jdk-sandbox: comparison hotspot/src/share/vm/gc/g1/g1CollectorPolicy.hpp

equal deleted inserted replaced

-:966a1acb1243
+:5a00fba36171
 #include "gc/g1/collectionSetChooser.hpp"
 #include "gc/g1/g1CollectorState.hpp"
 #include "gc/g1/g1InCSetState.hpp"
 #include "gc/g1/g1MMUTracker.hpp"
+#include "gc/g1/g1Predictions.hpp"
 #include "gc/shared/collectorPolicy.hpp"
 // A G1CollectorPolicy makes policy decisions that determine the
 // characteristics of the collector.  Examples include:
 //   * choice of collection set.
 return _adaptive_size;
 }
 };
 class G1CollectorPolicy: public CollectorPolicy {
 private:
+G1Predictions _predictor;
+double get_new_prediction(TruncatedSeq const* seq) const;
 // either equal to the number of parallel threads, if ParallelGCThreads
 // has been set, or 1 otherwise
 int _parallel_gc_threads;
 // The number of GC threads currently active.
 uintx _no_of_gc_threads;
-enum SomePrivateConstants {
-NumPrevPausesForHeuristics = 10
-};
 G1MMUTracker* _mmu_tracker;
 void initialize_alignments();
 void initialize_flags();
 double _reserve_factor;
 uint   _reserve_regions;
 enum PredictionConstants {
-TruncatedSeqLength = 10
+TruncatedSeqLength = 10,
+NumPrevPausesForHeuristics = 10
 };
 TruncatedSeq* _alloc_rate_ms_seq;
 double        _prev_collection_pause_end_ms;
 uint _free_regions_at_end_of_collection;
 size_t _recorded_rs_lengths;
 size_t _max_rs_lengths;
-double _sigma;
 size_t _rs_lengths_prediction;
-double sigma() const { return _sigma; }
-// A function that prevents us putting too much stock in small sample
-// sets.  Returns a number between 2.0 and 1.0, depending on the number
-// of samples.  5 or more samples yields one; fewer scales linearly from
-// 2.0 at 1 sample to 1.0 at 5.
-double confidence_factor(int samples) const {
-if (samples > 4) return 1.0;
-else return  1.0 + sigma() * ((double)(5 - samples))/2.0;
-}
-double get_new_neg_prediction(TruncatedSeq* seq) {
-return seq->davg() - sigma() * seq->dsd();
-}
 #ifndef PRODUCT
 bool verify_young_ages(HeapRegion* head, SurvRateGroup *surv_rate_group);
 #endif // PRODUCT
 double _pause_time_target_ms;
 size_t _pending_cards;
 public:
+G1Predictions& predictor() { return _predictor; }
 // Accessors
 void set_region_eden(HeapRegion* hr, int young_index_in_cset) {
 hr->set_eden();
 hr->install_surv_rate_group(_short_lived_surv_rate_group);
 #ifndef PRODUCT
 bool verify_young_ages();
 #endif // PRODUCT
-double get_new_prediction(TruncatedSeq* seq) const {
-return MAX2(seq->davg() + sigma() * seq->dsd(),
-seq->davg() * confidence_factor(seq->num()));
-}
 void record_max_rs_lengths(size_t rs_lengths) {
 _max_rs_lengths = rs_lengths;
 }
-size_t predict_rs_length_diff() const {
+size_t predict_rs_length_diff() const;
-return (size_t) get_new_prediction(_rs_length_diff_seq);
-}
+double predict_alloc_rate_ms() const;
-double predict_alloc_rate_ms() const {
+double predict_cost_per_card_ms() const;
-return get_new_prediction(_alloc_rate_ms_seq);
-}
+double predict_scan_hcc_ms() const;
-double predict_cost_per_card_ms() const {
+double predict_rs_update_time_ms(size_t pending_cards) const;
-return get_new_prediction(_cost_per_card_ms_seq);
-}
+double predict_young_cards_per_entry_ratio() const;
-double predict_scan_hcc_ms() const {
+double predict_mixed_cards_per_entry_ratio() const;
-return get_new_prediction(_cost_scan_hcc_seq);
-}
+size_t predict_young_card_num(size_t rs_length) const;
-double predict_rs_update_time_ms(size_t pending_cards) const {
+size_t predict_non_young_card_num(size_t rs_length) const;
-return (double) pending_cards * predict_cost_per_card_ms() + predict_scan_hcc_ms();
-}
+double predict_rs_scan_time_ms(size_t card_num) const;
-double predict_young_cards_per_entry_ratio() const {
+double predict_mixed_rs_scan_time_ms(size_t card_num) const;
-return get_new_prediction(_young_cards_per_entry_ratio_seq);
-}
+double predict_object_copy_time_ms_during_cm(size_t bytes_to_copy) const;
-double predict_mixed_cards_per_entry_ratio() const {
+double predict_object_copy_time_ms(size_t bytes_to_copy) const;
-if (_mixed_cards_per_entry_ratio_seq->num() < 2) {
-return predict_young_cards_per_entry_ratio();
+double predict_constant_other_time_ms() const;
-} else {
-return get_new_prediction(_mixed_cards_per_entry_ratio_seq);
+double predict_young_other_time_ms(size_t young_num) const;
-}
-}
+double predict_non_young_other_time_ms(size_t non_young_num) const;
-size_t predict_young_card_num(size_t rs_length) const {
-return (size_t) ((double) rs_length *
-predict_young_cards_per_entry_ratio());
-}
-size_t predict_non_young_card_num(size_t rs_length) const {
-return (size_t) ((double) rs_length *
-predict_mixed_cards_per_entry_ratio());
-}
-double predict_rs_scan_time_ms(size_t card_num) const {
-if (collector_state()->gcs_are_young()) {
-return (double) card_num * get_new_prediction(_cost_per_entry_ms_seq);
-} else {
-return predict_mixed_rs_scan_time_ms(card_num);
-}
-}
-double predict_mixed_rs_scan_time_ms(size_t card_num) const {
-if (_mixed_cost_per_entry_ms_seq->num() < 3) {
-return (double) card_num * get_new_prediction(_cost_per_entry_ms_seq);
-} else {
-return (double) (card_num *
-get_new_prediction(_mixed_cost_per_entry_ms_seq));
-}
-}
-double predict_object_copy_time_ms_during_cm(size_t bytes_to_copy) const {
-if (_cost_per_byte_ms_during_cm_seq->num() < 3) {
-return (1.1 * (double) bytes_to_copy) *
-get_new_prediction(_cost_per_byte_ms_seq);
-} else {
-return (double) bytes_to_copy *
-get_new_prediction(_cost_per_byte_ms_during_cm_seq);
-}
-}
-double predict_object_copy_time_ms(size_t bytes_to_copy) const {
-if (collector_state()->during_concurrent_mark()) {
-return predict_object_copy_time_ms_during_cm(bytes_to_copy);
-} else {
-return (double) bytes_to_copy *
-get_new_prediction(_cost_per_byte_ms_seq);
-}
-}
-double predict_constant_other_time_ms() const {
-return get_new_prediction(_constant_other_time_ms_seq);
-}
-double predict_young_other_time_ms(size_t young_num) const {
-return (double) young_num *
-get_new_prediction(_young_other_cost_per_region_ms_seq);
-}
-double predict_non_young_other_time_ms(size_t non_young_num) const {
-return (double) non_young_num *
-get_new_prediction(_non_young_other_cost_per_region_ms_seq);
-}
 double predict_base_elapsed_time_ms(size_t pending_cards) const;
 double predict_base_elapsed_time_ms(size_t pending_cards,
 size_t scanned_cards) const;
 size_t predict_bytes_to_copy(HeapRegion* hr) const;
 double max_pause_time_ms() const {
 return _mmu_tracker->max_gc_time() * 1000.0;
 }
-double predict_remark_time_ms() const {
+double predict_remark_time_ms() const;
-return get_new_prediction(_concurrent_mark_remark_times_ms);
-}
+double predict_cleanup_time_ms() const;
-double predict_cleanup_time_ms() const {
-return get_new_prediction(_concurrent_mark_cleanup_times_ms);
-}
 // Returns an estimate of the survival rate of the region at yg-age
 // "yg_age".
-double predict_yg_surv_rate(int age, SurvRateGroup* surv_rate_group) const {
+double predict_yg_surv_rate(int age, SurvRateGroup* surv_rate_group) const;
-TruncatedSeq* seq = surv_rate_group->get_seq(age);
-if (seq->num() == 0)
+double predict_yg_surv_rate(int age) const;
-gclog_or_tty->print("BARF! age is %d", age);
-guarantee( seq->num() > 0, "invariant" );
+double accum_yg_surv_rate_pred(int age) const;
-double pred = get_new_prediction(seq);
-if (pred > 1.0)
-pred = 1.0;
-return pred;
-}
-double predict_yg_surv_rate(int age) const {
-return predict_yg_surv_rate(age, _short_lived_surv_rate_group);
-}
-double accum_yg_surv_rate_pred(int age) const {
-return _short_lived_surv_rate_group->accum_surv_rate_pred(age);
-}
 private:
 // Statistics kept per GC stoppage, pause or full.
 TruncatedSeq* _recent_prev_end_times_for_all_gcs_sec;
 G1CollectorPolicy();
 virtual G1CollectorPolicy* as_g1_policy() { return this; }
-const G1CollectorState* collector_state() const;
+G1CollectorState* collector_state() const;
-G1CollectorState* collector_state();
 G1GCPhaseTimes* phase_times() const { return _phase_times; }
 // Check the current value of the young list RSet lengths and
 // compare it against the last prediction. If the current value is
 void update_survivors_policy();
 virtual void post_heap_initialize();
 };
-// This should move to some place more general...
-// If we have "n" measurements, and we've kept track of their "sum" and the
-// "sum_of_squares" of the measurements, this returns the variance of the
-// sequence.
-inline double variance(int n, double sum_of_squares, double sum) {
-double n_d = (double)n;
-double avg = sum/n_d;
-return (sum_of_squares - 2.0 * avg * sum + n_d * avg * avg) / n_d;
-}
 #endif // SHARE_VM_GC_G1_G1COLLECTORPOLICY_HPP

changeset 33214	5a00fba36171
parent 33204	b8a3901ac5b3
child 33216	8ecefd0f0d10