1 /*
2 * Copyright (c) 2018, Red Hat, Inc. and/or its affiliates.
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 #include "gc_implementation/shenandoah/heuristics/shenandoahAdaptiveHeuristics.hpp"
26 #include "gc_implementation/shenandoah/shenandoahCollectionSet.hpp"
27 #include "gc_implementation/shenandoah/shenandoahFreeSet.hpp"
28 #include "gc_implementation/shenandoah/shenandoahHeapRegion.hpp"
29 #include "gc_implementation/shenandoah/shenandoahLogging.hpp"
30 #include "utilities/quickSort.hpp"
31
32 ShenandoahAdaptiveHeuristics::ShenandoahAdaptiveHeuristics() :
33 ShenandoahHeuristics(),
34 _cycle_gap_history(new TruncatedSeq(5)),
35 _conc_mark_duration_history(new TruncatedSeq(5)),
36 _conc_uprefs_duration_history(new TruncatedSeq(5)) {
37 }
38
39 ShenandoahAdaptiveHeuristics::~ShenandoahAdaptiveHeuristics() {}
40
41 void ShenandoahAdaptiveHeuristics::choose_collection_set_from_regiondata(ShenandoahCollectionSet* cset,
42 RegionData* data, size_t size,
43 size_t actual_free) {
44 size_t garbage_threshold = ShenandoahHeapRegion::region_size_bytes() * ShenandoahGarbageThreshold / 100;
45
46 // The logic for cset selection in adaptive is as follows:
47 //
48 // 1. We cannot get cset larger than available free space. Otherwise we guarantee OOME
49 // during evacuation, and thus guarantee full GC. In practice, we also want to let
50 // application to allocate something. This is why we limit CSet to some fraction of
51 // available space. In non-overloaded heap, max_cset would contain all plausible candidates
52 // over garbage threshold.
53 //
54 // 2. We should not get cset too low so that free threshold would not be met right
55 // after the cycle. Otherwise we get back-to-back cycles for no reason if heap is
56 // too fragmented. In non-overloaded non-fragmented heap min_garbage would be around zero.
57 //
58 // Therefore, we start by sorting the regions by garbage. Then we unconditionally add the best candidates
59 // before we meet min_garbage. Then we add all candidates that fit with a garbage threshold before
60 // we hit max_cset. When max_cset is hit, we terminate the cset selection. Note that in this scheme,
61 // ShenandoahGarbageThreshold is the soft threshold which would be ignored until min_garbage is hit.
62
63 size_t capacity = ShenandoahHeap::heap()->capacity();
64 size_t free_target = ShenandoahMinFreeThreshold * capacity / 100;
65 size_t min_garbage = free_target > actual_free ? (free_target - actual_free) : 0;
66 size_t max_cset = (size_t)(1.0 * ShenandoahEvacReserve * capacity / 100 / ShenandoahEvacWaste);
67
68 log_info(gc, ergo)("Adaptive CSet Selection. Target Free: " SIZE_FORMAT "M, Actual Free: "
69 SIZE_FORMAT "M, Max CSet: " SIZE_FORMAT "M, Min Garbage: " SIZE_FORMAT "M",
70 free_target / M, actual_free / M, max_cset / M, min_garbage / M);
71
72 // Better select garbage-first regions
73 QuickSort::sort<RegionData>(data, (int)size, compare_by_garbage, false);
74
75 size_t cur_cset = 0;
76 size_t cur_garbage = 0;
77 _bytes_in_cset = 0;
78
79 for (size_t idx = 0; idx < size; idx++) {
80 ShenandoahHeapRegion* r = data[idx]._region;
81
82 size_t new_cset = cur_cset + r->get_live_data_bytes();
83 size_t new_garbage = cur_garbage + r->garbage();
84
85 if (new_cset > max_cset) {
86 break;
87 }
88
89 if ((new_garbage < min_garbage) || (r->garbage() > garbage_threshold)) {
90 cset->add_region(r);
91 _bytes_in_cset += r->used();
92 cur_cset = new_cset;
93 cur_garbage = new_garbage;
94 }
95 }
96 }
97
98 void ShenandoahAdaptiveHeuristics::record_cycle_start() {
99 ShenandoahHeuristics::record_cycle_start();
100 double last_cycle_gap = (_cycle_start - _last_cycle_end);
101 _cycle_gap_history->add(last_cycle_gap);
102 }
103
104 void ShenandoahAdaptiveHeuristics::record_phase_time(ShenandoahPhaseTimings::Phase phase, double secs) {
105 if (phase == ShenandoahPhaseTimings::conc_mark) {
106 _conc_mark_duration_history->add(secs);
107 } else if (phase == ShenandoahPhaseTimings::conc_update_refs) {
108 _conc_uprefs_duration_history->add(secs);
109 } // Else ignore
110 }
111
112 bool ShenandoahAdaptiveHeuristics::should_start_normal_gc() const {
113 ShenandoahHeap* heap = ShenandoahHeap::heap();
114 size_t capacity = heap->capacity();
115 size_t available = heap->free_set()->available();
116
117 // Check if we are falling below the worst limit, time to trigger the GC, regardless of
118 // anything else.
119 size_t min_threshold = ShenandoahMinFreeThreshold * heap->capacity() / 100;
120 if (available < min_threshold) {
121 log_info(gc)("Trigger: Free (" SIZE_FORMAT "M) is below minimum threshold (" SIZE_FORMAT "M)",
122 available / M, min_threshold / M);
123 return true;
124 }
125
126 // Check if are need to learn a bit about the application
127 const size_t max_learn = ShenandoahLearningSteps;
128 if (_gc_times_learned < max_learn) {
129 size_t init_threshold = ShenandoahInitFreeThreshold * heap->capacity() / 100;
130 if (available < init_threshold) {
131 log_info(gc)("Trigger: Learning " SIZE_FORMAT " of " SIZE_FORMAT ". Free (" SIZE_FORMAT "M) is below initial threshold (" SIZE_FORMAT "M)",
132 _gc_times_learned + 1, max_learn, available / M, init_threshold / M);
133 return true;
134 }
135 }
136
137 // Check if allocation headroom is still okay. This also factors in:
138 // 1. Some space to absorb allocation spikes
139 // 2. Accumulated penalties from Degenerated and Full GC
140
141 size_t allocation_headroom = available;
142
143 size_t spike_headroom = ShenandoahAllocSpikeFactor * capacity / 100;
144 size_t penalties = _gc_time_penalties * capacity / 100;
145
146 allocation_headroom -= MIN2(allocation_headroom, spike_headroom);
147 allocation_headroom -= MIN2(allocation_headroom, penalties);
148
149 // TODO: Allocation rate is way too averaged to be useful during state changes
150
151 double average_gc = _gc_time_history->avg();
152 double time_since_last = os::elapsedTime() - _cycle_start;
153 double allocation_rate = heap->bytes_allocated_since_gc_start() / time_since_last;
154
155 if (average_gc > allocation_headroom / allocation_rate) {
156 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)",
157 average_gc * 1000, allocation_rate / M, allocation_headroom / M);
158 log_info(gc, ergo)("Free headroom: " SIZE_FORMAT "M (free) - " SIZE_FORMAT "M (spike) - " SIZE_FORMAT "M (penalties) = " SIZE_FORMAT "M",
159 available / M, spike_headroom / M, penalties / M, allocation_headroom / M);
160 return true;
161 }
162
163 return ShenandoahHeuristics::should_start_normal_gc();
164 }
165
166 bool ShenandoahAdaptiveHeuristics::should_start_update_refs() {
167 if (! _update_refs_adaptive) {
168 return _update_refs_early;
169 }
170
171 double cycle_gap_avg = _cycle_gap_history->avg();
172 double conc_mark_avg = _conc_mark_duration_history->avg();
173 double conc_uprefs_avg = _conc_uprefs_duration_history->avg();
174
175 if (_update_refs_early) {
176 double threshold = ShenandoahMergeUpdateRefsMinGap / 100.0;
177 if (conc_mark_avg + conc_uprefs_avg > cycle_gap_avg * threshold) {
178 _update_refs_early = false;
179 }
180 } else {
181 double threshold = ShenandoahMergeUpdateRefsMaxGap / 100.0;
182 if (conc_mark_avg + conc_uprefs_avg < cycle_gap_avg * threshold) {
183 _update_refs_early = true;
184 }
185 }
186 return _update_refs_early;
187 }
188
189 const char* ShenandoahAdaptiveHeuristics::name() {
190 return "adaptive";
191 }
192
193 bool ShenandoahAdaptiveHeuristics::is_diagnostic() {
194 return false;
195 }
196
197 bool ShenandoahAdaptiveHeuristics::is_experimental() {
198 return false;
199 }