1 /*
2 * Copyright (c) 2018, Red Hat, Inc. All rights reserved.
3 *
4 * This code is free software; you can redistribute it and/or modify it
5 * under the terms of the GNU General Public License version 2 only, as
6 * published by the Free Software Foundation.
7 *
8 * This code is distributed in the hope that it will be useful, but WITHOUT
9 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
10 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
11 * version 2 for more details (a copy is included in the LICENSE file that
12 * accompanied this code).
13 *
14 * You should have received a copy of the GNU General Public License version
15 * 2 along with this work; if not, write to the Free Software Foundation,
16 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
17 *
18 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
19 * or visit www.oracle.com if you need additional information or have any
20 * questions.
21 *
22 */
23
24 #include "precompiled.hpp"
25
26 #include "gc/shenandoah/heuristics/shenandoahAdaptiveHeuristics.hpp"
27 #include "gc/shenandoah/shenandoahCollectionSet.hpp"
28 #include "gc/shenandoah/shenandoahFreeSet.hpp"
29 #include "gc/shenandoah/shenandoahHeapRegion.hpp"
30 #include "logging/log.hpp"
31 #include "logging/logTag.hpp"
32 #include "utilities/quickSort.hpp"
33
34 ShenandoahAdaptiveHeuristics::ShenandoahAdaptiveHeuristics() :
35 ShenandoahHeuristics(),
36 _cycle_gap_history(new TruncatedSeq(5)),
37 _conc_mark_duration_history(new TruncatedSeq(5)),
38 _conc_uprefs_duration_history(new TruncatedSeq(5)) {}
39
40 ShenandoahAdaptiveHeuristics::~ShenandoahAdaptiveHeuristics() {}
41
42 void ShenandoahAdaptiveHeuristics::choose_collection_set_from_regiondata(ShenandoahCollectionSet* cset,
43 RegionData* data, size_t size,
44 size_t actual_free) {
45 size_t garbage_threshold = ShenandoahHeapRegion::region_size_bytes() * ShenandoahGarbageThreshold / 100;
46
47 // The logic for cset selection in adaptive is as follows:
48 //
49 // 1. We cannot get cset larger than available free space. Otherwise we guarantee OOME
50 // during evacuation, and thus guarantee full GC. In practice, we also want to let
51 // application to allocate something. This is why we limit CSet to some fraction of
52 // available space. In non-overloaded heap, max_cset would contain all plausible candidates
53 // over garbage threshold.
54 //
55 // 2. We should not get cset too low so that free threshold would not be met right
56 // after the cycle. Otherwise we get back-to-back cycles for no reason if heap is
57 // too fragmented. In non-overloaded non-fragmented heap min_garbage would be around zero.
58 //
59 // Therefore, we start by sorting the regions by garbage. Then we unconditionally add the best candidates
60 // before we meet min_garbage. Then we add all candidates that fit with a garbage threshold before
61 // we hit max_cset. When max_cset is hit, we terminate the cset selection. Note that in this scheme,
62 // ShenandoahGarbageThreshold is the soft threshold which would be ignored until min_garbage is hit.
63
64 size_t capacity = ShenandoahHeap::heap()->max_capacity();
65 size_t free_target = capacity / 100 * ShenandoahMinFreeThreshold;
66 size_t min_garbage = free_target > actual_free ? (free_target - actual_free) : 0;
67 size_t max_cset = (size_t)((1.0 * capacity / 100 * ShenandoahEvacReserve) / ShenandoahEvacWaste);
68
69 log_info(gc, ergo)("Adaptive CSet Selection. Target Free: " SIZE_FORMAT "M, Actual Free: "
70 SIZE_FORMAT "M, Max CSet: " SIZE_FORMAT "M, Min Garbage: " SIZE_FORMAT "M",
71 free_target / M, actual_free / M, max_cset / M, min_garbage / M);
72
73 // Better select garbage-first regions
74 QuickSort::sort<RegionData>(data, (int)size, compare_by_garbage, false);
75
76 size_t cur_cset = 0;
77 size_t cur_garbage = 0;
78 _bytes_in_cset = 0;
79
80 for (size_t idx = 0; idx < size; idx++) {
81 ShenandoahHeapRegion* r = data[idx]._region;
82
83 size_t new_cset = cur_cset + r->get_live_data_bytes();
84 size_t new_garbage = cur_garbage + r->garbage();
85
86 if (new_cset > max_cset) {
87 break;
88 }
89
90 if ((new_garbage < min_garbage) || (r->garbage() > garbage_threshold)) {
91 cset->add_region(r);
92 _bytes_in_cset += r->used();
93 cur_cset = new_cset;
94 cur_garbage = new_garbage;
95 }
96 }
97 }
98
99 void ShenandoahAdaptiveHeuristics::record_cycle_start() {
100 ShenandoahHeuristics::record_cycle_start();
101 double last_cycle_gap = (_cycle_start - _last_cycle_end);
102 _cycle_gap_history->add(last_cycle_gap);
103 }
104
105 void ShenandoahAdaptiveHeuristics::record_phase_time(ShenandoahPhaseTimings::Phase phase, double secs) {
106 if (phase == ShenandoahPhaseTimings::conc_mark) {
107 _conc_mark_duration_history->add(secs);
108 } else if (phase == ShenandoahPhaseTimings::conc_update_refs) {
109 _conc_uprefs_duration_history->add(secs);
110 } // Else ignore
111 }
112
113 bool ShenandoahAdaptiveHeuristics::should_start_gc() const {
114 ShenandoahHeap* heap = ShenandoahHeap::heap();
115 size_t capacity = heap->max_capacity();
116 size_t available = heap->free_set()->available();
117
118 // Check if we are falling below the worst limit, time to trigger the GC, regardless of
119 // anything else.
120 size_t min_threshold = capacity / 100 * ShenandoahMinFreeThreshold;
121 if (available < min_threshold) {
122 log_info(gc)("Trigger: Free (" SIZE_FORMAT "M) is below minimum threshold (" SIZE_FORMAT "M)",
123 available / M, min_threshold / M);
124 return true;
125 }
126
127 // Check if are need to learn a bit about the application
128 const size_t max_learn = ShenandoahLearningSteps;
129 if (_gc_times_learned < max_learn) {
130 size_t init_threshold = capacity / 100 * ShenandoahInitFreeThreshold;
131 if (available < init_threshold) {
132 log_info(gc)("Trigger: Learning " SIZE_FORMAT " of " SIZE_FORMAT ". Free (" SIZE_FORMAT "M) is below initial threshold (" SIZE_FORMAT "M)",
133 _gc_times_learned + 1, max_learn, available / M, init_threshold / M);
134 return true;
135 }
136 }
137
138 // Check if allocation headroom is still okay. This also factors in:
139 // 1. Some space to absorb allocation spikes
140 // 2. Accumulated penalties from Degenerated and Full GC
141
142 size_t allocation_headroom = available;
143
144 size_t spike_headroom = capacity / 100 * ShenandoahAllocSpikeFactor;
145 size_t penalties = capacity / 100 * _gc_time_penalties;
146
147 allocation_headroom -= MIN2(allocation_headroom, spike_headroom);
148 allocation_headroom -= MIN2(allocation_headroom, penalties);
149
150 // TODO: Allocation rate is way too averaged to be useful during state changes
151
152 double average_gc = _gc_time_history->avg();
153 double time_since_last = time_since_last_gc();
154 double allocation_rate = heap->bytes_allocated_since_gc_start() / time_since_last;
155
156 if (average_gc > allocation_headroom / allocation_rate) {
157 log_info(gc)("Trigger: Average GC time (%.2f ms) is above the time for allocation rate (%.2f MB/s) to deplete free headroom (" SIZE_FORMAT "M)",
158 average_gc * 1000, allocation_rate / M, allocation_headroom / M);
159 log_info(gc, ergo)("Free headroom: " SIZE_FORMAT "M (free) - " SIZE_FORMAT "M (spike) - " SIZE_FORMAT "M (penalties) = " SIZE_FORMAT "M",
160 available / M, spike_headroom / M, penalties / M, allocation_headroom / M);
161 return true;
162 }
163
164 return ShenandoahHeuristics::should_start_gc();
165 }
166
167 bool ShenandoahAdaptiveHeuristics::should_start_update_refs() {
168 if (! _update_refs_adaptive) {
169 return _update_refs_early;
170 }
171
172 double cycle_gap_avg = _cycle_gap_history->avg();
173 double conc_mark_avg = _conc_mark_duration_history->avg();
174 double conc_uprefs_avg = _conc_uprefs_duration_history->avg();
175
176 if (_update_refs_early) {
177 double threshold = ShenandoahMergeUpdateRefsMinGap / 100.0;
178 if (conc_mark_avg + conc_uprefs_avg > cycle_gap_avg * threshold) {
179 _update_refs_early = false;
180 }
181 } else {
182 double threshold = ShenandoahMergeUpdateRefsMaxGap / 100.0;
183 if (conc_mark_avg + conc_uprefs_avg < cycle_gap_avg * threshold) {
184 _update_refs_early = true;
185 }
186 }
187 return _update_refs_early;
188 }
189
190 const char* ShenandoahAdaptiveHeuristics::name() {
191 return "adaptive";
192 }
193
194 bool ShenandoahAdaptiveHeuristics::is_diagnostic() {
195 return false;
196 }
197
198 bool ShenandoahAdaptiveHeuristics::is_experimental() {
199 return false;
200 }