/* Branch prediction routines for the GNU compiler. Copyright (C) 2000-2014 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 . */ /* 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 "tm.h" #include "tree.h" #include "calls.h" #include "rtl.h" #include "tm_p.h" #include "hard-reg-set.h" #include "basic-block.h" #include "insn-config.h" #include "regs.h" #include "flags.h" #include "function.h" #include "except.h" #include "diagnostic-core.h" #include "recog.h" #include "expr.h" #include "predict.h" #include "coverage.h" #include "sreal.h" #include "params.h" #include "target.h" #include "cfgloop.h" #include "pointer-set.h" #include "tree-ssa-alias.h" #include "internal-fn.h" #include "gimple-expr.h" #include "is-a.h" #include "gimple.h" #include "gimple-iterator.h" #include "gimple-ssa.h" #include "cgraph.h" #include "tree-cfg.h" #include "tree-phinodes.h" #include "ssa-iterators.h" #include "tree-ssa-loop-niter.h" #include "tree-ssa-loop.h" #include "tree-pass.h" #include "tree-scalar-evolution.h" #include "cfgloop.h" /* real constants: 0, 1, 1-1/REG_BR_PROB_BASE, REG_BR_PROB_BASE, 1/REG_BR_PROB_BASE, 0.5, BB_FREQ_MAX. */ static sreal real_zero, real_one, real_almost_one, real_br_prob_base, real_inv_br_prob_base, real_one_half, real_bb_freq_max; static void combine_predictions_for_insn (rtx, basic_block); static void dump_prediction (FILE *, enum br_predictor, int, basic_block, int); static void predict_paths_leading_to (basic_block, enum br_predictor, enum prediction); static void predict_paths_leading_to_edge (edge, enum br_predictor, enum prediction); static bool can_predict_insn_p (const_rtx); /* 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 /* Return TRUE if frequency FREQ is considered to be hot. */ static inline bool maybe_hot_frequency_p (struct function *fun, int freq) { struct cgraph_node *node = cgraph_get_node (fun->decl); if (!profile_info || !flag_branch_probabilities) { 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 && freq < (ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency * 2 / 3)) return false; if (PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION) == 0) return false; if (freq < (ENTRY_BLOCK_PTR_FOR_FN (fun)->frequency / PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION))) return false; return true; } static gcov_type min_count = -1; /* Determine the threshold for hot BB counts. */ gcov_type get_hot_bb_threshold () { gcov_working_set_t *ws; if (min_count == -1) { ws = find_working_set (PARAM_VALUE (HOT_BB_COUNT_WS_PERMILLE)); gcc_assert (ws); min_count = ws->min_counter; } return min_count; } /* Set the threshold for hot BB counts. */ void set_hot_bb_threshold (gcov_type min) { min_count = min; } /* Return TRUE if frequency FREQ is considered to be hot. */ bool maybe_hot_count_p (struct function *fun, gcov_type count) { if (fun && profile_status_for_fn (fun) != PROFILE_READ) return true; if (!profile_info) return false; /* Code executed at most once is not hot. */ if (profile_info->runs >= count) return false; return (count >= get_hot_bb_threshold ()); } /* Return true in case BB can be CPU intensive and should be optimized for maximal performance. */ bool maybe_hot_bb_p (struct function *fun, const_basic_block bb) { gcc_checking_assert (fun); if (profile_status_for_fn (fun) == PROFILE_READ) return maybe_hot_count_p (fun, bb->count); return maybe_hot_frequency_p (fun, bb->frequency); } /* Return true if the call can be hot. */ bool cgraph_maybe_hot_edge_p (struct cgraph_edge *edge) { if (profile_info && flag_branch_probabilities && !maybe_hot_count_p (NULL, edge->count)) return false; if (edge->caller->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED || (edge->callee && edge->callee->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED)) return false; if (edge->caller->frequency > NODE_FREQUENCY_UNLIKELY_EXECUTED && (edge->callee && edge->callee->frequency <= NODE_FREQUENCY_EXECUTED_ONCE)) return false; if (optimize_size) return false; if (edge->caller->frequency == NODE_FREQUENCY_HOT) return true; if (edge->caller->frequency == NODE_FREQUENCY_EXECUTED_ONCE && edge->frequency < CGRAPH_FREQ_BASE * 3 / 2) return false; if (flag_guess_branch_prob) { if (PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION) == 0 || edge->frequency <= (CGRAPH_FREQ_BASE / PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION))) return false; } return true; } /* Return true in case BB can be CPU intensive and should be optimized for maximal performance. */ bool maybe_hot_edge_p (edge e) { if (profile_status_for_fn (cfun) == PROFILE_READ) return maybe_hot_count_p (cfun, e->count); return maybe_hot_frequency_p (cfun, EDGE_FREQUENCY (e)); } /* Return true if profile COUNT and FREQUENCY, or function FUN static node frequency reflects never being executed. */ static bool probably_never_executed (struct function *fun, gcov_type count, int frequency) { gcc_checking_assert (fun); if (profile_status_for_fn (cfun) == PROFILE_READ) { int unlikely_count_fraction = PARAM_VALUE (UNLIKELY_BB_COUNT_FRACTION); if (count * unlikely_count_fraction >= profile_info->runs) return false; if (!frequency) return true; if (!ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency) return false; if (ENTRY_BLOCK_PTR_FOR_FN (cfun)->count) { gcov_type computed_count; /* Check for possibility of overflow, in which case entry bb count is large enough to do the division first without losing much precision. */ if (ENTRY_BLOCK_PTR_FOR_FN (cfun)->count < REG_BR_PROB_BASE * REG_BR_PROB_BASE) { gcov_type scaled_count = frequency * ENTRY_BLOCK_PTR_FOR_FN (cfun)->count * unlikely_count_fraction; computed_count = RDIV (scaled_count, ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency); } else { computed_count = RDIV (ENTRY_BLOCK_PTR_FOR_FN (cfun)->count, ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency); computed_count *= frequency * unlikely_count_fraction; } if (computed_count >= profile_info->runs) return false; } return true; } if ((!profile_info || !flag_branch_probabilities) && (cgraph_get_node (fun->decl)->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED)) return true; return false; } /* Return true in case BB is probably never executed. */ bool probably_never_executed_bb_p (struct function *fun, const_basic_block bb) { return probably_never_executed (fun, bb->count, bb->frequency); } /* Return true in case edge E is probably never executed. */ bool probably_never_executed_edge_p (struct function *fun, edge e) { return probably_never_executed (fun, e->count, EDGE_FREQUENCY (e)); } /* Return true if NODE should be optimized for size. */ bool cgraph_optimize_for_size_p (struct cgraph_node *node) { if (optimize_size) return true; if (node && (node->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED)) return true; else return false; } /* Return true when current function should always be optimized for size. */ bool optimize_function_for_size_p (struct function *fun) { if (optimize_size) return true; if (!fun || !fun->decl) return false; return cgraph_optimize_for_size_p (cgraph_get_node (fun->decl)); } /* Return true when current function should always be optimized for speed. */ bool optimize_function_for_speed_p (struct function *fun) { return !optimize_function_for_size_p (fun); } /* Return TRUE when BB should be optimized for size. */ bool optimize_bb_for_size_p (const_basic_block bb) { return optimize_function_for_size_p (cfun) || !maybe_hot_bb_p (cfun, bb); } /* Return TRUE when BB should be optimized for speed. */ bool optimize_bb_for_speed_p (const_basic_block bb) { return !optimize_bb_for_size_p (bb); } /* Return TRUE when BB should be optimized for size. */ bool optimize_edge_for_size_p (edge e) { return optimize_function_for_size_p (cfun) || !maybe_hot_edge_p (e); } /* Return TRUE when BB should be optimized for speed. */ bool optimize_edge_for_speed_p (edge e) { return !optimize_edge_for_size_p (e); } /* Return TRUE when BB should be optimized for size. */ bool optimize_insn_for_size_p (void) { return optimize_function_for_size_p (cfun) || !crtl->maybe_hot_insn_p; } /* Return TRUE when BB should be optimized for speed. */ bool optimize_insn_for_speed_p (void) { return !optimize_insn_for_size_p (); } /* Return TRUE when LOOP should be optimized for size. */ bool optimize_loop_for_size_p (struct loop *loop) { return optimize_bb_for_size_p (loop->header); } /* Return TRUE when LOOP should be optimized for speed. */ bool optimize_loop_for_speed_p (struct loop *loop) { return optimize_bb_for_speed_p (loop->header); } /* Return TRUE when LOOP nest should be optimized for speed. */ bool optimize_loop_nest_for_speed_p (struct loop *loop) { struct 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 when LOOP nest should be optimized for size. */ bool optimize_loop_nest_for_size_p (struct loop *loop) { return !optimize_loop_nest_for_speed_p (loop); } /* Return true when edge E is likely to be well predictable by branch predictor. */ bool predictable_edge_p (edge e) { if (profile_status_for_fn (cfun) == PROFILE_ABSENT) return false; if ((e->probability <= PARAM_VALUE (PARAM_PREDICTABLE_BRANCH_OUTCOME) * REG_BR_PROB_BASE / 100) || (REG_BR_PROB_BASE - e->probability <= PARAM_VALUE (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; } /* This map contains for a basic block the list of predictions for the outgoing edges. */ static struct pointer_map_t *bb_predictions; /* 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; }; /* 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; void **preds = pointer_map_contains (bb_predictions, bb); if (!preds) return false; for (i = (struct edge_prediction *) *preds; i; i = i->ep_next) if (i->ep_predictor == predictor) return true; return false; } /* Return true when the probability of edge is reliable. The profile guessing code is good at predicting branch outcome (ie. taken/not taken), that is predicted right slightly over 75% of time. It is however notoriously poor on predicting the probability itself. In general the profile appear a lot flatter (with probabilities closer to 50%) than the reality so it is bad idea to use it to drive optimization such as those disabling dynamic branch prediction for well predictable branches. There are two exceptions - edges leading to noreturn edges and edges predicted by number of iterations heuristics are predicted well. This macro should be able to distinguish those, but at the moment it simply check for noreturn heuristic that is only one giving probability over 99% or bellow 1%. In future we might want to propagate reliability information across the CFG if we find this information useful on multiple places. */ static bool probability_reliable_p (int prob) { return (profile_status_for_fn (cfun) == PROFILE_READ || (profile_status_for_fn (cfun) == PROFILE_GUESSED && (prob <= HITRATE (1) || prob >= HITRATE (99)))); } /* Same predicate as above, working on edges. */ bool edge_probability_reliable_p (const_edge e) { return probability_reliable_p (e->probability); } /* Same predicate as edge_probability_reliable_p, working on notes. */ bool br_prob_note_reliable_p (const_rtx note) { gcc_assert (REG_NOTE_KIND (note) == REG_BR_PROB); return probability_reliable_p (XINT (note, 0)); } static void predict_insn (rtx insn, 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, enum br_predictor predictor, enum prediction taken) { int probability = predictor_info[(int) predictor].hitrate; if (taken != TAKEN) probability = REG_BR_PROB_BASE - probability; predict_insn (insn, predictor, probability); } /* Predict edge E with given probability if possible. */ void rtl_predict_edge (edge e, enum br_predictor predictor, int probability) { rtx last_insn; last_insn = BB_END (e->src); /* We can store the branch prediction information only about conditional jumps. */ if (!any_condjump_p (last_insn)) return; /* We always store probability of branching. */ if (e->flags & EDGE_FALLTHRU) probability = REG_BR_PROB_BASE - probability; predict_insn (last_insn, predictor, probability); } /* Predict edge E with the given PROBABILITY. */ void gimple_predict_edge (edge e, enum br_predictor predictor, int probability) { gcc_assert (profile_status_for_fn (cfun) != PROFILE_GUESSED); if ((e->src != ENTRY_BLOCK_PTR_FOR_FN (cfun) && EDGE_COUNT (e->src->succs) > 1) && flag_guess_branch_prob && optimize) { struct edge_prediction *i = XNEW (struct edge_prediction); void **preds = pointer_map_insert (bb_predictions, e->src); i->ep_next = (struct edge_prediction *) *preds; *preds = i; i->ep_probability = probability; i->ep_predictor = predictor; i->ep_edge = e; } } /* Remove all predictions on given basic block that are attached to edge E. */ void remove_predictions_associated_with_edge (edge e) { void **preds; if (!bb_predictions) return; preds = pointer_map_contains (bb_predictions, e->src); if (preds) { struct edge_prediction **prediction = (struct edge_prediction **) preds; struct edge_prediction *next; while (*prediction) { if ((*prediction)->ep_edge == e) { next = (*prediction)->ep_next; free (*prediction); *prediction = next; } else prediction = &((*prediction)->ep_next); } } } /* Clears the list of predictions stored for BB. */ static void clear_bb_predictions (basic_block bb) { void **preds = pointer_map_contains (bb_predictions, bb); struct edge_prediction *pred, *next; if (!preds) return; for (pred = (struct edge_prediction *) *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) { return (JUMP_P (insn) && any_condjump_p (insn) && EDGE_COUNT (BLOCK_FOR_INSN (insn)->succs) >= 2); } /* Predict edge E by given predictor if possible. */ void predict_edge_def (edge e, enum br_predictor predictor, enum prediction taken) { int probability = predictor_info[(int) predictor].hitrate; if (taken != TAKEN) probability = REG_BR_PROB_BASE - probability; predict_edge (e, predictor, probability); } /* Invert all branch predictions or probability notes in the INSN. This needs to be done each time we invert the condition used by the jump. */ void invert_br_probabilities (rtx insn) { rtx note; for (note = REG_NOTES (insn); note; note = XEXP (note, 1)) if (REG_NOTE_KIND (note) == REG_BR_PROB) XINT (note, 0) = REG_BR_PROB_BASE - XINT (note, 0); else if (REG_NOTE_KIND (note) == REG_BR_PRED) XEXP (XEXP (note, 0), 1) = GEN_INT (REG_BR_PROB_BASE - INTVAL (XEXP (XEXP (note, 0), 1))); } /* Dump information about the branch prediction to the output file. */ static void dump_prediction (FILE *file, enum br_predictor predictor, int probability, basic_block bb, int used) { edge e; edge_iterator ei; if (!file) return; FOR_EACH_EDGE (e, ei, bb->succs) if (! (e->flags & EDGE_FALLTHRU)) break; fprintf (file, " %s heuristics%s: %.1f%%", predictor_info[predictor].name, used ? "" : " (ignored)", probability * 100.0 / REG_BR_PROB_BASE); if (bb->count) { fprintf (file, " exec "); fprintf (file, HOST_WIDEST_INT_PRINT_DEC, bb->count); if (e) { fprintf (file, " hit "); fprintf (file, HOST_WIDEST_INT_PRINT_DEC, e->count); fprintf (file, " (%.1f%%)", e->count * 100.0 / bb->count); } } fprintf (file, "\n"); } /* We can not predict the probabilities of outgoing edges of bb. Set them evenly and hope for the best. */ static void set_even_probabilities (basic_block bb) { int nedges = 0; edge e; edge_iterator ei; FOR_EACH_EDGE (e, ei, bb->succs) if (!(e->flags & (EDGE_EH | EDGE_FAKE))) nedges ++; FOR_EACH_EDGE (e, ei, bb->succs) if (!(e->flags & (EDGE_EH | EDGE_FAKE))) e->probability = (REG_BR_PROB_BASE + nedges / 2) / nedges; else e->probability = 0; } /* Combine all REG_BR_PRED notes into single probability and attach REG_BR_PROB note if not already present. Remove now useless REG_BR_PRED notes. */ static void combine_predictions_for_insn (rtx insn, basic_block bb) { rtx prob_note; rtx *pnote; rtx note; int best_probability = PROB_EVEN; enum br_predictor best_predictor = END_PREDICTORS; int combined_probability = REG_BR_PROB_BASE / 2; int d; bool first_match = false; bool found = false; if (!can_predict_insn_p (insn)) { set_even_probabilities (bb); return; } prob_note = find_reg_note (insn, REG_BR_PROB, 0); pnote = ®_NOTES (insn); if (dump_file) fprintf (dump_file, "Predictions for insn %i bb %i\n", INSN_UID (insn), bb->index); /* We implement "first match" heuristics and use probability guessed by predictor with smallest index. */ for (note = REG_NOTES (insn); note; note = XEXP (note, 1)) if (REG_NOTE_KIND (note) == REG_BR_PRED) { enum br_predictor predictor = ((enum br_predictor) INTVAL (XEXP (XEXP (note, 0), 0))); int probability = INTVAL (XEXP (XEXP (note, 0), 1)); found = true; if (best_predictor > predictor) best_probability = probability, best_predictor = predictor; d = (combined_probability * probability + (REG_BR_PROB_BASE - combined_probability) * (REG_BR_PROB_BASE - probability)); /* Use FP math to avoid overflows of 32bit integers. */ if (d == 0) /* If one probability is 0% and one 100%, avoid division by zero. */ combined_probability = REG_BR_PROB_BASE / 2; else combined_probability = (((double) combined_probability) * probability * REG_BR_PROB_BASE / d + 0.5); } /* Decide which heuristic to use. In case we didn't match anything, use no_prediction heuristic, in case we did match, use either first match or Dempster-Shaffer theory depending on the flags. */ if (predictor_info [best_predictor].flags & PRED_FLAG_FIRST_MATCH) first_match = true; if (!found) dump_prediction (dump_file, PRED_NO_PREDICTION, combined_probability, bb, true); else { dump_prediction (dump_file, PRED_DS_THEORY, combined_probability, bb, !first_match); dump_prediction (dump_file, PRED_FIRST_MATCH, best_probability, bb, first_match); } if (first_match) combined_probability = best_probability; dump_prediction (dump_file, PRED_COMBINED, combined_probability, bb, true); while (*pnote) { if (REG_NOTE_KIND (*pnote) == REG_BR_PRED) { enum br_predictor predictor = ((enum br_predictor) INTVAL (XEXP (XEXP (*pnote, 0), 0))); int probability = INTVAL (XEXP (XEXP (*pnote, 0), 1)); dump_prediction (dump_file, predictor, probability, bb, !first_match || best_predictor == predictor); *pnote = XEXP (*pnote, 1); } else pnote = &XEXP (*pnote, 1); } if (!prob_note) { add_int_reg_note (insn, REG_BR_PROB, combined_probability); /* Save the prediction into CFG in case we are seeing non-degenerated conditional jump. */ if (!single_succ_p (bb)) { BRANCH_EDGE (bb)->probability = combined_probability; FALLTHRU_EDGE (bb)->probability = REG_BR_PROB_BASE - combined_probability; } } else if (!single_succ_p (bb)) { int prob = XINT (prob_note, 0); BRANCH_EDGE (bb)->probability = prob; FALLTHRU_EDGE (bb)->probability = REG_BR_PROB_BASE - prob; } else single_succ_edge (bb)->probability = REG_BR_PROB_BASE; } /* Combine predictions into single probability and store them into CFG. Remove now useless prediction entries. */ static void combine_predictions_for_bb (basic_block bb) { int best_probability = PROB_EVEN; enum br_predictor best_predictor = END_PREDICTORS; int combined_probability = REG_BR_PROB_BASE / 2; int d; bool first_match = false; bool found = false; struct edge_prediction *pred; int nedges = 0; edge e, first = NULL, second = NULL; edge_iterator ei; void **preds; FOR_EACH_EDGE (e, ei, bb->succs) if (!(e->flags & (EDGE_EH | EDGE_FAKE))) { nedges ++; if (first && !second) second = e; if (!first) first = e; } /* When there is no successor or only one choice, prediction is easy. We are lazy for now and predict only basic blocks with two outgoing edges. It is possible to predict generic case too, but we have to ignore first match heuristics and do more involved combining. Implement this later. */ if (nedges != 2) { if (!bb->count) set_even_probabilities (bb); clear_bb_predictions (bb); if (dump_file) fprintf (dump_file, "%i edges in bb %i predicted to even probabilities\n", nedges, bb->index); return; } if (dump_file) fprintf (dump_file, "Predictions for bb %i\n", bb->index); preds = pointer_map_contains (bb_predictions, bb); if (preds) { /* We implement "first match" heuristics and use probability guessed by predictor with smallest index. */ for (pred = (struct edge_prediction *) *preds; pred; pred = pred->ep_next) { enum br_predictor predictor = pred->ep_predictor; int probability = pred->ep_probability; if (pred->ep_edge != first) probability = REG_BR_PROB_BASE - probability; found = true; /* First match heuristics would be widly confused if we predicted both directions. */ if (best_predictor > predictor) { struct edge_prediction *pred2; int prob = probability; for (pred2 = (struct edge_prediction *) *preds; pred2; pred2 = pred2->ep_next) if (pred2 != pred && pred2->ep_predictor == pred->ep_predictor) { int probability2 = pred->ep_probability; if (pred2->ep_edge != first) probability2 = REG_BR_PROB_BASE - probability2; if ((probability < REG_BR_PROB_BASE / 2) != (probability2 < REG_BR_PROB_BASE / 2)) break; /* If the same predictor later gave better result, go for it! */ if ((probability >= REG_BR_PROB_BASE / 2 && (probability2 > probability)) || (probability <= REG_BR_PROB_BASE / 2 && (probability2 < probability))) prob = probability2; } if (!pred2) best_probability = prob, best_predictor = predictor; } d = (combined_probability * probability + (REG_BR_PROB_BASE - combined_probability) * (REG_BR_PROB_BASE - probability)); /* Use FP math to avoid overflows of 32bit integers. */ if (d == 0) /* If one probability is 0% and one 100%, avoid division by zero. */ combined_probability = REG_BR_PROB_BASE / 2; else combined_probability = (((double) combined_probability) * probability * REG_BR_PROB_BASE / d + 0.5); } } /* Decide which heuristic to use. In case we didn't match anything, use no_prediction heuristic, in case we did match, use either first match or Dempster-Shaffer theory depending on the flags. */ if (predictor_info [best_predictor].flags & PRED_FLAG_FIRST_MATCH) first_match = true; if (!found) dump_prediction (dump_file, PRED_NO_PREDICTION, combined_probability, bb, true); else { dump_prediction (dump_file, PRED_DS_THEORY, combined_probability, bb, !first_match); dump_prediction (dump_file, PRED_FIRST_MATCH, best_probability, bb, first_match); } if (first_match) combined_probability = best_probability; dump_prediction (dump_file, PRED_COMBINED, combined_probability, bb, true); if (preds) { for (pred = (struct edge_prediction *) *preds; pred; pred = pred->ep_next) { enum br_predictor predictor = pred->ep_predictor; int probability = pred->ep_probability; if (pred->ep_edge != EDGE_SUCC (bb, 0)) probability = REG_BR_PROB_BASE - probability; dump_prediction (dump_file, predictor, probability, bb, !first_match || best_predictor == predictor); } } clear_bb_predictions (bb); if (!bb->count) { first->probability = combined_probability; second->probability = REG_BR_PROB_BASE - combined_probability; if (flag_check_branch_annotation && first_match && best_predictor == PRED_BUILTIN_EXPECT) { first->flags |= EDGE_PREDICTED_BY_EXPECT; second->flags |= EDGE_PREDICTED_BY_EXPECT; } } } /* 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 (gimple stmt, struct loop *loop, tree *loop_invariant, enum tree_code *compare_code, tree *loop_step, tree *loop_iv_base) { tree op0, op1, bound, base; affine_iv iv0, iv1; enum tree_code code; tree step; code = gimple_cond_code (stmt); *loop_invariant = NULL; switch (code) { case GT_EXPR: case GE_EXPR: case NE_EXPR: case LT_EXPR: case LE_EXPR: case EQ_EXPR: break; default: return false; } op0 = gimple_cond_lhs (stmt); op1 = gimple_cond_rhs (stmt); if ((TREE_CODE (op0) != SSA_NAME && TREE_CODE (op0) != INTEGER_CST) || (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op1) != INTEGER_CST)) return false; if (!simple_iv (loop, loop_containing_stmt (stmt), op0, &iv0, true)) return false; if (!simple_iv (loop, loop_containing_stmt (stmt), op1, &iv1, true)) return false; if (TREE_CODE (iv0.step) != INTEGER_CST || TREE_CODE (iv1.step) != INTEGER_CST) return false; if ((integer_zerop (iv0.step) && integer_zerop (iv1.step)) || (!integer_zerop (iv0.step) && !integer_zerop (iv1.step))) return false; if (integer_zerop (iv0.step)) { if (code != NE_EXPR && code != EQ_EXPR) code = invert_tree_comparison (code, false); bound = iv0.base; base = iv1.base; if (tree_fits_shwi_p (iv1.step)) step = iv1.step; else return false; } else { bound = iv1.base; base = iv0.base; if (tree_fits_shwi_p (iv0.step)) step = iv0.step; else return false; } if (TREE_CODE (bound) != INTEGER_CST) bound = get_base_value (bound); if (!bound) return false; if (TREE_CODE (base) != INTEGER_CST) base = get_base_value (base); if (!base) return false; *loop_invariant = bound; *compare_code = code; *loop_step = step; *loop_iv_base = base; return true; } /* Compare two SSA_NAMEs: returns TRUE if T1 and T2 are value coherent. */ static bool expr_coherent_p (tree t1, tree t2) { gimple stmt; tree ssa_name_1 = NULL; tree ssa_name_2 = NULL; gcc_assert (TREE_CODE (t1) == SSA_NAME || TREE_CODE (t1) == INTEGER_CST); gcc_assert (TREE_CODE (t2) == SSA_NAME || TREE_CODE (t2) == INTEGER_CST); if (t1 == t2) return true; if (TREE_CODE (t1) == INTEGER_CST && TREE_CODE (t2) == INTEGER_CST) return true; if (TREE_CODE (t1) == INTEGER_CST || TREE_CODE (t2) == INTEGER_CST) return false; /* Check to see if t1 is expressed/defined with t2. */ stmt = SSA_NAME_DEF_STMT (t1); gcc_assert (stmt != NULL); if (is_gimple_assign (stmt)) { ssa_name_1 = SINGLE_SSA_TREE_OPERAND (stmt, SSA_OP_USE); if (ssa_name_1 && ssa_name_1 == t2) return true; } /* Check to see if t2 is expressed/defined with t1. */ stmt = SSA_NAME_DEF_STMT (t2); gcc_assert (stmt != NULL); if (is_gimple_assign (stmt)) { ssa_name_2 = SINGLE_SSA_TREE_OPERAND (stmt, SSA_OP_USE); if (ssa_name_2 && ssa_name_2 == t1) return true; } /* Compare if t1 and t2's def_stmts are identical. */ if (ssa_name_2 != NULL && ssa_name_1 == ssa_name_2) return true; else return false; } /* Predict branch probability of BB when BB contains a branch that compares an induction variable in LOOP with LOOP_IV_BASE_VAR to LOOP_BOUND_VAR. The loop exit is compared using LOOP_BOUND_CODE, with step of LOOP_BOUND_STEP. E.g. for (int i = 0; i < bound; i++) { if (i < bound - 2) computation_1(); else computation_2(); } In this loop, we will predict the branch inside the loop to be taken. */ static void predict_iv_comparison (struct loop *loop, basic_block bb, tree loop_bound_var, tree loop_iv_base_var, enum tree_code loop_bound_code, int loop_bound_step) { gimple stmt; tree compare_var, compare_base; enum tree_code compare_code; tree compare_step_var; edge then_edge; edge_iterator ei; if (predicted_by_p (bb, PRED_LOOP_ITERATIONS_GUESSED) || predicted_by_p (bb, PRED_LOOP_ITERATIONS) || predicted_by_p (bb, PRED_LOOP_EXIT)) return; stmt = last_stmt (bb); if (!stmt || gimple_code (stmt) != GIMPLE_COND) return; if (!is_comparison_with_loop_invariant_p (stmt, loop, &compare_var, &compare_code, &compare_step_var, &compare_base)) return; /* Find the taken edge. */ FOR_EACH_EDGE (then_edge, ei, bb->succs) if (then_edge->flags & EDGE_TRUE_VALUE) break; /* When comparing an IV to a loop invariant, NE is more likely to be taken while EQ is more likely to be not-taken. */ if (compare_code == NE_EXPR) { predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); return; } else if (compare_code == EQ_EXPR) { predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN); return; } if (!expr_coherent_p (loop_iv_base_var, compare_base)) return; /* If loop bound, base and compare bound are all constants, we can calculate the probability directly. */ if (tree_fits_shwi_p (loop_bound_var) && tree_fits_shwi_p (compare_var) && tree_fits_shwi_p (compare_base)) { int probability; bool of, overflow = false; double_int mod, compare_count, tem, loop_count; double_int loop_bound = tree_to_double_int (loop_bound_var); double_int compare_bound = tree_to_double_int (compare_var); double_int base = tree_to_double_int (compare_base); double_int compare_step = tree_to_double_int (compare_step_var); /* (loop_bound - base) / compare_step */ tem = loop_bound.sub_with_overflow (base, &of); overflow |= of; loop_count = tem.divmod_with_overflow (compare_step, 0, TRUNC_DIV_EXPR, &mod, &of); overflow |= of; if ((!compare_step.is_negative ()) ^ (compare_code == LT_EXPR || compare_code == LE_EXPR)) { /* (loop_bound - compare_bound) / compare_step */ tem = loop_bound.sub_with_overflow (compare_bound, &of); overflow |= of; compare_count = tem.divmod_with_overflow (compare_step, 0, TRUNC_DIV_EXPR, &mod, &of); overflow |= of; } else { /* (compare_bound - base) / compare_step */ tem = compare_bound.sub_with_overflow (base, &of); overflow |= of; compare_count = tem.divmod_with_overflow (compare_step, 0, TRUNC_DIV_EXPR, &mod, &of); overflow |= of; } 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 (compare_count.is_negative ()) compare_count = double_int_zero; if (loop_count.is_negative ()) loop_count = double_int_zero; if (loop_count.is_zero ()) probability = 0; else if (compare_count.scmp (loop_count) == 1) probability = REG_BR_PROB_BASE; else { /* If loop_count is too big, such that REG_BR_PROB_BASE * loop_count could overflow, shift both loop_count and compare_count right a bit so that it doesn't overflow. Note both counts are known not to be negative at this point. */ int clz_bits = clz_hwi (loop_count.high); gcc_assert (REG_BR_PROB_BASE < 32768); if (clz_bits < 16) { loop_count.arshift (16 - clz_bits, HOST_BITS_PER_DOUBLE_INT); compare_count.arshift (16 - clz_bits, HOST_BITS_PER_DOUBLE_INT); } tem = compare_count.mul_with_sign (double_int::from_shwi (REG_BR_PROB_BASE), true, &of); gcc_assert (!of); tem = tem.divmod (loop_count, true, TRUNC_DIV_EXPR, &mod); probability = tem.to_uhwi (); } if (!overflow) predict_edge (then_edge, PRED_LOOP_IV_COMPARE, probability); return; } if (expr_coherent_p (loop_bound_var, compare_var)) { if ((loop_bound_code == LT_EXPR || loop_bound_code == LE_EXPR) && (compare_code == LT_EXPR || compare_code == LE_EXPR)) predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); else if ((loop_bound_code == GT_EXPR || loop_bound_code == GE_EXPR) && (compare_code == GT_EXPR || compare_code == GE_EXPR)) predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); else if (loop_bound_code == NE_EXPR) { /* If the loop backedge condition is "(i != bound)", we do the comparison based on the step of IV: * step < 0 : backedge condition is like (i > bound) * step > 0 : backedge condition is like (i < bound) */ gcc_assert (loop_bound_step != 0); if (loop_bound_step > 0 && (compare_code == LT_EXPR || compare_code == LE_EXPR)) predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); else if (loop_bound_step < 0 && (compare_code == GT_EXPR || compare_code == GE_EXPR)) predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); else predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN); } else /* The branch is predicted not-taken if loop_bound_code is opposite with compare_code. */ predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN); } else if (expr_coherent_p (loop_iv_base_var, compare_var)) { /* For cases like: for (i = s; i < h; i++) if (i > s + 2) .... The branch should be predicted taken. */ if (loop_bound_step > 0 && (compare_code == GT_EXPR || compare_code == GE_EXPR)) predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); else if (loop_bound_step < 0 && (compare_code == LT_EXPR || compare_code == LE_EXPR)) predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, TAKEN); else predict_edge_def (then_edge, PRED_LOOP_IV_COMPARE_GUESS, NOT_TAKEN); } } /* Predict for extra loop exits that will lead to EXIT_EDGE. The extra loop exits are resulted from short-circuit conditions that will generate an if_tmp. E.g.: if (foo() || global > 10) break; This will be translated into: BB3: loop header... BB4: if foo() goto BB6 else goto BB5 BB5: if global > 10 goto BB6 else goto BB7 BB6: goto BB7 BB7: iftmp = (PHI 0(BB5), 1(BB6)) if iftmp == 1 goto BB8 else goto BB3 BB8: outside of the loop... The edge BB7->BB8 is loop exit because BB8 is outside of the loop. From the dataflow, we can infer that BB4->BB6 and BB5->BB6 are also loop exits. This function takes BB7->BB8 as input, and finds out the extra loop exits to predict them using PRED_LOOP_EXIT. */ static void predict_extra_loop_exits (edge exit_edge) { unsigned i; bool check_value_one; gimple phi_stmt; tree cmp_rhs, cmp_lhs; gimple cmp_stmt = last_stmt (exit_edge->src); if (!cmp_stmt || gimple_code (cmp_stmt) != GIMPLE_COND) 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)); phi_stmt = SSA_NAME_DEF_STMT (cmp_lhs); if (!phi_stmt || gimple_code (phi_stmt) != GIMPLE_PHI) return; for (i = 0; i < gimple_phi_num_args (phi_stmt); i++) { edge e1; edge_iterator ei; tree val = gimple_phi_arg_def (phi_stmt, i); edge e = gimple_phi_arg_edge (phi_stmt, i); if (!TREE_CONSTANT (val) || !(integer_zerop (val) || integer_onep (val))) continue; if ((check_value_one ^ integer_onep (val)) == 1) continue; if (EDGE_COUNT (e->src->succs) != 1) { predict_paths_leading_to_edge (e, PRED_LOOP_EXIT, NOT_TAKEN); continue; } FOR_EACH_EDGE (e1, ei, e->src->preds) predict_paths_leading_to_edge (e1, PRED_LOOP_EXIT, NOT_TAKEN); } } /* Predict edge probabilities by exploiting loop structure. */ static void predict_loops (void) { struct loop *loop; /* Try to predict out blocks in a loop that are not part of a natural loop. */ FOR_EACH_LOOP (loop, 0) { basic_block bb, *bbs; unsigned j, n_exits; vec exits; struct tree_niter_desc niter_desc; edge ex; struct nb_iter_bound *nb_iter; enum tree_code loop_bound_code = ERROR_MARK; tree loop_bound_step = NULL; tree loop_bound_var = NULL; tree loop_iv_base = NULL; gimple stmt = NULL; exits = get_loop_exit_edges (loop); n_exits = exits.length (); if (!n_exits) { exits.release (); continue; } FOR_EACH_VEC_ELT (exits, j, ex) { tree niter = NULL; HOST_WIDE_INT nitercst; int max = PARAM_VALUE (PARAM_MAX_PREDICTED_ITERATIONS); int probability; enum br_predictor predictor; predict_extra_loop_exits (ex); if (number_of_iterations_exit (loop, ex, &niter_desc, false, false)) niter = niter_desc.niter; if (!niter || TREE_CODE (niter_desc.niter) != INTEGER_CST) niter = loop_niter_by_eval (loop, ex); if (TREE_CODE (niter) == INTEGER_CST) { if (tree_fits_uhwi_p (niter) && max && compare_tree_int (niter, max - 1) == -1) nitercst = tree_to_uhwi (niter) + 1; else nitercst = max; predictor = PRED_LOOP_ITERATIONS; } /* If we have just one exit and we can derive some information about the number of iterations of the loop from the statements inside the loop, use it to predict this exit. */ else if (n_exits == 1) { nitercst = estimated_stmt_executions_int (loop); if (nitercst < 0) continue; if (nitercst > max) nitercst = max; predictor = PRED_LOOP_ITERATIONS_GUESSED; } else continue; /* If the prediction for number of iterations is zero, do not predict the exit edges. */ if (nitercst == 0) continue; probability = ((REG_BR_PROB_BASE + nitercst / 2) / nitercst); predict_edge (ex, predictor, probability); } exits.release (); /* Find information about loop bound variables. */ for (nb_iter = loop->bounds; nb_iter; nb_iter = nb_iter->next) if (nb_iter->stmt && gimple_code (nb_iter->stmt) == GIMPLE_COND) { stmt = nb_iter->stmt; break; } if (!stmt && last_stmt (loop->header) && gimple_code (last_stmt (loop->header)) == GIMPLE_COND) stmt = last_stmt (loop->header); if (stmt) is_comparison_with_loop_invariant_p (stmt, loop, &loop_bound_var, &loop_bound_code, &loop_bound_step, &loop_iv_base); bbs = get_loop_body (loop); for (j = 0; j < loop->num_nodes; j++) { int header_found = 0; edge e; edge_iterator ei; bb = bbs[j]; /* Bypass loop heuristics on continue statement. These statements construct loops via "non-loop" constructs in the source language and are better to be handled separately. */ if (predicted_by_p (bb, PRED_CONTINUE)) continue; /* Loop branch heuristics - predict an edge back to a loop's head as taken. */ if (bb == loop->latch) { e = find_edge (loop->latch, loop->header); if (e) { header_found = 1; predict_edge_def (e, PRED_LOOP_BRANCH, TAKEN); } } /* Loop exit heuristics - predict an edge exiting the loop if the conditional has no loop header successors as not taken. */ if (!header_found /* If we already used more reliable loop exit predictors, do not bother with PRED_LOOP_EXIT. */ && !predicted_by_p (bb, PRED_LOOP_ITERATIONS_GUESSED) && !predicted_by_p (bb, PRED_LOOP_ITERATIONS)) { /* For loop with many exits we don't want to predict all exits with the pretty large probability, because if all exits are considered in row, the loop would be predicted to iterate almost never. The code to divide probability by number of exits is very rough. It should compute the number of exits taken in each patch through function (not the overall number of exits that might be a lot higher for loops with wide switch statements in them) and compute n-th square root. We limit the minimal probability by 2% to avoid EDGE_PROBABILITY_RELIABLE from trusting the branch prediction as this was causing regression in perl benchmark containing such a wide loop. */ int probability = ((REG_BR_PROB_BASE - predictor_info [(int) PRED_LOOP_EXIT].hitrate) / n_exits); if (probability < HITRATE (2)) probability = HITRATE (2); FOR_EACH_EDGE (e, ei, bb->succs) if (e->dest->index < NUM_FIXED_BLOCKS || !flow_bb_inside_loop_p (loop, e->dest)) predict_edge (e, PRED_LOOP_EXIT, probability); } if (loop_bound_var) predict_iv_comparison (loop, bb, loop_bound_var, loop_iv_base, loop_bound_code, tree_to_shwi (loop_bound_step)); } /* Free basic blocks from get_loop_body. */ free (bbs); } } /* Attempt to predict probabilities of BB outgoing edges using local properties. */ static void bb_estimate_probability_locally (basic_block bb) { rtx last_insn = BB_END (bb); rtx cond; if (! can_predict_insn_p (last_insn)) return; cond = get_condition (last_insn, NULL, false, false); if (! cond) return; /* Try "pointer heuristic." A comparison ptr == 0 is predicted as false. Similarly, a comparison ptr1 == ptr2 is predicted as false. */ if (COMPARISON_P (cond) && ((REG_P (XEXP (cond, 0)) && REG_POINTER (XEXP (cond, 0))) || (REG_P (XEXP (cond, 1)) && REG_POINTER (XEXP (cond, 1))))) { if (GET_CODE (cond) == EQ) predict_insn_def (last_insn, PRED_POINTER, NOT_TAKEN); else if (GET_CODE (cond) == NE) predict_insn_def (last_insn, PRED_POINTER, TAKEN); } else /* Try "opcode heuristic." EQ tests are usually false and NE tests are usually true. Also, most quantities are positive, so we can make the appropriate guesses about signed comparisons against zero. */ switch (GET_CODE (cond)) { case CONST_INT: /* Unconditional branch. */ predict_insn_def (last_insn, PRED_UNCONDITIONAL, cond == const0_rtx ? NOT_TAKEN : TAKEN); break; case EQ: case UNEQ: /* Floating point comparisons appears to behave in a very unpredictable way because of special role of = tests in FP code. */ if (FLOAT_MODE_P (GET_MODE (XEXP (cond, 0)))) ; /* Comparisons with 0 are often used for booleans and there is nothing useful to predict about them. */ else if (XEXP (cond, 1) == const0_rtx || XEXP (cond, 0) == const0_rtx) ; else predict_insn_def (last_insn, PRED_OPCODE_NONEQUAL, NOT_TAKEN); break; case NE: case LTGT: /* Floating point comparisons appears to behave in a very unpredictable way because of special role of = tests in FP code. */ if (FLOAT_MODE_P (GET_MODE (XEXP (cond, 0)))) ; /* Comparisons with 0 are often used for booleans and there is nothing useful to predict about them. */ else if (XEXP (cond, 1) == const0_rtx || XEXP (cond, 0) == const0_rtx) ; else predict_insn_def (last_insn, PRED_OPCODE_NONEQUAL, TAKEN); break; case ORDERED: predict_insn_def (last_insn, PRED_FPOPCODE, TAKEN); break; case UNORDERED: predict_insn_def (last_insn, PRED_FPOPCODE, NOT_TAKEN); break; case LE: case LT: if (XEXP (cond, 1) == const0_rtx || XEXP (cond, 1) == const1_rtx || XEXP (cond, 1) == constm1_rtx) predict_insn_def (last_insn, PRED_OPCODE_POSITIVE, NOT_TAKEN); break; case GE: case GT: if (XEXP (cond, 1) == const0_rtx || XEXP (cond, 1) == const1_rtx || XEXP (cond, 1) == constm1_rtx) predict_insn_def (last_insn, PRED_OPCODE_POSITIVE, TAKEN); break; default: break; } } /* Set edge->probability for each successor edge of BB. */ void guess_outgoing_edge_probabilities (basic_block bb) { bb_estimate_probability_locally (bb); combine_predictions_for_insn (BB_END (bb), bb); } static tree expr_expected_value (tree, bitmap, enum br_predictor *predictor); /* Helper function for expr_expected_value. */ static tree expr_expected_value_1 (tree type, tree op0, enum tree_code code, tree op1, bitmap visited, enum br_predictor *predictor) { gimple def; if (predictor) *predictor = PRED_UNCONDITIONAL; if (get_gimple_rhs_class (code) == GIMPLE_SINGLE_RHS) { if (TREE_CONSTANT (op0)) return op0; if (code != SSA_NAME) return NULL_TREE; def = SSA_NAME_DEF_STMT (op0); /* If we were already here, break the infinite cycle. */ if (!bitmap_set_bit (visited, SSA_NAME_VERSION (op0))) return NULL; if (gimple_code (def) == GIMPLE_PHI) { /* All the arguments of the PHI node must have the same constant length. */ int i, n = gimple_phi_num_args (def); tree val = NULL, new_val; for (i = 0; i < n; i++) { tree arg = PHI_ARG_DEF (def, i); enum br_predictor predictor2; /* If this PHI has itself as an argument, we cannot determine the string length of this argument. However, if we can find an expected constant value for the other PHI args then we can still be sure that this is likely a constant. So be optimistic and just continue with the next argument. */ if (arg == PHI_RESULT (def)) continue; new_val = expr_expected_value (arg, visited, &predictor2); /* It is difficult to combine value predictors. Simply assume that later predictor is weaker and take its prediction. */ if (predictor && *predictor < predictor2) *predictor = predictor2; if (!new_val) return NULL; if (!val) val = new_val; else if (!operand_equal_p (val, new_val, false)) return NULL; } return val; } if (is_gimple_assign (def)) { if (gimple_assign_lhs (def) != op0) return NULL; return expr_expected_value_1 (TREE_TYPE (gimple_assign_lhs (def)), gimple_assign_rhs1 (def), gimple_assign_rhs_code (def), gimple_assign_rhs2 (def), visited, predictor); } if (is_gimple_call (def)) { tree decl = gimple_call_fndecl (def); if (!decl) { if (gimple_call_internal_p (def) && gimple_call_internal_fn (def) == IFN_BUILTIN_EXPECT) { gcc_assert (gimple_call_num_args (def) == 3); tree val = gimple_call_arg (def, 0); if (TREE_CONSTANT (val)) return val; if (predictor) { *predictor = PRED_BUILTIN_EXPECT; tree val2 = gimple_call_arg (def, 2); gcc_assert (TREE_CODE (val2) == INTEGER_CST && tree_fits_uhwi_p (val2) && tree_to_uhwi (val2) < END_PREDICTORS); *predictor = (enum br_predictor) tree_to_uhwi (val2); } return gimple_call_arg (def, 1); } return NULL; } if (DECL_BUILT_IN_CLASS (decl) == BUILT_IN_NORMAL) switch (DECL_FUNCTION_CODE (decl)) { case BUILT_IN_EXPECT: { tree val; if (gimple_call_num_args (def) != 2) return NULL; val = gimple_call_arg (def, 0); if (TREE_CONSTANT (val)) return val; if (predictor) *predictor = PRED_BUILTIN_EXPECT; return gimple_call_arg (def, 1); } case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_N: case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_1: case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_2: case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_4: case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_8: case BUILT_IN_SYNC_BOOL_COMPARE_AND_SWAP_16: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_N: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_1: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_2: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_4: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_8: case BUILT_IN_ATOMIC_COMPARE_EXCHANGE_16: /* Assume that any given atomic operation has low contention, and thus the compare-and-swap operation succeeds. */ if (predictor) *predictor = PRED_COMPARE_AND_SWAP; return boolean_true_node; } } return NULL; } if (get_gimple_rhs_class (code) == GIMPLE_BINARY_RHS) { tree res; enum br_predictor predictor2; op0 = expr_expected_value (op0, visited, predictor); if (!op0) return NULL; op1 = expr_expected_value (op1, visited, &predictor2); if (predictor && *predictor < predictor2) *predictor = predictor2; if (!op1) return NULL; res = fold_build2 (code, type, op0, op1); if (TREE_CONSTANT (res)) return res; return NULL; } if (get_gimple_rhs_class (code) == GIMPLE_UNARY_RHS) { tree res; op0 = expr_expected_value (op0, visited, predictor); if (!op0) return NULL; res = fold_build1 (code, type, op0); if (TREE_CONSTANT (res)) return res; return NULL; } return NULL; } /* Return constant EXPR will likely have at execution time, NULL if unknown. The function is used by builtin_expect branch predictor so the evidence must come from this construct and additional possible constant folding. We may want to implement more involved value guess (such as value range propagation based prediction), but such tricks shall go to new implementation. */ static tree expr_expected_value (tree expr, bitmap visited, enum br_predictor *predictor) { enum tree_code code; tree op0, op1; if (TREE_CONSTANT (expr)) { if (predictor) *predictor = PRED_UNCONDITIONAL; return expr; } extract_ops_from_tree (expr, &code, &op0, &op1); return expr_expected_value_1 (TREE_TYPE (expr), op0, code, op1, visited, predictor); } /* Get rid of all builtin_expect calls and GIMPLE_PREDICT statements we no longer need. */ static unsigned int strip_predict_hints (void) { basic_block bb; gimple ass_stmt; tree var; FOR_EACH_BB_FN (bb, cfun) { gimple_stmt_iterator bi; for (bi = gsi_start_bb (bb); !gsi_end_p (bi);) { gimple stmt = gsi_stmt (bi); if (gimple_code (stmt) == GIMPLE_PREDICT) { gsi_remove (&bi, true); continue; } else if (is_gimple_call (stmt)) { tree fndecl = gimple_call_fndecl (stmt); if ((fndecl && DECL_BUILT_IN_CLASS (fndecl) == BUILT_IN_NORMAL && DECL_FUNCTION_CODE (fndecl) == BUILT_IN_EXPECT && gimple_call_num_args (stmt) == 2) || (gimple_call_internal_p (stmt) && gimple_call_internal_fn (stmt) == IFN_BUILTIN_EXPECT)) { var = gimple_call_lhs (stmt); if (var) { ass_stmt = gimple_build_assign (var, gimple_call_arg (stmt, 0)); gsi_replace (&bi, ass_stmt, true); } else { gsi_remove (&bi, true); continue; } } } gsi_next (&bi); } } return 0; } /* Predict using opcode of the last statement in basic block. */ static void tree_predict_by_opcode (basic_block bb) { gimple stmt = last_stmt (bb); edge then_edge; tree op0, op1; tree type; tree val; enum tree_code cmp; bitmap visited; edge_iterator ei; enum br_predictor predictor; if (!stmt || gimple_code (stmt) != GIMPLE_COND) return; FOR_EACH_EDGE (then_edge, ei, bb->succs) if (then_edge->flags & EDGE_TRUE_VALUE) break; op0 = gimple_cond_lhs (stmt); op1 = gimple_cond_rhs (stmt); cmp = gimple_cond_code (stmt); type = TREE_TYPE (op0); visited = BITMAP_ALLOC (NULL); val = expr_expected_value_1 (boolean_type_node, op0, cmp, op1, visited, &predictor); BITMAP_FREE (visited); if (val && TREE_CODE (val) == INTEGER_CST) { if (predictor == PRED_BUILTIN_EXPECT) { int percent = PARAM_VALUE (BUILTIN_EXPECT_PROBABILITY); gcc_assert (percent >= 0 && percent <= 100); if (integer_zerop (val)) percent = 100 - percent; predict_edge (then_edge, PRED_BUILTIN_EXPECT, HITRATE (percent)); } else predict_edge (then_edge, predictor, integer_zerop (val) ? NOT_TAKEN : TAKEN); } /* Try "pointer heuristic." A comparison ptr == 0 is predicted as false. Similarly, a comparison ptr1 == ptr2 is predicted as false. */ if (POINTER_TYPE_P (type)) { if (cmp == EQ_EXPR) predict_edge_def (then_edge, PRED_TREE_POINTER, NOT_TAKEN); else if (cmp == NE_EXPR) predict_edge_def (then_edge, PRED_TREE_POINTER, TAKEN); } else /* Try "opcode heuristic." EQ tests are usually false and NE tests are usually true. Also, most quantities are positive, so we can make the appropriate guesses about signed comparisons against zero. */ switch (cmp) { case EQ_EXPR: case UNEQ_EXPR: /* Floating point comparisons appears to behave in a very unpredictable way because of special role of = tests in FP code. */ if (FLOAT_TYPE_P (type)) ; /* Comparisons with 0 are often used for booleans and there is nothing useful to predict about them. */ else if (integer_zerop (op0) || integer_zerop (op1)) ; else predict_edge_def (then_edge, PRED_TREE_OPCODE_NONEQUAL, NOT_TAKEN); break; case NE_EXPR: case LTGT_EXPR: /* Floating point comparisons appears to behave in a very unpredictable way because of special role of = tests in FP code. */ if (FLOAT_TYPE_P (type)) ; /* Comparisons with 0 are often used for booleans and there is nothing useful to predict about them. */ else if (integer_zerop (op0) || integer_zerop (op1)) ; else predict_edge_def (then_edge, PRED_TREE_OPCODE_NONEQUAL, TAKEN); break; case ORDERED_EXPR: predict_edge_def (then_edge, PRED_TREE_FPOPCODE, TAKEN); break; case UNORDERED_EXPR: predict_edge_def (then_edge, PRED_TREE_FPOPCODE, NOT_TAKEN); break; case LE_EXPR: case LT_EXPR: if (integer_zerop (op1) || integer_onep (op1) || integer_all_onesp (op1) || real_zerop (op1) || real_onep (op1) || real_minus_onep (op1)) predict_edge_def (then_edge, PRED_TREE_OPCODE_POSITIVE, NOT_TAKEN); break; case GE_EXPR: case GT_EXPR: if (integer_zerop (op1) || integer_onep (op1) || integer_all_onesp (op1) || real_zerop (op1) || real_onep (op1) || real_minus_onep (op1)) predict_edge_def (then_edge, PRED_TREE_OPCODE_POSITIVE, TAKEN); break; default: break; } } /* Try to guess whether the value of return means error code. */ static enum br_predictor return_prediction (tree val, enum prediction *prediction) { /* VOID. */ if (!val) return PRED_NO_PREDICTION; /* Different heuristics for pointers and scalars. */ if (POINTER_TYPE_P (TREE_TYPE (val))) { /* NULL is usually not returned. */ if (integer_zerop (val)) { *prediction = NOT_TAKEN; return PRED_NULL_RETURN; } } else if (INTEGRAL_TYPE_P (TREE_TYPE (val))) { /* Negative return values are often used to indicate errors. */ if (TREE_CODE (val) == INTEGER_CST && tree_int_cst_sgn (val) < 0) { *prediction = NOT_TAKEN; return PRED_NEGATIVE_RETURN; } /* Constant return values seems to be commonly taken. Zero/one often represent booleans so exclude them from the heuristics. */ if (TREE_CONSTANT (val) && (!integer_zerop (val) && !integer_onep (val))) { *prediction = TAKEN; return PRED_CONST_RETURN; } } return PRED_NO_PREDICTION; } /* Find the basic block with return expression and look up for possible return value trying to apply RETURN_PREDICTION heuristics. */ static void apply_return_prediction (void) { gimple return_stmt = NULL; tree return_val; edge e; gimple 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) { return_stmt = last_stmt (e->src); if (return_stmt && gimple_code (return_stmt) == GIMPLE_RETURN) 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 = SSA_NAME_DEF_STMT (return_val); phi_num_args = gimple_phi_num_args (phi); pred = return_prediction (PHI_ARG_DEF (phi, 0), &direction); /* Avoid the degenerate case where all return values form the function belongs to same category (ie they are all positive constants) so we can hardly say something about them. */ for (i = 1; i < phi_num_args; i++) if (pred != return_prediction (PHI_ARG_DEF (phi, i), &direction)) break; if (i != phi_num_args) for (i = 0; i < phi_num_args; i++) { pred = return_prediction (PHI_ARG_DEF (phi, i), &direction); if (pred != PRED_NO_PREDICTION) predict_paths_leading_to_edge (gimple_phi_arg_edge (phi, i), pred, direction); } } /* Look for basic block that contains unlikely to happen events (such as noreturn calls) and mark all paths leading to execution of this basic blocks as unlikely. */ static void tree_bb_level_predictions (void) { basic_block bb; bool has_return_edges = false; edge e; edge_iterator ei; FOR_EACH_EDGE (e, ei, EXIT_BLOCK_PTR_FOR_FN (cfun)->preds) if (!(e->flags & (EDGE_ABNORMAL | EDGE_FAKE | EDGE_EH))) { has_return_edges = true; break; } apply_return_prediction (); FOR_EACH_BB_FN (bb, cfun) { gimple_stmt_iterator gsi; for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi)) { gimple stmt = gsi_stmt (gsi); tree decl; if (is_gimple_call (stmt)) { if ((gimple_call_flags (stmt) & ECF_NORETURN) && has_return_edges) predict_paths_leading_to (bb, PRED_NORETURN, NOT_TAKEN); decl = gimple_call_fndecl (stmt); if (decl && lookup_attribute ("cold", DECL_ATTRIBUTES (decl))) predict_paths_leading_to (bb, PRED_COLD_FUNCTION, NOT_TAKEN); } else if (gimple_code (stmt) == GIMPLE_PREDICT) { predict_paths_leading_to (bb, gimple_predict_predictor (stmt), gimple_predict_outcome (stmt)); /* Keep GIMPLE_PREDICT around so early inlining will propagate hints to callers. */ } } } } #ifdef ENABLE_CHECKING /* Callback for pointer_map_traverse, asserts that the pointer map is empty. */ static bool assert_is_empty (const void *key ATTRIBUTE_UNUSED, void **value, void *data ATTRIBUTE_UNUSED) { gcc_assert (!*value); return false; } #endif /* Predict branch probabilities and estimate profile for basic block BB. */ static void tree_estimate_probability_bb (basic_block bb) { edge e; edge_iterator ei; gimple last; FOR_EACH_EDGE (e, ei, bb->succs) { /* Predict edges to user labels with attributes. */ if (e->dest != EXIT_BLOCK_PTR_FOR_FN (cfun)) { gimple_stmt_iterator gi; for (gi = gsi_start_bb (e->dest); !gsi_end_p (gi); gsi_next (&gi)) { gimple stmt = gsi_stmt (gi); tree decl; if (gimple_code (stmt) != GIMPLE_LABEL) break; decl = gimple_label_label (stmt); if (DECL_ARTIFICIAL (decl)) continue; /* Finally, we have a user-defined label. */ if (lookup_attribute ("cold", DECL_ATTRIBUTES (decl))) predict_edge_def (e, PRED_COLD_LABEL, NOT_TAKEN); else if (lookup_attribute ("hot", DECL_ATTRIBUTES (decl))) predict_edge_def (e, PRED_HOT_LABEL, TAKEN); } } /* Predict early returns to be probable, as we've already taken care for error returns and other cases are often used for fast paths through function. Since we've already removed the return statements, we are looking for CFG like: if (conditional) { .. goto return_block } some other blocks return_block: return_stmt. */ if (e->dest != bb->next_bb && e->dest != EXIT_BLOCK_PTR_FOR_FN (cfun) && single_succ_p (e->dest) && single_succ_edge (e->dest)->dest == EXIT_BLOCK_PTR_FOR_FN (cfun) && (last = last_stmt (e->dest)) != NULL && gimple_code (last) == GIMPLE_RETURN) { edge e1; edge_iterator ei1; if (single_succ_p (bb)) { FOR_EACH_EDGE (e1, ei1, bb->preds) if (!predicted_by_p (e1->src, PRED_NULL_RETURN) && !predicted_by_p (e1->src, PRED_CONST_RETURN) && !predicted_by_p (e1->src, PRED_NEGATIVE_RETURN)) predict_edge_def (e1, PRED_TREE_EARLY_RETURN, NOT_TAKEN); } else if (!predicted_by_p (e->src, PRED_NULL_RETURN) && !predicted_by_p (e->src, PRED_CONST_RETURN) && !predicted_by_p (e->src, PRED_NEGATIVE_RETURN)) predict_edge_def (e, PRED_TREE_EARLY_RETURN, NOT_TAKEN); } /* Look for block we are guarding (ie we dominate it, but it doesn't postdominate us). */ if (e->dest != EXIT_BLOCK_PTR_FOR_FN (cfun) && e->dest != bb && dominated_by_p (CDI_DOMINATORS, e->dest, e->src) && !dominated_by_p (CDI_POST_DOMINATORS, e->src, e->dest)) { gimple_stmt_iterator bi; /* The call heuristic claims that a guarded function call is improbable. This is because such calls are often used to signal exceptional situations such as printing error messages. */ for (bi = gsi_start_bb (e->dest); !gsi_end_p (bi); gsi_next (&bi)) { gimple stmt = gsi_stmt (bi); if (is_gimple_call (stmt) /* Constant and pure calls are hardly used to signalize something exceptional. */ && gimple_has_side_effects (stmt)) { predict_edge_def (e, PRED_CALL, NOT_TAKEN); break; } } } } tree_predict_by_opcode (bb); } /* Predict branch probabilities and estimate profile of the tree CFG. This function can be called from the loop optimizers to recompute the profile information. */ void tree_estimate_probability (void) { basic_block bb; add_noreturn_fake_exit_edges (); connect_infinite_loops_to_exit (); /* We use loop_niter_by_eval, which requires that the loops have preheaders. */ create_preheaders (CP_SIMPLE_PREHEADERS); calculate_dominance_info (CDI_POST_DOMINATORS); bb_predictions = pointer_map_create (); tree_bb_level_predictions (); record_loop_exits (); if (number_of_loops (cfun) > 1) predict_loops (); FOR_EACH_BB_FN (bb, cfun) tree_estimate_probability_bb (bb); FOR_EACH_BB_FN (bb, cfun) combine_predictions_for_bb (bb); #ifdef ENABLE_CHECKING pointer_map_traverse (bb_predictions, assert_is_empty, NULL); #endif pointer_map_destroy (bb_predictions); bb_predictions = NULL; estimate_bb_frequencies (false); free_dominance_info (CDI_POST_DOMINATORS); remove_fake_exit_edges (); } /* Predict branch probabilities and estimate profile of the tree CFG. This is the driver function for PASS_PROFILE. */ static unsigned int tree_estimate_probability_driver (void) { unsigned nb_loops; loop_optimizer_init (LOOPS_NORMAL); if (dump_file && (dump_flags & TDF_DETAILS)) flow_loops_dump (dump_file, NULL, 0); mark_irreducible_loops (); nb_loops = number_of_loops (cfun); if (nb_loops > 1) scev_initialize (); tree_estimate_probability (); if (nb_loops > 1) scev_finalize (); loop_optimizer_finalize (); if (dump_file && (dump_flags & TDF_DETAILS)) gimple_dump_cfg (dump_file, dump_flags); if (profile_status_for_fn (cfun) == PROFILE_ABSENT) profile_status_for_fn (cfun) = PROFILE_GUESSED; return 0; } /* Predict edges to successors of CUR whose sources are not postdominated by BB by PRED and recurse to all postdominators. */ static void predict_paths_for_bb (basic_block cur, basic_block bb, enum br_predictor pred, enum prediction taken, bitmap visited) { edge e; edge_iterator ei; basic_block son; /* We are looking for all edges forming edge cut induced by set of all blocks postdominated by BB. */ FOR_EACH_EDGE (e, ei, cur->preds) if (e->src->index >= NUM_FIXED_BLOCKS && !dominated_by_p (CDI_POST_DOMINATORS, e->src, bb)) { edge e2; edge_iterator ei2; bool found = false; /* Ignore fake edges and eh, we predict them as not taken anyway. */ if (e->flags & (EDGE_EH | EDGE_FAKE)) continue; gcc_assert (bb == cur || dominated_by_p (CDI_POST_DOMINATORS, cur, bb)); /* See if there is an edge from e->src that is not abnormal and does not lead to BB. */ FOR_EACH_EDGE (e2, ei2, e->src->succs) if (e2 != e && !(e2->flags & (EDGE_EH | EDGE_FAKE)) && !dominated_by_p (CDI_POST_DOMINATORS, e2->dest, bb)) { found = true; break; } /* If there is non-abnormal path leaving e->src, predict edge using predictor. Otherwise we need to look for paths leading to e->src. The second may lead to infinite loop in the case we are predicitng regions that are only reachable by abnormal edges. We simply prevent visiting given BB twice. */ if (found) predict_edge_def (e, pred, taken); else if (bitmap_set_bit (visited, e->src->index)) predict_paths_for_bb (e->src, e->src, pred, taken, visited); } for (son = first_dom_son (CDI_POST_DOMINATORS, cur); son; son = next_dom_son (CDI_POST_DOMINATORS, son)) predict_paths_for_bb (son, bb, pred, taken, visited); } /* Sets branch probabilities according to PREDiction and FLAGS. */ static void predict_paths_leading_to (basic_block bb, enum br_predictor pred, enum prediction taken) { bitmap visited = BITMAP_ALLOC (NULL); predict_paths_for_bb (bb, bb, pred, taken, visited); BITMAP_FREE (visited); } /* Like predict_paths_leading_to but take edge instead of basic block. */ static void predict_paths_leading_to_edge (edge e, enum br_predictor pred, enum prediction taken) { bool has_nonloop_edge = false; edge_iterator ei; edge e2; basic_block bb = e->src; FOR_EACH_EDGE (e2, ei, bb->succs) if (e2->dest != e->src && e2->dest != e->dest && !(e->flags & (EDGE_EH | EDGE_FAKE)) && !dominated_by_p (CDI_POST_DOMINATORS, e->src, e2->dest)) { has_nonloop_edge = true; break; } if (!has_nonloop_edge) { bitmap visited = BITMAP_ALLOC (NULL); predict_paths_for_bb (bb, bb, pred, taken, visited); BITMAP_FREE (visited); } else predict_edge_def (e, pred, taken); } /* This is used to carry information about basic blocks. It is attached to the AUX field of the standard CFG block. */ typedef struct block_info_def { /* 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; } *block_info; /* Similar information for edges. */ typedef struct edge_info_def { /* 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; } *edge_info; #define BLOCK_INFO(B) ((block_info) (B)->aux) #define EDGE_INFO(E) ((edge_info) (E)->aux) /* Helper function for estimate_bb_frequencies. Propagate the frequencies in blocks marked in TOVISIT, starting in HEAD. */ static void propagate_freq (basic_block head, bitmap tovisit) { basic_block bb; basic_block last; unsigned i; edge e; basic_block nextbb; bitmap_iterator bi; /* For each basic block we need to visit count number of his predecessors we need to visit first. */ EXECUTE_IF_SET_IN_BITMAP (tovisit, 0, i, bi) { edge_iterator ei; int count = 0; bb = BASIC_BLOCK_FOR_FN (cfun, i); FOR_EACH_EDGE (e, ei, bb->preds) { bool visit = bitmap_bit_p (tovisit, e->src->index); if (visit && !(e->flags & EDGE_DFS_BACK)) count++; else if (visit && dump_file && !EDGE_INFO (e)->back_edge) fprintf (dump_file, "Irreducible region hit, ignoring edge to %i->%i\n", e->src->index, bb->index); } BLOCK_INFO (bb)->npredecessors = count; /* When function never returns, we will never process exit block. */ if (!count && bb == EXIT_BLOCK_PTR_FOR_FN (cfun)) bb->count = bb->frequency = 0; } memcpy (&BLOCK_INFO (head)->frequency, &real_one, sizeof (real_one)); last = head; for (bb = head; bb; bb = nextbb) { edge_iterator ei; sreal cyclic_probability, frequency; memcpy (&cyclic_probability, &real_zero, sizeof (real_zero)); memcpy (&frequency, &real_zero, sizeof (real_zero)); nextbb = BLOCK_INFO (bb)->next; BLOCK_INFO (bb)->next = NULL; /* Compute frequency of basic block. */ if (bb != head) { #ifdef ENABLE_CHECKING FOR_EACH_EDGE (e, ei, bb->preds) gcc_assert (!bitmap_bit_p (tovisit, e->src->index) || (e->flags & EDGE_DFS_BACK)); #endif FOR_EACH_EDGE (e, ei, bb->preds) if (EDGE_INFO (e)->back_edge) { sreal_add (&cyclic_probability, &cyclic_probability, &EDGE_INFO (e)->back_edge_prob); } else if (!(e->flags & EDGE_DFS_BACK)) { sreal tmp; /* frequency += (e->probability * BLOCK_INFO (e->src)->frequency / REG_BR_PROB_BASE); */ sreal_init (&tmp, e->probability, 0); sreal_mul (&tmp, &tmp, &BLOCK_INFO (e->src)->frequency); sreal_mul (&tmp, &tmp, &real_inv_br_prob_base); sreal_add (&frequency, &frequency, &tmp); } if (sreal_compare (&cyclic_probability, &real_zero) == 0) { memcpy (&BLOCK_INFO (bb)->frequency, &frequency, sizeof (frequency)); } else { if (sreal_compare (&cyclic_probability, &real_almost_one) > 0) { memcpy (&cyclic_probability, &real_almost_one, sizeof (real_almost_one)); } /* BLOCK_INFO (bb)->frequency = frequency / (1 - cyclic_probability) */ sreal_sub (&cyclic_probability, &real_one, &cyclic_probability); sreal_div (&BLOCK_INFO (bb)->frequency, &frequency, &cyclic_probability); } } bitmap_clear_bit (tovisit, bb->index); e = find_edge (bb, head); if (e) { sreal tmp; /* EDGE_INFO (e)->back_edge_prob = ((e->probability * BLOCK_INFO (bb)->frequency) / REG_BR_PROB_BASE); */ sreal_init (&tmp, e->probability, 0); sreal_mul (&tmp, &tmp, &BLOCK_INFO (bb)->frequency); sreal_mul (&EDGE_INFO (e)->back_edge_prob, &tmp, &real_inv_br_prob_base); } /* Propagate to successor blocks. */ FOR_EACH_EDGE (e, ei, bb->succs) if (!(e->flags & EDGE_DFS_BACK) && BLOCK_INFO (e->dest)->npredecessors) { BLOCK_INFO (e->dest)->npredecessors--; if (!BLOCK_INFO (e->dest)->npredecessors) { if (!nextbb) nextbb = e->dest; else BLOCK_INFO (last)->next = e->dest; last = e->dest; } } } } /* Estimate frequencies in loops at same nest level. */ static void estimate_loops_at_level (struct loop *first_loop) { struct loop *loop; for (loop = first_loop; loop; loop = loop->next) { edge e; basic_block *bbs; unsigned i; bitmap tovisit = BITMAP_ALLOC (NULL); estimate_loops_at_level (loop->inner); /* Find current loop back edge and mark it. */ e = loop_latch_edge (loop); EDGE_INFO (e)->back_edge = 1; bbs = get_loop_body (loop); for (i = 0; i < loop->num_nodes; i++) bitmap_set_bit (tovisit, bbs[i]->index); free (bbs); propagate_freq (loop->header, tovisit); BITMAP_FREE (tovisit); } } /* Propagates frequencies through structure of loops. */ static void estimate_loops (void) { bitmap tovisit = BITMAP_ALLOC (NULL); basic_block bb; /* Start by estimating the frequencies in the loops. */ if (number_of_loops (cfun) > 1) estimate_loops_at_level (current_loops->tree_root->inner); /* Now propagate the frequencies through all the blocks. */ FOR_ALL_BB_FN (bb, cfun) { bitmap_set_bit (tovisit, bb->index); } propagate_freq (ENTRY_BLOCK_PTR_FOR_FN (cfun), tovisit); BITMAP_FREE (tovisit); } /* Drop the profile for NODE to guessed, and update its frequency based on whether it is expected to be hot given the CALL_COUNT. */ static void drop_profile (struct cgraph_node *node, gcov_type call_count) { struct function *fn = DECL_STRUCT_FUNCTION (node->decl); /* In the case where this was called by another function with a dropped profile, call_count will be 0. Since there are no non-zero call counts to this function, we don't know for sure whether it is hot, and therefore it will be marked normal below. */ bool hot = maybe_hot_count_p (NULL, call_count); if (dump_file) fprintf (dump_file, "Dropping 0 profile for %s/%i. %s based on calls.\n", node->name (), node->order, hot ? "Function is hot" : "Function is normal"); /* We only expect to miss profiles for functions that are reached via non-zero call edges in cases where the function may have been linked from another module or library (COMDATs and extern templates). See the comments below for handle_missing_profiles. Also, only warn in cases where the missing counts exceed the number of training runs. In certain cases with an execv followed by a no-return call the profile for the no-return call is not dumped and there can be a mismatch. */ if (!DECL_COMDAT (node->decl) && !DECL_EXTERNAL (node->decl) && call_count > profile_info->runs) { if (flag_profile_correction) { if (dump_file) fprintf (dump_file, "Missing counts for called function %s/%i\n", node->name (), node->order); } else warning (0, "Missing counts for called function %s/%i", node->name (), node->order); } profile_status_for_fn (fn) = (flag_guess_branch_prob ? PROFILE_GUESSED : PROFILE_ABSENT); node->frequency = hot ? NODE_FREQUENCY_HOT : NODE_FREQUENCY_NORMAL; } /* In the case of COMDAT routines, multiple object files will contain the same function and the linker will select one for the binary. In that case all the other copies from the profile instrument binary will be missing profile counts. Look for cases where this happened, due to non-zero call counts going to 0-count functions, and drop the profile to guessed so that we can use the estimated probabilities and avoid optimizing only for size. The other case where the profile may be missing is when the routine is not going to be emitted to the object file, e.g. for "extern template" class methods. Those will be marked DECL_EXTERNAL. Emit a warning in all other cases of non-zero calls to 0-count functions. */ void handle_missing_profiles (void) { struct cgraph_node *node; int unlikely_count_fraction = PARAM_VALUE (UNLIKELY_BB_COUNT_FRACTION); vec worklist; worklist.create (64); /* See if 0 count function has non-0 count callers. In this case we lost some profile. Drop its function profile to PROFILE_GUESSED. */ FOR_EACH_DEFINED_FUNCTION (node) { struct cgraph_edge *e; gcov_type call_count = 0; gcov_type max_tp_first_run = 0; struct function *fn = DECL_STRUCT_FUNCTION (node->decl); if (node->count) continue; for (e = node->callers; e; e = e->next_caller) { call_count += e->count; if (e->caller->tp_first_run > max_tp_first_run) max_tp_first_run = e->caller->tp_first_run; } /* If time profile is missing, let assign the maximum that comes from caller functions. */ if (!node->tp_first_run && max_tp_first_run) node->tp_first_run = max_tp_first_run + 1; if (call_count && fn && fn->cfg && (call_count * unlikely_count_fraction >= profile_info->runs)) { drop_profile (node, call_count); worklist.safe_push (node); } } /* Propagate the profile dropping to other 0-count COMDATs that are potentially called by COMDATs we already dropped the profile on. */ while (worklist.length () > 0) { struct cgraph_edge *e; node = worklist.pop (); for (e = node->callees; e; e = e->next_caller) { struct cgraph_node *callee = e->callee; struct function *fn = DECL_STRUCT_FUNCTION (callee->decl); if (callee->count > 0) continue; if (DECL_COMDAT (callee->decl) && fn && fn->cfg && profile_status_for_fn (fn) == PROFILE_READ) { drop_profile (node, 0); worklist.safe_push (callee); } } } worklist.release (); } /* Convert counts measured by profile driven feedback to frequencies. Return nonzero iff there was any nonzero execution count. */ int counts_to_freqs (void) { gcov_type count_max, true_count_max = 0; basic_block bb; /* Don't overwrite the estimated frequencies when the profile for the function is missing. We may drop this function PROFILE_GUESSED later in drop_profile (). */ if (!flag_auto_profile && !ENTRY_BLOCK_PTR_FOR_FN (cfun)->count) return 0; FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) true_count_max = MAX (bb->count, true_count_max); count_max = MAX (true_count_max, 1); FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) bb->frequency = (bb->count * BB_FREQ_MAX + count_max / 2) / count_max; return true_count_max; } /* Return true if function is likely to be expensive, so there is no point to optimize performance of prologue, epilogue or do inlining at the expense of code size growth. THRESHOLD is the limit of number of instructions function can execute at average to be still considered not expensive. */ bool expensive_function_p (int threshold) { unsigned int sum = 0; basic_block bb; unsigned int limit; /* We can not compute accurately for large thresholds due to scaled frequencies. */ gcc_assert (threshold <= BB_FREQ_MAX); /* Frequencies are out of range. This either means that function contains internal loop executing more than BB_FREQ_MAX times or profile feedback is available and function has not been executed at all. */ if (ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency == 0) return true; /* Maximally BB_FREQ_MAX^2 so overflow won't happen. */ limit = ENTRY_BLOCK_PTR_FOR_FN (cfun)->frequency * threshold; FOR_EACH_BB_FN (bb, cfun) { rtx insn; FOR_BB_INSNS (bb, insn) if (active_insn_p (insn)) { sum += bb->frequency; if (sum > limit) return true; } } return false; } /* Estimate and propagate basic block frequencies using the given branch probabilities. If FORCE is true, the frequencies are used to estimate the counts even when there are already non-zero profile counts. */ void estimate_bb_frequencies (bool force) { basic_block bb; sreal freq_max; if (force || profile_status_for_fn (cfun) != PROFILE_READ || !counts_to_freqs ()) { static int real_values_initialized = 0; if (!real_values_initialized) { real_values_initialized = 1; sreal_init (&real_zero, 0, 0); sreal_init (&real_one, 1, 0); sreal_init (&real_br_prob_base, REG_BR_PROB_BASE, 0); sreal_init (&real_bb_freq_max, BB_FREQ_MAX, 0); sreal_init (&real_one_half, 1, -1); sreal_div (&real_inv_br_prob_base, &real_one, &real_br_prob_base); sreal_sub (&real_almost_one, &real_one, &real_inv_br_prob_base); } mark_dfs_back_edges (); single_succ_edge (ENTRY_BLOCK_PTR_FOR_FN (cfun))->probability = REG_BR_PROB_BASE; /* Set up block info for each basic block. */ alloc_aux_for_blocks (sizeof (struct block_info_def)); alloc_aux_for_edges (sizeof (struct edge_info_def)); 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) { sreal_init (&EDGE_INFO (e)->back_edge_prob, e->probability, 0); sreal_mul (&EDGE_INFO (e)->back_edge_prob, &EDGE_INFO (e)->back_edge_prob, &real_inv_br_prob_base); } } /* First compute frequencies locally for each loop from innermost to outermost to examine frequencies for back edges. */ estimate_loops (); memcpy (&freq_max, &real_zero, sizeof (real_zero)); FOR_EACH_BB_FN (bb, cfun) if (sreal_compare (&freq_max, &BLOCK_INFO (bb)->frequency) < 0) memcpy (&freq_max, &BLOCK_INFO (bb)->frequency, sizeof (freq_max)); sreal_div (&freq_max, &real_bb_freq_max, &freq_max); FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) { sreal tmp; sreal_mul (&tmp, &BLOCK_INFO (bb)->frequency, &freq_max); sreal_add (&tmp, &tmp, &real_one_half); bb->frequency = sreal_to_int (&tmp); } 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_get_node (current_function_decl); if (DECL_STATIC_CONSTRUCTOR (current_function_decl) || MAIN_NAME_P (DECL_NAME (current_function_decl))) node->only_called_at_startup = true; if (DECL_STATIC_DESTRUCTOR (current_function_decl)) node->only_called_at_exit = true; if (profile_status_for_fn (cfun) != PROFILE_READ || (flag_auto_profile && profile_status_for_fn (cfun) == PROFILE_GUESSED)) { int flags = flags_from_decl_or_type (current_function_decl); if (profile_info && flag_auto_profile_accurate) node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED; else if (lookup_attribute ("cold", DECL_ATTRIBUTES (current_function_decl)) != NULL) node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED; else if (lookup_attribute ("hot", DECL_ATTRIBUTES (current_function_decl)) != NULL) node->frequency = NODE_FREQUENCY_HOT; else if (flags & ECF_NORETURN) node->frequency = NODE_FREQUENCY_EXECUTED_ONCE; else if (MAIN_NAME_P (DECL_NAME (current_function_decl))) node->frequency = NODE_FREQUENCY_EXECUTED_ONCE; else if (DECL_STATIC_CONSTRUCTOR (current_function_decl) || DECL_STATIC_DESTRUCTOR (current_function_decl)) node->frequency = NODE_FREQUENCY_EXECUTED_ONCE; return; } /* Only first time try to drop function into unlikely executed. After inlining the roundoff errors may confuse us. Ipa-profile pass will drop functions only called from unlikely functions to unlikely and that is most of what we care about. */ if (!cfun->after_inlining) node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED; FOR_EACH_BB_FN (bb, cfun) { if (maybe_hot_bb_p (cfun, bb)) { node->frequency = NODE_FREQUENCY_HOT; return; } if (!probably_never_executed_bb_p (cfun, bb)) node->frequency = NODE_FREQUENCY_NORMAL; } } static bool gate_estimate_probability (void) { return flag_guess_branch_prob; } /* 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; } namespace { const pass_data pass_data_profile = { GIMPLE_PASS, /* type */ "profile_estimate", /* name */ OPTGROUP_NONE, /* optinfo_flags */ true, /* has_gate */ true, /* has_execute */ TV_BRANCH_PROB, /* tv_id */ PROP_cfg, /* properties_required */ 0, /* properties_provided */ 0, /* properties_destroyed */ 0, /* todo_flags_start */ TODO_verify_ssa, /* 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: */ bool gate () { return gate_estimate_probability (); } unsigned int execute () { return tree_estimate_probability_driver (); } }; // class pass_profile } // anon namespace gimple_opt_pass * make_pass_profile (gcc::context *ctxt) { return new pass_profile (ctxt); } namespace { const pass_data pass_data_strip_predict_hints = { GIMPLE_PASS, /* type */ "*strip_predict_hints", /* name */ OPTGROUP_NONE, /* optinfo_flags */ false, /* has_gate */ true, /* has_execute */ TV_BRANCH_PROB, /* tv_id */ PROP_cfg, /* properties_required */ 0, /* properties_provided */ 0, /* properties_destroyed */ 0, /* todo_flags_start */ TODO_verify_ssa, /* 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); } unsigned int execute () { return strip_predict_hints (); } }; // class pass_strip_predict_hints } // anon namespace gimple_opt_pass * make_pass_strip_predict_hints (gcc::context *ctxt) { return new pass_strip_predict_hints (ctxt); } /* Rebuild function frequencies. Passes are in general expected to maintain profile by hand, however in some cases this is not possible: for example when inlining several functions with loops freuqencies might run out of scale and thus needs to be recomputed. */ void rebuild_frequencies (void) { timevar_push (TV_REBUILD_FREQUENCIES); /* When the max bb count in the function is small, there is a higher chance that there were truncation errors in the integer scaling of counts by inlining and other optimizations. This could lead to incorrect classification of code as being cold when it isn't. In that case, force the estimation of bb counts/frequencies from the branch probabilities, rather than computing frequencies from counts, which may also lead to frequencies incorrectly reduced to 0. There is less precision in the probabilities, so we only do this for small max counts. */ gcov_type count_max = 0; basic_block bb; FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR_FOR_FN (cfun), NULL, next_bb) count_max = MAX (bb->count, count_max); if (profile_status_for_fn (cfun) == PROFILE_GUESSED || (!flag_auto_profile && profile_status_for_fn (cfun) == PROFILE_READ && count_max < REG_BR_PROB_BASE/10)) { loop_optimizer_init (0); add_noreturn_fake_exit_edges (); mark_irreducible_loops (); connect_infinite_loops_to_exit (); estimate_bb_frequencies (true); remove_fake_exit_edges (); loop_optimizer_finalize (); } else if (profile_status_for_fn (cfun) == PROFILE_READ) counts_to_freqs (); else gcc_unreachable (); timevar_pop (TV_REBUILD_FREQUENCIES); }