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Diffstat (limited to 'gcc-4.9/gcc/tree-vect-loop.c')
-rw-r--r-- | gcc-4.9/gcc/tree-vect-loop.c | 6123 |
1 files changed, 6123 insertions, 0 deletions
diff --git a/gcc-4.9/gcc/tree-vect-loop.c b/gcc-4.9/gcc/tree-vect-loop.c new file mode 100644 index 000000000..df6ab6fcb --- /dev/null +++ b/gcc-4.9/gcc/tree-vect-loop.c @@ -0,0 +1,6123 @@ +/* Loop Vectorization + Copyright (C) 2003-2014 Free Software Foundation, Inc. + Contributed by Dorit Naishlos <dorit@il.ibm.com> and + Ira Rosen <irar@il.ibm.com> + +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/>. */ + +#include "config.h" +#include "system.h" +#include "coretypes.h" +#include "dumpfile.h" +#include "tm.h" +#include "tree.h" +#include "stor-layout.h" +#include "basic-block.h" +#include "gimple-pretty-print.h" +#include "tree-ssa-alias.h" +#include "internal-fn.h" +#include "gimple-expr.h" +#include "is-a.h" +#include "gimple.h" +#include "gimplify.h" +#include "gimple-iterator.h" +#include "gimplify-me.h" +#include "gimple-ssa.h" +#include "tree-phinodes.h" +#include "ssa-iterators.h" +#include "stringpool.h" +#include "tree-ssanames.h" +#include "tree-ssa-loop-ivopts.h" +#include "tree-ssa-loop-manip.h" +#include "tree-ssa-loop-niter.h" +#include "tree-pass.h" +#include "cfgloop.h" +#include "expr.h" +#include "recog.h" +#include "optabs.h" +#include "params.h" +#include "diagnostic-core.h" +#include "tree-chrec.h" +#include "tree-scalar-evolution.h" +#include "tree-vectorizer.h" +#include "target.h" + +/* Loop Vectorization Pass. + + This pass tries to vectorize loops. + + For example, the vectorizer transforms the following simple loop: + + short a[N]; short b[N]; short c[N]; int i; + + for (i=0; i<N; i++){ + a[i] = b[i] + c[i]; + } + + as if it was manually vectorized by rewriting the source code into: + + typedef int __attribute__((mode(V8HI))) v8hi; + short a[N]; short b[N]; short c[N]; int i; + v8hi *pa = (v8hi*)a, *pb = (v8hi*)b, *pc = (v8hi*)c; + v8hi va, vb, vc; + + for (i=0; i<N/8; i++){ + vb = pb[i]; + vc = pc[i]; + va = vb + vc; + pa[i] = va; + } + + The main entry to this pass is vectorize_loops(), in which + the vectorizer applies a set of analyses on a given set of loops, + followed by the actual vectorization transformation for the loops that + had successfully passed the analysis phase. + Throughout this pass we make a distinction between two types of + data: scalars (which are represented by SSA_NAMES), and memory references + ("data-refs"). These two types of data require different handling both + during analysis and transformation. The types of data-refs that the + vectorizer currently supports are ARRAY_REFS which base is an array DECL + (not a pointer), and INDIRECT_REFS through pointers; both array and pointer + accesses are required to have a simple (consecutive) access pattern. + + Analysis phase: + =============== + The driver for the analysis phase is vect_analyze_loop(). + It applies a set of analyses, some of which rely on the scalar evolution + analyzer (scev) developed by Sebastian Pop. + + During the analysis phase the vectorizer records some information + per stmt in a "stmt_vec_info" struct which is attached to each stmt in the + loop, as well as general information about the loop as a whole, which is + recorded in a "loop_vec_info" struct attached to each loop. + + Transformation phase: + ===================== + The loop transformation phase scans all the stmts in the loop, and + creates a vector stmt (or a sequence of stmts) for each scalar stmt S in + the loop that needs to be vectorized. It inserts the vector code sequence + just before the scalar stmt S, and records a pointer to the vector code + in STMT_VINFO_VEC_STMT (stmt_info) (stmt_info is the stmt_vec_info struct + attached to S). This pointer will be used for the vectorization of following + stmts which use the def of stmt S. Stmt S is removed if it writes to memory; + otherwise, we rely on dead code elimination for removing it. + + For example, say stmt S1 was vectorized into stmt VS1: + + VS1: vb = px[i]; + S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1 + S2: a = b; + + To vectorize stmt S2, the vectorizer first finds the stmt that defines + the operand 'b' (S1), and gets the relevant vector def 'vb' from the + vector stmt VS1 pointed to by STMT_VINFO_VEC_STMT (stmt_info (S1)). The + resulting sequence would be: + + VS1: vb = px[i]; + S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1 + VS2: va = vb; + S2: a = b; STMT_VINFO_VEC_STMT (stmt_info (S2)) = VS2 + + Operands that are not SSA_NAMEs, are data-refs that appear in + load/store operations (like 'x[i]' in S1), and are handled differently. + + Target modeling: + ================= + Currently the only target specific information that is used is the + size of the vector (in bytes) - "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD". + Targets that can support different sizes of vectors, for now will need + to specify one value for "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD". More + flexibility will be added in the future. + + Since we only vectorize operations which vector form can be + expressed using existing tree codes, to verify that an operation is + supported, the vectorizer checks the relevant optab at the relevant + machine_mode (e.g, optab_handler (add_optab, V8HImode)). If + the value found is CODE_FOR_nothing, then there's no target support, and + we can't vectorize the stmt. + + For additional information on this project see: + http://gcc.gnu.org/projects/tree-ssa/vectorization.html +*/ + +static void vect_estimate_min_profitable_iters (loop_vec_info, int *, int *); + +/* Function vect_determine_vectorization_factor + + Determine the vectorization factor (VF). VF is the number of data elements + that are operated upon in parallel in a single iteration of the vectorized + loop. For example, when vectorizing a loop that operates on 4byte elements, + on a target with vector size (VS) 16byte, the VF is set to 4, since 4 + elements can fit in a single vector register. + + We currently support vectorization of loops in which all types operated upon + are of the same size. Therefore this function currently sets VF according to + the size of the types operated upon, and fails if there are multiple sizes + in the loop. + + VF is also the factor by which the loop iterations are strip-mined, e.g.: + original loop: + for (i=0; i<N; i++){ + a[i] = b[i] + c[i]; + } + + vectorized loop: + for (i=0; i<N; i+=VF){ + a[i:VF] = b[i:VF] + c[i:VF]; + } +*/ + +static bool +vect_determine_vectorization_factor (loop_vec_info loop_vinfo) +{ + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo); + int nbbs = loop->num_nodes; + gimple_stmt_iterator si; + unsigned int vectorization_factor = 0; + tree scalar_type; + gimple phi; + tree vectype; + unsigned int nunits; + stmt_vec_info stmt_info; + int i; + HOST_WIDE_INT dummy; + gimple stmt, pattern_stmt = NULL; + gimple_seq pattern_def_seq = NULL; + gimple_stmt_iterator pattern_def_si = gsi_none (); + bool analyze_pattern_stmt = false; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== vect_determine_vectorization_factor ===\n"); + + for (i = 0; i < nbbs; i++) + { + basic_block bb = bbs[i]; + + for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si)) + { + phi = gsi_stmt (si); + stmt_info = vinfo_for_stmt (phi); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "==> examining phi: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0); + dump_printf (MSG_NOTE, "\n"); + } + + gcc_assert (stmt_info); + + if (STMT_VINFO_RELEVANT_P (stmt_info)) + { + gcc_assert (!STMT_VINFO_VECTYPE (stmt_info)); + scalar_type = TREE_TYPE (PHI_RESULT (phi)); + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "get vectype for scalar type: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type); + dump_printf (MSG_NOTE, "\n"); + } + + vectype = get_vectype_for_scalar_type (scalar_type); + if (!vectype) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: unsupported " + "data-type "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, + scalar_type); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + STMT_VINFO_VECTYPE (stmt_info) = vectype; + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "vectype: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, vectype); + dump_printf (MSG_NOTE, "\n"); + } + + nunits = TYPE_VECTOR_SUBPARTS (vectype); + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "nunits = %d\n", + nunits); + + if (!vectorization_factor + || (nunits > vectorization_factor)) + vectorization_factor = nunits; + } + } + + for (si = gsi_start_bb (bb); !gsi_end_p (si) || analyze_pattern_stmt;) + { + tree vf_vectype; + + if (analyze_pattern_stmt) + stmt = pattern_stmt; + else + stmt = gsi_stmt (si); + + stmt_info = vinfo_for_stmt (stmt); + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "==> examining statement: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + + gcc_assert (stmt_info); + + /* Skip stmts which do not need to be vectorized. */ + if ((!STMT_VINFO_RELEVANT_P (stmt_info) + && !STMT_VINFO_LIVE_P (stmt_info)) + || gimple_clobber_p (stmt)) + { + if (STMT_VINFO_IN_PATTERN_P (stmt_info) + && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info)) + && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt)) + || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt)))) + { + stmt = pattern_stmt; + stmt_info = vinfo_for_stmt (pattern_stmt); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "==> examining pattern statement: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + } + else + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "skip.\n"); + gsi_next (&si); + continue; + } + } + else if (STMT_VINFO_IN_PATTERN_P (stmt_info) + && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info)) + && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt)) + || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt)))) + analyze_pattern_stmt = true; + + /* If a pattern statement has def stmts, analyze them too. */ + if (is_pattern_stmt_p (stmt_info)) + { + if (pattern_def_seq == NULL) + { + pattern_def_seq = STMT_VINFO_PATTERN_DEF_SEQ (stmt_info); + pattern_def_si = gsi_start (pattern_def_seq); + } + else if (!gsi_end_p (pattern_def_si)) + gsi_next (&pattern_def_si); + if (pattern_def_seq != NULL) + { + gimple pattern_def_stmt = NULL; + stmt_vec_info pattern_def_stmt_info = NULL; + + while (!gsi_end_p (pattern_def_si)) + { + pattern_def_stmt = gsi_stmt (pattern_def_si); + pattern_def_stmt_info + = vinfo_for_stmt (pattern_def_stmt); + if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info) + || STMT_VINFO_LIVE_P (pattern_def_stmt_info)) + break; + gsi_next (&pattern_def_si); + } + + if (!gsi_end_p (pattern_def_si)) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "==> examining pattern def stmt: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, + pattern_def_stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + + stmt = pattern_def_stmt; + stmt_info = pattern_def_stmt_info; + } + else + { + pattern_def_si = gsi_none (); + analyze_pattern_stmt = false; + } + } + else + analyze_pattern_stmt = false; + } + + if (gimple_get_lhs (stmt) == NULL_TREE + /* MASK_STORE has no lhs, but is ok. */ + && (!is_gimple_call (stmt) + || !gimple_call_internal_p (stmt) + || gimple_call_internal_fn (stmt) != IFN_MASK_STORE)) + { + if (is_gimple_call (stmt)) + { + /* Ignore calls with no lhs. These must be calls to + #pragma omp simd functions, and what vectorization factor + it really needs can't be determined until + vectorizable_simd_clone_call. */ + if (!analyze_pattern_stmt && gsi_end_p (pattern_def_si)) + { + pattern_def_seq = NULL; + gsi_next (&si); + } + continue; + } + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: irregular stmt."); + dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, + 0); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + + if (VECTOR_MODE_P (TYPE_MODE (gimple_expr_type (stmt)))) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: vector stmt in loop:"); + dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + + if (STMT_VINFO_VECTYPE (stmt_info)) + { + /* The only case when a vectype had been already set is for stmts + that contain a dataref, or for "pattern-stmts" (stmts + generated by the vectorizer to represent/replace a certain + idiom). */ + gcc_assert (STMT_VINFO_DATA_REF (stmt_info) + || is_pattern_stmt_p (stmt_info) + || !gsi_end_p (pattern_def_si)); + vectype = STMT_VINFO_VECTYPE (stmt_info); + } + else + { + gcc_assert (!STMT_VINFO_DATA_REF (stmt_info)); + if (is_gimple_call (stmt) + && gimple_call_internal_p (stmt) + && gimple_call_internal_fn (stmt) == IFN_MASK_STORE) + scalar_type = TREE_TYPE (gimple_call_arg (stmt, 3)); + else + scalar_type = TREE_TYPE (gimple_get_lhs (stmt)); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "get vectype for scalar type: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type); + dump_printf (MSG_NOTE, "\n"); + } + vectype = get_vectype_for_scalar_type (scalar_type); + if (!vectype) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: unsupported " + "data-type "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, + scalar_type); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + + STMT_VINFO_VECTYPE (stmt_info) = vectype; + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "vectype: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, vectype); + dump_printf (MSG_NOTE, "\n"); + } + } + + /* The vectorization factor is according to the smallest + scalar type (or the largest vector size, but we only + support one vector size per loop). */ + scalar_type = vect_get_smallest_scalar_type (stmt, &dummy, + &dummy); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "get vectype for scalar type: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type); + dump_printf (MSG_NOTE, "\n"); + } + vf_vectype = get_vectype_for_scalar_type (scalar_type); + if (!vf_vectype) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: unsupported data-type "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, + scalar_type); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + + if ((GET_MODE_SIZE (TYPE_MODE (vectype)) + != GET_MODE_SIZE (TYPE_MODE (vf_vectype)))) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: different sized vector " + "types in statement, "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, + vectype); + dump_printf (MSG_MISSED_OPTIMIZATION, " and "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, + vf_vectype); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "vectype: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, vf_vectype); + dump_printf (MSG_NOTE, "\n"); + } + + nunits = TYPE_VECTOR_SUBPARTS (vf_vectype); + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "nunits = %d\n", nunits); + if (!vectorization_factor + || (nunits > vectorization_factor)) + vectorization_factor = nunits; + + if (!analyze_pattern_stmt && gsi_end_p (pattern_def_si)) + { + pattern_def_seq = NULL; + gsi_next (&si); + } + } + } + + /* TODO: Analyze cost. Decide if worth while to vectorize. */ + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "vectorization factor = %d\n", + vectorization_factor); + if (vectorization_factor <= 1) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: unsupported data-type\n"); + return false; + } + LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor; + + return true; +} + + +/* Function vect_is_simple_iv_evolution. + + FORNOW: A simple evolution of an induction variables in the loop is + considered a polynomial evolution. */ + +static bool +vect_is_simple_iv_evolution (unsigned loop_nb, tree access_fn, tree * init, + tree * step) +{ + tree init_expr; + tree step_expr; + tree evolution_part = evolution_part_in_loop_num (access_fn, loop_nb); + basic_block bb; + + /* When there is no evolution in this loop, the evolution function + is not "simple". */ + if (evolution_part == NULL_TREE) + return false; + + /* When the evolution is a polynomial of degree >= 2 + the evolution function is not "simple". */ + if (tree_is_chrec (evolution_part)) + return false; + + step_expr = evolution_part; + init_expr = unshare_expr (initial_condition_in_loop_num (access_fn, loop_nb)); + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "step: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, step_expr); + dump_printf (MSG_NOTE, ", init: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, init_expr); + dump_printf (MSG_NOTE, "\n"); + } + + *init = init_expr; + *step = step_expr; + + if (TREE_CODE (step_expr) != INTEGER_CST + && (TREE_CODE (step_expr) != SSA_NAME + || ((bb = gimple_bb (SSA_NAME_DEF_STMT (step_expr))) + && flow_bb_inside_loop_p (get_loop (cfun, loop_nb), bb)) + || (!INTEGRAL_TYPE_P (TREE_TYPE (step_expr)) + && (!SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr)) + || !flag_associative_math))) + && (TREE_CODE (step_expr) != REAL_CST + || !flag_associative_math)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "step unknown.\n"); + return false; + } + + return true; +} + +/* Function vect_analyze_scalar_cycles_1. + + Examine the cross iteration def-use cycles of scalar variables + in LOOP. LOOP_VINFO represents the loop that is now being + considered for vectorization (can be LOOP, or an outer-loop + enclosing LOOP). */ + +static void +vect_analyze_scalar_cycles_1 (loop_vec_info loop_vinfo, struct loop *loop) +{ + basic_block bb = loop->header; + tree init, step; + auto_vec<gimple, 64> worklist; + gimple_stmt_iterator gsi; + bool double_reduc; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== vect_analyze_scalar_cycles ===\n"); + + /* First - identify all inductions. Reduction detection assumes that all the + inductions have been identified, therefore, this order must not be + changed. */ + for (gsi = gsi_start_phis (bb); !gsi_end_p (gsi); gsi_next (&gsi)) + { + gimple phi = gsi_stmt (gsi); + tree access_fn = NULL; + tree def = PHI_RESULT (phi); + stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi); + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "Analyze phi: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0); + dump_printf (MSG_NOTE, "\n"); + } + + /* Skip virtual phi's. The data dependences that are associated with + virtual defs/uses (i.e., memory accesses) are analyzed elsewhere. */ + if (virtual_operand_p (def)) + continue; + + STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_unknown_def_type; + + /* Analyze the evolution function. */ + access_fn = analyze_scalar_evolution (loop, def); + if (access_fn) + { + STRIP_NOPS (access_fn); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "Access function of PHI: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, access_fn); + dump_printf (MSG_NOTE, "\n"); + } + STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo) + = evolution_part_in_loop_num (access_fn, loop->num); + } + + if (!access_fn + || !vect_is_simple_iv_evolution (loop->num, access_fn, &init, &step) + || (LOOP_VINFO_LOOP (loop_vinfo) != loop + && TREE_CODE (step) != INTEGER_CST)) + { + worklist.safe_push (phi); + continue; + } + + gcc_assert (STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo) != NULL_TREE); + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "Detected induction.\n"); + STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_induction_def; + } + + + /* Second - identify all reductions and nested cycles. */ + while (worklist.length () > 0) + { + gimple phi = worklist.pop (); + tree def = PHI_RESULT (phi); + stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi); + gimple reduc_stmt; + bool nested_cycle; + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "Analyze phi: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0); + dump_printf (MSG_NOTE, "\n"); + } + + gcc_assert (!virtual_operand_p (def) + && STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_unknown_def_type); + + nested_cycle = (loop != LOOP_VINFO_LOOP (loop_vinfo)); + reduc_stmt = vect_force_simple_reduction (loop_vinfo, phi, !nested_cycle, + &double_reduc); + if (reduc_stmt) + { + if (double_reduc) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Detected double reduction.\n"); + + STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_double_reduction_def; + STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) = + vect_double_reduction_def; + } + else + { + if (nested_cycle) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Detected vectorizable nested cycle.\n"); + + STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_nested_cycle; + STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) = + vect_nested_cycle; + } + else + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Detected reduction.\n"); + + STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_reduction_def; + STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) = + vect_reduction_def; + /* Store the reduction cycles for possible vectorization in + loop-aware SLP. */ + LOOP_VINFO_REDUCTIONS (loop_vinfo).safe_push (reduc_stmt); + } + } + } + else + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "Unknown def-use cycle pattern.\n"); + } +} + + +/* Function vect_analyze_scalar_cycles. + + Examine the cross iteration def-use cycles of scalar variables, by + analyzing the loop-header PHIs of scalar variables. Classify each + cycle as one of the following: invariant, induction, reduction, unknown. + We do that for the loop represented by LOOP_VINFO, and also to its + inner-loop, if exists. + Examples for scalar cycles: + + Example1: reduction: + + loop1: + for (i=0; i<N; i++) + sum += a[i]; + + Example2: induction: + + loop2: + for (i=0; i<N; i++) + a[i] = i; */ + +static void +vect_analyze_scalar_cycles (loop_vec_info loop_vinfo) +{ + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + + vect_analyze_scalar_cycles_1 (loop_vinfo, loop); + + /* When vectorizing an outer-loop, the inner-loop is executed sequentially. + Reductions in such inner-loop therefore have different properties than + the reductions in the nest that gets vectorized: + 1. When vectorized, they are executed in the same order as in the original + scalar loop, so we can't change the order of computation when + vectorizing them. + 2. FIXME: Inner-loop reductions can be used in the inner-loop, so the + current checks are too strict. */ + + if (loop->inner) + vect_analyze_scalar_cycles_1 (loop_vinfo, loop->inner); +} + + +/* Function vect_get_loop_niters. + + Determine how many iterations the loop is executed and place it + in NUMBER_OF_ITERATIONS. Place the number of latch iterations + in NUMBER_OF_ITERATIONSM1. + + Return the loop exit condition. */ + +static gimple +vect_get_loop_niters (struct loop *loop, tree *number_of_iterations, + tree *number_of_iterationsm1) +{ + tree niters; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== get_loop_niters ===\n"); + + niters = number_of_latch_executions (loop); + *number_of_iterationsm1 = niters; + + /* We want the number of loop header executions which is the number + of latch executions plus one. + ??? For UINT_MAX latch executions this number overflows to zero + for loops like do { n++; } while (n != 0); */ + if (niters && !chrec_contains_undetermined (niters)) + niters = fold_build2 (PLUS_EXPR, TREE_TYPE (niters), unshare_expr (niters), + build_int_cst (TREE_TYPE (niters), 1)); + *number_of_iterations = niters; + + return get_loop_exit_condition (loop); +} + + +/* Function bb_in_loop_p + + Used as predicate for dfs order traversal of the loop bbs. */ + +static bool +bb_in_loop_p (const_basic_block bb, const void *data) +{ + const struct loop *const loop = (const struct loop *)data; + if (flow_bb_inside_loop_p (loop, bb)) + return true; + return false; +} + + +/* Function new_loop_vec_info. + + Create and initialize a new loop_vec_info struct for LOOP, as well as + stmt_vec_info structs for all the stmts in LOOP. */ + +static loop_vec_info +new_loop_vec_info (struct loop *loop) +{ + loop_vec_info res; + basic_block *bbs; + gimple_stmt_iterator si; + unsigned int i, nbbs; + + res = (loop_vec_info) xcalloc (1, sizeof (struct _loop_vec_info)); + LOOP_VINFO_LOOP (res) = loop; + + bbs = get_loop_body (loop); + + /* Create/Update stmt_info for all stmts in the loop. */ + for (i = 0; i < loop->num_nodes; i++) + { + basic_block bb = bbs[i]; + + /* BBs in a nested inner-loop will have been already processed (because + we will have called vect_analyze_loop_form for any nested inner-loop). + Therefore, for stmts in an inner-loop we just want to update the + STMT_VINFO_LOOP_VINFO field of their stmt_info to point to the new + loop_info of the outer-loop we are currently considering to vectorize + (instead of the loop_info of the inner-loop). + For stmts in other BBs we need to create a stmt_info from scratch. */ + if (bb->loop_father != loop) + { + /* Inner-loop bb. */ + gcc_assert (loop->inner && bb->loop_father == loop->inner); + for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si)) + { + gimple phi = gsi_stmt (si); + stmt_vec_info stmt_info = vinfo_for_stmt (phi); + loop_vec_info inner_loop_vinfo = + STMT_VINFO_LOOP_VINFO (stmt_info); + gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo)); + STMT_VINFO_LOOP_VINFO (stmt_info) = res; + } + 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); + loop_vec_info inner_loop_vinfo = + STMT_VINFO_LOOP_VINFO (stmt_info); + gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo)); + STMT_VINFO_LOOP_VINFO (stmt_info) = res; + } + } + else + { + /* bb in current nest. */ + for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si)) + { + gimple phi = gsi_stmt (si); + gimple_set_uid (phi, 0); + set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, res, NULL)); + } + + for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si)) + { + gimple stmt = gsi_stmt (si); + gimple_set_uid (stmt, 0); + set_vinfo_for_stmt (stmt, new_stmt_vec_info (stmt, res, NULL)); + } + } + } + + /* CHECKME: We want to visit all BBs before their successors (except for + latch blocks, for which this assertion wouldn't hold). In the simple + case of the loop forms we allow, a dfs order of the BBs would the same + as reversed postorder traversal, so we are safe. */ + + free (bbs); + bbs = XCNEWVEC (basic_block, loop->num_nodes); + nbbs = dfs_enumerate_from (loop->header, 0, bb_in_loop_p, + bbs, loop->num_nodes, loop); + gcc_assert (nbbs == loop->num_nodes); + + LOOP_VINFO_BBS (res) = bbs; + LOOP_VINFO_NITERSM1 (res) = NULL; + LOOP_VINFO_NITERS (res) = NULL; + LOOP_VINFO_NITERS_UNCHANGED (res) = NULL; + LOOP_VINFO_COST_MODEL_MIN_ITERS (res) = 0; + LOOP_VINFO_VECTORIZABLE_P (res) = 0; + LOOP_VINFO_PEELING_FOR_ALIGNMENT (res) = 0; + LOOP_VINFO_VECT_FACTOR (res) = 0; + LOOP_VINFO_LOOP_NEST (res).create (3); + LOOP_VINFO_DATAREFS (res).create (10); + LOOP_VINFO_DDRS (res).create (10 * 10); + LOOP_VINFO_UNALIGNED_DR (res) = NULL; + LOOP_VINFO_MAY_MISALIGN_STMTS (res).create ( + PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIGNMENT_CHECKS)); + LOOP_VINFO_MAY_ALIAS_DDRS (res).create ( + PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS)); + LOOP_VINFO_GROUPED_STORES (res).create (10); + LOOP_VINFO_REDUCTIONS (res).create (10); + LOOP_VINFO_REDUCTION_CHAINS (res).create (10); + LOOP_VINFO_SLP_INSTANCES (res).create (10); + LOOP_VINFO_SLP_UNROLLING_FACTOR (res) = 1; + LOOP_VINFO_TARGET_COST_DATA (res) = init_cost (loop); + LOOP_VINFO_PEELING_FOR_GAPS (res) = false; + LOOP_VINFO_PEELING_FOR_NITER (res) = false; + LOOP_VINFO_OPERANDS_SWAPPED (res) = false; + + return res; +} + + +/* Function destroy_loop_vec_info. + + Free LOOP_VINFO struct, as well as all the stmt_vec_info structs of all the + stmts in the loop. */ + +void +destroy_loop_vec_info (loop_vec_info loop_vinfo, bool clean_stmts) +{ + struct loop *loop; + basic_block *bbs; + int nbbs; + gimple_stmt_iterator si; + int j; + vec<slp_instance> slp_instances; + slp_instance instance; + bool swapped; + + if (!loop_vinfo) + return; + + loop = LOOP_VINFO_LOOP (loop_vinfo); + + bbs = LOOP_VINFO_BBS (loop_vinfo); + nbbs = clean_stmts ? loop->num_nodes : 0; + swapped = LOOP_VINFO_OPERANDS_SWAPPED (loop_vinfo); + + for (j = 0; j < nbbs; j++) + { + basic_block bb = bbs[j]; + for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si)) + free_stmt_vec_info (gsi_stmt (si)); + + for (si = gsi_start_bb (bb); !gsi_end_p (si); ) + { + gimple stmt = gsi_stmt (si); + + /* We may have broken canonical form by moving a constant + into RHS1 of a commutative op. Fix such occurrences. */ + if (swapped && is_gimple_assign (stmt)) + { + enum tree_code code = gimple_assign_rhs_code (stmt); + + if ((code == PLUS_EXPR + || code == POINTER_PLUS_EXPR + || code == MULT_EXPR) + && CONSTANT_CLASS_P (gimple_assign_rhs1 (stmt))) + swap_ssa_operands (stmt, + gimple_assign_rhs1_ptr (stmt), + gimple_assign_rhs2_ptr (stmt)); + } + + /* Free stmt_vec_info. */ + free_stmt_vec_info (stmt); + gsi_next (&si); + } + } + + free (LOOP_VINFO_BBS (loop_vinfo)); + vect_destroy_datarefs (loop_vinfo, NULL); + free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo)); + LOOP_VINFO_LOOP_NEST (loop_vinfo).release (); + LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).release (); + LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo).release (); + slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo); + FOR_EACH_VEC_ELT (slp_instances, j, instance) + vect_free_slp_instance (instance); + + LOOP_VINFO_SLP_INSTANCES (loop_vinfo).release (); + LOOP_VINFO_GROUPED_STORES (loop_vinfo).release (); + LOOP_VINFO_REDUCTIONS (loop_vinfo).release (); + LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo).release (); + + if (LOOP_VINFO_PEELING_HTAB (loop_vinfo).is_created ()) + LOOP_VINFO_PEELING_HTAB (loop_vinfo).dispose (); + + destroy_cost_data (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo)); + + free (loop_vinfo); + loop->aux = NULL; +} + + +/* Function vect_analyze_loop_1. + + Apply a set of analyses on LOOP, and create a loop_vec_info struct + for it. The different analyses will record information in the + loop_vec_info struct. This is a subset of the analyses applied in + vect_analyze_loop, to be applied on an inner-loop nested in the loop + that is now considered for (outer-loop) vectorization. */ + +static loop_vec_info +vect_analyze_loop_1 (struct loop *loop) +{ + loop_vec_info loop_vinfo; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "===== analyze_loop_nest_1 =====\n"); + + /* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */ + + loop_vinfo = vect_analyze_loop_form (loop); + if (!loop_vinfo) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad inner-loop form.\n"); + return NULL; + } + + return loop_vinfo; +} + + +/* Function vect_analyze_loop_form. + + Verify that certain CFG restrictions hold, including: + - the loop has a pre-header + - the loop has a single entry and exit + - the loop exit condition is simple enough, and the number of iterations + can be analyzed (a countable loop). */ + +loop_vec_info +vect_analyze_loop_form (struct loop *loop) +{ + loop_vec_info loop_vinfo; + gimple loop_cond; + tree number_of_iterations = NULL, number_of_iterationsm1 = NULL; + loop_vec_info inner_loop_vinfo = NULL; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== vect_analyze_loop_form ===\n"); + + /* Different restrictions apply when we are considering an inner-most loop, + vs. an outer (nested) loop. + (FORNOW. May want to relax some of these restrictions in the future). */ + + if (!loop->inner) + { + /* Inner-most loop. We currently require that the number of BBs is + exactly 2 (the header and latch). Vectorizable inner-most loops + look like this: + + (pre-header) + | + header <--------+ + | | | + | +--> latch --+ + | + (exit-bb) */ + + if (loop->num_nodes != 2) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: control flow in loop.\n"); + return NULL; + } + + if (empty_block_p (loop->header)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: empty loop.\n"); + return NULL; + } + } + else + { + struct loop *innerloop = loop->inner; + edge entryedge; + + /* Nested loop. We currently require that the loop is doubly-nested, + contains a single inner loop, and the number of BBs is exactly 5. + Vectorizable outer-loops look like this: + + (pre-header) + | + header <---+ + | | + inner-loop | + | | + tail ------+ + | + (exit-bb) + + The inner-loop has the properties expected of inner-most loops + as described above. */ + + if ((loop->inner)->inner || (loop->inner)->next) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: multiple nested loops.\n"); + return NULL; + } + + /* Analyze the inner-loop. */ + inner_loop_vinfo = vect_analyze_loop_1 (loop->inner); + if (!inner_loop_vinfo) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: Bad inner loop.\n"); + return NULL; + } + + if (!expr_invariant_in_loop_p (loop, + LOOP_VINFO_NITERS (inner_loop_vinfo))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: inner-loop count not" + " invariant.\n"); + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + if (loop->num_nodes != 5) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: control flow in loop.\n"); + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + gcc_assert (EDGE_COUNT (innerloop->header->preds) == 2); + entryedge = EDGE_PRED (innerloop->header, 0); + if (EDGE_PRED (innerloop->header, 0)->src == innerloop->latch) + entryedge = EDGE_PRED (innerloop->header, 1); + + if (entryedge->src != loop->header + || !single_exit (innerloop) + || single_exit (innerloop)->dest != EDGE_PRED (loop->latch, 0)->src) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: unsupported outerloop form.\n"); + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Considering outer-loop vectorization.\n"); + } + + if (!single_exit (loop) + || EDGE_COUNT (loop->header->preds) != 2) + { + if (dump_enabled_p ()) + { + if (!single_exit (loop)) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: multiple exits.\n"); + else if (EDGE_COUNT (loop->header->preds) != 2) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: too many incoming edges.\n"); + } + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + /* We assume that the loop exit condition is at the end of the loop. i.e, + that the loop is represented as a do-while (with a proper if-guard + before the loop if needed), where the loop header contains all the + executable statements, and the latch is empty. */ + if (!empty_block_p (loop->latch) + || !gimple_seq_empty_p (phi_nodes (loop->latch))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: latch block not empty.\n"); + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + /* Make sure there exists a single-predecessor exit bb: */ + if (!single_pred_p (single_exit (loop)->dest)) + { + edge e = single_exit (loop); + if (!(e->flags & EDGE_ABNORMAL)) + { + split_loop_exit_edge (e); + if (dump_enabled_p ()) + dump_printf (MSG_NOTE, "split exit edge.\n"); + } + else + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: abnormal loop exit edge.\n"); + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + } + + loop_cond = vect_get_loop_niters (loop, &number_of_iterations, + &number_of_iterationsm1); + if (!loop_cond) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: complicated exit condition.\n"); + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + if (!number_of_iterations + || chrec_contains_undetermined (number_of_iterations)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: number of iterations cannot be " + "computed.\n"); + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + if (integer_zerop (number_of_iterations)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: number of iterations = 0.\n"); + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, true); + return NULL; + } + + loop_vinfo = new_loop_vec_info (loop); + LOOP_VINFO_NITERSM1 (loop_vinfo) = number_of_iterationsm1; + LOOP_VINFO_NITERS (loop_vinfo) = number_of_iterations; + LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = number_of_iterations; + + if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "Symbolic number of iterations is "); + dump_generic_expr (MSG_NOTE, TDF_DETAILS, number_of_iterations); + dump_printf (MSG_NOTE, "\n"); + } + } + + STMT_VINFO_TYPE (vinfo_for_stmt (loop_cond)) = loop_exit_ctrl_vec_info_type; + + /* CHECKME: May want to keep it around it in the future. */ + if (inner_loop_vinfo) + destroy_loop_vec_info (inner_loop_vinfo, false); + + gcc_assert (!loop->aux); + loop->aux = loop_vinfo; + return loop_vinfo; +} + + +/* Function vect_analyze_loop_operations. + + Scan the loop stmts and make sure they are all vectorizable. */ + +static bool +vect_analyze_loop_operations (loop_vec_info loop_vinfo, bool slp) +{ + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo); + int nbbs = loop->num_nodes; + gimple_stmt_iterator si; + unsigned int vectorization_factor = 0; + int i; + gimple phi; + stmt_vec_info stmt_info; + bool need_to_vectorize = false; + int min_profitable_iters; + int min_scalar_loop_bound; + unsigned int th; + bool only_slp_in_loop = true, ok; + HOST_WIDE_INT max_niter; + HOST_WIDE_INT estimated_niter; + int min_profitable_estimate; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== vect_analyze_loop_operations ===\n"); + + gcc_assert (LOOP_VINFO_VECT_FACTOR (loop_vinfo)); + vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo); + if (slp) + { + /* If all the stmts in the loop can be SLPed, we perform only SLP, and + vectorization factor of the loop is the unrolling factor required by + the SLP instances. If that unrolling factor is 1, we say, that we + perform pure SLP on loop - cross iteration parallelism is not + exploited. */ + for (i = 0; i < nbbs; i++) + { + basic_block bb = bbs[i]; + 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); + gcc_assert (stmt_info); + if ((STMT_VINFO_RELEVANT_P (stmt_info) + || VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info))) + && !PURE_SLP_STMT (stmt_info)) + /* STMT needs both SLP and loop-based vectorization. */ + only_slp_in_loop = false; + } + } + + if (only_slp_in_loop) + vectorization_factor = LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo); + else + vectorization_factor = least_common_multiple (vectorization_factor, + LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo)); + + LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor; + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Updating vectorization factor to %d\n", + vectorization_factor); + } + + for (i = 0; i < nbbs; i++) + { + basic_block bb = bbs[i]; + + for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si)) + { + phi = gsi_stmt (si); + ok = true; + + stmt_info = vinfo_for_stmt (phi); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "examining phi: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0); + dump_printf (MSG_NOTE, "\n"); + } + + /* Inner-loop loop-closed exit phi in outer-loop vectorization + (i.e., a phi in the tail of the outer-loop). */ + if (! is_loop_header_bb_p (bb)) + { + /* FORNOW: we currently don't support the case that these phis + are not used in the outerloop (unless it is double reduction, + i.e., this phi is vect_reduction_def), cause this case + requires to actually do something here. */ + if ((!STMT_VINFO_RELEVANT_P (stmt_info) + || STMT_VINFO_LIVE_P (stmt_info)) + && STMT_VINFO_DEF_TYPE (stmt_info) + != vect_double_reduction_def) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "Unsupported loop-closed phi in " + "outer-loop.\n"); + return false; + } + + /* If PHI is used in the outer loop, we check that its operand + is defined in the inner loop. */ + if (STMT_VINFO_RELEVANT_P (stmt_info)) + { + tree phi_op; + gimple op_def_stmt; + + if (gimple_phi_num_args (phi) != 1) + return false; + + phi_op = PHI_ARG_DEF (phi, 0); + if (TREE_CODE (phi_op) != SSA_NAME) + return false; + + op_def_stmt = SSA_NAME_DEF_STMT (phi_op); + if (gimple_nop_p (op_def_stmt) + || !flow_bb_inside_loop_p (loop, gimple_bb (op_def_stmt)) + || !vinfo_for_stmt (op_def_stmt)) + return false; + + if (STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt)) + != vect_used_in_outer + && STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt)) + != vect_used_in_outer_by_reduction) + return false; + } + + continue; + } + + gcc_assert (stmt_info); + + if (STMT_VINFO_LIVE_P (stmt_info)) + { + /* FORNOW: not yet supported. */ + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: value used after loop.\n"); + return false; + } + + if (STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_scope + && STMT_VINFO_DEF_TYPE (stmt_info) != vect_induction_def) + { + /* A scalar-dependence cycle that we don't support. */ + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: scalar dependence cycle.\n"); + return false; + } + + if (STMT_VINFO_RELEVANT_P (stmt_info)) + { + need_to_vectorize = true; + if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def) + ok = vectorizable_induction (phi, NULL, NULL); + } + + if (!ok) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: relevant phi not " + "supported: "); + dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, phi, 0); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + } + + for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si)) + { + gimple stmt = gsi_stmt (si); + if (!gimple_clobber_p (stmt) + && !vect_analyze_stmt (stmt, &need_to_vectorize, NULL)) + return false; + } + } /* bbs */ + + /* All operations in the loop are either irrelevant (deal with loop + control, or dead), or only used outside the loop and can be moved + out of the loop (e.g. invariants, inductions). The loop can be + optimized away by scalar optimizations. We're better off not + touching this loop. */ + if (!need_to_vectorize) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "All the computation can be taken out of the loop.\n"); + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: redundant loop. no profit to " + "vectorize.\n"); + return false; + } + + if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) && dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "vectorization_factor = %d, niters = " + HOST_WIDE_INT_PRINT_DEC "\n", vectorization_factor, + LOOP_VINFO_INT_NITERS (loop_vinfo)); + + if ((LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) + && (LOOP_VINFO_INT_NITERS (loop_vinfo) < vectorization_factor)) + || ((max_niter = max_stmt_executions_int (loop)) != -1 + && (unsigned HOST_WIDE_INT) max_niter < vectorization_factor)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: iteration count too small.\n"); + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: iteration count smaller than " + "vectorization factor.\n"); + return false; + } + + /* Analyze cost. Decide if worth while to vectorize. */ + + /* Once VF is set, SLP costs should be updated since the number of created + vector stmts depends on VF. */ + vect_update_slp_costs_according_to_vf (loop_vinfo); + + vect_estimate_min_profitable_iters (loop_vinfo, &min_profitable_iters, + &min_profitable_estimate); + LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo) = min_profitable_iters; + + if (min_profitable_iters < 0) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: vectorization not profitable.\n"); + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: vector version will never be " + "profitable.\n"); + return false; + } + + min_scalar_loop_bound = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND) + * vectorization_factor) - 1); + + + /* Use the cost model only if it is more conservative than user specified + threshold. */ + + th = (unsigned) min_scalar_loop_bound; + if (min_profitable_iters + && (!min_scalar_loop_bound + || min_profitable_iters > min_scalar_loop_bound)) + th = (unsigned) min_profitable_iters; + + if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) + && LOOP_VINFO_INT_NITERS (loop_vinfo) <= th) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: vectorization not profitable.\n"); + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "not vectorized: iteration count smaller than user " + "specified loop bound parameter or minimum profitable " + "iterations (whichever is more conservative).\n"); + return false; + } + + if ((estimated_niter = estimated_stmt_executions_int (loop)) != -1 + && ((unsigned HOST_WIDE_INT) estimated_niter + <= MAX (th, (unsigned)min_profitable_estimate))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: estimated iteration count too " + "small.\n"); + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "not vectorized: estimated iteration count smaller " + "than specified loop bound parameter or minimum " + "profitable iterations (whichever is more " + "conservative).\n"); + return false; + } + + return true; +} + + +/* Function vect_analyze_loop_2. + + Apply a set of analyses on LOOP, and create a loop_vec_info struct + for it. The different analyses will record information in the + loop_vec_info struct. */ +static bool +vect_analyze_loop_2 (loop_vec_info loop_vinfo) +{ + bool ok, slp = false; + int max_vf = MAX_VECTORIZATION_FACTOR; + int min_vf = 2; + + /* Find all data references in the loop (which correspond to vdefs/vuses) + and analyze their evolution in the loop. Also adjust the minimal + vectorization factor according to the loads and stores. + + FORNOW: Handle only simple, array references, which + alignment can be forced, and aligned pointer-references. */ + + ok = vect_analyze_data_refs (loop_vinfo, NULL, &min_vf); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad data references.\n"); + return false; + } + + /* Analyze the access patterns of the data-refs in the loop (consecutive, + complex, etc.). FORNOW: Only handle consecutive access pattern. */ + + ok = vect_analyze_data_ref_accesses (loop_vinfo, NULL); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad data access.\n"); + return false; + } + + /* Classify all cross-iteration scalar data-flow cycles. + Cross-iteration cycles caused by virtual phis are analyzed separately. */ + + vect_analyze_scalar_cycles (loop_vinfo); + + vect_pattern_recog (loop_vinfo, NULL); + + /* Data-flow analysis to detect stmts that do not need to be vectorized. */ + + ok = vect_mark_stmts_to_be_vectorized (loop_vinfo); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "unexpected pattern.\n"); + return false; + } + + /* Analyze data dependences between the data-refs in the loop + and adjust the maximum vectorization factor according to + the dependences. + FORNOW: fail at the first data dependence that we encounter. */ + + ok = vect_analyze_data_ref_dependences (loop_vinfo, &max_vf); + if (!ok + || max_vf < min_vf) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad data dependence.\n"); + return false; + } + + ok = vect_determine_vectorization_factor (loop_vinfo); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "can't determine vectorization factor.\n"); + return false; + } + if (max_vf < LOOP_VINFO_VECT_FACTOR (loop_vinfo)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad data dependence.\n"); + return false; + } + + /* Analyze the alignment of the data-refs in the loop. + Fail if a data reference is found that cannot be vectorized. */ + + ok = vect_analyze_data_refs_alignment (loop_vinfo, NULL); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad data alignment.\n"); + return false; + } + + /* Prune the list of ddrs to be tested at run-time by versioning for alias. + It is important to call pruning after vect_analyze_data_ref_accesses, + since we use grouping information gathered by interleaving analysis. */ + ok = vect_prune_runtime_alias_test_list (loop_vinfo); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "number of versioning for alias " + "run-time tests exceeds %d " + "(--param vect-max-version-for-alias-checks)\n", + PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS)); + return false; + } + + /* This pass will decide on using loop versioning and/or loop peeling in + order to enhance the alignment of data references in the loop. */ + + ok = vect_enhance_data_refs_alignment (loop_vinfo); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad data alignment.\n"); + return false; + } + + /* Check the SLP opportunities in the loop, analyze and build SLP trees. */ + ok = vect_analyze_slp (loop_vinfo, NULL); + if (ok) + { + /* Decide which possible SLP instances to SLP. */ + slp = vect_make_slp_decision (loop_vinfo); + + /* Find stmts that need to be both vectorized and SLPed. */ + vect_detect_hybrid_slp (loop_vinfo); + } + else + return false; + + /* Scan all the operations in the loop and make sure they are + vectorizable. */ + + ok = vect_analyze_loop_operations (loop_vinfo, slp); + if (!ok) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad operation or unsupported loop bound.\n"); + return false; + } + + /* Decide whether we need to create an epilogue loop to handle + remaining scalar iterations. */ + if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) + && LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) > 0) + { + if (ctz_hwi (LOOP_VINFO_INT_NITERS (loop_vinfo) + - LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo)) + < exact_log2 (LOOP_VINFO_VECT_FACTOR (loop_vinfo))) + LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo) = true; + } + else if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) + || (tree_ctz (LOOP_VINFO_NITERS (loop_vinfo)) + < (unsigned)exact_log2 (LOOP_VINFO_VECT_FACTOR (loop_vinfo)))) + LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo) = true; + + /* If an epilogue loop is required make sure we can create one. */ + if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) + || LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "epilog loop required\n"); + if (!vect_can_advance_ivs_p (loop_vinfo) + || !slpeel_can_duplicate_loop_p (LOOP_VINFO_LOOP (loop_vinfo), + single_exit (LOOP_VINFO_LOOP + (loop_vinfo)))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not vectorized: can't create required " + "epilog loop\n"); + return false; + } + } + + return true; +} + +/* Function vect_analyze_loop. + + Apply a set of analyses on LOOP, and create a loop_vec_info struct + for it. The different analyses will record information in the + loop_vec_info struct. */ +loop_vec_info +vect_analyze_loop (struct loop *loop) +{ + loop_vec_info loop_vinfo; + unsigned int vector_sizes; + + /* Autodetect first vector size we try. */ + current_vector_size = 0; + vector_sizes = targetm.vectorize.autovectorize_vector_sizes (); + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "===== analyze_loop_nest =====\n"); + + if (loop_outer (loop) + && loop_vec_info_for_loop (loop_outer (loop)) + && LOOP_VINFO_VECTORIZABLE_P (loop_vec_info_for_loop (loop_outer (loop)))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "outer-loop already vectorized.\n"); + return NULL; + } + + while (1) + { + /* Check the CFG characteristics of the loop (nesting, entry/exit). */ + loop_vinfo = vect_analyze_loop_form (loop); + if (!loop_vinfo) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "bad loop form.\n"); + return NULL; + } + + if (vect_analyze_loop_2 (loop_vinfo)) + { + LOOP_VINFO_VECTORIZABLE_P (loop_vinfo) = 1; + + return loop_vinfo; + } + + destroy_loop_vec_info (loop_vinfo, true); + + 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); + } +} + + +/* Function reduction_code_for_scalar_code + + Input: + CODE - tree_code of a reduction operations. + + Output: + REDUC_CODE - the corresponding tree-code to be used to reduce the + vector of partial results into a single scalar result (which + will also reside in a vector) or ERROR_MARK if the operation is + a supported reduction operation, but does not have such tree-code. + + Return FALSE if CODE currently cannot be vectorized as reduction. */ + +static bool +reduction_code_for_scalar_code (enum tree_code code, + enum tree_code *reduc_code) +{ + switch (code) + { + case MAX_EXPR: + *reduc_code = REDUC_MAX_EXPR; + return true; + + case MIN_EXPR: + *reduc_code = REDUC_MIN_EXPR; + return true; + + case PLUS_EXPR: + *reduc_code = REDUC_PLUS_EXPR; + return true; + + case MULT_EXPR: + case MINUS_EXPR: + case BIT_IOR_EXPR: + case BIT_XOR_EXPR: + case BIT_AND_EXPR: + *reduc_code = ERROR_MARK; + return true; + + default: + return false; + } +} + + +/* Error reporting helper for vect_is_simple_reduction below. GIMPLE statement + STMT is printed with a message MSG. */ + +static void +report_vect_op (int msg_type, gimple stmt, const char *msg) +{ + dump_printf_loc (msg_type, vect_location, "%s", msg); + dump_gimple_stmt (msg_type, TDF_SLIM, stmt, 0); + dump_printf (msg_type, "\n"); +} + + +/* Detect SLP reduction of the form: + + #a1 = phi <a5, a0> + a2 = operation (a1) + a3 = operation (a2) + a4 = operation (a3) + a5 = operation (a4) + + #a = phi <a5> + + PHI is the reduction phi node (#a1 = phi <a5, a0> above) + FIRST_STMT is the first reduction stmt in the chain + (a2 = operation (a1)). + + Return TRUE if a reduction chain was detected. */ + +static bool +vect_is_slp_reduction (loop_vec_info loop_info, gimple phi, gimple first_stmt) +{ + struct loop *loop = (gimple_bb (phi))->loop_father; + struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info); + enum tree_code code; + gimple current_stmt = NULL, loop_use_stmt = NULL, first, next_stmt; + stmt_vec_info use_stmt_info, current_stmt_info; + tree lhs; + imm_use_iterator imm_iter; + use_operand_p use_p; + int nloop_uses, size = 0, n_out_of_loop_uses; + bool found = false; + + if (loop != vect_loop) + return false; + + lhs = PHI_RESULT (phi); + code = gimple_assign_rhs_code (first_stmt); + while (1) + { + nloop_uses = 0; + n_out_of_loop_uses = 0; + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs) + { + gimple use_stmt = USE_STMT (use_p); + if (is_gimple_debug (use_stmt)) + continue; + + /* Check if we got back to the reduction phi. */ + if (use_stmt == phi) + { + loop_use_stmt = use_stmt; + found = true; + break; + } + + if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))) + { + if (vinfo_for_stmt (use_stmt) + && !STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (use_stmt))) + { + loop_use_stmt = use_stmt; + nloop_uses++; + } + } + else + n_out_of_loop_uses++; + + /* There are can be either a single use in the loop or two uses in + phi nodes. */ + if (nloop_uses > 1 || (n_out_of_loop_uses && nloop_uses)) + return false; + } + + if (found) + break; + + /* We reached a statement with no loop uses. */ + if (nloop_uses == 0) + return false; + + /* This is a loop exit phi, and we haven't reached the reduction phi. */ + if (gimple_code (loop_use_stmt) == GIMPLE_PHI) + return false; + + if (!is_gimple_assign (loop_use_stmt) + || code != gimple_assign_rhs_code (loop_use_stmt) + || !flow_bb_inside_loop_p (loop, gimple_bb (loop_use_stmt))) + return false; + + /* Insert USE_STMT into reduction chain. */ + use_stmt_info = vinfo_for_stmt (loop_use_stmt); + if (current_stmt) + { + current_stmt_info = vinfo_for_stmt (current_stmt); + GROUP_NEXT_ELEMENT (current_stmt_info) = loop_use_stmt; + GROUP_FIRST_ELEMENT (use_stmt_info) + = GROUP_FIRST_ELEMENT (current_stmt_info); + } + else + GROUP_FIRST_ELEMENT (use_stmt_info) = loop_use_stmt; + + lhs = gimple_assign_lhs (loop_use_stmt); + current_stmt = loop_use_stmt; + size++; + } + + if (!found || loop_use_stmt != phi || size < 2) + return false; + + /* Swap the operands, if needed, to make the reduction operand be the second + operand. */ + lhs = PHI_RESULT (phi); + next_stmt = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt)); + while (next_stmt) + { + if (gimple_assign_rhs2 (next_stmt) == lhs) + { + tree op = gimple_assign_rhs1 (next_stmt); + gimple def_stmt = NULL; + + if (TREE_CODE (op) == SSA_NAME) + def_stmt = SSA_NAME_DEF_STMT (op); + + /* Check that the other def is either defined in the loop + ("vect_internal_def"), or it's an induction (defined by a + loop-header phi-node). */ + if (def_stmt + && gimple_bb (def_stmt) + && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt)) + && (is_gimple_assign (def_stmt) + || is_gimple_call (def_stmt) + || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt)) + == vect_induction_def + || (gimple_code (def_stmt) == GIMPLE_PHI + && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt)) + == vect_internal_def + && !is_loop_header_bb_p (gimple_bb (def_stmt))))) + { + lhs = gimple_assign_lhs (next_stmt); + next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt)); + continue; + } + + return false; + } + else + { + tree op = gimple_assign_rhs2 (next_stmt); + gimple def_stmt = NULL; + + if (TREE_CODE (op) == SSA_NAME) + def_stmt = SSA_NAME_DEF_STMT (op); + + /* Check that the other def is either defined in the loop + ("vect_internal_def"), or it's an induction (defined by a + loop-header phi-node). */ + if (def_stmt + && gimple_bb (def_stmt) + && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt)) + && (is_gimple_assign (def_stmt) + || is_gimple_call (def_stmt) + || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt)) + == vect_induction_def + || (gimple_code (def_stmt) == GIMPLE_PHI + && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt)) + == vect_internal_def + && !is_loop_header_bb_p (gimple_bb (def_stmt))))) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "swapping oprnds: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, next_stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + + swap_ssa_operands (next_stmt, + gimple_assign_rhs1_ptr (next_stmt), + gimple_assign_rhs2_ptr (next_stmt)); + update_stmt (next_stmt); + + if (CONSTANT_CLASS_P (gimple_assign_rhs1 (next_stmt))) + LOOP_VINFO_OPERANDS_SWAPPED (loop_info) = true; + } + else + return false; + } + + lhs = gimple_assign_lhs (next_stmt); + next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt)); + } + + /* Save the chain for further analysis in SLP detection. */ + first = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt)); + LOOP_VINFO_REDUCTION_CHAINS (loop_info).safe_push (first); + GROUP_SIZE (vinfo_for_stmt (first)) = size; + + return true; +} + + +/* Function vect_is_simple_reduction_1 + + (1) Detect a cross-iteration def-use cycle that represents a simple + reduction computation. We look for the following pattern: + + loop_header: + a1 = phi < a0, a2 > + a3 = ... + a2 = operation (a3, a1) + + or + + a3 = ... + loop_header: + a1 = phi < a0, a2 > + a2 = operation (a3, a1) + + such that: + 1. operation is commutative and associative and it is safe to + change the order of the computation (if CHECK_REDUCTION is true) + 2. no uses for a2 in the loop (a2 is used out of the loop) + 3. no uses of a1 in the loop besides the reduction operation + 4. no uses of a1 outside the loop. + + Conditions 1,4 are tested here. + Conditions 2,3 are tested in vect_mark_stmts_to_be_vectorized. + + (2) Detect a cross-iteration def-use cycle in nested loops, i.e., + nested cycles, if CHECK_REDUCTION is false. + + (3) Detect cycles of phi nodes in outer-loop vectorization, i.e., double + reductions: + + a1 = phi < a0, a2 > + inner loop (def of a3) + a2 = phi < a3 > + + If MODIFY is true it tries also to rework the code in-place to enable + detection of more reduction patterns. For the time being we rewrite + "res -= RHS" into "rhs += -RHS" when it seems worthwhile. +*/ + +static gimple +vect_is_simple_reduction_1 (loop_vec_info loop_info, gimple phi, + bool check_reduction, bool *double_reduc, + bool modify) +{ + struct loop *loop = (gimple_bb (phi))->loop_father; + struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info); + edge latch_e = loop_latch_edge (loop); + tree loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e); + gimple def_stmt, def1 = NULL, def2 = NULL; + enum tree_code orig_code, code; + tree op1, op2, op3 = NULL_TREE, op4 = NULL_TREE; + tree type; + int nloop_uses; + tree name; + imm_use_iterator imm_iter; + use_operand_p use_p; + bool phi_def; + + *double_reduc = false; + + /* If CHECK_REDUCTION is true, we assume inner-most loop vectorization, + otherwise, we assume outer loop vectorization. */ + gcc_assert ((check_reduction && loop == vect_loop) + || (!check_reduction && flow_loop_nested_p (vect_loop, loop))); + + name = PHI_RESULT (phi); + /* ??? If there are no uses of the PHI result the inner loop reduction + won't be detected as possibly double-reduction by vectorizable_reduction + because that tries to walk the PHI arg from the preheader edge which + can be constant. See PR60382. */ + if (has_zero_uses (name)) + return NULL; + nloop_uses = 0; + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name) + { + gimple use_stmt = USE_STMT (use_p); + if (is_gimple_debug (use_stmt)) + continue; + + if (!flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "intermediate value used outside loop.\n"); + + return NULL; + } + + if (vinfo_for_stmt (use_stmt) + && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt))) + nloop_uses++; + if (nloop_uses > 1) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "reduction used in loop.\n"); + return NULL; + } + } + + if (TREE_CODE (loop_arg) != SSA_NAME) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "reduction: not ssa_name: "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, loop_arg); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return NULL; + } + + def_stmt = SSA_NAME_DEF_STMT (loop_arg); + if (!def_stmt) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "reduction: no def_stmt.\n"); + return NULL; + } + + if (!is_gimple_assign (def_stmt) && gimple_code (def_stmt) != GIMPLE_PHI) + { + if (dump_enabled_p ()) + { + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, def_stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + return NULL; + } + + if (is_gimple_assign (def_stmt)) + { + name = gimple_assign_lhs (def_stmt); + phi_def = false; + } + else + { + name = PHI_RESULT (def_stmt); + phi_def = true; + } + + nloop_uses = 0; + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name) + { + gimple use_stmt = USE_STMT (use_p); + if (is_gimple_debug (use_stmt)) + continue; + if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt)) + && vinfo_for_stmt (use_stmt) + && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt))) + nloop_uses++; + if (nloop_uses > 1) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "reduction used in loop.\n"); + return NULL; + } + } + + /* If DEF_STMT is a phi node itself, we expect it to have a single argument + defined in the inner loop. */ + if (phi_def) + { + op1 = PHI_ARG_DEF (def_stmt, 0); + + if (gimple_phi_num_args (def_stmt) != 1 + || TREE_CODE (op1) != SSA_NAME) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "unsupported phi node definition.\n"); + + return NULL; + } + + def1 = SSA_NAME_DEF_STMT (op1); + if (flow_bb_inside_loop_p (loop, gimple_bb (def_stmt)) + && loop->inner + && flow_bb_inside_loop_p (loop->inner, gimple_bb (def1)) + && is_gimple_assign (def1)) + { + if (dump_enabled_p ()) + report_vect_op (MSG_NOTE, def_stmt, + "detected double reduction: "); + + *double_reduc = true; + return def_stmt; + } + + return NULL; + } + + code = orig_code = gimple_assign_rhs_code (def_stmt); + + /* We can handle "res -= x[i]", which is non-associative by + simply rewriting this into "res += -x[i]". Avoid changing + gimple instruction for the first simple tests and only do this + if we're allowed to change code at all. */ + if (code == MINUS_EXPR + && modify + && (op1 = gimple_assign_rhs1 (def_stmt)) + && TREE_CODE (op1) == SSA_NAME + && SSA_NAME_DEF_STMT (op1) == phi) + code = PLUS_EXPR; + + if (check_reduction + && (!commutative_tree_code (code) || !associative_tree_code (code))) + { + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: not commutative/associative: "); + return NULL; + } + + if (get_gimple_rhs_class (code) != GIMPLE_BINARY_RHS) + { + if (code != COND_EXPR) + { + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: not binary operation: "); + + return NULL; + } + + op3 = gimple_assign_rhs1 (def_stmt); + if (COMPARISON_CLASS_P (op3)) + { + op4 = TREE_OPERAND (op3, 1); + op3 = TREE_OPERAND (op3, 0); + } + + op1 = gimple_assign_rhs2 (def_stmt); + op2 = gimple_assign_rhs3 (def_stmt); + + if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME) + { + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: uses not ssa_names: "); + + return NULL; + } + } + else + { + op1 = gimple_assign_rhs1 (def_stmt); + op2 = gimple_assign_rhs2 (def_stmt); + + if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME) + { + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: uses not ssa_names: "); + + return NULL; + } + } + + type = TREE_TYPE (gimple_assign_lhs (def_stmt)); + if ((TREE_CODE (op1) == SSA_NAME + && !types_compatible_p (type,TREE_TYPE (op1))) + || (TREE_CODE (op2) == SSA_NAME + && !types_compatible_p (type, TREE_TYPE (op2))) + || (op3 && TREE_CODE (op3) == SSA_NAME + && !types_compatible_p (type, TREE_TYPE (op3))) + || (op4 && TREE_CODE (op4) == SSA_NAME + && !types_compatible_p (type, TREE_TYPE (op4)))) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "reduction: multiple types: operation type: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, type); + dump_printf (MSG_NOTE, ", operands types: "); + dump_generic_expr (MSG_NOTE, TDF_SLIM, + TREE_TYPE (op1)); + dump_printf (MSG_NOTE, ","); + dump_generic_expr (MSG_NOTE, TDF_SLIM, + TREE_TYPE (op2)); + if (op3) + { + dump_printf (MSG_NOTE, ","); + dump_generic_expr (MSG_NOTE, TDF_SLIM, + TREE_TYPE (op3)); + } + + if (op4) + { + dump_printf (MSG_NOTE, ","); + dump_generic_expr (MSG_NOTE, TDF_SLIM, + TREE_TYPE (op4)); + } + dump_printf (MSG_NOTE, "\n"); + } + + return NULL; + } + + /* Check that it's ok to change the order of the computation. + Generally, when vectorizing a reduction we change the order of the + computation. This may change the behavior of the program in some + cases, so we need to check that this is ok. One exception is when + vectorizing an outer-loop: the inner-loop is executed sequentially, + and therefore vectorizing reductions in the inner-loop during + outer-loop vectorization is safe. */ + + /* CHECKME: check for !flag_finite_math_only too? */ + if (SCALAR_FLOAT_TYPE_P (type) && !flag_associative_math + && check_reduction) + { + /* Changing the order of operations changes the semantics. */ + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: unsafe fp math optimization: "); + return NULL; + } + else if (INTEGRAL_TYPE_P (type) && TYPE_OVERFLOW_TRAPS (type) + && check_reduction) + { + /* Changing the order of operations changes the semantics. */ + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: unsafe int math optimization: "); + return NULL; + } + else if (SAT_FIXED_POINT_TYPE_P (type) && check_reduction) + { + /* Changing the order of operations changes the semantics. */ + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: unsafe fixed-point math optimization: "); + return NULL; + } + + /* If we detected "res -= x[i]" earlier, rewrite it into + "res += -x[i]" now. If this turns out to be useless reassoc + will clean it up again. */ + if (orig_code == MINUS_EXPR) + { + tree rhs = gimple_assign_rhs2 (def_stmt); + tree negrhs = make_ssa_name (TREE_TYPE (rhs), NULL); + gimple negate_stmt = gimple_build_assign_with_ops (NEGATE_EXPR, negrhs, + rhs, NULL); + gimple_stmt_iterator gsi = gsi_for_stmt (def_stmt); + set_vinfo_for_stmt (negate_stmt, new_stmt_vec_info (negate_stmt, + loop_info, NULL)); + gsi_insert_before (&gsi, negate_stmt, GSI_NEW_STMT); + gimple_assign_set_rhs2 (def_stmt, negrhs); + gimple_assign_set_rhs_code (def_stmt, PLUS_EXPR); + update_stmt (def_stmt); + } + + /* Reduction is safe. We're dealing with one of the following: + 1) integer arithmetic and no trapv + 2) floating point arithmetic, and special flags permit this optimization + 3) nested cycle (i.e., outer loop vectorization). */ + if (TREE_CODE (op1) == SSA_NAME) + def1 = SSA_NAME_DEF_STMT (op1); + + if (TREE_CODE (op2) == SSA_NAME) + def2 = SSA_NAME_DEF_STMT (op2); + + if (code != COND_EXPR + && ((!def1 || gimple_nop_p (def1)) && (!def2 || gimple_nop_p (def2)))) + { + if (dump_enabled_p ()) + report_vect_op (MSG_NOTE, def_stmt, "reduction: no defs for operands: "); + return NULL; + } + + /* Check that one def is the reduction def, defined by PHI, + the other def is either defined in the loop ("vect_internal_def"), + or it's an induction (defined by a loop-header phi-node). */ + + if (def2 && def2 == phi + && (code == COND_EXPR + || !def1 || gimple_nop_p (def1) + || !flow_bb_inside_loop_p (loop, gimple_bb (def1)) + || (def1 && flow_bb_inside_loop_p (loop, gimple_bb (def1)) + && (is_gimple_assign (def1) + || is_gimple_call (def1) + || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1)) + == vect_induction_def + || (gimple_code (def1) == GIMPLE_PHI + && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1)) + == vect_internal_def + && !is_loop_header_bb_p (gimple_bb (def1))))))) + { + if (dump_enabled_p ()) + report_vect_op (MSG_NOTE, def_stmt, "detected reduction: "); + return def_stmt; + } + + if (def1 && def1 == phi + && (code == COND_EXPR + || !def2 || gimple_nop_p (def2) + || !flow_bb_inside_loop_p (loop, gimple_bb (def2)) + || (def2 && flow_bb_inside_loop_p (loop, gimple_bb (def2)) + && (is_gimple_assign (def2) + || is_gimple_call (def2) + || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2)) + == vect_induction_def + || (gimple_code (def2) == GIMPLE_PHI + && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2)) + == vect_internal_def + && !is_loop_header_bb_p (gimple_bb (def2))))))) + { + if (check_reduction) + { + /* Swap operands (just for simplicity - so that the rest of the code + can assume that the reduction variable is always the last (second) + argument). */ + if (dump_enabled_p ()) + report_vect_op (MSG_NOTE, def_stmt, + "detected reduction: need to swap operands: "); + + swap_ssa_operands (def_stmt, gimple_assign_rhs1_ptr (def_stmt), + gimple_assign_rhs2_ptr (def_stmt)); + + if (CONSTANT_CLASS_P (gimple_assign_rhs1 (def_stmt))) + LOOP_VINFO_OPERANDS_SWAPPED (loop_info) = true; + } + else + { + if (dump_enabled_p ()) + report_vect_op (MSG_NOTE, def_stmt, "detected reduction: "); + } + + return def_stmt; + } + + /* Try to find SLP reduction chain. */ + if (check_reduction && vect_is_slp_reduction (loop_info, phi, def_stmt)) + { + if (dump_enabled_p ()) + report_vect_op (MSG_NOTE, def_stmt, + "reduction: detected reduction chain: "); + + return def_stmt; + } + + if (dump_enabled_p ()) + report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt, + "reduction: unknown pattern: "); + + return NULL; +} + +/* Wrapper around vect_is_simple_reduction_1, that won't modify code + in-place. Arguments as there. */ + +static gimple +vect_is_simple_reduction (loop_vec_info loop_info, gimple phi, + bool check_reduction, bool *double_reduc) +{ + return vect_is_simple_reduction_1 (loop_info, phi, check_reduction, + double_reduc, false); +} + +/* Wrapper around vect_is_simple_reduction_1, which will modify code + in-place if it enables detection of more reductions. Arguments + as there. */ + +gimple +vect_force_simple_reduction (loop_vec_info loop_info, gimple phi, + bool check_reduction, bool *double_reduc) +{ + return vect_is_simple_reduction_1 (loop_info, phi, check_reduction, + double_reduc, true); +} + +/* Calculate the cost of one scalar iteration of the loop. */ +int +vect_get_single_scalar_iteration_cost (loop_vec_info loop_vinfo) +{ + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo); + int nbbs = loop->num_nodes, factor, scalar_single_iter_cost = 0; + int innerloop_iters, i, stmt_cost; + + /* Count statements in scalar loop. Using this as scalar cost for a single + iteration for now. + + TODO: Add outer loop support. + + TODO: Consider assigning different costs to different scalar + statements. */ + + /* FORNOW. */ + innerloop_iters = 1; + if (loop->inner) + innerloop_iters = 50; /* FIXME */ + + for (i = 0; i < nbbs; i++) + { + gimple_stmt_iterator si; + basic_block bb = bbs[i]; + + if (bb->loop_father == loop->inner) + factor = innerloop_iters; + else + factor = 1; + + 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 (!is_gimple_assign (stmt) && !is_gimple_call (stmt)) + continue; + + /* Skip stmts that are not vectorized inside the loop. */ + if (stmt_info + && !STMT_VINFO_RELEVANT_P (stmt_info) + && (!STMT_VINFO_LIVE_P (stmt_info) + || !VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info))) + && !STMT_VINFO_IN_PATTERN_P (stmt_info)) + continue; + + if (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt))) + { + if (DR_IS_READ (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)))) + 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_single_iter_cost += stmt_cost * factor; + } + } + return scalar_single_iter_cost; +} + +/* Calculate cost of peeling the loop PEEL_ITERS_PROLOGUE times. */ +int +vect_get_known_peeling_cost (loop_vec_info loop_vinfo, int peel_iters_prologue, + int *peel_iters_epilogue, + int scalar_single_iter_cost, + stmt_vector_for_cost *prologue_cost_vec, + stmt_vector_for_cost *epilogue_cost_vec) +{ + int retval = 0; + int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo); + + if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)) + { + *peel_iters_epilogue = vf/2; + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "cost model: epilogue peel iters set to vf/2 " + "because loop iterations are unknown .\n"); + + /* If peeled iterations are known but number of scalar loop + iterations are unknown, count a taken branch per peeled loop. */ + retval = record_stmt_cost (prologue_cost_vec, 2, cond_branch_taken, + NULL, 0, vect_prologue); + } + else + { + int niters = LOOP_VINFO_INT_NITERS (loop_vinfo); + peel_iters_prologue = niters < peel_iters_prologue ? + niters : peel_iters_prologue; + *peel_iters_epilogue = (niters - peel_iters_prologue) % vf; + /* If we need to peel for gaps, but no peeling is required, we have to + peel VF iterations. */ + if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) && !*peel_iters_epilogue) + *peel_iters_epilogue = vf; + } + + if (peel_iters_prologue) + retval += record_stmt_cost (prologue_cost_vec, + peel_iters_prologue * scalar_single_iter_cost, + scalar_stmt, NULL, 0, vect_prologue); + if (*peel_iters_epilogue) + retval += record_stmt_cost (epilogue_cost_vec, + *peel_iters_epilogue * scalar_single_iter_cost, + scalar_stmt, NULL, 0, vect_epilogue); + return retval; +} + +/* Function vect_estimate_min_profitable_iters + + Return the number of iterations required for the vector version of the + loop to be profitable relative to the cost of the scalar version of the + loop. */ + +static void +vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo, + int *ret_min_profitable_niters, + int *ret_min_profitable_estimate) +{ + int min_profitable_iters; + int min_profitable_estimate; + int peel_iters_prologue; + int peel_iters_epilogue; + unsigned vec_inside_cost = 0; + int vec_outside_cost = 0; + unsigned vec_prologue_cost = 0; + unsigned vec_epilogue_cost = 0; + int scalar_single_iter_cost = 0; + int scalar_outside_cost = 0; + int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo); + int npeel = LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo); + void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo); + + /* Cost model disabled. */ + if (unlimited_cost_model (LOOP_VINFO_LOOP (loop_vinfo))) + { + dump_printf_loc (MSG_NOTE, vect_location, "cost model disabled.\n"); + *ret_min_profitable_niters = 0; + *ret_min_profitable_estimate = 0; + return; + } + + /* Requires loop versioning tests to handle misalignment. */ + if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)) + { + /* FIXME: Make cost depend on complexity of individual check. */ + unsigned len = LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).length (); + (void) add_stmt_cost (target_cost_data, len, vector_stmt, NULL, 0, + vect_prologue); + dump_printf (MSG_NOTE, + "cost model: Adding cost of checks for loop " + "versioning to treat misalignment.\n"); + } + + /* Requires loop versioning with alias checks. */ + if (LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo)) + { + /* FIXME: Make cost depend on complexity of individual check. */ + unsigned len = LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo).length (); + (void) add_stmt_cost (target_cost_data, len, vector_stmt, NULL, 0, + vect_prologue); + dump_printf (MSG_NOTE, + "cost model: Adding cost of checks for loop " + "versioning aliasing.\n"); + } + + if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo) + || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo)) + (void) add_stmt_cost (target_cost_data, 1, cond_branch_taken, NULL, 0, + vect_prologue); + + /* Count statements in scalar loop. Using this as scalar cost for a single + iteration for now. + + TODO: Add outer loop support. + + TODO: Consider assigning different costs to different scalar + statements. */ + + scalar_single_iter_cost = vect_get_single_scalar_iteration_cost (loop_vinfo); + + /* Add additional cost for the peeled instructions in prologue and epilogue + loop. + + FORNOW: If we don't know the value of peel_iters for prologue or epilogue + at compile-time - we assume it's vf/2 (the worst would be vf-1). + + TODO: Build an expression that represents peel_iters for prologue and + epilogue to be used in a run-time test. */ + + if (npeel < 0) + { + peel_iters_prologue = vf/2; + dump_printf (MSG_NOTE, "cost model: " + "prologue peel iters set to vf/2.\n"); + + /* If peeling for alignment is unknown, loop bound of main loop becomes + unknown. */ + peel_iters_epilogue = vf/2; + dump_printf (MSG_NOTE, "cost model: " + "epilogue peel iters set to vf/2 because " + "peeling for alignment is unknown.\n"); + + /* If peeled iterations are unknown, count a taken branch and a not taken + branch per peeled loop. Even if scalar loop iterations are known, + vector iterations are not known since peeled prologue iterations are + not known. Hence guards remain the same. */ + (void) add_stmt_cost (target_cost_data, 2, cond_branch_taken, + NULL, 0, vect_prologue); + (void) add_stmt_cost (target_cost_data, 2, cond_branch_not_taken, + NULL, 0, vect_prologue); + /* FORNOW: Don't attempt to pass individual scalar instructions to + the model; just assume linear cost for scalar iterations. */ + (void) add_stmt_cost (target_cost_data, + peel_iters_prologue * scalar_single_iter_cost, + scalar_stmt, NULL, 0, vect_prologue); + (void) add_stmt_cost (target_cost_data, + peel_iters_epilogue * scalar_single_iter_cost, + scalar_stmt, NULL, 0, vect_epilogue); + } + else + { + stmt_vector_for_cost prologue_cost_vec, epilogue_cost_vec; + stmt_info_for_cost *si; + int j; + void *data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo); + + prologue_cost_vec.create (2); + epilogue_cost_vec.create (2); + peel_iters_prologue = npeel; + + (void) vect_get_known_peeling_cost (loop_vinfo, peel_iters_prologue, + &peel_iters_epilogue, + scalar_single_iter_cost, + &prologue_cost_vec, + &epilogue_cost_vec); + + FOR_EACH_VEC_ELT (prologue_cost_vec, j, 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); + } + + FOR_EACH_VEC_ELT (epilogue_cost_vec, j, 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_epilogue); + } + + prologue_cost_vec.release (); + epilogue_cost_vec.release (); + } + + /* FORNOW: The scalar outside cost is incremented in one of the + following ways: + + 1. The vectorizer checks for alignment and aliasing and generates + a condition that allows dynamic vectorization. A cost model + check is ANDED with the versioning condition. Hence scalar code + path now has the added cost of the versioning check. + + if (cost > th & versioning_check) + jmp to vector code + + Hence run-time scalar is incremented by not-taken branch cost. + + 2. The vectorizer then checks if a prologue is required. If the + cost model check was not done before during versioning, it has to + be done before the prologue check. + + if (cost <= th) + prologue = scalar_iters + if (prologue == 0) + jmp to vector code + else + execute prologue + if (prologue == num_iters) + go to exit + + Hence the run-time scalar cost is incremented by a taken branch, + plus a not-taken branch, plus a taken branch cost. + + 3. The vectorizer then checks if an epilogue is required. If the + cost model check was not done before during prologue check, it + has to be done with the epilogue check. + + if (prologue == 0) + jmp to vector code + else + execute prologue + if (prologue == num_iters) + go to exit + vector code: + if ((cost <= th) | (scalar_iters-prologue-epilogue == 0)) + jmp to epilogue + + Hence the run-time scalar cost should be incremented by 2 taken + branches. + + TODO: The back end may reorder the BBS's differently and reverse + conditions/branch directions. Change the estimates below to + something more reasonable. */ + + /* If the number of iterations is known and we do not do versioning, we can + decide whether to vectorize at compile time. Hence the scalar version + do not carry cost model guard costs. */ + if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) + || LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo) + || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo)) + { + /* Cost model check occurs at versioning. */ + if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo) + || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo)) + scalar_outside_cost += vect_get_stmt_cost (cond_branch_not_taken); + else + { + /* Cost model check occurs at prologue generation. */ + if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) < 0) + scalar_outside_cost += 2 * vect_get_stmt_cost (cond_branch_taken) + + vect_get_stmt_cost (cond_branch_not_taken); + /* Cost model check occurs at epilogue generation. */ + else + scalar_outside_cost += 2 * vect_get_stmt_cost (cond_branch_taken); + } + } + + /* Complete the target-specific cost calculations. */ + finish_cost (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo), &vec_prologue_cost, + &vec_inside_cost, &vec_epilogue_cost); + + vec_outside_cost = (int)(vec_prologue_cost + vec_epilogue_cost); + + /* Calculate number of iterations required to make the vector version + profitable, relative to the loop bodies only. The following condition + must hold true: + SIC * niters + SOC > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC + where + SIC = scalar iteration cost, VIC = vector iteration cost, + VOC = vector outside cost, VF = vectorization factor, + PL_ITERS = prologue iterations, EP_ITERS= epilogue iterations + SOC = scalar outside cost for run time cost model check. */ + + if ((scalar_single_iter_cost * vf) > (int) vec_inside_cost) + { + if (vec_outside_cost <= 0) + min_profitable_iters = 1; + else + { + min_profitable_iters = ((vec_outside_cost - scalar_outside_cost) * vf + - vec_inside_cost * peel_iters_prologue + - vec_inside_cost * peel_iters_epilogue) + / ((scalar_single_iter_cost * vf) + - vec_inside_cost); + + if ((scalar_single_iter_cost * vf * min_profitable_iters) + <= (((int) vec_inside_cost * min_profitable_iters) + + (((int) vec_outside_cost - scalar_outside_cost) * vf))) + min_profitable_iters++; + } + } + /* vector version will never be profitable. */ + else + { + if (LOOP_VINFO_LOOP (loop_vinfo)->force_vect) + warning_at (vect_location, OPT_Wopenmp_simd, "vectorization " + "did not happen for a simd loop"); + + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "cost model: the vector iteration cost = %d " + "divided by the scalar iteration cost = %d " + "is greater or equal to the vectorization factor = %d" + ".\n", + vec_inside_cost, scalar_single_iter_cost, vf); + *ret_min_profitable_niters = -1; + *ret_min_profitable_estimate = -1; + return; + } + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, "Cost model analysis: \n"); + dump_printf (MSG_NOTE, " Vector inside of loop 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 iteration cost: %d\n", + scalar_single_iter_cost); + dump_printf (MSG_NOTE, " Scalar outside cost: %d\n", + scalar_outside_cost); + dump_printf (MSG_NOTE, " Vector outside cost: %d\n", + vec_outside_cost); + dump_printf (MSG_NOTE, " prologue iterations: %d\n", + peel_iters_prologue); + dump_printf (MSG_NOTE, " epilogue iterations: %d\n", + peel_iters_epilogue); + dump_printf (MSG_NOTE, + " Calculated minimum iters for profitability: %d\n", + min_profitable_iters); + dump_printf (MSG_NOTE, "\n"); + } + + min_profitable_iters = + min_profitable_iters < vf ? vf : min_profitable_iters; + + /* Because the condition we create is: + if (niters <= min_profitable_iters) + then skip the vectorized loop. */ + min_profitable_iters--; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + " Runtime profitability threshold = %d\n", + min_profitable_iters); + + *ret_min_profitable_niters = min_profitable_iters; + + /* Calculate number of iterations required to make the vector version + profitable, relative to the loop bodies only. + + Non-vectorized variant is SIC * niters and it must win over vector + variant on the expected loop trip count. The following condition must hold true: + SIC * niters > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC + SOC */ + + if (vec_outside_cost <= 0) + min_profitable_estimate = 1; + else + { + min_profitable_estimate = ((vec_outside_cost + scalar_outside_cost) * vf + - vec_inside_cost * peel_iters_prologue + - vec_inside_cost * peel_iters_epilogue) + / ((scalar_single_iter_cost * vf) + - vec_inside_cost); + } + min_profitable_estimate --; + min_profitable_estimate = MAX (min_profitable_estimate, min_profitable_iters); + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + " Static estimate profitability threshold = %d\n", + min_profitable_iters); + + *ret_min_profitable_estimate = min_profitable_estimate; +} + + +/* TODO: Close dependency between vect_model_*_cost and vectorizable_* + functions. Design better to avoid maintenance issues. */ + +/* Function vect_model_reduction_cost. + + Models cost for a reduction operation, including the vector ops + generated within the strip-mine loop, the initial definition before + the loop, and the epilogue code that must be generated. */ + +static bool +vect_model_reduction_cost (stmt_vec_info stmt_info, enum tree_code reduc_code, + int ncopies) +{ + int prologue_cost = 0, epilogue_cost = 0; + enum tree_code code; + optab optab; + tree vectype; + gimple stmt, orig_stmt; + tree reduction_op; + enum machine_mode mode; + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo); + + /* Cost of reduction op inside loop. */ + unsigned inside_cost = add_stmt_cost (target_cost_data, ncopies, vector_stmt, + stmt_info, 0, vect_body); + stmt = STMT_VINFO_STMT (stmt_info); + + switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt))) + { + case GIMPLE_SINGLE_RHS: + gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) == ternary_op); + reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), 2); + break; + case GIMPLE_UNARY_RHS: + reduction_op = gimple_assign_rhs1 (stmt); + break; + case GIMPLE_BINARY_RHS: + reduction_op = gimple_assign_rhs2 (stmt); + break; + case GIMPLE_TERNARY_RHS: + reduction_op = gimple_assign_rhs3 (stmt); + break; + default: + gcc_unreachable (); + } + + vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op)); + if (!vectype) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "unsupported data-type "); + dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, + TREE_TYPE (reduction_op)); + dump_printf (MSG_MISSED_OPTIMIZATION, "\n"); + } + return false; + } + + mode = TYPE_MODE (vectype); + orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info); + + if (!orig_stmt) + orig_stmt = STMT_VINFO_STMT (stmt_info); + + code = gimple_assign_rhs_code (orig_stmt); + + /* Add in cost for initial definition. */ + prologue_cost += add_stmt_cost (target_cost_data, 1, scalar_to_vec, + stmt_info, 0, vect_prologue); + + /* Determine cost of epilogue code. + + We have a reduction operator that will reduce the vector in one statement. + Also requires scalar extract. */ + + if (!nested_in_vect_loop_p (loop, orig_stmt)) + { + if (reduc_code != ERROR_MARK) + { + epilogue_cost += add_stmt_cost (target_cost_data, 1, vector_stmt, + stmt_info, 0, vect_epilogue); + epilogue_cost += add_stmt_cost (target_cost_data, 1, vec_to_scalar, + stmt_info, 0, vect_epilogue); + } + else + { + int vec_size_in_bits = tree_to_uhwi (TYPE_SIZE (vectype)); + tree bitsize = + TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt))); + int element_bitsize = tree_to_uhwi (bitsize); + int nelements = vec_size_in_bits / element_bitsize; + + optab = optab_for_tree_code (code, vectype, optab_default); + + /* We have a whole vector shift available. */ + if (VECTOR_MODE_P (mode) + && optab_handler (optab, mode) != CODE_FOR_nothing + && optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing) + { + /* Final reduction via vector shifts and the reduction operator. + Also requires scalar extract. */ + epilogue_cost += add_stmt_cost (target_cost_data, + exact_log2 (nelements) * 2, + vector_stmt, stmt_info, 0, + vect_epilogue); + epilogue_cost += add_stmt_cost (target_cost_data, 1, + vec_to_scalar, stmt_info, 0, + vect_epilogue); + } + else + /* Use extracts and reduction op for final reduction. For N + elements, we have N extracts and N-1 reduction ops. */ + epilogue_cost += add_stmt_cost (target_cost_data, + nelements + nelements - 1, + vector_stmt, stmt_info, 0, + vect_epilogue); + } + } + + if (dump_enabled_p ()) + dump_printf (MSG_NOTE, + "vect_model_reduction_cost: inside_cost = %d, " + "prologue_cost = %d, epilogue_cost = %d .\n", inside_cost, + prologue_cost, epilogue_cost); + + return true; +} + + +/* Function vect_model_induction_cost. + + Models cost for induction operations. */ + +static void +vect_model_induction_cost (stmt_vec_info stmt_info, int ncopies) +{ + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info); + void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo); + unsigned inside_cost, prologue_cost; + + /* loop cost for vec_loop. */ + inside_cost = add_stmt_cost (target_cost_data, ncopies, vector_stmt, + stmt_info, 0, vect_body); + + /* prologue cost for vec_init and vec_step. */ + prologue_cost = add_stmt_cost (target_cost_data, 2, scalar_to_vec, + stmt_info, 0, vect_prologue); + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "vect_model_induction_cost: inside_cost = %d, " + "prologue_cost = %d .\n", inside_cost, prologue_cost); +} + + +/* Function get_initial_def_for_induction + + Input: + STMT - a stmt that performs an induction operation in the loop. + IV_PHI - the initial value of the induction variable + + Output: + Return a vector variable, initialized with the first VF values of + the induction variable. E.g., for an iv with IV_PHI='X' and + evolution S, for a vector of 4 units, we want to return: + [X, X + S, X + 2*S, X + 3*S]. */ + +static tree +get_initial_def_for_induction (gimple iv_phi) +{ + stmt_vec_info stmt_vinfo = vinfo_for_stmt (iv_phi); + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + tree vectype; + int nunits; + edge pe = loop_preheader_edge (loop); + struct loop *iv_loop; + basic_block new_bb; + tree new_vec, vec_init, vec_step, t; + tree new_var; + tree new_name; + gimple init_stmt, induction_phi, new_stmt; + tree induc_def, vec_def, vec_dest; + tree init_expr, step_expr; + int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo); + int i; + int ncopies; + tree expr; + stmt_vec_info phi_info = vinfo_for_stmt (iv_phi); + bool nested_in_vect_loop = false; + gimple_seq stmts = NULL; + imm_use_iterator imm_iter; + use_operand_p use_p; + gimple exit_phi; + edge latch_e; + tree loop_arg; + gimple_stmt_iterator si; + basic_block bb = gimple_bb (iv_phi); + tree stepvectype; + tree resvectype; + + /* Is phi in an inner-loop, while vectorizing an enclosing outer-loop? */ + if (nested_in_vect_loop_p (loop, iv_phi)) + { + nested_in_vect_loop = true; + iv_loop = loop->inner; + } + else + iv_loop = loop; + gcc_assert (iv_loop == (gimple_bb (iv_phi))->loop_father); + + latch_e = loop_latch_edge (iv_loop); + loop_arg = PHI_ARG_DEF_FROM_EDGE (iv_phi, latch_e); + + step_expr = STMT_VINFO_LOOP_PHI_EVOLUTION_PART (phi_info); + gcc_assert (step_expr != NULL_TREE); + + pe = loop_preheader_edge (iv_loop); + init_expr = PHI_ARG_DEF_FROM_EDGE (iv_phi, + loop_preheader_edge (iv_loop)); + + vectype = get_vectype_for_scalar_type (TREE_TYPE (init_expr)); + resvectype = get_vectype_for_scalar_type (TREE_TYPE (PHI_RESULT (iv_phi))); + gcc_assert (vectype); + nunits = TYPE_VECTOR_SUBPARTS (vectype); + ncopies = vf / nunits; + + gcc_assert (phi_info); + gcc_assert (ncopies >= 1); + + /* Convert the step to the desired type. */ + step_expr = force_gimple_operand (fold_convert (TREE_TYPE (vectype), + step_expr), + &stmts, true, NULL_TREE); + if (stmts) + { + new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts); + gcc_assert (!new_bb); + } + + /* Find the first insertion point in the BB. */ + si = gsi_after_labels (bb); + + /* Create the vector that holds the initial_value of the induction. */ + if (nested_in_vect_loop) + { + /* iv_loop is nested in the loop to be vectorized. init_expr had already + been created during vectorization of previous stmts. We obtain it + from the STMT_VINFO_VEC_STMT of the defining stmt. */ + vec_init = vect_get_vec_def_for_operand (init_expr, iv_phi, NULL); + /* If the initial value is not of proper type, convert it. */ + if (!useless_type_conversion_p (vectype, TREE_TYPE (vec_init))) + { + new_stmt = gimple_build_assign_with_ops + (VIEW_CONVERT_EXPR, + vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_"), + build1 (VIEW_CONVERT_EXPR, vectype, vec_init), NULL_TREE); + vec_init = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt); + gimple_assign_set_lhs (new_stmt, vec_init); + new_bb = gsi_insert_on_edge_immediate (loop_preheader_edge (iv_loop), + new_stmt); + gcc_assert (!new_bb); + set_vinfo_for_stmt (new_stmt, + new_stmt_vec_info (new_stmt, loop_vinfo, NULL)); + } + } + else + { + vec<constructor_elt, va_gc> *v; + + /* iv_loop is the loop to be vectorized. Create: + vec_init = [X, X+S, X+2*S, X+3*S] (S = step_expr, X = init_expr) */ + new_var = vect_get_new_vect_var (TREE_TYPE (vectype), + vect_scalar_var, "var_"); + new_name = force_gimple_operand (fold_convert (TREE_TYPE (vectype), + init_expr), + &stmts, false, new_var); + if (stmts) + { + new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts); + gcc_assert (!new_bb); + } + + vec_alloc (v, nunits); + bool constant_p = is_gimple_min_invariant (new_name); + CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, new_name); + for (i = 1; i < nunits; i++) + { + /* Create: new_name_i = new_name + step_expr */ + new_name = fold_build2 (PLUS_EXPR, TREE_TYPE (new_name), + new_name, step_expr); + if (!is_gimple_min_invariant (new_name)) + { + init_stmt = gimple_build_assign (new_var, new_name); + new_name = make_ssa_name (new_var, init_stmt); + gimple_assign_set_lhs (init_stmt, new_name); + new_bb = gsi_insert_on_edge_immediate (pe, init_stmt); + gcc_assert (!new_bb); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "created new init_stmt: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, init_stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + constant_p = false; + } + CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, new_name); + } + /* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1] */ + if (constant_p) + new_vec = build_vector_from_ctor (vectype, v); + else + new_vec = build_constructor (vectype, v); + vec_init = vect_init_vector (iv_phi, new_vec, vectype, NULL); + } + + + /* Create the vector that holds the step of the induction. */ + if (nested_in_vect_loop) + /* iv_loop is nested in the loop to be vectorized. Generate: + vec_step = [S, S, S, S] */ + new_name = step_expr; + else + { + /* iv_loop is the loop to be vectorized. Generate: + vec_step = [VF*S, VF*S, VF*S, VF*S] */ + if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr))) + { + expr = build_int_cst (integer_type_node, vf); + expr = fold_convert (TREE_TYPE (step_expr), expr); + } + else + expr = build_int_cst (TREE_TYPE (step_expr), vf); + new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr), + expr, step_expr); + if (TREE_CODE (step_expr) == SSA_NAME) + new_name = vect_init_vector (iv_phi, new_name, + TREE_TYPE (step_expr), NULL); + } + + t = unshare_expr (new_name); + gcc_assert (CONSTANT_CLASS_P (new_name) + || TREE_CODE (new_name) == SSA_NAME); + stepvectype = get_vectype_for_scalar_type (TREE_TYPE (new_name)); + gcc_assert (stepvectype); + new_vec = build_vector_from_val (stepvectype, t); + vec_step = vect_init_vector (iv_phi, new_vec, stepvectype, NULL); + + + /* Create the following def-use cycle: + loop prolog: + vec_init = ... + vec_step = ... + loop: + vec_iv = PHI <vec_init, vec_loop> + ... + STMT + ... + vec_loop = vec_iv + vec_step; */ + + /* Create the induction-phi that defines the induction-operand. */ + vec_dest = vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_"); + induction_phi = create_phi_node (vec_dest, iv_loop->header); + set_vinfo_for_stmt (induction_phi, + new_stmt_vec_info (induction_phi, loop_vinfo, NULL)); + induc_def = PHI_RESULT (induction_phi); + + /* Create the iv update inside the loop */ + new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest, + induc_def, vec_step); + vec_def = make_ssa_name (vec_dest, new_stmt); + gimple_assign_set_lhs (new_stmt, vec_def); + gsi_insert_before (&si, new_stmt, GSI_SAME_STMT); + set_vinfo_for_stmt (new_stmt, new_stmt_vec_info (new_stmt, loop_vinfo, + NULL)); + + /* Set the arguments of the phi node: */ + add_phi_arg (induction_phi, vec_init, pe, UNKNOWN_LOCATION); + add_phi_arg (induction_phi, vec_def, loop_latch_edge (iv_loop), + UNKNOWN_LOCATION); + + + /* In case that vectorization factor (VF) is bigger than the number + of elements that we can fit in a vectype (nunits), we have to generate + more than one vector stmt - i.e - we need to "unroll" the + vector stmt by a factor VF/nunits. For more details see documentation + in vectorizable_operation. */ + + if (ncopies > 1) + { + stmt_vec_info prev_stmt_vinfo; + /* FORNOW. This restriction should be relaxed. */ + gcc_assert (!nested_in_vect_loop); + + /* Create the vector that holds the step of the induction. */ + if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr))) + { + expr = build_int_cst (integer_type_node, nunits); + expr = fold_convert (TREE_TYPE (step_expr), expr); + } + else + expr = build_int_cst (TREE_TYPE (step_expr), nunits); + new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr), + expr, step_expr); + if (TREE_CODE (step_expr) == SSA_NAME) + new_name = vect_init_vector (iv_phi, new_name, + TREE_TYPE (step_expr), NULL); + t = unshare_expr (new_name); + gcc_assert (CONSTANT_CLASS_P (new_name) + || TREE_CODE (new_name) == SSA_NAME); + new_vec = build_vector_from_val (stepvectype, t); + vec_step = vect_init_vector (iv_phi, new_vec, stepvectype, NULL); + + vec_def = induc_def; + prev_stmt_vinfo = vinfo_for_stmt (induction_phi); + for (i = 1; i < ncopies; i++) + { + /* vec_i = vec_prev + vec_step */ + new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest, + vec_def, vec_step); + vec_def = make_ssa_name (vec_dest, new_stmt); + gimple_assign_set_lhs (new_stmt, vec_def); + + gsi_insert_before (&si, new_stmt, GSI_SAME_STMT); + if (!useless_type_conversion_p (resvectype, vectype)) + { + new_stmt = gimple_build_assign_with_ops + (VIEW_CONVERT_EXPR, + vect_get_new_vect_var (resvectype, vect_simple_var, + "vec_iv_"), + build1 (VIEW_CONVERT_EXPR, resvectype, + gimple_assign_lhs (new_stmt)), NULL_TREE); + gimple_assign_set_lhs (new_stmt, + make_ssa_name + (gimple_assign_lhs (new_stmt), new_stmt)); + gsi_insert_before (&si, new_stmt, GSI_SAME_STMT); + } + set_vinfo_for_stmt (new_stmt, + new_stmt_vec_info (new_stmt, loop_vinfo, NULL)); + STMT_VINFO_RELATED_STMT (prev_stmt_vinfo) = new_stmt; + prev_stmt_vinfo = vinfo_for_stmt (new_stmt); + } + } + + if (nested_in_vect_loop) + { + /* Find the loop-closed exit-phi of the induction, and record + the final vector of induction results: */ + exit_phi = NULL; + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg) + { + gimple use_stmt = USE_STMT (use_p); + if (is_gimple_debug (use_stmt)) + continue; + + if (!flow_bb_inside_loop_p (iv_loop, gimple_bb (use_stmt))) + { + exit_phi = use_stmt; + break; + } + } + if (exit_phi) + { + stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_phi); + /* FORNOW. Currently not supporting the case that an inner-loop induction + is not used in the outer-loop (i.e. only outside the outer-loop). */ + gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo) + && !STMT_VINFO_LIVE_P (stmt_vinfo)); + + STMT_VINFO_VEC_STMT (stmt_vinfo) = new_stmt; + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "vector of inductions after inner-loop:"); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, new_stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + } + } + + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "transform induction: created def-use cycle: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, induction_phi, 0); + dump_printf (MSG_NOTE, "\n"); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, + SSA_NAME_DEF_STMT (vec_def), 0); + dump_printf (MSG_NOTE, "\n"); + } + + STMT_VINFO_VEC_STMT (phi_info) = induction_phi; + if (!useless_type_conversion_p (resvectype, vectype)) + { + new_stmt = gimple_build_assign_with_ops + (VIEW_CONVERT_EXPR, + vect_get_new_vect_var (resvectype, vect_simple_var, "vec_iv_"), + build1 (VIEW_CONVERT_EXPR, resvectype, induc_def), NULL_TREE); + induc_def = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt); + gimple_assign_set_lhs (new_stmt, induc_def); + si = gsi_after_labels (bb); + gsi_insert_before (&si, new_stmt, GSI_SAME_STMT); + set_vinfo_for_stmt (new_stmt, + new_stmt_vec_info (new_stmt, loop_vinfo, NULL)); + STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_stmt)) + = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (induction_phi)); + } + + return induc_def; +} + + +/* Function get_initial_def_for_reduction + + Input: + STMT - a stmt that performs a reduction operation in the loop. + INIT_VAL - the initial value of the reduction variable + + Output: + ADJUSTMENT_DEF - a tree that holds a value to be added to the final result + of the reduction (used for adjusting the epilog - see below). + Return a vector variable, initialized according to the operation that STMT + performs. This vector will be used as the initial value of the + vector of partial results. + + Option1 (adjust in epilog): Initialize the vector as follows: + add/bit or/xor: [0,0,...,0,0] + mult/bit and: [1,1,...,1,1] + min/max/cond_expr: [init_val,init_val,..,init_val,init_val] + and when necessary (e.g. add/mult case) let the caller know + that it needs to adjust the result by init_val. + + Option2: Initialize the vector as follows: + add/bit or/xor: [init_val,0,0,...,0] + mult/bit and: [init_val,1,1,...,1] + min/max/cond_expr: [init_val,init_val,...,init_val] + and no adjustments are needed. + + For example, for the following code: + + s = init_val; + for (i=0;i<n;i++) + s = s + a[i]; + + STMT is 's = s + a[i]', and the reduction variable is 's'. + For a vector of 4 units, we want to return either [0,0,0,init_val], + or [0,0,0,0] and let the caller know that it needs to adjust + the result at the end by 'init_val'. + + FORNOW, we are using the 'adjust in epilog' scheme, because this way the + initialization vector is simpler (same element in all entries), if + ADJUSTMENT_DEF is not NULL, and Option2 otherwise. + + A cost model should help decide between these two schemes. */ + +tree +get_initial_def_for_reduction (gimple stmt, tree init_val, + tree *adjustment_def) +{ + stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt); + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + tree scalar_type = TREE_TYPE (init_val); + tree vectype = get_vectype_for_scalar_type (scalar_type); + int nunits; + enum tree_code code = gimple_assign_rhs_code (stmt); + tree def_for_init; + tree init_def; + tree *elts; + int i; + bool nested_in_vect_loop = false; + tree init_value; + REAL_VALUE_TYPE real_init_val = dconst0; + int int_init_val = 0; + gimple def_stmt = NULL; + + gcc_assert (vectype); + nunits = TYPE_VECTOR_SUBPARTS (vectype); + + gcc_assert (POINTER_TYPE_P (scalar_type) || INTEGRAL_TYPE_P (scalar_type) + || SCALAR_FLOAT_TYPE_P (scalar_type)); + + if (nested_in_vect_loop_p (loop, stmt)) + nested_in_vect_loop = true; + else + gcc_assert (loop == (gimple_bb (stmt))->loop_father); + + /* In case of double reduction we only create a vector variable to be put + in the reduction phi node. The actual statement creation is done in + vect_create_epilog_for_reduction. */ + if (adjustment_def && nested_in_vect_loop + && TREE_CODE (init_val) == SSA_NAME + && (def_stmt = SSA_NAME_DEF_STMT (init_val)) + && gimple_code (def_stmt) == GIMPLE_PHI + && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt)) + && vinfo_for_stmt (def_stmt) + && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt)) + == vect_double_reduction_def) + { + *adjustment_def = NULL; + return vect_create_destination_var (init_val, vectype); + } + + if (TREE_CONSTANT (init_val)) + { + if (SCALAR_FLOAT_TYPE_P (scalar_type)) + init_value = build_real (scalar_type, TREE_REAL_CST (init_val)); + else + init_value = build_int_cst (scalar_type, TREE_INT_CST_LOW (init_val)); + } + else + init_value = init_val; + + switch (code) + { + case WIDEN_SUM_EXPR: + case DOT_PROD_EXPR: + case PLUS_EXPR: + case MINUS_EXPR: + case BIT_IOR_EXPR: + case BIT_XOR_EXPR: + case MULT_EXPR: + case BIT_AND_EXPR: + /* ADJUSMENT_DEF is NULL when called from + vect_create_epilog_for_reduction to vectorize double reduction. */ + if (adjustment_def) + { + if (nested_in_vect_loop) + *adjustment_def = vect_get_vec_def_for_operand (init_val, stmt, + NULL); + else + *adjustment_def = init_val; + } + + if (code == MULT_EXPR) + { + real_init_val = dconst1; + int_init_val = 1; + } + + if (code == BIT_AND_EXPR) + int_init_val = -1; + + if (SCALAR_FLOAT_TYPE_P (scalar_type)) + def_for_init = build_real (scalar_type, real_init_val); + else + def_for_init = build_int_cst (scalar_type, int_init_val); + + /* Create a vector of '0' or '1' except the first element. */ + elts = XALLOCAVEC (tree, nunits); + for (i = nunits - 2; i >= 0; --i) + elts[i + 1] = def_for_init; + + /* Option1: the first element is '0' or '1' as well. */ + if (adjustment_def) + { + elts[0] = def_for_init; + init_def = build_vector (vectype, elts); + break; + } + + /* Option2: the first element is INIT_VAL. */ + elts[0] = init_val; + if (TREE_CONSTANT (init_val)) + init_def = build_vector (vectype, elts); + else + { + vec<constructor_elt, va_gc> *v; + vec_alloc (v, nunits); + CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, init_val); + for (i = 1; i < nunits; ++i) + CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, elts[i]); + init_def = build_constructor (vectype, v); + } + + break; + + case MIN_EXPR: + case MAX_EXPR: + case COND_EXPR: + if (adjustment_def) + { + *adjustment_def = NULL_TREE; + init_def = vect_get_vec_def_for_operand (init_val, stmt, NULL); + break; + } + + init_def = build_vector_from_val (vectype, init_value); + break; + + default: + gcc_unreachable (); + } + + return init_def; +} + + +/* Function vect_create_epilog_for_reduction + + Create code at the loop-epilog to finalize the result of a reduction + computation. + + VECT_DEFS is list of vector of partial results, i.e., the lhs's of vector + reduction statements. + STMT is the scalar reduction stmt that is being vectorized. + NCOPIES is > 1 in case the vectorization factor (VF) is bigger than the + number of elements that we can fit in a vectype (nunits). In this case + we have to generate more than one vector stmt - i.e - we need to "unroll" + the vector stmt by a factor VF/nunits. For more details see documentation + in vectorizable_operation. + REDUC_CODE is the tree-code for the epilog reduction. + REDUCTION_PHIS is a list of the phi-nodes that carry the reduction + computation. + REDUC_INDEX is the index of the operand in the right hand side of the + statement that is defined by REDUCTION_PHI. + DOUBLE_REDUC is TRUE if double reduction phi nodes should be handled. + SLP_NODE is an SLP node containing a group of reduction statements. The + first one in this group is STMT. + + This function: + 1. Creates the reduction def-use cycles: sets the arguments for + REDUCTION_PHIS: + The loop-entry argument is the vectorized initial-value of the reduction. + The loop-latch argument is taken from VECT_DEFS - the vector of partial + sums. + 2. "Reduces" each vector of partial results VECT_DEFS into a single result, + by applying the operation specified by REDUC_CODE if available, or by + other means (whole-vector shifts or a scalar loop). + The function also creates a new phi node at the loop exit to preserve + loop-closed form, as illustrated below. + + The flow at the entry to this function: + + loop: + vec_def = phi <null, null> # REDUCTION_PHI + VECT_DEF = vector_stmt # vectorized form of STMT + s_loop = scalar_stmt # (scalar) STMT + loop_exit: + s_out0 = phi <s_loop> # (scalar) EXIT_PHI + use <s_out0> + use <s_out0> + + The above is transformed by this function into: + + loop: + vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI + VECT_DEF = vector_stmt # vectorized form of STMT + s_loop = scalar_stmt # (scalar) STMT + loop_exit: + s_out0 = phi <s_loop> # (scalar) EXIT_PHI + v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI + v_out2 = reduce <v_out1> + s_out3 = extract_field <v_out2, 0> + s_out4 = adjust_result <s_out3> + use <s_out4> + use <s_out4> +*/ + +static void +vect_create_epilog_for_reduction (vec<tree> vect_defs, gimple stmt, + int ncopies, enum tree_code reduc_code, + vec<gimple> reduction_phis, + int reduc_index, bool double_reduc, + slp_tree slp_node) +{ + stmt_vec_info stmt_info = vinfo_for_stmt (stmt); + stmt_vec_info prev_phi_info; + tree vectype; + enum machine_mode mode; + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo), *outer_loop = NULL; + basic_block exit_bb; + tree scalar_dest; + tree scalar_type; + gimple new_phi = NULL, phi; + gimple_stmt_iterator exit_gsi; + tree vec_dest; + tree new_temp = NULL_TREE, new_dest, new_name, new_scalar_dest; + gimple epilog_stmt = NULL; + enum tree_code code = gimple_assign_rhs_code (stmt); + gimple exit_phi; + tree bitsize, bitpos; + tree adjustment_def = NULL; + tree vec_initial_def = NULL; + tree reduction_op, expr, def; + tree orig_name, scalar_result; + imm_use_iterator imm_iter, phi_imm_iter; + use_operand_p use_p, phi_use_p; + bool extract_scalar_result = false; + gimple use_stmt, orig_stmt, reduction_phi = NULL; + bool nested_in_vect_loop = false; + auto_vec<gimple> new_phis; + auto_vec<gimple> inner_phis; + enum vect_def_type dt = vect_unknown_def_type; + int j, i; + auto_vec<tree> scalar_results; + unsigned int group_size = 1, k, ratio; + auto_vec<tree> vec_initial_defs; + auto_vec<gimple> phis; + bool slp_reduc = false; + tree new_phi_result; + gimple inner_phi = NULL; + + if (slp_node) + group_size = SLP_TREE_SCALAR_STMTS (slp_node).length (); + + if (nested_in_vect_loop_p (loop, stmt)) + { + outer_loop = loop; + loop = loop->inner; + nested_in_vect_loop = true; + gcc_assert (!slp_node); + } + + switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt))) + { + case GIMPLE_SINGLE_RHS: + gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) + == ternary_op); + reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), reduc_index); + break; + case GIMPLE_UNARY_RHS: + reduction_op = gimple_assign_rhs1 (stmt); + break; + case GIMPLE_BINARY_RHS: + reduction_op = reduc_index ? + gimple_assign_rhs2 (stmt) : gimple_assign_rhs1 (stmt); + break; + case GIMPLE_TERNARY_RHS: + reduction_op = gimple_op (stmt, reduc_index + 1); + break; + default: + gcc_unreachable (); + } + + vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op)); + gcc_assert (vectype); + mode = TYPE_MODE (vectype); + + /* 1. Create the reduction def-use cycle: + Set the arguments of REDUCTION_PHIS, i.e., transform + + loop: + vec_def = phi <null, null> # REDUCTION_PHI + VECT_DEF = vector_stmt # vectorized form of STMT + ... + + into: + + loop: + vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI + VECT_DEF = vector_stmt # vectorized form of STMT + ... + + (in case of SLP, do it for all the phis). */ + + /* Get the loop-entry arguments. */ + if (slp_node) + vect_get_vec_defs (reduction_op, NULL_TREE, stmt, &vec_initial_defs, + NULL, slp_node, reduc_index); + else + { + vec_initial_defs.create (1); + /* For the case of reduction, vect_get_vec_def_for_operand returns + the scalar def before the loop, that defines the initial value + of the reduction variable. */ + vec_initial_def = vect_get_vec_def_for_operand (reduction_op, stmt, + &adjustment_def); + vec_initial_defs.quick_push (vec_initial_def); + } + + /* Set phi nodes arguments. */ + FOR_EACH_VEC_ELT (reduction_phis, i, phi) + { + tree vec_init_def = vec_initial_defs[i]; + tree def = vect_defs[i]; + for (j = 0; j < ncopies; j++) + { + /* Set the loop-entry arg of the reduction-phi. */ + add_phi_arg (phi, vec_init_def, loop_preheader_edge (loop), + UNKNOWN_LOCATION); + + /* Set the loop-latch arg for the reduction-phi. */ + if (j > 0) + def = vect_get_vec_def_for_stmt_copy (vect_unknown_def_type, def); + + add_phi_arg (phi, def, loop_latch_edge (loop), UNKNOWN_LOCATION); + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "transform reduction: created def-use cycle: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0); + dump_printf (MSG_NOTE, "\n"); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, SSA_NAME_DEF_STMT (def), 0); + dump_printf (MSG_NOTE, "\n"); + } + + phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi)); + } + } + + /* 2. Create epilog code. + The reduction epilog code operates across the elements of the vector + of partial results computed by the vectorized loop. + The reduction epilog code consists of: + + step 1: compute the scalar result in a vector (v_out2) + step 2: extract the scalar result (s_out3) from the vector (v_out2) + step 3: adjust the scalar result (s_out3) if needed. + + Step 1 can be accomplished using one the following three schemes: + (scheme 1) using reduc_code, if available. + (scheme 2) using whole-vector shifts, if available. + (scheme 3) using a scalar loop. In this case steps 1+2 above are + combined. + + The overall epilog code looks like this: + + s_out0 = phi <s_loop> # original EXIT_PHI + v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI + v_out2 = reduce <v_out1> # step 1 + s_out3 = extract_field <v_out2, 0> # step 2 + s_out4 = adjust_result <s_out3> # step 3 + + (step 3 is optional, and steps 1 and 2 may be combined). + Lastly, the uses of s_out0 are replaced by s_out4. */ + + + /* 2.1 Create new loop-exit-phis to preserve loop-closed form: + v_out1 = phi <VECT_DEF> + Store them in NEW_PHIS. */ + + exit_bb = single_exit (loop)->dest; + prev_phi_info = NULL; + new_phis.create (vect_defs.length ()); + FOR_EACH_VEC_ELT (vect_defs, i, def) + { + for (j = 0; j < ncopies; j++) + { + tree new_def = copy_ssa_name (def, NULL); + phi = create_phi_node (new_def, exit_bb); + set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, loop_vinfo, NULL)); + if (j == 0) + new_phis.quick_push (phi); + else + { + def = vect_get_vec_def_for_stmt_copy (dt, def); + STMT_VINFO_RELATED_STMT (prev_phi_info) = phi; + } + + SET_PHI_ARG_DEF (phi, single_exit (loop)->dest_idx, def); + prev_phi_info = vinfo_for_stmt (phi); + } + } + + /* The epilogue is created for the outer-loop, i.e., for the loop being + vectorized. Create exit phis for the outer loop. */ + if (double_reduc) + { + loop = outer_loop; + exit_bb = single_exit (loop)->dest; + inner_phis.create (vect_defs.length ()); + FOR_EACH_VEC_ELT (new_phis, i, phi) + { + tree new_result = copy_ssa_name (PHI_RESULT (phi), NULL); + gimple outer_phi = create_phi_node (new_result, exit_bb); + SET_PHI_ARG_DEF (outer_phi, single_exit (loop)->dest_idx, + PHI_RESULT (phi)); + set_vinfo_for_stmt (outer_phi, new_stmt_vec_info (outer_phi, + loop_vinfo, NULL)); + inner_phis.quick_push (phi); + new_phis[i] = outer_phi; + prev_phi_info = vinfo_for_stmt (outer_phi); + while (STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi))) + { + phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi)); + new_result = copy_ssa_name (PHI_RESULT (phi), NULL); + outer_phi = create_phi_node (new_result, exit_bb); + SET_PHI_ARG_DEF (outer_phi, single_exit (loop)->dest_idx, + PHI_RESULT (phi)); + set_vinfo_for_stmt (outer_phi, new_stmt_vec_info (outer_phi, + loop_vinfo, NULL)); + STMT_VINFO_RELATED_STMT (prev_phi_info) = outer_phi; + prev_phi_info = vinfo_for_stmt (outer_phi); + } + } + } + + exit_gsi = gsi_after_labels (exit_bb); + + /* 2.2 Get the relevant tree-code to use in the epilog for schemes 2,3 + (i.e. when reduc_code is not available) and in the final adjustment + code (if needed). Also get the original scalar reduction variable as + defined in the loop. In case STMT is a "pattern-stmt" (i.e. - it + represents a reduction pattern), the tree-code and scalar-def are + taken from the original stmt that the pattern-stmt (STMT) replaces. + Otherwise (it is a regular reduction) - the tree-code and scalar-def + are taken from STMT. */ + + orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info); + if (!orig_stmt) + { + /* Regular reduction */ + orig_stmt = stmt; + } + else + { + /* Reduction pattern */ + stmt_vec_info stmt_vinfo = vinfo_for_stmt (orig_stmt); + gcc_assert (STMT_VINFO_IN_PATTERN_P (stmt_vinfo)); + gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo) == stmt); + } + + code = gimple_assign_rhs_code (orig_stmt); + /* For MINUS_EXPR the initial vector is [init_val,0,...,0], therefore, + partial results are added and not subtracted. */ + if (code == MINUS_EXPR) + code = PLUS_EXPR; + + scalar_dest = gimple_assign_lhs (orig_stmt); + scalar_type = TREE_TYPE (scalar_dest); + scalar_results.create (group_size); + new_scalar_dest = vect_create_destination_var (scalar_dest, NULL); + bitsize = TYPE_SIZE (scalar_type); + + /* In case this is a reduction in an inner-loop while vectorizing an outer + loop - we don't need to extract a single scalar result at the end of the + inner-loop (unless it is double reduction, i.e., the use of reduction is + outside the outer-loop). The final vector of partial results will be used + in the vectorized outer-loop, or reduced to a scalar result at the end of + the outer-loop. */ + if (nested_in_vect_loop && !double_reduc) + goto vect_finalize_reduction; + + /* SLP reduction without reduction chain, e.g., + # a1 = phi <a2, a0> + # b1 = phi <b2, b0> + a2 = operation (a1) + b2 = operation (b1) */ + slp_reduc = (slp_node && !GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))); + + /* In case of reduction chain, e.g., + # a1 = phi <a3, a0> + a2 = operation (a1) + a3 = operation (a2), + + we may end up with more than one vector result. Here we reduce them to + one vector. */ + if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) + { + tree first_vect = PHI_RESULT (new_phis[0]); + tree tmp; + gimple new_vec_stmt = NULL; + + vec_dest = vect_create_destination_var (scalar_dest, vectype); + for (k = 1; k < new_phis.length (); k++) + { + gimple next_phi = new_phis[k]; + tree second_vect = PHI_RESULT (next_phi); + + tmp = build2 (code, vectype, first_vect, second_vect); + new_vec_stmt = gimple_build_assign (vec_dest, tmp); + first_vect = make_ssa_name (vec_dest, new_vec_stmt); + gimple_assign_set_lhs (new_vec_stmt, first_vect); + gsi_insert_before (&exit_gsi, new_vec_stmt, GSI_SAME_STMT); + } + + new_phi_result = first_vect; + if (new_vec_stmt) + { + new_phis.truncate (0); + new_phis.safe_push (new_vec_stmt); + } + } + else + new_phi_result = PHI_RESULT (new_phis[0]); + + /* 2.3 Create the reduction code, using one of the three schemes described + above. In SLP we simply need to extract all the elements from the + vector (without reducing them), so we use scalar shifts. */ + if (reduc_code != ERROR_MARK && !slp_reduc) + { + tree tmp; + + /*** Case 1: Create: + v_out2 = reduc_expr <v_out1> */ + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Reduce using direct vector reduction.\n"); + + vec_dest = vect_create_destination_var (scalar_dest, vectype); + tmp = build1 (reduc_code, vectype, new_phi_result); + epilog_stmt = gimple_build_assign (vec_dest, tmp); + new_temp = make_ssa_name (vec_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_temp); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + + extract_scalar_result = true; + } + else + { + enum tree_code shift_code = ERROR_MARK; + bool have_whole_vector_shift = true; + int bit_offset; + int element_bitsize = tree_to_uhwi (bitsize); + int vec_size_in_bits = tree_to_uhwi (TYPE_SIZE (vectype)); + tree vec_temp; + + if (optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing) + shift_code = VEC_RSHIFT_EXPR; + else + have_whole_vector_shift = false; + + /* Regardless of whether we have a whole vector shift, if we're + emulating the operation via tree-vect-generic, we don't want + to use it. Only the first round of the reduction is likely + to still be profitable via emulation. */ + /* ??? It might be better to emit a reduction tree code here, so that + tree-vect-generic can expand the first round via bit tricks. */ + if (!VECTOR_MODE_P (mode)) + have_whole_vector_shift = false; + else + { + optab optab = optab_for_tree_code (code, vectype, optab_default); + if (optab_handler (optab, mode) == CODE_FOR_nothing) + have_whole_vector_shift = false; + } + + if (have_whole_vector_shift && !slp_reduc) + { + /*** Case 2: Create: + for (offset = VS/2; offset >= element_size; offset/=2) + { + Create: va' = vec_shift <va, offset> + Create: va = vop <va, va'> + } */ + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Reduce using vector shifts\n"); + + vec_dest = vect_create_destination_var (scalar_dest, vectype); + new_temp = new_phi_result; + for (bit_offset = vec_size_in_bits/2; + bit_offset >= element_bitsize; + bit_offset /= 2) + { + tree bitpos = size_int (bit_offset); + + epilog_stmt = gimple_build_assign_with_ops (shift_code, + vec_dest, new_temp, bitpos); + new_name = make_ssa_name (vec_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_name); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + + epilog_stmt = gimple_build_assign_with_ops (code, vec_dest, + new_name, new_temp); + new_temp = make_ssa_name (vec_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_temp); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + } + + extract_scalar_result = true; + } + else + { + tree rhs; + + /*** Case 3: Create: + s = extract_field <v_out2, 0> + for (offset = element_size; + offset < vector_size; + offset += element_size;) + { + Create: s' = extract_field <v_out2, offset> + Create: s = op <s, s'> // For non SLP cases + } */ + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Reduce using scalar code.\n"); + + vec_size_in_bits = tree_to_uhwi (TYPE_SIZE (vectype)); + FOR_EACH_VEC_ELT (new_phis, i, new_phi) + { + if (gimple_code (new_phi) == GIMPLE_PHI) + vec_temp = PHI_RESULT (new_phi); + else + vec_temp = gimple_assign_lhs (new_phi); + rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, bitsize, + bitsize_zero_node); + epilog_stmt = gimple_build_assign (new_scalar_dest, rhs); + new_temp = make_ssa_name (new_scalar_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_temp); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + + /* In SLP we don't need to apply reduction operation, so we just + collect s' values in SCALAR_RESULTS. */ + if (slp_reduc) + scalar_results.safe_push (new_temp); + + for (bit_offset = element_bitsize; + bit_offset < vec_size_in_bits; + bit_offset += element_bitsize) + { + tree bitpos = bitsize_int (bit_offset); + tree rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, + bitsize, bitpos); + + epilog_stmt = gimple_build_assign (new_scalar_dest, rhs); + new_name = make_ssa_name (new_scalar_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_name); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + + if (slp_reduc) + { + /* In SLP we don't need to apply reduction operation, so + we just collect s' values in SCALAR_RESULTS. */ + new_temp = new_name; + scalar_results.safe_push (new_name); + } + else + { + epilog_stmt = gimple_build_assign_with_ops (code, + new_scalar_dest, new_name, new_temp); + new_temp = make_ssa_name (new_scalar_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_temp); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + } + } + } + + /* The only case where we need to reduce scalar results in SLP, is + unrolling. If the size of SCALAR_RESULTS is greater than + GROUP_SIZE, we reduce them combining elements modulo + GROUP_SIZE. */ + if (slp_reduc) + { + tree res, first_res, new_res; + gimple new_stmt; + + /* Reduce multiple scalar results in case of SLP unrolling. */ + for (j = group_size; scalar_results.iterate (j, &res); + j++) + { + first_res = scalar_results[j % group_size]; + new_stmt = gimple_build_assign_with_ops (code, + new_scalar_dest, first_res, res); + new_res = make_ssa_name (new_scalar_dest, new_stmt); + gimple_assign_set_lhs (new_stmt, new_res); + gsi_insert_before (&exit_gsi, new_stmt, GSI_SAME_STMT); + scalar_results[j % group_size] = new_res; + } + } + else + /* Not SLP - we have one scalar to keep in SCALAR_RESULTS. */ + scalar_results.safe_push (new_temp); + + extract_scalar_result = false; + } + } + + /* 2.4 Extract the final scalar result. Create: + s_out3 = extract_field <v_out2, bitpos> */ + + if (extract_scalar_result) + { + tree rhs; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "extract scalar result\n"); + + if (BYTES_BIG_ENDIAN) + bitpos = size_binop (MULT_EXPR, + bitsize_int (TYPE_VECTOR_SUBPARTS (vectype) - 1), + TYPE_SIZE (scalar_type)); + else + bitpos = bitsize_zero_node; + + rhs = build3 (BIT_FIELD_REF, scalar_type, new_temp, bitsize, bitpos); + epilog_stmt = gimple_build_assign (new_scalar_dest, rhs); + new_temp = make_ssa_name (new_scalar_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_temp); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + scalar_results.safe_push (new_temp); + } + +vect_finalize_reduction: + + if (double_reduc) + loop = loop->inner; + + /* 2.5 Adjust the final result by the initial value of the reduction + variable. (When such adjustment is not needed, then + 'adjustment_def' is zero). For example, if code is PLUS we create: + new_temp = loop_exit_def + adjustment_def */ + + if (adjustment_def) + { + gcc_assert (!slp_reduc); + if (nested_in_vect_loop) + { + new_phi = new_phis[0]; + gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) == VECTOR_TYPE); + expr = build2 (code, vectype, PHI_RESULT (new_phi), adjustment_def); + new_dest = vect_create_destination_var (scalar_dest, vectype); + } + else + { + new_temp = scalar_results[0]; + gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) != VECTOR_TYPE); + expr = build2 (code, scalar_type, new_temp, adjustment_def); + new_dest = vect_create_destination_var (scalar_dest, scalar_type); + } + + epilog_stmt = gimple_build_assign (new_dest, expr); + new_temp = make_ssa_name (new_dest, epilog_stmt); + gimple_assign_set_lhs (epilog_stmt, new_temp); + gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT); + if (nested_in_vect_loop) + { + set_vinfo_for_stmt (epilog_stmt, + new_stmt_vec_info (epilog_stmt, loop_vinfo, + NULL)); + STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt)) = + STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi)); + + if (!double_reduc) + scalar_results.quick_push (new_temp); + else + scalar_results[0] = new_temp; + } + else + scalar_results[0] = new_temp; + + new_phis[0] = epilog_stmt; + } + + /* 2.6 Handle the loop-exit phis. Replace the uses of scalar loop-exit + phis with new adjusted scalar results, i.e., replace use <s_out0> + with use <s_out4>. + + Transform: + loop_exit: + s_out0 = phi <s_loop> # (scalar) EXIT_PHI + v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI + v_out2 = reduce <v_out1> + s_out3 = extract_field <v_out2, 0> + s_out4 = adjust_result <s_out3> + use <s_out0> + use <s_out0> + + into: + + loop_exit: + s_out0 = phi <s_loop> # (scalar) EXIT_PHI + v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI + v_out2 = reduce <v_out1> + s_out3 = extract_field <v_out2, 0> + s_out4 = adjust_result <s_out3> + use <s_out4> + use <s_out4> */ + + + /* In SLP reduction chain we reduce vector results into one vector if + necessary, hence we set here GROUP_SIZE to 1. SCALAR_DEST is the LHS of + the last stmt in the reduction chain, since we are looking for the loop + exit phi node. */ + if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) + { + scalar_dest = gimple_assign_lhs ( + SLP_TREE_SCALAR_STMTS (slp_node)[group_size - 1]); + group_size = 1; + } + + /* In SLP we may have several statements in NEW_PHIS and REDUCTION_PHIS (in + case that GROUP_SIZE is greater than vectorization factor). Therefore, we + need to match SCALAR_RESULTS with corresponding statements. The first + (GROUP_SIZE / number of new vector stmts) scalar results correspond to + the first vector stmt, etc. + (RATIO is equal to (GROUP_SIZE / number of new vector stmts)). */ + if (group_size > new_phis.length ()) + { + ratio = group_size / new_phis.length (); + gcc_assert (!(group_size % new_phis.length ())); + } + else + ratio = 1; + + for (k = 0; k < group_size; k++) + { + if (k % ratio == 0) + { + epilog_stmt = new_phis[k / ratio]; + reduction_phi = reduction_phis[k / ratio]; + if (double_reduc) + inner_phi = inner_phis[k / ratio]; + } + + if (slp_reduc) + { + gimple current_stmt = SLP_TREE_SCALAR_STMTS (slp_node)[k]; + + orig_stmt = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (current_stmt)); + /* SLP statements can't participate in patterns. */ + gcc_assert (!orig_stmt); + scalar_dest = gimple_assign_lhs (current_stmt); + } + + phis.create (3); + /* Find the loop-closed-use at the loop exit of the original scalar + result. (The reduction result is expected to have two immediate uses - + one at the latch block, and one at the loop exit). */ + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest) + if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))) + && !is_gimple_debug (USE_STMT (use_p))) + phis.safe_push (USE_STMT (use_p)); + + /* While we expect to have found an exit_phi because of loop-closed-ssa + form we can end up without one if the scalar cycle is dead. */ + + FOR_EACH_VEC_ELT (phis, i, exit_phi) + { + if (outer_loop) + { + stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi); + gimple vect_phi; + + /* FORNOW. Currently not supporting the case that an inner-loop + reduction is not used in the outer-loop (but only outside the + outer-loop), unless it is double reduction. */ + gcc_assert ((STMT_VINFO_RELEVANT_P (exit_phi_vinfo) + && !STMT_VINFO_LIVE_P (exit_phi_vinfo)) + || double_reduc); + + STMT_VINFO_VEC_STMT (exit_phi_vinfo) = epilog_stmt; + if (!double_reduc + || STMT_VINFO_DEF_TYPE (exit_phi_vinfo) + != vect_double_reduction_def) + continue; + + /* Handle double reduction: + + stmt1: s1 = phi <s0, s2> - double reduction phi (outer loop) + stmt2: s3 = phi <s1, s4> - (regular) reduc phi (inner loop) + stmt3: s4 = use (s3) - (regular) reduc stmt (inner loop) + stmt4: s2 = phi <s4> - double reduction stmt (outer loop) + + At that point the regular reduction (stmt2 and stmt3) is + already vectorized, as well as the exit phi node, stmt4. + Here we vectorize the phi node of double reduction, stmt1, and + update all relevant statements. */ + + /* Go through all the uses of s2 to find double reduction phi + node, i.e., stmt1 above. */ + orig_name = PHI_RESULT (exit_phi); + FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name) + { + stmt_vec_info use_stmt_vinfo; + stmt_vec_info new_phi_vinfo; + tree vect_phi_init, preheader_arg, vect_phi_res, init_def; + basic_block bb = gimple_bb (use_stmt); + gimple use; + + /* Check that USE_STMT is really double reduction phi + node. */ + if (gimple_code (use_stmt) != GIMPLE_PHI + || gimple_phi_num_args (use_stmt) != 2 + || bb->loop_father != outer_loop) + continue; + use_stmt_vinfo = vinfo_for_stmt (use_stmt); + if (!use_stmt_vinfo + || STMT_VINFO_DEF_TYPE (use_stmt_vinfo) + != vect_double_reduction_def) + continue; + + /* Create vector phi node for double reduction: + vs1 = phi <vs0, vs2> + vs1 was created previously in this function by a call to + vect_get_vec_def_for_operand and is stored in + vec_initial_def; + vs2 is defined by INNER_PHI, the vectorized EXIT_PHI; + vs0 is created here. */ + + /* Create vector phi node. */ + vect_phi = create_phi_node (vec_initial_def, bb); + new_phi_vinfo = new_stmt_vec_info (vect_phi, + loop_vec_info_for_loop (outer_loop), NULL); + set_vinfo_for_stmt (vect_phi, new_phi_vinfo); + + /* Create vs0 - initial def of the double reduction phi. */ + preheader_arg = PHI_ARG_DEF_FROM_EDGE (use_stmt, + loop_preheader_edge (outer_loop)); + init_def = get_initial_def_for_reduction (stmt, + preheader_arg, NULL); + vect_phi_init = vect_init_vector (use_stmt, init_def, + vectype, NULL); + + /* Update phi node arguments with vs0 and vs2. */ + add_phi_arg (vect_phi, vect_phi_init, + loop_preheader_edge (outer_loop), + UNKNOWN_LOCATION); + add_phi_arg (vect_phi, PHI_RESULT (inner_phi), + loop_latch_edge (outer_loop), UNKNOWN_LOCATION); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "created double reduction phi node: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, vect_phi, 0); + dump_printf (MSG_NOTE, "\n"); + } + + vect_phi_res = PHI_RESULT (vect_phi); + + /* Replace the use, i.e., set the correct vs1 in the regular + reduction phi node. FORNOW, NCOPIES is always 1, so the + loop is redundant. */ + use = reduction_phi; + for (j = 0; j < ncopies; j++) + { + edge pr_edge = loop_preheader_edge (loop); + SET_PHI_ARG_DEF (use, pr_edge->dest_idx, vect_phi_res); + use = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (use)); + } + } + } + } + + phis.release (); + if (nested_in_vect_loop) + { + if (double_reduc) + loop = outer_loop; + else + continue; + } + + phis.create (3); + /* Find the loop-closed-use at the loop exit of the original scalar + result. (The reduction result is expected to have two immediate uses, + one at the latch block, and one at the loop exit). For double + reductions we are looking for exit phis of the outer loop. */ + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest) + { + if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p)))) + { + if (!is_gimple_debug (USE_STMT (use_p))) + phis.safe_push (USE_STMT (use_p)); + } + else + { + if (double_reduc && gimple_code (USE_STMT (use_p)) == GIMPLE_PHI) + { + tree phi_res = PHI_RESULT (USE_STMT (use_p)); + + FOR_EACH_IMM_USE_FAST (phi_use_p, phi_imm_iter, phi_res) + { + if (!flow_bb_inside_loop_p (loop, + gimple_bb (USE_STMT (phi_use_p))) + && !is_gimple_debug (USE_STMT (phi_use_p))) + phis.safe_push (USE_STMT (phi_use_p)); + } + } + } + } + + FOR_EACH_VEC_ELT (phis, i, exit_phi) + { + /* Replace the uses: */ + orig_name = PHI_RESULT (exit_phi); + scalar_result = scalar_results[k]; + FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name) + FOR_EACH_IMM_USE_ON_STMT (use_p, imm_iter) + SET_USE (use_p, scalar_result); + } + + phis.release (); + } +} + + +/* Function vectorizable_reduction. + + Check if STMT performs a reduction operation that can be vectorized. + If VEC_STMT is also passed, vectorize the STMT: create a vectorized + stmt to replace it, put it in VEC_STMT, and insert it at GSI. + Return FALSE if not a vectorizable STMT, TRUE otherwise. + + This function also handles reduction idioms (patterns) that have been + recognized in advance during vect_pattern_recog. In this case, STMT may be + of this form: + X = pattern_expr (arg0, arg1, ..., X) + and it's STMT_VINFO_RELATED_STMT points to the last stmt in the original + sequence that had been detected and replaced by the pattern-stmt (STMT). + + In some cases of reduction patterns, the type of the reduction variable X is + different than the type of the other arguments of STMT. + In such cases, the vectype that is used when transforming STMT into a vector + stmt is different than the vectype that is used to determine the + vectorization factor, because it consists of a different number of elements + than the actual number of elements that are being operated upon in parallel. + + For example, consider an accumulation of shorts into an int accumulator. + On some targets it's possible to vectorize this pattern operating on 8 + shorts at a time (hence, the vectype for purposes of determining the + vectorization factor should be V8HI); on the other hand, the vectype that + is used to create the vector form is actually V4SI (the type of the result). + + Upon entry to this function, STMT_VINFO_VECTYPE records the vectype that + indicates what is the actual level of parallelism (V8HI in the example), so + that the right vectorization factor would be derived. This vectype + corresponds to the type of arguments to the reduction stmt, and should *NOT* + be used to create the vectorized stmt. The right vectype for the vectorized + stmt is obtained from the type of the result X: + get_vectype_for_scalar_type (TREE_TYPE (X)) + + This means that, contrary to "regular" reductions (or "regular" stmts in + general), the following equation: + STMT_VINFO_VECTYPE == get_vectype_for_scalar_type (TREE_TYPE (X)) + does *NOT* necessarily hold for reduction patterns. */ + +bool +vectorizable_reduction (gimple stmt, gimple_stmt_iterator *gsi, + gimple *vec_stmt, slp_tree slp_node) +{ + tree vec_dest; + tree scalar_dest; + tree loop_vec_def0 = NULL_TREE, loop_vec_def1 = NULL_TREE; + stmt_vec_info stmt_info = vinfo_for_stmt (stmt); + tree vectype_out = STMT_VINFO_VECTYPE (stmt_info); + tree vectype_in = NULL_TREE; + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + enum tree_code code, orig_code, epilog_reduc_code; + enum machine_mode vec_mode; + int op_type; + optab optab, reduc_optab; + tree new_temp = NULL_TREE; + tree def; + gimple def_stmt; + enum vect_def_type dt; + gimple new_phi = NULL; + tree scalar_type; + bool is_simple_use; + gimple orig_stmt; + stmt_vec_info orig_stmt_info; + tree expr = NULL_TREE; + int i; + int ncopies; + int epilog_copies; + stmt_vec_info prev_stmt_info, prev_phi_info; + bool single_defuse_cycle = false; + tree reduc_def = NULL_TREE; + gimple new_stmt = NULL; + int j; + tree ops[3]; + bool nested_cycle = false, found_nested_cycle_def = false; + gimple reduc_def_stmt = NULL; + /* The default is that the reduction variable is the last in statement. */ + int reduc_index = 2; + bool double_reduc = false, dummy; + basic_block def_bb; + struct loop * def_stmt_loop, *outer_loop = NULL; + tree def_arg; + gimple def_arg_stmt; + auto_vec<tree> vec_oprnds0; + auto_vec<tree> vec_oprnds1; + auto_vec<tree> vect_defs; + auto_vec<gimple> phis; + int vec_num; + tree def0, def1, tem, op0, op1 = NULL_TREE; + + /* In case of reduction chain we switch to the first stmt in the chain, but + we don't update STMT_INFO, since only the last stmt is marked as reduction + and has reduction properties. */ + if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt))) + stmt = GROUP_FIRST_ELEMENT (stmt_info); + + if (nested_in_vect_loop_p (loop, stmt)) + { + outer_loop = loop; + loop = loop->inner; + nested_cycle = true; + } + + /* 1. Is vectorizable reduction? */ + /* Not supportable if the reduction variable is used in the loop, unless + it's a reduction chain. */ + if (STMT_VINFO_RELEVANT (stmt_info) > vect_used_in_outer + && !GROUP_FIRST_ELEMENT (stmt_info)) + return false; + + /* Reductions that are not used even in an enclosing outer-loop, + are expected to be "live" (used out of the loop). */ + if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope + && !STMT_VINFO_LIVE_P (stmt_info)) + return false; + + /* Make sure it was already recognized as a reduction computation. */ + if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def + && STMT_VINFO_DEF_TYPE (stmt_info) != vect_nested_cycle) + return false; + + /* 2. Has this been recognized as a reduction pattern? + + Check if STMT represents a pattern that has been recognized + in earlier analysis stages. For stmts that represent a pattern, + the STMT_VINFO_RELATED_STMT field records the last stmt in + the original sequence that constitutes the pattern. */ + + orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info); + if (orig_stmt) + { + orig_stmt_info = vinfo_for_stmt (orig_stmt); + gcc_assert (STMT_VINFO_IN_PATTERN_P (orig_stmt_info)); + gcc_assert (!STMT_VINFO_IN_PATTERN_P (stmt_info)); + } + + /* 3. Check the operands of the operation. The first operands are defined + inside the loop body. The last operand is the reduction variable, + which is defined by the loop-header-phi. */ + + gcc_assert (is_gimple_assign (stmt)); + + /* Flatten RHS. */ + switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt))) + { + case GIMPLE_SINGLE_RHS: + op_type = TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)); + if (op_type == ternary_op) + { + tree rhs = gimple_assign_rhs1 (stmt); + ops[0] = TREE_OPERAND (rhs, 0); + ops[1] = TREE_OPERAND (rhs, 1); + ops[2] = TREE_OPERAND (rhs, 2); + code = TREE_CODE (rhs); + } + else + return false; + break; + + case GIMPLE_BINARY_RHS: + code = gimple_assign_rhs_code (stmt); + op_type = TREE_CODE_LENGTH (code); + gcc_assert (op_type == binary_op); + ops[0] = gimple_assign_rhs1 (stmt); + ops[1] = gimple_assign_rhs2 (stmt); + break; + + case GIMPLE_TERNARY_RHS: + code = gimple_assign_rhs_code (stmt); + op_type = TREE_CODE_LENGTH (code); + gcc_assert (op_type == ternary_op); + ops[0] = gimple_assign_rhs1 (stmt); + ops[1] = gimple_assign_rhs2 (stmt); + ops[2] = gimple_assign_rhs3 (stmt); + break; + + case GIMPLE_UNARY_RHS: + return false; + + default: + gcc_unreachable (); + } + + if (code == COND_EXPR && slp_node) + return false; + + scalar_dest = gimple_assign_lhs (stmt); + scalar_type = TREE_TYPE (scalar_dest); + if (!POINTER_TYPE_P (scalar_type) && !INTEGRAL_TYPE_P (scalar_type) + && !SCALAR_FLOAT_TYPE_P (scalar_type)) + return false; + + /* Do not try to vectorize bit-precision reductions. */ + if ((TYPE_PRECISION (scalar_type) + != GET_MODE_PRECISION (TYPE_MODE (scalar_type)))) + return false; + + /* All uses but the last are expected to be defined in the loop. + The last use is the reduction variable. In case of nested cycle this + assumption is not true: we use reduc_index to record the index of the + reduction variable. */ + for (i = 0; i < op_type - 1; i++) + { + /* The condition of COND_EXPR is checked in vectorizable_condition(). */ + if (i == 0 && code == COND_EXPR) + continue; + + is_simple_use = vect_is_simple_use_1 (ops[i], stmt, loop_vinfo, NULL, + &def_stmt, &def, &dt, &tem); + if (!vectype_in) + vectype_in = tem; + gcc_assert (is_simple_use); + + if (dt != vect_internal_def + && dt != vect_external_def + && dt != vect_constant_def + && dt != vect_induction_def + && !(dt == vect_nested_cycle && nested_cycle)) + return false; + + if (dt == vect_nested_cycle) + { + found_nested_cycle_def = true; + reduc_def_stmt = def_stmt; + reduc_index = i; + } + } + + is_simple_use = vect_is_simple_use_1 (ops[i], stmt, loop_vinfo, NULL, + &def_stmt, &def, &dt, &tem); + if (!vectype_in) + vectype_in = tem; + gcc_assert (is_simple_use); + if (!(dt == vect_reduction_def + || dt == vect_nested_cycle + || ((dt == vect_internal_def || dt == vect_external_def + || dt == vect_constant_def || dt == vect_induction_def) + && nested_cycle && found_nested_cycle_def))) + { + /* For pattern recognized stmts, orig_stmt might be a reduction, + but some helper statements for the pattern might not, or + might be COND_EXPRs with reduction uses in the condition. */ + gcc_assert (orig_stmt); + return false; + } + if (!found_nested_cycle_def) + reduc_def_stmt = def_stmt; + + gcc_assert (gimple_code (reduc_def_stmt) == GIMPLE_PHI); + if (orig_stmt) + gcc_assert (orig_stmt == vect_is_simple_reduction (loop_vinfo, + reduc_def_stmt, + !nested_cycle, + &dummy)); + else + { + gimple tmp = vect_is_simple_reduction (loop_vinfo, reduc_def_stmt, + !nested_cycle, &dummy); + /* We changed STMT to be the first stmt in reduction chain, hence we + check that in this case the first element in the chain is STMT. */ + gcc_assert (stmt == tmp + || GROUP_FIRST_ELEMENT (vinfo_for_stmt (tmp)) == stmt); + } + + if (STMT_VINFO_LIVE_P (vinfo_for_stmt (reduc_def_stmt))) + return false; + + if (slp_node || PURE_SLP_STMT (stmt_info)) + ncopies = 1; + else + ncopies = (LOOP_VINFO_VECT_FACTOR (loop_vinfo) + / TYPE_VECTOR_SUBPARTS (vectype_in)); + + gcc_assert (ncopies >= 1); + + vec_mode = TYPE_MODE (vectype_in); + + if (code == COND_EXPR) + { + if (!vectorizable_condition (stmt, gsi, NULL, ops[reduc_index], 0, NULL)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "unsupported condition in reduction\n"); + + return false; + } + } + else + { + /* 4. Supportable by target? */ + + if (code == LSHIFT_EXPR || code == RSHIFT_EXPR + || code == LROTATE_EXPR || code == RROTATE_EXPR) + { + /* Shifts and rotates are only supported by vectorizable_shifts, + not vectorizable_reduction. */ + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "unsupported shift or rotation.\n"); + return false; + } + + /* 4.1. check support for the operation in the loop */ + optab = optab_for_tree_code (code, vectype_in, optab_default); + if (!optab) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "no optab.\n"); + + return false; + } + + if (optab_handler (optab, vec_mode) == CODE_FOR_nothing) + { + if (dump_enabled_p ()) + dump_printf (MSG_NOTE, "op not supported by target.\n"); + + if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD + || LOOP_VINFO_VECT_FACTOR (loop_vinfo) + < vect_min_worthwhile_factor (code)) + return false; + + if (dump_enabled_p ()) + dump_printf (MSG_NOTE, "proceeding using word mode.\n"); + } + + /* Worthwhile without SIMD support? */ + if (!VECTOR_MODE_P (TYPE_MODE (vectype_in)) + && LOOP_VINFO_VECT_FACTOR (loop_vinfo) + < vect_min_worthwhile_factor (code)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "not worthwhile without SIMD support.\n"); + + return false; + } + } + + /* 4.2. Check support for the epilog operation. + + If STMT represents a reduction pattern, then the type of the + reduction variable may be different than the type of the rest + of the arguments. For example, consider the case of accumulation + of shorts into an int accumulator; The original code: + S1: int_a = (int) short_a; + orig_stmt-> S2: int_acc = plus <int_a ,int_acc>; + + was replaced with: + STMT: int_acc = widen_sum <short_a, int_acc> + + This means that: + 1. The tree-code that is used to create the vector operation in the + epilog code (that reduces the partial results) is not the + tree-code of STMT, but is rather the tree-code of the original + stmt from the pattern that STMT is replacing. I.e, in the example + above we want to use 'widen_sum' in the loop, but 'plus' in the + epilog. + 2. The type (mode) we use to check available target support + for the vector operation to be created in the *epilog*, is + determined by the type of the reduction variable (in the example + above we'd check this: optab_handler (plus_optab, vect_int_mode])). + However the type (mode) we use to check available target support + for the vector operation to be created *inside the loop*, is + determined by the type of the other arguments to STMT (in the + example we'd check this: optab_handler (widen_sum_optab, + vect_short_mode)). + + This is contrary to "regular" reductions, in which the types of all + the arguments are the same as the type of the reduction variable. + For "regular" reductions we can therefore use the same vector type + (and also the same tree-code) when generating the epilog code and + when generating the code inside the loop. */ + + if (orig_stmt) + { + /* This is a reduction pattern: get the vectype from the type of the + reduction variable, and get the tree-code from orig_stmt. */ + orig_code = gimple_assign_rhs_code (orig_stmt); + gcc_assert (vectype_out); + vec_mode = TYPE_MODE (vectype_out); + } + else + { + /* Regular reduction: use the same vectype and tree-code as used for + the vector code inside the loop can be used for the epilog code. */ + orig_code = code; + } + + if (nested_cycle) + { + def_bb = gimple_bb (reduc_def_stmt); + def_stmt_loop = def_bb->loop_father; + def_arg = PHI_ARG_DEF_FROM_EDGE (reduc_def_stmt, + loop_preheader_edge (def_stmt_loop)); + if (TREE_CODE (def_arg) == SSA_NAME + && (def_arg_stmt = SSA_NAME_DEF_STMT (def_arg)) + && gimple_code (def_arg_stmt) == GIMPLE_PHI + && flow_bb_inside_loop_p (outer_loop, gimple_bb (def_arg_stmt)) + && vinfo_for_stmt (def_arg_stmt) + && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_arg_stmt)) + == vect_double_reduction_def) + double_reduc = true; + } + + epilog_reduc_code = ERROR_MARK; + if (reduction_code_for_scalar_code (orig_code, &epilog_reduc_code)) + { + reduc_optab = optab_for_tree_code (epilog_reduc_code, vectype_out, + optab_default); + if (!reduc_optab) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "no optab for reduction.\n"); + + epilog_reduc_code = ERROR_MARK; + } + + if (reduc_optab + && optab_handler (reduc_optab, vec_mode) == CODE_FOR_nothing) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "reduc op not supported by target.\n"); + + epilog_reduc_code = ERROR_MARK; + } + } + else + { + if (!nested_cycle || double_reduc) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "no reduc code for scalar code.\n"); + + return false; + } + } + + if (double_reduc && ncopies > 1) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "multiple types in double reduction\n"); + + return false; + } + + /* In case of widenning multiplication by a constant, we update the type + of the constant to be the type of the other operand. We check that the + constant fits the type in the pattern recognition pass. */ + if (code == DOT_PROD_EXPR + && !types_compatible_p (TREE_TYPE (ops[0]), TREE_TYPE (ops[1]))) + { + if (TREE_CODE (ops[0]) == INTEGER_CST) + ops[0] = fold_convert (TREE_TYPE (ops[1]), ops[0]); + else if (TREE_CODE (ops[1]) == INTEGER_CST) + ops[1] = fold_convert (TREE_TYPE (ops[0]), ops[1]); + else + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "invalid types in dot-prod\n"); + + return false; + } + } + + if (!vec_stmt) /* transformation not required. */ + { + if (!vect_model_reduction_cost (stmt_info, epilog_reduc_code, ncopies)) + return false; + STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type; + return true; + } + + /** Transform. **/ + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "transform reduction.\n"); + + /* FORNOW: Multiple types are not supported for condition. */ + if (code == COND_EXPR) + gcc_assert (ncopies == 1); + + /* Create the destination vector */ + vec_dest = vect_create_destination_var (scalar_dest, vectype_out); + + /* In case the vectorization factor (VF) is bigger than the number + of elements that we can fit in a vectype (nunits), we have to generate + more than one vector stmt - i.e - we need to "unroll" the + vector stmt by a factor VF/nunits. For more details see documentation + in vectorizable_operation. */ + + /* If the reduction is used in an outer loop we need to generate + VF intermediate results, like so (e.g. for ncopies=2): + r0 = phi (init, r0) + r1 = phi (init, r1) + r0 = x0 + r0; + r1 = x1 + r1; + (i.e. we generate VF results in 2 registers). + In this case we have a separate def-use cycle for each copy, and therefore + for each copy we get the vector def for the reduction variable from the + respective phi node created for this copy. + + Otherwise (the reduction is unused in the loop nest), we can combine + together intermediate results, like so (e.g. for ncopies=2): + r = phi (init, r) + r = x0 + r; + r = x1 + r; + (i.e. we generate VF/2 results in a single register). + In this case for each copy we get the vector def for the reduction variable + from the vectorized reduction operation generated in the previous iteration. + */ + + if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope) + { + single_defuse_cycle = true; + epilog_copies = 1; + } + else + epilog_copies = ncopies; + + prev_stmt_info = NULL; + prev_phi_info = NULL; + if (slp_node) + { + vec_num = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node); + gcc_assert (TYPE_VECTOR_SUBPARTS (vectype_out) + == TYPE_VECTOR_SUBPARTS (vectype_in)); + } + else + { + vec_num = 1; + vec_oprnds0.create (1); + if (op_type == ternary_op) + vec_oprnds1.create (1); + } + + phis.create (vec_num); + vect_defs.create (vec_num); + if (!slp_node) + vect_defs.quick_push (NULL_TREE); + + for (j = 0; j < ncopies; j++) + { + if (j == 0 || !single_defuse_cycle) + { + for (i = 0; i < vec_num; i++) + { + /* Create the reduction-phi that defines the reduction + operand. */ + new_phi = create_phi_node (vec_dest, loop->header); + set_vinfo_for_stmt (new_phi, + new_stmt_vec_info (new_phi, loop_vinfo, + NULL)); + if (j == 0 || slp_node) + phis.quick_push (new_phi); + } + } + + if (code == COND_EXPR) + { + gcc_assert (!slp_node); + vectorizable_condition (stmt, gsi, vec_stmt, + PHI_RESULT (phis[0]), + reduc_index, NULL); + /* Multiple types are not supported for condition. */ + break; + } + + /* Handle uses. */ + if (j == 0) + { + op0 = ops[!reduc_index]; + if (op_type == ternary_op) + { + if (reduc_index == 0) + op1 = ops[2]; + else + op1 = ops[1]; + } + + if (slp_node) + vect_get_vec_defs (op0, op1, stmt, &vec_oprnds0, &vec_oprnds1, + slp_node, -1); + else + { + loop_vec_def0 = vect_get_vec_def_for_operand (ops[!reduc_index], + stmt, NULL); + vec_oprnds0.quick_push (loop_vec_def0); + if (op_type == ternary_op) + { + loop_vec_def1 = vect_get_vec_def_for_operand (op1, stmt, + NULL); + vec_oprnds1.quick_push (loop_vec_def1); + } + } + } + else + { + if (!slp_node) + { + enum vect_def_type dt; + gimple dummy_stmt; + tree dummy; + + vect_is_simple_use (ops[!reduc_index], stmt, loop_vinfo, NULL, + &dummy_stmt, &dummy, &dt); + loop_vec_def0 = vect_get_vec_def_for_stmt_copy (dt, + loop_vec_def0); + vec_oprnds0[0] = loop_vec_def0; + if (op_type == ternary_op) + { + vect_is_simple_use (op1, stmt, loop_vinfo, NULL, &dummy_stmt, + &dummy, &dt); + loop_vec_def1 = vect_get_vec_def_for_stmt_copy (dt, + loop_vec_def1); + vec_oprnds1[0] = loop_vec_def1; + } + } + + if (single_defuse_cycle) + reduc_def = gimple_assign_lhs (new_stmt); + + STMT_VINFO_RELATED_STMT (prev_phi_info) = new_phi; + } + + FOR_EACH_VEC_ELT (vec_oprnds0, i, def0) + { + if (slp_node) + reduc_def = PHI_RESULT (phis[i]); + else + { + if (!single_defuse_cycle || j == 0) + reduc_def = PHI_RESULT (new_phi); + } + + def1 = ((op_type == ternary_op) + ? vec_oprnds1[i] : NULL); + if (op_type == binary_op) + { + if (reduc_index == 0) + expr = build2 (code, vectype_out, reduc_def, def0); + else + expr = build2 (code, vectype_out, def0, reduc_def); + } + else + { + if (reduc_index == 0) + expr = build3 (code, vectype_out, reduc_def, def0, def1); + else + { + if (reduc_index == 1) + expr = build3 (code, vectype_out, def0, reduc_def, def1); + else + expr = build3 (code, vectype_out, def0, def1, reduc_def); + } + } + + new_stmt = gimple_build_assign (vec_dest, expr); + new_temp = make_ssa_name (vec_dest, new_stmt); + gimple_assign_set_lhs (new_stmt, new_temp); + vect_finish_stmt_generation (stmt, new_stmt, gsi); + + if (slp_node) + { + SLP_TREE_VEC_STMTS (slp_node).quick_push (new_stmt); + vect_defs.quick_push (new_temp); + } + else + vect_defs[0] = new_temp; + } + + if (slp_node) + continue; + + if (j == 0) + STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt; + else + STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt; + + prev_stmt_info = vinfo_for_stmt (new_stmt); + prev_phi_info = vinfo_for_stmt (new_phi); + } + + /* Finalize the reduction-phi (set its arguments) and create the + epilog reduction code. */ + if ((!single_defuse_cycle || code == COND_EXPR) && !slp_node) + { + new_temp = gimple_assign_lhs (*vec_stmt); + vect_defs[0] = new_temp; + } + + vect_create_epilog_for_reduction (vect_defs, stmt, epilog_copies, + epilog_reduc_code, phis, reduc_index, + double_reduc, slp_node); + + return true; +} + +/* Function vect_min_worthwhile_factor. + + For a loop where we could vectorize the operation indicated by CODE, + return the minimum vectorization factor that makes it worthwhile + to use generic vectors. */ +int +vect_min_worthwhile_factor (enum tree_code code) +{ + switch (code) + { + case PLUS_EXPR: + case MINUS_EXPR: + case NEGATE_EXPR: + return 4; + + case BIT_AND_EXPR: + case BIT_IOR_EXPR: + case BIT_XOR_EXPR: + case BIT_NOT_EXPR: + return 2; + + default: + return INT_MAX; + } +} + + +/* Function vectorizable_induction + + Check if PHI performs an induction computation that can be vectorized. + If VEC_STMT is also passed, vectorize the induction PHI: create a vectorized + phi to replace it, put it in VEC_STMT, and add it to the same basic block. + Return FALSE if not a vectorizable STMT, TRUE otherwise. */ + +bool +vectorizable_induction (gimple phi, gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED, + gimple *vec_stmt) +{ + stmt_vec_info stmt_info = vinfo_for_stmt (phi); + tree vectype = STMT_VINFO_VECTYPE (stmt_info); + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + int nunits = TYPE_VECTOR_SUBPARTS (vectype); + int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits; + tree vec_def; + + gcc_assert (ncopies >= 1); + /* FORNOW. These restrictions should be relaxed. */ + if (nested_in_vect_loop_p (loop, phi)) + { + imm_use_iterator imm_iter; + use_operand_p use_p; + gimple exit_phi; + edge latch_e; + tree loop_arg; + + if (ncopies > 1) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "multiple types in nested loop.\n"); + return false; + } + + exit_phi = NULL; + latch_e = loop_latch_edge (loop->inner); + loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e); + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg) + { + gimple use_stmt = USE_STMT (use_p); + if (is_gimple_debug (use_stmt)) + continue; + + if (!flow_bb_inside_loop_p (loop->inner, gimple_bb (use_stmt))) + { + exit_phi = use_stmt; + break; + } + } + if (exit_phi) + { + stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi); + if (!(STMT_VINFO_RELEVANT_P (exit_phi_vinfo) + && !STMT_VINFO_LIVE_P (exit_phi_vinfo))) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "inner-loop induction only used outside " + "of the outer vectorized loop.\n"); + return false; + } + } + } + + if (!STMT_VINFO_RELEVANT_P (stmt_info)) + return false; + + /* FORNOW: SLP not supported. */ + if (STMT_SLP_TYPE (stmt_info)) + return false; + + gcc_assert (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def); + + if (gimple_code (phi) != GIMPLE_PHI) + return false; + + if (!vec_stmt) /* transformation not required. */ + { + STMT_VINFO_TYPE (stmt_info) = induc_vec_info_type; + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== vectorizable_induction ===\n"); + vect_model_induction_cost (stmt_info, ncopies); + return true; + } + + /** Transform. **/ + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "transform induction phi.\n"); + + vec_def = get_initial_def_for_induction (phi); + *vec_stmt = SSA_NAME_DEF_STMT (vec_def); + return true; +} + +/* Function vectorizable_live_operation. + + STMT computes a value that is used outside the loop. Check if + it can be supported. */ + +bool +vectorizable_live_operation (gimple stmt, + gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED, + gimple *vec_stmt) +{ + stmt_vec_info stmt_info = vinfo_for_stmt (stmt); + loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info); + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + int i; + int op_type; + tree op; + tree def; + gimple def_stmt; + enum vect_def_type dt; + enum tree_code code; + enum gimple_rhs_class rhs_class; + + gcc_assert (STMT_VINFO_LIVE_P (stmt_info)); + + if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_reduction_def) + return false; + + if (!is_gimple_assign (stmt)) + { + if (gimple_call_internal_p (stmt) + && gimple_call_internal_fn (stmt) == IFN_GOMP_SIMD_LANE + && gimple_call_lhs (stmt) + && loop->simduid + && TREE_CODE (gimple_call_arg (stmt, 0)) == SSA_NAME + && loop->simduid + == SSA_NAME_VAR (gimple_call_arg (stmt, 0))) + { + edge e = single_exit (loop); + basic_block merge_bb = e->dest; + imm_use_iterator imm_iter; + use_operand_p use_p; + tree lhs = gimple_call_lhs (stmt); + + FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs) + { + gimple use_stmt = USE_STMT (use_p); + if (gimple_code (use_stmt) == GIMPLE_PHI + && gimple_bb (use_stmt) == merge_bb) + { + if (vec_stmt) + { + tree vfm1 + = build_int_cst (unsigned_type_node, + loop_vinfo->vectorization_factor - 1); + SET_PHI_ARG_DEF (use_stmt, e->dest_idx, vfm1); + } + return true; + } + } + } + + return false; + } + + if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME) + return false; + + /* FORNOW. CHECKME. */ + if (nested_in_vect_loop_p (loop, stmt)) + return false; + + code = gimple_assign_rhs_code (stmt); + op_type = TREE_CODE_LENGTH (code); + rhs_class = get_gimple_rhs_class (code); + gcc_assert (rhs_class != GIMPLE_UNARY_RHS || op_type == unary_op); + gcc_assert (rhs_class != GIMPLE_BINARY_RHS || op_type == binary_op); + + /* FORNOW: support only if all uses are invariant. This means + that the scalar operations can remain in place, unvectorized. + The original last scalar value that they compute will be used. */ + + for (i = 0; i < op_type; i++) + { + if (rhs_class == GIMPLE_SINGLE_RHS) + op = TREE_OPERAND (gimple_op (stmt, 1), i); + else + op = gimple_op (stmt, i + 1); + if (op + && !vect_is_simple_use (op, stmt, loop_vinfo, NULL, &def_stmt, &def, + &dt)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location, + "use not simple.\n"); + return false; + } + + if (dt != vect_external_def && dt != vect_constant_def) + return false; + } + + /* No transformation is required for the cases we currently support. */ + return true; +} + +/* Kill any debug uses outside LOOP of SSA names defined in STMT. */ + +static void +vect_loop_kill_debug_uses (struct loop *loop, gimple stmt) +{ + ssa_op_iter op_iter; + imm_use_iterator imm_iter; + def_operand_p def_p; + gimple ustmt; + + FOR_EACH_PHI_OR_STMT_DEF (def_p, stmt, op_iter, SSA_OP_DEF) + { + FOR_EACH_IMM_USE_STMT (ustmt, imm_iter, DEF_FROM_PTR (def_p)) + { + basic_block bb; + + if (!is_gimple_debug (ustmt)) + continue; + + bb = gimple_bb (ustmt); + + if (!flow_bb_inside_loop_p (loop, bb)) + { + if (gimple_debug_bind_p (ustmt)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "killing debug use\n"); + + gimple_debug_bind_reset_value (ustmt); + update_stmt (ustmt); + } + else + gcc_unreachable (); + } + } + } +} + + +/* This function builds ni_name = number of iterations. Statements + are emitted on the loop preheader edge. */ + +static tree +vect_build_loop_niters (loop_vec_info loop_vinfo) +{ + tree ni = unshare_expr (LOOP_VINFO_NITERS (loop_vinfo)); + if (TREE_CODE (ni) == INTEGER_CST) + return ni; + else + { + tree ni_name, var; + gimple_seq stmts = NULL; + edge pe = loop_preheader_edge (LOOP_VINFO_LOOP (loop_vinfo)); + + var = create_tmp_var (TREE_TYPE (ni), "niters"); + ni_name = force_gimple_operand (ni, &stmts, false, var); + if (stmts) + gsi_insert_seq_on_edge_immediate (pe, stmts); + + return ni_name; + } +} + + +/* This function generates the following statements: + + ni_name = number of iterations loop executes + ratio = ni_name / vf + ratio_mult_vf_name = ratio * vf + + and places them on the loop preheader edge. */ + +static void +vect_generate_tmps_on_preheader (loop_vec_info loop_vinfo, + tree ni_name, + tree *ratio_mult_vf_name_ptr, + tree *ratio_name_ptr) +{ + tree ni_minus_gap_name; + tree var; + tree ratio_name; + tree ratio_mult_vf_name; + int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo); + edge pe = loop_preheader_edge (LOOP_VINFO_LOOP (loop_vinfo)); + tree log_vf; + + log_vf = build_int_cst (TREE_TYPE (ni_name), exact_log2 (vf)); + + /* If epilogue loop is required because of data accesses with gaps, we + subtract one iteration from the total number of iterations here for + correct calculation of RATIO. */ + if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)) + { + ni_minus_gap_name = fold_build2 (MINUS_EXPR, TREE_TYPE (ni_name), + ni_name, + build_one_cst (TREE_TYPE (ni_name))); + if (!is_gimple_val (ni_minus_gap_name)) + { + var = create_tmp_var (TREE_TYPE (ni_name), "ni_gap"); + gimple stmts = NULL; + ni_minus_gap_name = force_gimple_operand (ni_minus_gap_name, &stmts, + true, var); + gsi_insert_seq_on_edge_immediate (pe, stmts); + } + } + else + ni_minus_gap_name = ni_name; + + /* Create: ratio = ni >> log2(vf) */ + /* ??? As we have ni == number of latch executions + 1, ni could + have overflown to zero. So avoid computing ratio based on ni + but compute it using the fact that we know ratio will be at least + one, thus via (ni - vf) >> log2(vf) + 1. */ + ratio_name + = fold_build2 (PLUS_EXPR, TREE_TYPE (ni_name), + fold_build2 (RSHIFT_EXPR, TREE_TYPE (ni_name), + fold_build2 (MINUS_EXPR, TREE_TYPE (ni_name), + ni_minus_gap_name, + build_int_cst + (TREE_TYPE (ni_name), vf)), + log_vf), + build_int_cst (TREE_TYPE (ni_name), 1)); + if (!is_gimple_val (ratio_name)) + { + var = create_tmp_var (TREE_TYPE (ni_name), "bnd"); + gimple stmts = NULL; + ratio_name = force_gimple_operand (ratio_name, &stmts, true, var); + gsi_insert_seq_on_edge_immediate (pe, stmts); + } + *ratio_name_ptr = ratio_name; + + /* Create: ratio_mult_vf = ratio << log2 (vf). */ + + if (ratio_mult_vf_name_ptr) + { + ratio_mult_vf_name = fold_build2 (LSHIFT_EXPR, TREE_TYPE (ratio_name), + ratio_name, log_vf); + if (!is_gimple_val (ratio_mult_vf_name)) + { + var = create_tmp_var (TREE_TYPE (ni_name), "ratio_mult_vf"); + gimple stmts = NULL; + ratio_mult_vf_name = force_gimple_operand (ratio_mult_vf_name, &stmts, + true, var); + gsi_insert_seq_on_edge_immediate (pe, stmts); + } + *ratio_mult_vf_name_ptr = ratio_mult_vf_name; + } + + return; +} + + +/* Function vect_transform_loop. + + The analysis phase has determined that the loop is vectorizable. + Vectorize the loop - created vectorized stmts to replace the scalar + stmts in the loop, and update the loop exit condition. */ + +void +vect_transform_loop (loop_vec_info loop_vinfo) +{ + struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo); + basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo); + int nbbs = loop->num_nodes; + gimple_stmt_iterator si; + int i; + tree ratio = NULL; + int vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo); + bool grouped_store; + bool slp_scheduled = false; + gimple stmt, pattern_stmt; + gimple_seq pattern_def_seq = NULL; + gimple_stmt_iterator pattern_def_si = gsi_none (); + bool transform_pattern_stmt = false; + bool check_profitability = false; + int th; + /* Record number of iterations before we started tampering with the profile. */ + gcov_type expected_iterations = expected_loop_iterations_unbounded (loop); + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "=== vec_transform_loop ===\n"); + + /* If profile is inprecise, we have chance to fix it up. */ + if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)) + expected_iterations = LOOP_VINFO_INT_NITERS (loop_vinfo); + + /* Use the more conservative vectorization threshold. If the number + of iterations is constant assume the cost check has been performed + by our caller. If the threshold makes all loops profitable that + run at least the vectorization factor number of times checking + is pointless, too. */ + th = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND) + * LOOP_VINFO_VECT_FACTOR (loop_vinfo)) - 1); + th = MAX (th, LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo)); + if (th >= LOOP_VINFO_VECT_FACTOR (loop_vinfo) - 1 + && !LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "Profitability threshold is %d loop iterations.\n", + th); + check_profitability = true; + } + + /* Version the loop first, if required, so the profitability check + comes first. */ + + if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo) + || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo)) + { + vect_loop_versioning (loop_vinfo, th, check_profitability); + check_profitability = false; + } + + tree ni_name = vect_build_loop_niters (loop_vinfo); + LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = ni_name; + + /* Peel the loop if there are data refs with unknown alignment. + Only one data ref with unknown store is allowed. */ + + if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo)) + { + vect_do_peeling_for_alignment (loop_vinfo, ni_name, + th, check_profitability); + check_profitability = false; + /* The above adjusts LOOP_VINFO_NITERS, so cause ni_name to + be re-computed. */ + ni_name = NULL_TREE; + } + + /* If the loop has a symbolic number of iterations 'n' (i.e. it's not a + compile time constant), or it is a constant that doesn't divide by the + vectorization factor, then an epilog loop needs to be created. + We therefore duplicate the loop: the original loop will be vectorized, + and will compute the first (n/VF) iterations. The second copy of the loop + will remain scalar and will compute the remaining (n%VF) iterations. + (VF is the vectorization factor). */ + + if (LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo) + || LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)) + { + tree ratio_mult_vf; + if (!ni_name) + ni_name = vect_build_loop_niters (loop_vinfo); + vect_generate_tmps_on_preheader (loop_vinfo, ni_name, &ratio_mult_vf, + &ratio); + vect_do_peeling_for_loop_bound (loop_vinfo, ni_name, ratio_mult_vf, + th, check_profitability); + } + else if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)) + ratio = build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo)), + LOOP_VINFO_INT_NITERS (loop_vinfo) / vectorization_factor); + else + { + if (!ni_name) + ni_name = vect_build_loop_niters (loop_vinfo); + vect_generate_tmps_on_preheader (loop_vinfo, ni_name, NULL, &ratio); + } + + /* 1) Make sure the loop header has exactly two entries + 2) Make sure we have a preheader basic block. */ + + gcc_assert (EDGE_COUNT (loop->header->preds) == 2); + + split_edge (loop_preheader_edge (loop)); + + /* FORNOW: the vectorizer supports only loops which body consist + of one basic block (header + empty latch). When the vectorizer will + support more involved loop forms, the order by which the BBs are + traversed need to be reconsidered. */ + + for (i = 0; i < nbbs; i++) + { + basic_block bb = bbs[i]; + stmt_vec_info stmt_info; + gimple phi; + + for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si)) + { + phi = gsi_stmt (si); + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "------>vectorizing phi: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0); + dump_printf (MSG_NOTE, "\n"); + } + stmt_info = vinfo_for_stmt (phi); + if (!stmt_info) + continue; + + if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info)) + vect_loop_kill_debug_uses (loop, phi); + + if (!STMT_VINFO_RELEVANT_P (stmt_info) + && !STMT_VINFO_LIVE_P (stmt_info)) + continue; + + if (STMT_VINFO_VECTYPE (stmt_info) + && (TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info)) + != (unsigned HOST_WIDE_INT) vectorization_factor) + && dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "multiple-types.\n"); + + if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def) + { + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "transform phi.\n"); + vect_transform_stmt (phi, NULL, NULL, NULL, NULL); + } + } + + pattern_stmt = NULL; + for (si = gsi_start_bb (bb); !gsi_end_p (si) || transform_pattern_stmt;) + { + bool is_store; + + if (transform_pattern_stmt) + stmt = pattern_stmt; + else + { + stmt = gsi_stmt (si); + /* During vectorization remove existing clobber stmts. */ + if (gimple_clobber_p (stmt)) + { + unlink_stmt_vdef (stmt); + gsi_remove (&si, true); + release_defs (stmt); + continue; + } + } + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "------>vectorizing statement: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + + stmt_info = vinfo_for_stmt (stmt); + + /* vector stmts created in the outer-loop during vectorization of + stmts in an inner-loop may not have a stmt_info, and do not + need to be vectorized. */ + if (!stmt_info) + { + gsi_next (&si); + continue; + } + + if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info)) + vect_loop_kill_debug_uses (loop, stmt); + + if (!STMT_VINFO_RELEVANT_P (stmt_info) + && !STMT_VINFO_LIVE_P (stmt_info)) + { + if (STMT_VINFO_IN_PATTERN_P (stmt_info) + && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info)) + && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt)) + || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt)))) + { + stmt = pattern_stmt; + stmt_info = vinfo_for_stmt (stmt); + } + else + { + gsi_next (&si); + continue; + } + } + else if (STMT_VINFO_IN_PATTERN_P (stmt_info) + && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info)) + && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt)) + || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt)))) + transform_pattern_stmt = true; + + /* If pattern statement has def stmts, vectorize them too. */ + if (is_pattern_stmt_p (stmt_info)) + { + if (pattern_def_seq == NULL) + { + pattern_def_seq = STMT_VINFO_PATTERN_DEF_SEQ (stmt_info); + pattern_def_si = gsi_start (pattern_def_seq); + } + else if (!gsi_end_p (pattern_def_si)) + gsi_next (&pattern_def_si); + if (pattern_def_seq != NULL) + { + gimple pattern_def_stmt = NULL; + stmt_vec_info pattern_def_stmt_info = NULL; + + while (!gsi_end_p (pattern_def_si)) + { + pattern_def_stmt = gsi_stmt (pattern_def_si); + pattern_def_stmt_info + = vinfo_for_stmt (pattern_def_stmt); + if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info) + || STMT_VINFO_LIVE_P (pattern_def_stmt_info)) + break; + gsi_next (&pattern_def_si); + } + + if (!gsi_end_p (pattern_def_si)) + { + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "==> vectorizing pattern def " + "stmt: "); + dump_gimple_stmt (MSG_NOTE, TDF_SLIM, + pattern_def_stmt, 0); + dump_printf (MSG_NOTE, "\n"); + } + + stmt = pattern_def_stmt; + stmt_info = pattern_def_stmt_info; + } + else + { + pattern_def_si = gsi_none (); + transform_pattern_stmt = false; + } + } + else + transform_pattern_stmt = false; + } + + if (STMT_VINFO_VECTYPE (stmt_info)) + { + unsigned int nunits + = (unsigned int) + TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info)); + if (!STMT_SLP_TYPE (stmt_info) + && nunits != (unsigned int) vectorization_factor + && dump_enabled_p ()) + /* For SLP VF is set according to unrolling factor, and not + to vector size, hence for SLP this print is not valid. */ + dump_printf_loc (MSG_NOTE, vect_location, "multiple-types.\n"); + } + + /* SLP. Schedule all the SLP instances when the first SLP stmt is + reached. */ + if (STMT_SLP_TYPE (stmt_info)) + { + if (!slp_scheduled) + { + slp_scheduled = true; + + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, + "=== scheduling SLP instances ===\n"); + + vect_schedule_slp (loop_vinfo, NULL); + } + + /* Hybrid SLP stmts must be vectorized in addition to SLP. */ + if (!vinfo_for_stmt (stmt) || PURE_SLP_STMT (stmt_info)) + { + if (!transform_pattern_stmt && gsi_end_p (pattern_def_si)) + { + pattern_def_seq = NULL; + gsi_next (&si); + } + continue; + } + } + + /* -------- vectorize statement ------------ */ + if (dump_enabled_p ()) + dump_printf_loc (MSG_NOTE, vect_location, "transform statement.\n"); + + grouped_store = false; + is_store = vect_transform_stmt (stmt, &si, &grouped_store, NULL, NULL); + if (is_store) + { + if (STMT_VINFO_GROUPED_ACCESS (stmt_info)) + { + /* Interleaving. If IS_STORE is TRUE, the vectorization of the + interleaving chain was completed - free all the stores in + the chain. */ + gsi_next (&si); + vect_remove_stores (GROUP_FIRST_ELEMENT (stmt_info)); + } + else + { + /* Free the attached stmt_vec_info and remove the stmt. */ + gimple store = gsi_stmt (si); + free_stmt_vec_info (store); + unlink_stmt_vdef (store); + gsi_remove (&si, true); + release_defs (store); + } + + /* Stores can only appear at the end of pattern statements. */ + gcc_assert (!transform_pattern_stmt); + pattern_def_seq = NULL; + } + else if (!transform_pattern_stmt && gsi_end_p (pattern_def_si)) + { + pattern_def_seq = NULL; + gsi_next (&si); + } + } /* stmts in BB */ + } /* BBs in loop */ + + slpeel_make_loop_iterate_ntimes (loop, ratio); + + /* Reduce loop iterations by the vectorization factor. */ + scale_loop_profile (loop, GCOV_COMPUTE_SCALE (1, vectorization_factor), + expected_iterations / vectorization_factor); + loop->nb_iterations_upper_bound + = loop->nb_iterations_upper_bound.udiv (double_int::from_uhwi (vectorization_factor), + FLOOR_DIV_EXPR); + if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) + && loop->nb_iterations_upper_bound != double_int_zero) + loop->nb_iterations_upper_bound = loop->nb_iterations_upper_bound - double_int_one; + if (loop->any_estimate) + { + loop->nb_iterations_estimate + = loop->nb_iterations_estimate.udiv (double_int::from_uhwi (vectorization_factor), + FLOOR_DIV_EXPR); + if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) + && loop->nb_iterations_estimate != double_int_zero) + loop->nb_iterations_estimate = loop->nb_iterations_estimate - double_int_one; + } + + if (dump_enabled_p ()) + { + dump_printf_loc (MSG_NOTE, vect_location, + "LOOP VECTORIZED\n"); + if (loop->inner) + dump_printf_loc (MSG_NOTE, vect_location, + "OUTER LOOP VECTORIZED\n"); + dump_printf (MSG_NOTE, "\n"); + } +} |