1 /*
2 * Copyright (c) 2018, 2019, 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/shenandoahTraversalHeuristics.hpp"
27 #include "gc/shenandoah/shenandoahCollectionSet.hpp"
28 #include "gc/shenandoah/shenandoahFreeSet.hpp"
29 #include "gc/shenandoah/shenandoahHeap.inline.hpp"
30 #include "gc/shenandoah/shenandoahHeuristics.hpp"
31 #include "gc/shenandoah/shenandoahTraversalGC.hpp"
32 #include "logging/log.hpp"
33 #include "logging/logTag.hpp"
34 #include "utilities/quickSort.hpp"
35
36 ShenandoahTraversalHeuristics::ShenandoahTraversalHeuristics() : ShenandoahHeuristics(),
37 _last_cset_select(0) {}
38
39 bool ShenandoahTraversalHeuristics::is_experimental() {
40 return true;
41 }
42
43 bool ShenandoahTraversalHeuristics::is_diagnostic() {
44 return false;
45 }
46
47 const char* ShenandoahTraversalHeuristics::name() {
48 return "traversal";
49 }
50
51 void ShenandoahTraversalHeuristics::choose_collection_set(ShenandoahCollectionSet* collection_set) {
52 ShenandoahHeap* heap = ShenandoahHeap::heap();
53
54 ShenandoahTraversalGC* traversal_gc = heap->traversal_gc();
55
56 ShenandoahHeapRegionSet* traversal_set = traversal_gc->traversal_set();
57 traversal_set->clear();
58
59 RegionData *data = get_region_data_cache(heap->num_regions());
60 size_t cnt = 0;
61
62 // Step 0. Prepare all regions
63
64 for (size_t i = 0; i < heap->num_regions(); i++) {
65 ShenandoahHeapRegion* r = heap->get_region(i);
66 if (r->used() > 0) {
67 if (r->is_regular()) {
68 data[cnt]._region = r;
69 data[cnt]._garbage = r->garbage();
70 data[cnt]._seqnum_last_alloc = r->seqnum_last_alloc_mutator();
71 cnt++;
72 }
73 traversal_set->add_region(r);
74 }
75 }
76
77 // The logic for cset selection is similar to that of adaptive:
78 //
79 // 1. We cannot get cset larger than available free space. Otherwise we guarantee OOME
80 // during evacuation, and thus guarantee full GC. In practice, we also want to let
81 // application to allocate something. This is why we limit CSet to some fraction of
82 // available space. In non-overloaded heap, max_cset would contain all plausible candidates
83 // over garbage threshold.
84 //
85 // 2. We should not get cset too low so that free threshold would not be met right
86 // after the cycle. Otherwise we get back-to-back cycles for no reason if heap is
87 // too fragmented. In non-overloaded non-fragmented heap min_garbage would be around zero.
88 //
89 // Therefore, we start by sorting the regions by garbage. Then we unconditionally add the best candidates
90 // before we meet min_garbage. Then we add all candidates that fit with a garbage threshold before
91 // we hit max_cset. When max_cset is hit, we terminate the cset selection. Note that in this scheme,
92 // ShenandoahGarbageThreshold is the soft threshold which would be ignored until min_garbage is hit.
93 //
94 // The significant complication is that liveness data was collected at the previous cycle, and only
95 // for those regions that were allocated before previous cycle started.
96
97 size_t capacity = heap->max_capacity();
98 size_t actual_free = heap->free_set()->available();
99 size_t free_target = capacity / 100 * ShenandoahMinFreeThreshold;
100 size_t min_garbage = free_target > actual_free ? (free_target - actual_free) : 0;
101 size_t max_cset = (size_t)((1.0 * capacity / 100 * ShenandoahEvacReserve) / ShenandoahEvacWaste);
102
103 log_info(gc, ergo)("Adaptive CSet Selection. Target Free: " SIZE_FORMAT "M, Actual Free: "
104 SIZE_FORMAT "M, Max CSet: " SIZE_FORMAT "M, Min Garbage: " SIZE_FORMAT "M",
105 free_target / M, actual_free / M, max_cset / M, min_garbage / M);
106
107 // Better select garbage-first regions, and then older ones
108 QuickSort::sort<RegionData>(data, (int) cnt, compare_by_garbage_then_alloc_seq_ascending, false);
109
110 size_t cur_cset = 0;
111 size_t cur_garbage = 0;
112
113 size_t garbage_threshold = ShenandoahHeapRegion::region_size_bytes() / 100 * ShenandoahGarbageThreshold;
114
115 // Step 1. Add trustworthy regions to collection set.
116 //
117 // We can trust live/garbage data from regions that were fully traversed during
118 // previous cycle. Even if actual liveness is different now, we can only have _less_
119 // live objects, because dead objects are not resurrected. Which means we can undershoot
120 // the collection set, but not overshoot it.
121
122 for (size_t i = 0; i < cnt; i++) {
123 if (data[i]._seqnum_last_alloc > _last_cset_select) continue;
124
125 ShenandoahHeapRegion* r = data[i]._region;
126 assert (r->is_regular(), "should have been filtered before");
127
128 size_t new_garbage = cur_garbage + r->garbage();
129 size_t new_cset = cur_cset + r->get_live_data_bytes();
130
131 if (new_cset > max_cset) {
132 break;
133 }
134
135 if ((new_garbage < min_garbage) || (r->garbage() > garbage_threshold)) {
136 assert(!collection_set->is_in(r), "must not yet be in cset");
137 collection_set->add_region(r);
138 cur_cset = new_cset;
139 cur_garbage = new_garbage;
140 }
141 }
142
143 // Step 2. Try to catch some recently allocated regions for evacuation ride.
144 //
145 // Pessimistically assume we are going to evacuate the entire region. While this
146 // is very pessimistic and in most cases undershoots the collection set when regions
147 // are mostly dead, it also provides more safety against running into allocation
148 // failure when newly allocated regions are fully live.
149
150 for (size_t i = 0; i < cnt; i++) {
151 if (data[i]._seqnum_last_alloc <= _last_cset_select) continue;
152
153 ShenandoahHeapRegion* r = data[i]._region;
154 assert (r->is_regular(), "should have been filtered before");
155
156 // size_t new_garbage = cur_garbage + 0; (implied)
157 size_t new_cset = cur_cset + r->used();
158
159 if (new_cset > max_cset) {
160 break;
161 }
162
163 assert(!collection_set->is_in(r), "must not yet be in cset");
164 collection_set->add_region(r);
165 cur_cset = new_cset;
166 }
167
168 // Step 3. Clear liveness data
169 // TODO: Merge it with step 0, but save live data in RegionData before.
170 for (size_t i = 0; i < heap->num_regions(); i++) {
171 ShenandoahHeapRegion* r = heap->get_region(i);
172 if (r->used() > 0) {
173 r->clear_live_data();
174 }
175 }
176
177 collection_set->update_region_status();
178
179 _last_cset_select = ShenandoahHeapRegion::seqnum_current_alloc();
180 }
181
182 bool ShenandoahTraversalHeuristics::should_start_gc() const {
183 ShenandoahHeap* heap = ShenandoahHeap::heap();
184 assert(!heap->has_forwarded_objects(), "no forwarded objects here");
185
186 size_t capacity = heap->max_capacity();
187 size_t available = heap->free_set()->available();
188
189 // Check if we are falling below the worst limit, time to trigger the GC, regardless of
190 // anything else.
191 size_t min_threshold = capacity / 100 * ShenandoahMinFreeThreshold;
192 if (available < min_threshold) {
193 log_info(gc)("Trigger: Free (" SIZE_FORMAT "M) is below minimum threshold (" SIZE_FORMAT "M)",
194 available / M, min_threshold / M);
195 return true;
196 }
197
198 // Check if are need to learn a bit about the application
199 const size_t max_learn = ShenandoahLearningSteps;
200 if (_gc_times_learned < max_learn) {
201 size_t init_threshold = capacity / 100 * ShenandoahInitFreeThreshold;
202 if (available < init_threshold) {
203 log_info(gc)("Trigger: Learning " SIZE_FORMAT " of " SIZE_FORMAT ". Free (" SIZE_FORMAT "M) is below initial threshold (" SIZE_FORMAT "M)",
204 _gc_times_learned + 1, max_learn, available / M, init_threshold / M);
205 return true;
206 }
207 }
208
209 // Check if allocation headroom is still okay. This also factors in:
210 // 1. Some space to absorb allocation spikes
211 // 2. Accumulated penalties from Degenerated and Full GC
212
213 size_t allocation_headroom = available;
214
215 size_t spike_headroom = capacity / 100 * ShenandoahAllocSpikeFactor;
216 size_t penalties = capacity / 100 * _gc_time_penalties;
217
218 allocation_headroom -= MIN2(allocation_headroom, spike_headroom);
219 allocation_headroom -= MIN2(allocation_headroom, penalties);
220
221 double average_gc = _gc_time_history->avg();
222 double time_since_last = time_since_last_gc();
223 double allocation_rate = heap->bytes_allocated_since_gc_start() / time_since_last;
224
225 if (average_gc > allocation_headroom / allocation_rate) {
226 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)",
227 average_gc * 1000, allocation_rate / M, allocation_headroom / M);
228 log_info(gc, ergo)("Free headroom: " SIZE_FORMAT "M (free) - " SIZE_FORMAT "M (spike) - " SIZE_FORMAT "M (penalties) = " SIZE_FORMAT "M",
229 available / M, spike_headroom / M, penalties / M, allocation_headroom / M);
230 return true;
231 } else if (ShenandoahHeuristics::should_start_gc()) {
232 return true;
233 }
234
235 return false;
236 }
237
238 void ShenandoahTraversalHeuristics::choose_collection_set_from_regiondata(ShenandoahCollectionSet* set,
239 RegionData* data, size_t data_size,
240 size_t free) {
241 ShouldNotReachHere();
242 }