/* SLP - Basic Block Vectorization Copyright (C) 2007-2013 Free Software Foundation, Inc. Contributed by Dorit Naishlos and Ira Rosen 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 . */ #include "config.h" #include "system.h" #include "coretypes.h" #include "dumpfile.h" #include "tm.h" #include "ggc.h" #include "tree.h" #include "target.h" #include "basic-block.h" #include "gimple-pretty-print.h" #include "gimple.h" #include "gimple-ssa.h" #include "tree-phinodes.h" #include "ssa-iterators.h" #include "tree-ssanames.h" #include "tree-pass.h" #include "cfgloop.h" #include "expr.h" #include "recog.h" /* FIXME: for insn_data */ #include "optabs.h" #include "tree-vectorizer.h" #include "langhooks.h" /* Extract the location of the basic block in the source code. Return the basic block location if succeed and NULL if not. */ LOC find_bb_location (basic_block bb) { gimple stmt = NULL; gimple_stmt_iterator si; if (!bb) return UNKNOWN_LOC; for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si)) { stmt = gsi_stmt (si); if (gimple_location (stmt) != UNKNOWN_LOC) return gimple_location (stmt); } return UNKNOWN_LOC; } /* Recursively free the memory allocated for the SLP tree rooted at NODE. */ static void vect_free_slp_tree (slp_tree node) { int i; slp_tree child; if (!node) return; FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_free_slp_tree (child); SLP_TREE_CHILDREN (node).release (); SLP_TREE_SCALAR_STMTS (node).release (); SLP_TREE_VEC_STMTS (node).release (); SLP_TREE_LOAD_PERMUTATION (node).release (); free (node); } /* Free the memory allocated for the SLP instance. */ void vect_free_slp_instance (slp_instance instance) { vect_free_slp_tree (SLP_INSTANCE_TREE (instance)); SLP_INSTANCE_LOADS (instance).release (); SLP_INSTANCE_BODY_COST_VEC (instance).release (); free (instance); } /* Create an SLP node for SCALAR_STMTS. */ static slp_tree vect_create_new_slp_node (vec scalar_stmts) { slp_tree node; gimple stmt = scalar_stmts[0]; unsigned int nops; if (is_gimple_call (stmt)) nops = gimple_call_num_args (stmt); else if (is_gimple_assign (stmt)) { nops = gimple_num_ops (stmt) - 1; if (gimple_assign_rhs_code (stmt) == COND_EXPR) nops++; } else return NULL; node = XNEW (struct _slp_tree); SLP_TREE_SCALAR_STMTS (node) = scalar_stmts; SLP_TREE_VEC_STMTS (node).create (0); SLP_TREE_CHILDREN (node).create (nops); SLP_TREE_LOAD_PERMUTATION (node) = vNULL; return node; } /* Allocate operands info for NOPS operands, and GROUP_SIZE def-stmts for each operand. */ static vec vect_create_oprnd_info (int nops, int group_size) { int i; slp_oprnd_info oprnd_info; vec oprnds_info; oprnds_info.create (nops); for (i = 0; i < nops; i++) { oprnd_info = XNEW (struct _slp_oprnd_info); oprnd_info->def_stmts.create (group_size); oprnd_info->first_dt = vect_uninitialized_def; oprnd_info->first_op_type = NULL_TREE; oprnd_info->first_pattern = false; oprnds_info.quick_push (oprnd_info); } return oprnds_info; } /* Free operands info. */ static void vect_free_oprnd_info (vec &oprnds_info) { int i; slp_oprnd_info oprnd_info; FOR_EACH_VEC_ELT (oprnds_info, i, oprnd_info) { oprnd_info->def_stmts.release (); XDELETE (oprnd_info); } oprnds_info.release (); } /* Find the place of the data-ref in STMT in the interleaving chain that starts from FIRST_STMT. Return -1 if the data-ref is not a part of the chain. */ static int vect_get_place_in_interleaving_chain (gimple stmt, gimple first_stmt) { gimple next_stmt = first_stmt; int result = 0; if (first_stmt != GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) return -1; do { if (next_stmt == stmt) return result; result++; next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt)); } while (next_stmt); return -1; } /* Get the defs for the rhs of STMT (collect them in OPRNDS_INFO), check that they are of a valid type and that they match the defs of the first stmt of the SLP group (stored in OPRNDS_INFO). */ static bool vect_get_and_check_slp_defs (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo, gimple stmt, bool first, vec *oprnds_info) { tree oprnd; unsigned int i, number_of_oprnds; tree def; gimple def_stmt; enum vect_def_type dt = vect_uninitialized_def; struct loop *loop = NULL; bool pattern = false; slp_oprnd_info oprnd_info; int op_idx = 1; tree compare_rhs = NULL_TREE; if (loop_vinfo) loop = LOOP_VINFO_LOOP (loop_vinfo); if (is_gimple_call (stmt)) { number_of_oprnds = gimple_call_num_args (stmt); op_idx = 3; } else if (is_gimple_assign (stmt)) { number_of_oprnds = gimple_num_ops (stmt) - 1; if (gimple_assign_rhs_code (stmt) == COND_EXPR) number_of_oprnds++; } else return false; for (i = 0; i < number_of_oprnds; i++) { if (compare_rhs) { oprnd = compare_rhs; compare_rhs = NULL_TREE; } else oprnd = gimple_op (stmt, op_idx++); oprnd_info = (*oprnds_info)[i]; if (COMPARISON_CLASS_P (oprnd)) { compare_rhs = TREE_OPERAND (oprnd, 1); oprnd = TREE_OPERAND (oprnd, 0); } if (!vect_is_simple_use (oprnd, NULL, loop_vinfo, bb_vinfo, &def_stmt, &def, &dt) || (!def_stmt && dt != vect_constant_def)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: can't find def for "); dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, oprnd); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } /* Check if DEF_STMT is a part of a pattern in LOOP and get the def stmt from the pattern. Check that all the stmts of the node are in the pattern. */ if (def_stmt && gimple_bb (def_stmt) && ((loop && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))) || (!loop && gimple_bb (def_stmt) == BB_VINFO_BB (bb_vinfo) && gimple_code (def_stmt) != GIMPLE_PHI)) && vinfo_for_stmt (def_stmt) && STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (def_stmt)) && !STMT_VINFO_RELEVANT (vinfo_for_stmt (def_stmt)) && !STMT_VINFO_LIVE_P (vinfo_for_stmt (def_stmt))) { pattern = true; if (!first && !oprnd_info->first_pattern) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: some of the stmts" " are in a pattern, and others are not "); dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, oprnd); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } def_stmt = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (def_stmt)); dt = STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt)); if (dt == vect_unknown_def_type) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Unsupported pattern.\n"); return false; } switch (gimple_code (def_stmt)) { case GIMPLE_PHI: def = gimple_phi_result (def_stmt); break; case GIMPLE_ASSIGN: def = gimple_assign_lhs (def_stmt); break; default: if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "unsupported defining stmt:\n"); return false; } } if (first) { oprnd_info->first_dt = dt; oprnd_info->first_pattern = pattern; oprnd_info->first_op_type = TREE_TYPE (oprnd); } else { /* Not first stmt of the group, check that the def-stmt/s match the def-stmt/s of the first stmt. Allow different definition types for reduction chains: the first stmt must be a vect_reduction_def (a phi node), and the rest vect_internal_def. */ if (((oprnd_info->first_dt != dt && !(oprnd_info->first_dt == vect_reduction_def && dt == vect_internal_def) && !((oprnd_info->first_dt == vect_external_def || oprnd_info->first_dt == vect_constant_def) && (dt == vect_external_def || dt == vect_constant_def))) || !types_compatible_p (oprnd_info->first_op_type, TREE_TYPE (oprnd)))) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: different types\n"); return false; } } /* Check the types of the definitions. */ switch (dt) { case vect_constant_def: case vect_external_def: case vect_reduction_def: break; case vect_internal_def: oprnd_info->def_stmts.quick_push (def_stmt); break; default: /* FORNOW: Not supported. */ if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: illegal type of def "); dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, def); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } } return true; } /* Verify if the scalar stmts STMTS are isomorphic, require data permutation or are of unsupported types of operation. Return true if they are, otherwise return false and indicate in *MATCHES which stmts are not isomorphic to the first one. If MATCHES[0] is false then this indicates the comparison could not be carried out or the stmts will never be vectorized by SLP. */ static bool vect_build_slp_tree_1 (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo, vec stmts, unsigned int group_size, unsigned nops, unsigned int *max_nunits, unsigned int vectorization_factor, bool *matches) { unsigned int i; gimple stmt = stmts[0]; enum tree_code first_stmt_code = ERROR_MARK, rhs_code = ERROR_MARK; enum tree_code first_cond_code = ERROR_MARK; tree lhs; bool need_same_oprnds = false; tree vectype, scalar_type, first_op1 = NULL_TREE; optab optab; int icode; enum machine_mode optab_op2_mode; enum machine_mode vec_mode; struct data_reference *first_dr; HOST_WIDE_INT dummy; gimple first_load = NULL, prev_first_load = NULL, old_first_load = NULL; tree cond; /* For every stmt in NODE find its def stmt/s. */ FOR_EACH_VEC_ELT (stmts, i, stmt) { matches[i] = false; if (dump_enabled_p ()) { dump_printf_loc (MSG_NOTE, vect_location, "Build SLP for "); dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0); dump_printf (MSG_NOTE, "\n"); } /* Fail to vectorize statements marked as unvectorizable. */ if (!STMT_VINFO_VECTORIZABLE (vinfo_for_stmt (stmt))) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unvectorizable statement "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } lhs = gimple_get_lhs (stmt); if (lhs == NULL_TREE) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: not GIMPLE_ASSIGN nor " "GIMPLE_CALL "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } if (is_gimple_assign (stmt) && gimple_assign_rhs_code (stmt) == COND_EXPR && (cond = gimple_assign_rhs1 (stmt)) && !COMPARISON_CLASS_P (cond)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: condition is not " "comparison "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } scalar_type = vect_get_smallest_scalar_type (stmt, &dummy, &dummy); vectype = get_vectype_for_scalar_type (scalar_type); if (!vectype) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unsupported data-type "); dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, scalar_type); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } /* In case of multiple types we need to detect the smallest type. */ if (*max_nunits < TYPE_VECTOR_SUBPARTS (vectype)) { *max_nunits = TYPE_VECTOR_SUBPARTS (vectype); if (bb_vinfo) vectorization_factor = *max_nunits; } if (is_gimple_call (stmt)) { rhs_code = CALL_EXPR; if (gimple_call_internal_p (stmt) || gimple_call_tail_p (stmt) || gimple_call_noreturn_p (stmt) || !gimple_call_nothrow_p (stmt) || gimple_call_chain (stmt)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unsupported call type "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } } else rhs_code = gimple_assign_rhs_code (stmt); /* Check the operation. */ if (i == 0) { first_stmt_code = rhs_code; /* Shift arguments should be equal in all the packed stmts for a vector shift with scalar shift operand. */ if (rhs_code == LSHIFT_EXPR || rhs_code == RSHIFT_EXPR || rhs_code == LROTATE_EXPR || rhs_code == RROTATE_EXPR) { vec_mode = TYPE_MODE (vectype); /* First see if we have a vector/vector shift. */ optab = optab_for_tree_code (rhs_code, vectype, optab_vector); if (!optab || optab_handler (optab, vec_mode) == CODE_FOR_nothing) { /* No vector/vector shift, try for a vector/scalar shift. */ optab = optab_for_tree_code (rhs_code, vectype, optab_scalar); if (!optab) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: no optab.\n"); /* Fatal mismatch. */ matches[0] = false; return false; } icode = (int) optab_handler (optab, vec_mode); if (icode == CODE_FOR_nothing) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: " "op not supported by target.\n"); /* Fatal mismatch. */ matches[0] = false; return false; } optab_op2_mode = insn_data[icode].operand[2].mode; if (!VECTOR_MODE_P (optab_op2_mode)) { need_same_oprnds = true; first_op1 = gimple_assign_rhs2 (stmt); } } } else if (rhs_code == WIDEN_LSHIFT_EXPR) { need_same_oprnds = true; first_op1 = gimple_assign_rhs2 (stmt); } } else { if (first_stmt_code != rhs_code && (first_stmt_code != IMAGPART_EXPR || rhs_code != REALPART_EXPR) && (first_stmt_code != REALPART_EXPR || rhs_code != IMAGPART_EXPR) && !(STMT_VINFO_GROUPED_ACCESS (vinfo_for_stmt (stmt)) && (first_stmt_code == ARRAY_REF || first_stmt_code == BIT_FIELD_REF || first_stmt_code == INDIRECT_REF || first_stmt_code == COMPONENT_REF || first_stmt_code == MEM_REF))) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: different operation " "in stmt "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Mismatch. */ continue; } if (need_same_oprnds && !operand_equal_p (first_op1, gimple_assign_rhs2 (stmt), 0)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: different shift " "arguments in "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Mismatch. */ continue; } if (rhs_code == CALL_EXPR) { gimple first_stmt = stmts[0]; if (gimple_call_num_args (stmt) != nops || !operand_equal_p (gimple_call_fn (first_stmt), gimple_call_fn (stmt), 0) || gimple_call_fntype (first_stmt) != gimple_call_fntype (stmt)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: different calls in "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Mismatch. */ continue; } } } /* Grouped store or load. */ if (STMT_VINFO_GROUPED_ACCESS (vinfo_for_stmt (stmt))) { if (REFERENCE_CLASS_P (lhs)) { /* Store. */ ; } else { /* Load. */ unsigned unrolling_factor = least_common_multiple (*max_nunits, group_size) / group_size; /* FORNOW: Check that there is no gap between the loads and no gap between the groups when we need to load multiple groups at once. ??? We should enhance this to only disallow gaps inside vectors. */ if ((unrolling_factor > 1 && GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)) == stmt && GROUP_GAP (vinfo_for_stmt (stmt)) != 0) || (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)) != stmt && GROUP_GAP (vinfo_for_stmt (stmt)) != 1)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: grouped " "loads have gaps "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } /* Check that the size of interleaved loads group is not greater than the SLP group size. */ unsigned ncopies = vectorization_factor / TYPE_VECTOR_SUBPARTS (vectype); if (loop_vinfo && GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)) == stmt && ((GROUP_SIZE (vinfo_for_stmt (stmt)) - GROUP_GAP (vinfo_for_stmt (stmt))) > ncopies * group_size)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: the number " "of interleaved loads is greater than " "the SLP group size "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } old_first_load = first_load; first_load = GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)); if (prev_first_load) { /* Check that there are no loads from different interleaving chains in the same node. */ if (prev_first_load != first_load) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: different " "interleaving chains in one node "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Mismatch. */ continue; } } else prev_first_load = first_load; /* In some cases a group of loads is just the same load repeated N times. Only analyze its cost once. */ if (first_load == stmt && old_first_load != first_load) { first_dr = STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)); if (vect_supportable_dr_alignment (first_dr, false) == dr_unaligned_unsupported) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unsupported " "unaligned load "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } } } } /* Grouped access. */ else { if (TREE_CODE_CLASS (rhs_code) == tcc_reference) { /* Not grouped load. */ if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: not grouped load "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* FORNOW: Not grouped loads are not supported. */ /* Fatal mismatch. */ matches[0] = false; return false; } /* Not memory operation. */ if (TREE_CODE_CLASS (rhs_code) != tcc_binary && TREE_CODE_CLASS (rhs_code) != tcc_unary && rhs_code != COND_EXPR && rhs_code != CALL_EXPR) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: operation"); dump_printf (MSG_MISSED_OPTIMIZATION, " unsupported "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Fatal mismatch. */ matches[0] = false; return false; } if (rhs_code == COND_EXPR) { tree cond_expr = gimple_assign_rhs1 (stmt); if (i == 0) first_cond_code = TREE_CODE (cond_expr); else if (first_cond_code != TREE_CODE (cond_expr)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: different" " operation"); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } /* Mismatch. */ continue; } } } matches[i] = true; } for (i = 0; i < group_size; ++i) if (!matches[i]) return false; return true; } /* Recursively build an SLP tree starting from NODE. Fail (and return a value not equal to zero) if def-stmts are not isomorphic, require data permutation or are of unsupported types of operation. Otherwise, return 0. The value returned is the depth in the SLP tree where a mismatch was found. */ static bool vect_build_slp_tree (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo, slp_tree *node, unsigned int group_size, unsigned int *max_nunits, vec *loads, unsigned int vectorization_factor, bool *matches, unsigned *npermutes) { unsigned nops, i, this_npermutes = 0; gimple stmt; if (!matches) matches = XALLOCAVEC (bool, group_size); if (!npermutes) npermutes = &this_npermutes; matches[0] = false; stmt = SLP_TREE_SCALAR_STMTS (*node)[0]; if (is_gimple_call (stmt)) nops = gimple_call_num_args (stmt); else if (is_gimple_assign (stmt)) { nops = gimple_num_ops (stmt) - 1; if (gimple_assign_rhs_code (stmt) == COND_EXPR) nops++; } else return false; if (!vect_build_slp_tree_1 (loop_vinfo, bb_vinfo, SLP_TREE_SCALAR_STMTS (*node), group_size, nops, max_nunits, vectorization_factor, matches)) return false; /* If the SLP node is a load, terminate the recursion. */ if (STMT_VINFO_GROUPED_ACCESS (vinfo_for_stmt (stmt)) && DR_IS_READ (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)))) { loads->safe_push (*node); return true; } /* Get at the operands, verifying they are compatible. */ vec oprnds_info = vect_create_oprnd_info (nops, group_size); slp_oprnd_info oprnd_info; FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (*node), i, stmt) { if (!vect_get_and_check_slp_defs (loop_vinfo, bb_vinfo, stmt, (i == 0), &oprnds_info)) { vect_free_oprnd_info (oprnds_info); return false; } } stmt = SLP_TREE_SCALAR_STMTS (*node)[0]; /* Create SLP_TREE nodes for the definition node/s. */ FOR_EACH_VEC_ELT (oprnds_info, i, oprnd_info) { slp_tree child; unsigned old_nloads = loads->length (); unsigned old_max_nunits = *max_nunits; if (oprnd_info->first_dt != vect_internal_def) continue; child = vect_create_new_slp_node (oprnd_info->def_stmts); if (!child) { vect_free_oprnd_info (oprnds_info); return false; } bool *matches = XALLOCAVEC (bool, group_size); if (vect_build_slp_tree (loop_vinfo, bb_vinfo, &child, group_size, max_nunits, loads, vectorization_factor, matches, npermutes)) { oprnd_info->def_stmts = vNULL; SLP_TREE_CHILDREN (*node).quick_push (child); continue; } /* If the SLP build for operand zero failed and operand zero and one can be commutated try that for the scalar stmts that failed the match. */ if (i == 0 /* A first scalar stmt mismatch signals a fatal mismatch. */ && matches[0] /* ??? For COND_EXPRs we can swap the comparison operands as well as the arms under some constraints. */ && nops == 2 && oprnds_info[1]->first_dt == vect_internal_def && is_gimple_assign (stmt) && commutative_tree_code (gimple_assign_rhs_code (stmt)) /* Do so only if the number of not successful permutes was nor more than a cut-ff as re-trying the recursive match on possibly each level of the tree would expose exponential behavior. */ && *npermutes < 4) { /* Roll back. */ *max_nunits = old_max_nunits; loads->truncate (old_nloads); /* Swap mismatched definition stmts. */ for (unsigned j = 0; j < group_size; ++j) if (!matches[j]) { gimple tem = oprnds_info[0]->def_stmts[j]; oprnds_info[0]->def_stmts[j] = oprnds_info[1]->def_stmts[j]; oprnds_info[1]->def_stmts[j] = tem; } /* And try again ... */ if (vect_build_slp_tree (loop_vinfo, bb_vinfo, &child, group_size, max_nunits, loads, vectorization_factor, matches, npermutes)) { oprnd_info->def_stmts = vNULL; SLP_TREE_CHILDREN (*node).quick_push (child); continue; } ++*npermutes; } oprnd_info->def_stmts = vNULL; vect_free_slp_tree (child); vect_free_oprnd_info (oprnds_info); return false; } vect_free_oprnd_info (oprnds_info); return true; } /* Dump a slp tree NODE using flags specified in DUMP_KIND. */ static void vect_print_slp_tree (int dump_kind, slp_tree node) { int i; gimple stmt; slp_tree child; if (!node) return; dump_printf (dump_kind, "node "); FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) { dump_printf (dump_kind, "\n\tstmt %d ", i); dump_gimple_stmt (dump_kind, TDF_SLIM, stmt, 0); } dump_printf (dump_kind, "\n"); FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_print_slp_tree (dump_kind, child); } /* Mark the tree rooted at NODE with MARK (PURE_SLP or HYBRID). If MARK is HYBRID, it refers to a specific stmt in NODE (the stmt at index J). Otherwise, MARK is PURE_SLP and J is -1, which indicates that all the stmts in NODE are to be marked. */ static void vect_mark_slp_stmts (slp_tree node, enum slp_vect_type mark, int j) { int i; gimple stmt; slp_tree child; if (!node) return; FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) if (j < 0 || i == j) STMT_SLP_TYPE (vinfo_for_stmt (stmt)) = mark; FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_mark_slp_stmts (child, mark, j); } /* Mark the statements of the tree rooted at NODE as relevant (vect_used). */ static void vect_mark_slp_stmts_relevant (slp_tree node) { int i; gimple stmt; stmt_vec_info stmt_info; slp_tree child; if (!node) return; FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) { stmt_info = vinfo_for_stmt (stmt); gcc_assert (!STMT_VINFO_RELEVANT (stmt_info) || STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_scope); STMT_VINFO_RELEVANT (stmt_info) = vect_used_in_scope; } FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_mark_slp_stmts_relevant (child); } /* Rearrange the statements of NODE according to PERMUTATION. */ static void vect_slp_rearrange_stmts (slp_tree node, unsigned int group_size, vec permutation) { gimple stmt; vec tmp_stmts; unsigned int i; slp_tree child; FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_slp_rearrange_stmts (child, group_size, permutation); gcc_assert (group_size == SLP_TREE_SCALAR_STMTS (node).length ()); tmp_stmts.create (group_size); tmp_stmts.quick_grow_cleared (group_size); FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) tmp_stmts[permutation[i]] = stmt; SLP_TREE_SCALAR_STMTS (node).release (); SLP_TREE_SCALAR_STMTS (node) = tmp_stmts; } /* Check if the required load permutations in the SLP instance SLP_INSTN are supported. */ static bool vect_supported_load_permutation_p (slp_instance slp_instn) { unsigned int group_size = SLP_INSTANCE_GROUP_SIZE (slp_instn); unsigned int i, j, k, next; sbitmap load_index; slp_tree node; gimple stmt, load, next_load, first_load; struct data_reference *dr; if (dump_enabled_p ()) { dump_printf_loc (MSG_NOTE, vect_location, "Load permutation "); FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) if (node->load_permutation.exists ()) FOR_EACH_VEC_ELT (node->load_permutation, j, next) dump_printf (MSG_NOTE, "%d ", next); else for (i = 0; i < group_size; ++i) dump_printf (MSG_NOTE, "%d ", i); dump_printf (MSG_NOTE, "\n"); } /* In case of reduction every load permutation is allowed, since the order of the reduction statements is not important (as opposed to the case of grouped stores). The only condition we need to check is that all the load nodes are of the same size and have the same permutation (and then rearrange all the nodes of the SLP instance according to this permutation). */ /* Check that all the load nodes are of the same size. */ /* ??? Can't we assert this? */ FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) if (SLP_TREE_SCALAR_STMTS (node).length () != (unsigned) group_size) return false; node = SLP_INSTANCE_TREE (slp_instn); stmt = SLP_TREE_SCALAR_STMTS (node)[0]; /* Reduction (there are no data-refs in the root). In reduction chain the order of the loads is important. */ if (!STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)) && !GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) { slp_tree load; unsigned int lidx; /* Compare all the permutation sequences to the first one. We know that at least one load is permuted. */ node = SLP_INSTANCE_LOADS (slp_instn)[0]; if (!node->load_permutation.exists ()) return false; for (i = 1; SLP_INSTANCE_LOADS (slp_instn).iterate (i, &load); ++i) { if (!load->load_permutation.exists ()) return false; FOR_EACH_VEC_ELT (load->load_permutation, j, lidx) if (lidx != node->load_permutation[j]) return false; } /* Check that the loads in the first sequence are different and there are no gaps between them. */ load_index = sbitmap_alloc (group_size); bitmap_clear (load_index); FOR_EACH_VEC_ELT (node->load_permutation, i, lidx) { if (bitmap_bit_p (load_index, lidx)) { sbitmap_free (load_index); return false; } bitmap_set_bit (load_index, lidx); } for (i = 0; i < group_size; i++) if (!bitmap_bit_p (load_index, i)) { sbitmap_free (load_index); return false; } sbitmap_free (load_index); /* This permutation is valid for reduction. Since the order of the statements in the nodes is not important unless they are memory accesses, we can rearrange the statements in all the nodes according to the order of the loads. */ vect_slp_rearrange_stmts (SLP_INSTANCE_TREE (slp_instn), group_size, node->load_permutation); /* We are done, no actual permutations need to be generated. */ FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) SLP_TREE_LOAD_PERMUTATION (node).release (); return true; } /* In basic block vectorization we allow any subchain of an interleaving chain. FORNOW: not supported in loop SLP because of realignment compications. */ if (STMT_VINFO_BB_VINFO (vinfo_for_stmt (stmt))) { /* Check that for every node in the instance the loads form a subchain. */ FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) { next_load = NULL; FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), j, load) { if (j != 0 && next_load != load) return false; next_load = GROUP_NEXT_ELEMENT (vinfo_for_stmt (load)); } } /* Check that the alignment of the first load in every subchain, i.e., the first statement in every load node, is supported. ??? This belongs in alignment checking. */ FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) { first_load = SLP_TREE_SCALAR_STMTS (node)[0]; if (first_load != GROUP_FIRST_ELEMENT (vinfo_for_stmt (first_load))) { dr = STMT_VINFO_DATA_REF (vinfo_for_stmt (first_load)); if (vect_supportable_dr_alignment (dr, false) == dr_unaligned_unsupported) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "unsupported unaligned load "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, first_load, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } } } /* We are done, no actual permutations need to be generated. */ FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) SLP_TREE_LOAD_PERMUTATION (node).release (); return true; } /* FORNOW: the only supported permutation is 0..01..1.. of length equal to GROUP_SIZE and where each sequence of same drs is of GROUP_SIZE length as well (unless it's reduction). */ if (SLP_INSTANCE_LOADS (slp_instn).length () != group_size) return false; FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) if (!node->load_permutation.exists ()) return false; load_index = sbitmap_alloc (group_size); bitmap_clear (load_index); FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) { unsigned int lidx = node->load_permutation[0]; if (bitmap_bit_p (load_index, lidx)) { sbitmap_free (load_index); return false; } bitmap_set_bit (load_index, lidx); FOR_EACH_VEC_ELT (node->load_permutation, j, k) if (k != lidx) { sbitmap_free (load_index); return false; } } for (i = 0; i < group_size; i++) if (!bitmap_bit_p (load_index, i)) { sbitmap_free (load_index); return false; } sbitmap_free (load_index); FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (slp_instn), i, node) if (node->load_permutation.exists () && !vect_transform_slp_perm_load (node, vNULL, NULL, SLP_INSTANCE_UNROLLING_FACTOR (slp_instn), slp_instn, true)) return false; return true; } /* Find the first load in the loop that belongs to INSTANCE. When loads are in several SLP nodes, there can be a case in which the first load does not appear in the first SLP node to be transformed, causing incorrect order of statements. Since we generate all the loads together, they must be inserted before the first load of the SLP instance and not before the first load of the first node of the instance. */ static gimple vect_find_first_load_in_slp_instance (slp_instance instance) { int i, j; slp_tree load_node; gimple first_load = NULL, load; FOR_EACH_VEC_ELT (SLP_INSTANCE_LOADS (instance), i, load_node) FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (load_node), j, load) first_load = get_earlier_stmt (load, first_load); return first_load; } /* Find the last store in SLP INSTANCE. */ static gimple vect_find_last_store_in_slp_instance (slp_instance instance) { int i; slp_tree node; gimple last_store = NULL, store; node = SLP_INSTANCE_TREE (instance); for (i = 0; SLP_TREE_SCALAR_STMTS (node).iterate (i, &store); i++) last_store = get_later_stmt (store, last_store); return last_store; } /* Compute the cost for the SLP node NODE in the SLP instance INSTANCE. */ static void vect_analyze_slp_cost_1 (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo, slp_instance instance, slp_tree node, stmt_vector_for_cost *prologue_cost_vec, unsigned ncopies_for_cost) { stmt_vector_for_cost *body_cost_vec = &SLP_INSTANCE_BODY_COST_VEC (instance); unsigned i; slp_tree child; gimple stmt, s; stmt_vec_info stmt_info; tree lhs; unsigned group_size = SLP_INSTANCE_GROUP_SIZE (instance); /* Recurse down the SLP tree. */ FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_analyze_slp_cost_1 (loop_vinfo, bb_vinfo, instance, child, prologue_cost_vec, ncopies_for_cost); /* Look at the first scalar stmt to determine the cost. */ stmt = SLP_TREE_SCALAR_STMTS (node)[0]; stmt_info = vinfo_for_stmt (stmt); if (STMT_VINFO_GROUPED_ACCESS (stmt_info)) { if (DR_IS_WRITE (STMT_VINFO_DATA_REF (stmt_info))) vect_model_store_cost (stmt_info, ncopies_for_cost, false, vect_uninitialized_def, node, prologue_cost_vec, body_cost_vec); else { int i; gcc_checking_assert (DR_IS_READ (STMT_VINFO_DATA_REF (stmt_info))); vect_model_load_cost (stmt_info, ncopies_for_cost, false, node, prologue_cost_vec, body_cost_vec); /* If the load is permuted record the cost for the permutation. ??? Loads from multiple chains are let through here only for a single special case involving complex numbers where in the end no permutation is necessary. */ FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, s) if ((STMT_VINFO_GROUP_FIRST_ELEMENT (vinfo_for_stmt (s)) == STMT_VINFO_GROUP_FIRST_ELEMENT (stmt_info)) && vect_get_place_in_interleaving_chain (s, STMT_VINFO_GROUP_FIRST_ELEMENT (stmt_info)) != i) { record_stmt_cost (body_cost_vec, group_size, vec_perm, stmt_info, 0, vect_body); break; } } } else record_stmt_cost (body_cost_vec, ncopies_for_cost, vector_stmt, stmt_info, 0, vect_body); /* Scan operands and account for prologue cost of constants/externals. ??? This over-estimates cost for multiple uses and should be re-engineered. */ lhs = gimple_get_lhs (stmt); for (i = 0; i < gimple_num_ops (stmt); ++i) { tree def, op = gimple_op (stmt, i); gimple def_stmt; enum vect_def_type dt; if (!op || op == lhs) continue; if (vect_is_simple_use (op, NULL, loop_vinfo, bb_vinfo, &def_stmt, &def, &dt) && (dt == vect_constant_def || dt == vect_external_def)) record_stmt_cost (prologue_cost_vec, 1, vector_stmt, stmt_info, 0, vect_prologue); } } /* Compute the cost for the SLP instance INSTANCE. */ static void vect_analyze_slp_cost (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo, slp_instance instance, unsigned nunits) { stmt_vector_for_cost body_cost_vec, prologue_cost_vec; unsigned ncopies_for_cost; stmt_info_for_cost *si; unsigned i; /* Calculate the number of vector stmts to create based on the unrolling factor (number of vectors is 1 if NUNITS >= GROUP_SIZE, and is GROUP_SIZE / NUNITS otherwise. */ unsigned group_size = SLP_INSTANCE_GROUP_SIZE (instance); ncopies_for_cost = least_common_multiple (nunits, group_size) / nunits; prologue_cost_vec.create (10); body_cost_vec.create (10); SLP_INSTANCE_BODY_COST_VEC (instance) = body_cost_vec; vect_analyze_slp_cost_1 (loop_vinfo, bb_vinfo, instance, SLP_INSTANCE_TREE (instance), &prologue_cost_vec, ncopies_for_cost); /* Record the prologue costs, which were delayed until we were sure that SLP was successful. Unlike the body costs, we know the final values now regardless of the loop vectorization factor. */ void *data = (loop_vinfo ? LOOP_VINFO_TARGET_COST_DATA (loop_vinfo) : BB_VINFO_TARGET_COST_DATA (bb_vinfo)); FOR_EACH_VEC_ELT (prologue_cost_vec, i, si) { struct _stmt_vec_info *stmt_info = si->stmt ? vinfo_for_stmt (si->stmt) : NULL; (void) add_stmt_cost (data, si->count, si->kind, stmt_info, si->misalign, vect_prologue); } prologue_cost_vec.release (); } /* Analyze an SLP instance starting from a group of grouped stores. Call vect_build_slp_tree to build a tree of packed stmts if possible. Return FALSE if it's impossible to SLP any stmt in the loop. */ static bool vect_analyze_slp_instance (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo, gimple stmt) { slp_instance new_instance; slp_tree node; unsigned int group_size = GROUP_SIZE (vinfo_for_stmt (stmt)); unsigned int unrolling_factor = 1, nunits; tree vectype, scalar_type = NULL_TREE; gimple next; unsigned int vectorization_factor = 0; int i; unsigned int max_nunits = 0; vec loads; struct data_reference *dr = STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)); vec scalar_stmts; if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) { if (dr) { scalar_type = TREE_TYPE (DR_REF (dr)); vectype = get_vectype_for_scalar_type (scalar_type); } else { gcc_assert (loop_vinfo); vectype = STMT_VINFO_VECTYPE (vinfo_for_stmt (stmt)); } group_size = GROUP_SIZE (vinfo_for_stmt (stmt)); } else { gcc_assert (loop_vinfo); vectype = STMT_VINFO_VECTYPE (vinfo_for_stmt (stmt)); group_size = LOOP_VINFO_REDUCTIONS (loop_vinfo).length (); } if (!vectype) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unsupported data-type "); dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, scalar_type); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } nunits = TYPE_VECTOR_SUBPARTS (vectype); if (loop_vinfo) vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo); else vectorization_factor = nunits; /* Calculate the unrolling factor. */ unrolling_factor = least_common_multiple (nunits, group_size) / group_size; if (unrolling_factor != 1 && !loop_vinfo) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unrolling required in basic" " block SLP\n"); return false; } /* Create a node (a root of the SLP tree) for the packed grouped stores. */ scalar_stmts.create (group_size); next = stmt; if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) { /* Collect the stores and store them in SLP_TREE_SCALAR_STMTS. */ while (next) { if (STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (next)) && STMT_VINFO_RELATED_STMT (vinfo_for_stmt (next))) scalar_stmts.safe_push ( STMT_VINFO_RELATED_STMT (vinfo_for_stmt (next))); else scalar_stmts.safe_push (next); next = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next)); } } else { /* Collect reduction statements. */ vec reductions = LOOP_VINFO_REDUCTIONS (loop_vinfo); for (i = 0; reductions.iterate (i, &next); i++) scalar_stmts.safe_push (next); } node = vect_create_new_slp_node (scalar_stmts); loads.create (group_size); /* Build the tree for the SLP instance. */ if (vect_build_slp_tree (loop_vinfo, bb_vinfo, &node, group_size, &max_nunits, &loads, vectorization_factor, NULL, NULL)) { /* Calculate the unrolling factor based on the smallest type. */ if (max_nunits > nunits) unrolling_factor = least_common_multiple (max_nunits, group_size) / group_size; if (unrolling_factor != 1 && !loop_vinfo) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unrolling required in basic" " block SLP\n"); vect_free_slp_tree (node); loads.release (); return false; } /* Create a new SLP instance. */ new_instance = XNEW (struct _slp_instance); SLP_INSTANCE_TREE (new_instance) = node; SLP_INSTANCE_GROUP_SIZE (new_instance) = group_size; SLP_INSTANCE_UNROLLING_FACTOR (new_instance) = unrolling_factor; SLP_INSTANCE_BODY_COST_VEC (new_instance) = vNULL; SLP_INSTANCE_LOADS (new_instance) = loads; SLP_INSTANCE_FIRST_LOAD_STMT (new_instance) = NULL; /* Compute the load permutation. */ slp_tree load_node; bool loads_permuted = false; FOR_EACH_VEC_ELT (loads, i, load_node) { vec load_permutation; int j; gimple load, first_stmt; bool this_load_permuted = false; load_permutation.create (group_size); first_stmt = GROUP_FIRST_ELEMENT (vinfo_for_stmt (SLP_TREE_SCALAR_STMTS (load_node)[0])); FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (load_node), j, load) { int load_place = vect_get_place_in_interleaving_chain (load, first_stmt); gcc_assert (load_place != -1); if (load_place != j) this_load_permuted = true; load_permutation.safe_push (load_place); } if (!this_load_permuted) { load_permutation.release (); continue; } SLP_TREE_LOAD_PERMUTATION (load_node) = load_permutation; loads_permuted = true; } if (loads_permuted) { if (!vect_supported_load_permutation_p (new_instance)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Build SLP failed: unsupported load " "permutation "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } vect_free_slp_instance (new_instance); return false; } SLP_INSTANCE_FIRST_LOAD_STMT (new_instance) = vect_find_first_load_in_slp_instance (new_instance); } /* Compute the costs of this SLP instance. */ vect_analyze_slp_cost (loop_vinfo, bb_vinfo, new_instance, TYPE_VECTOR_SUBPARTS (vectype)); if (loop_vinfo) LOOP_VINFO_SLP_INSTANCES (loop_vinfo).safe_push (new_instance); else BB_VINFO_SLP_INSTANCES (bb_vinfo).safe_push (new_instance); if (dump_enabled_p ()) vect_print_slp_tree (MSG_NOTE, node); return true; } /* Failed to SLP. */ /* Free the allocated memory. */ vect_free_slp_tree (node); loads.release (); return false; } /* Check if there are stmts in the loop can be vectorized using SLP. Build SLP trees of packed scalar stmts if SLP is possible. */ bool vect_analyze_slp (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo) { unsigned int i; vec grouped_stores; vec reductions = vNULL; vec reduc_chains = vNULL; gimple first_element; bool ok = false; if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "=== vect_analyze_slp ===\n"); if (loop_vinfo) { grouped_stores = LOOP_VINFO_GROUPED_STORES (loop_vinfo); reduc_chains = LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo); reductions = LOOP_VINFO_REDUCTIONS (loop_vinfo); } else grouped_stores = BB_VINFO_GROUPED_STORES (bb_vinfo); /* Find SLP sequences starting from groups of grouped stores. */ FOR_EACH_VEC_ELT (grouped_stores, i, first_element) if (vect_analyze_slp_instance (loop_vinfo, bb_vinfo, first_element)) ok = true; if (bb_vinfo && !ok) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "Failed to SLP the basic block.\n"); return false; } if (loop_vinfo && LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo).length () > 0) { /* Find SLP sequences starting from reduction chains. */ FOR_EACH_VEC_ELT (reduc_chains, i, first_element) if (vect_analyze_slp_instance (loop_vinfo, bb_vinfo, first_element)) ok = true; else return false; /* Don't try to vectorize SLP reductions if reduction chain was detected. */ return ok; } /* Find SLP sequences starting from groups of reductions. */ if (loop_vinfo && LOOP_VINFO_REDUCTIONS (loop_vinfo).length () > 1 && vect_analyze_slp_instance (loop_vinfo, bb_vinfo, reductions[0])) ok = true; return true; } /* For each possible SLP instance decide whether to SLP it and calculate overall unrolling factor needed to SLP the loop. Return TRUE if decided to SLP at least one instance. */ bool vect_make_slp_decision (loop_vec_info loop_vinfo) { unsigned int i, unrolling_factor = 1; vec slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo); slp_instance instance; int decided_to_slp = 0; if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "=== vect_make_slp_decision ===" "\n"); FOR_EACH_VEC_ELT (slp_instances, i, instance) { /* FORNOW: SLP if you can. */ if (unrolling_factor < SLP_INSTANCE_UNROLLING_FACTOR (instance)) unrolling_factor = SLP_INSTANCE_UNROLLING_FACTOR (instance); /* Mark all the stmts that belong to INSTANCE as PURE_SLP stmts. Later we call vect_detect_hybrid_slp () to find stmts that need hybrid SLP and loop-based vectorization. Such stmts will be marked as HYBRID. */ vect_mark_slp_stmts (SLP_INSTANCE_TREE (instance), pure_slp, -1); decided_to_slp++; } LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo) = unrolling_factor; if (decided_to_slp && dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "Decided to SLP %d instances. Unrolling factor %d\n", decided_to_slp, unrolling_factor); return (decided_to_slp > 0); } /* Find stmts that must be both vectorized and SLPed (since they feed stmts that can't be SLPed) in the tree rooted at NODE. Mark such stmts as HYBRID. */ static void vect_detect_hybrid_slp_stmts (slp_tree node) { int i; vec stmts = SLP_TREE_SCALAR_STMTS (node); gimple stmt = stmts[0]; imm_use_iterator imm_iter; gimple use_stmt; stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt); slp_tree child; loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo); struct loop *loop = NULL; bb_vec_info bb_vinfo = STMT_VINFO_BB_VINFO (stmt_vinfo); basic_block bb = NULL; if (!node) return; if (loop_vinfo) loop = LOOP_VINFO_LOOP (loop_vinfo); else bb = BB_VINFO_BB (bb_vinfo); FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) if (PURE_SLP_STMT (vinfo_for_stmt (stmt)) && TREE_CODE (gimple_op (stmt, 0)) == SSA_NAME) FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, gimple_op (stmt, 0)) if (gimple_bb (use_stmt) && ((loop && flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))) || bb == gimple_bb (use_stmt)) && (stmt_vinfo = vinfo_for_stmt (use_stmt)) && !STMT_SLP_TYPE (stmt_vinfo) && (STMT_VINFO_RELEVANT (stmt_vinfo) || VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_vinfo))) && !(gimple_code (use_stmt) == GIMPLE_PHI && STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_reduction_def)) vect_mark_slp_stmts (node, hybrid, i); FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_detect_hybrid_slp_stmts (child); } /* Find stmts that must be both vectorized and SLPed. */ void vect_detect_hybrid_slp (loop_vec_info loop_vinfo) { unsigned int i; vec slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo); slp_instance instance; if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "=== vect_detect_hybrid_slp ===" "\n"); FOR_EACH_VEC_ELT (slp_instances, i, instance) vect_detect_hybrid_slp_stmts (SLP_INSTANCE_TREE (instance)); } /* Create and initialize a new bb_vec_info struct for BB, as well as stmt_vec_info structs for all the stmts in it. */ static bb_vec_info new_bb_vec_info (basic_block bb) { bb_vec_info res = NULL; gimple_stmt_iterator gsi; res = (bb_vec_info) xcalloc (1, sizeof (struct _bb_vec_info)); BB_VINFO_BB (res) = bb; for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi)) { gimple stmt = gsi_stmt (gsi); gimple_set_uid (stmt, 0); set_vinfo_for_stmt (stmt, new_stmt_vec_info (stmt, NULL, res)); } BB_VINFO_GROUPED_STORES (res).create (10); BB_VINFO_SLP_INSTANCES (res).create (2); BB_VINFO_TARGET_COST_DATA (res) = init_cost (NULL); bb->aux = res; return res; } /* Free BB_VINFO struct, as well as all the stmt_vec_info structs of all the stmts in the basic block. */ static void destroy_bb_vec_info (bb_vec_info bb_vinfo) { vec slp_instances; slp_instance instance; basic_block bb; gimple_stmt_iterator si; unsigned i; if (!bb_vinfo) return; bb = BB_VINFO_BB (bb_vinfo); for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si)) { gimple stmt = gsi_stmt (si); stmt_vec_info stmt_info = vinfo_for_stmt (stmt); if (stmt_info) /* Free stmt_vec_info. */ free_stmt_vec_info (stmt); } vect_destroy_datarefs (NULL, bb_vinfo); free_dependence_relations (BB_VINFO_DDRS (bb_vinfo)); BB_VINFO_GROUPED_STORES (bb_vinfo).release (); slp_instances = BB_VINFO_SLP_INSTANCES (bb_vinfo); FOR_EACH_VEC_ELT (slp_instances, i, instance) vect_free_slp_instance (instance); BB_VINFO_SLP_INSTANCES (bb_vinfo).release (); destroy_cost_data (BB_VINFO_TARGET_COST_DATA (bb_vinfo)); free (bb_vinfo); bb->aux = NULL; } /* Analyze statements contained in SLP tree node after recursively analyzing the subtree. Return TRUE if the operations are supported. */ static bool vect_slp_analyze_node_operations (bb_vec_info bb_vinfo, slp_tree node) { bool dummy; int i; gimple stmt; slp_tree child; if (!node) return true; FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) if (!vect_slp_analyze_node_operations (bb_vinfo, child)) return false; FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) { stmt_vec_info stmt_info = vinfo_for_stmt (stmt); gcc_assert (stmt_info); gcc_assert (PURE_SLP_STMT (stmt_info)); if (!vect_analyze_stmt (stmt, &dummy, node)) return false; } return true; } /* Analyze statements in SLP instances of the basic block. Return TRUE if the operations are supported. */ static bool vect_slp_analyze_operations (bb_vec_info bb_vinfo) { vec slp_instances = BB_VINFO_SLP_INSTANCES (bb_vinfo); slp_instance instance; int i; for (i = 0; slp_instances.iterate (i, &instance); ) { if (!vect_slp_analyze_node_operations (bb_vinfo, SLP_INSTANCE_TREE (instance))) { vect_free_slp_instance (instance); slp_instances.ordered_remove (i); } else i++; } if (!slp_instances.length ()) return false; return true; } /* Compute the scalar cost of the SLP node NODE and its children and return it. Do not account defs that are marked in LIFE and update LIFE according to uses of NODE. */ static unsigned vect_bb_slp_scalar_cost (basic_block bb, slp_tree node, vec life) { unsigned scalar_cost = 0; unsigned i; gimple stmt; slp_tree child; FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) { unsigned stmt_cost; ssa_op_iter op_iter; def_operand_p def_p; stmt_vec_info stmt_info; if (life[i]) continue; /* If there is a non-vectorized use of the defs then the scalar stmt is kept live in which case we do not account it or any required defs in the SLP children in the scalar cost. This way we make the vectorization more costly when compared to the scalar cost. */ FOR_EACH_SSA_DEF_OPERAND (def_p, stmt, op_iter, SSA_OP_DEF) { imm_use_iterator use_iter; gimple use_stmt; FOR_EACH_IMM_USE_STMT (use_stmt, use_iter, DEF_FROM_PTR (def_p)) if (gimple_code (use_stmt) == GIMPLE_PHI || gimple_bb (use_stmt) != bb || !STMT_VINFO_VECTORIZABLE (vinfo_for_stmt (use_stmt))) { life[i] = true; BREAK_FROM_IMM_USE_STMT (use_iter); } } if (life[i]) continue; stmt_info = vinfo_for_stmt (stmt); if (STMT_VINFO_DATA_REF (stmt_info)) { if (DR_IS_READ (STMT_VINFO_DATA_REF (stmt_info))) stmt_cost = vect_get_stmt_cost (scalar_load); else stmt_cost = vect_get_stmt_cost (scalar_store); } else stmt_cost = vect_get_stmt_cost (scalar_stmt); scalar_cost += stmt_cost; } FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) scalar_cost += vect_bb_slp_scalar_cost (bb, child, life); return scalar_cost; } /* Check if vectorization of the basic block is profitable. */ static bool vect_bb_vectorization_profitable_p (bb_vec_info bb_vinfo) { vec slp_instances = BB_VINFO_SLP_INSTANCES (bb_vinfo); slp_instance instance; int i, j; unsigned int vec_inside_cost = 0, vec_outside_cost = 0, scalar_cost = 0; unsigned int vec_prologue_cost = 0, vec_epilogue_cost = 0; void *target_cost_data = BB_VINFO_TARGET_COST_DATA (bb_vinfo); stmt_vec_info stmt_info = NULL; stmt_vector_for_cost body_cost_vec; stmt_info_for_cost *ci; /* Calculate vector costs. */ FOR_EACH_VEC_ELT (slp_instances, i, instance) { body_cost_vec = SLP_INSTANCE_BODY_COST_VEC (instance); FOR_EACH_VEC_ELT (body_cost_vec, j, ci) { stmt_info = ci->stmt ? vinfo_for_stmt (ci->stmt) : NULL; (void) add_stmt_cost (target_cost_data, ci->count, ci->kind, stmt_info, ci->misalign, vect_body); } } /* Calculate scalar cost. */ FOR_EACH_VEC_ELT (slp_instances, i, instance) { vec life; vec_stack_alloc (bool, life, SLP_INSTANCE_GROUP_SIZE (instance)); life.quick_grow_cleared (SLP_INSTANCE_GROUP_SIZE (instance)); scalar_cost += vect_bb_slp_scalar_cost (BB_VINFO_BB (bb_vinfo), SLP_INSTANCE_TREE (instance), life); life.release (); } /* Complete the target-specific cost calculation. */ finish_cost (BB_VINFO_TARGET_COST_DATA (bb_vinfo), &vec_prologue_cost, &vec_inside_cost, &vec_epilogue_cost); vec_outside_cost = vec_prologue_cost + vec_epilogue_cost; if (dump_enabled_p ()) { dump_printf_loc (MSG_NOTE, vect_location, "Cost model analysis: \n"); dump_printf (MSG_NOTE, " Vector inside of basic block cost: %d\n", vec_inside_cost); dump_printf (MSG_NOTE, " Vector prologue cost: %d\n", vec_prologue_cost); dump_printf (MSG_NOTE, " Vector epilogue cost: %d\n", vec_epilogue_cost); dump_printf (MSG_NOTE, " Scalar cost of basic block: %d\n", scalar_cost); } /* Vectorization is profitable if its cost is less than the cost of scalar version. */ if (vec_outside_cost + vec_inside_cost >= scalar_cost) return false; return true; } /* Check if the basic block can be vectorized. */ static bb_vec_info vect_slp_analyze_bb_1 (basic_block bb) { bb_vec_info bb_vinfo; vec slp_instances; slp_instance instance; int i; int min_vf = 2; bb_vinfo = new_bb_vec_info (bb); if (!bb_vinfo) return NULL; if (!vect_analyze_data_refs (NULL, bb_vinfo, &min_vf)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: unhandled data-ref in basic " "block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } if (BB_VINFO_DATAREFS (bb_vinfo).length () < 2) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: not enough data-refs in " "basic block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } if (!vect_analyze_data_ref_accesses (NULL, bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: unhandled data access in " "basic block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } vect_pattern_recog (NULL, bb_vinfo); if (!vect_slp_analyze_data_ref_dependences (bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: unhandled data dependence " "in basic block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } if (!vect_analyze_data_refs_alignment (NULL, bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: bad data alignment in basic " "block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } /* Check the SLP opportunities in the basic block, analyze and build SLP trees. */ if (!vect_analyze_slp (NULL, bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: failed to find SLP opportunities " "in basic block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } slp_instances = BB_VINFO_SLP_INSTANCES (bb_vinfo); /* Mark all the statements that we want to vectorize as pure SLP and relevant. */ FOR_EACH_VEC_ELT (slp_instances, i, instance) { vect_mark_slp_stmts (SLP_INSTANCE_TREE (instance), pure_slp, -1); vect_mark_slp_stmts_relevant (SLP_INSTANCE_TREE (instance)); } if (!vect_verify_datarefs_alignment (NULL, bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: unsupported alignment in basic " "block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } if (!vect_slp_analyze_operations (bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: bad operation in basic block.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } /* Cost model: check if the vectorization is worthwhile. */ if (!unlimited_cost_model () && !vect_bb_vectorization_profitable_p (bb_vinfo)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: vectorization is not " "profitable.\n"); destroy_bb_vec_info (bb_vinfo); return NULL; } if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "Basic block will be vectorized using SLP\n"); return bb_vinfo; } bb_vec_info vect_slp_analyze_bb (basic_block bb) { bb_vec_info bb_vinfo; int insns = 0; gimple_stmt_iterator gsi; unsigned int vector_sizes; if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "===vect_slp_analyze_bb===\n"); for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi)) { gimple stmt = gsi_stmt (gsi); if (!is_gimple_debug (stmt) && !gimple_nop_p (stmt) && gimple_code (stmt) != GIMPLE_LABEL) insns++; } if (insns > PARAM_VALUE (PARAM_SLP_MAX_INSNS_IN_BB)) { if (dump_enabled_p ()) dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "not vectorized: too many instructions in " "basic block.\n"); return NULL; } /* Autodetect first vector size we try. */ current_vector_size = 0; vector_sizes = targetm.vectorize.autovectorize_vector_sizes (); while (1) { bb_vinfo = vect_slp_analyze_bb_1 (bb); if (bb_vinfo) return bb_vinfo; destroy_bb_vec_info (bb_vinfo); vector_sizes &= ~current_vector_size; if (vector_sizes == 0 || current_vector_size == 0) return NULL; /* Try the next biggest vector size. */ current_vector_size = 1 << floor_log2 (vector_sizes); if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "***** Re-trying analysis with " "vector size %d\n", current_vector_size); } } /* SLP costs are calculated according to SLP instance unrolling factor (i.e., the number of created vector stmts depends on the unrolling factor). However, the actual number of vector stmts for every SLP node depends on VF which is set later in vect_analyze_operations (). Hence, SLP costs should be updated. In this function we assume that the inside costs calculated in vect_model_xxx_cost are linear in ncopies. */ void vect_update_slp_costs_according_to_vf (loop_vec_info loop_vinfo) { unsigned int i, j, vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo); vec slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo); slp_instance instance; stmt_vector_for_cost body_cost_vec; stmt_info_for_cost *si; void *data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo); if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "=== vect_update_slp_costs_according_to_vf ===\n"); FOR_EACH_VEC_ELT (slp_instances, i, instance) { /* We assume that costs are linear in ncopies. */ int ncopies = vf / SLP_INSTANCE_UNROLLING_FACTOR (instance); /* Record the instance's instructions in the target cost model. This was delayed until here because the count of instructions isn't known beforehand. */ body_cost_vec = SLP_INSTANCE_BODY_COST_VEC (instance); FOR_EACH_VEC_ELT (body_cost_vec, j, si) (void) add_stmt_cost (data, si->count * ncopies, si->kind, vinfo_for_stmt (si->stmt), si->misalign, vect_body); } } /* For constant and loop invariant defs of SLP_NODE this function returns (vector) defs (VEC_OPRNDS) that will be used in the vectorized stmts. OP_NUM determines if we gather defs for operand 0 or operand 1 of the RHS of scalar stmts. NUMBER_OF_VECTORS is the number of vector defs to create. REDUC_INDEX is the index of the reduction operand in the statements, unless it is -1. */ static void vect_get_constant_vectors (tree op, slp_tree slp_node, vec *vec_oprnds, unsigned int op_num, unsigned int number_of_vectors, int reduc_index) { vec stmts = SLP_TREE_SCALAR_STMTS (slp_node); gimple stmt = stmts[0]; stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt); unsigned nunits; tree vec_cst; tree *elts; unsigned j, number_of_places_left_in_vector; tree vector_type; tree vop; int group_size = stmts.length (); unsigned int vec_num, i; unsigned number_of_copies = 1; vec voprnds; voprnds.create (number_of_vectors); bool constant_p, is_store; tree neutral_op = NULL; enum tree_code code = gimple_expr_code (stmt); gimple def_stmt; struct loop *loop; gimple_seq ctor_seq = NULL; if (STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_reduction_def && reduc_index != -1) { op_num = reduc_index - 1; op = gimple_op (stmt, reduc_index); /* For additional copies (see the explanation of NUMBER_OF_COPIES below) we need either neutral operands or the original operands. See get_initial_def_for_reduction() for details. */ switch (code) { case WIDEN_SUM_EXPR: case DOT_PROD_EXPR: case PLUS_EXPR: case MINUS_EXPR: case BIT_IOR_EXPR: case BIT_XOR_EXPR: if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (op))) neutral_op = build_real (TREE_TYPE (op), dconst0); else neutral_op = build_int_cst (TREE_TYPE (op), 0); break; case MULT_EXPR: if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (op))) neutral_op = build_real (TREE_TYPE (op), dconst1); else neutral_op = build_int_cst (TREE_TYPE (op), 1); break; case BIT_AND_EXPR: neutral_op = build_int_cst (TREE_TYPE (op), -1); break; case MAX_EXPR: case MIN_EXPR: def_stmt = SSA_NAME_DEF_STMT (op); loop = (gimple_bb (stmt))->loop_father; neutral_op = PHI_ARG_DEF_FROM_EDGE (def_stmt, loop_preheader_edge (loop)); break; default: neutral_op = NULL; } } if (STMT_VINFO_DATA_REF (stmt_vinfo)) { is_store = true; op = gimple_assign_rhs1 (stmt); } else is_store = false; gcc_assert (op); if (CONSTANT_CLASS_P (op)) constant_p = true; else constant_p = false; vector_type = get_vectype_for_scalar_type (TREE_TYPE (op)); gcc_assert (vector_type); nunits = TYPE_VECTOR_SUBPARTS (vector_type); /* NUMBER_OF_COPIES is the number of times we need to use the same values in created vectors. It is greater than 1 if unrolling is performed. For example, we have two scalar operands, s1 and s2 (e.g., group of strided accesses of size two), while NUNITS is four (i.e., four scalars of this type can be packed in a vector). The output vector will contain two copies of each scalar operand: {s1, s2, s1, s2}. (NUMBER_OF_COPIES will be 2). If GROUP_SIZE > NUNITS, the scalars will be split into several vectors containing the operands. For example, NUNITS is four as before, and the group size is 8 (s1, s2, ..., s8). We will create two vectors {s1, s2, s3, s4} and {s5, s6, s7, s8}. */ number_of_copies = least_common_multiple (nunits, group_size) / group_size; number_of_places_left_in_vector = nunits; elts = XALLOCAVEC (tree, nunits); for (j = 0; j < number_of_copies; j++) { for (i = group_size - 1; stmts.iterate (i, &stmt); i--) { if (is_store) op = gimple_assign_rhs1 (stmt); else { switch (code) { case COND_EXPR: if (op_num == 0 || op_num == 1) { tree cond = gimple_assign_rhs1 (stmt); op = TREE_OPERAND (cond, op_num); } else { if (op_num == 2) op = gimple_assign_rhs2 (stmt); else op = gimple_assign_rhs3 (stmt); } break; case CALL_EXPR: op = gimple_call_arg (stmt, op_num); break; case LSHIFT_EXPR: case RSHIFT_EXPR: case LROTATE_EXPR: case RROTATE_EXPR: op = gimple_op (stmt, op_num + 1); /* Unlike the other binary operators, shifts/rotates have the shift count being int, instead of the same type as the lhs, so make sure the scalar is the right type if we are dealing with vectors of long long/long/short/char. */ if (op_num == 1 && TREE_CODE (op) == INTEGER_CST) op = fold_convert (TREE_TYPE (vector_type), op); break; default: op = gimple_op (stmt, op_num + 1); break; } } if (reduc_index != -1) { loop = (gimple_bb (stmt))->loop_father; def_stmt = SSA_NAME_DEF_STMT (op); gcc_assert (loop); /* Get the def before the loop. In reduction chain we have only one initial value. */ if ((j != (number_of_copies - 1) || (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)) && i != 0)) && neutral_op) op = neutral_op; else op = PHI_ARG_DEF_FROM_EDGE (def_stmt, loop_preheader_edge (loop)); } /* Create 'vect_ = {op0,op1,...,opn}'. */ number_of_places_left_in_vector--; if (!types_compatible_p (TREE_TYPE (vector_type), TREE_TYPE (op))) { if (CONSTANT_CLASS_P (op)) { op = fold_unary (VIEW_CONVERT_EXPR, TREE_TYPE (vector_type), op); gcc_assert (op && CONSTANT_CLASS_P (op)); } else { tree new_temp = make_ssa_name (TREE_TYPE (vector_type), NULL); gimple init_stmt; op = build1 (VIEW_CONVERT_EXPR, TREE_TYPE (vector_type), op); init_stmt = gimple_build_assign_with_ops (VIEW_CONVERT_EXPR, new_temp, op, NULL_TREE); gimple_seq_add_stmt (&ctor_seq, init_stmt); op = new_temp; } } elts[number_of_places_left_in_vector] = op; if (!CONSTANT_CLASS_P (op)) constant_p = false; if (number_of_places_left_in_vector == 0) { number_of_places_left_in_vector = nunits; if (constant_p) vec_cst = build_vector (vector_type, elts); else { vec *v; unsigned k; vec_alloc (v, nunits); for (k = 0; k < nunits; ++k) CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, elts[k]); vec_cst = build_constructor (vector_type, v); } voprnds.quick_push (vect_init_vector (stmt, vec_cst, vector_type, NULL)); if (ctor_seq != NULL) { gimple init_stmt = SSA_NAME_DEF_STMT (voprnds.last ()); gimple_stmt_iterator gsi = gsi_for_stmt (init_stmt); gsi_insert_seq_before_without_update (&gsi, ctor_seq, GSI_SAME_STMT); ctor_seq = NULL; } } } } /* Since the vectors are created in the reverse order, we should invert them. */ vec_num = voprnds.length (); for (j = vec_num; j != 0; j--) { vop = voprnds[j - 1]; vec_oprnds->quick_push (vop); } voprnds.release (); /* In case that VF is greater than the unrolling factor needed for the SLP group of stmts, NUMBER_OF_VECTORS to be created is greater than NUMBER_OF_SCALARS/NUNITS or NUNITS/NUMBER_OF_SCALARS, and hence we have to replicate the vectors. */ while (number_of_vectors > vec_oprnds->length ()) { tree neutral_vec = NULL; if (neutral_op) { if (!neutral_vec) neutral_vec = build_vector_from_val (vector_type, neutral_op); vec_oprnds->quick_push (neutral_vec); } else { for (i = 0; vec_oprnds->iterate (i, &vop) && i < vec_num; i++) vec_oprnds->quick_push (vop); } } } /* Get vectorized definitions from SLP_NODE that contains corresponding vectorized def-stmts. */ static void vect_get_slp_vect_defs (slp_tree slp_node, vec *vec_oprnds) { tree vec_oprnd; gimple vec_def_stmt; unsigned int i; gcc_assert (SLP_TREE_VEC_STMTS (slp_node).exists ()); FOR_EACH_VEC_ELT (SLP_TREE_VEC_STMTS (slp_node), i, vec_def_stmt) { gcc_assert (vec_def_stmt); vec_oprnd = gimple_get_lhs (vec_def_stmt); vec_oprnds->quick_push (vec_oprnd); } } /* Get vectorized definitions for SLP_NODE. If the scalar definitions are loop invariants or constants, collect them and call vect_get_constant_vectors() to create vector stmts. Otherwise, the def-stmts must be already vectorized and the vectorized stmts must be stored in the corresponding child of SLP_NODE, and we call vect_get_slp_vect_defs () to retrieve them. */ void vect_get_slp_defs (vec ops, slp_tree slp_node, vec > *vec_oprnds, int reduc_index) { gimple first_stmt; int number_of_vects = 0, i; unsigned int child_index = 0; HOST_WIDE_INT lhs_size_unit, rhs_size_unit; slp_tree child = NULL; vec vec_defs; tree oprnd; bool vectorized_defs; first_stmt = SLP_TREE_SCALAR_STMTS (slp_node)[0]; FOR_EACH_VEC_ELT (ops, i, oprnd) { /* For each operand we check if it has vectorized definitions in a child node or we need to create them (for invariants and constants). We check if the LHS of the first stmt of the next child matches OPRND. If it does, we found the correct child. Otherwise, we call vect_get_constant_vectors (), and not advance CHILD_INDEX in order to check this child node for the next operand. */ vectorized_defs = false; if (SLP_TREE_CHILDREN (slp_node).length () > child_index) { child = SLP_TREE_CHILDREN (slp_node)[child_index]; /* We have to check both pattern and original def, if available. */ gimple first_def = SLP_TREE_SCALAR_STMTS (child)[0]; gimple related = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (first_def)); if (operand_equal_p (oprnd, gimple_get_lhs (first_def), 0) || (related && operand_equal_p (oprnd, gimple_get_lhs (related), 0))) { /* The number of vector defs is determined by the number of vector statements in the node from which we get those statements. */ number_of_vects = SLP_TREE_NUMBER_OF_VEC_STMTS (child); vectorized_defs = true; child_index++; } } if (!vectorized_defs) { if (i == 0) { number_of_vects = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node); /* Number of vector stmts was calculated according to LHS in vect_schedule_slp_instance (), fix it by replacing LHS with RHS, if necessary. See vect_get_smallest_scalar_type () for details. */ vect_get_smallest_scalar_type (first_stmt, &lhs_size_unit, &rhs_size_unit); if (rhs_size_unit != lhs_size_unit) { number_of_vects *= rhs_size_unit; number_of_vects /= lhs_size_unit; } } } /* Allocate memory for vectorized defs. */ vec_defs = vNULL; vec_defs.create (number_of_vects); /* For reduction defs we call vect_get_constant_vectors (), since we are looking for initial loop invariant values. */ if (vectorized_defs && reduc_index == -1) /* The defs are already vectorized. */ vect_get_slp_vect_defs (child, &vec_defs); else /* Build vectors from scalar defs. */ vect_get_constant_vectors (oprnd, slp_node, &vec_defs, i, number_of_vects, reduc_index); vec_oprnds->quick_push (vec_defs); /* For reductions, we only need initial values. */ if (reduc_index != -1) return; } } /* Create NCOPIES permutation statements using the mask MASK_BYTES (by building a vector of type MASK_TYPE from it) and two input vectors placed in DR_CHAIN at FIRST_VEC_INDX and SECOND_VEC_INDX for the first copy and shifting by STRIDE elements of DR_CHAIN for every copy. (STRIDE is the number of vectorized stmts for NODE divided by the number of copies). VECT_STMTS_COUNTER specifies the index in the vectorized stmts of NODE, where the created stmts must be inserted. */ static inline void vect_create_mask_and_perm (gimple stmt, gimple next_scalar_stmt, tree mask, int first_vec_indx, int second_vec_indx, gimple_stmt_iterator *gsi, slp_tree node, tree vectype, vec dr_chain, int ncopies, int vect_stmts_counter) { tree perm_dest; gimple perm_stmt = NULL; stmt_vec_info next_stmt_info; int i, stride; tree first_vec, second_vec, data_ref; stride = SLP_TREE_NUMBER_OF_VEC_STMTS (node) / ncopies; /* Initialize the vect stmts of NODE to properly insert the generated stmts later. */ for (i = SLP_TREE_VEC_STMTS (node).length (); i < (int) SLP_TREE_NUMBER_OF_VEC_STMTS (node); i++) SLP_TREE_VEC_STMTS (node).quick_push (NULL); perm_dest = vect_create_destination_var (gimple_assign_lhs (stmt), vectype); for (i = 0; i < ncopies; i++) { first_vec = dr_chain[first_vec_indx]; second_vec = dr_chain[second_vec_indx]; /* Generate the permute statement. */ perm_stmt = gimple_build_assign_with_ops (VEC_PERM_EXPR, perm_dest, first_vec, second_vec, mask); data_ref = make_ssa_name (perm_dest, perm_stmt); gimple_set_lhs (perm_stmt, data_ref); vect_finish_stmt_generation (stmt, perm_stmt, gsi); /* Store the vector statement in NODE. */ SLP_TREE_VEC_STMTS (node)[stride * i + vect_stmts_counter] = perm_stmt; first_vec_indx += stride; second_vec_indx += stride; } /* Mark the scalar stmt as vectorized. */ next_stmt_info = vinfo_for_stmt (next_scalar_stmt); STMT_VINFO_VEC_STMT (next_stmt_info) = perm_stmt; } /* Given FIRST_MASK_ELEMENT - the mask element in element representation, return in CURRENT_MASK_ELEMENT its equivalent in target specific representation. Check that the mask is valid and return FALSE if not. Return TRUE in NEED_NEXT_VECTOR if the permutation requires to move to the next vector, i.e., the current first vector is not needed. */ static bool vect_get_mask_element (gimple stmt, int first_mask_element, int m, int mask_nunits, bool only_one_vec, int index, unsigned char *mask, int *current_mask_element, bool *need_next_vector, int *number_of_mask_fixes, bool *mask_fixed, bool *needs_first_vector) { int i; /* Convert to target specific representation. */ *current_mask_element = first_mask_element + m; /* Adjust the value in case it's a mask for second and third vectors. */ *current_mask_element -= mask_nunits * (*number_of_mask_fixes - 1); if (*current_mask_element < mask_nunits) *needs_first_vector = true; /* We have only one input vector to permute but the mask accesses values in the next vector as well. */ if (only_one_vec && *current_mask_element >= mask_nunits) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "permutation requires at least two vectors "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } /* The mask requires the next vector. */ if (*current_mask_element >= mask_nunits * 2) { if (*needs_first_vector || *mask_fixed) { /* We either need the first vector too or have already moved to the next vector. In both cases, this permutation needs three vectors. */ if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "permutation requires at " "least three vectors "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } /* We move to the next vector, dropping the first one and working with the second and the third - we need to adjust the values of the mask accordingly. */ *current_mask_element -= mask_nunits * *number_of_mask_fixes; for (i = 0; i < index; i++) mask[i] -= mask_nunits * *number_of_mask_fixes; (*number_of_mask_fixes)++; *mask_fixed = true; } *need_next_vector = *mask_fixed; /* This was the last element of this mask. Start a new one. */ if (index == mask_nunits - 1) { *number_of_mask_fixes = 1; *mask_fixed = false; *needs_first_vector = false; } return true; } /* Generate vector permute statements from a list of loads in DR_CHAIN. If ANALYZE_ONLY is TRUE, only check that it is possible to create valid permute statements for the SLP node NODE of the SLP instance SLP_NODE_INSTANCE. */ bool vect_transform_slp_perm_load (slp_tree node, vec dr_chain, gimple_stmt_iterator *gsi, int vf, slp_instance slp_node_instance, bool analyze_only) { gimple stmt = SLP_TREE_SCALAR_STMTS (node)[0]; stmt_vec_info stmt_info = vinfo_for_stmt (stmt); tree mask_element_type = NULL_TREE, mask_type; int i, j, k, nunits, vec_index = 0, scalar_index; tree vectype = STMT_VINFO_VECTYPE (stmt_info); gimple next_scalar_stmt; int group_size = SLP_INSTANCE_GROUP_SIZE (slp_node_instance); int first_mask_element; int index, unroll_factor, current_mask_element, ncopies; unsigned char *mask; bool only_one_vec = false, need_next_vector = false; int first_vec_index, second_vec_index, orig_vec_stmts_num, vect_stmts_counter; int number_of_mask_fixes = 1; bool mask_fixed = false; bool needs_first_vector = false; enum machine_mode mode; mode = TYPE_MODE (vectype); if (!can_vec_perm_p (mode, false, NULL)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "no vect permute for "); dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); } return false; } /* The generic VEC_PERM_EXPR code always uses an integral type of the same size as the vector element being permuted. */ mask_element_type = lang_hooks.types.type_for_mode (int_mode_for_mode (TYPE_MODE (TREE_TYPE (vectype))), 1); mask_type = get_vectype_for_scalar_type (mask_element_type); nunits = TYPE_VECTOR_SUBPARTS (vectype); mask = XALLOCAVEC (unsigned char, nunits); unroll_factor = SLP_INSTANCE_UNROLLING_FACTOR (slp_node_instance); /* The number of vector stmts to generate based only on SLP_NODE_INSTANCE unrolling factor. */ orig_vec_stmts_num = group_size * SLP_INSTANCE_UNROLLING_FACTOR (slp_node_instance) / nunits; if (orig_vec_stmts_num == 1) only_one_vec = true; /* Number of copies is determined by the final vectorization factor relatively to SLP_NODE_INSTANCE unrolling factor. */ ncopies = vf / SLP_INSTANCE_UNROLLING_FACTOR (slp_node_instance); if (!STMT_VINFO_GROUPED_ACCESS (stmt_info)) return false; /* Generate permutation masks for every NODE. Number of masks for each NODE is equal to GROUP_SIZE. E.g., we have a group of three nodes with three loads from the same location in each node, and the vector size is 4. I.e., we have a a0b0c0a1b1c1... sequence and we need to create the following vectors: for a's: a0a0a0a1 a1a1a2a2 a2a3a3a3 for b's: b0b0b0b1 b1b1b2b2 b2b3b3b3 ... The masks for a's should be: {0,0,0,3} {3,3,6,6} {6,9,9,9}. The last mask is illegal since we assume two operands for permute operation, and the mask element values can't be outside that range. Hence, the last mask must be converted into {2,5,5,5}. For the first two permutations we need the first and the second input vectors: {a0,b0,c0,a1} and {b1,c1,a2,b2}, and for the last permutation we need the second and the third vectors: {b1,c1,a2,b2} and {c2,a3,b3,c3}. */ { scalar_index = 0; index = 0; vect_stmts_counter = 0; vec_index = 0; first_vec_index = vec_index++; if (only_one_vec) second_vec_index = first_vec_index; else second_vec_index = vec_index++; for (j = 0; j < unroll_factor; j++) { for (k = 0; k < group_size; k++) { i = SLP_TREE_LOAD_PERMUTATION (node)[k]; first_mask_element = i + j * group_size; if (!vect_get_mask_element (stmt, first_mask_element, 0, nunits, only_one_vec, index, mask, ¤t_mask_element, &need_next_vector, &number_of_mask_fixes, &mask_fixed, &needs_first_vector)) return false; mask[index++] = current_mask_element; if (index == nunits) { index = 0; if (!can_vec_perm_p (mode, false, mask)) { if (dump_enabled_p ()) { dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, "unsupported vect permute { "); for (i = 0; i < nunits; ++i) dump_printf (MSG_MISSED_OPTIMIZATION, "%d ", mask[i]); dump_printf (MSG_MISSED_OPTIMIZATION, "}\n"); } return false; } if (!analyze_only) { int l; tree mask_vec, *mask_elts; mask_elts = XALLOCAVEC (tree, nunits); for (l = 0; l < nunits; ++l) mask_elts[l] = build_int_cst (mask_element_type, mask[l]); mask_vec = build_vector (mask_type, mask_elts); if (need_next_vector) { first_vec_index = second_vec_index; second_vec_index = vec_index; } next_scalar_stmt = SLP_TREE_SCALAR_STMTS (node)[scalar_index++]; vect_create_mask_and_perm (stmt, next_scalar_stmt, mask_vec, first_vec_index, second_vec_index, gsi, node, vectype, dr_chain, ncopies, vect_stmts_counter++); } } } } } return true; } /* Vectorize SLP instance tree in postorder. */ static bool vect_schedule_slp_instance (slp_tree node, slp_instance instance, unsigned int vectorization_factor) { gimple stmt; bool grouped_store, is_store; gimple_stmt_iterator si; stmt_vec_info stmt_info; unsigned int vec_stmts_size, nunits, group_size; tree vectype; int i; slp_tree child; if (!node) return false; FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_schedule_slp_instance (child, instance, vectorization_factor); stmt = SLP_TREE_SCALAR_STMTS (node)[0]; stmt_info = vinfo_for_stmt (stmt); /* VECTYPE is the type of the destination. */ vectype = STMT_VINFO_VECTYPE (stmt_info); nunits = (unsigned int) TYPE_VECTOR_SUBPARTS (vectype); group_size = SLP_INSTANCE_GROUP_SIZE (instance); /* For each SLP instance calculate number of vector stmts to be created for the scalar stmts in each node of the SLP tree. Number of vector elements in one vector iteration is the number of scalar elements in one scalar iteration (GROUP_SIZE) multiplied by VF divided by vector size. */ vec_stmts_size = (vectorization_factor * group_size) / nunits; if (!SLP_TREE_VEC_STMTS (node).exists ()) { SLP_TREE_VEC_STMTS (node).create (vec_stmts_size); SLP_TREE_NUMBER_OF_VEC_STMTS (node) = vec_stmts_size; } if (dump_enabled_p ()) { dump_printf_loc (MSG_NOTE,vect_location, "------>vectorizing SLP node starting from: "); dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0); dump_printf (MSG_NOTE, "\n"); } /* Loads should be inserted before the first load. */ if (SLP_INSTANCE_FIRST_LOAD_STMT (instance) && STMT_VINFO_GROUPED_ACCESS (stmt_info) && !REFERENCE_CLASS_P (gimple_get_lhs (stmt)) && SLP_TREE_LOAD_PERMUTATION (node).exists ()) si = gsi_for_stmt (SLP_INSTANCE_FIRST_LOAD_STMT (instance)); else if (is_pattern_stmt_p (stmt_info)) si = gsi_for_stmt (STMT_VINFO_RELATED_STMT (stmt_info)); else si = gsi_for_stmt (stmt); /* Stores should be inserted just before the last store. */ if (STMT_VINFO_GROUPED_ACCESS (stmt_info) && REFERENCE_CLASS_P (gimple_get_lhs (stmt))) { gimple last_store = vect_find_last_store_in_slp_instance (instance); if (is_pattern_stmt_p (vinfo_for_stmt (last_store))) last_store = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (last_store)); si = gsi_for_stmt (last_store); } /* Mark the first element of the reduction chain as reduction to properly transform the node. In the analysis phase only the last element of the chain is marked as reduction. */ if (GROUP_FIRST_ELEMENT (stmt_info) && !STMT_VINFO_GROUPED_ACCESS (stmt_info) && GROUP_FIRST_ELEMENT (stmt_info) == stmt) { STMT_VINFO_DEF_TYPE (stmt_info) = vect_reduction_def; STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type; } is_store = vect_transform_stmt (stmt, &si, &grouped_store, node, instance); return is_store; } /* Replace scalar calls from SLP node NODE with setting of their lhs to zero. For loop vectorization this is done in vectorizable_call, but for SLP it needs to be deferred until end of vect_schedule_slp, because multiple SLP instances may refer to the same scalar stmt. */ static void vect_remove_slp_scalar_calls (slp_tree node) { gimple stmt, new_stmt; gimple_stmt_iterator gsi; int i; slp_tree child; tree lhs; stmt_vec_info stmt_info; if (!node) return; FOR_EACH_VEC_ELT (SLP_TREE_CHILDREN (node), i, child) vect_remove_slp_scalar_calls (child); FOR_EACH_VEC_ELT (SLP_TREE_SCALAR_STMTS (node), i, stmt) { if (!is_gimple_call (stmt) || gimple_bb (stmt) == NULL) continue; stmt_info = vinfo_for_stmt (stmt); if (stmt_info == NULL || is_pattern_stmt_p (stmt_info) || !PURE_SLP_STMT (stmt_info)) continue; lhs = gimple_call_lhs (stmt); new_stmt = gimple_build_assign (lhs, build_zero_cst (TREE_TYPE (lhs))); set_vinfo_for_stmt (new_stmt, stmt_info); set_vinfo_for_stmt (stmt, NULL); STMT_VINFO_STMT (stmt_info) = new_stmt; gsi = gsi_for_stmt (stmt); gsi_replace (&gsi, new_stmt, false); SSA_NAME_DEF_STMT (gimple_assign_lhs (new_stmt)) = new_stmt; } } /* Generate vector code for all SLP instances in the loop/basic block. */ bool vect_schedule_slp (loop_vec_info loop_vinfo, bb_vec_info bb_vinfo) { vec slp_instances; slp_instance instance; unsigned int i, vf; bool is_store = false; if (loop_vinfo) { slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo); vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo); } else { slp_instances = BB_VINFO_SLP_INSTANCES (bb_vinfo); vf = 1; } FOR_EACH_VEC_ELT (slp_instances, i, instance) { /* Schedule the tree of INSTANCE. */ is_store = vect_schedule_slp_instance (SLP_INSTANCE_TREE (instance), instance, vf); if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "vectorizing stmts using SLP.\n"); } FOR_EACH_VEC_ELT (slp_instances, i, instance) { slp_tree root = SLP_INSTANCE_TREE (instance); gimple store; unsigned int j; gimple_stmt_iterator gsi; /* Remove scalar call stmts. Do not do this for basic-block vectorization as not all uses may be vectorized. ??? Why should this be necessary? DCE should be able to remove the stmts itself. ??? For BB vectorization we can as well remove scalar stmts starting from the SLP tree root if they have no uses. */ if (loop_vinfo) vect_remove_slp_scalar_calls (root); for (j = 0; SLP_TREE_SCALAR_STMTS (root).iterate (j, &store) && j < SLP_INSTANCE_GROUP_SIZE (instance); j++) { if (!STMT_VINFO_DATA_REF (vinfo_for_stmt (store))) break; if (is_pattern_stmt_p (vinfo_for_stmt (store))) store = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (store)); /* Free the attached stmt_vec_info and remove the stmt. */ gsi = gsi_for_stmt (store); unlink_stmt_vdef (store); gsi_remove (&gsi, true); release_defs (store); free_stmt_vec_info (store); } } return is_store; } /* Vectorize the basic block. */ void vect_slp_transform_bb (basic_block bb) { bb_vec_info bb_vinfo = vec_info_for_bb (bb); gimple_stmt_iterator si; gcc_assert (bb_vinfo); if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "SLPing BB\n"); for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si)) { gimple stmt = gsi_stmt (si); stmt_vec_info stmt_info; if (dump_enabled_p ()) { dump_printf_loc (MSG_NOTE, vect_location, "------>SLPing statement: "); dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0); dump_printf (MSG_NOTE, "\n"); } stmt_info = vinfo_for_stmt (stmt); gcc_assert (stmt_info); /* Schedule all the SLP instances when the first SLP stmt is reached. */ if (STMT_SLP_TYPE (stmt_info)) { vect_schedule_slp (NULL, bb_vinfo); break; } } if (dump_enabled_p ()) dump_printf_loc (MSG_NOTE, vect_location, "BASIC BLOCK VECTORIZED\n"); destroy_bb_vec_info (bb_vinfo); }