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Diffstat (limited to 'gcc/predict.cc')
| -rw-r--r-- | gcc/predict.cc | 4566 |
1 files changed, 4566 insertions, 0 deletions
diff --git a/gcc/predict.cc b/gcc/predict.cc new file mode 100644 index 0000000..36046ab --- /dev/null +++ b/gcc/predict.cc @@ -0,0 +1,4566 @@ +/* Branch prediction routines for the GNU compiler. + Copyright (C) 2000-2022 Free Software Foundation, Inc. + +This file is part of GCC. + +GCC is free software; you can redistribute it and/or modify it under +the terms of the GNU General Public License as published by the Free +Software Foundation; either version 3, or (at your option) any later +version. + +GCC is distributed in the hope that it will be useful, but WITHOUT ANY +WARRANTY; without even the implied warranty of MERCHANTABILITY or +FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License +for more details. + +You should have received a copy of the GNU General Public License +along with GCC; see the file COPYING3. If not see +<http://www.gnu.org/licenses/>. */ + +/* References: + + [1] "Branch Prediction for Free" + Ball and Larus; PLDI '93. + [2] "Static Branch Frequency and Program Profile Analysis" + Wu and Larus; MICRO-27. + [3] "Corpus-based Static Branch Prediction" + Calder, Grunwald, Lindsay, Martin, Mozer, and Zorn; PLDI '95. */ + + +#include "config.h" +#include "system.h" +#include "coretypes.h" +#include "backend.h" +#include "rtl.h" +#include "tree.h" +#include "gimple.h" +#include "cfghooks.h" +#include "tree-pass.h" +#include "ssa.h" +#include "memmodel.h" +#include "emit-rtl.h" +#include "cgraph.h" +#include "coverage.h" +#include "diagnostic-core.h" +#include "gimple-predict.h" +#include "fold-const.h" +#include "calls.h" +#include "cfganal.h" +#include "profile.h" +#include "sreal.h" +#include "cfgloop.h" +#include "gimple-iterator.h" +#include "tree-cfg.h" +#include "tree-ssa-loop-niter.h" +#include "tree-ssa-loop.h" +#include "tree-scalar-evolution.h" +#include "ipa-utils.h" +#include "gimple-pretty-print.h" +#include "selftest.h" +#include "cfgrtl.h" +#include "stringpool.h" +#include "attribs.h" + +/* Enum with reasons why a predictor is ignored. */ + +enum predictor_reason +{ + REASON_NONE, + REASON_IGNORED, + REASON_SINGLE_EDGE_DUPLICATE, + REASON_EDGE_PAIR_DUPLICATE +}; + +/* String messages for the aforementioned enum. */ + +static const char *reason_messages[] = {"", " (ignored)", + " (single edge duplicate)", " (edge pair duplicate)"}; + + +static void combine_predictions_for_insn (rtx_insn *, basic_block); +static void dump_prediction (FILE *, enum br_predictor, int, basic_block, + enum predictor_reason, edge); +static void predict_paths_leading_to (basic_block, enum br_predictor, + enum prediction, + class loop *in_loop = NULL); +static void predict_paths_leading_to_edge (edge, enum br_predictor, + enum prediction, + class loop *in_loop = NULL); +static bool can_predict_insn_p (const rtx_insn *); +static HOST_WIDE_INT get_predictor_value (br_predictor, HOST_WIDE_INT); +static void determine_unlikely_bbs (); + +/* Information we hold about each branch predictor. + Filled using information from predict.def. */ + +struct predictor_info +{ + const char *const name; /* Name used in the debugging dumps. */ + const int hitrate; /* Expected hitrate used by + predict_insn_def call. */ + const int flags; +}; + +/* Use given predictor without Dempster-Shaffer theory if it matches + using first_match heuristics. */ +#define PRED_FLAG_FIRST_MATCH 1 + +/* Recompute hitrate in percent to our representation. */ + +#define HITRATE(VAL) ((int) ((VAL) * REG_BR_PROB_BASE + 50) / 100) + +#define DEF_PREDICTOR(ENUM, NAME, HITRATE, FLAGS) {NAME, HITRATE, FLAGS}, +static const struct predictor_info predictor_info[]= { +#include "predict.def" + + /* Upper bound on predictors. */ + {NULL, 0, 0} +}; +#undef DEF_PREDICTOR + +static gcov_type min_count = -1; + +/* Determine the threshold for hot BB counts. */ + +gcov_type +get_hot_bb_threshold () +{ + if (min_count == -1) + { + const int hot_frac = param_hot_bb_count_fraction; + const gcov_type min_hot_count + = hot_frac + ? profile_info->sum_max / hot_frac + : (gcov_type)profile_count::max_count; + set_hot_bb_threshold (min_hot_count); + if (dump_file) + fprintf (dump_file, "Setting hotness threshold to %" PRId64 ".\n", + min_hot_count); + } + return min_count; +} + +/* Set the threshold for hot BB counts. */ + +void +set_hot_bb_threshold (gcov_type min) +{ + min_count = min; +} + +/* Return TRUE if COUNT is considered to be hot in function FUN. */ + +bool +maybe_hot_count_p (struct function *fun, profile_count count) +{ + if (!count.initialized_p ()) + return true; + if (count.ipa () == profile_count::zero ()) + return false; + if (!count.ipa_p ()) + { + struct cgraph_node *node = cgraph_node::get (fun->decl); + if (!profile_info || profile_status_for_fn (fun) != PROFILE_READ) + { + if (node->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED) + return false; + if (node->frequency == NODE_FREQUENCY_HOT) + return true; + } + if (profile_status_for_fn (fun) == PROFILE_ABSENT) + return true; + if (node->frequency == NODE_FREQUENCY_EXECUTED_ONCE + && count < (ENTRY_BLOCK_PTR_FOR_FN (fun)->count.apply_scale (2, 3))) + return false; + if (count.apply_scale (param_hot_bb_frequency_fraction, 1) + < ENTRY_BLOCK_PTR_FOR_FN (fun)->count) + return false; + return true; + } + /* Code executed at most once is not hot. */ + if (count <= MAX (profile_info ? profile_info->runs : 1, 1)) + return false; + return (count >= get_hot_bb_threshold ()); +} + +/* Return true if basic block BB of function FUN can be CPU intensive + and should thus be optimized for maximum performance. */ + +bool +maybe_hot_bb_p (struct function *fun, const_basic_block bb) +{ + gcc_checking_assert (fun); + return maybe_hot_count_p (fun, bb->count); +} + +/* Return true if edge E can be CPU intensive and should thus be optimized + for maximum performance. */ + +bool +maybe_hot_edge_p (edge e) +{ + return maybe_hot_count_p (cfun, e->count ()); +} + +/* Return true if COUNT is considered to be never executed in function FUN + or if function FUN is considered so in the static profile. */ + +static bool +probably_never_executed (struct function *fun, profile_count count) +{ + gcc_checking_assert (fun); + if (count.ipa () == profile_count::zero ()) + return true; + /* Do not trust adjusted counts. This will make us to drop int cold section + code with low execution count as a result of inlining. These low counts + are not safe even with read profile and may lead us to dropping + code which actually gets executed into cold section of binary that is not + desirable. */ + if (count.precise_p () && profile_status_for_fn (fun) == PROFILE_READ) + { + const int unlikely_frac = param_unlikely_bb_count_fraction; + if (count.apply_scale (unlikely_frac, 1) >= profile_info->runs) + return false; + return true; + } + if ((!profile_info || profile_status_for_fn (fun) != PROFILE_READ) + && (cgraph_node::get (fun->decl)->frequency + == NODE_FREQUENCY_UNLIKELY_EXECUTED)) + return true; + return false; +} + +/* Return true if basic block BB of function FUN is probably never executed. */ + +bool +probably_never_executed_bb_p (struct function *fun, const_basic_block bb) +{ + return probably_never_executed (fun, bb->count); +} + +/* Return true if edge E is unlikely executed for obvious reasons. */ + +static bool +unlikely_executed_edge_p (edge e) +{ + return (e->src->count == profile_count::zero () + || e->probability == profile_probability::never ()) + || (e->flags & (EDGE_EH | EDGE_FAKE)); +} + +/* Return true if edge E of function FUN is probably never executed. */ + +bool +probably_never_executed_edge_p (struct function *fun, edge e) +{ + if (unlikely_executed_edge_p (e)) + return true; + return probably_never_executed (fun, e->count ()); +} + +/* Return true if function FUN should always be optimized for size. */ + +optimize_size_level +optimize_function_for_size_p (struct function *fun) +{ + if (!fun || !fun->decl) + return optimize_size ? OPTIMIZE_SIZE_MAX : OPTIMIZE_SIZE_NO; + cgraph_node *n = cgraph_node::get (fun->decl); + if (n) + return n->optimize_for_size_p (); + return OPTIMIZE_SIZE_NO; +} + +/* Return true if function FUN should always be optimized for speed. */ + +bool +optimize_function_for_speed_p (struct function *fun) +{ + return !optimize_function_for_size_p (fun); +} + +/* Return the optimization type that should be used for function FUN. */ + +optimization_type +function_optimization_type (struct function *fun) +{ + return (optimize_function_for_speed_p (fun) + ? OPTIMIZE_FOR_SPEED + : OPTIMIZE_FOR_SIZE); +} + +/* Return TRUE if basic block BB should be optimized for size. */ + +optimize_size_level +optimize_bb_for_size_p (const_basic_block bb) +{ + enum optimize_size_level ret = optimize_function_for_size_p (cfun); + + if (bb && ret < OPTIMIZE_SIZE_MAX && bb->count == profile_count::zero ()) + ret = OPTIMIZE_SIZE_MAX; + if (bb && ret < OPTIMIZE_SIZE_BALANCED && !maybe_hot_bb_p (cfun, bb)) + ret = OPTIMIZE_SIZE_BALANCED; + return ret; +} + +/* Return TRUE if basic block BB should be optimized for speed. */ + +bool +optimize_bb_for_speed_p (const_basic_block bb) +{ + return !optimize_bb_for_size_p (bb); +} + +/* Return the optimization type that should be used for basic block BB. */ + +optimization_type +bb_optimization_type (const_basic_block bb) +{ + return (optimize_bb_for_speed_p (bb) + ? OPTIMIZE_FOR_SPEED + : OPTIMIZE_FOR_SIZE); +} + +/* Return TRUE if edge E should be optimized for size. */ + +optimize_size_level +optimize_edge_for_size_p (edge e) +{ + enum optimize_size_level ret = optimize_function_for_size_p (cfun); + + if (ret < OPTIMIZE_SIZE_MAX && unlikely_executed_edge_p (e)) + ret = OPTIMIZE_SIZE_MAX; + if (ret < OPTIMIZE_SIZE_BALANCED && !maybe_hot_edge_p (e)) + ret = OPTIMIZE_SIZE_BALANCED; + return ret; +} + +/* Return TRUE if edge E should be optimized for speed. */ + +bool +optimize_edge_for_speed_p (edge e) +{ + return !optimize_edge_for_size_p (e); +} + +/* Return TRUE if the current function is optimized for size. */ + +optimize_size_level +optimize_insn_for_size_p (void) +{ + enum optimize_size_level ret = optimize_function_for_size_p (cfun); + if (ret < OPTIMIZE_SIZE_BALANCED && !crtl->maybe_hot_insn_p) + ret = OPTIMIZE_SIZE_BALANCED; + return ret; +} + +/* Return TRUE if the current function is optimized for speed. */ + +bool +optimize_insn_for_speed_p (void) +{ + return !optimize_insn_for_size_p (); +} + +/* Return TRUE if LOOP should be optimized for size. */ + +optimize_size_level +optimize_loop_for_size_p (class loop *loop) +{ + return optimize_bb_for_size_p (loop->header); +} + +/* Return TRUE if LOOP should be optimized for speed. */ + +bool +optimize_loop_for_speed_p (class loop *loop) +{ + return optimize_bb_for_speed_p (loop->header); +} + +/* Return TRUE if nest rooted at LOOP should be optimized for speed. */ + +bool +optimize_loop_nest_for_speed_p (class loop *loop) +{ + class loop *l = loop; + if (optimize_loop_for_speed_p (loop)) + return true; + l = loop->inner; + while (l && l != loop) + { + if (optimize_loop_for_speed_p (l)) + return true; + if (l->inner) + l = l->inner; + else if (l->next) + l = l->next; + else + { + while (l != loop && !l->next) + l = loop_outer (l); + if (l != loop) + l = l->next; + } + } + return false; +} + +/* Return TRUE if nest rooted at LOOP should be optimized for size. */ + +optimize_size_level +optimize_loop_nest_for_size_p (class loop *loop) +{ + enum optimize_size_level ret = optimize_loop_for_size_p (loop); + class loop *l = loop; + + l = loop->inner; + while (l && l != loop) + { + if (ret == OPTIMIZE_SIZE_NO) + break; + ret = MIN (optimize_loop_for_size_p (l), ret); + if (l->inner) + l = l->inner; + else if (l->next) + l = l->next; + else + { + while (l != loop && !l->next) + l = loop_outer (l); + if (l != loop) + l = l->next; + } + } + return ret; +} + +/* Return true if edge E is likely to be well predictable by branch + predictor. */ + +bool +predictable_edge_p (edge e) +{ + if (!e->probability.initialized_p ()) + return false; + if ((e->probability.to_reg_br_prob_base () + <= param_predictable_branch_outcome * REG_BR_PROB_BASE / 100) + || (REG_BR_PROB_BASE - e->probability.to_reg_br_prob_base () + <= param_predictable_branch_outcome * REG_BR_PROB_BASE / 100)) + return true; + return false; +} + + +/* Set RTL expansion for BB profile. */ + +void +rtl_profile_for_bb (basic_block bb) +{ + crtl->maybe_hot_insn_p = maybe_hot_bb_p (cfun, bb); +} + +/* Set RTL expansion for edge profile. */ + +void +rtl_profile_for_edge (edge e) +{ + crtl->maybe_hot_insn_p = maybe_hot_edge_p (e); +} + +/* Set RTL expansion to default mode (i.e. when profile info is not known). */ +void +default_rtl_profile (void) +{ + crtl->maybe_hot_insn_p = true; +} + +/* Return true if the one of outgoing edges is already predicted by + PREDICTOR. */ + +bool +rtl_predicted_by_p (const_basic_block bb, enum br_predictor predictor) +{ + rtx note; + if (!INSN_P (BB_END (bb))) + return false; + for (note = REG_NOTES (BB_END (bb)); note; note = XEXP (note, 1)) + if (REG_NOTE_KIND (note) == REG_BR_PRED + && INTVAL (XEXP (XEXP (note, 0), 0)) == (int)predictor) + return true; + return false; +} + +/* Structure representing predictions in tree level. */ + +struct edge_prediction { + struct edge_prediction *ep_next; + edge ep_edge; + enum br_predictor ep_predictor; + int ep_probability; +}; + +/* This map contains for a basic block the list of predictions for the + outgoing edges. */ + +static hash_map<const_basic_block, edge_prediction *> *bb_predictions; + +/* Return true if the one of outgoing edges is already predicted by + PREDICTOR. */ + +bool +gimple_predicted_by_p (const_basic_block bb, enum br_predictor predictor) +{ + struct edge_prediction *i; + edge_prediction **preds = bb_predictions->get (bb); + + if (!preds) + return false; + + for (i = *preds; i; i = i->ep_next) + if (i->ep_predictor == predictor) + return true; + return false; +} + +/* Return true if the one of outgoing edges is already predicted by + PREDICTOR for edge E predicted as TAKEN. */ + +bool +edge_predicted_by_p (edge e, enum br_predictor predictor, bool taken) +{ + struct edge_prediction *i; + basic_block bb = e->src; + edge_prediction **preds = bb_predictions->get (bb); + if (!preds) + return false; + + int probability = predictor_info[(int) predictor].hitrate; + + if (taken != TAKEN) + probability = REG_BR_PROB_BASE - probability; + + for (i = *preds; i; i = i->ep_next) + if (i->ep_predictor == predictor + && i->ep_edge == e + && i->ep_probability == probability) + return true; + return false; +} + +/* Same predicate as above, working on edges. */ +bool +edge_probability_reliable_p (const_edge e) +{ + return e->probability.probably_reliable_p (); +} + +/* 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 profile_probability::from_reg_br_prob_note + (XINT (note, 0)).probably_reliable_p (); +} + +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; + gcc_assert (probability != PROB_UNINITIALIZED); + + 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) +{ + 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; + } +} + +/* Filter edge predictions PREDS by a function FILTER: if FILTER return false + the prediction is removed. + DATA are passed to the filter function. */ + +static void +filter_predictions (edge_prediction **preds, + bool (*filter) (edge_prediction *, void *), void *data) +{ + if (!bb_predictions) + return; + + if (preds) + { + struct edge_prediction **prediction = preds; + struct edge_prediction *next; + + while (*prediction) + { + if ((*filter) (*prediction, data)) + prediction = &((*prediction)->ep_next); + else + { + next = (*prediction)->ep_next; + free (*prediction); + *prediction = next; + } + } + } +} + +/* Filter function predicate that returns true for a edge predicate P + if its edge is equal to DATA. */ + +static bool +not_equal_edge_p (edge_prediction *p, void *data) +{ + return p->ep_edge != (edge)data; +} + +/* 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); + filter_predictions (preds, not_equal_edge_p, e); +} + +/* 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) = profile_probability::from_reg_br_prob_note + (XINT (note, 0)).invert ().to_reg_br_prob_note (); + 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, enum predictor_reason reason = REASON_NONE, + edge ep_edge = NULL) +{ + edge e = ep_edge; + edge_iterator ei; + + if (!file) + return; + + if (e == NULL) + FOR_EACH_EDGE (e, ei, bb->succs) + if (! (e->flags & EDGE_FALLTHRU)) + break; + + char edge_info_str[128]; + if (ep_edge) + sprintf (edge_info_str, " of edge %d->%d", ep_edge->src->index, + ep_edge->dest->index); + else + edge_info_str[0] = '\0'; + + fprintf (file, " %s heuristics%s%s: %.2f%%", + predictor_info[predictor].name, + edge_info_str, reason_messages[reason], + probability * 100.0 / REG_BR_PROB_BASE); + + if (bb->count.initialized_p ()) + { + fprintf (file, " exec "); + bb->count.dump (file); + if (e) + { + fprintf (file, " hit "); + e->count ().dump (file); + fprintf (file, " (%.1f%%)", e->count ().to_gcov_type() * 100.0 + / bb->count.to_gcov_type ()); + } + } + + fprintf (file, "\n"); + + /* Print output that be easily read by analyze_brprob.py script. We are + interested only in counts that are read from GCDA files. */ + if (dump_file && (dump_flags & TDF_DETAILS) + && bb->count.precise_p () + && reason == REASON_NONE) + { + fprintf (file, ";;heuristics;%s;%" PRId64 ";%" PRId64 ";%.1f;\n", + predictor_info[predictor].name, + bb->count.to_gcov_type (), e->count ().to_gcov_type (), + probability * 100.0 / REG_BR_PROB_BASE); + } +} + +/* Return true if STMT is known to be unlikely executed. */ + +static bool +unlikely_executed_stmt_p (gimple *stmt) +{ + if (!is_gimple_call (stmt)) + return false; + /* NORETURN attribute alone is not strong enough: exit() may be quite + likely executed once during program run. */ + if (gimple_call_fntype (stmt) + && lookup_attribute ("cold", + TYPE_ATTRIBUTES (gimple_call_fntype (stmt))) + && !lookup_attribute ("cold", DECL_ATTRIBUTES (current_function_decl))) + return true; + tree decl = gimple_call_fndecl (stmt); + if (!decl) + return false; + if (lookup_attribute ("cold", DECL_ATTRIBUTES (decl)) + && !lookup_attribute ("cold", DECL_ATTRIBUTES (current_function_decl))) + return true; + + cgraph_node *n = cgraph_node::get (decl); + if (!n) + return false; + + availability avail; + n = n->ultimate_alias_target (&avail); + if (avail < AVAIL_AVAILABLE) + return false; + if (!n->analyzed + || n->decl == current_function_decl) + return false; + return n->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED; +} + +/* Return true if BB is unlikely executed. */ + +static bool +unlikely_executed_bb_p (basic_block bb) +{ + if (bb->count == profile_count::zero ()) + return true; + if (bb == ENTRY_BLOCK_PTR_FOR_FN (cfun) || bb == EXIT_BLOCK_PTR_FOR_FN (cfun)) + return false; + for (gimple_stmt_iterator gsi = gsi_start_bb (bb); + !gsi_end_p (gsi); gsi_next (&gsi)) + { + if (unlikely_executed_stmt_p (gsi_stmt (gsi))) + return true; + if (stmt_can_terminate_bb_p (gsi_stmt (gsi))) + return false; + } + return false; +} + +/* We cannot predict the probabilities of outgoing edges of bb. Set them + evenly and hope for the best. If UNLIKELY_EDGES is not null, distribute + even probability for all edges not mentioned in the set. These edges + are given PROB_VERY_UNLIKELY probability. Similarly for LIKELY_EDGES, + if we have exactly one likely edge, make the other edges predicted + as not probable. */ + +static void +set_even_probabilities (basic_block bb, + hash_set<edge> *unlikely_edges = NULL, + hash_set<edge_prediction *> *likely_edges = NULL) +{ + unsigned nedges = 0, unlikely_count = 0; + edge e = NULL; + edge_iterator ei; + profile_probability all = profile_probability::always (); + + FOR_EACH_EDGE (e, ei, bb->succs) + if (e->probability.initialized_p ()) + all -= e->probability; + else if (!unlikely_executed_edge_p (e)) + { + nedges++; + if (unlikely_edges != NULL && unlikely_edges->contains (e)) + { + all -= profile_probability::very_unlikely (); + unlikely_count++; + } + } + + /* Make the distribution even if all edges are unlikely. */ + unsigned likely_count = likely_edges ? likely_edges->elements () : 0; + if (unlikely_count == nedges) + { + unlikely_edges = NULL; + unlikely_count = 0; + } + + /* If we have one likely edge, then use its probability and distribute + remaining probabilities as even. */ + if (likely_count == 1) + { + FOR_EACH_EDGE (e, ei, bb->succs) + if (e->probability.initialized_p ()) + ; + else if (!unlikely_executed_edge_p (e)) + { + edge_prediction *prediction = *likely_edges->begin (); + int p = prediction->ep_probability; + profile_probability prob + = profile_probability::from_reg_br_prob_base (p); + + if (prediction->ep_edge == e) + e->probability = prob; + else if (unlikely_edges != NULL && unlikely_edges->contains (e)) + e->probability = profile_probability::very_unlikely (); + else + { + profile_probability remainder = prob.invert (); + remainder -= profile_probability::very_unlikely () + .apply_scale (unlikely_count, 1); + int count = nedges - unlikely_count - 1; + gcc_assert (count >= 0); + + e->probability = remainder.apply_scale (1, count); + } + } + else + e->probability = profile_probability::never (); + } + else + { + /* Make all unlikely edges unlikely and the rest will have even + probability. */ + unsigned scale = nedges - unlikely_count; + FOR_EACH_EDGE (e, ei, bb->succs) + if (e->probability.initialized_p ()) + ; + else if (!unlikely_executed_edge_p (e)) + { + if (unlikely_edges != NULL && unlikely_edges->contains (e)) + e->probability = profile_probability::very_unlikely (); + else + e->probability = all.apply_scale (1, scale); + } + else + e->probability = profile_probability::never (); + } +} + +/* Add REG_BR_PROB note to JUMP with PROB. */ + +void +add_reg_br_prob_note (rtx_insn *jump, profile_probability prob) +{ + gcc_checking_assert (JUMP_P (jump) && !find_reg_note (jump, REG_BR_PROB, 0)); + add_int_reg_note (jump, REG_BR_PROB, prob.to_reg_br_prob_note ()); +} + +/* 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 + && predictor_info[predictor].flags & PRED_FLAG_FIRST_MATCH) + 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 (best_predictor != END_PREDICTORS) + first_match = true; + + if (!found) + dump_prediction (dump_file, PRED_NO_PREDICTION, + combined_probability, bb); + else + { + if (!first_match) + dump_prediction (dump_file, PRED_DS_THEORY, combined_probability, + bb, !first_match ? REASON_NONE : REASON_IGNORED); + else + dump_prediction (dump_file, PRED_FIRST_MATCH, best_probability, + bb, first_match ? REASON_NONE : REASON_IGNORED); + } + + if (first_match) + combined_probability = best_probability; + dump_prediction (dump_file, PRED_COMBINED, combined_probability, bb); + + 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) + ? REASON_NONE : REASON_IGNORED); + *pnote = XEXP (*pnote, 1); + } + else + pnote = &XEXP (*pnote, 1); + } + + if (!prob_note) + { + profile_probability p + = profile_probability::from_reg_br_prob_base (combined_probability); + add_reg_br_prob_note (insn, p); + + /* Save the prediction into CFG in case we are seeing non-degenerated + conditional jump. */ + if (!single_succ_p (bb)) + { + BRANCH_EDGE (bb)->probability = p; + FALLTHRU_EDGE (bb)->probability + = BRANCH_EDGE (bb)->probability.invert (); + } + } + else if (!single_succ_p (bb)) + { + profile_probability prob = profile_probability::from_reg_br_prob_note + (XINT (prob_note, 0)); + + BRANCH_EDGE (bb)->probability = prob; + FALLTHRU_EDGE (bb)->probability = prob.invert (); + } + else + single_succ_edge (bb)->probability = profile_probability::always (); +} + +/* Edge prediction hash traits. */ + +struct predictor_hash: pointer_hash <edge_prediction> +{ + + static inline hashval_t hash (const edge_prediction *); + static inline bool equal (const edge_prediction *, const edge_prediction *); +}; + +/* Calculate hash value of an edge prediction P based on predictor and + normalized probability. */ + +inline hashval_t +predictor_hash::hash (const edge_prediction *p) +{ + inchash::hash hstate; + hstate.add_int (p->ep_predictor); + + int prob = p->ep_probability; + if (prob > REG_BR_PROB_BASE / 2) + prob = REG_BR_PROB_BASE - prob; + + hstate.add_int (prob); + + return hstate.end (); +} + +/* Return true whether edge predictions P1 and P2 use the same predictor and + have equal (or opposed probability). */ + +inline bool +predictor_hash::equal (const edge_prediction *p1, const edge_prediction *p2) +{ + return (p1->ep_predictor == p2->ep_predictor + && (p1->ep_probability == p2->ep_probability + || p1->ep_probability == REG_BR_PROB_BASE - p2->ep_probability)); +} + +struct predictor_hash_traits: predictor_hash, + typed_noop_remove <edge_prediction *> {}; + +/* Return true if edge prediction P is not in DATA hash set. */ + +static bool +not_removed_prediction_p (edge_prediction *p, void *data) +{ + hash_set<edge_prediction *> *remove = (hash_set<edge_prediction *> *) data; + return !remove->contains (p); +} + +/* Prune predictions for a basic block BB. Currently we do following + clean-up steps: + + 1) remove duplicate prediction that is guessed with the same probability + (different than 1/2) to both edge + 2) remove duplicates for a prediction that belongs with the same probability + to a single edge + + */ + +static void +prune_predictions_for_bb (basic_block bb) +{ + edge_prediction **preds = bb_predictions->get (bb); + + if (preds) + { + hash_table <predictor_hash_traits> s (13); + hash_set <edge_prediction *> remove; + + /* Step 1: identify predictors that should be removed. */ + for (edge_prediction *pred = *preds; pred; pred = pred->ep_next) + { + edge_prediction *existing = s.find (pred); + if (existing) + { + if (pred->ep_edge == existing->ep_edge + && pred->ep_probability == existing->ep_probability) + { + /* Remove a duplicate predictor. */ + dump_prediction (dump_file, pred->ep_predictor, + pred->ep_probability, bb, + REASON_SINGLE_EDGE_DUPLICATE, pred->ep_edge); + + remove.add (pred); + } + else if (pred->ep_edge != existing->ep_edge + && pred->ep_probability == existing->ep_probability + && pred->ep_probability != REG_BR_PROB_BASE / 2) + { + /* Remove both predictors as they predict the same + for both edges. */ + dump_prediction (dump_file, existing->ep_predictor, + pred->ep_probability, bb, + REASON_EDGE_PAIR_DUPLICATE, + existing->ep_edge); + dump_prediction (dump_file, pred->ep_predictor, + pred->ep_probability, bb, + REASON_EDGE_PAIR_DUPLICATE, + pred->ep_edge); + + remove.add (existing); + remove.add (pred); + } + } + + edge_prediction **slot2 = s.find_slot (pred, INSERT); + *slot2 = pred; + } + + /* Step 2: Remove predictors. */ + filter_predictions (preds, not_removed_prediction_p, &remove); + } +} + +/* Combine predictions into single probability and store them into CFG. + Remove now useless prediction entries. + If DRY_RUN is set, only produce dumps and do not modify profile. */ + +static void +combine_predictions_for_bb (basic_block bb, bool dry_run) +{ + 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; + int nzero = 0; + int nunknown = 0; + + FOR_EACH_EDGE (e, ei, bb->succs) + { + if (!unlikely_executed_edge_p (e)) + { + nedges ++; + if (first && !second) + second = e; + if (!first) + first = e; + } + else if (!e->probability.initialized_p ()) + e->probability = profile_probability::never (); + if (!e->probability.initialized_p ()) + nunknown++; + else if (e->probability == profile_probability::never ()) + nzero++; + } + + /* When there is no successor or only one choice, prediction is easy. + + When we have a basic block with more than 2 successors, the situation + is more complicated as DS theory cannot be used literally. + More precisely, let's assume we predicted edge e1 with probability p1, + thus: m1({b1}) = p1. As we're going to combine more than 2 edges, we + need to find probability of e.g. m1({b2}), which we don't know. + The only approximation is to equally distribute 1-p1 to all edges + different from b1. + + According to numbers we've got from SPEC2006 benchark, there's only + one interesting reliable predictor (noreturn call), which can be + handled with a bit easier approach. */ + if (nedges != 2) + { + hash_set<edge> unlikely_edges (4); + hash_set<edge_prediction *> likely_edges (4); + + /* Identify all edges that have a probability close to very unlikely. + Doing the approach for very unlikely doesn't worth for doing as + there's no such probability in SPEC2006 benchmark. */ + edge_prediction **preds = bb_predictions->get (bb); + if (preds) + for (pred = *preds; pred; pred = pred->ep_next) + { + if (pred->ep_probability <= PROB_VERY_UNLIKELY + || pred->ep_predictor == PRED_COLD_LABEL) + unlikely_edges.add (pred->ep_edge); + else if (pred->ep_probability >= PROB_VERY_LIKELY + || pred->ep_predictor == PRED_BUILTIN_EXPECT + || pred->ep_predictor == PRED_HOT_LABEL) + likely_edges.add (pred); + } + + /* It can happen that an edge is both in likely_edges and unlikely_edges. + Clear both sets in that situation. */ + for (hash_set<edge_prediction *>::iterator it = likely_edges.begin (); + it != likely_edges.end (); ++it) + if (unlikely_edges.contains ((*it)->ep_edge)) + { + likely_edges.empty (); + unlikely_edges.empty (); + break; + } + + if (!dry_run) + set_even_probabilities (bb, &unlikely_edges, &likely_edges); + clear_bb_predictions (bb); + if (dump_file) + { + fprintf (dump_file, "Predictions for bb %i\n", bb->index); + if (unlikely_edges.is_empty ()) + fprintf (dump_file, + "%i edges in bb %i predicted to even probabilities\n", + nedges, bb->index); + else + { + fprintf (dump_file, + "%i edges in bb %i predicted with some unlikely edges\n", + nedges, bb->index); + FOR_EACH_EDGE (e, ei, bb->succs) + if (!unlikely_executed_edge_p (e)) + dump_prediction (dump_file, PRED_COMBINED, + e->probability.to_reg_br_prob_base (), bb, REASON_NONE, e); + } + } + return; + } + + if (dump_file) + fprintf (dump_file, "Predictions for bb %i\n", bb->index); + + prune_predictions_for_bb (bb); + + 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 + && predictor_info[predictor].flags & PRED_FLAG_FIRST_MATCH) + { + 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 = pred2->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 (best_predictor != END_PREDICTORS) + first_match = true; + + if (!found) + dump_prediction (dump_file, PRED_NO_PREDICTION, combined_probability, bb); + else + { + if (!first_match) + dump_prediction (dump_file, PRED_DS_THEORY, combined_probability, bb, + !first_match ? REASON_NONE : REASON_IGNORED); + else + dump_prediction (dump_file, PRED_FIRST_MATCH, best_probability, bb, + first_match ? REASON_NONE : REASON_IGNORED); + } + + if (first_match) + combined_probability = best_probability; + dump_prediction (dump_file, PRED_COMBINED, combined_probability, bb); + + 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; + + dump_prediction (dump_file, predictor, probability, bb, + (!first_match || best_predictor == predictor) + ? REASON_NONE : REASON_IGNORED, pred->ep_edge); + } + } + clear_bb_predictions (bb); + + + /* If we have only one successor which is unknown, we can compute missing + probability. */ + if (nunknown == 1) + { + profile_probability prob = profile_probability::always (); + edge missing = NULL; + + FOR_EACH_EDGE (e, ei, bb->succs) + if (e->probability.initialized_p ()) + prob -= e->probability; + else if (missing == NULL) + missing = e; + else + gcc_unreachable (); + missing->probability = prob; + } + /* If nothing is unknown, we have nothing to update. */ + else if (!nunknown && nzero != (int)EDGE_COUNT (bb->succs)) + ; + else if (!dry_run) + { + first->probability + = profile_probability::from_reg_br_prob_base (combined_probability); + second->probability = first->probability.invert (); + } +} + +/* 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, class 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; +} + +/* Return true if E is predicted by one of loop heuristics. */ + +static bool +predicted_by_loop_heuristics_p (basic_block bb) +{ + struct edge_prediction *i; + edge_prediction **preds = bb_predictions->get (bb); + + if (!preds) + return false; + + for (i = *preds; i; i = i->ep_next) + if (i->ep_predictor == PRED_LOOP_ITERATIONS_GUESSED + || i->ep_predictor == PRED_LOOP_ITERATIONS_MAX + || i->ep_predictor == PRED_LOOP_ITERATIONS + || i->ep_predictor == PRED_LOOP_EXIT + || i->ep_predictor == PRED_LOOP_EXIT_WITH_RECURSION + || i->ep_predictor == PRED_LOOP_EXTRA_EXIT) + return true; + 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 (class 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_loop_heuristics_p (bb)) + 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; + wi::overflow_type overflow; + bool 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 (); + } + + /* FIXME: The branch prediction seems broken. It has only 20% hitrate. */ + 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_EXTRA_EXIT. */ + +static void +predict_extra_loop_exits (class loop *loop, 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_EXTRA_EXIT, NOT_TAKEN, + loop); + continue; + } + + FOR_EACH_EDGE (e1, ei, e->src->preds) + predict_paths_leading_to_edge (e1, PRED_LOOP_EXTRA_EXIT, NOT_TAKEN, + loop); + } +} + + +/* Predict edge probabilities by exploiting loop structure. */ + +static void +predict_loops (void) +{ + basic_block bb; + hash_set <class loop *> with_recursion(10); + + FOR_EACH_BB_FN (bb, cfun) + { + gimple_stmt_iterator gsi; + tree decl; + + for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi)) + if (is_gimple_call (gsi_stmt (gsi)) + && (decl = gimple_call_fndecl (gsi_stmt (gsi))) != NULL + && recursive_call_p (current_function_decl, decl)) + { + class loop *loop = bb->loop_father; + while (loop && !with_recursion.add (loop)) + loop = loop_outer (loop); + } + } + + /* Try to predict out blocks in a loop that are not part of a + natural loop. */ + for (auto loop : loops_list (cfun, LI_FROM_INNERMOST)) + { + basic_block bb, *bbs; + unsigned j, n_exits = 0; + class tree_niter_desc niter_desc; + edge ex; + class 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; + bool recursion = with_recursion.contains (loop); + + auto_vec<edge> exits = get_loop_exit_edges (loop); + FOR_EACH_VEC_ELT (exits, j, ex) + if (!unlikely_executed_edge_p (ex) && !(ex->flags & EDGE_ABNORMAL_CALL)) + n_exits ++; + if (!n_exits) + continue; + + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Predicting loop %i%s with %i exits.\n", + loop->num, recursion ? " (with recursion)":"", n_exits); + if (dump_file && (dump_flags & TDF_DETAILS) + && max_loop_iterations_int (loop) >= 0) + { + fprintf (dump_file, + "Loop %d iterates at most %i times.\n", loop->num, + (int)max_loop_iterations_int (loop)); + } + if (dump_file && (dump_flags & TDF_DETAILS) + && likely_max_loop_iterations_int (loop) >= 0) + { + fprintf (dump_file, "Loop %d likely iterates at most %i times.\n", + loop->num, (int)likely_max_loop_iterations_int (loop)); + } + + FOR_EACH_VEC_ELT (exits, j, ex) + { + tree niter = NULL; + HOST_WIDE_INT nitercst; + int max = param_max_predicted_iterations; + int probability; + enum br_predictor predictor; + widest_int nit; + + if (unlikely_executed_edge_p (ex) + || (ex->flags & EDGE_ABNORMAL_CALL)) + continue; + /* Loop heuristics do not expect exit conditional to be inside + inner loop. We predict from innermost to outermost loop. */ + if (predicted_by_loop_heuristics_p (ex->src)) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Skipping exit %i->%i because " + "it is already predicted.\n", + ex->src->index, ex->dest->index); + continue; + } + predict_extra_loop_exits (loop, 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 (dump_file && (dump_flags & TDF_DETAILS) + && TREE_CODE (niter) == INTEGER_CST) + { + fprintf (dump_file, "Exit %i->%i %d iterates ", + ex->src->index, ex->dest->index, + loop->num); + print_generic_expr (dump_file, niter, TDF_SLIM); + fprintf (dump_file, " times.\n"); + } + + 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 + && estimated_stmt_executions (loop, &nit)) + { + if (wi::gtu_p (nit, max)) + nitercst = max; + else + nitercst = nit.to_shwi (); + predictor = PRED_LOOP_ITERATIONS_GUESSED; + } + /* If we have likely upper bound, trust it for very small iteration + counts. Such loops would otherwise get mispredicted by standard + LOOP_EXIT heuristics. */ + else if (n_exits == 1 + && likely_max_stmt_executions (loop, &nit) + && wi::ltu_p (nit, + RDIV (REG_BR_PROB_BASE, + REG_BR_PROB_BASE + - predictor_info + [recursion + ? PRED_LOOP_EXIT_WITH_RECURSION + : PRED_LOOP_EXIT].hitrate))) + { + nitercst = nit.to_shwi (); + predictor = PRED_LOOP_ITERATIONS_MAX; + } + else + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Nothing known about exit %i->%i.\n", + ex->src->index, ex->dest->index); + continue; + } + + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Recording prediction to %i iterations by %s.\n", + (int)nitercst, predictor_info[predictor].name); + /* If the prediction for number of iterations is zero, do not + predict the exit edges. */ + if (nitercst == 0) + continue; + + probability = RDIV (REG_BR_PROB_BASE, nitercst); + predict_edge (ex, predictor, probability); + } + + /* 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++) + { + 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)) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "BB %i predicted by continue.\n", + bb->index); + continue; + } + + /* If we already used more reliable loop exit predictors, do not + bother with PRED_LOOP_EXIT. */ + if (!predicted_by_loop_heuristics_p (bb)) + { + /* 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 + [recursion + ? PRED_LOOP_EXIT_WITH_RECURSION + : 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)) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, + "Predicting exit %i->%i with prob %i.\n", + e->src->index, e->dest->index, probability); + predict_edge (e, + recursion ? PRED_LOOP_EXIT_WITH_RECURSION + : 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)); + } + + /* In the following code + for (loop1) + if (cond) + for (loop2) + body; + guess that cond is unlikely. */ + if (loop_outer (loop)->num) + { + basic_block bb = NULL; + edge preheader_edge = loop_preheader_edge (loop); + + if (single_pred_p (preheader_edge->src) + && single_succ_p (preheader_edge->src)) + preheader_edge = single_pred_edge (preheader_edge->src); + + gimple *stmt = last_stmt (preheader_edge->src); + /* Pattern match fortran loop preheader: + _16 = BUILTIN_EXPECT (_15, 1, PRED_FORTRAN_LOOP_PREHEADER); + _17 = (logical(kind=4)) _16; + if (_17 != 0) + goto <bb 11>; + else + goto <bb 13>; + + Loop guard branch prediction says nothing about duplicated loop + headers produced by fortran frontend and in this case we want + to predict paths leading to this preheader. */ + + if (stmt + && gimple_code (stmt) == GIMPLE_COND + && gimple_cond_code (stmt) == NE_EXPR + && TREE_CODE (gimple_cond_lhs (stmt)) == SSA_NAME + && integer_zerop (gimple_cond_rhs (stmt))) + { + gimple *call_stmt = SSA_NAME_DEF_STMT (gimple_cond_lhs (stmt)); + if (gimple_code (call_stmt) == GIMPLE_ASSIGN + && CONVERT_EXPR_CODE_P (gimple_assign_rhs_code (call_stmt)) + && TREE_CODE (gimple_assign_rhs1 (call_stmt)) == SSA_NAME) + call_stmt = SSA_NAME_DEF_STMT (gimple_assign_rhs1 (call_stmt)); + if (gimple_call_internal_p (call_stmt, IFN_BUILTIN_EXPECT) + && TREE_CODE (gimple_call_arg (call_stmt, 2)) == INTEGER_CST + && tree_fits_uhwi_p (gimple_call_arg (call_stmt, 2)) + && tree_to_uhwi (gimple_call_arg (call_stmt, 2)) + == PRED_FORTRAN_LOOP_PREHEADER) + bb = preheader_edge->src; + } + if (!bb) + { + if (!dominated_by_p (CDI_DOMINATORS, + loop_outer (loop)->latch, loop->header)) + predict_paths_leading_to_edge (loop_preheader_edge (loop), + recursion + ? PRED_LOOP_GUARD_WITH_RECURSION + : PRED_LOOP_GUARD, + NOT_TAKEN, + loop_outer (loop)); + } + else + { + if (!dominated_by_p (CDI_DOMINATORS, + loop_outer (loop)->latch, bb)) + predict_paths_leading_to (bb, + recursion + ? PRED_LOOP_GUARD_WITH_RECURSION + : PRED_LOOP_GUARD, + NOT_TAKEN, + loop_outer (loop)); + } + } + + /* 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, + HOST_WIDE_INT *probability); + +/* 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, + HOST_WIDE_INT *probability) +{ + gimple *def; + + /* Reset returned probability value. */ + *probability = -1; + *predictor = PRED_UNCONDITIONAL; + + if (get_gimple_rhs_class (code) == GIMPLE_SINGLE_RHS) + { + if (TREE_CONSTANT (op0)) + return op0; + + if (code == IMAGPART_EXPR) + { + if (TREE_CODE (TREE_OPERAND (op0, 0)) == SSA_NAME) + { + def = SSA_NAME_DEF_STMT (TREE_OPERAND (op0, 0)); + if (is_gimple_call (def) + && gimple_call_internal_p (def) + && (gimple_call_internal_fn (def) + == IFN_ATOMIC_COMPARE_EXCHANGE)) + { + /* Assume that any given atomic operation has low contention, + and thus the compare-and-swap operation succeeds. */ + *predictor = PRED_COMPARE_AND_SWAP; + return build_one_cst (TREE_TYPE (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; + + HOST_WIDE_INT probability2; + new_val = expr_expected_value (arg, visited, &predictor2, + &probability2); + + /* It is difficult to combine value predictors. Simply assume + that later predictor is weaker and take its prediction. */ + if (*predictor < predictor2) + { + *predictor = predictor2; + *probability = probability2; + } + 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, probability); + } + + 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; + 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); + if (*predictor == PRED_BUILTIN_EXPECT) + *probability + = HITRATE (param_builtin_expect_probability); + return gimple_call_arg (def, 1); + } + return NULL; + } + + if (DECL_IS_MALLOC (decl) || DECL_IS_OPERATOR_NEW_P (decl)) + { + if (predictor) + *predictor = PRED_MALLOC_NONNULL; + return boolean_true_node; + } + + 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; + *predictor = PRED_BUILTIN_EXPECT; + *probability + = HITRATE (param_builtin_expect_probability); + return gimple_call_arg (def, 1); + } + case BUILT_IN_EXPECT_WITH_PROBABILITY: + { + tree val; + if (gimple_call_num_args (def) != 3) + return NULL; + val = gimple_call_arg (def, 0); + if (TREE_CONSTANT (val)) + return val; + /* Compute final probability as: + probability * REG_BR_PROB_BASE. */ + tree prob = gimple_call_arg (def, 2); + tree t = TREE_TYPE (prob); + tree base = build_int_cst (integer_type_node, + REG_BR_PROB_BASE); + base = build_real_from_int_cst (t, base); + tree r = fold_build2_initializer_loc (UNKNOWN_LOCATION, + MULT_EXPR, t, prob, base); + if (TREE_CODE (r) != REAL_CST) + { + error_at (gimple_location (def), + "probability %qE must be " + "constant floating-point expression", prob); + return NULL; + } + HOST_WIDE_INT probi + = real_to_integer (TREE_REAL_CST_PTR (r)); + if (probi >= 0 && probi <= REG_BR_PROB_BASE) + { + *predictor = PRED_BUILTIN_EXPECT_WITH_PROBABILITY; + *probability = probi; + } + else + error_at (gimple_location (def), + "probability %qE is outside " + "the range [0.0, 1.0]", prob); + + 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. */ + *predictor = PRED_COMPARE_AND_SWAP; + return boolean_true_node; + case BUILT_IN_REALLOC: + if (predictor) + *predictor = PRED_MALLOC_NONNULL; + return boolean_true_node; + default: + break; + } + } + + return NULL; + } + + if (get_gimple_rhs_class (code) == GIMPLE_BINARY_RHS) + { + tree res; + enum br_predictor predictor2; + HOST_WIDE_INT probability2; + op0 = expr_expected_value (op0, visited, predictor, probability); + if (!op0) + return NULL; + op1 = expr_expected_value (op1, visited, &predictor2, &probability2); + if (!op1) + return NULL; + res = fold_build2 (code, type, op0, op1); + if (TREE_CODE (res) == INTEGER_CST + && TREE_CODE (op0) == INTEGER_CST + && TREE_CODE (op1) == INTEGER_CST) + { + /* Combine binary predictions. */ + if (*probability != -1 || probability2 != -1) + { + HOST_WIDE_INT p1 = get_predictor_value (*predictor, *probability); + HOST_WIDE_INT p2 = get_predictor_value (predictor2, probability2); + *probability = RDIV (p1 * p2, REG_BR_PROB_BASE); + } + + if (*predictor < predictor2) + *predictor = predictor2; + + return res; + } + return NULL; + } + if (get_gimple_rhs_class (code) == GIMPLE_UNARY_RHS) + { + tree res; + op0 = expr_expected_value (op0, visited, predictor, probability); + 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, + HOST_WIDE_INT *probability) +{ + enum tree_code code; + tree op0, op1; + + if (TREE_CONSTANT (expr)) + { + *predictor = PRED_UNCONDITIONAL; + *probability = -1; + return expr; + } + + extract_ops_from_tree (expr, &code, &op0, &op1); + return expr_expected_value_1 (TREE_TYPE (expr), + op0, code, op1, visited, predictor, + probability); +} + + +/* Return probability of a PREDICTOR. If the predictor has variable + probability return passed PROBABILITY. */ + +static HOST_WIDE_INT +get_predictor_value (br_predictor predictor, HOST_WIDE_INT probability) +{ + switch (predictor) + { + case PRED_BUILTIN_EXPECT: + case PRED_BUILTIN_EXPECT_WITH_PROBABILITY: + gcc_assert (probability != -1); + return probability; + default: + gcc_assert (probability == -1); + return predictor_info[(int) predictor].hitrate; + } +} + +/* 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; + edge_iterator ei; + enum br_predictor predictor; + HOST_WIDE_INT probability; + + if (!stmt) + return; + + if (gswitch *sw = dyn_cast <gswitch *> (stmt)) + { + tree index = gimple_switch_index (sw); + tree val = expr_expected_value (index, auto_bitmap (), + &predictor, &probability); + if (val && TREE_CODE (val) == INTEGER_CST) + { + edge e = find_taken_edge_switch_expr (sw, val); + if (predictor == PRED_BUILTIN_EXPECT) + { + int percent = param_builtin_expect_probability; + gcc_assert (percent >= 0 && percent <= 100); + predict_edge (e, PRED_BUILTIN_EXPECT, + HITRATE (percent)); + } + else + predict_edge_def (e, predictor, TAKEN); + } + } + + if (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); + val = expr_expected_value_1 (boolean_type_node, op0, cmp, op1, auto_bitmap (), + &predictor, &probability); + if (val && TREE_CODE (val) == INTEGER_CST) + { + HOST_WIDE_INT prob = get_predictor_value (predictor, probability); + if (integer_zerop (val)) + prob = REG_BR_PROB_BASE - prob; + predict_edge (then_edge, predictor, prob); + } + /* 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; + } +} + +/* Returns TRUE if the STMT is exit(0) like statement. */ + +static bool +is_exit_with_zero_arg (const gimple *stmt) +{ + /* This is not exit, _exit or _Exit. */ + if (!gimple_call_builtin_p (stmt, BUILT_IN_EXIT) + && !gimple_call_builtin_p (stmt, BUILT_IN__EXIT) + && !gimple_call_builtin_p (stmt, BUILT_IN__EXIT2)) + return false; + + /* Argument is an interger zero. */ + return integer_zerop (gimple_call_arg (stmt, 0)); +} + +/* 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 = NOT_TAKEN; + return PRED_CONST_RETURN; + } + } + return PRED_NO_PREDICTION; +} + +/* Return zero if phi result could have values other than -1, 0 or 1, + otherwise return a bitmask, with bits 0, 1 and 2 set if -1, 0 and 1 + values are used or likely. */ + +static int +zero_one_minusone (gphi *phi, int limit) +{ + int phi_num_args = gimple_phi_num_args (phi); + int ret = 0; + for (int i = 0; i < phi_num_args; i++) + { + tree t = PHI_ARG_DEF (phi, i); + if (TREE_CODE (t) != INTEGER_CST) + continue; + wide_int w = wi::to_wide (t); + if (w == -1) + ret |= 1; + else if (w == 0) + ret |= 2; + else if (w == 1) + ret |= 4; + else + return 0; + } + for (int i = 0; i < phi_num_args; i++) + { + tree t = PHI_ARG_DEF (phi, i); + if (TREE_CODE (t) == INTEGER_CST) + continue; + if (TREE_CODE (t) != SSA_NAME) + return 0; + gimple *g = SSA_NAME_DEF_STMT (t); + if (gimple_code (g) == GIMPLE_PHI && limit > 0) + if (int r = zero_one_minusone (as_a <gphi *> (g), limit - 1)) + { + ret |= r; + continue; + } + if (!is_gimple_assign (g)) + return 0; + if (gimple_assign_cast_p (g)) + { + tree rhs1 = gimple_assign_rhs1 (g); + if (TREE_CODE (rhs1) != SSA_NAME + || !INTEGRAL_TYPE_P (TREE_TYPE (rhs1)) + || TYPE_PRECISION (TREE_TYPE (rhs1)) != 1 + || !TYPE_UNSIGNED (TREE_TYPE (rhs1))) + return 0; + ret |= (2 | 4); + continue; + } + if (TREE_CODE_CLASS (gimple_assign_rhs_code (g)) != tcc_comparison) + return 0; + ret |= (2 | 4); + } + return ret; +} + +/* 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 case where the function returns -1, 0 and 1 values and + nothing else. Those could be qsort etc. comparison functions + where the negative return isn't less probable than positive. + For this require that the function returns at least -1 or 1 + or -1 and a boolean value or comparison result, so that functions + returning just -1 and 0 are treated as if -1 represents error value. */ + if (INTEGRAL_TYPE_P (TREE_TYPE (return_val)) + && !TYPE_UNSIGNED (TREE_TYPE (return_val)) + && TYPE_PRECISION (TREE_TYPE (return_val)) > 1) + if (int r = zero_one_minusone (phi, 3)) + if ((r & (1 | 4)) == (1 | 4)) + return; + + /* 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 (!unlikely_executed_edge_p (e) && !(e->flags & EDGE_ABNORMAL_CALL)) + { + 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_noreturn_p (stmt) + && has_return_edges + && !is_exit_with_zero_arg (stmt)) + 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); + if (decl && recursive_call_p (current_function_decl, decl)) + predict_paths_leading_to (bb, PRED_RECURSIVE_CALL, + 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. */ + } + } + } +} + +/* 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 true; +} + +/* Predict branch probabilities and estimate profile for basic block BB. + When LOCAL_ONLY is set do not use any global properties of CFG. */ + +static void +tree_estimate_probability_bb (basic_block bb, bool local_only) +{ + edge e; + edge_iterator ei; + + FOR_EACH_EDGE (e, ei, bb->succs) + { + /* 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 + && !local_only + && 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) + && !gimple_inexpensive_call_p (as_a <gcall *> (stmt)) + /* Constant and pure calls are hardly used to signalize + something exceptional. */ + && gimple_has_side_effects (stmt)) + { + if (gimple_call_fndecl (stmt)) + predict_edge_def (e, PRED_CALL, NOT_TAKEN); + else if (virtual_method_call_p (gimple_call_fn (stmt))) + predict_edge_def (e, PRED_POLYMORPHIC_CALL, NOT_TAKEN); + else + predict_edge_def (e, PRED_INDIR_CALL, 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. + If DRY_RUN is set, do not modify CFG and only produce dump files. */ + +void +tree_estimate_probability (bool dry_run) +{ + basic_block bb; + + 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); + /* Decide which edges are known to be unlikely. This improves later + branch prediction. */ + determine_unlikely_bbs (); + + 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, false); + + FOR_EACH_BB_FN (bb, cfun) + combine_predictions_for_bb (bb, dry_run); + + if (flag_checking) + bb_predictions->traverse<void *, assert_is_empty> (NULL); + + delete bb_predictions; + bb_predictions = NULL; + + if (!dry_run) + estimate_bb_frequencies (false); + free_dominance_info (CDI_POST_DOMINATORS); + remove_fake_exit_edges (); +} + +/* Set edge->probability for each successor edge of BB. */ +void +tree_guess_outgoing_edge_probabilities (basic_block bb) +{ + bb_predictions = new hash_map<const_basic_block, edge_prediction *>; + tree_estimate_probability_bb (bb, true); + combine_predictions_for_bb (bb, false); + if (flag_checking) + bb_predictions->traverse<void *, assert_is_empty> (NULL); + delete bb_predictions; + bb_predictions = NULL; +} + +/* Filter function predicate that returns true for a edge predicate P + if its edge is equal to DATA. */ + +static bool +not_loop_guard_equal_edge_p (edge_prediction *p, void *data) +{ + return p->ep_edge != (edge)data || p->ep_predictor != PRED_LOOP_GUARD; +} + +/* Predict edge E with PRED unless it is already predicted by some predictor + considered equivalent. */ + +static void +maybe_predict_edge (edge e, enum br_predictor pred, enum prediction taken) +{ + if (edge_predicted_by_p (e, pred, taken)) + return; + if (pred == PRED_LOOP_GUARD + && edge_predicted_by_p (e, PRED_LOOP_GUARD_WITH_RECURSION, taken)) + return; + /* Consider PRED_LOOP_GUARD_WITH_RECURSION superrior to LOOP_GUARD. */ + if (pred == PRED_LOOP_GUARD_WITH_RECURSION) + { + edge_prediction **preds = bb_predictions->get (e->src); + if (preds) + filter_predictions (preds, not_loop_guard_equal_edge_p, e); + } + predict_edge_def (e, pred, taken); +} +/* 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, class loop *in_loop = NULL) +{ + edge e; + edge_iterator ei; + basic_block son; + + /* If we exited the loop or CUR is unconditional in the loop, there is + nothing to do. */ + if (in_loop + && (!flow_bb_inside_loop_p (in_loop, cur) + || dominated_by_p (CDI_DOMINATORS, in_loop->latch, cur))) + return; + + /* 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 (unlikely_executed_edge_p (e)) + 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 and does not exit the loop. */ + FOR_EACH_EDGE (e2, ei2, e->src->succs) + if (e2 != e + && !unlikely_executed_edge_p (e2) + && !dominated_by_p (CDI_POST_DOMINATORS, e2->dest, bb) + && (!in_loop || !loop_exit_edge_p (in_loop, e2))) + { + 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) + maybe_predict_edge (e, pred, taken); + else if (bitmap_set_bit (visited, e->src->index)) + predict_paths_for_bb (e->src, e->src, pred, taken, visited, in_loop); + } + 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, in_loop); +} + +/* Sets branch probabilities according to PREDiction and + FLAGS. */ + +static void +predict_paths_leading_to (basic_block bb, enum br_predictor pred, + enum prediction taken, class loop *in_loop) +{ + predict_paths_for_bb (bb, bb, pred, taken, auto_bitmap (), in_loop); +} + +/* 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, class loop *in_loop) +{ + 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 + && !unlikely_executed_edge_p (e2) + && !dominated_by_p (CDI_POST_DOMINATORS, e->src, e2->dest)) + { + has_nonloop_edge = true; + break; + } + + if (!has_nonloop_edge) + predict_paths_for_bb (bb, bb, pred, taken, auto_bitmap (), in_loop); + else + maybe_predict_edge (e, pred, taken); +} + +/* This is used to carry information about basic blocks. It is + attached to the AUX field of the standard CFG block. */ + +class block_info +{ +public: + /* 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. */ +class edge_prob_info +{ +public: + /* 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, + sreal max_cyclic_prob) +{ + 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 = profile_count::zero (); + } + + 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) + { + if (flag_checking) + FOR_EACH_EDGE (e, ei, bb->preds) + gcc_assert (!bitmap_bit_p (tovisit, e->src->index) + || (e->flags & EDGE_DFS_BACK)); + + 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)) + { + /* FIXME: Graphite is producing edges with no profile. Once + this is fixed, drop this. */ + sreal tmp = e->probability.initialized_p () ? + e->probability.to_sreal () : 0; + frequency += tmp * BLOCK_INFO (e->src)->frequency; + } + + if (cyclic_probability == 0) + { + BLOCK_INFO (bb)->frequency = frequency; + } + else + { + if (cyclic_probability > max_cyclic_prob) + { + if (dump_file) + fprintf (dump_file, + "cyclic probability of bb %i is %f (capped to %f)" + "; turning freq %f", + bb->index, cyclic_probability.to_double (), + max_cyclic_prob.to_double (), + frequency.to_double ()); + + cyclic_probability = max_cyclic_prob; + } + else if (dump_file) + fprintf (dump_file, + "cyclic probability of bb %i is %f; turning freq %f", + bb->index, cyclic_probability.to_double (), + frequency.to_double ()); + + BLOCK_INFO (bb)->frequency = frequency + / (sreal (1) - cyclic_probability); + if (dump_file) + fprintf (dump_file, " to %f\n", + BLOCK_INFO (bb)->frequency.to_double ()); + } + } + + bitmap_clear_bit (tovisit, bb->index); + + e = find_edge (bb, head); + if (e) + { + /* FIXME: Graphite is producing edges with no profile. Once + this is fixed, drop this. */ + sreal tmp = e->probability.initialized_p () ? + e->probability.to_sreal () : 0; + EDGE_INFO (e)->back_edge_prob = tmp * BLOCK_INFO (bb)->frequency; + } + + /* 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 (class loop *first_loop, sreal max_cyclic_prob) +{ + class loop *loop; + + for (loop = first_loop; loop; loop = loop->next) + { + edge e; + basic_block *bbs; + unsigned i; + auto_bitmap tovisit; + + estimate_loops_at_level (loop->inner, max_cyclic_prob); + + /* 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, max_cyclic_prob); + } +} + +/* Propagates frequencies through structure of loops. */ + +static void +estimate_loops (void) +{ + auto_bitmap tovisit; + basic_block bb; + sreal max_cyclic_prob = (sreal)1 + - (sreal)1 / (param_max_predicted_iterations + 1); + + /* Start by estimating the frequencies in the loops. */ + if (number_of_loops (cfun) > 1) + estimate_loops_at_level (current_loops->tree_root->inner, max_cyclic_prob); + + /* 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, max_cyclic_prob); +} + +/* 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, profile_count 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. %s based on calls.\n", + node->dump_name (), + 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\n", + node->dump_name ()); + } + else + warning (0, "Missing counts for called function %s", + node->dump_name ()); + } + + basic_block bb; + if (opt_for_fn (node->decl, flag_guess_branch_prob)) + { + bool clear_zeros + = !ENTRY_BLOCK_PTR_FOR_FN (fn)->count.nonzero_p (); + FOR_ALL_BB_FN (bb, fn) + if (clear_zeros || !(bb->count == profile_count::zero ())) + bb->count = bb->count.guessed_local (); + fn->cfg->count_max = fn->cfg->count_max.guessed_local (); + } + else + { + FOR_ALL_BB_FN (bb, fn) + bb->count = profile_count::uninitialized (); + fn->cfg->count_max = profile_count::uninitialized (); + } + + struct cgraph_edge *e; + for (e = node->callees; e; e = e->next_callee) + e->count = gimple_bb (e->call_stmt)->count; + for (e = node->indirect_calls; e; e = e->next_callee) + e->count = gimple_bb (e->call_stmt)->count; + node->count = ENTRY_BLOCK_PTR_FOR_FN (fn)->count; + + 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) +{ + const int unlikely_frac = param_unlikely_bb_count_fraction; + struct cgraph_node *node; + auto_vec<struct cgraph_node *, 64> worklist; + + /* 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; + profile_count call_count = profile_count::zero (); + gcov_type max_tp_first_run = 0; + struct function *fn = DECL_STRUCT_FUNCTION (node->decl); + + if (node->count.ipa ().nonzero_p ()) + continue; + for (e = node->callers; e; e = e->next_caller) + if (e->count.ipa ().initialized_p () && e->count.ipa () > 0) + { + call_count = call_count + e->count.ipa (); + + 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 > 0 + && fn && fn->cfg + && call_count.apply_scale (unlikely_frac, 1) >= 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 (!(e->count.ipa () == profile_count::zero ()) + && callee->count.ipa ().nonzero_p ()) + continue; + if ((DECL_COMDAT (callee->decl) || DECL_EXTERNAL (callee->decl)) + && fn && fn->cfg + && profile_status_for_fn (fn) == PROFILE_READ) + { + drop_profile (node, profile_count::zero ()); + worklist.safe_push (callee); + } + } + } +} + +/* Convert counts measured by profile driven feedback to frequencies. + Return nonzero iff there was any nonzero execution count. */ + +bool +update_max_bb_count (void) +{ + profile_count true_count_max = profile_count::uninitialized (); + basic_block bb; + + FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) + true_count_max = true_count_max.max (bb->count); + + cfun->cfg->count_max = true_count_max; + + return true_count_max.ipa ().nonzero_p (); +} + +/* 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) +{ + basic_block bb; + + /* If profile was scaled in a way entry block has count 0, then the function + is deifnitly taking a lot of time. */ + if (!ENTRY_BLOCK_PTR_FOR_FN (cfun)->count.nonzero_p ()) + return true; + + profile_count limit = ENTRY_BLOCK_PTR_FOR_FN + (cfun)->count.apply_scale (threshold, 1); + profile_count sum = profile_count::zero (); + FOR_EACH_BB_FN (bb, cfun) + { + rtx_insn *insn; + + if (!bb->count.initialized_p ()) + { + if (dump_file) + fprintf (dump_file, "Function is considered expensive because" + " count of bb %i is not initialized\n", bb->index); + return true; + } + + FOR_BB_INSNS (bb, insn) + if (active_insn_p (insn)) + { + sum += bb->count; + if (sum > limit) + return true; + } + } + + return false; +} + +/* All basic blocks that are reachable only from unlikely basic blocks are + unlikely. */ + +void +propagate_unlikely_bbs_forward (void) +{ + auto_vec<basic_block, 64> worklist; + basic_block bb; + edge_iterator ei; + edge e; + + if (!(ENTRY_BLOCK_PTR_FOR_FN (cfun)->count == profile_count::zero ())) + { + ENTRY_BLOCK_PTR_FOR_FN (cfun)->aux = (void *)(size_t) 1; + worklist.safe_push (ENTRY_BLOCK_PTR_FOR_FN (cfun)); + + while (worklist.length () > 0) + { + bb = worklist.pop (); + FOR_EACH_EDGE (e, ei, bb->succs) + if (!(e->count () == profile_count::zero ()) + && !(e->dest->count == profile_count::zero ()) + && !e->dest->aux) + { + e->dest->aux = (void *)(size_t) 1; + worklist.safe_push (e->dest); + } + } + } + + FOR_ALL_BB_FN (bb, cfun) + { + if (!bb->aux) + { + if (!(bb->count == profile_count::zero ()) + && (dump_file && (dump_flags & TDF_DETAILS))) + fprintf (dump_file, + "Basic block %i is marked unlikely by forward prop\n", + bb->index); + bb->count = profile_count::zero (); + } + else + bb->aux = NULL; + } +} + +/* Determine basic blocks/edges that are known to be unlikely executed and set + their counters to zero. + This is done with first identifying obviously unlikely BBs/edges and then + propagating in both directions. */ + +static void +determine_unlikely_bbs () +{ + basic_block bb; + auto_vec<basic_block, 64> worklist; + edge_iterator ei; + edge e; + + FOR_EACH_BB_FN (bb, cfun) + { + if (!(bb->count == profile_count::zero ()) + && unlikely_executed_bb_p (bb)) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Basic block %i is locally unlikely\n", + bb->index); + bb->count = profile_count::zero (); + } + + FOR_EACH_EDGE (e, ei, bb->succs) + if (!(e->probability == profile_probability::never ()) + && unlikely_executed_edge_p (e)) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Edge %i->%i is locally unlikely\n", + bb->index, e->dest->index); + e->probability = profile_probability::never (); + } + + gcc_checking_assert (!bb->aux); + } + propagate_unlikely_bbs_forward (); + + auto_vec<int, 64> nsuccs; + nsuccs.safe_grow_cleared (last_basic_block_for_fn (cfun), true); + FOR_ALL_BB_FN (bb, cfun) + if (!(bb->count == profile_count::zero ()) + && bb != EXIT_BLOCK_PTR_FOR_FN (cfun)) + { + nsuccs[bb->index] = 0; + FOR_EACH_EDGE (e, ei, bb->succs) + if (!(e->probability == profile_probability::never ()) + && !(e->dest->count == profile_count::zero ())) + nsuccs[bb->index]++; + if (!nsuccs[bb->index]) + worklist.safe_push (bb); + } + while (worklist.length () > 0) + { + bb = worklist.pop (); + if (bb->count == profile_count::zero ()) + continue; + if (bb != ENTRY_BLOCK_PTR_FOR_FN (cfun)) + { + bool found = false; + for (gimple_stmt_iterator gsi = gsi_start_bb (bb); + !gsi_end_p (gsi); gsi_next (&gsi)) + if (stmt_can_terminate_bb_p (gsi_stmt (gsi)) + /* stmt_can_terminate_bb_p special cases noreturns because it + assumes that fake edges are created. We want to know that + noreturn alone does not imply BB to be unlikely. */ + || (is_gimple_call (gsi_stmt (gsi)) + && (gimple_call_flags (gsi_stmt (gsi)) & ECF_NORETURN))) + { + found = true; + break; + } + if (found) + continue; + } + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, + "Basic block %i is marked unlikely by backward prop\n", + bb->index); + bb->count = profile_count::zero (); + FOR_EACH_EDGE (e, ei, bb->preds) + if (!(e->probability == profile_probability::never ())) + { + if (!(e->src->count == profile_count::zero ())) + { + gcc_checking_assert (nsuccs[e->src->index] > 0); + nsuccs[e->src->index]--; + if (!nsuccs[e->src->index]) + worklist.safe_push (e->src); + } + } + } + /* Finally all edges from non-0 regions to 0 are unlikely. */ + FOR_ALL_BB_FN (bb, cfun) + { + if (!(bb->count == profile_count::zero ())) + FOR_EACH_EDGE (e, ei, bb->succs) + if (!(e->probability == profile_probability::never ()) + && e->dest->count == profile_count::zero ()) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Edge %i->%i is unlikely because " + "it enters unlikely block\n", + bb->index, e->dest->index); + e->probability = profile_probability::never (); + } + + edge other = NULL; + + FOR_EACH_EDGE (e, ei, bb->succs) + if (e->probability == profile_probability::never ()) + ; + else if (other) + { + other = NULL; + break; + } + else + other = e; + if (other + && !(other->probability == profile_probability::always ())) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Edge %i->%i is locally likely\n", + bb->index, other->dest->index); + other->probability = profile_probability::always (); + } + } + if (ENTRY_BLOCK_PTR_FOR_FN (cfun)->count == profile_count::zero ()) + cgraph_node::get (current_function_decl)->count = profile_count::zero (); +} + +/* 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; + + determine_unlikely_bbs (); + + if (force || profile_status_for_fn (cfun) != PROFILE_READ + || !update_max_bb_count ()) + { + + mark_dfs_back_edges (); + + single_succ_edge (ENTRY_BLOCK_PTR_FOR_FN (cfun))->probability = + profile_probability::always (); + + /* 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) + { + /* FIXME: Graphite is producing edges with no profile. Once + this is fixed, drop this. */ + if (e->probability.initialized_p ()) + EDGE_INFO (e)->back_edge_prob + = e->probability.to_sreal (); + else + /* back_edge_prob = 0.5 */ + EDGE_INFO (e)->back_edge_prob = sreal (1, -1); + } + } + + /* 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; + + /* Scaling frequencies up to maximal profile count may result in + frequent overflows especially when inlining loops. + Small scalling results in unnecesary precision loss. Stay in + the half of the (exponential) range. */ + freq_max = (sreal (1) << (profile_count::n_bits / 2)) / freq_max; + if (freq_max < 16) + freq_max = 16; + profile_count ipa_count = ENTRY_BLOCK_PTR_FOR_FN (cfun)->count.ipa (); + cfun->cfg->count_max = profile_count::uninitialized (); + FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) + { + sreal tmp = BLOCK_INFO (bb)->frequency; + if (tmp >= 1) + { + gimple_stmt_iterator gsi; + tree decl; + + /* Self recursive calls can not have frequency greater than 1 + or program will never terminate. This will result in an + inconsistent bb profile but it is better than greatly confusing + IPA cost metrics. */ + for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi)) + if (is_gimple_call (gsi_stmt (gsi)) + && (decl = gimple_call_fndecl (gsi_stmt (gsi))) != NULL + && recursive_call_p (current_function_decl, decl)) + { + if (dump_file) + fprintf (dump_file, "Dropping frequency of recursive call" + " in bb %i from %f\n", bb->index, + tmp.to_double ()); + tmp = (sreal)9 / (sreal)10; + break; + } + } + tmp = tmp * freq_max + sreal (1, -1); + profile_count count = profile_count::from_gcov_type (tmp.to_int ()); + + /* If we have profile feedback in which this function was never + executed, then preserve this info. */ + if (!(bb->count == profile_count::zero ())) + bb->count = count.guessed_local ().combine_with_ipa_count (ipa_count); + cfun->cfg->count_max = cfun->cfg->count_max.max (bb->count); + } + + 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 (!ENTRY_BLOCK_PTR_FOR_FN (cfun)->count.ipa_p ()) + { + 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; + } + + node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED; + warn_function_cold (current_function_decl); + if (ENTRY_BLOCK_PTR_FOR_FN (cfun)->count.ipa() == profile_count::zero ()) + return; + 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); + + nb_loops = number_of_loops (fun); + if (nb_loops > 1) + scev_initialize (); + + tree_estimate_probability (false); + + 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; + if (dump_file && (dump_flags & TDF_DETAILS)) + { + for (auto loop : loops_list (cfun, LI_FROM_INNERMOST)) + if (loop->header->count.initialized_p ()) + fprintf (dump_file, "Loop got predicted %d to iterate %i times.\n", + loop->num, + (int)expected_loop_iterations_unbounded (loop)); + } + return 0; +} + +} // anon namespace + +gimple_opt_pass * +make_pass_profile (gcc::context *ctxt) +{ + return new pass_profile (ctxt); +} + +/* Return true when PRED predictor should be removed after early + tree passes. Most of the predictors are beneficial to survive + as early inlining can also distribute then into caller's bodies. */ + +static bool +strip_predictor_early (enum br_predictor pred) +{ + switch (pred) + { + case PRED_TREE_EARLY_RETURN: + return true; + default: + return false; + } +} + +/* Get rid of all builtin_expect calls and GIMPLE_PREDICT statements + we no longer need. EARLY is set to true when called from early + optimizations. */ + +unsigned int +strip_predict_hints (function *fun, bool early) +{ + basic_block bb; + gimple *ass_stmt; + tree var; + bool changed = false; + + 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) + { + if (!early + || strip_predictor_early (gimple_predict_predictor (stmt))) + { + gsi_remove (&bi, true); + changed = true; + continue; + } + } + else if (is_gimple_call (stmt)) + { + tree fndecl = gimple_call_fndecl (stmt); + + if (!early + && ((fndecl != NULL_TREE + && fndecl_built_in_p (fndecl, BUILT_IN_EXPECT) + && gimple_call_num_args (stmt) == 2) + || (fndecl != NULL_TREE + && fndecl_built_in_p (fndecl, + BUILT_IN_EXPECT_WITH_PROBABILITY) + && gimple_call_num_args (stmt) == 3) + || (gimple_call_internal_p (stmt) + && gimple_call_internal_fn (stmt) == IFN_BUILTIN_EXPECT))) + { + var = gimple_call_lhs (stmt); + changed = true; + 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 changed ? TODO_cleanup_cfg : 0; +} + +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); } + void set_pass_param (unsigned int n, bool param) + { + gcc_assert (n == 0); + early_p = param; + } + + virtual unsigned int execute (function *); + +private: + bool early_p; + +}; // class pass_strip_predict_hints + +unsigned int +pass_strip_predict_hints::execute (function *fun) +{ + return strip_predict_hints (fun, early_p); +} + +} // 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. */ + cfun->cfg->count_max = profile_count::uninitialized (); + basic_block bb; + FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) + cfun->cfg->count_max = cfun->cfg->count_max.max (bb->count); + + if (profile_status_for_fn (cfun) == PROFILE_GUESSED) + { + loop_optimizer_init (LOOPS_HAVE_MARKED_IRREDUCIBLE_REGIONS); + 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) + update_max_bb_count (); + else if (profile_status_for_fn (cfun) == PROFILE_ABSENT + && !flag_guess_branch_prob) + ; + else + gcc_unreachable (); + timevar_pop (TV_REBUILD_FREQUENCIES); +} + +/* Perform a dry run of the branch prediction pass and report comparsion of + the predicted and real profile into the dump file. */ + +void +report_predictor_hitrates (void) +{ + unsigned nb_loops; + + loop_optimizer_init (LOOPS_NORMAL); + if (dump_file && (dump_flags & TDF_DETAILS)) + flow_loops_dump (dump_file, NULL, 0); + + nb_loops = number_of_loops (cfun); + if (nb_loops > 1) + scev_initialize (); + + tree_estimate_probability (true); + + if (nb_loops > 1) + scev_finalize (); + + loop_optimizer_finalize (); +} + +/* Force edge E to be cold. + If IMPOSSIBLE is true, for edge to have count and probability 0 otherwise + keep low probability to represent possible error in a guess. This is used + i.e. in case we predict loop to likely iterate given number of times but + we are not 100% sure. + + This function locally updates profile without attempt to keep global + consistency which cannot be reached in full generality without full profile + rebuild from probabilities alone. Doing so is not necessarily a good idea + because frequencies and counts may be more realistic then probabilities. + + In some cases (such as for elimination of early exits during full loop + unrolling) the caller can ensure that profile will get consistent + afterwards. */ + +void +force_edge_cold (edge e, bool impossible) +{ + profile_count count_sum = profile_count::zero (); + profile_probability prob_sum = profile_probability::never (); + edge_iterator ei; + edge e2; + bool uninitialized_exit = false; + + /* When branch probability guesses are not known, then do nothing. */ + if (!impossible && !e->count ().initialized_p ()) + return; + + profile_probability goal = (impossible ? profile_probability::never () + : profile_probability::very_unlikely ()); + + /* If edge is already improbably or cold, just return. */ + if (e->probability <= goal + && (!impossible || e->count () == profile_count::zero ())) + return; + FOR_EACH_EDGE (e2, ei, e->src->succs) + if (e2 != e) + { + if (e->flags & EDGE_FAKE) + continue; + if (e2->count ().initialized_p ()) + count_sum += e2->count (); + if (e2->probability.initialized_p ()) + prob_sum += e2->probability; + else + uninitialized_exit = true; + } + + /* If we are not guessing profiles but have some other edges out, + just assume the control flow goes elsewhere. */ + if (uninitialized_exit) + e->probability = goal; + /* If there are other edges out of e->src, redistribute probabilitity + there. */ + else if (prob_sum > profile_probability::never ()) + { + if (!(e->probability < goal)) + e->probability = goal; + + profile_probability prob_comp = prob_sum / e->probability.invert (); + + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Making edge %i->%i %s by redistributing " + "probability to other edges.\n", + e->src->index, e->dest->index, + impossible ? "impossible" : "cold"); + FOR_EACH_EDGE (e2, ei, e->src->succs) + if (e2 != e) + { + e2->probability /= prob_comp; + } + if (current_ir_type () != IR_GIMPLE + && e->src != ENTRY_BLOCK_PTR_FOR_FN (cfun)) + update_br_prob_note (e->src); + } + /* If all edges out of e->src are unlikely, the basic block itself + is unlikely. */ + else + { + if (prob_sum == profile_probability::never ()) + e->probability = profile_probability::always (); + else + { + if (impossible) + e->probability = profile_probability::never (); + /* If BB has some edges out that are not impossible, we cannot + assume that BB itself is. */ + impossible = false; + } + if (current_ir_type () != IR_GIMPLE + && e->src != ENTRY_BLOCK_PTR_FOR_FN (cfun)) + update_br_prob_note (e->src); + if (e->src->count == profile_count::zero ()) + return; + if (count_sum == profile_count::zero () && impossible) + { + bool found = false; + if (e->src == ENTRY_BLOCK_PTR_FOR_FN (cfun)) + ; + else if (current_ir_type () == IR_GIMPLE) + for (gimple_stmt_iterator gsi = gsi_start_bb (e->src); + !gsi_end_p (gsi); gsi_next (&gsi)) + { + if (stmt_can_terminate_bb_p (gsi_stmt (gsi))) + { + found = true; + break; + } + } + /* FIXME: Implement RTL path. */ + else + found = true; + if (!found) + { + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, + "Making bb %i impossible and dropping count to 0.\n", + e->src->index); + e->src->count = profile_count::zero (); + FOR_EACH_EDGE (e2, ei, e->src->preds) + force_edge_cold (e2, impossible); + return; + } + } + + /* If we did not adjusting, the source basic block has no likely edeges + leaving other direction. In that case force that bb cold, too. + This in general is difficult task to do, but handle special case when + BB has only one predecestor. This is common case when we are updating + after loop transforms. */ + if (!(prob_sum > profile_probability::never ()) + && count_sum == profile_count::zero () + && single_pred_p (e->src) && e->src->count.to_frequency (cfun) + > (impossible ? 0 : 1)) + { + int old_frequency = e->src->count.to_frequency (cfun); + if (dump_file && (dump_flags & TDF_DETAILS)) + fprintf (dump_file, "Making bb %i %s.\n", e->src->index, + impossible ? "impossible" : "cold"); + int new_frequency = MIN (e->src->count.to_frequency (cfun), + impossible ? 0 : 1); + if (impossible) + e->src->count = profile_count::zero (); + else + e->src->count = e->count ().apply_scale (new_frequency, + old_frequency); + force_edge_cold (single_pred_edge (e->src), impossible); + } + else if (dump_file && (dump_flags & TDF_DETAILS) + && maybe_hot_bb_p (cfun, e->src)) + fprintf (dump_file, "Giving up on making bb %i %s.\n", e->src->index, + impossible ? "impossible" : "cold"); + } +} + +/* Change E's probability to NEW_E_PROB, redistributing the probabilities + of other outgoing edges proportionally. + + Note that this function does not change the profile counts of any + basic blocks. The caller must do that instead, using whatever + information it has about the region that needs updating. */ + +void +change_edge_frequency (edge e, profile_probability new_e_prob) +{ + profile_probability old_e_prob = e->probability; + profile_probability old_other_prob = old_e_prob.invert (); + profile_probability new_other_prob = new_e_prob.invert (); + + e->probability = new_e_prob; + profile_probability cumulative_prob = new_e_prob; + + unsigned int num_other = EDGE_COUNT (e->src->succs) - 1; + edge other_e; + edge_iterator ei; + FOR_EACH_EDGE (other_e, ei, e->src->succs) + if (other_e != e) + { + num_other -= 1; + if (num_other == 0) + /* Ensure that the probabilities add up to 1 without + rounding error. */ + other_e->probability = cumulative_prob.invert (); + else + { + other_e->probability /= old_other_prob; + other_e->probability *= new_other_prob; + cumulative_prob += other_e->probability; + } + } +} + +#if CHECKING_P + +namespace selftest { + +/* Test that value range of predictor values defined in predict.def is + within range (50, 100]. */ + +struct branch_predictor +{ + const char *name; + int probability; +}; + +#define DEF_PREDICTOR(ENUM, NAME, HITRATE, FLAGS) { NAME, HITRATE }, + +static void +test_prediction_value_range () +{ + branch_predictor predictors[] = { +#include "predict.def" + { NULL, PROB_UNINITIALIZED } + }; + + for (unsigned i = 0; predictors[i].name != NULL; i++) + { + if (predictors[i].probability == PROB_UNINITIALIZED) + continue; + + unsigned p = 100 * predictors[i].probability / REG_BR_PROB_BASE; + ASSERT_TRUE (p >= 50 && p <= 100); + } +} + +#undef DEF_PREDICTOR + +/* Run all of the selfests within this file. */ + +void +predict_c_tests () +{ + test_prediction_value_range (); +} + +} // namespace selftest +#endif /* CHECKING_P. */ |