gcUtil.hpp revision 8413:92457dfb91bd
1236884Smm/* 2236884Smm * Copyright (c) 2002, 2015, Oracle and/or its affiliates. All rights reserved. 3236884Smm * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. 4236884Smm * 5236884Smm * This code is free software; you can redistribute it and/or modify it 6236884Smm * under the terms of the GNU General Public License version 2 only, as 7236884Smm * published by the Free Software Foundation. 8236884Smm * 9236884Smm * This code is distributed in the hope that it will be useful, but WITHOUT 10236884Smm * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or 11236884Smm * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License 12236884Smm * version 2 for more details (a copy is included in the LICENSE file that 13236884Smm * accompanied this code). 14236884Smm * 15236884Smm * You should have received a copy of the GNU General Public License version 16236884Smm * 2 along with this work; if not, write to the Free Software Foundation, 17236884Smm * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. 18236884Smm * 19236884Smm * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA 20236884Smm * or visit www.oracle.com if you need additional information or have any 21236884Smm * questions. 22236884Smm * 23286708Smav */ 24246586Sdelphij 25255750Sdelphij#ifndef SHARE_VM_GC_SHARED_GCUTIL_HPP 26268126Sdelphij#define SHARE_VM_GC_SHARED_GCUTIL_HPP 27236884Smm 28236884Smm#include "memory/allocation.hpp" 29236884Smm#include "runtime/timer.hpp" 30236884Smm#include "utilities/debug.hpp" 31236884Smm#include "utilities/globalDefinitions.hpp" 32236884Smm#include "utilities/ostream.hpp" 33236884Smm 34236884Smm// Catch-all file for utility classes 35236884Smm 36236884Smm// A weighted average maintains a running, weighted average 37236884Smm// of some float value (templates would be handy here if we 38236884Smm// need different types). 39236884Smm// 40236884Smm// The average is adaptive in that we smooth it for the 41236884Smm// initial samples; we don't use the weight until we have 42236884Smm// enough samples for it to be meaningful. 43236884Smm// 44236884Smm// This serves as our best estimate of a future unknown. 45236884Smm// 46236884Smmclass AdaptiveWeightedAverage : public CHeapObj<mtGC> { 47236884Smm private: 48236884Smm float _average; // The last computed average 49236884Smm unsigned _sample_count; // How often we've sampled this average 50236884Smm unsigned _weight; // The weight used to smooth the averages 51236884Smm // A higher weight favors the most 52236884Smm // recent data. 53236884Smm bool _is_old; // Has enough historical data 54236884Smm 55236884Smm const static unsigned OLD_THRESHOLD = 100; 56236884Smm 57236884Smm protected: 58236884Smm float _last_sample; // The last value sampled. 59274337Sdelphij 60274337Sdelphij void increment_count() { 61236884Smm _sample_count++; 62236884Smm if (!_is_old && _sample_count > OLD_THRESHOLD) { 63236884Smm _is_old = true; 64236884Smm } 65236884Smm } 66236884Smm 67236884Smm void set_average(float avg) { _average = avg; } 68236884Smm 69236884Smm // Helper function, computes an adaptive weighted average 70236884Smm // given a sample and the last average 71236884Smm float compute_adaptive_average(float new_sample, float average); 72236884Smm 73236884Smm public: 74236884Smm // Input weight must be between 0 and 100 75236884Smm AdaptiveWeightedAverage(unsigned weight, float avg = 0.0) : 76236884Smm _average(avg), _sample_count(0), _weight(weight), _last_sample(0.0), 77236884Smm _is_old(false) { 78236884Smm } 79236884Smm 80236884Smm void clear() { 81236884Smm _average = 0; 82236884Smm _sample_count = 0; 83236884Smm _last_sample = 0; 84236884Smm _is_old = false; 85236884Smm } 86236884Smm 87236884Smm // Useful for modifying static structures after startup. 88236884Smm void modify(size_t avg, unsigned wt, bool force = false) { 89236884Smm assert(force, "Are you sure you want to call this?"); 90236884Smm _average = (float)avg; 91236884Smm _weight = wt; 92236884Smm } 93236884Smm 94236884Smm // Accessors 95236884Smm float average() const { return _average; } 96259813Sdelphij unsigned weight() const { return _weight; } 97236884Smm unsigned count() const { return _sample_count; } 98259813Sdelphij float last_sample() const { return _last_sample; } 99259813Sdelphij bool is_old() const { return _is_old; } 100236884Smm 101259813Sdelphij // Update data with a new sample. 102236884Smm void sample(float new_sample); 103236884Smm 104236884Smm static inline float exp_avg(float avg, float sample, 105259813Sdelphij unsigned int weight) { 106236884Smm assert(weight <= 100, "weight must be a percent"); 107259813Sdelphij return (100.0F - weight) * avg / 100.0F + weight * sample / 100.0F; 108236884Smm } 109236884Smm static inline size_t exp_avg(size_t avg, size_t sample, 110236884Smm unsigned int weight) { 111259813Sdelphij // Convert to float and back to avoid integer overflow. 112236884Smm return (size_t)exp_avg((float)avg, (float)sample, weight); 113236884Smm } 114236884Smm 115236884Smm // Printing 116236884Smm void print_on(outputStream* st) const; 117236884Smm void print() const; 118236884Smm}; 119260150Sdelphij 120289562Smav 121289562Smav// A weighted average that includes a deviation from the average, 122260150Sdelphij// some multiple of which is added to the average. 123260150Sdelphij// 124260150Sdelphij// This serves as our best estimate of an upper bound on a future 125260150Sdelphij// unknown. 126260150Sdelphijclass AdaptivePaddedAverage : public AdaptiveWeightedAverage { 127260150Sdelphij private: 128260150Sdelphij float _padded_avg; // The last computed padded average 129260150Sdelphij float _deviation; // Running deviation from the average 130260150Sdelphij unsigned _padding; // A multiple which, added to the average, 131236884Smm // gives us an upper bound guess. 132259813Sdelphij 133286708Smav protected: 134236884Smm void set_padded_average(float avg) { _padded_avg = avg; } 135236884Smm void set_deviation(float dev) { _deviation = dev; } 136259813Sdelphij 137236884Smm public: 138236884Smm AdaptivePaddedAverage() : 139236884Smm AdaptiveWeightedAverage(0), 140286708Smav _padded_avg(0.0), _deviation(0.0), _padding(0) {} 141286708Smav 142236884Smm AdaptivePaddedAverage(unsigned weight, unsigned padding) : 143236884Smm AdaptiveWeightedAverage(weight), 144236884Smm _padded_avg(0.0), _deviation(0.0), _padding(padding) {} 145236884Smm 146236884Smm // Placement support 147236884Smm void* operator new(size_t ignored, void* p) throw() { return p; } 148259813Sdelphij // Allocator 149236884Smm void* operator new(size_t size) throw() { return CHeapObj<mtGC>::operator new(size); } 150236884Smm 151236884Smm // Accessor 152286708Smav float padded_average() const { return _padded_avg; } 153236884Smm float deviation() const { return _deviation; } 154236884Smm unsigned padding() const { return _padding; } 155236884Smm 156236884Smm void clear() { 157236884Smm AdaptiveWeightedAverage::clear(); 158236884Smm _padded_avg = 0; 159236884Smm _deviation = 0; 160236884Smm } 161286708Smav 162286708Smav // Override 163260150Sdelphij void sample(float new_sample); 164239774Smm 165239774Smm // Printing 166286708Smav void print_on(outputStream* st) const; 167286708Smav void print() const; 168260150Sdelphij}; 169246586Sdelphij 170246586Sdelphij// A weighted average that includes a deviation from the average, 171286708Smav// some multiple of which is added to the average. 172286708Smav// 173260150Sdelphij// This serves as our best estimate of an upper bound on a future 174255750Sdelphij// unknown. 175255750Sdelphij// A special sort of padded average: it doesn't update deviations 176286708Smav// if the sample is zero. The average is allowed to change. We're 177286708Smav// preventing the zero samples from drastically changing our padded 178260150Sdelphij// average. 179258717Savgclass AdaptivePaddedNoZeroDevAverage : public AdaptivePaddedAverage { 180258717Savgpublic: 181286708Smav AdaptivePaddedNoZeroDevAverage(unsigned weight, unsigned padding) : 182286708Smav AdaptivePaddedAverage(weight, padding) {} 183260150Sdelphij // Override 184260150Sdelphij void sample(float new_sample); 185260150Sdelphij 186286708Smav // Printing 187286708Smav void print_on(outputStream* st) const; 188260150Sdelphij void print() const; 189260150Sdelphij}; 190260150Sdelphij 191260150Sdelphij// Use a least squares fit to a set of data to generate a linear 192260150Sdelphij// equation. 193260150Sdelphij// y = intercept + slope * x 194286708Smav 195286708Smavclass LinearLeastSquareFit : public CHeapObj<mtGC> { 196260150Sdelphij double _sum_x; // sum of all independent data points x 197259813Sdelphij double _sum_x_squared; // sum of all independent data points x**2 198259813Sdelphij double _sum_y; // sum of all dependent data points y 199259813Sdelphij double _sum_xy; // sum of all x * y. 200286708Smav double _intercept; // constant term 201260183Sdelphij double _slope; // slope 202260183Sdelphij // The weighted averages are not currently used but perhaps should 203260183Sdelphij // be used to get decaying averages. 204260183Sdelphij AdaptiveWeightedAverage _mean_x; // weighted mean of independent variable 205260183Sdelphij AdaptiveWeightedAverage _mean_y; // weighted mean of dependent variable 206260183Sdelphij 207260183Sdelphij public: 208260183Sdelphij LinearLeastSquareFit(unsigned weight); 209286708Smav void update(double x, double y); 210264835Sdelphij double y(double x); 211264835Sdelphij double slope() { return _slope; } 212264835Sdelphij // Methods to decide if a change in the dependent variable will 213264835Sdelphij // achieve a desired goal. Note that these methods are not 214264835Sdelphij // complementary and both are needed. 215264835Sdelphij bool decrement_will_decrease(); 216264835Sdelphij bool increment_will_decrease(); 217286708Smav}; 218286708Smav 219268075Sdelphij#endif // SHARE_VM_GC_SHARED_GCUTIL_HPP 220268075Sdelphij