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|
/* Basic IPA optimizations based on profile.
Copyright (C) 2003-2014 Free Software Foundation, Inc.
This file is part of GCC.
GCC is free software; you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free
Software Foundation; either version 3, or (at your option) any later
version.
GCC is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
for more details.
You should have received a copy of the GNU General Public License
along with GCC; see the file COPYING3. If not see
<http://www.gnu.org/licenses/>. */
/* ipa-profile pass implements the following analysis propagating profille
inter-procedurally.
- Count histogram construction. This is a histogram analyzing how much
time is spent executing statements with a given execution count read
from profile feedback. This histogram is complete only with LTO,
otherwise it contains information only about the current unit.
Similar histogram is also estimated by coverage runtime. This histogram
is not dependent on LTO, but it suffers from various defects; first
gcov runtime is not weighting individual basic block by estimated execution
time and second the merging of multiple runs makes assumption that the
histogram distribution did not change. Consequentely histogram constructed
here may be more precise.
The information is used to set hot/cold thresholds.
- Next speculative indirect call resolution is performed: the local
profile pass assigns profile-id to each function and provide us with a
histogram specifying the most common target. We look up the callgraph
node corresponding to the target and produce a speculative call.
This call may or may not survive through IPA optimization based on decision
of inliner.
- Finally we propagate the following flags: unlikely executed, executed
once, executed at startup and executed at exit. These flags are used to
control code size/performance threshold and and code placement (by producing
.text.unlikely/.text.hot/.text.startup/.text.exit subsections). */
#include "config.h"
#include "system.h"
#include "coretypes.h"
#include "tm.h"
#include "tree.h"
#include "predict.h"
#include "dominance.h"
#include "cfg.h"
#include "basic-block.h"
#include "hash-map.h"
#include "is-a.h"
#include "plugin-api.h"
#include "vec.h"
#include "hashtab.h"
#include "hash-set.h"
#include "machmode.h"
#include "hard-reg-set.h"
#include "input.h"
#include "function.h"
#include "ipa-ref.h"
#include "cgraph.h"
#include "tree-pass.h"
#include "tree-ssa-alias.h"
#include "internal-fn.h"
#include "gimple-expr.h"
#include "gimple.h"
#include "gimple-iterator.h"
#include "flags.h"
#include "target.h"
#include "tree-iterator.h"
#include "ipa-utils.h"
#include "profile.h"
#include "params.h"
#include "value-prof.h"
#include "alloc-pool.h"
#include "tree-inline.h"
#include "lto-streamer.h"
#include "data-streamer.h"
#include "ipa-prop.h"
#include "ipa-inline.h"
/* Entry in the histogram. */
struct histogram_entry
{
gcov_type count;
int time;
int size;
};
/* Histogram of profile values.
The histogram is represented as an ordered vector of entries allocated via
histogram_pool. During construction a separate hashtable is kept to lookup
duplicate entries. */
vec<histogram_entry *> histogram;
static alloc_pool histogram_pool;
/* Hashtable support for storing SSA names hashed by their SSA_NAME_VAR. */
struct histogram_hash : typed_noop_remove <histogram_entry>
{
typedef histogram_entry value_type;
typedef histogram_entry compare_type;
static inline hashval_t hash (const value_type *);
static inline int equal (const value_type *, const compare_type *);
};
inline hashval_t
histogram_hash::hash (const histogram_entry *val)
{
return val->count;
}
inline int
histogram_hash::equal (const histogram_entry *val, const histogram_entry *val2)
{
return val->count == val2->count;
}
/* Account TIME and SIZE executed COUNT times into HISTOGRAM.
HASHTABLE is the on-side hash kept to avoid duplicates. */
static void
account_time_size (hash_table<histogram_hash> *hashtable,
vec<histogram_entry *> &histogram,
gcov_type count, int time, int size)
{
histogram_entry key = {count, 0, 0};
histogram_entry **val = hashtable->find_slot (&key, INSERT);
if (!*val)
{
*val = (histogram_entry *) pool_alloc (histogram_pool);
**val = key;
histogram.safe_push (*val);
}
(*val)->time += time;
(*val)->size += size;
}
int
cmp_counts (const void *v1, const void *v2)
{
const histogram_entry *h1 = *(const histogram_entry * const *)v1;
const histogram_entry *h2 = *(const histogram_entry * const *)v2;
if (h1->count < h2->count)
return 1;
if (h1->count > h2->count)
return -1;
return 0;
}
/* Dump HISTOGRAM to FILE. */
static void
dump_histogram (FILE *file, vec<histogram_entry *> histogram)
{
unsigned int i;
gcov_type overall_time = 0, cumulated_time = 0, cumulated_size = 0, overall_size = 0;
fprintf (dump_file, "Histogram:\n");
for (i = 0; i < histogram.length (); i++)
{
overall_time += histogram[i]->count * histogram[i]->time;
overall_size += histogram[i]->size;
}
if (!overall_time)
overall_time = 1;
if (!overall_size)
overall_size = 1;
for (i = 0; i < histogram.length (); i++)
{
cumulated_time += histogram[i]->count * histogram[i]->time;
cumulated_size += histogram[i]->size;
fprintf (file, " %"PRId64": time:%i (%2.2f) size:%i (%2.2f)\n",
(int64_t) histogram[i]->count,
histogram[i]->time,
cumulated_time * 100.0 / overall_time,
histogram[i]->size,
cumulated_size * 100.0 / overall_size);
}
}
/* Collect histogram from CFG profiles. */
static void
ipa_profile_generate_summary (void)
{
struct cgraph_node *node;
gimple_stmt_iterator gsi;
basic_block bb;
hash_table<histogram_hash> hashtable (10);
histogram_pool = create_alloc_pool ("IPA histogram", sizeof (struct histogram_entry),
10);
FOR_EACH_FUNCTION_WITH_GIMPLE_BODY (node)
FOR_EACH_BB_FN (bb, DECL_STRUCT_FUNCTION (node->decl))
{
int time = 0;
int size = 0;
for (gsi = gsi_start_bb (bb); !gsi_end_p (gsi); gsi_next (&gsi))
{
gimple stmt = gsi_stmt (gsi);
if (gimple_code (stmt) == GIMPLE_CALL
&& !gimple_call_fndecl (stmt))
{
histogram_value h;
h = gimple_histogram_value_of_type
(DECL_STRUCT_FUNCTION (node->decl),
stmt, HIST_TYPE_INDIR_CALL);
/* No need to do sanity check: gimple_ic_transform already
takes away bad histograms. */
if (h)
{
/* counter 0 is target, counter 1 is number of execution we called target,
counter 2 is total number of executions. */
if (h->hvalue.counters[2])
{
struct cgraph_edge * e = node->get_edge (stmt);
if (e && !e->indirect_unknown_callee)
continue;
e->indirect_info->common_target_id
= h->hvalue.counters [0];
e->indirect_info->common_target_probability
= GCOV_COMPUTE_SCALE (h->hvalue.counters [1], h->hvalue.counters [2]);
if (e->indirect_info->common_target_probability > REG_BR_PROB_BASE)
{
if (dump_file)
fprintf (dump_file, "Probability capped to 1\n");
e->indirect_info->common_target_probability = REG_BR_PROB_BASE;
}
}
gimple_remove_histogram_value (DECL_STRUCT_FUNCTION (node->decl),
stmt, h);
}
}
time += estimate_num_insns (stmt, &eni_time_weights);
size += estimate_num_insns (stmt, &eni_size_weights);
}
account_time_size (&hashtable, histogram, bb->count, time, size);
}
histogram.qsort (cmp_counts);
}
/* Serialize the ipa info for lto. */
static void
ipa_profile_write_summary (void)
{
struct lto_simple_output_block *ob
= lto_create_simple_output_block (LTO_section_ipa_profile);
unsigned int i;
streamer_write_uhwi_stream (ob->main_stream, histogram.length ());
for (i = 0; i < histogram.length (); i++)
{
streamer_write_gcov_count_stream (ob->main_stream, histogram[i]->count);
streamer_write_uhwi_stream (ob->main_stream, histogram[i]->time);
streamer_write_uhwi_stream (ob->main_stream, histogram[i]->size);
}
lto_destroy_simple_output_block (ob);
}
/* Deserialize the ipa info for lto. */
static void
ipa_profile_read_summary (void)
{
struct lto_file_decl_data ** file_data_vec
= lto_get_file_decl_data ();
struct lto_file_decl_data * file_data;
int j = 0;
hash_table<histogram_hash> hashtable (10);
histogram_pool = create_alloc_pool ("IPA histogram", sizeof (struct histogram_entry),
10);
while ((file_data = file_data_vec[j++]))
{
const char *data;
size_t len;
struct lto_input_block *ib
= lto_create_simple_input_block (file_data,
LTO_section_ipa_profile,
&data, &len);
if (ib)
{
unsigned int num = streamer_read_uhwi (ib);
unsigned int n;
for (n = 0; n < num; n++)
{
gcov_type count = streamer_read_gcov_count (ib);
int time = streamer_read_uhwi (ib);
int size = streamer_read_uhwi (ib);
account_time_size (&hashtable, histogram,
count, time, size);
}
lto_destroy_simple_input_block (file_data,
LTO_section_ipa_profile,
ib, data, len);
}
}
histogram.qsort (cmp_counts);
}
/* Data used by ipa_propagate_frequency. */
struct ipa_propagate_frequency_data
{
bool maybe_unlikely_executed;
bool maybe_executed_once;
bool only_called_at_startup;
bool only_called_at_exit;
};
/* Worker for ipa_propagate_frequency_1. */
static bool
ipa_propagate_frequency_1 (struct cgraph_node *node, void *data)
{
struct ipa_propagate_frequency_data *d;
struct cgraph_edge *edge;
d = (struct ipa_propagate_frequency_data *)data;
for (edge = node->callers;
edge && (d->maybe_unlikely_executed || d->maybe_executed_once
|| d->only_called_at_startup || d->only_called_at_exit);
edge = edge->next_caller)
{
if (edge->caller != node)
{
d->only_called_at_startup &= edge->caller->only_called_at_startup;
/* It makes sense to put main() together with the static constructors.
It will be executed for sure, but rest of functions called from
main are definitely not at startup only. */
if (MAIN_NAME_P (DECL_NAME (edge->caller->decl)))
d->only_called_at_startup = 0;
d->only_called_at_exit &= edge->caller->only_called_at_exit;
}
/* When profile feedback is available, do not try to propagate too hard;
counts are already good guide on function frequencies and roundoff
errors can make us to push function into unlikely section even when
it is executed by the train run. Transfer the function only if all
callers are unlikely executed. */
if (profile_info && flag_branch_probabilities
&& (edge->caller->frequency != NODE_FREQUENCY_UNLIKELY_EXECUTED
|| (edge->caller->global.inlined_to
&& edge->caller->global.inlined_to->frequency
!= NODE_FREQUENCY_UNLIKELY_EXECUTED)))
d->maybe_unlikely_executed = false;
if (!edge->frequency)
continue;
switch (edge->caller->frequency)
{
case NODE_FREQUENCY_UNLIKELY_EXECUTED:
break;
case NODE_FREQUENCY_EXECUTED_ONCE:
if (dump_file && (dump_flags & TDF_DETAILS))
fprintf (dump_file, " Called by %s that is executed once\n",
edge->caller->name ());
d->maybe_unlikely_executed = false;
if (inline_edge_summary (edge)->loop_depth)
{
d->maybe_executed_once = false;
if (dump_file && (dump_flags & TDF_DETAILS))
fprintf (dump_file, " Called in loop\n");
}
break;
case NODE_FREQUENCY_HOT:
case NODE_FREQUENCY_NORMAL:
if (dump_file && (dump_flags & TDF_DETAILS))
fprintf (dump_file, " Called by %s that is normal or hot\n",
edge->caller->name ());
d->maybe_unlikely_executed = false;
d->maybe_executed_once = false;
break;
}
}
return edge != NULL;
}
/* Return ture if NODE contains hot calls. */
bool
contains_hot_call_p (struct cgraph_node *node)
{
struct cgraph_edge *e;
for (e = node->callees; e; e = e->next_callee)
if (e->maybe_hot_p ())
return true;
else if (!e->inline_failed
&& contains_hot_call_p (e->callee))
return true;
for (e = node->indirect_calls; e; e = e->next_callee)
if (e->maybe_hot_p ())
return true;
return false;
}
/* See if the frequency of NODE can be updated based on frequencies of its
callers. */
bool
ipa_propagate_frequency (struct cgraph_node *node)
{
struct ipa_propagate_frequency_data d = {true, true, true, true};
bool changed = false;
/* We can not propagate anything useful about externally visible functions
nor about virtuals. */
if (!node->local.local
|| node->alias
|| (opt_for_fn (node->decl, flag_devirtualize)
&& DECL_VIRTUAL_P (node->decl)))
return false;
gcc_assert (node->analyzed);
if (dump_file && (dump_flags & TDF_DETAILS))
fprintf (dump_file, "Processing frequency %s\n", node->name ());
node->call_for_symbol_thunks_and_aliases (ipa_propagate_frequency_1, &d,
true);
if ((d.only_called_at_startup && !d.only_called_at_exit)
&& !node->only_called_at_startup)
{
node->only_called_at_startup = true;
if (dump_file)
fprintf (dump_file, "Node %s promoted to only called at startup.\n",
node->name ());
changed = true;
}
if ((d.only_called_at_exit && !d.only_called_at_startup)
&& !node->only_called_at_exit)
{
node->only_called_at_exit = true;
if (dump_file)
fprintf (dump_file, "Node %s promoted to only called at exit.\n",
node->name ());
changed = true;
}
/* With profile we can decide on hot/normal based on count. */
if (node->count)
{
bool hot = false;
if (node->count >= get_hot_bb_threshold ())
hot = true;
if (!hot)
hot |= contains_hot_call_p (node);
if (hot)
{
if (node->frequency != NODE_FREQUENCY_HOT)
{
if (dump_file)
fprintf (dump_file, "Node %s promoted to hot.\n",
node->name ());
node->frequency = NODE_FREQUENCY_HOT;
return true;
}
return false;
}
else if (node->frequency == NODE_FREQUENCY_HOT)
{
if (dump_file)
fprintf (dump_file, "Node %s reduced to normal.\n",
node->name ());
node->frequency = NODE_FREQUENCY_NORMAL;
changed = true;
}
}
/* These come either from profile or user hints; never update them. */
if (node->frequency == NODE_FREQUENCY_HOT
|| node->frequency == NODE_FREQUENCY_UNLIKELY_EXECUTED)
return changed;
if (d.maybe_unlikely_executed)
{
node->frequency = NODE_FREQUENCY_UNLIKELY_EXECUTED;
if (dump_file)
fprintf (dump_file, "Node %s promoted to unlikely executed.\n",
node->name ());
changed = true;
}
else if (d.maybe_executed_once && node->frequency != NODE_FREQUENCY_EXECUTED_ONCE)
{
node->frequency = NODE_FREQUENCY_EXECUTED_ONCE;
if (dump_file)
fprintf (dump_file, "Node %s promoted to executed once.\n",
node->name ());
changed = true;
}
return changed;
}
/* Simple ipa profile pass propagating frequencies across the callgraph. */
static unsigned int
ipa_profile (void)
{
struct cgraph_node **order;
struct cgraph_edge *e;
int order_pos;
bool something_changed = false;
int i;
gcov_type overall_time = 0, cutoff = 0, cumulated = 0, overall_size = 0;
struct cgraph_node *n,*n2;
int nindirect = 0, ncommon = 0, nunknown = 0, nuseless = 0, nconverted = 0;
bool node_map_initialized = false;
if (dump_file)
dump_histogram (dump_file, histogram);
for (i = 0; i < (int)histogram.length (); i++)
{
overall_time += histogram[i]->count * histogram[i]->time;
overall_size += histogram[i]->size;
}
if (overall_time)
{
gcov_type threshold;
gcc_assert (overall_size);
if (dump_file)
{
gcov_type min, cumulated_time = 0, cumulated_size = 0;
fprintf (dump_file, "Overall time: %"PRId64"\n",
(int64_t)overall_time);
min = get_hot_bb_threshold ();
for (i = 0; i < (int)histogram.length () && histogram[i]->count >= min;
i++)
{
cumulated_time += histogram[i]->count * histogram[i]->time;
cumulated_size += histogram[i]->size;
}
fprintf (dump_file, "GCOV min count: %"PRId64
" Time:%3.2f%% Size:%3.2f%%\n",
(int64_t)min,
cumulated_time * 100.0 / overall_time,
cumulated_size * 100.0 / overall_size);
}
cutoff = (overall_time * PARAM_VALUE (HOT_BB_COUNT_WS_PERMILLE) + 500) / 1000;
threshold = 0;
for (i = 0; cumulated < cutoff; i++)
{
cumulated += histogram[i]->count * histogram[i]->time;
threshold = histogram[i]->count;
}
if (!threshold)
threshold = 1;
if (dump_file)
{
gcov_type cumulated_time = 0, cumulated_size = 0;
for (i = 0;
i < (int)histogram.length () && histogram[i]->count >= threshold;
i++)
{
cumulated_time += histogram[i]->count * histogram[i]->time;
cumulated_size += histogram[i]->size;
}
fprintf (dump_file, "Determined min count: %"PRId64
" Time:%3.2f%% Size:%3.2f%%\n",
(int64_t)threshold,
cumulated_time * 100.0 / overall_time,
cumulated_size * 100.0 / overall_size);
}
if (threshold > get_hot_bb_threshold ()
|| in_lto_p)
{
if (dump_file)
fprintf (dump_file, "Threshold updated.\n");
set_hot_bb_threshold (threshold);
}
}
histogram.release ();
free_alloc_pool (histogram_pool);
/* Produce speculative calls: we saved common traget from porfiling into
e->common_target_id. Now, at link time, we can look up corresponding
function node and produce speculative call. */
FOR_EACH_DEFINED_FUNCTION (n)
{
bool update = false;
for (e = n->indirect_calls; e; e = e->next_callee)
{
if (n->count)
nindirect++;
if (e->indirect_info->common_target_id)
{
if (!node_map_initialized)
init_node_map (false);
node_map_initialized = true;
ncommon++;
n2 = find_func_by_profile_id (e->indirect_info->common_target_id);
if (n2)
{
if (dump_file)
{
fprintf (dump_file, "Indirect call -> direct call from"
" other module %s/%i => %s/%i, prob %3.2f\n",
xstrdup (n->name ()), n->order,
xstrdup (n2->name ()), n2->order,
e->indirect_info->common_target_probability
/ (float)REG_BR_PROB_BASE);
}
if (e->indirect_info->common_target_probability
< REG_BR_PROB_BASE / 2)
{
nuseless++;
if (dump_file)
fprintf (dump_file,
"Not speculating: probability is too low.\n");
}
else if (!e->maybe_hot_p ())
{
nuseless++;
if (dump_file)
fprintf (dump_file,
"Not speculating: call is cold.\n");
}
else if (n2->get_availability () <= AVAIL_INTERPOSABLE
&& n2->can_be_discarded_p ())
{
nuseless++;
if (dump_file)
fprintf (dump_file,
"Not speculating: target is overwritable "
"and can be discarded.\n");
}
else
{
/* Target may be overwritable, but profile says that
control flow goes to this particular implementation
of N2. Speculate on the local alias to allow inlining.
*/
if (!n2->can_be_discarded_p ())
{
cgraph_node *alias;
alias = dyn_cast<cgraph_node *> (n2->noninterposable_alias ());
if (alias)
n2 = alias;
}
nconverted++;
e->make_speculative
(n2,
apply_scale (e->count,
e->indirect_info->common_target_probability),
apply_scale (e->frequency,
e->indirect_info->common_target_probability));
update = true;
}
}
else
{
if (dump_file)
fprintf (dump_file, "Function with profile-id %i not found.\n",
e->indirect_info->common_target_id);
nunknown++;
}
}
}
if (update)
inline_update_overall_summary (n);
}
if (node_map_initialized)
del_node_map ();
if (dump_file && nindirect)
fprintf (dump_file,
"%i indirect calls trained.\n"
"%i (%3.2f%%) have common target.\n"
"%i (%3.2f%%) targets was not found.\n"
"%i (%3.2f%%) speculations seems useless.\n"
"%i (%3.2f%%) speculations produced.\n",
nindirect,
ncommon, ncommon * 100.0 / nindirect,
nunknown, nunknown * 100.0 / nindirect,
nuseless, nuseless * 100.0 / nindirect,
nconverted, nconverted * 100.0 / nindirect);
order = XCNEWVEC (struct cgraph_node *, symtab->cgraph_count);
order_pos = ipa_reverse_postorder (order);
for (i = order_pos - 1; i >= 0; i--)
{
if (order[i]->local.local && ipa_propagate_frequency (order[i]))
{
for (e = order[i]->callees; e; e = e->next_callee)
if (e->callee->local.local && !e->callee->aux)
{
something_changed = true;
e->callee->aux = (void *)1;
}
}
order[i]->aux = NULL;
}
while (something_changed)
{
something_changed = false;
for (i = order_pos - 1; i >= 0; i--)
{
if (order[i]->aux && ipa_propagate_frequency (order[i]))
{
for (e = order[i]->callees; e; e = e->next_callee)
if (e->callee->local.local && !e->callee->aux)
{
something_changed = true;
e->callee->aux = (void *)1;
}
}
order[i]->aux = NULL;
}
}
free (order);
return 0;
}
namespace {
const pass_data pass_data_ipa_profile =
{
IPA_PASS, /* type */
"profile_estimate", /* name */
OPTGROUP_NONE, /* optinfo_flags */
TV_IPA_PROFILE, /* tv_id */
0, /* properties_required */
0, /* properties_provided */
0, /* properties_destroyed */
0, /* todo_flags_start */
0, /* todo_flags_finish */
};
class pass_ipa_profile : public ipa_opt_pass_d
{
public:
pass_ipa_profile (gcc::context *ctxt)
: ipa_opt_pass_d (pass_data_ipa_profile, ctxt,
ipa_profile_generate_summary, /* generate_summary */
ipa_profile_write_summary, /* write_summary */
ipa_profile_read_summary, /* read_summary */
NULL, /* write_optimization_summary */
NULL, /* read_optimization_summary */
NULL, /* stmt_fixup */
0, /* function_transform_todo_flags_start */
NULL, /* function_transform */
NULL) /* variable_transform */
{}
/* opt_pass methods: */
virtual bool gate (function *) { return flag_ipa_profile || in_lto_p; }
virtual unsigned int execute (function *) { return ipa_profile (); }
}; // class pass_ipa_profile
} // anon namespace
ipa_opt_pass_d *
make_pass_ipa_profile (gcc::context *ctxt)
{
return new pass_ipa_profile (ctxt);
}
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