
edge_iterator ei;
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
if (!(e->flags & (EDGE_EH | EDGE_FAKE)))
|
||
nedges ++;
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
if (!(e->flags & (EDGE_EH | EDGE_FAKE)))
|
||
e->probability = (REG_BR_PROB_BASE + nedges / 2) / nedges;
|
||
else
|
||
e->probability = 0;
|
||
}
|
||
|
||
/* Combine all REG_BR_PRED notes into single probability and attach REG_BR_PROB
|
||
note if not already present. Remove now useless REG_BR_PRED notes. */
|
||
|
||
static void
|
||
combine_predictions_for_insn (rtx_insn *insn, basic_block bb)
|
||
{
|
||
rtx prob_note;
|
||
rtx *pnote;
|
||
rtx note;
|
||
int best_probability = PROB_EVEN;
|
||
enum br_predictor best_predictor = END_PREDICTORS;
|
||
int combined_probability = REG_BR_PROB_BASE / 2;
|
||
int d;
|
||
bool first_match = false;
|
||
bool found = false;
|
||
|
||
if (!can_predict_insn_p (insn))
|
||
{
|
||
set_even_probabilities (bb);
|
||
return;
|
||
}
|
||
|
||
prob_note = find_reg_note (insn, REG_BR_PROB, 0);
|
||
pnote = ®_NOTES (insn);
|
||
if (dump_file)
|
||
fprintf (dump_file, "Predictions for insn %i bb %i\n", INSN_UID (insn),
|
||
bb->index);
|
||
|
||
/* We implement "first match" heuristics and use probability guessed
|
||
by predictor with smallest index. */
|
||
for (note = REG_NOTES (insn); note; note = XEXP (note, 1))
|
||
if (REG_NOTE_KIND (note) == REG_BR_PRED)
|
||
{
|
||
enum br_predictor predictor = ((enum br_predictor)
|
||
INTVAL (XEXP (XEXP (note, 0), 0)));
|
||
int probability = INTVAL (XEXP (XEXP (note, 0), 1));
|
||
|
||
found = true;
|
||
if (best_predictor > predictor)
|
||
best_probability = probability, best_predictor = predictor;
|
||
|
||
d = (combined_probability * probability
|
||
+ (REG_BR_PROB_BASE - combined_probability)
|
||
* (REG_BR_PROB_BASE - probability));
|
||
|
||
/* Use FP math to avoid overflows of 32bit integers. */
|
||
if (d == 0)
|
||
/* If one probability is 0% and one 100%, avoid division by zero. */
|
||
combined_probability = REG_BR_PROB_BASE / 2;
|
||
else
|
||
combined_probability = (((double) combined_probability) * probability
|
||
* REG_BR_PROB_BASE / d + 0.5);
|
||
}
|
||
|
||
/* Decide which heuristic to use. In case we didn't match anything,
|
||
use no_prediction heuristic, in case we did match, use either
|
||
first match or Dempster-Shaffer theory depending on the flags. */
|
||
|
||
if (predictor_info [best_predictor].flags & PRED_FLAG_FIRST_MATCH)
|
||
first_match = true;
|
||
|
||
if (!found)
|
||
dump_prediction (dump_file, PRED_NO_PREDICTION,
|
||
combined_probability, bb, true);
|
||
else
|
||
{
|
||
dump_prediction (dump_file, PRED_DS_THEORY, combined_probability,
|
||
bb, !first_match);
|
||
dump_prediction (dump_file, PRED_FIRST_MATCH, best_probability,
|
||
bb, first_match);
|
||
}
|
||
|
||
if (first_match)
|
||
combined_probability = best_probability;
|
||
dump_prediction (dump_file, PRED_COMBINED, combined_probability, bb, true);
|
||
|
||
while (*pnote)
|
||
{
|
||
if (REG_NOTE_KIND (*pnote) == REG_BR_PRED)
|
||
{
|
||
enum br_predictor predictor = ((enum br_predictor)
|
||
INTVAL (XEXP (XEXP (*pnote, 0), 0)));
|
||
int probability = INTVAL (XEXP (XEXP (*pnote, 0), 1));
|
||
|
||
dump_prediction (dump_file, predictor, probability, bb,
|
||
!first_match || best_predictor == predictor);
|
||
*pnote = XEXP (*pnote, 1);
|
||
}
|
||
else
|
||
pnote = &XEXP (*pnote, 1);
|
||
}
|
||
|
||
if (!prob_note)
|
||
{
|
||
add_int_reg_note (insn, REG_BR_PROB, combined_probability);
|
||
|
||
/* Save the prediction into CFG in case we are seeing non-degenerated
|
||
conditional jump. */
|
||
if (!single_succ_p (bb))
|
||
{
|
||
BRANCH_EDGE (bb)->probability = combined_probability;
|
||
FALLTHRU_EDGE (bb)->probability
|
||
= REG_BR_PROB_BASE - combined_probability;
|
||
}
|
||
}
|
||
else if (!single_succ_p (bb))
|
||
{
|
||
int prob = XINT (prob_note, 0);
|
||
|
||
BRANCH_EDGE (bb)->probability = prob;
|
||
FALLTHRU_EDGE (bb)->probability = REG_BR_PROB_BASE - prob;
|
||
}
|
||
else
|
||
single_succ_edge (bb)->probability = REG_BR_PROB_BASE;
|
||
}
|
||
|
||
/* Combine predictions into single probability and store them into CFG.
|
||
Remove now useless prediction entries. */
|
||
|
||
static void
|
||
combine_predictions_for_bb (basic_block bb)
|
||
{
|
||
int best_probability = PROB_EVEN;
|
||
enum br_predictor best_predictor = END_PREDICTORS;
|
||
int combined_probability = REG_BR_PROB_BASE / 2;
|
||
int d;
|
||
bool first_match = false;
|
||
bool found = false;
|
||
struct edge_prediction *pred;
|
||
int nedges = 0;
|
||
edge e, first = NULL, second = NULL;
|
||
edge_iterator ei;
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
if (!(e->flags & (EDGE_EH | EDGE_FAKE)))
|
||
{
|
||
nedges ++;
|
||
if (first && !second)
|
||
second = e;
|
||
if (!first)
|
||
first = e;
|
||
}
|
||
|
||
/* When there is no successor or only one choice, prediction is easy.
|
||
|
||
We are lazy for now and predict only basic blocks with two outgoing
|
||
edges. It is possible to predict generic case too, but we have to
|
||
ignore first match heuristics and do more involved combining. Implement
|
||
this later. */
|
||
if (nedges != 2)
|
||
{
|
||
if (!bb->count)
|
||
set_even_probabilities (bb);
|
||
clear_bb_predictions (bb);
|
||
if (dump_file)
|
||
fprintf (dump_file, "%i edges in bb %i predicted to even probabilities\n",
|
||
nedges, bb->index);
|
||
return;
|
||
}
|
||
|
||
if (dump_file)
|
||
fprintf (dump_file, "Predictions for bb %i\n", bb->index);
|
||
|
||
edge_prediction **preds = bb_predictions->get (bb);
|
||
if (preds)
|
||
{
|
||
/* We implement "first match" heuristics and use probability guessed
|
||
by predictor with smallest index. */
|
||
for (pred = *preds; pred; pred = pred->ep_next)
|
||
{
|
||
enum br_predictor predictor = pred->ep_predictor;
|
||
int probability = pred->ep_probability;
|
||
|
||
if (pred->ep_edge != first)
|
||
probability = REG_BR_PROB_BASE - probability;
|
||
|
||
found = true;
|
||
/* First match heuristics would be widly confused if we predicted
|
||
both directions. */
|
||
if (best_predictor > predictor)
|
||
{
|
||
struct edge_prediction *pred2;
|
||
int prob = probability;
|
||
|
||
for (pred2 = (struct edge_prediction *) *preds;
|
||
pred2; pred2 = pred2->ep_next)
|
||
if (pred2 != pred && pred2->ep_predictor == pred->ep_predictor)
|
||
{
|
||
int probability2 = pred->ep_probability;
|
||
|
||
if (pred2->ep_edge != first)
|
||
probability2 = REG_BR_PROB_BASE - probability2;
|
||
|
||
if ((probability < REG_BR_PROB_BASE / 2) !=
|
||
(probability2 < REG_BR_PROB_BASE / 2))
|
||
break;
|
||
|
||
/* If the same predictor later gave better result, go for it! */
|
||
if ((probability >= REG_BR_PROB_BASE / 2 && (probability2 > probability))
|
||
|| (probability <= REG_BR_PROB_BASE / 2 && (probability2 < probability)))
|
||
prob = probability2;
|
||
}
|
||
if (!pred2)
|
||
best_probability = prob, best_predictor = predictor;
|
||
}
|
||
|
||
d = (combined_probability * probability
|
||
+ (REG_BR_PROB_BASE - combined_probability)
|
||
* (REG_BR_PROB_BASE - probability));
|
||
|
||
/* Use FP math to avoid overflows of 32bit integers. */
|
||
if (d == 0)
|
||
/* If one probability is 0% and one 100%, avoid division by zero. */
|
||
combined_probability = REG_BR_PROB_BASE / 2;
|
||
else
|
||
combined_probability = (((double) combined_probability)
|
||
* probability
|
||
* REG_BR_PROB_BASE / d + 0.5);
|
||
}
|
||
}
|
||
|
||
/* Decide which heuristic to use. In case we didn't match anything,
|
||
use no_prediction heuristic, in case we did match, use either
|
||
first match or Dempster-Shaffer theory depending on the flags. */
|
||
|
||
if (predictor_info [best_predictor].flags & PRED_FLAG_FIRST_MATCH)
|
||
first_match = true;
|
||
|
||
if (!found)
|
||
dump_prediction (dump_file, PRED_NO_PREDICTION, combined_probability, bb, true);
|
||
else
|
||
{
|
||
dump_prediction (dump_file, PRED_DS_THEORY, combined_probability, bb,
|
||
!first_match);
|
||
dump_prediction (dump_file, PRED_FIRST_MATCH, best_probability, bb,
|
||
first_match);
|
||
}
|
||
|
||
if (first_match)
|
||
combined_probability = best_probability;
|
||
dump_prediction (dump_file, PRED_COMBINED, combined_probability, bb, true);
|
||
|
||
if (preds)
|
||
{
|
||
for (pred = (struct edge_prediction *) *preds; pred; pred = pred->ep_next)
|
||
{
|
||
enum br_predictor predictor = pred->ep_predictor;
|
||
int probability = pred->ep_probability;
|
||
|
||
if (pred->ep_edge != EDGE_SUCC (bb, 0))
|
||
probability = REG_BR_PROB_BASE - probability;
|
||
dump_prediction (dump_file, predictor, probability, bb,
|
||
!first_match || best_predictor == predictor);
|
||
}
|
||
}
|
||
clear_bb_predictions (bb);
|
||
|
||
if (!bb->count)
|
||
{
|
||
first->probability = combined_probability;
|
||
second->probability = REG_BR_PROB_BASE - combined_probability;
|
||
}
|
||
}
|
||
|
||
/* Check if T1 and T2 satisfy the IV_COMPARE condition.
|
||
Return the SSA_NAME if the condition satisfies, NULL otherwise.
|
||
|
||
T1 and T2 should be one of the following cases:
|
||
1. T1 is SSA_NAME, T2 is NULL
|
||
2. T1 is SSA_NAME, T2 is INTEGER_CST between [-4, 4]
|
||
3. T2 is SSA_NAME, T1 is INTEGER_CST between [-4, 4] */
|
||
|
||
static tree
|
||
strips_small_constant (tree t1, tree t2)
|
||
{
|
||
tree ret = NULL;
|
||
int value = 0;
|
||
|
||
if (!t1)
|
||
return NULL;
|
||
else if (TREE_CODE (t1) == SSA_NAME)
|
||
ret = t1;
|
||
else if (tree_fits_shwi_p (t1))
|
||
value = tree_to_shwi (t1);
|
||
else
|
||
return NULL;
|
||
|
||
if (!t2)
|
||
return ret;
|
||
else if (tree_fits_shwi_p (t2))
|
||
value = tree_to_shwi (t2);
|
||
else if (TREE_CODE (t2) == SSA_NAME)
|
||
{
|
||
if (ret)
|
||
return NULL;
|
||
else
|
||
ret = t2;
|
||
}
|
||
|
||
if (value <= 4 && value >= -4)
|
||
return ret;
|
||
else
|
||
return NULL;
|
||
}
|
||
|
||
/* Return the SSA_NAME in T or T's operands.
|
||
Return NULL if SSA_NAME cannot be found. */
|
||
|
||
static tree
|
||
get_base_value (tree t)
|
||
{
|
||
if (TREE_CODE (t) == SSA_NAME)
|
||
return t;
|
||
|
||
if (!BINARY_CLASS_P (t))
|
||
return NULL;
|
||
|
||
switch (TREE_OPERAND_LENGTH (t))
|
||
{
|
||
case 1:
|
||
return strips_small_constant (TREE_OPERAND (t, 0), NULL);
|
||
case 2:
|
||
return strips_small_constant (TREE_OPERAND (t, 0),
|
||
TREE_OPERAND (t, 1));
|
||
default:
|
||
return NULL;
|
||
}
|
||
}
|
||
|
||
/* Check the compare STMT in LOOP. If it compares an induction
|
||
variable to a loop invariant, return true, and save
|
||
LOOP_INVARIANT, COMPARE_CODE and LOOP_STEP.
|
||
Otherwise return false and set LOOP_INVAIANT to NULL. */
|
||
|
||
static bool
|
||
is_comparison_with_loop_invariant_p (gcond *stmt, struct loop *loop,
|
||
tree *loop_invariant,
|
||
enum tree_code *compare_code,
|
||
tree *loop_step,
|
||
tree *loop_iv_base)
|
||
{
|
||
tree op0, op1, bound, base;
|
||
affine_iv iv0, iv1;
|
||
enum tree_code code;
|
||
tree step;
|
||
|
||
code = gimple_cond_code (stmt);
|
||
*loop_invariant = NULL;
|
||
|
||
switch (code)
|
||
{
|
||
case GT_EXPR:
|
||
case GE_EXPR:
|
||
case NE_EXPR:
|
||
case LT_EXPR:
|
||
case LE_EXPR:
|
||
case EQ_EXPR:
|
||
break;
|
||
|
||
default:
|
||
return false;
|
||
}
|
||
|
||
op0 = gimple_cond_lhs (stmt);
|
||
op1 = gimple_cond_rhs (stmt);
|
||
|
||
if ((TREE_CODE (op0) != SSA_NAME && TREE_CODE (op0) != INTEGER_CST)
|
||
|| (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op1) != INTEGER_CST))
|
||
return false;
|
||
if (!simple_iv (loop, loop_containing_stmt (stmt), op0, &iv0, true))
|
||
return false;
|
||
if (!simple_iv (loop, loop_containing_stmt (stmt), op1, &iv1, true))
|
||
return false;
|
||
if (TREE_CODE (iv0.step) != INTEGER_CST
|
||
|| TREE_CODE (iv1.step) != INTEGER_CST)
|
||
return false;
|
||
if ((integer_zerop (iv0.step) && integer_zerop (iv1.step))
|
||
|| (!integer_zerop (iv0.step) && !integer_zerop (iv1.step)))
|
||
return false;
|
||
|
||
if (integer_zerop (iv0.step))
|
||
{
|
||
if (code != NE_EXPR && code != EQ_EXPR)
|
||
code = invert_tree_comparison (code, false);
|
||
bound = iv0.base;
|
||
base = iv1.base;
|
||
if (tree_fits_shwi_p (iv1.step))
|
||
step = iv1.step;
|
||
else
|
||
return false;
|
||
}
|
||
else
|
||
{
|
||
bound = iv1.base;
|
||
base = iv0.base;
|
||
if (tree_fits_shwi_p (iv0.step))
|
||
step = iv0.step;
|
||
else
|
||
return false;
|
||
}
|
||
|
||
if (TREE_CODE (bound) != INTEGER_CST)
|
||
bound = get_base_value (bound);
|
||
if (!bound)
|
||
return false;
|
||
if (TREE_CODE (base) != INTEGER_CST)
|
||
base = get_base_value (base);
|
||
if (!base)
|
||
return false;
|
||
|
||
*loop_invariant = bound;
|
||
*compare_code = code;
|
||
*loop_step = step;
|
||
*loop_iv_base = base;
|
||
return true;
|
||
}
|
||
|
||
/* Compare two SSA_NAMEs: returns TRUE if T1 and T2 are value coherent. */
|
||
|
||
static bool
|
||
expr_coherent_p (tree t1, tree t2)
|
||
{
|
||
gimple stmt;
|
||
tree ssa_name_1 = NULL;
|
||
tree ssa_name_2 = NULL;
|
||
|
||
gcc_assert (TREE_CODE (t1) == SSA_NAME || TREE_CODE (t1) == INTEGER_CST);
|
||
gcc_assert (TREE_CODE (t2) == SSA_NAME || TREE_CODE (t2) == INTEGER_CST);
|
||
|
||
if (t1 == t2)
|
||
return true;
|
||
|
||
if (TREE_CODE (t1) == INTEGER_CST && TREE_CODE (t2) == INTEGER_CST)
|
||
return true;
|
||
if (TREE_CODE (t1) == INTEGER_CST || TREE_CODE (t2) == INTEGER_CST)
|
||
return false;
|
||
|
||
/* Check to see if t1 is expressed/defined with t2. */
|
||
stmt = SSA_NAME_DEF_STMT (t1);
|
||
gcc_assert (stmt != NULL);
|
||
if (is_gimple_assign (stmt))
|
||
{
|
||
ssa_name_1 = SINGLE_SSA_TREE_OPERAND (stmt, SSA_OP_USE);
|
||
if (ssa_name_1 && ssa_name_1 == t2)
|
||
return true;
|
||
}
|
||
|
||
/* Check to see if t2 is expressed/defined with t1. */
|
||
stmt = SSA_NAME_DEF_STMT (t2);
|
||
gcc_assert (stmt != NULL);
|
||
if (is_gimple_assign (stmt))
|
||
{
|
||
ssa_name_2 = SINGLE_SSA_TREE_OPERAND (stmt, SSA_OP_USE);
|
||
if (ssa_name_2 && ssa_name_2 == t1)
|
||
return true;
|
||
}
|
||
|
||
/* Compare if t1 and t2's def_stmts are identical. */
|
||
if (ssa_name_2 != NULL && ssa_name_1 == ssa_name_2)
|
||
return true;
|
||
else
|
||
return false;
|
||
}
|
||
|
||
/* Predict branch probability of BB when BB contains a branch that compares
|
||
an induction variable in LOOP with LOOP_IV_BASE_VAR to LOOP_BOUND_VAR. The
|
||
loop exit is compared using LOOP_BOUND_CODE, with step of LOOP_BOUND_STEP.
|
||
|
||
E.g.
|
||
for (int i = 0; i < bound; i++) {
|
||
if (i < bound - 2)
|
||
computation_1();
|
||
else
|
||
computation_2();
|
||
}
|
||
|
||
In this loop, we will predict the branch inside the loop to be taken. */
|
||
|
||
static void
|
||
predict_iv_comparison (struct loop *loop, basic_block bb,
|
||
tree loop_bound_var,
|
||
tree loop_iv_base_var,
|
||
enum tree_code loop_bound_code,
|
||
int loop_bound_step)
|
||
{
|
||
gimple stmt;
|
||
tree compare_var, compare_base;
|
||
enum tree_code compare_code;
|
||
tree compare_step_var;
|
||
edge then_edge;
|
||
edge_iterator ei;
|
||
|
||
if (predicted_by_p (bb, PRED_LOOP_ITERATIONS_GUESSED)
|
||
|| predicted_by_p (bb, PRED_LOOP_ITERATIONS)
|
||
|| predicted_by_p (bb, PRED_LOOP_EXIT))
|
||
return;
|
||
|
||
stmt = last_stmt (bb);
|
||
if (!stmt || gimple_code (stmt) != GIMPLE_COND)
|
||
return;
|
||
if (!is_comparison_with_loop_invariant_p (as_a <gcond *> (stmt),
|
||
loop, &compare_var,
|
||
&compare_code,
|
||
&compare_step_var,
|
||
&compare_base))
|
||
return;
|
||
|
||
/* Find the taken edge. */
|
||
FOR_EACH_EDGE (then_edge, ei, bb->succs)
|
||
if (then_edge->flags & EDGE_TRUE_VALUE)
|
||
break;
|
||
|
||
/* When comparing an IV to a loop invariant, NE is more likely to be
|
||
taken while EQ is more likely to be not-taken. */
|
||
if (compare_code == NE_EXPR)
|
||
{
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
return;
|
||
}
|
||
else if (compare_code == EQ_EXPR)
|
||
{
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN);
|
||
return;
|
||
}
|
||
|
||
if (!expr_coherent_p (loop_iv_base_var, compare_base))
|
||
return;
|
||
|
||
/* If loop bound, base and compare bound are all constants, we can
|
||
calculate the probability directly. */
|
||
if (tree_fits_shwi_p (loop_bound_var)
|
||
&& tree_fits_shwi_p (compare_var)
|
||
&& tree_fits_shwi_p (compare_base))
|
||
{
|
||
int probability;
|
||
bool overflow, overall_overflow = false;
|
||
widest_int compare_count, tem;
|
||
|
||
/* (loop_bound - base) / compare_step */
|
||
tem = wi::sub (wi::to_widest (loop_bound_var),
|
||
wi::to_widest (compare_base), SIGNED, &overflow);
|
||
overall_overflow |= overflow;
|
||
widest_int loop_count = wi::div_trunc (tem,
|
||
wi::to_widest (compare_step_var),
|
||
SIGNED, &overflow);
|
||
overall_overflow |= overflow;
|
||
|
||
if (!wi::neg_p (wi::to_widest (compare_step_var))
|
||
^ (compare_code == LT_EXPR || compare_code == LE_EXPR))
|
||
{
|
||
/* (loop_bound - compare_bound) / compare_step */
|
||
tem = wi::sub (wi::to_widest (loop_bound_var),
|
||
wi::to_widest (compare_var), SIGNED, &overflow);
|
||
overall_overflow |= overflow;
|
||
compare_count = wi::div_trunc (tem, wi::to_widest (compare_step_var),
|
||
SIGNED, &overflow);
|
||
overall_overflow |= overflow;
|
||
}
|
||
else
|
||
{
|
||
/* (compare_bound - base) / compare_step */
|
||
tem = wi::sub (wi::to_widest (compare_var),
|
||
wi::to_widest (compare_base), SIGNED, &overflow);
|
||
overall_overflow |= overflow;
|
||
compare_count = wi::div_trunc (tem, wi::to_widest (compare_step_var),
|
||
SIGNED, &overflow);
|
||
overall_overflow |= overflow;
|
||
}
|
||
if (compare_code == LE_EXPR || compare_code == GE_EXPR)
|
||
++compare_count;
|
||
if (loop_bound_code == LE_EXPR || loop_bound_code == GE_EXPR)
|
||
++loop_count;
|
||
if (wi::neg_p (compare_count))
|
||
compare_count = 0;
|
||
if (wi::neg_p (loop_count))
|
||
loop_count = 0;
|
||
if (loop_count == 0)
|
||
probability = 0;
|
||
else if (wi::cmps (compare_count, loop_count) == 1)
|
||
probability = REG_BR_PROB_BASE;
|
||
else
|
||
{
|
||
tem = compare_count * REG_BR_PROB_BASE;
|
||
tem = wi::udiv_trunc (tem, loop_count);
|
||
probability = tem.to_uhwi ();
|
||
}
|
||
|
||
if (!overall_overflow)
|
||
predict_edge (then_edge, PRED_LOOP_IV_COMPARE, probability);
|
||
|
||
return;
|
||
}
|
||
|
||
if (expr_coherent_p (loop_bound_var, compare_var))
|
||
{
|
||
if ((loop_bound_code == LT_EXPR || loop_bound_code == LE_EXPR)
|
||
&& (compare_code == LT_EXPR || compare_code == LE_EXPR))
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
else if ((loop_bound_code == GT_EXPR || loop_bound_code == GE_EXPR)
|
||
&& (compare_code == GT_EXPR || compare_code == GE_EXPR))
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
else if (loop_bound_code == NE_EXPR)
|
||
{
|
||
/* If the loop backedge condition is "(i != bound)", we do
|
||
the comparison based on the step of IV:
|
||
* step < 0 : backedge condition is like (i > bound)
|
||
* step > 0 : backedge condition is like (i < bound) */
|
||
gcc_assert (loop_bound_step != 0);
|
||
if (loop_bound_step > 0
|
||
&& (compare_code == LT_EXPR
|
||
|| compare_code == LE_EXPR))
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
else if (loop_bound_step < 0
|
||
&& (compare_code == GT_EXPR
|
||
|| compare_code == GE_EXPR))
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
else
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN);
|
||
}
|
||
else
|
||
/* The branch is predicted not-taken if loop_bound_code is
|
||
opposite with compare_code. */
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN);
|
||
}
|
||
else if (expr_coherent_p (loop_iv_base_var, compare_var))
|
||
{
|
||
/* For cases like:
|
||
for (i = s; i < h; i++)
|
||
if (i > s + 2) ....
|
||
The branch should be predicted taken. */
|
||
if (loop_bound_step > 0
|
||
&& (compare_code == GT_EXPR || compare_code == GE_EXPR))
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
else if (loop_bound_step < 0
|
||
&& (compare_code == LT_EXPR || compare_code == LE_EXPR))
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN);
|
||
else
|
||
predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN);
|
||
}
|
||
}
|
||
|
||
/* Predict for extra loop exits that will lead to EXIT_EDGE. The extra loop
|
||
exits are resulted from short-circuit conditions that will generate an
|
||
if_tmp. E.g.:
|
||
|
||
if (foo() || global > 10)
|
||
break;
|
||
|
||
This will be translated into:
|
||
|
||
BB3:
|
||
loop header...
|
||
BB4:
|
||
if foo() goto BB6 else goto BB5
|
||
BB5:
|
||
if global > 10 goto BB6 else goto BB7
|
||
BB6:
|
||
goto BB7
|
||
BB7:
|
||
iftmp = (PHI 0(BB5), 1(BB6))
|
||
if iftmp == 1 goto BB8 else goto BB3
|
||
BB8:
|
||
outside of the loop...
|
||
|
||
The edge BB7->BB8 is loop exit because BB8 is outside of the loop.
|
||
From the dataflow, we can infer that BB4->BB6 and BB5->BB6 are also loop
|
||
exits. This function takes BB7->BB8 as input, and finds out the extra loop
|
||
exits to predict them using PRED_LOOP_EXIT. */
|
||
|
||
static void
|
||
predict_extra_loop_exits (edge exit_edge)
|
||
{
|
||
unsigned i;
|
||
bool check_value_one;
|
||
gimple lhs_def_stmt;
|
||
gphi *phi_stmt;
|
||
tree cmp_rhs, cmp_lhs;
|
||
gimple last;
|
||
gcond *cmp_stmt;
|
||
|
||
last = last_stmt (exit_edge->src);
|
||
if (!last)
|
||
return;
|
||
cmp_stmt = dyn_cast <gcond *> (last);
|
||
if (!cmp_stmt)
|
||
return;
|
||
|
||
cmp_rhs = gimple_cond_rhs (cmp_stmt);
|
||
cmp_lhs = gimple_cond_lhs (cmp_stmt);
|
||
if (!TREE_CONSTANT (cmp_rhs)
|
||
|| !(integer_zerop (cmp_rhs) || integer_onep (cmp_rhs)))
|
||
return;
|
||
if (TREE_CODE (cmp_lhs) != SSA_NAME)
|
||
return;
|
||
|
||
/* If check_value_one is true, only the phi_args with value '1' will lead
|
||
to loop exit. Otherwise, only the phi_args with value '0' will lead to
|
||
loop exit. */
|
||
check_value_one = (((integer_onep (cmp_rhs))
|
||
^ (gimple_cond_code (cmp_stmt) == EQ_EXPR))
|
||
^ ((exit_edge->flags & EDGE_TRUE_VALUE) != 0));
|
||
|
||
lhs_def_stmt = SSA_NAME_DEF_STMT (cmp_lhs);
|
||
if (!lhs_def_stmt)
|
||
return;
|
||
|
||
phi_stmt = dyn_cast <gphi *> (lhs_def_stmt);
|
||
if (!phi_stmt)
|
||
return;
|
||
|
||
for (i = 0; i < gimple_phi_num_args (phi_stmt); i++)
|
||
{
|
||
edge e1;
|
||
edge_iterator ei;
|
||
tree val = gimple_phi_arg_def (phi_stmt, i);
|
||
edge e = gimple_phi_arg_edge (phi_stmt, i);
|
||
|
||
if (!TREE_CONSTANT (val) || !(integer_zerop (val) || integer_onep (val)))
|
||
continue;
|
||
if ((check_value_one ^ integer_onep (val)) == 1)
|
||
continue;
|
||
if (EDGE_COUNT (e->src->succs) != 1)
|
||
{
|
||
predict_paths_leading_to_edge (e, PRED_LOOP_EXIT, NOT_TAKEN);
|
||
continue;
|
||
}
|
||
|
||
FOR_EACH_EDGE (e1, ei, e->src->preds)
|
||
predict_paths_leading_to_edge (e1, PRED_LOOP_EXIT, NOT_TAKEN);
|
||
}
|
||
}
|
||
|
||
/* Predict edge probabilities by exploiting loop structure. */
|
||
|
||
static void
|
||
predict_loops (void)
|
||
{
|
||
struct loop *loop;
|
||
|
||
/* Try to predict out blocks in a loop that are not part of a
|
||
natural loop. */
|
||
FOR_EACH_LOOP (loop, 0)
|
||
{
|
||
basic_block bb, *bbs;
|
||
unsigned j, n_exits;
|
||
vec<edge> exits;
|
||
struct tree_niter_desc niter_desc;
|
||
edge ex;
|
||
struct nb_iter_bound *nb_iter;
|
||
enum tree_code loop_bound_code = ERROR_MARK;
|
||
tree loop_bound_step = NULL;
|
||
tree loop_bound_var = NULL;
|
||
tree loop_iv_base = NULL;
|
||
gcond *stmt = NULL;
|
||
|
||
exits = get_loop_exit_edges (loop);
|
||
n_exits = exits.length ();
|
||
if (!n_exits)
|
||
{
|
||
exits.release ();
|
||
continue;
|
||
}
|
||
|
||
FOR_EACH_VEC_ELT (exits, j, ex)
|
||
{
|
||
tree niter = NULL;
|
||
HOST_WIDE_INT nitercst;
|
||
int max = PARAM_VALUE (PARAM_MAX_PREDICTED_ITERATIONS);
|
||
int probability;
|
||
enum br_predictor predictor;
|
||
|
||
predict_extra_loop_exits (ex);
|
||
|
||
if (number_of_iterations_exit (loop, ex, &niter_desc, false, false))
|
||
niter = niter_desc.niter;
|
||
if (!niter || TREE_CODE (niter_desc.niter) != INTEGER_CST)
|
||
niter = loop_niter_by_eval (loop, ex);
|
||
|
||
if (TREE_CODE (niter) == INTEGER_CST)
|
||
{
|
||
if (tree_fits_uhwi_p (niter)
|
||
&& max
|
||
&& compare_tree_int (niter, max - 1) == -1)
|
||
nitercst = tree_to_uhwi (niter) + 1;
|
||
else
|
||
nitercst = max;
|
||
predictor = PRED_LOOP_ITERATIONS;
|
||
}
|
||
/* If we have just one exit and we can derive some information about
|
||
the number of iterations of the loop from the statements inside
|
||
the loop, use it to predict this exit. */
|
||
else if (n_exits == 1)
|
||
{
|
||
nitercst = estimated_stmt_executions_int (loop);
|
||
if (nitercst < 0)
|
||
continue;
|
||
if (nitercst > max)
|
||
nitercst = max;
|
||
|
||
predictor = PRED_LOOP_ITERATIONS_GUESSED;
|
||
}
|
||
else
|
||
continue;
|
||
|
||
/* If the prediction for number of iterations is zero, do not
|
||
predict the exit edges. */
|
||
if (nitercst == 0)
|
||
continue;
|
||
|
||
probability = ((REG_BR_PROB_BASE + nitercst / 2) / nitercst);
|
||
predict_edge (ex, predictor, probability);
|
||
}
|
||
exits.release ();
|
||
|
||
/* Find information about loop bound variables. */
|
||
for (nb_iter = loop->bounds; nb_iter;
|
||
nb_iter = nb_iter->next)
|
||
if (nb_iter->stmt
|
||
&& gimple_code (nb_iter->stmt) == GIMPLE_COND)
|
||
{
|
||
stmt = as_a <gcond *> (nb_iter->stmt);
|
||
break;
|
||
}
|
||
if (!stmt && last_stmt (loop->header)
|
||
&& gimple_code (last_stmt (loop->header)) == GIMPLE_COND)
|
||
stmt = as_a <gcond *> (last_stmt (loop->header));
|
||
if (stmt)
|
||
is_comparison_with_loop_invariant_p (stmt, loop,
|
||
&loop_bound_var,
|
||
&loop_bound_code,
|
||
&loop_bound_step,
|
||
&loop_iv_base);
|
||
|
||
bbs = get_loop_body (loop);
|
||
|
||
for (j = 0; j < loop->num_nodes; j++)
|
||
{
|
||
int header_found = 0;
|
||
edge e;
|
||
edge_iterator ei;
|
||
|
||
bb = bbs[j];
|
||
|
||
/* Bypass loop heuristics on continue statement. These
|
||
statements construct loops via "non-loop" constructs
|
||
in the source language and are better to be handled
|
||
separately. */
|
||
if (predicted_by_p (bb, PRED_CONTINUE))
|
||
continue;
|
||
|
||
/* Loop branch heuristics - predict an edge back to a
|
||
loop's head as taken. */
|
||
if (bb == loop->latch)
|
||
{
|
||
e = find_edge (loop->latch, loop->header);
|
||
if (e)
|
||
{
|
||
header_found = 1;
|
||
predict_edge_def (e, PRED_LOOP_BRANCH, TAKEN);
|
||
}
|
||
}
|
||
|
||
/* Loop exit heuristics - predict an edge exiting the loop if the
|
||
conditional has no loop header successors as not taken. */
|
||
if (!header_found
|
||
/* If we already used more reliable loop exit predictors, do not
|
||
bother with PRED_LOOP_EXIT. */
|
||
&& !predicted_by_p (bb, PRED_LOOP_ITERATIONS_GUESSED)
|
||
&& !predicted_by_p (bb, PRED_LOOP_ITERATIONS))
|
||
{
|
||
/* For loop with many exits we don't want to predict all exits
|
||
with the pretty large probability, because if all exits are
|
||
considered in row, the loop would be predicted to iterate
|
||
almost never. The code to divide probability by number of
|
||
exits is very rough. It should compute the number of exits
|
||
taken in each patch through function (not the overall number
|
||
of exits that might be a lot higher for loops with wide switch
|
||
statements in them) and compute n-th square root.
|
||
|
||
We limit the minimal probability by 2% to avoid
|
||
EDGE_PROBABILITY_RELIABLE from trusting the branch prediction
|
||
as this was causing regression in perl benchmark containing such
|
||
a wide loop. */
|
||
|
||
int probability = ((REG_BR_PROB_BASE
|
||
- predictor_info [(int) PRED_LOOP_EXIT].hitrate)
|
||
/ n_exits);
|
||
if (probability < HITRATE (2))
|
||
probability = HITRATE (2);
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
if (e->dest->index < NUM_FIXED_BLOCKS
|
||
|| !flow_bb_inside_loop_p (loop, e->dest))
|
||
predict_edge (e, PRED_LOOP_EXIT, probability);
|
||
}
|
||
if (loop_bound_var)
|
||
predict_iv_comparison (loop, bb, loop_bound_var, loop_iv_base,
|
||
loop_bound_code,
|
||
tree_to_shwi (loop_bound_step));
|
||
}
|
||
|
||
/* Free basic blocks from get_loop_body. */
|
||
free (bbs);
|
||
}
|
||
}
|
||
|
||
/* Attempt to predict probabilities of BB outgoing edges using local
|
||
properties. */
|
||
static void
|
||
bb_estimate_probability_locally (basic_block bb)
|
||
{
|
||
rtx_insn *last_insn = BB_END (bb);
|
||
rtx cond;
|
||
|
||
if (! can_predict_insn_p (last_insn))
|
||
return;
|
||
cond = get_condition (last_insn, NULL, false, false);
|
||
if (! cond)
|
||
return;
|
||
|
||
/* Try "pointer heuristic."
|
||
A comparison ptr == 0 is predicted as false.
|
||
Similarly, a comparison ptr1 == ptr2 is predicted as false. */
|
||
if (COMPARISON_P (cond)
|
||
&& ((REG_P (XEXP (cond, 0)) && REG_POINTER (XEXP (cond, 0)))
|
||
|| (REG_P (XEXP (cond, 1)) && REG_POINTER (XEXP (cond, 1)))))
|
||
{
|
||
if (GET_CODE (cond) == EQ)
|
||
predict_insn_def (last_insn, PRED_POINTER, NOT_TAKEN);
|
||
else if (GET_CODE (cond) == NE)
|
||
predict_insn_def (last_insn, PRED_POINTER, TAKEN);
|
||
}
|
||
else
|
||
|
||
/* Try "opcode heuristic."
|
||
EQ tests are usually false and NE tests are usually true. Also,
|
||
most quantities are positive, so we can make the appropriate guesses
|
||
about signed comparisons against zero. */
|
||
switch (GET_CODE (cond))
|
||
{
|
||
case CONST_INT:
|
||
/* Unconditional branch. */
|
||
predict_insn_def (last_insn, PRED_UNCONDITIONAL,
|
||
cond == const0_rtx ? NOT_TAKEN : TAKEN);
|
||
break;
|
||
|
||
case EQ:
|
||
case UNEQ:
|
||
/* Floating point comparisons appears to behave in a very
|
||
unpredictable way because of special role of = tests in
|
||
FP code. */
|
||
if (FLOAT_MODE_P (GET_MODE (XEXP (cond, 0))))
|
||
;
|
||
/* Comparisons with 0 are often used for booleans and there is
|
||
nothing useful to predict about them. */
|
||
else if (XEXP (cond, 1) == const0_rtx
|
||
|| XEXP (cond, 0) == const0_rtx)
|
||
;
|
||
else
|
||
predict_insn_def (last_insn, PRED_OPCODE_NONEQUAL, NOT_TAKEN);
|
||
break;
|
||
|
||
case NE:
|
||
case LTGT:
|
||
/* Floating point comparisons appears to behave in a very
|
||
unpredictable way because of special role of = tests in
|
||
FP code. */
|
||
if (FLOAT_MODE_P (GET_MODE (XEXP (cond, 0))))
|
||
;
|
||
/* Comparisons with 0 are often used for booleans and there is
|
||
nothing useful to predict about them. */
|
||
else if (XEXP (cond, 1) == const0_rtx
|
||
|| XEXP (cond, 0) == const0_rtx)
|
||
;
|
||
else
|
||
predict_insn_def (last_insn, PRED_OPCODE_NONEQUAL, TAKEN);
|
||
break;
|
||
|
||
case ORDERED:
|
||
predict_insn_def (last_insn, PRED_FPOPCODE, TAKEN);
|
||
break;
|
||
|
||
case UNORDERED:
|
||
predict_insn_def (last_insn, PRED_FPOPCODE, NOT_TAKEN);
|
||
break;
|
||
|
||
case LE:
|
||
case LT:
|
||
if (XEXP (cond, 1) == const0_rtx || XEXP (cond, 1) == const1_rtx
|
||
|| XEXP (cond, 1) == constm1_rtx)
|
||
predict_insn_def (last_insn, PRED_OPCODE_POSITIVE, NOT_TAKEN);
|
||
break;
|
||
|
||
case GE:
|
||
case GT:
|
||
if (XEXP (cond, 1) == const0_rtx || XEXP (cond, 1) == const1_rtx
|
||
|| XEXP (cond, 1) == constm1_rtx)
|
||
predict_insn_def (last_insn, PRED_OPCODE_POSITIVE, TAKEN);
|
||
break;
|
||
|
||
default:
|
||
break;
|
||
}
|
||
}
|
||
|
||
/* Set edge->probability for each successor edge of BB. */
|
||
void
|
||
guess_outgoing_edge_probabilities (basic_block bb)
|
||
{
|
||
bb_estimate_probability_locally (bb);
|
||
combine_predictions_for_insn (BB_END (bb), bb);
|
||
}
|
||
|
||
static tree expr_expected_value (tree, bitmap, enum br_predictor *predictor);
|
||
|
||
/* Helper function for expr_expected_value. */
|
||
|
||
static tree
|
||
expr_expected_value_1 (tree type, tree op0, enum tree_code code,
|
||
tree op1, bitmap visited, enum br_predictor *predictor)
|
||
{
|
||
gimple def;
|
||
|
||
if (predictor)
|
||
*predictor = PRED_UNCONDITIONAL;
|
||
|
||
if (get_gimple_rhs_class (code) == GIMPLE_SINGLE_RHS)
|
||
{
|
||
if (TREE_CONSTANT (op0))
|
||
return op0;
|
||
|
||
if (code != SSA_NAME)
|
||
return NULL_TREE;
|
||
|
||
def = SSA_NAME_DEF_STMT (op0);
|
||
|
||
/* If we were already here, break the infinite cycle. */
|
||
if (!bitmap_set_bit (visited, SSA_NAME_VERSION (op0)))
|
||
return NULL;
|
||
|
||
if (gimple_code (def) == GIMPLE_PHI)
|
||
{
|
||
/* All the arguments of the PHI node must have the same constant
|
||
length. */
|
||
int i, n = gimple_phi_num_args (def);
|
||
tree val = NULL, new_val;
|
||
|
||
for (i = 0; i < n; i++)
|
||
{
|
||
tree arg = PHI_ARG_DEF (def, i);
|
||
enum br_predictor predictor2;
|
||
|
||
/* If this PHI has itself as an argument, we cannot
|
||
determine the string length of this argument. However,
|
||
if we can find an expected constant value for the other
|
||
PHI args then we can still be sure that this is
|
||
likely a constant. So be optimistic and just
|
||
continue with the next argument. */
|
||
if (arg == PHI_RESULT (def))
|
||
continue;
|
||
|
||
new_val = expr_expected_value (arg, visited, &predictor2);
|
||
|
||
/* It is difficult to combine value predictors. Simply assume
|
||
that later predictor is weaker and take its prediction. */
|
||
if (predictor && *predictor < predictor2)
|
||
*predictor = predictor2;
|
||
if (!new_val)
|
||
return NULL;
|
||
if (!val)
|
||
val = new_val;
|
||
else if (!operand_equal_p (val, new_val, false))
|
||
return NULL;
|
||
}
|
||
return val;
|
||
}
|
||
if (is_gimple_assign (def))
|
||
{
|
||
if (gimple_assign_lhs (def) != op0)
|
||
return NULL;
|
||
|
||
return expr_expected_value_1 (TREE_TYPE (gimple_assign_lhs (def)),
|
||
gimple_assign_rhs1 (def),
|
||
gimple_assign_rhs_code (def),
|
||
gimple_assign_rhs2 (def),
|
||
visited, predictor);
|
||
}
|
||
|
||
if (is_gimple_call (def))
|
||
{
|
||
tree decl = gimple_call_fndecl (def);
|
||
if (!decl)
|
||
{
|
||
if (gimple_call_internal_p (def)
|
||
&& gimple_call_internal_fn (def) == IFN_BUILTIN_EXPECT)
|
||
{
|
||
gcc_assert (gimple_call_num_args (def) == 3);
|
||
tree val = gimple_call_arg (def, 0);
|
||
if (TREE_CONSTANT (val))
|
||
return val;
|
||
if (predictor)
|
||
{
|
||
tree val2 = gimple_call_arg (def, 2);
|
||
gcc_assert (TREE_CODE (val2) == INTEGER_CST
|
||
&& tree_fits_uhwi_p (val2)
|
||
&& tree_to_uhwi (val2) < END_PREDICTORS);
|
||
*predictor = (enum br_predictor) tree_to_uhwi (val2);
|
||
}
|
||
return gimple_call_arg (def, 1);
|
||
}
|
||
return NULL;
|
||
}
|
||
if (DECL_BUILT_IN_CLASS (decl) == BUILT_IN_NORMAL)
|
||
switch (DECL_FUNCTION_CODE (decl))
|
||
{
|
||
case BUILT_IN_EXPECT:
|
||
{
|
||
tree val;
|
||
if (gimple_call_num_args (def) != 2)
|
||
return NULL;
|
||
val = gimple_call_arg (def, 0);
|
||
if (TREE_CONSTANT (val))
|
||
return val;
|
||
if (predictor)
|
||
*predictor = PRED_BUILTIN_EXPECT;
|
||
return gimple_call_arg (def, 1);
|
||
}
|
||
|
||
case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_N:
|
||
case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_1:
|
||
case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_2:
|
||
case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_4:
|
||
case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_8:
|
||
case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_16:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_N:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_1:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_2:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_4:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_8:
|
||
case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_16:
|
||
/* Assume that any given atomic operation has low contention,
|
||
and thus the compare-and-swap operation succeeds. */
|
||
if (predictor)
|
||
*predictor = PRED_COMPARE_AND_SWAP;
|
||
return boolean_true_node;
|
||
default:
|
||
break;
|
||
}
|
||
}
|
||
|
||
return NULL;
|
||
}
|
||
|
||
if (get_gimple_rhs_class (code) == GIMPLE_BINARY_RHS)
|
||
{
|
||
tree res;
|
||
enum br_predictor predictor2;
|
||
op0 = expr_expected_value (op0, visited, predictor);
|
||
if (!op0)
|
||
return NULL;
|
||
op1 = expr_expected_value (op1, visited, &predictor2);
|
||
if (predictor && *predictor < predictor2)
|
||
*predictor = predictor2;
|
||
if (!op1)
|
||
return NULL;
|
||
res = fold_build2 (code, type, op0, op1);
|
||
if (TREE_CONSTANT (res))
|
||
return res;
|
||
return NULL;
|
||
}
|
||
if (get_gimple_rhs_class (code) == GIMPLE_UNARY_RHS)
|
||
{
|
||
tree res;
|
||
op0 = expr_expected_value (op0, visited, predictor);
|
||
if (!op0)
|
||
return NULL;
|
||
res = fold_build1 (code, type, op0);
|
||
if (TREE_CONSTANT (res))
|
||
return res;
|
||
return NULL;
|
||
}
|
||
return NULL;
|
||
}
|
||
|
||
/* Return constant EXPR will likely have at execution time, NULL if unknown.
|
||
The function is used by builtin_expect branch predictor so the evidence
|
||
must come from this construct and additional possible constant folding.
|
||
|
||
We may want to implement more involved value guess (such as value range
|
||
propagation based prediction), but such tricks shall go to new
|
||
implementation. */
|
||
|
||
static tree
|
||
expr_expected_value (tree expr, bitmap visited,
|
||
enum br_predictor *predictor)
|
||
{
|
||
enum tree_code code;
|
||
tree op0, op1;
|
||
|
||
if (TREE_CONSTANT (expr))
|
||
{
|
||
if (predictor)
|
||
*predictor = PRED_UNCONDITIONAL;
|
||
return expr;
|
||
}
|
||
|
||
extract_ops_from_tree (expr, &code, &op0, &op1);
|
||
return expr_expected_value_1 (TREE_TYPE (expr),
|
||
op0, code, op1, visited, predictor);
|
||
}
|
||
|
||
/* Predict using opcode of the last statement in basic block. */
|
||
static void
|
||
tree_predict_by_opcode (basic_block bb)
|
||
{
|
||
gimple stmt = last_stmt (bb);
|
||
edge then_edge;
|
||
tree op0, op1;
|
||
tree type;
|
||
tree val;
|
||
enum tree_code cmp;
|
||
bitmap visited;
|
||
edge_iterator ei;
|
||
enum br_predictor predictor;
|
||
|
||
if (!stmt || gimple_code (stmt) != GIMPLE_COND)
|
||
return;
|
||
FOR_EACH_EDGE (then_edge, ei, bb->succs)
|
||
if (then_edge->flags & EDGE_TRUE_VALUE)
|
||
break;
|
||
op0 = gimple_cond_lhs (stmt);
|
||
op1 = gimple_cond_rhs (stmt);
|
||
cmp = gimple_cond_code (stmt);
|
||
type = TREE_TYPE (op0);
|
||
visited = BITMAP_ALLOC (NULL);
|
||
val = expr_expected_value_1 (boolean_type_node, op0, cmp, op1, visited,
|
||
&predictor);
|
||
BITMAP_FREE (visited);
|
||
if (val && TREE_CODE (val) == INTEGER_CST)
|
||
{
|
||
if (predictor == PRED_BUILTIN_EXPECT)
|
||
{
|
||
int percent = PARAM_VALUE (BUILTIN_EXPECT_PROBABILITY);
|
||
|
||
gcc_assert (percent >= 0 && percent <= 100);
|
||
if (integer_zerop (val))
|
||
percent = 100 - percent;
|
||
predict_edge (then_edge, PRED_BUILTIN_EXPECT, HITRATE (percent));
|
||
}
|
||
else
|
||
predict_edge (then_edge, predictor,
|
||
integer_zerop (val) ? NOT_TAKEN : TAKEN);
|
||
}
|
||
/* Try "pointer heuristic."
|
||
A comparison ptr == 0 is predicted as false.
|
||
Similarly, a comparison ptr1 == ptr2 is predicted as false. */
|
||
if (POINTER_TYPE_P (type))
|
||
{
|
||
if (cmp == EQ_EXPR)
|
||
predict_edge_def (then_edge, PRED_TREE_POINTER, NOT_TAKEN);
|
||
else if (cmp == NE_EXPR)
|
||
predict_edge_def (then_edge, PRED_TREE_POINTER, TAKEN);
|
||
}
|
||
else
|
||
|
||
/* Try "opcode heuristic."
|
||
EQ tests are usually false and NE tests are usually true. Also,
|
||
most quantities are positive, so we can make the appropriate guesses
|
||
about signed comparisons against zero. */
|
||
switch (cmp)
|
||
{
|
||
case EQ_EXPR:
|
||
case UNEQ_EXPR:
|
||
/* Floating point comparisons appears to behave in a very
|
||
unpredictable way because of special role of = tests in
|
||
FP code. */
|
||
if (FLOAT_TYPE_P (type))
|
||
;
|
||
/* Comparisons with 0 are often used for booleans and there is
|
||
nothing useful to predict about them. */
|
||
else if (integer_zerop (op0) || integer_zerop (op1))
|
||
;
|
||
else
|
||
predict_edge_def (then_edge, PRED_TREE_OPCODE_NONEQUAL, NOT_TAKEN);
|
||
break;
|
||
|
||
case NE_EXPR:
|
||
case LTGT_EXPR:
|
||
/* Floating point comparisons appears to behave in a very
|
||
unpredictable way because of special role of = tests in
|
||
FP code. */
|
||
if (FLOAT_TYPE_P (type))
|
||
;
|
||
/* Comparisons with 0 are often used for booleans and there is
|
||
nothing useful to predict about them. */
|
||
else if (integer_zerop (op0)
|
||
|| integer_zerop (op1))
|
||
;
|
||
else
|
||
predict_edge_def (then_edge, PRED_TREE_OPCODE_NONEQUAL, TAKEN);
|
||
break;
|
||
|
||
case ORDERED_EXPR:
|
||
predict_edge_def (then_edge, PRED_TREE_FPOPCODE, TAKEN);
|
||
break;
|
||
|
||
case UNORDERED_EXPR:
|
||
predict_edge_def (then_edge, PRED_TREE_FPOPCODE, NOT_TAKEN);
|
||
break;
|
||
|
||
case LE_EXPR:
|
||
case LT_EXPR:
|
||
if (integer_zerop (op1)
|
||
|| integer_onep (op1)
|
||
|| integer_all_onesp (op1)
|
||
|| real_zerop (op1)
|
||
|| real_onep (op1)
|
||
|| real_minus_onep (op1))
|
||
predict_edge_def (then_edge, PRED_TREE_OPCODE_POSITIVE, NOT_TAKEN);
|
||
break;
|
||
|
||
case GE_EXPR:
|
||
case GT_EXPR:
|
||
if (integer_zerop (op1)
|
||
|| integer_onep (op1)
|
||
|| integer_all_onesp (op1)
|
||
|| real_zerop (op1)
|
||
|| real_onep (op1)
|
||
|| real_minus_onep (op1))
|
||
predict_edge_def (then_edge, PRED_TREE_OPCODE_POSITIVE, TAKEN);
|
||
break;
|
||
|
||
default:
|
||
break;
|
||
}
|
||
}
|
||
|
||
/* Try to guess whether the value of return means error code. */
|
||
|
||
static enum br_predictor
|
||
return_prediction (tree val, enum prediction *prediction)
|
||
{
|
||
/* VOID. */
|
||
if (!val)
|
||
return PRED_NO_PREDICTION;
|
||
/* Different heuristics for pointers and scalars. */
|
||
if (POINTER_TYPE_P (TREE_TYPE (val)))
|
||
{
|
||
/* NULL is usually not returned. */
|
||
if (integer_zerop (val))
|
||
{
|
||
*prediction = NOT_TAKEN;
|
||
return PRED_NULL_RETURN;
|
||
}
|
||
}
|
||
else if (INTEGRAL_TYPE_P (TREE_TYPE (val)))
|
||
{
|
||
/* Negative return values are often used to indicate
|
||
errors. */
|
||
if (TREE_CODE (val) == INTEGER_CST
|
||
&& tree_int_cst_sgn (val) < 0)
|
||
{
|
||
*prediction = NOT_TAKEN;
|
||
return PRED_NEGATIVE_RETURN;
|
||
}
|
||
/* Constant return values seems to be commonly taken.
|
||
Zero/one often represent booleans so exclude them from the
|
||
heuristics. */
|
||
if (TREE_CONSTANT (val)
|
||
&& (!integer_zerop (val) && !integer_onep (val)))
|
||
{
|
||
*prediction = TAKEN;
|
||
return PRED_CONST_RETURN;
|
||
}
|
||
}
|
||
return PRED_NO_PREDICTION;
|
||
}
|
||
|
||
/* Find the basic block with return expression and look up for possible
|
||
return value trying to apply RETURN_PREDICTION heuristics. */
|
||
static void
|
||
apply_return_prediction (void)
|
||
{
|
||
greturn *return_stmt = NULL;
|
||
tree return_val;
|
||
edge e;
|
||
gphi *phi;
|
||
int phi_num_args, i;
|
||
enum br_predictor pred;
|
||
enum prediction direction;
|
||
edge_iterator ei;
|
||
|
||
FOR_EACH_EDGE (e, ei, EXIT_BLOCK_PTR_FOR_FN (cfun)->preds)
|
||
{
|
||
gimple last = last_stmt (e->src);
|
||
if (last
|
||
&& gimple_code (last) == GIMPLE_RETURN)
|
||
{
|
||
return_stmt = as_a <greturn *> (last);
|
||
break;
|
||
}
|
||
}
|
||
if (!e)
|
||
return;
|
||
return_val = gimple_return_retval (return_stmt);
|
||
if (!return_val)
|
||
return;
|
||
if (TREE_CODE (return_val) != SSA_NAME
|
||
|| !SSA_NAME_DEF_STMT (return_val)
|
||
|| gimple_code (SSA_NAME_DEF_STMT (return_val)) != GIMPLE_PHI)
|
||
return;
|
||
phi = as_a <gphi *> (SSA_NAME_DEF_STMT (return_val));
|
||
phi_num_args = gimple_phi_num_args (phi);
|
||
pred = return_prediction (PHI_ARG_DEF (phi, 0), &direction);
|
||
|
||
/* Avoid the degenerate case where all return values form the function
|
||
belongs to same category (ie they are all positive constants)
|
||
so we can hardly say something about them. */
|
||
for (i = 1; i < phi_num_args; i++)
|
||
if (pred != return_prediction (PHI_ARG_DEF (phi, i), &direction))
|
||
break;
|
||
if (i != phi_num_args)
|
||
for (i = 0; i < phi_num_args; i++)
|
||
{
|
||
pred = return_prediction (PHI_ARG_DEF (phi, i), &direction);
|
||
if (pred != PRED_NO_PREDICTION)
|
||
predict_paths_leading_to_edge (gimple_phi_arg_edge (phi, i), pred,
|
||
direction);
|
||
}
|
||
}
|
||
|
||
/* Look for basic block that contains unlikely to happen events
|
||
(such as noreturn calls) and mark all paths leading to execution
|
||
of this basic blocks as unlikely. */
|
||
|
||
static void
|
||
tree_bb_level_predictions (void)
|
||
{
|
||
basic_block bb;
|
||
bool has_return_edges = false;
|
||
edge e;
|
||
edge_iterator ei;
|
||
|
||
FOR_EACH_EDGE (e, ei, EXIT_BLOCK_PTR_FOR_FN (cfun)->preds)
|
||
if (!(e->flags & (EDGE_ABNORMAL | EDGE_FAKE | EDGE_EH)))
|
||
{
|
||
has_return_edges = true;
|
||
break;
|
||
}
|
||
|
||
apply_return_prediction ();
|
||
|
||
FOR_EACH_BB_FN (bb, cfun)
|
||
{
|
||
gimple_stmt_iterator gsi;
|
||
|
||
for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi))
|
||
{
|
||
gimple stmt = gsi_stmt (gsi);
|
||
tree decl;
|
||
|
||
if (is_gimple_call (stmt))
|
||
{
|
||
if ((gimple_call_flags (stmt) & ECF_NORETURN)
|
||
&& has_return_edges)
|
||
predict_paths_leading_to (bb, PRED_NORETURN,
|
||
NOT_TAKEN);
|
||
decl = gimple_call_fndecl (stmt);
|
||
if (decl
|
||
&& lookup_attribute ("cold",
|
||
DECL_ATTRIBUTES (decl)))
|
||
predict_paths_leading_to (bb, PRED_COLD_FUNCTION,
|
||
NOT_TAKEN);
|
||
}
|
||
else if (gimple_code (stmt) == GIMPLE_PREDICT)
|
||
{
|
||
predict_paths_leading_to (bb, gimple_predict_predictor (stmt),
|
||
gimple_predict_outcome (stmt));
|
||
/* Keep GIMPLE_PREDICT around so early inlining will propagate
|
||
hints to callers. */
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
#ifdef ENABLE_CHECKING
|
||
|
||
/* Callback for hash_map::traverse, asserts that the pointer map is
|
||
empty. */
|
||
|
||
bool
|
||
assert_is_empty (const_basic_block const &, edge_prediction *const &value,
|
||
void *)
|
||
{
|
||
gcc_assert (!value);
|
||
return false;
|
||
}
|
||
#endif
|
||
|
||
/* Predict branch probabilities and estimate profile for basic block BB. */
|
||
|
||
static void
|
||
tree_estimate_probability_bb (basic_block bb)
|
||
{
|
||
edge e;
|
||
edge_iterator ei;
|
||
gimple last;
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
{
|
||
/* Predict edges to user labels with attributes. */
|
||
if (e->dest != EXIT_BLOCK_PTR_FOR_FN (cfun))
|
||
{
|
||
gimple_stmt_iterator gi;
|
||
for (gi = gsi_start_bb (e->dest); !gsi_end_p (gi); gsi_next (&gi))
|
||
{
|
||
glabel *label_stmt = dyn_cast <glabel *> (gsi_stmt (gi));
|
||
tree decl;
|
||
|
||
if (!label_stmt)
|
||
break;
|
||
decl = gimple_label_label (label_stmt);
|
||
if (DECL_ARTIFICIAL (decl))
|
||
continue;
|
||
|
||
/* Finally, we have a user-defined label. */
|
||
if (lookup_attribute ("cold", DECL_ATTRIBUTES (decl)))
|
||
predict_edge_def (e, PRED_COLD_LABEL, NOT_TAKEN);
|
||
else if (lookup_attribute ("hot", DECL_ATTRIBUTES (decl)))
|
||
predict_edge_def (e, PRED_HOT_LABEL, TAKEN);
|
||
}
|
||
}
|
||
|
||
/* Predict early returns to be probable, as we've already taken
|
||
care for error returns and other cases are often used for
|
||
fast paths through function.
|
||
|
||
Since we've already removed the return statements, we are
|
||
looking for CFG like:
|
||
|
||
if (conditional)
|
||
{
|
||
..
|
||
goto return_block
|
||
}
|
||
some other blocks
|
||
return_block:
|
||
return_stmt. */
|
||
if (e->dest != bb->next_bb
|
||
&& e->dest != EXIT_BLOCK_PTR_FOR_FN (cfun)
|
||
&& single_succ_p (e->dest)
|
||
&& single_succ_edge (e->dest)->dest == EXIT_BLOCK_PTR_FOR_FN (cfun)
|
||
&& (last = last_stmt (e->dest)) != NULL
|
||
&& gimple_code (last) == GIMPLE_RETURN)
|
||
{
|
||
edge e1;
|
||
edge_iterator ei1;
|
||
|
||
if (single_succ_p (bb))
|
||
{
|
||
FOR_EACH_EDGE (e1, ei1, bb->preds)
|
||
if (!predicted_by_p (e1->src, PRED_NULL_RETURN)
|
||
&& !predicted_by_p (e1->src, PRED_CONST_RETURN)
|
||
&& !predicted_by_p (e1->src, PRED_NEGATIVE_RETURN))
|
||
predict_edge_def (e1, PRED_TREE_EARLY_RETURN, NOT_TAKEN);
|
||
}
|
||
else
|
||
if (!predicted_by_p (e->src, PRED_NULL_RETURN)
|
||
&& !predicted_by_p (e->src, PRED_CONST_RETURN)
|
||
&& !predicted_by_p (e->src, PRED_NEGATIVE_RETURN))
|
||
predict_edge_def (e, PRED_TREE_EARLY_RETURN, NOT_TAKEN);
|
||
}
|
||
|
||
/* Look for block we are guarding (ie we dominate it,
|
||
but it doesn't postdominate us). */
|
||
if (e->dest != EXIT_BLOCK_PTR_FOR_FN (cfun) && e->dest != bb
|
||
&& dominated_by_p (CDI_DOMINATORS, e->dest, e->src)
|
||
&& !dominated_by_p (CDI_POST_DOMINATORS, e->src, e->dest))
|
||
{
|
||
gimple_stmt_iterator bi;
|
||
|
||
/* The call heuristic claims that a guarded function call
|
||
is improbable. This is because such calls are often used
|
||
to signal exceptional situations such as printing error
|
||
messages. */
|
||
for (bi = gsi_start_bb (e->dest); !gsi_end_p (bi);
|
||
gsi_next (&bi))
|
||
{
|
||
gimple stmt = gsi_stmt (bi);
|
||
if (is_gimple_call (stmt)
|
||
/* Constant and pure calls are hardly used to signalize
|
||
something exceptional. */
|
||
&& gimple_has_side_effects (stmt))
|
||
{
|
||
predict_edge_def (e, PRED_CALL, NOT_TAKEN);
|
||
break;
|
||
}
|
||
}
|
||
}
|
||
}
|
||
tree_predict_by_opcode (bb);
|
||
}
|
||
|
||
/* Predict branch probabilities and estimate profile of the tree CFG.
|
||
This function can be called from the loop optimizers to recompute
|
||
the profile information. */
|
||
|
||
void
|
||
tree_estimate_probability (void)
|
||
{
|
||
basic_block bb;
|
||
|
||
add_noreturn_fake_exit_edges ();
|
||
connect_infinite_loops_to_exit ();
|
||
/* We use loop_niter_by_eval, which requires that the loops have
|
||
preheaders. */
|
||
create_preheaders (CP_SIMPLE_PREHEADERS);
|
||
calculate_dominance_info (CDI_POST_DOMINATORS);
|
||
|
||
bb_predictions = new hash_map<const_basic_block, edge_prediction *>;
|
||
tree_bb_level_predictions ();
|
||
record_loop_exits ();
|
||
|
||
if (number_of_loops (cfun) > 1)
|
||
predict_loops ();
|
||
|
||
FOR_EACH_BB_FN (bb, cfun)
|
||
tree_estimate_probability_bb (bb);
|
||
|
||
FOR_EACH_BB_FN (bb, cfun)
|
||
combine_predictions_for_bb (bb);
|
||
|
||
#ifdef ENABLE_CHECKING
|
||
bb_predictions->traverse<void *, assert_is_empty> (NULL);
|
||
#endif
|
||
delete bb_predictions;
|
||
bb_predictions = NULL;
|
||
|
||
estimate_bb_frequencies (false);
|
||
free_dominance_info (CDI_POST_DOMINATORS);
|
||
remove_fake_exit_edges ();
|
||
}
|
||
|
||
/* Predict edges to successors of CUR whose sources are not postdominated by
|
||
BB by PRED and recurse to all postdominators. */
|
||
|
||
static void
|
||
predict_paths_for_bb (basic_block cur, basic_block bb,
|
||
enum br_predictor pred,
|
||
enum prediction taken,
|
||
bitmap visited)
|
||
{
|
||
edge e;
|
||
edge_iterator ei;
|
||
basic_block son;
|
||
|
||
/* We are looking for all edges forming edge cut induced by
|
||
set of all blocks postdominated by BB. */
|
||
FOR_EACH_EDGE (e, ei, cur->preds)
|
||
if (e->src->index >= NUM_FIXED_BLOCKS
|
||
&& !dominated_by_p (CDI_POST_DOMINATORS, e->src, bb))
|
||
{
|
||
edge e2;
|
||
edge_iterator ei2;
|
||
bool found = false;
|
||
|
||
/* Ignore fake edges and eh, we predict them as not taken anyway. */
|
||
if (e->flags & (EDGE_EH | EDGE_FAKE))
|
||
continue;
|
||
gcc_assert (bb == cur || dominated_by_p (CDI_POST_DOMINATORS, cur, bb));
|
||
|
||
/* See if there is an edge from e->src that is not abnormal
|
||
and does not lead to BB. */
|
||
FOR_EACH_EDGE (e2, ei2, e->src->succs)
|
||
if (e2 != e
|
||
&& !(e2->flags & (EDGE_EH | EDGE_FAKE))
|
||
&& !dominated_by_p (CDI_POST_DOMINATORS, e2->dest, bb))
|
||
{
|
||
found = true;
|
||
break;
|
||
}
|
||
|
||
/* If there is non-abnormal path leaving e->src, predict edge
|
||
using predictor. Otherwise we need to look for paths
|
||
leading to e->src.
|
||
|
||
The second may lead to infinite loop in the case we are predicitng
|
||
regions that are only reachable by abnormal edges. We simply
|
||
prevent visiting given BB twice. */
|
||
if (found)
|
||
predict_edge_def (e, pred, taken);
|
||
else if (bitmap_set_bit (visited, e->src->index))
|
||
predict_paths_for_bb (e->src, e->src, pred, taken, visited);
|
||
}
|
||
for (son = first_dom_son (CDI_POST_DOMINATORS, cur);
|
||
son;
|
||
son = next_dom_son (CDI_POST_DOMINATORS, son))
|
||
predict_paths_for_bb (son, bb, pred, taken, visited);
|
||
}
|
||
|
||
/* Sets branch probabilities according to PREDiction and
|
||
FLAGS. */
|
||
|
||
static void
|
||
predict_paths_leading_to (basic_block bb, enum br_predictor pred,
|
||
enum prediction taken)
|
||
{
|
||
bitmap visited = BITMAP_ALLOC (NULL);
|
||
predict_paths_for_bb (bb, bb, pred, taken, visited);
|
||
BITMAP_FREE (visited);
|
||
}
|
||
|
||
/* Like predict_paths_leading_to but take edge instead of basic block. */
|
||
|
||
static void
|
||
predict_paths_leading_to_edge (edge e, enum br_predictor pred,
|
||
enum prediction taken)
|
||
{
|
||
bool has_nonloop_edge = false;
|
||
edge_iterator ei;
|
||
edge e2;
|
||
|
||
basic_block bb = e->src;
|
||
FOR_EACH_EDGE (e2, ei, bb->succs)
|
||
if (e2->dest != e->src && e2->dest != e->dest
|
||
&& !(e->flags & (EDGE_EH | EDGE_FAKE))
|
||
&& !dominated_by_p (CDI_POST_DOMINATORS, e->src, e2->dest))
|
||
{
|
||
has_nonloop_edge = true;
|
||
break;
|
||
}
|
||
if (!has_nonloop_edge)
|
||
{
|
||
bitmap visited = BITMAP_ALLOC (NULL);
|
||
predict_paths_for_bb (bb, bb, pred, taken, visited);
|
||
BITMAP_FREE (visited);
|
||
}
|
||
else
|
||
predict_edge_def (e, pred, taken);
|
||
}
|
||
|
||
/* This is used to carry information about basic blocks. It is
|
||
attached to the AUX field of the standard CFG block. */
|
||
|
||
struct block_info
|
||
{
|
||
/* Estimated frequency of execution of basic_block. */
|
||
sreal frequency;
|
||
|
||
/* To keep queue of basic blocks to process. */
|
||
basic_block next;
|
||
|
||
/* Number of predecessors we need to visit first. */
|
||
int npredecessors;
|
||
};
|
||
|
||
/* Similar information for edges. */
|
||
struct edge_prob_info
|
||
{
|
||
/* In case edge is a loopback edge, the probability edge will be reached
|
||
in case header is. Estimated number of iterations of the loop can be
|
||
then computed as 1 / (1 - back_edge_prob). */
|
||
sreal back_edge_prob;
|
||
/* True if the edge is a loopback edge in the natural loop. */
|
||
unsigned int back_edge:1;
|
||
};
|
||
|
||
#define BLOCK_INFO(B) ((block_info *) (B)->aux)
|
||
#undef EDGE_INFO
|
||
#define EDGE_INFO(E) ((edge_prob_info *) (E)->aux)
|
||
|
||
/* Helper function for estimate_bb_frequencies.
|
||
Propagate the frequencies in blocks marked in
|
||
TOVISIT, starting in HEAD. */
|
||
|
||
static void
|
||
propagate_freq (basic_block head, bitmap tovisit)
|
||
{
|
||
basic_block bb;
|
||
basic_block last;
|
||
unsigned i;
|
||
edge e;
|
||
basic_block nextbb;
|
||
bitmap_iterator bi;
|
||
|
||
/* For each basic block we need to visit count number of his predecessors
|
||
we need to visit first. */
|
||
EXECUTE_IF_SET_IN_BITMAP (tovisit, 0, i, bi)
|
||
{
|
||
edge_iterator ei;
|
||
int count = 0;
|
||
|
||
bb = BASIC_BLOCK_FOR_FN (cfun, i);
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->preds)
|
||
{
|
||
bool visit = bitmap_bit_p (tovisit, e->src->index);
|
||
|
||
if (visit && !(e->flags & EDGE_DFS_BACK))
|
||
count++;
|
||
else if (visit && dump_file && !EDGE_INFO (e)->back_edge)
|
||
fprintf (dump_file,
|
||
"Irreducible region hit, ignoring edge to %i->%i\n",
|
||
e->src->index, bb->index);
|
||
}
|
||
BLOCK_INFO (bb)->npredecessors = count;
|
||
/* When function never returns, we will never process exit block. */
|
||
if (!count && bb == EXIT_BLOCK_PTR_FOR_FN (cfun))
|
||
bb->count = bb->frequency = 0;
|
||
}
|
||
|
||
BLOCK_INFO (head)->frequency = 1;
|
||
last = head;
|
||
for (bb = head; bb; bb = nextbb)
|
||
{
|
||
edge_iterator ei;
|
||
sreal cyclic_probability = 0;
|
||
sreal frequency = 0;
|
||
|
||
nextbb = BLOCK_INFO (bb)->next;
|
||
BLOCK_INFO (bb)->next = NULL;
|
||
|
||
/* Compute frequency of basic block. */
|
||
if (bb != head)
|
||
{
|
||
#ifdef ENABLE_CHECKING
|
||
FOR_EACH_EDGE (e, ei, bb->preds)
|
||
gcc_assert (!bitmap_bit_p (tovisit, e->src->index)
|
||
|| (e->flags & EDGE_DFS_BACK));
|
||
#endif
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->preds)
|
||
if (EDGE_INFO (e)->back_edge)
|
||
{
|
||
cyclic_probability += EDGE_INFO (e)->back_edge_prob;
|
||
}
|
||
else if (!(e->flags & EDGE_DFS_BACK))
|
||
{
|
||
/* frequency += (e->probability
|
||
* BLOCK_INFO (e->src)->frequency /
|
||
REG_BR_PROB_BASE); */
|
||
|
||
sreal tmp = e->probability;
|
||
tmp *= BLOCK_INFO (e->src)->frequency;
|
||
tmp *= real_inv_br_prob_base;
|
||
frequency += tmp;
|
||
}
|
||
|
||
if (cyclic_probability == 0)
|
||
{
|
||
BLOCK_INFO (bb)->frequency = frequency;
|
||
}
|
||
else
|
||
{
|
||
if (cyclic_probability > real_almost_one)
|
||
cyclic_probability = real_almost_one;
|
||
|
||
/* BLOCK_INFO (bb)->frequency = frequency
|
||
/ (1 - cyclic_probability) */
|
||
|
||
cyclic_probability = sreal (1) - cyclic_probability;
|
||
BLOCK_INFO (bb)->frequency = frequency / cyclic_probability;
|
||
}
|
||
}
|
||
|
||
bitmap_clear_bit (tovisit, bb->index);
|
||
|
||
e = find_edge (bb, head);
|
||
if (e)
|
||
{
|
||
/* EDGE_INFO (e)->back_edge_prob
|
||
= ((e->probability * BLOCK_INFO (bb)->frequency)
|
||
/ REG_BR_PROB_BASE); */
|
||
|
||
sreal tmp = e->probability;
|
||
tmp *= BLOCK_INFO (bb)->frequency;
|
||
EDGE_INFO (e)->back_edge_prob = tmp * real_inv_br_prob_base;
|
||
}
|
||
|
||
/* Propagate to successor blocks. */
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
if (!(e->flags & EDGE_DFS_BACK)
|
||
&& BLOCK_INFO (e->dest)->npredecessors)
|
||
{
|
||
BLOCK_INFO (e->dest)->npredecessors--;
|
||
if (!BLOCK_INFO (e->dest)->npredecessors)
|
||
{
|
||
if (!nextbb)
|
||
nextbb = e->dest;
|
||
else
|
||
BLOCK_INFO (last)->next = e->dest;
|
||
|
||
last = e->dest;
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
/* Estimate frequencies in loops at same nest level. */
|
||
|
||
static void
|
||
estimate_loops_at_level (struct loop *first_loop)
|
||
{
|
||
struct loop *loop;
|
||
|
||
for (loop = first_loop; loop; loop = loop->next)
|
||
{
|
||
edge e;
|
||
basic_block *bbs;
|
||
unsigned i;
|
||
bitmap tovisit = BITMAP_ALLOC (NULL);
|
||
|
||
estimate_loops_at_level (loop->inner);
|
||
|
||
/* Find current loop back edge and mark it. */
|
||
e = loop_latch_edge (loop);
|
||
EDGE_INFO (e)->back_edge = 1;
|
||
|
||
bbs = get_loop_body (loop);
|
||
for (i = 0; i < loop->num_nodes; i++)
|
||
bitmap_set_bit (tovisit, bbs[i]->index);
|
||
free (bbs);
|
||
propagate_freq (loop->header, tovisit);
|
||
BITMAP_FREE (tovisit);
|
||
}
|
||
}
|
||
|
||
/* Propagates frequencies through structure of loops. */
|
||
|
||
static void
|
||
estimate_loops (void)
|
||
{
|
||
bitmap tovisit = BITMAP_ALLOC (NULL);
|
||
basic_block bb;
|
||
|
||
/* Start by estimating the frequencies in the loops. */
|
||
if (number_of_loops (cfun) > 1)
|
||
estimate_loops_at_level (current_loops->tree_root->inner);
|
||
|
||
/* Now propagate the frequencies through all the blocks. */
|
||
FOR_ALL_BB_FN (bb, cfun)
|
||
{
|
||
bitmap_set_bit (tovisit, bb->index);
|
||
}
|
||
propagate_freq (ENTRY_BLOCK_PTR_FOR_FN (cfun), tovisit);
|
||
BITMAP_FREE (tovisit);
|
||
}
|
||
|
||
/* Drop the profile for NODE to guessed, and update its frequency based on
|
||
whether it is expected to be hot given the CALL_COUNT. */
|
||
|
||
static void
|
||
drop_profile (struct cgraph_node *node, gcov_type call_count)
|
||
{
|
||
struct function *fn = DECL_STRUCT_FUNCTION (node->decl);
|
||
/* In the case where this was called by another function with a
|
||
dropped profile, call_count will be 0. Since there are no
|
||
non-zero call counts to this function, we don't know for sure
|
||
whether it is hot, and therefore it will be marked normal below. */
|
||
bool hot = maybe_hot_count_p (NULL, call_count);
|
||
|
||
if (dump_file)
|
||
fprintf (dump_file,
|
||
"Dropping 0 profile for %s/%i. %s based on calls.\n",
|
||
node->name (), node->order,
|
||
hot ? "Function is hot" : "Function is normal");
|
||
/* We only expect to miss profiles for functions that are reached
|
||
via non-zero call edges in cases where the function may have
|
||
been linked from another module or library (COMDATs and extern
|
||
templates). See the comments below for handle_missing_profiles.
|
||
Also, only warn in cases where the missing counts exceed the
|
||
number of training runs. In certain cases with an execv followed
|
||
by a no-return call the profile for the no-return call is not
|
||
dumped and there can be a mismatch. */
|
||
if (!DECL_COMDAT (node->decl) && !DECL_EXTERNAL (node->decl)
|
||
&& call_count > profile_info->runs)
|
||
{
|
||
if (flag_profile_correction)
|
||
{
|
||
if (dump_file)
|
||
fprintf (dump_file,
|
||
"Missing counts for called function %s/%i\n",
|
||
node->name (), node->order);
|
||
}
|
||
else
|
||
warning (0, "Missing counts for called function %s/%i",
|
||
node->name (), node->order);
|
||
}
|
||
|
||
profile_status_for_fn (fn)
|
||
= (flag_guess_branch_prob ? PROFILE_GUESSED : PROFILE_ABSENT);
|
||
node->frequency
|
||
= hot ? NODE_FREQUENCY_HOT : NODE_FREQUENCY_NORMAL;
|
||
}
|
||
|
||
/* In the case of COMDAT routines, multiple object files will contain the same
|
||
function and the linker will select one for the binary. In that case
|
||
all the other copies from the profile instrument binary will be missing
|
||
profile counts. Look for cases where this happened, due to non-zero
|
||
call counts going to 0-count functions, and drop the profile to guessed
|
||
so that we can use the estimated probabilities and avoid optimizing only
|
||
for size.
|
||
|
||
The other case where the profile may be missing is when the routine
|
||
is not going to be emitted to the object file, e.g. for "extern template"
|
||
class methods. Those will be marked DECL_EXTERNAL. Emit a warning in
|
||
all other cases of non-zero calls to 0-count functions. */
|
||
|
||
void
|
||
handle_missing_profiles (void)
|
||
{
|
||
struct cgraph_node *node;
|
||
int unlikely_count_fraction = PARAM_VALUE (UNLIKELY_BB_COUNT_FRACTION);
|
||
vec<struct cgraph_node *> worklist;
|
||
worklist.create (64);
|
||
|
||
/* See if 0 count function has non-0 count callers. In this case we
|
||
lost some profile. Drop its function profile to PROFILE_GUESSED. */
|
||
FOR_EACH_DEFINED_FUNCTION (node)
|
||
{
|
||
struct cgraph_edge *e;
|
||
gcov_type call_count = 0;
|
||
gcov_type max_tp_first_run = 0;
|
||
struct function *fn = DECL_STRUCT_FUNCTION (node->decl);
|
||
|
||
if (node->count)
|
||
continue;
|
||
for (e = node->callers; e; e = e->next_caller)
|
||
{
|
||
call_count += e->count;
|
||
|
||
if (e->caller->tp_first_run > max_tp_first_run)
|
||
max_tp_first_run = e->caller->tp_first_run;
|
||
}
|
||
|
||
/* If time profile is missing, let assign the maximum that comes from
|
||
caller functions. */
|
||
if (!node->tp_first_run && max_tp_first_run)
|
||
node->tp_first_run = max_tp_first_run + 1;
|
||
|
||
if (call_count
|
||
&& fn && fn->cfg
|
||
&& (call_count * unlikely_count_fraction >= profile_info->runs))
|
||
{
|
||
drop_profile (node, call_count);
|
||
worklist.safe_push (node);
|
||
}
|
||
}
|
||
|
||
/* Propagate the profile dropping to other 0-count COMDATs that are
|
||
potentially called by COMDATs we already dropped the profile on. */
|
||
while (worklist.length () > 0)
|
||
{
|
||
struct cgraph_edge *e;
|
||
|
||
node = worklist.pop ();
|
||
for (e = node->callees; e; e = e->next_caller)
|
||
{
|
||
struct cgraph_node *callee = e->callee;
|
||
struct function *fn = DECL_STRUCT_FUNCTION (callee->decl);
|
||
|
||
if (callee->count > 0)
|
||
continue;
|
||
if (DECL_COMDAT (callee->decl) && fn && fn->cfg
|
||
&& profile_status_for_fn (fn) == PROFILE_READ)
|
||
{
|
||
drop_profile (node, 0);
|
||
worklist.safe_push (callee);
|
||
}
|
||
}
|
||
}
|
||
worklist.release ();
|
||
}
|
||
|
||
/* Convert counts measured by profile driven feedback to frequencies.
|
||
Return nonzero iff there was any nonzero execution count. */
|
||
|
||
int
|
||
counts_to_freqs (void)
|
||
{
|
||
gcov_type count_max, true_count_max = 0;
|
||
basic_block bb;
|
||
|
||
/* Don't overwrite the estimated frequencies when the profile for
|
||
the function is missing. We may drop this function PROFILE_GUESSED
|
||
later in drop_profile (). */
|
||
if (!flag_auto_profile && !ENTRY_BLOCK_PTR_FOR_FN (cfun)->count)
|
||
return 0;
|
||
|
||
FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb)
|
||
true_count_max = MAX (bb->count, true_count_max);
|
||
|
||
count_max = MAX (true_count_max, 1);
|
||
FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb)
|
||
bb->frequency = (bb->count * BB_FREQ_MAX + count_max / 2) / count_max;
|
||
|
||
return true_count_max;
|
||
}
|
||
|
||
/* Return true if function is likely to be expensive, so there is no point to
|
||
optimize performance of prologue, epilogue or do inlining at the expense
|
||
of code size growth. THRESHOLD is the limit of number of instructions
|
||
function can execute at average to be still considered not expensive. */
|
||
|
||
bool
|
||
expensive_function_p (int threshold)
|
||
{
|
||
unsigned int sum = 0;
|
||
basic_block bb;
|
||
unsigned int limit;
|
||
|
||
/* We can not compute accurately for large thresholds due to scaled
|
||
frequencies. */
|
||
gcc_assert (threshold <= BB_FREQ_MAX);
|
||
|
||
/* Frequencies are out of range. This either means that function contains
|
||
internal loop executing more than BB_FREQ_MAX times or profile feedback
|
||
is available and function has not been executed at all. */
|
||
if (ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency == 0)
|
||
return true;
|
||
|
||
/* Maximally BB_FREQ_MAX^2 so overflow won't happen. */
|
||
limit = ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency * threshold;
|
||
FOR_EACH_BB_FN (bb, cfun)
|
||
{
|
||
rtx_insn *insn;
|
||
|
||
FOR_BB_INSNS (bb, insn)
|
||
if (active_insn_p (insn))
|
||
{
|
||
sum += bb->frequency;
|
||
if (sum > limit)
|
||
return true;
|
||
}
|
||
}
|
||
|
||
return false;
|
||
}
|
||
|
||
/* Estimate and propagate basic block frequencies using the given branch
|
||
probabilities. If FORCE is true, the frequencies are used to estimate
|
||
the counts even when there are already non-zero profile counts. */
|
||
|
||
void
|
||
estimate_bb_frequencies (bool force)
|
||
{
|
||
basic_block bb;
|
||
sreal freq_max;
|
||
|
||
if (force || profile_status_for_fn (cfun) != PROFILE_READ || !counts_to_freqs ())
|
||
{
|
||
static int real_values_initialized = 0;
|
||
|
||
if (!real_values_initialized)
|
||
{
|
||
real_values_initialized = 1;
|
||
real_br_prob_base = REG_BR_PROB_BASE;
|
||
real_bb_freq_max = BB_FREQ_MAX;
|
||
real_one_half = sreal (1, -1);
|
||
real_inv_br_prob_base = sreal (1) / real_br_prob_base;
|
||
real_almost_one = sreal (1) - real_inv_br_prob_base;
|
||
}
|
||
|
||
mark_dfs_back_edges ();
|
||
|
||
single_succ_edge (ENTRY_BLOCK_PTR_FOR_FN (cfun))->probability =
|
||
REG_BR_PROB_BASE;
|
||
|
||
/* Set up block info for each basic block. */
|
||
alloc_aux_for_blocks (sizeof (block_info));
|
||
alloc_aux_for_edges (sizeof (edge_prob_info));
|
||
FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb)
|
||
{
|
||
edge e;
|
||
edge_iterator ei;
|
||
|
||
FOR_EACH_EDGE (e, ei, bb->succs)
|
||
{
|
||
EDGE_INFO (e)->back_edge_prob = e->probability;
|
||
EDGE_INFO (e)->back_edge_prob *= real_inv_br_prob_base;
|
||
}
|
||
}
|
||
|
||
/* First compute frequencies locally for each loop from innermost
|
||
to outermost to examine frequencies for back edges. */
|
||
estimate_loops ();
|
||
|
||
freq_max = 0;
|
||
FOR_EACH_BB_FN (bb, cfun)
|
||
if (freq_max < BLOCK_INFO (bb)->frequency)
|
||
freq_max = BLOCK_INFO (bb)->frequency;
|
||
|
||
freq_max = real_bb_freq_max / freq_max;
|
||
FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb)
|
||
{
|
||
sreal tmp = BLOCK_INFO (bb)->frequency * freq_max + real_one_half;
|
||
bb->frequency = tmp.to_int ();
|
||
}
|
||
|
||
free_aux_for_blocks ();
|
||
free_aux_for_edges ();
|
||
}
|
||
compute_function_frequency ();
|
||
}
|
||
|
||
/* Decide whether function is hot, cold or unlikely executed. */
|
||
void
|
||
compute_function_frequency (void)
|
||
{
|
||
basic_block bb;
|
||
struct cgraph_node *node = cgraph_node::get (current_function_decl);
|
||
|
||
if (DECL_STATIC_CONSTRUCTOR (current_function_decl)
|
||
|| MAIN_NAME_P (DECL_NAME (current_function_decl)))
|
||
node->only_called_at_startup = true;
|
||
if (DECL_STATIC_DESTRUCTOR (current_function_decl))
|
||
node->only_called_at_exit = true;
|
||
|
||
if (profile_status_for_fn (cfun) != PROFILE_READ)
|
||
{
|
||
int flags = flags_from_decl_or_type (current_function_decl);
|
||
if (lookup_attribute ("cold", DECL_ATTRIBUTES (current_function_decl))
|
||
!= NULL)
|
||
node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED;
|
||
else if (lookup_attribute ("hot", DECL_ATTRIBUTES (current_function_decl))
|
||
!= NULL)
|
||
node->frequency = NODE_FREQUENCY_HOT;
|
||
else if (flags & ECF_NORETURN)
|
||
node->frequency = NODE_FREQUENCY_EXECUTED_ONCE;
|
||
else if (MAIN_NAME_P (DECL_NAME (current_function_decl)))
|
||
node->frequency = NODE_FREQUENCY_EXECUTED_ONCE;
|
||
else if (DECL_STATIC_CONSTRUCTOR (current_function_decl)
|
||
|| DECL_STATIC_DESTRUCTOR (current_function_decl))
|
||
node->frequency = NODE_FREQUENCY_EXECUTED_ONCE;
|
||
return;
|
||
}
|
||
|
||
/* Only first time try to drop function into unlikely executed.
|
||
After inlining the roundoff errors may confuse us.
|
||
Ipa-profile pass will drop functions only called from unlikely
|
||
functions to unlikely and that is most of what we care about. */
|
||
if (!cfun->after_inlining)
|
||
node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED;
|
||
FOR_EACH_BB_FN (bb, cfun)
|
||
{
|
||
if (maybe_hot_bb_p (cfun, bb))
|
||
{
|
||
node->frequency = NODE_FREQUENCY_HOT;
|
||
return;
|
||
}
|
||
if (!probably_never_executed_bb_p (cfun, bb))
|
||
node->frequency = NODE_FREQUENCY_NORMAL;
|
||
}
|
||
}
|
||
|
||
/* Build PREDICT_EXPR. */
|
||
tree
|
||
build_predict_expr (enum br_predictor predictor, enum prediction taken)
|
||
{
|
||
tree t = build1 (PREDICT_EXPR, void_type_node,
|
||
build_int_cst (integer_type_node, predictor));
|
||
SET_PREDICT_EXPR_OUTCOME (t, taken);
|
||
return t;
|
||
}
|
||
|
||
const char *
|
||
predictor_name (enum br_predictor predictor)
|
||
{
|
||
return predictor_info[predictor].name;
|
||
}
|
||
|
||
/* Predict branch probabilities and estimate profile of the tree CFG. */
|
||
|
||
namespace {
|
||
|
||
const pass_data pass_data_profile =
|
||
{
|
||
GIMPLE_PASS, /* type */
|
||
"profile_estimate", /* name */
|
||
OPTGROUP_NONE, /* optinfo_flags */
|
||
TV_BRANCH_PROB, /* tv_id */
|
||
PROP_cfg, /* properties_required */
|
||
0, /* properties_provided */
|
||
0, /* properties_destroyed */
|
||
0, /* todo_flags_start */
|
||
0, /* todo_flags_finish */
|
||
};
|
||
|
||
class pass_profile : public gimple_opt_pass
|
||
{
|
||
public:
|
||
pass_profile (gcc::context *ctxt)
|
||
: gimple_opt_pass (pass_data_profile, ctxt)
|
||
{}
|
||
|
||
/* opt_pass methods: */
|
||
virtual bool gate (function *) { return flag_guess_branch_prob; }
|
||
virtual unsigned int execute (function *);
|
||
|
||
}; // class pass_profile
|
||
|
||
unsigned int
|
||
pass_profile::execute (function *fun)
|
||
{
|
||
unsigned nb_loops;
|
||
|
||
if (profile_status_for_fn (cfun) == PROFILE_GUESSED)
|
||
return 0;
|
||
|
||
loop_optimizer_init (LOOPS_NORMAL);
|
||
if (dump_file && (dump_flags & TDF_DETAILS))
|
||
flow_loops_dump (dump_file, NULL, 0);
|
||
|
||
mark_irreducible_loops ();
|
||
|
||
nb_loops = number_of_loops (fun);
|
||
if (nb_loops > 1)
|
||
scev_initialize ();
|
||
|
||
tree_estimate_probability ();
|
||
|
||
if (nb_loops > 1)
|
||
scev_finalize ();
|
||
|
||
loop_optimizer_finalize ();
|
||
if (dump_file && (dump_flags & TDF_DETAILS))
|
||
gimple_dump_cfg (dump_file, dump_flags);
|
||
if (profile_status_for_fn (fun) == PROFILE_ABSENT)
|
||
profile_status_for_fn (fun) = PROFILE_GUESSED;
|
||
return 0;
|
||
}
|
||
|
||
} // anon namespace
|
||
|
||
gimple_opt_pass *
|
||
make_pass_profile (gcc::context *ctxt)
|
||
{
|
||
return new pass_profile (ctxt);
|
||
}
|
||
|
||
namespace {
|
||
|
||
const pass_data pass_data_strip_predict_hints =
|
||
{
|
||
GIMPLE_PASS, /* type */
|
||
"*strip_predict_hints", /* name */
|
||
OPTGROUP_NONE, /* optinfo_flags */
|
||
TV_BRANCH_PROB, /* tv_id */
|
||
PROP_cfg, /* properties_required */
|
||
0, /* properties_provided */
|
||
0, /* properties_destroyed */
|
||
0, /* todo_flags_start */
|
||
0, /* todo_flags_finish */
|
||
};
|
||
|
||
class pass_strip_predict_hints : public gimple_opt_pass
|
||
{
|
||
public:
|
||
pass_strip_predict_hints (gcc::context *ctxt)
|
||
: gimple_opt_pass (pass_data_strip_predict_hints, ctxt)
|
||
{}
|
||
|
||
/* opt_pass methods: */
|
||
opt_pass * clone () { return new pass_strip_predict_hints (m_ctxt); }
|
||
virtual unsigned int execute (function *);
|
||
|
||
}; // class pass_strip_predict_hints
|
||
|
||
/* Get rid of all builtin_expect calls and GIMPLE_PREDICT statements
|
||
we no longer need. */
|
||
unsigned int
|
||
pass_strip_predict_hints::execute (function *fun)
|
||
{
|
||
basic_block bb;
|
||
gimple ass_stmt;
|
||
tree var;
|
||
|
||
FOR_EACH_BB_FN (bb, fun)
|
||
{
|
||
gimple_stmt_iterator bi;
|
||
for (bi = gsi_start_bb (bb); !gsi_end_p (bi);)
|
||
{
|
||
gimple stmt = gsi_stmt (bi);
|
||
|
||
if (gimple_code (stmt) == GIMPLE_PREDICT)
|
||
{
|
||
gsi_remove (&bi, true);
|
||
continue;
|
||
}
|
||
else if (is_gimple_call (stmt))
|
||
{
|
||
tree fndecl = gimple_call_fndecl (stmt);
|
||
|
||
if ((fndecl
|
||
&& DECL_BUILT_IN_CLASS (fndecl) == BUILT_IN_NORMAL
|
||
&& DECL_FUNCTION_CODE (fndecl) == BUILT_IN_EXPECT
|
||
&& gimple_call_num_args (stmt) == 2)
|
||
|| (gimple_call_internal_p (stmt)
|
||
&& gimple_call_internal_fn (stmt) == IFN_BUILTIN_EXPECT))
|
||
{
|
||
var = gimple_call_lhs (stmt);
|
||
if (var)
|
||
{
|
||
ass_stmt
|
||
= gimple_build_assign (var, gimple_call_arg (stmt, 0));
|
||
gsi_replace (&bi, ass_stmt, true);
|
||
}
|
||
else
|
||
{
|
||
gsi_remove (&bi, true);
|
||
continue;
|
||
}
|
||
}
|
||
}
|
||
gsi_next (&bi);
|
||
}
|
||
}
|
||
return 0;
|
||
}
|
||
|
||
} // anon namespace
|
||
|
||
gimple_opt_pass *
|
||
make_pass_strip_predict_hints (gcc::context *ctxt)
|
||
{
|
||
return new pass_strip_predict_hints (ctxt);
|
||
}
|
||
|
||
/* Rebuild function frequencies. Passes are in general expected to
|
||
maintain profile by hand, however in some cases this is not possible:
|
||
for example when inlining several functions with loops freuqencies might run
|
||
out of scale and thus needs to be recomputed. */
|
||
|
||
void
|
||
rebuild_frequencies (void)
|
||
{
|
||
timevar_push (TV_REBUILD_FREQUENCIES);
|
||
|
||
/* When the max bb count in the function is small, there is a higher
|
||
chance that there were truncation errors in the integer scaling
|
||
of counts by inlining and other optimizations. This could lead
|
||
to incorrect classification of code as being cold when it isn't.
|
||
In that case, force the estimation of bb counts/frequencies from the
|
||
branch probabilities, rather than computing frequencies from counts,
|
||
which may also lead to frequencies incorrectly reduced to 0. There
|
||
is less precision in the probabilities, so we only do this for small
|
||
max counts. */
|
||
gcov_type count_max = 0;
|
||
basic_block bb;
|
||
FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb)
|
||
count_max = MAX (bb->count, count_max);
|
||
|
||
if (profile_status_for_fn (cfun) == PROFILE_GUESSED
|
||
|| (!flag_auto_profile && profile_status_for_fn (cfun) == PROFILE_READ
|
||
&& count_max < REG_BR_PROB_BASE/10))
|
||
{
|
||
loop_optimizer_init (0);
|
||
add_noreturn_fake_exit_edges ();
|
||
mark_irreducible_loops ();
|
||
connect_infinite_loops_to_exit ();
|
||
estimate_bb_frequencies (true);
|
||
remove_fake_exit_edges ();
|
||
loop_optimizer_finalize ();
|
||
}
|
||
else if (profile_status_for_fn (cfun) == PROFILE_READ)
|
||
counts_to_freqs ();
|
||
else
|
||
gcc_unreachable ();
|
||
timevar_pop (TV_REBUILD_FREQUENCIES);
|
||
}
|