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/* Branch prediction routines for the GNU compiler. Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2007, 2008, 2009 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 "tm.h" #include "tree.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 "output.h" #include "function.h" #include "except.h" #include "toplev.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 "tree-flow.h" #include "ggc.h" #include "tree-dump.h" #include "tree-pass.h" #include "timevar.h" #include "tree-scalar-evolution.h" #include "cfgloop.h" #include "pointer-set.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; /* Random guesstimation given names. PROV_VERY_UNLIKELY should be small enough so basic block predicted by it gets bellow HOT_BB_FREQUENCY_FRANCTION. */ #define PROB_VERY_UNLIKELY (REG_BR_PROB_BASE / 2000 - 1) #define PROB_EVEN (REG_BR_PROB_BASE / 2) #define PROB_VERY_LIKELY (REG_BR_PROB_BASE - PROB_VERY_UNLIKELY) #define PROB_ALWAYS (REG_BR_PROB_BASE) 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 choose_function_section (void); 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 (int freq) { if (!profile_info || !flag_branch_probabilities) { if (cfun->function_frequency == FUNCTION_FREQUENCY_UNLIKELY_EXECUTED) return false; if (cfun->function_frequency == FUNCTION_FREQUENCY_HOT) return true; } if (profile_status == PROFILE_ABSENT) return true; if (freq < BB_FREQ_MAX / PARAM_VALUE (HOT_BB_FREQUENCY_FRACTION)) return false; return true; } /* Return TRUE if frequency FREQ is considered to be hot. */ static inline bool maybe_hot_count_p (gcov_type count) { if (profile_status != PROFILE_READ) return true; /* Code executed at most once is not hot. */ if (profile_info->runs >= count) return false; return (count > profile_info->sum_max / PARAM_VALUE (HOT_BB_COUNT_FRACTION)); } /* Return true in case BB can be CPU intensive and should be optimized for maximal performance. */ bool maybe_hot_bb_p (const_basic_block bb) { if (profile_status == PROFILE_READ) return maybe_hot_count_p (bb->count); return maybe_hot_frequency_p (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 && (edge->count <= profile_info->sum_max / PARAM_VALUE (HOT_BB_COUNT_FRACTION))) return false; if (lookup_attribute ("cold", DECL_ATTRIBUTES (edge->callee->decl)) || lookup_attribute ("cold", DECL_ATTRIBUTES (edge->caller->decl))) return false; if (lookup_attribute ("hot", DECL_ATTRIBUTES (edge->caller->decl))) return true; if (flag_guess_branch_prob && 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 == PROFILE_READ) return maybe_hot_count_p (e->count); return maybe_hot_frequency_p (EDGE_FREQUENCY (e)); } /* Return true in case BB is probably never executed. */ bool probably_never_executed_bb_p (const_basic_block bb) { if (profile_info && flag_branch_probabilities) return ((bb->count + profile_info->runs / 2) / profile_info->runs) == 0; if ((!profile_info || !flag_branch_probabilities) && cfun->function_frequency == FUNCTION_FREQUENCY_UNLIKELY_EXECUTED) return true; return false; } /* Return true when current function should always be optimized for size. */ bool optimize_function_for_size_p (struct function *fun) { return (optimize_size || (fun && (fun->function_frequency == FUNCTION_FREQUENCY_UNLIKELY_EXECUTED))); } /* 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 (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 == 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 (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; /* 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 == PROFILE_READ || (profile_status == 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 (INTVAL (XEXP (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 != PROFILE_GUESSED); if ((e->src != ENTRY_BLOCK_PTR && 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) XEXP (note, 0) = GEN_INT (REG_BR_PROB_BASE - INTVAL (XEXP (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_reg_note (insn, REG_BR_PROB, GEN_INT (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 = INTVAL (XEXP (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; } } /* Predict edge probabilities by exploiting loop structure. */ static void predict_loops (void) { loop_iterator li; struct loop *loop; /* Try to predict out blocks in a loop that are not part of a natural loop. */ FOR_EACH_LOOP (li, loop, 0) { basic_block bb, *bbs; unsigned j, n_exits; VEC (edge, heap) *exits; struct tree_niter_desc niter_desc; edge ex; exits = get_loop_exit_edges (loop); n_exits = VEC_length (edge, exits); for (j = 0; VEC_iterate (edge, exits, j, ex); j++) { tree niter = NULL; HOST_WIDE_INT nitercst; int max = PARAM_VALUE (PARAM_MAX_PREDICTED_ITERATIONS); int probability; enum br_predictor predictor; if (number_of_iterations_exit (loop, ex, &niter_desc, 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 (host_integerp (niter, 1) && compare_tree_int (niter, max-1) == -1) nitercst = tree_low_cst (niter, 1) + 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_loop_iterations_int (loop, false); if (nitercst < 0) continue; if (nitercst > max) nitercst = max; predictor = PRED_LOOP_ITERATIONS_GUESSED; } else continue; probability = ((REG_BR_PROB_BASE + nitercst / 2) / nitercst); predict_edge (ex, predictor, probability); } VEC_free (edge, heap, exits); 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); } } /* 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); /* Helper function for expr_expected_value. */ static tree expr_expected_value_1 (tree type, tree op0, enum tree_code code, tree op1, bitmap visited) { gimple def; 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_bit_p (visited, SSA_NAME_VERSION (op0))) return NULL; bitmap_set_bit (visited, SSA_NAME_VERSION (op0)); 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); /* 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); 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); } if (is_gimple_call (def)) { tree decl = gimple_call_fndecl (def); if (!decl) return NULL; if (DECL_BUILT_IN_CLASS (decl) == BUILT_IN_NORMAL && DECL_FUNCTION_CODE (decl) == 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; return gimple_call_arg (def, 1); } } return NULL; } if (get_gimple_rhs_class (code) == GIMPLE_BINARY_RHS) { tree res; op0 = expr_expected_value (op0, visited); if (!op0) return NULL; op1 = expr_expected_value (op1, visited); 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); 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 tree_code code; tree op0, op1; if (TREE_CONSTANT (expr)) return expr; extract_ops_from_tree (expr, &code, &op0, &op1); return expr_expected_value_1 (TREE_TYPE (expr), op0, code, op1, visited); } /* 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 (bb) { 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 (gimple_code (stmt) == GIMPLE_CALL) { 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) { var = gimple_call_lhs (stmt); ass_stmt = gimple_build_assign (var, gimple_call_arg (stmt, 0)); gsi_replace (&bi, ass_stmt, true); } } 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; 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); BITMAP_FREE (visited); if (val) { if (integer_zerop (val)) predict_edge_def (then_edge, PRED_BUILTIN_EXPECT, NOT_TAKEN); else predict_edge_def (then_edge, PRED_BUILTIN_EXPECT, TAKEN); return; } /* 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->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 (gimple_phi_arg_edge (phi, i)->src, 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->preds) if (!(e->flags & (EDGE_ABNORMAL | EDGE_FAKE | EDGE_EH))) { has_return_edges = true; break; } apply_return_prediction (); FOR_EACH_BB (bb) { 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 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 && single_succ_p (e->dest) && single_succ_edge (e->dest)->dest == EXIT_BLOCK_PTR && (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 && 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 () > 1) predict_loops (); FOR_EACH_BB (bb) tree_estimate_probability_bb (bb); FOR_EACH_BB (bb) 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 (); 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 (0); if (dump_file && (dump_flags & TDF_DETAILS)) flow_loops_dump (dump_file, NULL, 0); mark_irreducible_loops (); nb_loops = number_of_loops (); 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 == PROFILE_ABSENT) profile_status = 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) { 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)) { gcc_assert (bb == cur || dominated_by_p (CDI_POST_DOMINATORS, cur, bb)); predict_edge_def (e, pred, taken); } 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); } /* Sets branch probabilities according to PREDiction and FLAGS. */ static void predict_paths_leading_to (basic_block bb, enum br_predictor pred, enum prediction taken) { predict_paths_for_bb (bb, bb, 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; /* The outermost "loop" includes the exit block, which we can not look up via BASIC_BLOCK. Detect this and use EXIT_BLOCK_PTR directly. Do the same for the entry block. */ bb = BASIC_BLOCK (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; } 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 probabilities of loopback edges 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 () > 1) estimate_loops_at_level (current_loops->tree_root->inner); /* Now propagate the frequencies through all the blocks. */ FOR_ALL_BB (bb) { bitmap_set_bit (tovisit, bb->index); } propagate_freq (ENTRY_BLOCK_PTR, tovisit); BITMAP_FREE (tovisit); } /* 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; FOR_BB_BETWEEN (bb, ENTRY_BLOCK_PTR, 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, 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->frequency == 0) return true; /* Maximally BB_FREQ_MAX^2 so overflow won't happen. */ limit = ENTRY_BLOCK_PTR->frequency * threshold; FOR_EACH_BB (bb) { rtx insn; for (insn = BB_HEAD (bb); insn != NEXT_INSN (BB_END (bb)); insn = NEXT_INSN (insn)) if (active_insn_p (insn)) { sum += bb->frequency; if (sum > limit) return true; } } return false; } /* Estimate basic blocks frequency by given branch probabilities. */ void estimate_bb_frequencies (void) { basic_block bb; sreal freq_max; if (profile_status != 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)->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, 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 probabilities locally for each loop from innermost to outermost to examine probabilities for back edges. */ estimate_loops (); memcpy (&freq_max, &real_zero, sizeof (real_zero)); FOR_EACH_BB (bb) 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, 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 (); if (flag_reorder_functions) choose_function_section (); } /* Decide whether function is hot, cold or unlikely executed. */ void compute_function_frequency (void) { basic_block bb; if (!profile_info || !flag_branch_probabilities) { if (lookup_attribute ("cold", DECL_ATTRIBUTES (current_function_decl)) != NULL) cfun->function_frequency = FUNCTION_FREQUENCY_UNLIKELY_EXECUTED; else if (lookup_attribute ("hot", DECL_ATTRIBUTES (current_function_decl)) != NULL) cfun->function_frequency = FUNCTION_FREQUENCY_HOT; return; } cfun->function_frequency = FUNCTION_FREQUENCY_UNLIKELY_EXECUTED; FOR_EACH_BB (bb) { if (maybe_hot_bb_p (bb)) { cfun->function_frequency = FUNCTION_FREQUENCY_HOT; return; } if (!probably_never_executed_bb_p (bb)) cfun->function_frequency = FUNCTION_FREQUENCY_NORMAL; } } /* Choose appropriate section for the function. */ static void choose_function_section (void) { if (DECL_SECTION_NAME (current_function_decl) || !targetm.have_named_sections /* Theoretically we can split the gnu.linkonce text section too, but this requires more work as the frequency needs to match for all generated objects so we need to merge the frequency of all instances. For now just never set frequency for these. */ || DECL_ONE_ONLY (current_function_decl)) return; /* If we are doing the partitioning optimization, let the optimization choose the correct section into which to put things. */ if (flag_reorder_blocks_and_partition) return; if (cfun->function_frequency == FUNCTION_FREQUENCY_HOT) DECL_SECTION_NAME (current_function_decl) = build_string (strlen (HOT_TEXT_SECTION_NAME), HOT_TEXT_SECTION_NAME); if (cfun->function_frequency == FUNCTION_FREQUENCY_UNLIKELY_EXECUTED) DECL_SECTION_NAME (current_function_decl) = build_string (strlen (UNLIKELY_EXECUTED_TEXT_SECTION_NAME), UNLIKELY_EXECUTED_TEXT_SECTION_NAME); } 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 (NULL, predictor)); SET_PREDICT_EXPR_OUTCOME (t, taken); return t; } const char * predictor_name (enum br_predictor predictor) { return predictor_info[predictor].name; } struct gimple_opt_pass pass_profile = { { GIMPLE_PASS, "profile", /* name */ gate_estimate_probability, /* gate */ tree_estimate_probability_driver, /* execute */ NULL, /* sub */ NULL, /* next */ 0, /* static_pass_number */ TV_BRANCH_PROB, /* tv_id */ PROP_cfg, /* properties_required */ 0, /* properties_provided */ 0, /* properties_destroyed */ 0, /* todo_flags_start */ TODO_ggc_collect | TODO_verify_ssa /* todo_flags_finish */ } }; struct gimple_opt_pass pass_strip_predict_hints = { { GIMPLE_PASS, "*strip_predict_hints", /* name */ NULL, /* gate */ strip_predict_hints, /* execute */ NULL, /* sub */ NULL, /* next */ 0, /* static_pass_number */ TV_BRANCH_PROB, /* tv_id */ PROP_cfg, /* properties_required */ 0, /* properties_provided */ 0, /* properties_destroyed */ 0, /* todo_flags_start */ TODO_ggc_collect | TODO_verify_ssa /* todo_flags_finish */ } };
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