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+/* Loop Vectorization
+ Copyright (C) 2003, 2004, 2005, 2006, 2007, 2008, 2009 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 "tm.h"
+#include "ggc.h"
+#include "tree.h"
+#include "basic-block.h"
+#include "diagnostic.h"
+#include "tree-flow.h"
+#include "tree-dump.h"
+#include "cfgloop.h"
+#include "cfglayout.h"
+#include "expr.h"
+#include "recog.h"
+#include "optabs.h"
+#include "params.h"
+#include "toplev.h"
+#include "tree-chrec.h"
+#include "tree-scalar-evolution.h"
+#include "tree-vectorizer.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) - "UNITS_PER_SIMD_WORD". Targets that can
+ support different sizes of vectors, for now will need to specify one value
+ for "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)->insn_code). 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
+*/
+
+/* 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;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== vect_determine_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);
+ stmt_info = vinfo_for_stmt (phi);
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "==> examining phi: ");
+ print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
+ }
+
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "get vectype for scalar type: ");
+ print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
+ }
+
+ vectype = get_vectype_for_scalar_type (scalar_type);
+ if (!vectype)
+ {
+ if (vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
+ {
+ fprintf (vect_dump,
+ "not vectorized: unsupported data-type ");
+ print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
+ }
+ return false;
+ }
+ STMT_VINFO_VECTYPE (stmt_info) = vectype;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "vectype: ");
+ print_generic_expr (vect_dump, vectype, TDF_SLIM);
+ }
+
+ nunits = TYPE_VECTOR_SUBPARTS (vectype);
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "nunits = %d", nunits);
+
+ if (!vectorization_factor
+ || (nunits > vectorization_factor))
+ vectorization_factor = nunits;
+ }
+ }
+
+ for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
+ {
+ gimple stmt = gsi_stmt (si);
+ stmt_info = vinfo_for_stmt (stmt);
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "==> examining statement: ");
+ print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
+ }
+
+ 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))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "skip.");
+ continue;
+ }
+
+ if (gimple_get_lhs (stmt) == NULL_TREE)
+ {
+ if (vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
+ {
+ fprintf (vect_dump, "not vectorized: irregular stmt.");
+ print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
+ }
+ return false;
+ }
+
+ if (VECTOR_MODE_P (TYPE_MODE (gimple_expr_type (stmt))))
+ {
+ if (vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
+ {
+ fprintf (vect_dump, "not vectorized: vector stmt in loop:");
+ print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
+ }
+ 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));
+ vectype = STMT_VINFO_VECTYPE (stmt_info);
+ }
+ else
+ {
+
+ gcc_assert (! STMT_VINFO_DATA_REF (stmt_info)
+ && !is_pattern_stmt_p (stmt_info));
+
+ scalar_type = vect_get_smallest_scalar_type (stmt, &dummy,
+ &dummy);
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "get vectype for scalar type: ");
+ print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
+ }
+
+ vectype = get_vectype_for_scalar_type (scalar_type);
+ if (!vectype)
+ {
+ if (vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
+ {
+ fprintf (vect_dump,
+ "not vectorized: unsupported data-type ");
+ print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
+ }
+ return false;
+ }
+ STMT_VINFO_VECTYPE (stmt_info) = vectype;
+ }
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "vectype: ");
+ print_generic_expr (vect_dump, vectype, TDF_SLIM);
+ }
+
+ nunits = TYPE_VECTOR_SUBPARTS (vectype);
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "nunits = %d", nunits);
+
+ if (!vectorization_factor
+ || (nunits > vectorization_factor))
+ vectorization_factor = nunits;
+
+ }
+ }
+
+ /* TODO: Analyze cost. Decide if worth while to vectorize. */
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "vectorization factor = %d", vectorization_factor);
+ if (vectorization_factor <= 1)
+ {
+ if (vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
+ fprintf (vect_dump, "not vectorized: unsupported data-type");
+ 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 with constant step. */
+
+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);
+
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "step: ");
+ print_generic_expr (vect_dump, step_expr, TDF_SLIM);
+ fprintf (vect_dump, ", init: ");
+ print_generic_expr (vect_dump, init_expr, TDF_SLIM);
+ }
+
+ *init = init_expr;
+ *step = step_expr;
+
+ if (TREE_CODE (step_expr) != INTEGER_CST)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "step unknown.");
+ 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 dumy;
+ VEC(gimple,heap) *worklist = VEC_alloc (gimple, heap, 64);
+ gimple_stmt_iterator gsi;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== vect_analyze_scalar_cycles ===");
+
+ /* First - identify all inductions. */
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "Analyze phi: ");
+ print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
+ }
+
+ /* Skip virtual phi's. The data dependences that are associated with
+ virtual defs/uses (i.e., memory accesses) are analyzed elsewhere. */
+ if (!is_gimple_reg (SSA_NAME_VAR (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 && vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "Access function of PHI: ");
+ print_generic_expr (vect_dump, access_fn, TDF_SLIM);
+ }
+
+ if (!access_fn
+ || !vect_is_simple_iv_evolution (loop->num, access_fn, &dumy, &dumy))
+ {
+ VEC_safe_push (gimple, heap, worklist, phi);
+ continue;
+ }
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Detected induction.");
+ STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_induction_def;
+ }
+
+
+ /* Second - identify all reductions. */
+ while (VEC_length (gimple, worklist) > 0)
+ {
+ gimple phi = VEC_pop (gimple, worklist);
+ tree def = PHI_RESULT (phi);
+ stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
+ gimple reduc_stmt;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "Analyze phi: ");
+ print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
+ }
+
+ gcc_assert (is_gimple_reg (SSA_NAME_VAR (def)));
+ gcc_assert (STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_unknown_def_type);
+
+ reduc_stmt = vect_is_simple_reduction (loop_vinfo, phi);
+ if (reduc_stmt)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Detected reduction.");
+ STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_reduction_def;
+ STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
+ vect_reduction_def;
+ }
+ else
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Unknown def-use cycle pattern.");
+ }
+
+ VEC_free (gimple, heap, worklist);
+ return;
+}
+
+
+/* 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.
+ If an expression that represents the number of iterations
+ can be constructed, place it in NUMBER_OF_ITERATIONS.
+ Return the loop exit condition. */
+
+static gimple
+vect_get_loop_niters (struct loop *loop, tree *number_of_iterations)
+{
+ tree niters;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== get_loop_niters ===");
+
+ niters = number_of_exit_cond_executions (loop);
+
+ if (niters != NULL_TREE
+ && niters != chrec_dont_know)
+ {
+ *number_of_iterations = niters;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "==> get_loop_niters:" );
+ print_generic_expr (vect_dump, *number_of_iterations, TDF_SLIM);
+ }
+ }
+
+ 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));
+ }
+
+ 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));
+ }
+ }
+ }
+
+ /* 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_NITERS (res) = NULL;
+ LOOP_VINFO_NITERS_UNCHANGED (res) = NULL;
+ LOOP_VINFO_COST_MODEL_MIN_ITERS (res) = 0;
+ LOOP_VINFO_VECTORIZABLE_P (res) = 0;
+ LOOP_PEELING_FOR_ALIGNMENT (res) = 0;
+ LOOP_VINFO_VECT_FACTOR (res) = 0;
+ LOOP_VINFO_DATAREFS (res) = VEC_alloc (data_reference_p, heap, 10);
+ LOOP_VINFO_DDRS (res) = VEC_alloc (ddr_p, heap, 10 * 10);
+ LOOP_VINFO_UNALIGNED_DR (res) = NULL;
+ LOOP_VINFO_MAY_MISALIGN_STMTS (res) =
+ VEC_alloc (gimple, heap,
+ PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIGNMENT_CHECKS));
+ LOOP_VINFO_MAY_ALIAS_DDRS (res) =
+ VEC_alloc (ddr_p, heap,
+ PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS));
+ LOOP_VINFO_STRIDED_STORES (res) = VEC_alloc (gimple, heap, 10);
+ LOOP_VINFO_SLP_INSTANCES (res) = VEC_alloc (slp_instance, heap, 10);
+ LOOP_VINFO_SLP_UNROLLING_FACTOR (res) = 1;
+
+ 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, heap) *slp_instances;
+ slp_instance instance;
+
+ if (!loop_vinfo)
+ return;
+
+ loop = LOOP_VINFO_LOOP (loop_vinfo);
+
+ bbs = LOOP_VINFO_BBS (loop_vinfo);
+ nbbs = loop->num_nodes;
+
+ if (!clean_stmts)
+ {
+ free (LOOP_VINFO_BBS (loop_vinfo));
+ free_data_refs (LOOP_VINFO_DATAREFS (loop_vinfo));
+ free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo));
+ VEC_free (gimple, heap, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
+
+ free (loop_vinfo);
+ loop->aux = NULL;
+ return;
+ }
+
+ 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);
+ stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
+
+ if (stmt_info)
+ {
+ /* Check if this is a "pattern stmt" (introduced by the
+ vectorizer during the pattern recognition pass). */
+ bool remove_stmt_p = false;
+ gimple orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
+ if (orig_stmt)
+ {
+ stmt_vec_info orig_stmt_info = vinfo_for_stmt (orig_stmt);
+ if (orig_stmt_info
+ && STMT_VINFO_IN_PATTERN_P (orig_stmt_info))
+ remove_stmt_p = true;
+ }
+
+ /* Free stmt_vec_info. */
+ free_stmt_vec_info (stmt);
+
+ /* Remove dead "pattern stmts". */
+ if (remove_stmt_p)
+ gsi_remove (&si, true);
+ }
+ gsi_next (&si);
+ }
+ }
+
+ free (LOOP_VINFO_BBS (loop_vinfo));
+ free_data_refs (LOOP_VINFO_DATAREFS (loop_vinfo));
+ free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo));
+ VEC_free (gimple, heap, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
+ VEC_free (ddr_p, heap, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo));
+ slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
+ for (j = 0; VEC_iterate (slp_instance, slp_instances, j, instance); j++)
+ vect_free_slp_instance (instance);
+
+ VEC_free (slp_instance, heap, LOOP_VINFO_SLP_INSTANCES (loop_vinfo));
+ VEC_free (gimple, heap, LOOP_VINFO_STRIDED_STORES (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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "===== analyze_loop_nest_1 =====");
+
+ /* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */
+
+ loop_vinfo = vect_analyze_loop_form (loop);
+ if (!loop_vinfo)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad inner-loop form.");
+ 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;
+ loop_vec_info inner_loop_vinfo = NULL;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== vect_analyze_loop_form ===");
+
+ /* 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 (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: too many BBs in loop.");
+ return NULL;
+ }
+
+ if (empty_block_p (loop->header))
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: empty loop.");
+ return NULL;
+ }
+ }
+ else
+ {
+ struct loop *innerloop = loop->inner;
+ edge backedge, 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 (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: multiple nested loops.");
+ return NULL;
+ }
+
+ /* Analyze the inner-loop. */
+ inner_loop_vinfo = vect_analyze_loop_1 (loop->inner);
+ if (!inner_loop_vinfo)
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: Bad inner loop.");
+ return NULL;
+ }
+
+ if (!expr_invariant_in_loop_p (loop,
+ LOOP_VINFO_NITERS (inner_loop_vinfo)))
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump,
+ "not vectorized: inner-loop count not invariant.");
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+
+ if (loop->num_nodes != 5)
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: too many BBs in loop.");
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+
+ gcc_assert (EDGE_COUNT (innerloop->header->preds) == 2);
+ backedge = EDGE_PRED (innerloop->header, 1);
+ entryedge = EDGE_PRED (innerloop->header, 0);
+ if (EDGE_PRED (innerloop->header, 0)->src == innerloop->latch)
+ {
+ backedge = EDGE_PRED (innerloop->header, 0);
+ 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 (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: unsupported outerloop form.");
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Considering outer-loop vectorization.");
+ }
+
+ if (!single_exit (loop)
+ || EDGE_COUNT (loop->header->preds) != 2)
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ {
+ if (!single_exit (loop))
+ fprintf (vect_dump, "not vectorized: multiple exits.");
+ else if (EDGE_COUNT (loop->header->preds) != 2)
+ fprintf (vect_dump, "not vectorized: too many incoming edges.");
+ }
+ 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)
+ || phi_nodes (loop->latch))
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: unexpected loop form.");
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "split exit edge.");
+ }
+ else
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: abnormal loop exit edge.");
+ if (inner_loop_vinfo)
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+ }
+
+ loop_cond = vect_get_loop_niters (loop, &number_of_iterations);
+ if (!loop_cond)
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "not vectorized: complicated exit condition.");
+ if (inner_loop_vinfo)
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+
+ if (!number_of_iterations)
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump,
+ "not vectorized: number of iterations cannot be computed.");
+ if (inner_loop_vinfo)
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+
+ if (chrec_contains_undetermined (number_of_iterations))
+ {
+ if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
+ fprintf (vect_dump, "Infinite number of iterations.");
+ if (inner_loop_vinfo)
+ destroy_loop_vec_info (inner_loop_vinfo, true);
+ return NULL;
+ }
+
+ if (!NITERS_KNOWN_P (number_of_iterations))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "Symbolic number of iterations is ");
+ print_generic_expr (vect_dump, number_of_iterations, TDF_DETAILS);
+ }
+ }
+ else if (TREE_INT_CST_LOW (number_of_iterations) == 0)
+ {
+ if (vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
+ fprintf (vect_dump, "not vectorized: number of iterations = 0.");
+ if (inner_loop_vinfo)
+ destroy_loop_vec_info (inner_loop_vinfo, false);
+ return NULL;
+ }
+
+ loop_vinfo = new_loop_vec_info (loop);
+ LOOP_VINFO_NITERS (loop_vinfo) = number_of_iterations;
+ LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = number_of_iterations;
+
+ 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.
+
+ 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)
+{
+ bool ok;
+ loop_vec_info loop_vinfo;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "===== analyze_loop_nest =====");
+
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "outer-loop already vectorized.");
+ return NULL;
+ }
+
+ /* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */
+
+ loop_vinfo = vect_analyze_loop_form (loop);
+ if (!loop_vinfo)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad loop form.");
+ return NULL;
+ }
+
+ /* Find all data references in the loop (which correspond to vdefs/vuses)
+ and analyze their evolution in the loop.
+
+ FORNOW: Handle only simple, array references, which
+ alignment can be forced, and aligned pointer-references. */
+
+ ok = vect_analyze_data_refs (loop_vinfo);
+ if (!ok)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad data references.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* 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);
+
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "unexpected pattern.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* 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);
+ if (!ok)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad data alignment.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ ok = vect_determine_vectorization_factor (loop_vinfo);
+ if (!ok)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "can't determine vectorization factor.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* Analyze data dependences between the data-refs in the loop.
+ FORNOW: fail at the first data dependence that we encounter. */
+
+ ok = vect_analyze_data_ref_dependences (loop_vinfo);
+ if (!ok)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad data dependence.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* 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);
+ if (!ok)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad data access.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "too long list of versioning for alias "
+ "run-time tests.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* Check the SLP opportunities in the loop, analyze and build SLP trees. */
+ ok = vect_analyze_slp (loop_vinfo);
+ if (ok)
+ {
+ /* Decide which possible SLP instances to SLP. */
+ vect_make_slp_decision (loop_vinfo);
+
+ /* Find stmts that need to be both vectorized and SLPed. */
+ vect_detect_hybrid_slp (loop_vinfo);
+ }
+
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad data alignment.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ /* Scan all the operations in the loop and make sure they are
+ vectorizable. */
+
+ ok = vect_analyze_operations (loop_vinfo);
+ if (!ok)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "bad operation or unsupported loop bound.");
+ destroy_loop_vec_info (loop_vinfo, true);
+ return NULL;
+ }
+
+ LOOP_VINFO_VECTORIZABLE_P (loop_vinfo) = 1;
+
+ return loop_vinfo;
+}
+
+
+/* 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).
+
+ Return TRUE if a corresponding REDUC_CODE was found, FALSE otherwise. */
+
+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;
+
+ 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 (gimple stmt, const char *msg)
+{
+ fprintf (vect_dump, "%s", msg);
+ print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
+}
+
+
+/* Function vect_is_simple_reduction
+
+ 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)
+
+ such that:
+ 1. operation is commutative and associative and it is safe to
+ change the order of the computation.
+ 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.
+
+ Condition 1 is tested here.
+ Conditions 2,3 are tested in vect_mark_stmts_to_be_vectorized. */
+
+gimple
+vect_is_simple_reduction (loop_vec_info loop_info, gimple phi)
+{
+ 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, def2;
+ enum tree_code code;
+ tree op1, op2;
+ tree type;
+ int nloop_uses;
+ tree name;
+ imm_use_iterator imm_iter;
+ use_operand_p use_p;
+
+ gcc_assert (loop == vect_loop || flow_loop_nested_p (vect_loop, loop));
+
+ name = PHI_RESULT (phi);
+ nloop_uses = 0;
+ FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
+ {
+ gimple use_stmt = USE_STMT (use_p);
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "reduction used in loop.");
+ return NULL;
+ }
+ }
+
+ if (TREE_CODE (loop_arg) != SSA_NAME)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "reduction: not ssa_name: ");
+ print_generic_expr (vect_dump, loop_arg, TDF_SLIM);
+ }
+ return NULL;
+ }
+
+ def_stmt = SSA_NAME_DEF_STMT (loop_arg);
+ if (!def_stmt)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "reduction: no def_stmt.");
+ return NULL;
+ }
+
+ if (!is_gimple_assign (def_stmt))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ print_gimple_stmt (vect_dump, def_stmt, 0, TDF_SLIM);
+ return NULL;
+ }
+
+ name = gimple_assign_lhs (def_stmt);
+ nloop_uses = 0;
+ FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
+ {
+ gimple use_stmt = USE_STMT (use_p);
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "reduction used in loop.");
+ return NULL;
+ }
+ }
+
+ code = gimple_assign_rhs_code (def_stmt);
+
+ if (!commutative_tree_code (code) || !associative_tree_code (code))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "reduction: not commutative/associative: ");
+ return NULL;
+ }
+
+ if (get_gimple_rhs_class (code) != GIMPLE_BINARY_RHS)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "reduction: not binary operation: ");
+ return NULL;
+ }
+
+ op1 = gimple_assign_rhs1 (def_stmt);
+ op2 = gimple_assign_rhs2 (def_stmt);
+ if (TREE_CODE (op1) != SSA_NAME || TREE_CODE (op2) != SSA_NAME)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "reduction: uses not ssa_names: ");
+ return NULL;
+ }
+
+ /* Check that it's ok to change the order of the computation. */
+ type = TREE_TYPE (gimple_assign_lhs (def_stmt));
+ if (TYPE_MAIN_VARIANT (type) != TYPE_MAIN_VARIANT (TREE_TYPE (op1))
+ || TYPE_MAIN_VARIANT (type) != TYPE_MAIN_VARIANT (TREE_TYPE (op2)))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "reduction: multiple types: operation type: ");
+ print_generic_expr (vect_dump, type, TDF_SLIM);
+ fprintf (vect_dump, ", operands types: ");
+ print_generic_expr (vect_dump, TREE_TYPE (op1), TDF_SLIM);
+ fprintf (vect_dump, ",");
+ print_generic_expr (vect_dump, TREE_TYPE (op2), TDF_SLIM);
+ }
+ return NULL;
+ }
+
+ /* 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
+ && !nested_in_vect_loop_p (vect_loop, def_stmt))
+ {
+ /* Changing the order of operations changes the semantics. */
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "reduction: unsafe fp math optimization: ");
+ return NULL;
+ }
+ else if (INTEGRAL_TYPE_P (type) && TYPE_OVERFLOW_TRAPS (type)
+ && !nested_in_vect_loop_p (vect_loop, def_stmt))
+ {
+ /* Changing the order of operations changes the semantics. */
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "reduction: unsafe int math optimization: ");
+ return NULL;
+ }
+ else if (SAT_FIXED_POINT_TYPE_P (type))
+ {
+ /* Changing the order of operations changes the semantics. */
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt,
+ "reduction: unsafe fixed-point math optimization: ");
+ return NULL;
+ }
+
+ /* 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.
+ */
+ def1 = SSA_NAME_DEF_STMT (op1);
+ def2 = SSA_NAME_DEF_STMT (op2);
+ if (!def1 || !def2 || gimple_nop_p (def1) || gimple_nop_p (def2))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (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_loop_def"),
+ or it's an induction (defined by a loop-header phi-node). */
+
+ if (def2 == phi
+ && flow_bb_inside_loop_p (loop, gimple_bb (def1))
+ && (is_gimple_assign (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_loop_def
+ && !is_loop_header_bb_p (gimple_bb (def1)))))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "detected reduction:");
+ return def_stmt;
+ }
+ else if (def1 == phi
+ && flow_bb_inside_loop_p (loop, gimple_bb (def2))
+ && (is_gimple_assign (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_loop_def
+ && !is_loop_header_bb_p (gimple_bb (def2)))))
+ {
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt ,
+ "detected reduction: need to swap operands:");
+ swap_tree_operands (def_stmt, gimple_assign_rhs1_ptr (def_stmt),
+ gimple_assign_rhs2_ptr (def_stmt));
+ return def_stmt;
+ }
+ else
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ report_vect_op (def_stmt, "reduction: unknown pattern.");
+ return NULL;
+ }
+}
+
+
+/* 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.
+
+ TODO: Take profile info into account before making vectorization
+ decisions, if available. */
+
+int
+vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo)
+{
+ int i;
+ int min_profitable_iters;
+ int peel_iters_prologue;
+ int peel_iters_epilogue;
+ int vec_inside_cost = 0;
+ int vec_outside_cost = 0;
+ int scalar_single_iter_cost = 0;
+ int scalar_outside_cost = 0;
+ int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
+ struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
+ basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
+ int nbbs = loop->num_nodes;
+ int byte_misalign = LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo);
+ int peel_guard_costs = 0;
+ int innerloop_iters = 0, factor;
+ VEC (slp_instance, heap) *slp_instances;
+ slp_instance instance;
+
+ /* Cost model disabled. */
+ if (!flag_vect_cost_model)
+ {
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model disabled.");
+ return 0;
+ }
+
+ /* Requires loop versioning tests to handle misalignment. */
+ if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo)))
+ {
+ /* FIXME: Make cost depend on complexity of individual check. */
+ vec_outside_cost +=
+ VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model: Adding cost of checks for loop "
+ "versioning to treat misalignment.\n");
+ }
+
+ if (VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
+ {
+ /* FIXME: Make cost depend on complexity of individual check. */
+ vec_outside_cost +=
+ VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo));
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model: Adding cost of checks for loop "
+ "versioning aliasing.\n");
+ }
+
+ if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
+ || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
+ {
+ vec_outside_cost += TARG_COND_TAKEN_BRANCH_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. */
+ 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);
+ /* Skip stmts that are not vectorized inside the loop. */
+ if (!STMT_VINFO_RELEVANT_P (stmt_info)
+ && (!STMT_VINFO_LIVE_P (stmt_info)
+ || STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def))
+ continue;
+ scalar_single_iter_cost += cost_for_stmt (stmt) * factor;
+ vec_inside_cost += STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) * factor;
+ /* FIXME: for stmts in the inner-loop in outer-loop vectorization,
+ some of the "outside" costs are generated inside the outer-loop. */
+ vec_outside_cost += STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info);
+ }
+ }
+
+ /* 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 (byte_misalign < 0)
+ {
+ peel_iters_prologue = vf/2;
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model: "
+ "prologue peel iters set to vf/2.");
+
+ /* If peeling for alignment is unknown, loop bound of main loop becomes
+ unknown. */
+ peel_iters_epilogue = vf/2;
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model: "
+ "epilogue peel iters set to vf/2 because "
+ "peeling for alignment is unknown .");
+
+ /* 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. */
+ peel_guard_costs += 2 * (TARG_COND_TAKEN_BRANCH_COST
+ + TARG_COND_NOT_TAKEN_BRANCH_COST);
+ }
+ else
+ {
+ if (byte_misalign)
+ {
+ struct data_reference *dr = LOOP_VINFO_UNALIGNED_DR (loop_vinfo);
+ int element_size = GET_MODE_SIZE (TYPE_MODE (TREE_TYPE (DR_REF (dr))));
+ tree vectype = STMT_VINFO_VECTYPE (vinfo_for_stmt (DR_STMT (dr)));
+ int nelements = TYPE_VECTOR_SUBPARTS (vectype);
+
+ peel_iters_prologue = nelements - (byte_misalign / element_size);
+ }
+ else
+ peel_iters_prologue = 0;
+
+ if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
+ {
+ peel_iters_epilogue = vf/2;
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model: "
+ "epilogue peel iters set to vf/2 because "
+ "loop iterations are unknown .");
+
+ /* If peeled iterations are known but number of scalar loop
+ iterations are unknown, count a taken branch per peeled loop. */
+ peel_guard_costs += 2 * TARG_COND_TAKEN_BRANCH_COST;
+
+ }
+ 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;
+ }
+ }
+
+ vec_outside_cost += (peel_iters_prologue * scalar_single_iter_cost)
+ + (peel_iters_epilogue * scalar_single_iter_cost)
+ + peel_guard_costs;
+
+ /* 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)
+ || VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
+ || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
+ {
+ /* Cost model check occurs at versioning. */
+ if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
+ || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
+ scalar_outside_cost += TARG_COND_NOT_TAKEN_BRANCH_COST;
+ else
+ {
+ /* Cost model check occurs at prologue generation. */
+ if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo) < 0)
+ scalar_outside_cost += 2 * TARG_COND_TAKEN_BRANCH_COST
+ + TARG_COND_NOT_TAKEN_BRANCH_COST;
+ /* Cost model check occurs at epilogue generation. */
+ else
+ scalar_outside_cost += 2 * TARG_COND_TAKEN_BRANCH_COST;
+ }
+ }
+
+ /* Add SLP costs. */
+ slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
+ for (i = 0; VEC_iterate (slp_instance, slp_instances, i, instance); i++)
+ {
+ vec_outside_cost += SLP_INSTANCE_OUTSIDE_OF_LOOP_COST (instance);
+ vec_inside_cost += SLP_INSTANCE_INSIDE_OF_LOOP_COST (instance);
+ }
+
+ /* 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) > 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)
+ <= ((vec_inside_cost * min_profitable_iters)
+ + ((vec_outside_cost - scalar_outside_cost) * vf)))
+ min_profitable_iters++;
+ }
+ }
+ /* vector version will never be profitable. */
+ else
+ {
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "cost model: vector iteration cost = %d "
+ "is divisible by scalar iteration cost = %d by a factor "
+ "greater than or equal to the vectorization factor = %d .",
+ vec_inside_cost, scalar_single_iter_cost, vf);
+ return -1;
+ }
+
+ if (vect_print_dump_info (REPORT_COST))
+ {
+ fprintf (vect_dump, "Cost model analysis: \n");
+ fprintf (vect_dump, " Vector inside of loop cost: %d\n",
+ vec_inside_cost);
+ fprintf (vect_dump, " Vector outside of loop cost: %d\n",
+ vec_outside_cost);
+ fprintf (vect_dump, " Scalar iteration cost: %d\n",
+ scalar_single_iter_cost);
+ fprintf (vect_dump, " Scalar outside cost: %d\n", scalar_outside_cost);
+ fprintf (vect_dump, " prologue iterations: %d\n",
+ peel_iters_prologue);
+ fprintf (vect_dump, " epilogue iterations: %d\n",
+ peel_iters_epilogue);
+ fprintf (vect_dump, " Calculated minimum iters for profitability: %d\n",
+ min_profitable_iters);
+ }
+
+ 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 (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, " Profitability threshold = %d\n",
+ min_profitable_iters);
+
+ return min_profitable_iters;
+}
+
+
+/* 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 outer_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);
+
+
+ /* Cost of reduction op inside loop. */
+ STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) += ncopies * TARG_VEC_STMT_COST;
+
+ 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;
+ default:
+ gcc_unreachable ();
+ }
+
+ vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
+ if (!vectype)
+ {
+ if (vect_print_dump_info (REPORT_COST))
+ {
+ fprintf (vect_dump, "unsupported data-type ");
+ print_generic_expr (vect_dump, TREE_TYPE (reduction_op), TDF_SLIM);
+ }
+ 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. */
+ outer_cost += TARG_SCALAR_TO_VEC_COST;
+
+ /* 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 < NUM_TREE_CODES)
+ outer_cost += TARG_VEC_STMT_COST + TARG_VEC_TO_SCALAR_COST;
+ else
+ {
+ int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
+ tree bitsize =
+ TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt)));
+ int element_bitsize = tree_low_cst (bitsize, 1);
+ 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)->insn_code != CODE_FOR_nothing
+ && optab_handler (vec_shr_optab, mode)->insn_code != CODE_FOR_nothing)
+ /* Final reduction via vector shifts and the reduction operator. Also
+ requires scalar extract. */
+ outer_cost += ((exact_log2(nelements) * 2) * TARG_VEC_STMT_COST
+ + TARG_VEC_TO_SCALAR_COST);
+ else
+ /* Use extracts and reduction op for final reduction. For N elements,
+ we have N extracts and N-1 reduction ops. */
+ outer_cost += ((nelements + nelements - 1) * TARG_VEC_STMT_COST);
+ }
+ }
+
+ STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info) = outer_cost;
+
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "vect_model_reduction_cost: inside_cost = %d, "
+ "outside_cost = %d .", STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info),
+ STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info));
+
+ 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 cost for vec_loop. */
+ STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) = ncopies * TARG_VEC_STMT_COST;
+ /* prologue cost for vec_init and vec_step. */
+ STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info) = 2 * TARG_SCALAR_TO_VEC_COST;
+
+ if (vect_print_dump_info (REPORT_COST))
+ fprintf (vect_dump, "vect_model_induction_cost: inside_cost = %d, "
+ "outside_cost = %d .", STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info),
+ STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info));
+}
+
+
+/* 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 scalar_type = TREE_TYPE (gimple_phi_result (iv_phi));
+ tree vectype;
+ int nunits;
+ edge pe = loop_preheader_edge (loop);
+ struct loop *iv_loop;
+ basic_block new_bb;
+ tree vec, vec_init, vec_step, t;
+ tree access_fn;
+ 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;
+ bool ok;
+ 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);
+
+ vectype = get_vectype_for_scalar_type (scalar_type);
+ gcc_assert (vectype);
+ nunits = TYPE_VECTOR_SUBPARTS (vectype);
+ ncopies = vf / nunits;
+
+ gcc_assert (phi_info);
+ gcc_assert (ncopies >= 1);
+
+ /* Find the first insertion point in the BB. */
+ si = gsi_after_labels (bb);
+
+ if (INTEGRAL_TYPE_P (scalar_type) || POINTER_TYPE_P (scalar_type))
+ step_expr = build_int_cst (scalar_type, 0);
+ else
+ step_expr = build_real (scalar_type, dconst0);
+
+ /* 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);
+
+ access_fn = analyze_scalar_evolution (iv_loop, PHI_RESULT (iv_phi));
+ gcc_assert (access_fn);
+ ok = vect_is_simple_iv_evolution (iv_loop->num, access_fn,
+ &init_expr, &step_expr);
+ gcc_assert (ok);
+ pe = loop_preheader_edge (iv_loop);
+
+ /* 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. */
+ tree iv_def = PHI_ARG_DEF_FROM_EDGE (iv_phi, loop_preheader_edge (iv_loop));
+ vec_init = vect_get_vec_def_for_operand (iv_def, iv_phi, NULL);
+ }
+ else
+ {
+ /* 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 (scalar_type, vect_scalar_var, "var_");
+ add_referenced_var (new_var);
+
+ new_name = force_gimple_operand (init_expr, &stmts, false, new_var);
+ if (stmts)
+ {
+ new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
+ gcc_assert (!new_bb);
+ }
+
+ t = NULL_TREE;
+ t = tree_cons (NULL_TREE, init_expr, t);
+ for (i = 1; i < nunits; i++)
+ {
+ /* Create: new_name_i = new_name + step_expr */
+ enum tree_code code = POINTER_TYPE_P (scalar_type)
+ ? POINTER_PLUS_EXPR : PLUS_EXPR;
+ init_stmt = gimple_build_assign_with_ops (code, new_var,
+ new_name, step_expr);
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "created new init_stmt: ");
+ print_gimple_stmt (vect_dump, init_stmt, 0, TDF_SLIM);
+ }
+ t = tree_cons (NULL_TREE, new_name, t);
+ }
+ /* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1] */
+ vec = build_constructor_from_list (vectype, nreverse (t));
+ vec_init = vect_init_vector (iv_phi, 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] */
+ expr = build_int_cst (scalar_type, vf);
+ new_name = fold_build2 (MULT_EXPR, scalar_type, expr, step_expr);
+ }
+
+ t = NULL_TREE;
+ for (i = 0; i < nunits; i++)
+ t = tree_cons (NULL_TREE, unshare_expr (new_name), t);
+ gcc_assert (CONSTANT_CLASS_P (new_name));
+ vec = build_vector (vectype, t);
+ vec_step = vect_init_vector (iv_phi, vec, vectype, 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_");
+ add_referenced_var (vec_dest);
+ induction_phi = create_phi_node (vec_dest, iv_loop->header);
+ set_vinfo_for_stmt (induction_phi,
+ new_stmt_vec_info (induction_phi, loop_vinfo));
+ 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));
+
+ /* Set the arguments of the phi node: */
+ add_phi_arg (induction_phi, vec_init, pe);
+ add_phi_arg (induction_phi, vec_def, loop_latch_edge (iv_loop));
+
+
+ /* 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. */
+ expr = build_int_cst (scalar_type, nunits);
+ new_name = fold_build2 (MULT_EXPR, scalar_type, expr, step_expr);
+ t = NULL_TREE;
+ for (i = 0; i < nunits; i++)
+ t = tree_cons (NULL_TREE, unshare_expr (new_name), t);
+ gcc_assert (CONSTANT_CLASS_P (new_name));
+ vec = build_vector (vectype, t);
+ vec_step = vect_init_vector (iv_phi, vec, vectype, 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);
+ set_vinfo_for_stmt (new_stmt,
+ new_stmt_vec_info (new_stmt, loop_vinfo));
+ 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)
+ {
+ if (!flow_bb_inside_loop_p (iv_loop, gimple_bb (USE_STMT (use_p))))
+ {
+ exit_phi = USE_STMT (use_p);
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "vector of inductions after inner-loop:");
+ print_gimple_stmt (vect_dump, new_stmt, 0, TDF_SLIM);
+ }
+ }
+ }
+
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "transform induction: created def-use cycle: ");
+ print_gimple_stmt (vect_dump, induction_phi, 0, TDF_SLIM);
+ fprintf (vect_dump, "\n");
+ print_gimple_stmt (vect_dump, SSA_NAME_DEF_STMT (vec_def), 0, TDF_SLIM);
+ }
+
+ STMT_VINFO_VEC_STMT (phi_info) = 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: [0,0,...,0,0]
+ mult: [1,1,...,1,1]
+ min/max: [init_val,init_val,..,init_val,init_val]
+ bit and/or: [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: [0,0,...,0,init_val]
+ mult: [1,1,...,1,init_val]
+ min/max: [init_val,init_val,...,init_val]
+ bit and/or: [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).
+ 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 vectype = STMT_VINFO_VECTYPE (stmt_vinfo);
+ int nunits = TYPE_VECTOR_SUBPARTS (vectype);
+ tree scalar_type = TREE_TYPE (vectype);
+ enum tree_code code = gimple_assign_rhs_code (stmt);
+ tree type = TREE_TYPE (init_val);
+ tree vecdef;
+ tree def_for_init;
+ tree init_def;
+ tree t = NULL_TREE;
+ int i;
+ bool nested_in_vect_loop = false;
+
+ gcc_assert (POINTER_TYPE_P (type) || INTEGRAL_TYPE_P (type) || SCALAR_FLOAT_TYPE_P (type));
+ if (nested_in_vect_loop_p (loop, stmt))
+ nested_in_vect_loop = true;
+ else
+ gcc_assert (loop == (gimple_bb (stmt))->loop_father);
+
+ vecdef = vect_get_vec_def_for_operand (init_val, stmt, NULL);
+
+ switch (code)
+ {
+ case WIDEN_SUM_EXPR:
+ case DOT_PROD_EXPR:
+ case PLUS_EXPR:
+ if (nested_in_vect_loop)
+ *adjustment_def = vecdef;
+ else
+ *adjustment_def = init_val;
+ /* Create a vector of zeros for init_def. */
+ if (SCALAR_FLOAT_TYPE_P (scalar_type))
+ def_for_init = build_real (scalar_type, dconst0);
+ else
+ def_for_init = build_int_cst (scalar_type, 0);
+
+ for (i = nunits - 1; i >= 0; --i)
+ t = tree_cons (NULL_TREE, def_for_init, t);
+ init_def = build_vector (vectype, t);
+ break;
+
+ case MIN_EXPR:
+ case MAX_EXPR:
+ *adjustment_def = NULL_TREE;
+ init_def = vecdef;
+ 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_DEF is a vector of partial results.
+ REDUC_CODE is the tree-code for the epilog reduction.
+ 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.
+ STMT is the scalar reduction stmt that is being vectorized.
+ REDUCTION_PHI is the phi-node that carries the reduction computation.
+
+ This function:
+ 1. Creates the reduction def-use cycle: sets the arguments for
+ REDUCTION_PHI:
+ The loop-entry argument is the vectorized initial-value of the reduction.
+ The loop-latch argument is VECT_DEF - the vector of partial sums.
+ 2. "Reduces" the vector of partial results VECT_DEF 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 (tree vect_def, gimple stmt,
+ int ncopies,
+ enum tree_code reduc_code,
+ gimple reduction_phi)
+{
+ 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);
+ 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;
+ tree new_name;
+ gimple epilog_stmt = NULL;
+ tree new_scalar_dest, new_dest;
+ gimple exit_phi;
+ tree bitsize, bitpos, bytesize;
+ enum tree_code code = gimple_assign_rhs_code (stmt);
+ tree adjustment_def;
+ tree vec_initial_def, def;
+ tree orig_name;
+ imm_use_iterator imm_iter;
+ use_operand_p use_p;
+ bool extract_scalar_result = false;
+ tree reduction_op, expr;
+ gimple orig_stmt;
+ gimple use_stmt;
+ bool nested_in_vect_loop = false;
+ VEC(gimple,heap) *phis = NULL;
+ enum vect_def_type dt = vect_unknown_def_type;
+ int j, i;
+
+ if (nested_in_vect_loop_p (loop, stmt))
+ {
+ loop = loop->inner;
+ nested_in_vect_loop = true;
+ }
+
+ 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;
+ 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 ***/
+
+ /* 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);
+
+ phi = reduction_phi;
+ def = vect_def;
+ for (j = 0; j < ncopies; j++)
+ {
+ /* 1.1 set the loop-entry arg of the reduction-phi: */
+ add_phi_arg (phi, vec_initial_def, loop_preheader_edge (loop));
+
+ /* 1.2 set the loop-latch arg for the reduction-phi: */
+ if (j > 0)
+ def = vect_get_vec_def_for_stmt_copy (dt, def);
+ add_phi_arg (phi, def, loop_latch_edge (loop));
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "transform reduction: created def-use cycle: ");
+ print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
+ fprintf (vect_dump, "\n");
+ print_gimple_stmt (vect_dump, SSA_NAME_DEF_STMT (def), 0, TDF_SLIM);
+ }
+
+ 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-phi to preserve loop-closed form:
+ v_out1 = phi <v_loop> */
+
+ exit_bb = single_exit (loop)->dest;
+ def = vect_def;
+ prev_phi_info = NULL;
+ for (j = 0; j < ncopies; j++)
+ {
+ phi = create_phi_node (SSA_NAME_VAR (vect_def), exit_bb);
+ set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, loop_vinfo));
+ if (j == 0)
+ new_phi = 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);
+ }
+ 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);
+ scalar_dest = gimple_assign_lhs (orig_stmt);
+ scalar_type = TREE_TYPE (scalar_dest);
+ new_scalar_dest = vect_create_destination_var (scalar_dest, NULL);
+ bitsize = TYPE_SIZE (scalar_type);
+ bytesize = TYPE_SIZE_UNIT (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. 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)
+ goto vect_finalize_reduction;
+
+ /* FORNOW */
+ gcc_assert (ncopies == 1);
+
+ /* 2.3 Create the reduction code, using one of the three schemes described
+ above. */
+
+ if (reduc_code < NUM_TREE_CODES)
+ {
+ tree tmp;
+
+ /*** Case 1: Create:
+ v_out2 = reduc_expr <v_out1> */
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Reduce using direct vector reduction.");
+
+ vec_dest = vect_create_destination_var (scalar_dest, vectype);
+ tmp = build1 (reduc_code, vectype, PHI_RESULT (new_phi));
+ 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 = 0;
+ bool have_whole_vector_shift = true;
+ int bit_offset;
+ int element_bitsize = tree_low_cst (bitsize, 1);
+ int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
+ tree vec_temp;
+
+ if (optab_handler (vec_shr_optab, mode)->insn_code != 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)->insn_code == CODE_FOR_nothing)
+ have_whole_vector_shift = false;
+ }
+
+ if (have_whole_vector_shift)
+ {
+ /*** Case 2: Create:
+ for (offset = VS/2; offset >= element_size; offset/=2)
+ {
+ Create: va' = vec_shift <va, offset>
+ Create: va = vop <va, va'>
+ } */
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Reduce using vector shifts");
+
+ vec_dest = vect_create_destination_var (scalar_dest, vectype);
+ new_temp = PHI_RESULT (new_phi);
+
+ 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'>
+ } */
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "Reduce using scalar code. ");
+
+ vec_temp = PHI_RESULT (new_phi);
+ vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
+ 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);
+
+ 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);
+
+ 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);
+ }
+
+ 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;
+
+ gcc_assert (!nested_in_vect_loop);
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "extract scalar result");
+
+ 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);
+ }
+
+vect_finalize_reduction:
+
+ /* 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)
+ {
+ if (nested_in_vect_loop)
+ {
+ 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
+ {
+ 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);
+ SSA_NAME_DEF_STMT (new_temp) = epilog_stmt;
+ gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
+ }
+
+
+ /* 2.6 Handle the loop-exit phi */
+
+ /* Replace uses of s_out0 with uses of s_out3:
+ 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). */
+ phis = VEC_alloc (gimple, heap, 10);
+ FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
+ {
+ if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))))
+ {
+ exit_phi = USE_STMT (use_p);
+ VEC_quick_push (gimple, phis, exit_phi);
+ }
+ }
+ /* We expect to have found an exit_phi because of loop-closed-ssa form. */
+ gcc_assert (!VEC_empty (gimple, phis));
+
+ for (i = 0; VEC_iterate (gimple, phis, i, exit_phi); i++)
+ {
+ if (nested_in_vect_loop)
+ {
+ stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_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). */
+ gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo)
+ && !STMT_VINFO_LIVE_P (stmt_vinfo));
+
+ epilog_stmt = adjustment_def ? epilog_stmt : new_phi;
+ STMT_VINFO_VEC_STMT (stmt_vinfo) = epilog_stmt;
+ set_vinfo_for_stmt (epilog_stmt,
+ new_stmt_vec_info (epilog_stmt, loop_vinfo));
+ if (adjustment_def)
+ STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt)) =
+ STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi));
+ continue;
+ }
+
+ /* Replace the uses: */
+ orig_name = PHI_RESULT (exit_phi);
+ 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, new_temp);
+ }
+ VEC_free (gimple, heap, phis);
+}
+
+
+/* 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 BSI.
+ 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)
+{
+ 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 = STMT_VINFO_VECTYPE (stmt_info);
+ 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 = 0;
+ 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 nunits = TYPE_VECTOR_SUBPARTS (vectype);
+ int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
+ int epilog_copies;
+ stmt_vec_info prev_stmt_info, prev_phi_info;
+ gimple first_phi = NULL;
+ bool single_defuse_cycle = false;
+ tree reduc_def;
+ gimple new_stmt = NULL;
+ int j;
+ tree ops[3];
+
+ if (nested_in_vect_loop_p (loop, stmt))
+ loop = loop->inner;
+
+ gcc_assert (ncopies >= 1);
+
+ /* FORNOW: SLP not supported. */
+ if (STMT_SLP_TYPE (stmt_info))
+ return false;
+
+ /* 1. Is vectorizable reduction? */
+
+ /* Not supportable if the reduction variable is used in the loop. */
+ if (STMT_VINFO_RELEVANT (stmt_info) > vect_used_in_outer)
+ 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_loop
+ && !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)
+ 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_RELATED_STMT (orig_stmt_info) == 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_UNARY_RHS:
+ return false;
+
+ default:
+ gcc_unreachable ();
+ }
+
+ 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;
+
+ /* All uses but the last are expected to be defined in the loop.
+ The last use is the reduction variable. */
+ for (i = 0; i < op_type-1; i++)
+ {
+ is_simple_use = vect_is_simple_use (ops[i], loop_vinfo, &def_stmt,
+ &def, &dt);
+ gcc_assert (is_simple_use);
+ if (dt != vect_loop_def
+ && dt != vect_invariant_def
+ && dt != vect_constant_def
+ && dt != vect_induction_def)
+ return false;
+ }
+
+ is_simple_use = vect_is_simple_use (ops[i], loop_vinfo, &def_stmt, &def, &dt);
+ gcc_assert (is_simple_use);
+ gcc_assert (dt == vect_reduction_def);
+ gcc_assert (gimple_code (def_stmt) == GIMPLE_PHI);
+ if (orig_stmt)
+ gcc_assert (orig_stmt == vect_is_simple_reduction (loop_vinfo, def_stmt));
+ else
+ gcc_assert (stmt == vect_is_simple_reduction (loop_vinfo, def_stmt));
+
+ if (STMT_VINFO_LIVE_P (vinfo_for_stmt (def_stmt)))
+ return false;
+
+ /* 4. Supportable by target? */
+
+ /* 4.1. check support for the operation in the loop */
+ optab = optab_for_tree_code (code, vectype, optab_default);
+ if (!optab)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "no optab.");
+ return false;
+ }
+ vec_mode = TYPE_MODE (vectype);
+ if (optab_handler (optab, vec_mode)->insn_code == CODE_FOR_nothing)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "op not supported by target.");
+ if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD
+ || LOOP_VINFO_VECT_FACTOR (loop_vinfo)
+ < vect_min_worthwhile_factor (code))
+ return false;
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "proceeding using word mode.");
+ }
+
+ /* Worthwhile without SIMD support? */
+ if (!VECTOR_MODE_P (TYPE_MODE (vectype))
+ && LOOP_VINFO_VECT_FACTOR (loop_vinfo)
+ < vect_min_worthwhile_factor (code))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "not worthwhile without SIMD support.");
+ 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: 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: 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);
+ vectype = get_vectype_for_scalar_type (TREE_TYPE (def));
+ if (!vectype)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "unsupported data-type ");
+ print_generic_expr (vect_dump, TREE_TYPE (def), TDF_SLIM);
+ }
+ return false;
+ }
+
+ vec_mode = TYPE_MODE (vectype);
+ }
+ 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 (!reduction_code_for_scalar_code (orig_code, &epilog_reduc_code))
+ return false;
+ reduc_optab = optab_for_tree_code (epilog_reduc_code, vectype, optab_default);
+ if (!reduc_optab)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "no optab for reduction.");
+ epilog_reduc_code = NUM_TREE_CODES;
+ }
+ if (optab_handler (reduc_optab, vec_mode)->insn_code == CODE_FOR_nothing)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "reduc op not supported by target.");
+ epilog_reduc_code = NUM_TREE_CODES;
+ }
+
+ if (!vec_stmt) /* transformation not required. */
+ {
+ STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type;
+ if (!vect_model_reduction_cost (stmt_info, epilog_reduc_code, ncopies))
+ return false;
+ return true;
+ }
+
+ /** Transform. **/
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "transform reduction.");
+
+ /* Create the destination vector */
+ vec_dest = vect_create_destination_var (scalar_dest, vectype);
+
+ /* 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_loop)
+ {
+ single_defuse_cycle = true;
+ epilog_copies = 1;
+ }
+ else
+ epilog_copies = ncopies;
+
+ prev_stmt_info = NULL;
+ prev_phi_info = NULL;
+ for (j = 0; j < ncopies; j++)
+ {
+ if (j == 0 || !single_defuse_cycle)
+ {
+ /* 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));
+ }
+
+ /* Handle uses. */
+ if (j == 0)
+ {
+ loop_vec_def0 = vect_get_vec_def_for_operand (ops[0], stmt, NULL);
+ if (op_type == ternary_op)
+ {
+ loop_vec_def1 = vect_get_vec_def_for_operand (ops[1], stmt, NULL);
+ }
+
+ /* Get the vector def for the reduction variable from the phi node */
+ reduc_def = PHI_RESULT (new_phi);
+ first_phi = new_phi;
+ }
+ else
+ {
+ enum vect_def_type dt = vect_unknown_def_type; /* Dummy */
+ loop_vec_def0 = vect_get_vec_def_for_stmt_copy (dt, loop_vec_def0);
+ if (op_type == ternary_op)
+ loop_vec_def1 = vect_get_vec_def_for_stmt_copy (dt, loop_vec_def1);
+
+ if (single_defuse_cycle)
+ reduc_def = gimple_assign_lhs (new_stmt);
+ else
+ reduc_def = PHI_RESULT (new_phi);
+
+ STMT_VINFO_RELATED_STMT (prev_phi_info) = new_phi;
+ }
+
+ /* Arguments are ready. create the new vector stmt. */
+ if (op_type == binary_op)
+ expr = build2 (code, vectype, loop_vec_def0, reduc_def);
+ else
+ expr = build3 (code, vectype, loop_vec_def0, loop_vec_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 (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)
+ new_temp = gimple_assign_lhs (*vec_stmt);
+ vect_create_epilog_for_reduction (new_temp, stmt, epilog_copies,
+ epilog_reduc_code, first_phi);
+ 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. This restriction should be relaxed. */
+ if (nested_in_vect_loop_p (loop, phi) && ncopies > 1)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "multiple types in nested loop.");
+ 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== vectorizable_induction ===");
+ vect_model_induction_cost (stmt_info, ncopies);
+ return true;
+ }
+
+ /** Transform. **/
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "transform induction phi.");
+
+ 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 ATTRIBUTE_UNUSED)
+{
+ 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))
+ 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, loop_vinfo, &def_stmt, &def, &dt))
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "use not simple.");
+ return false;
+ }
+
+ if (dt != vect_invariant_def && dt != vect_constant_def)
+ return false;
+ }
+
+ /* No transformation is required for the cases we currently support. */
+ return true;
+}
+
+/* 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 strided_store;
+ bool slp_scheduled = false;
+ unsigned int nunits;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== vec_transform_loop ===");
+
+ if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
+ || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
+ vect_loop_versioning (loop_vinfo);
+
+ /* CHECKME: we wouldn't need this if we called update_ssa once
+ for all loops. */
+ bitmap_zero (vect_memsyms_to_rename);
+
+ /* Peel the loop if there are data refs with unknown alignment.
+ Only one data ref with unknown store is allowed. */
+
+ if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo))
+ vect_do_peeling_for_alignment (loop_vinfo);
+
+ /* 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_NITERS_KNOWN_P (loop_vinfo)
+ || (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
+ && LOOP_VINFO_INT_NITERS (loop_vinfo) % vectorization_factor != 0))
+ vect_do_peeling_for_loop_bound (loop_vinfo, &ratio);
+ else
+ ratio = build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo)),
+ LOOP_VINFO_INT_NITERS (loop_vinfo) / vectorization_factor);
+
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "------>vectorizing phi: ");
+ print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
+ }
+ stmt_info = vinfo_for_stmt (phi);
+ if (!stmt_info)
+ continue;
+
+ if (!STMT_VINFO_RELEVANT_P (stmt_info)
+ && !STMT_VINFO_LIVE_P (stmt_info))
+ continue;
+
+ if ((TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info))
+ != (unsigned HOST_WIDE_INT) vectorization_factor)
+ && vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "multiple-types.");
+
+ if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
+ {
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "transform phi.");
+ vect_transform_stmt (phi, NULL, NULL, NULL, NULL);
+ }
+ }
+
+ for (si = gsi_start_bb (bb); !gsi_end_p (si);)
+ {
+ gimple stmt = gsi_stmt (si);
+ bool is_store;
+
+ if (vect_print_dump_info (REPORT_DETAILS))
+ {
+ fprintf (vect_dump, "------>vectorizing statement: ");
+ print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
+ }
+
+ 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 (!STMT_VINFO_RELEVANT_P (stmt_info)
+ && !STMT_VINFO_LIVE_P (stmt_info))
+ {
+ gsi_next (&si);
+ continue;
+ }
+
+ gcc_assert (STMT_VINFO_VECTYPE (stmt_info));
+ nunits =
+ (unsigned int) TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info));
+ if (!STMT_SLP_TYPE (stmt_info)
+ && nunits != (unsigned int) vectorization_factor
+ && vect_print_dump_info (REPORT_DETAILS))
+ /* For SLP VF is set according to unrolling factor, and not to
+ vector size, hence for SLP this print is not valid. */
+ fprintf (vect_dump, "multiple-types.");
+
+ /* 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 (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "=== scheduling SLP instances ===");
+
+ is_store = vect_schedule_slp (loop_vinfo);
+
+ /* IS_STORE is true if STMT is a store. Stores cannot be of
+ hybrid SLP type. They are removed in
+ vect_schedule_slp_instance and their vinfo is destroyed. */
+ if (is_store)
+ {
+ gsi_next (&si);
+ continue;
+ }
+ }
+
+ /* Hybrid SLP stmts must be vectorized in addition to SLP. */
+ if (PURE_SLP_STMT (stmt_info))
+ {
+ gsi_next (&si);
+ continue;
+ }
+ }
+
+ /* -------- vectorize statement ------------ */
+ if (vect_print_dump_info (REPORT_DETAILS))
+ fprintf (vect_dump, "transform statement.");
+
+ strided_store = false;
+ is_store = vect_transform_stmt (stmt, &si, &strided_store, NULL, NULL);
+ if (is_store)
+ {
+ if (STMT_VINFO_STRIDED_ACCESS (stmt_info))
+ {
+ /* Interleaving. If IS_STORE is TRUE, the vectorization of the
+ interleaving chain was completed - free all the stores in
+ the chain. */
+ vect_remove_stores (DR_GROUP_FIRST_DR (stmt_info));
+ gsi_remove (&si, true);
+ continue;
+ }
+ else
+ {
+ /* Free the attached stmt_vec_info and remove the stmt. */
+ free_stmt_vec_info (stmt);
+ gsi_remove (&si, true);
+ continue;
+ }
+ }
+ gsi_next (&si);
+ } /* stmts in BB */
+ } /* BBs in loop */
+
+ slpeel_make_loop_iterate_ntimes (loop, ratio);
+
+ mark_set_for_renaming (vect_memsyms_to_rename);
+
+ /* The memory tags and pointers in vectorized statements need to
+ have their SSA forms updated. FIXME, why can't this be delayed
+ until all the loops have been transformed? */
+ update_ssa (TODO_update_ssa);
+
+ if (vect_print_dump_info (REPORT_VECTORIZED_LOOPS))
+ fprintf (vect_dump, "LOOP VECTORIZED.");
+ if (loop->inner && vect_print_dump_info (REPORT_VECTORIZED_LOOPS))
+ fprintf (vect_dump, "OUTER LOOP VECTORIZED.");
+}
+
+
+