On Wed, Dec 4, 2019 at 10:52 PM Jan Hubicka <[email protected]> wrote:
>
> Hi,
> with recent fixes to proile updating I noticed that we get more regressions
> compared to gcc 9 at Firefox testing. This is because Firefox train run is
> not covering all the benchmarks and gcc 9, thanks to updating bugs sometimes
> optimize code for speed even if it was not trained.
>
> While in general one should have reasonable train run, in some cases it is
> not practical to do so. For example, skia library has optimized vector code
> for different ISAs and thus firefox renders quickly only if it is trained
> on same CPU as run.
>
> This patch adds flag -fprofile-partial-training which makes GCC to optimize
> untrained functions as w/o -fprofile-use. This nullifies code size
> improvements
> of FDO but can be used in cases where full training is not quite possible
> (and one can use it only on portions of programs).
>
> Previously only good answer was to disable profiling for a given function, but
> that needs to be done quite precisely and in general is hard to arrange.
>
> Patch works by
> 1) not setting PROFILE_READ for functions with entry count 0
> 2) make inliner and ipa-cp to drop profile to local one when all
> trained executions are redirected to clones
> 3) reduce quality of branch probabilities of branches leading to never
> executed regions to GUESSED. This is necessary to prevent gcc from
> proagating thins back.
>
> Bootstrapped/regtested x86_64-linux. I plan to commit it tomorrow if there
> are no complains. Feedback is welcome!
I wonder if the behavior shouldn't be the default? The only thing we lose
is failing to notice really cold calls (error paths) in programs?
Richard.
>
> Honza
>
> * cgraphclones.c (localize_profile): New function.
> (cgraph_node::create_clone): Use it for partial profiles.
> * common.opt (fprofile-partial-training): New flag.
> * doc/invoke.texi (-fprofile-partial-training): Document.
> * ipa-cp.c (update_profiling_info): For partial profiles do not
> set function profile to zero.
> * profile.c (compute_branch_probabilities): With partial profile
> watch if edge count is zero and turn all probabilities to guessed.
> (compute_branch_probabilities): For partial profiles do not apply
> profile when entry count is zero.
> * tree-profile.c (tree_profiling): Only do
> value_profile_transformations
> when profile is read.
> Index: cgraphclones.c
> ===================================================================
> --- cgraphclones.c (revision 278944)
> +++ cgraphclones.c (working copy)
> @@ -307,6 +307,22 @@ dump_callgraph_transformation (const cgr
> }
> }
>
> +/* Turn profile of N to local profile. */
> +
> +static void
> +localize_profile (cgraph_node *n)
> +{
> + n->count = n->count.guessed_local ();
> + for (cgraph_edge *e = n->callees; e; e=e->next_callee)
> + {
> + e->count = e->count.guessed_local ();
> + if (!e->inline_failed)
> + localize_profile (e->callee);
> + }
> + for (cgraph_edge *e = n->indirect_calls; e; e=e->next_callee)
> + e->count = e->count.guessed_local ();
> +}
> +
> /* Create node representing clone of N executed COUNT times. Decrease
> the execution counts from original node too.
> The new clone will have decl set to DECL that may or may not be the same
> @@ -340,6 +356,7 @@ cgraph_node::create_clone (tree new_decl
> cgraph_edge *e;
> unsigned i;
> profile_count old_count = count;
> + bool nonzero = count.ipa ().nonzero_p ();
>
> if (new_inlined_to)
> dump_callgraph_transformation (this, new_inlined_to, "inlining to");
> @@ -426,6 +446,15 @@ cgraph_node::create_clone (tree new_decl
>
> if (call_duplication_hook)
> symtab->call_cgraph_duplication_hooks (this, new_node);
> + /* With partial train run we do not want to assume that original's
> + count is zero whenever we redurect all executed edges to clone.
> + Simply drop profile to local one in this case. */
> + if (update_original
> + && opt_for_fn (decl, flag_partial_profile_training)
> + && nonzero
> + && count.ipa_p ()
> + && !count.ipa ().nonzero_p ())
> + localize_profile (this);
>
> if (!new_inlined_to)
> dump_callgraph_transformation (this, new_node, suffix);
> Index: common.opt
> ===================================================================
> --- common.opt (revision 278944)
> +++ common.opt (working copy)
> @@ -2160,6 +2160,10 @@ fprofile-generate=
> Common Joined RejectNegative
> Enable common options for generating profile info for profile feedback
> directed optimizations, and set -fprofile-dir=.
>
> +fprofile-partial-training
> +Common Report Var(flag_partial_profile_training) Optimization
> +Do not assume that functions never executed during the train run are cold
> +
> fprofile-use
> Common Var(flag_profile_use)
> Enable common options for performing profile feedback directed optimizations.
> Index: doc/invoke.texi
> ===================================================================
> --- doc/invoke.texi (revision 278944)
> +++ doc/invoke.texi (working copy)
> @@ -453,8 +453,8 @@ Objective-C and Objective-C++ Dialects}.
> -fpartial-inlining -fpeel-loops -fpredictive-commoning @gol
> -fprefetch-loop-arrays @gol
> -fprofile-correction @gol
> --fprofile-use -fprofile-use=@var{path} -fprofile-values @gol
> --fprofile-reorder-functions @gol
> +-fprofile-use -fprofile-use=@var{path} -fprofile-partial-training @gol
> +-fprofile-values -fprofile-reorder-functions @gol
> -freciprocal-math -free -frename-registers -freorder-blocks @gol
> -freorder-blocks-algorithm=@var{algorithm} @gol
> -freorder-blocks-and-partition -freorder-functions @gol
> @@ -10634,6 +10634,17 @@ default, GCC emits an error message when
>
> This option is enabled by @option{-fauto-profile}.
>
> +@item -fprofile-partial-training
> +@opindex fprofile-use
> +With @code{-fprofile-use} all portions of programs not executed during train
> +run are optimized agressively for size rather than speed. In some cases it
> is not
> +practical to train all possible paths hot paths in the program. (For example
> +program may contain functions specific for a given hardware and trianing may
> +not cover all hardware configurations program is run on.) With
> +@code{-fprofile-partial-training} profile feedback will be ignored for all
> +functions not executed during the train run leading them to be optimized as
> +if they were compiled without profile feedback.
> +
> @item -fprofile-use
> @itemx -fprofile-use=@var{path}
> @opindex fprofile-use
> Index: ipa-cp.c
> ===================================================================
> --- ipa-cp.c (revision 278944)
> +++ ipa-cp.c (working copy)
> @@ -4295,6 +4295,15 @@ update_profiling_info (struct cgraph_nod
>
> remainder = orig_node_count.combine_with_ipa_count (orig_node_count.ipa ()
> - new_sum.ipa ());
> +
> + /* With partial train run we do not want to assume that original's
> + count is zero whenever we redurect all executed edges to clone.
> + Simply drop profile to local one in this case. */
> + if (remainder.ipa_p () && !remainder.ipa ().nonzero_p ()
> + && orig_node->count.ipa_p () && orig_node->count.ipa ().nonzero_p ()
> + && flag_partial_profile_training)
> + remainder = remainder.guessed_local ();
> +
> new_sum = orig_node_count.combine_with_ipa_count (new_sum);
> new_node->count = new_sum;
> orig_node->count = remainder;
> Index: profile.c
> ===================================================================
> --- profile.c (revision 278944)
> +++ profile.c (working copy)
> @@ -635,9 +635,20 @@ compute_branch_probabilities (unsigned c
> }
> if (bb_gcov_count (bb))
> {
> + bool set_to_guessed = false;
> FOR_EACH_EDGE (e, ei, bb->succs)
> - e->probability = profile_probability::probability_in_gcov_type
> - (edge_gcov_count (e), bb_gcov_count (bb));
> + {
> + bool prev_never = e->probability == profile_probability::never
> ();
> + e->probability = profile_probability::probability_in_gcov_type
> + (edge_gcov_count (e), bb_gcov_count (bb));
> + if (e->probability == profile_probability::never ()
> + && !prev_never
> + && flag_partial_profile_training)
> + set_to_guessed = true;
> + }
> + if (set_to_guessed)
> + FOR_EACH_EDGE (e, ei, bb->succs)
> + e->probability = e->probability.guessed ();
> if (bb->index >= NUM_FIXED_BLOCKS
> && block_ends_with_condjump_p (bb)
> && EDGE_COUNT (bb->succs) >= 2)
> @@ -697,17 +708,23 @@ compute_branch_probabilities (unsigned c
> }
> }
>
> - if (exec_counts)
> + if (exec_counts
> + && (bb_gcov_count (ENTRY_BLOCK_PTR_FOR_FN (cfun))
> + || !flag_partial_profile_training))
> profile_status_for_fn (cfun) = PROFILE_READ;
>
> /* If we have real data, use them! */
> if (bb_gcov_count (ENTRY_BLOCK_PTR_FOR_FN (cfun))
> || !flag_guess_branch_prob)
> FOR_ALL_BB_FN (bb, cfun)
> - bb->count = profile_count::from_gcov_type (bb_gcov_count (bb));
> + if (bb_gcov_count (bb) || !flag_partial_profile_training)
> + bb->count = profile_count::from_gcov_type (bb_gcov_count (bb));
> + else
> + bb->count = profile_count::guessed_zero ();
> /* If function was not trained, preserve local estimates including
> statically
> determined zero counts. */
> - else if (profile_status_for_fn (cfun) == PROFILE_READ)
> + else if (profile_status_for_fn (cfun) == PROFILE_READ
> + && !flag_partial_profile_training)
> FOR_ALL_BB_FN (bb, cfun)
> if (!(bb->count == profile_count::zero ()))
> bb->count = bb->count.global0 ();
> @@ -1417,7 +1434,7 @@ branch_prob (bool thunk)
> /* At this moment we have precise loop iteration count estimates.
> Record them to loop structure before the profile gets out of date. */
> FOR_EACH_LOOP (loop, 0)
> - if (loop->header->count > 0)
> + if (loop->header->count > 0 && loop->header->count.reliable_p ())
> {
> gcov_type nit = expected_loop_iterations_unbounded (loop);
> widest_int bound = gcov_type_to_wide_int (nit);
> Index: tree-profile.c
> ===================================================================
> --- tree-profile.c (revision 278944)
> +++ tree-profile.c (working copy)
> @@ -785,7 +785,8 @@ tree_profiling (void)
> if (flag_branch_probabilities
> && !thunk
> && flag_profile_values
> - && flag_value_profile_transformations)
> + && flag_value_profile_transformations
> + && profile_status_for_fn (cfun) == PROFILE_READ)
> gimple_value_profile_transformations ();
>
> /* The above could hose dominator info. Currently there is
