< prev index next > src/hotspot/share/gc/shenandoah/heuristics/shenandoahAdaptiveHeuristics.cpp
Print this page
/*
* Copyright (c) 2018, 2019, Red Hat, Inc. All rights reserved.
+ * Copyright Amazon.com Inc. or its affiliates. All Rights Reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation.
*
*/
#include "precompiled.hpp"
+ #include "gc/shared/gcCause.hpp"
+ #include "gc/shenandoah/heuristics/shenandoahHeuristics.hpp"
+ #include "gc/shenandoah/heuristics/shenandoahSpaceInfo.hpp"
#include "gc/shenandoah/heuristics/shenandoahAdaptiveHeuristics.hpp"
#include "gc/shenandoah/shenandoahCollectionSet.hpp"
+ #include "gc/shenandoah/shenandoahCollectorPolicy.hpp"
#include "gc/shenandoah/shenandoahFreeSet.hpp"
#include "gc/shenandoah/shenandoahHeap.inline.hpp"
#include "gc/shenandoah/shenandoahHeapRegion.inline.hpp"
#include "logging/log.hpp"
#include "logging/logTag.hpp"
+ #include "runtime/globals.hpp"
#include "utilities/quickSort.hpp"
// These constants are used to adjust the margin of error for the moving
// average of the allocation rate and cycle time. The units are standard
// deviations.
// that the true value of our estimate is outside the interval. These are used
// as bounds on the adjustments applied at the outcome of a GC cycle.
const double ShenandoahAdaptiveHeuristics::MINIMUM_CONFIDENCE = 0.319; // 25%
const double ShenandoahAdaptiveHeuristics::MAXIMUM_CONFIDENCE = 3.291; // 99.9%
! ShenandoahAdaptiveHeuristics::ShenandoahAdaptiveHeuristics() :
! ShenandoahHeuristics(),
_margin_of_error_sd(ShenandoahAdaptiveInitialConfidence),
_spike_threshold_sd(ShenandoahAdaptiveInitialSpikeThreshold),
! _last_trigger(OTHER) { }
ShenandoahAdaptiveHeuristics::~ShenandoahAdaptiveHeuristics() {}
void ShenandoahAdaptiveHeuristics::choose_collection_set_from_regiondata(ShenandoahCollectionSet* cset,
RegionData* data, size_t size,
// that the true value of our estimate is outside the interval. These are used
// as bounds on the adjustments applied at the outcome of a GC cycle.
const double ShenandoahAdaptiveHeuristics::MINIMUM_CONFIDENCE = 0.319; // 25%
const double ShenandoahAdaptiveHeuristics::MAXIMUM_CONFIDENCE = 3.291; // 99.9%
! ShenandoahAdaptiveHeuristics::ShenandoahAdaptiveHeuristics(ShenandoahSpaceInfo* space_info) :
! ShenandoahHeuristics(space_info),
_margin_of_error_sd(ShenandoahAdaptiveInitialConfidence),
_spike_threshold_sd(ShenandoahAdaptiveInitialSpikeThreshold),
! _last_trigger(OTHER),
+ _available(Moving_Average_Samples, ShenandoahAdaptiveDecayFactor) { }
ShenandoahAdaptiveHeuristics::~ShenandoahAdaptiveHeuristics() {}
void ShenandoahAdaptiveHeuristics::choose_collection_set_from_regiondata(ShenandoahCollectionSet* cset,
RegionData* data, size_t size,
// Therefore, we start by sorting the regions by garbage. Then we unconditionally add the best candidates
// before we meet min_garbage. Then we add all candidates that fit with a garbage threshold before
// we hit max_cset. When max_cset is hit, we terminate the cset selection. Note that in this scheme,
// ShenandoahGarbageThreshold is the soft threshold which would be ignored until min_garbage is hit.
! size_t capacity = ShenandoahHeap::heap()->soft_max_capacity();
size_t max_cset = (size_t)((1.0 * capacity / 100 * ShenandoahEvacReserve) / ShenandoahEvacWaste);
! size_t free_target = (capacity / 100 * ShenandoahMinFreeThreshold) + max_cset;
! size_t min_garbage = (free_target > actual_free ? (free_target - actual_free) : 0);
log_info(gc, ergo)("Adaptive CSet Selection. Target Free: " SIZE_FORMAT "%s, Actual Free: "
! SIZE_FORMAT "%s, Max CSet: " SIZE_FORMAT "%s, Min Garbage: " SIZE_FORMAT "%s",
byte_size_in_proper_unit(free_target), proper_unit_for_byte_size(free_target),
byte_size_in_proper_unit(actual_free), proper_unit_for_byte_size(actual_free),
byte_size_in_proper_unit(max_cset), proper_unit_for_byte_size(max_cset),
byte_size_in_proper_unit(min_garbage), proper_unit_for_byte_size(min_garbage));
// Therefore, we start by sorting the regions by garbage. Then we unconditionally add the best candidates
// before we meet min_garbage. Then we add all candidates that fit with a garbage threshold before
// we hit max_cset. When max_cset is hit, we terminate the cset selection. Note that in this scheme,
// ShenandoahGarbageThreshold is the soft threshold which would be ignored until min_garbage is hit.
! size_t capacity = _space_info->soft_max_capacity();
size_t max_cset = (size_t)((1.0 * capacity / 100 * ShenandoahEvacReserve) / ShenandoahEvacWaste);
! size_t free_target = (capacity * ShenandoahMinFreeThreshold) / 100 + max_cset;
! size_t min_garbage = (free_target > actual_free) ? (free_target - actual_free) : 0;
log_info(gc, ergo)("Adaptive CSet Selection. Target Free: " SIZE_FORMAT "%s, Actual Free: "
! SIZE_FORMAT "%s, Max Evacuation: " SIZE_FORMAT "%s, Min Garbage: " SIZE_FORMAT "%s",
byte_size_in_proper_unit(free_target), proper_unit_for_byte_size(free_target),
byte_size_in_proper_unit(actual_free), proper_unit_for_byte_size(actual_free),
byte_size_in_proper_unit(max_cset), proper_unit_for_byte_size(max_cset),
byte_size_in_proper_unit(min_garbage), proper_unit_for_byte_size(min_garbage));
size_t cur_cset = 0;
size_t cur_garbage = 0;
for (size_t idx = 0; idx < size; idx++) {
! ShenandoahHeapRegion* r = data[idx]._region;
size_t new_cset = cur_cset + r->get_live_data_bytes();
size_t new_garbage = cur_garbage + r->garbage();
if (new_cset > max_cset) {
size_t cur_cset = 0;
size_t cur_garbage = 0;
for (size_t idx = 0; idx < size; idx++) {
! ShenandoahHeapRegion* r = data[idx].get_region();
size_t new_cset = cur_cset + r->get_live_data_bytes();
size_t new_garbage = cur_garbage + r->garbage();
if (new_cset > max_cset) {
}
void ShenandoahAdaptiveHeuristics::record_success_concurrent() {
ShenandoahHeuristics::record_success_concurrent();
! size_t available = ShenandoahHeap::heap()->free_set()->available();
- _available.add(available);
double z_score = 0.0;
! if (_available.sd() > 0) {
! z_score = (available - _available.avg()) / _available.sd();
}
! log_debug(gc, ergo)("Available: " SIZE_FORMAT " %sB, z-score=%.3f. Average available: %.1f %sB +/- %.1f %sB.",
- byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
- z_score,
- byte_size_in_proper_unit(_available.avg()), proper_unit_for_byte_size(_available.avg()),
- byte_size_in_proper_unit(_available.sd()), proper_unit_for_byte_size(_available.sd()));
// In the case when a concurrent GC cycle completes successfully but with an
// unusually small amount of available memory we will adjust our trigger
// parameters so that they are more likely to initiate a new cycle.
// Conversely, when a GC cycle results in an above average amount of available
}
void ShenandoahAdaptiveHeuristics::record_success_concurrent() {
ShenandoahHeuristics::record_success_concurrent();
! size_t available = _space_info->available();
double z_score = 0.0;
! double available_sd = _available.sd();
! if (available_sd > 0) {
+ double available_avg = _available.avg();
+ z_score = (double(available) - available_avg) / available_sd;
+ log_debug(gc, ergo)("%s Available: " SIZE_FORMAT " %sB, z-score=%.3f. Average available: %.1f %sB +/- %.1f %sB.",
+ _space_info->name(),
+ byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
+ z_score,
+ byte_size_in_proper_unit(available_avg), proper_unit_for_byte_size(available_avg),
+ byte_size_in_proper_unit(available_sd), proper_unit_for_byte_size(available_sd));
}
! _available.add(double(available));
// In the case when a concurrent GC cycle completes successfully but with an
// unusually small amount of available memory we will adjust our trigger
// parameters so that they are more likely to initiate a new cycle.
// Conversely, when a GC cycle results in an above average amount of available
static double saturate(double value, double min, double max) {
return MAX2(MIN2(value, max), min);
}
bool ShenandoahAdaptiveHeuristics::should_start_gc() {
! ShenandoahHeap* heap = ShenandoahHeap::heap();
! size_t max_capacity = heap->max_capacity();
! size_t capacity = heap->soft_max_capacity();
- size_t available = heap->free_set()->available();
- size_t allocated = heap->bytes_allocated_since_gc_start();
! // Make sure the code below treats available without the soft tail.
! size_t soft_tail = max_capacity - capacity;
! available = (available > soft_tail) ? (available - soft_tail) : 0;
// Track allocation rate even if we decide to start a cycle for other reasons.
double rate = _allocation_rate.sample(allocated);
_last_trigger = OTHER;
! size_t min_threshold = capacity / 100 * ShenandoahMinFreeThreshold;
if (available < min_threshold) {
! log_info(gc)("Trigger: Free (" SIZE_FORMAT "%s) is below minimum threshold (" SIZE_FORMAT "%s)",
! byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
byte_size_in_proper_unit(min_threshold), proper_unit_for_byte_size(min_threshold));
return true;
}
const size_t max_learn = ShenandoahLearningSteps;
if (_gc_times_learned < max_learn) {
size_t init_threshold = capacity / 100 * ShenandoahInitFreeThreshold;
if (available < init_threshold) {
! log_info(gc)("Trigger: Learning " SIZE_FORMAT " of " SIZE_FORMAT ". Free (" SIZE_FORMAT "%s) is below initial threshold (" SIZE_FORMAT "%s)",
! _gc_times_learned + 1, max_learn,
! byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
byte_size_in_proper_unit(init_threshold), proper_unit_for_byte_size(init_threshold));
return true;
}
}
-
// Check if allocation headroom is still okay. This also factors in:
! // 1. Some space to absorb allocation spikes
// 2. Accumulated penalties from Degenerated and Full GC
size_t allocation_headroom = available;
size_t spike_headroom = capacity / 100 * ShenandoahAllocSpikeFactor;
size_t penalties = capacity / 100 * _gc_time_penalties;
allocation_headroom -= MIN2(allocation_headroom, spike_headroom);
allocation_headroom -= MIN2(allocation_headroom, penalties);
! double avg_cycle_time = _gc_time_history->davg() + (_margin_of_error_sd * _gc_time_history->dsd());
double avg_alloc_rate = _allocation_rate.upper_bound(_margin_of_error_sd);
if (avg_cycle_time * avg_alloc_rate > allocation_headroom) {
! log_info(gc)("Trigger: Average GC time (%.2f ms) is above the time for average allocation rate (%.0f %sB/s) to deplete free headroom (" SIZE_FORMAT "%s) (margin of error = %.2f)",
! avg_cycle_time * 1000,
byte_size_in_proper_unit(avg_alloc_rate), proper_unit_for_byte_size(avg_alloc_rate),
byte_size_in_proper_unit(allocation_headroom), proper_unit_for_byte_size(allocation_headroom),
_margin_of_error_sd);
-
log_info(gc, ergo)("Free headroom: " SIZE_FORMAT "%s (free) - " SIZE_FORMAT "%s (spike) - " SIZE_FORMAT "%s (penalties) = " SIZE_FORMAT "%s",
byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
byte_size_in_proper_unit(spike_headroom), proper_unit_for_byte_size(spike_headroom),
byte_size_in_proper_unit(penalties), proper_unit_for_byte_size(penalties),
byte_size_in_proper_unit(allocation_headroom), proper_unit_for_byte_size(allocation_headroom));
-
_last_trigger = RATE;
return true;
}
bool is_spiking = _allocation_rate.is_spiking(rate, _spike_threshold_sd);
if (is_spiking && avg_cycle_time > allocation_headroom / rate) {
! log_info(gc)("Trigger: Average GC time (%.2f ms) is above the time for instantaneous allocation rate (%.0f %sB/s) to deplete free headroom (" SIZE_FORMAT "%s) (spike threshold = %.2f)",
! avg_cycle_time * 1000,
byte_size_in_proper_unit(rate), proper_unit_for_byte_size(rate),
byte_size_in_proper_unit(allocation_headroom), proper_unit_for_byte_size(allocation_headroom),
_spike_threshold_sd);
_last_trigger = SPIKE;
return true;
static double saturate(double value, double min, double max) {
return MAX2(MIN2(value, max), min);
}
+ // Rationale:
+ // The idea is that there is an average allocation rate and there are occasional abnormal bursts (or spikes) of
+ // allocations that exceed the average allocation rate. What do these spikes look like?
+ //
+ // 1. At certain phase changes, we may discard large amounts of data and replace it with large numbers of newly
+ // allocated objects. This "spike" looks more like a phase change. We were in steady state at M bytes/sec
+ // allocation rate and now we're in a "reinitialization phase" that looks like N bytes/sec. We need the "spike"
+ // accommodation to give us enough runway to recalibrate our "average allocation rate".
+ //
+ // 2. The typical workload changes. "Suddenly", our typical workload of N TPS increases to N+delta TPS. This means
+ // our average allocation rate needs to be adjusted. Once again, we need the "spike" accomodation to give us
+ // enough runway to recalibrate our "average allocation rate".
+ //
+ // 3. Though there is an "average" allocation rate, a given workload's demand for allocation may be very bursty. We
+ // allocate a bunch of LABs during the 5 ms that follow completion of a GC, then we perform no more allocations for
+ // the next 150 ms. It seems we want the "spike" to represent the maximum divergence from average within the
+ // period of time between consecutive evaluation of the should_start_gc() service. Here's the thinking:
+ //
+ // a) Between now and the next time I ask whether should_start_gc(), we might experience a spike representing
+ // the anticipated burst of allocations. If that would put us over budget, then we should start GC immediately.
+ // b) Between now and the anticipated depletion of allocation pool, there may be two or more bursts of allocations.
+ // If there are more than one of these bursts, we can "approximate" that these will be separated by spans of
+ // time with very little or no allocations so the "average" allocation rate should be a suitable approximation
+ // of how this will behave.
+ //
+ // For cases 1 and 2, we need to "quickly" recalibrate the average allocation rate whenever we detect a change
+ // in operation mode. We want some way to decide that the average rate has changed, while keeping average
+ // allocation rate computation independent.
bool ShenandoahAdaptiveHeuristics::should_start_gc() {
! size_t capacity = _space_info->soft_max_capacity();
! size_t available = _space_info->soft_available();
! size_t allocated = _space_info->bytes_allocated_since_gc_start();
! log_debug(gc)("should_start_gc (%s)? available: " SIZE_FORMAT ", soft_max_capacity: " SIZE_FORMAT
! ", allocated: " SIZE_FORMAT,
! _space_info->name(), available, capacity, allocated);
// Track allocation rate even if we decide to start a cycle for other reasons.
double rate = _allocation_rate.sample(allocated);
_last_trigger = OTHER;
! size_t min_threshold = min_free_threshold();
if (available < min_threshold) {
! log_info(gc)("Trigger (%s): Free (" SIZE_FORMAT "%s) is below minimum threshold (" SIZE_FORMAT "%s)", _space_info->name(),
! byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
byte_size_in_proper_unit(min_threshold), proper_unit_for_byte_size(min_threshold));
return true;
}
+ // Check if we need to learn a bit about the application
const size_t max_learn = ShenandoahLearningSteps;
if (_gc_times_learned < max_learn) {
size_t init_threshold = capacity / 100 * ShenandoahInitFreeThreshold;
if (available < init_threshold) {
! log_info(gc)("Trigger (%s): Learning " SIZE_FORMAT " of " SIZE_FORMAT ". Free (" SIZE_FORMAT "%s) is below initial threshold (" SIZE_FORMAT "%s)",
! _space_info->name(), _gc_times_learned + 1, max_learn,
! byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
byte_size_in_proper_unit(init_threshold), proper_unit_for_byte_size(init_threshold));
return true;
}
}
// Check if allocation headroom is still okay. This also factors in:
! // 1. Some space to absorb allocation spikes (ShenandoahAllocSpikeFactor)
// 2. Accumulated penalties from Degenerated and Full GC
size_t allocation_headroom = available;
size_t spike_headroom = capacity / 100 * ShenandoahAllocSpikeFactor;
size_t penalties = capacity / 100 * _gc_time_penalties;
allocation_headroom -= MIN2(allocation_headroom, spike_headroom);
allocation_headroom -= MIN2(allocation_headroom, penalties);
! double avg_cycle_time = _gc_cycle_time_history->davg() + (_margin_of_error_sd * _gc_cycle_time_history->dsd());
double avg_alloc_rate = _allocation_rate.upper_bound(_margin_of_error_sd);
+ log_debug(gc)("%s: average GC time: %.2f ms, allocation rate: %.0f %s/s",
+ _space_info->name(),
+ avg_cycle_time * 1000, byte_size_in_proper_unit(avg_alloc_rate), proper_unit_for_byte_size(avg_alloc_rate));
if (avg_cycle_time * avg_alloc_rate > allocation_headroom) {
! log_info(gc)("Trigger (%s): Average GC time (%.2f ms) is above the time for average allocation rate (%.0f %sB/s)"
! " to deplete free headroom (" SIZE_FORMAT "%s) (margin of error = %.2f)",
+ _space_info->name(), avg_cycle_time * 1000,
byte_size_in_proper_unit(avg_alloc_rate), proper_unit_for_byte_size(avg_alloc_rate),
byte_size_in_proper_unit(allocation_headroom), proper_unit_for_byte_size(allocation_headroom),
_margin_of_error_sd);
log_info(gc, ergo)("Free headroom: " SIZE_FORMAT "%s (free) - " SIZE_FORMAT "%s (spike) - " SIZE_FORMAT "%s (penalties) = " SIZE_FORMAT "%s",
byte_size_in_proper_unit(available), proper_unit_for_byte_size(available),
byte_size_in_proper_unit(spike_headroom), proper_unit_for_byte_size(spike_headroom),
byte_size_in_proper_unit(penalties), proper_unit_for_byte_size(penalties),
byte_size_in_proper_unit(allocation_headroom), proper_unit_for_byte_size(allocation_headroom));
_last_trigger = RATE;
return true;
}
bool is_spiking = _allocation_rate.is_spiking(rate, _spike_threshold_sd);
if (is_spiking && avg_cycle_time > allocation_headroom / rate) {
! log_info(gc)("Trigger (%s): Average GC time (%.2f ms) is above the time for instantaneous allocation rate (%.0f %sB/s) to deplete free headroom (" SIZE_FORMAT "%s) (spike threshold = %.2f)",
! _space_info->name(), avg_cycle_time * 1000,
byte_size_in_proper_unit(rate), proper_unit_for_byte_size(rate),
byte_size_in_proper_unit(allocation_headroom), proper_unit_for_byte_size(allocation_headroom),
_spike_threshold_sd);
_last_trigger = SPIKE;
return true;
void ShenandoahAdaptiveHeuristics::adjust_spike_threshold(double amount) {
_spike_threshold_sd = saturate(_spike_threshold_sd - amount, MINIMUM_CONFIDENCE, MAXIMUM_CONFIDENCE);
log_debug(gc, ergo)("Spike threshold now: %.2f", _spike_threshold_sd);
}
+ size_t ShenandoahAdaptiveHeuristics::min_free_threshold() {
+ // Note that soft_max_capacity() / 100 * min_free_threshold is smaller than max_capacity() / 100 * min_free_threshold.
+ // We want to behave conservatively here, so use max_capacity(). By returning a larger value, we cause the GC to
+ // trigger when the remaining amount of free shrinks below the larger threshold.
+ return _space_info->max_capacity() / 100 * ShenandoahMinFreeThreshold;
+ }
+
ShenandoahAllocationRate::ShenandoahAllocationRate() :
_last_sample_time(os::elapsedTime()),
_last_sample_value(0),
_interval_sec(1.0 / ShenandoahAdaptiveSampleFrequencyHz),
_rate(int(ShenandoahAdaptiveSampleSizeSeconds * ShenandoahAdaptiveSampleFrequencyHz), ShenandoahAdaptiveDecayFactor),
< prev index next >