duke@435: /*
coleenp@5614:  * Copyright (c) 2002, 2013, Oracle and/or its affiliates. All rights reserved.
duke@435:  * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
duke@435:  *
duke@435:  * This code is free software; you can redistribute it and/or modify it
duke@435:  * under the terms of the GNU General Public License version 2 only, as
duke@435:  * published by the Free Software Foundation.
duke@435:  *
duke@435:  * This code is distributed in the hope that it will be useful, but WITHOUT
duke@435:  * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
duke@435:  * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
duke@435:  * version 2 for more details (a copy is included in the LICENSE file that
duke@435:  * accompanied this code).
duke@435:  *
duke@435:  * You should have received a copy of the GNU General Public License version
duke@435:  * 2 along with this work; if not, write to the Free Software Foundation,
duke@435:  * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
duke@435:  *
trims@1907:  * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
trims@1907:  * or visit www.oracle.com if you need additional information or have any
trims@1907:  * questions.
duke@435:  *
duke@435:  */
duke@435: 
stefank@2314: #ifndef SHARE_VM_GC_IMPLEMENTATION_SHARED_GCUTIL_HPP
stefank@2314: #define SHARE_VM_GC_IMPLEMENTATION_SHARED_GCUTIL_HPP
stefank@2314: 
stefank@2314: #include "memory/allocation.hpp"
stefank@2314: #include "runtime/timer.hpp"
stefank@2314: #include "utilities/debug.hpp"
stefank@2314: #include "utilities/globalDefinitions.hpp"
stefank@2314: #include "utilities/ostream.hpp"
stefank@2314: 
duke@435: // Catch-all file for utility classes
duke@435: 
duke@435: // A weighted average maintains a running, weighted average
duke@435: // of some float value (templates would be handy here if we
duke@435: // need different types).
duke@435: //
duke@435: // The average is adaptive in that we smooth it for the
duke@435: // initial samples; we don't use the weight until we have
duke@435: // enough samples for it to be meaningful.
duke@435: //
duke@435: // This serves as our best estimate of a future unknown.
duke@435: //
zgu@3900: class AdaptiveWeightedAverage : public CHeapObj<mtGC> {
duke@435:  private:
duke@435:   float            _average;        // The last computed average
duke@435:   unsigned         _sample_count;   // How often we've sampled this average
duke@435:   unsigned         _weight;         // The weight used to smooth the averages
duke@435:                                     //   A higher weight favors the most
duke@435:                                     //   recent data.
mikael@3763:   bool             _is_old;         // Has enough historical data
mikael@3763: 
mikael@3763:   const static unsigned OLD_THRESHOLD = 100;
duke@435: 
duke@435:  protected:
duke@435:   float            _last_sample;    // The last value sampled.
duke@435: 
mikael@3763:   void  increment_count() {
mikael@3763:     _sample_count++;
mikael@3763:     if (!_is_old && _sample_count > OLD_THRESHOLD) {
mikael@3763:       _is_old = true;
mikael@3763:     }
mikael@3763:   }
mikael@3763: 
duke@435:   void  set_average(float avg)  { _average = avg;        }
duke@435: 
duke@435:   // Helper function, computes an adaptive weighted average
duke@435:   // given a sample and the last average
duke@435:   float compute_adaptive_average(float new_sample, float average);
duke@435: 
duke@435:  public:
duke@435:   // Input weight must be between 0 and 100
ysr@1580:   AdaptiveWeightedAverage(unsigned weight, float avg = 0.0) :
mikael@3763:     _average(avg), _sample_count(0), _weight(weight), _last_sample(0.0),
mikael@3763:     _is_old(false) {
duke@435:   }
duke@435: 
iveresov@703:   void clear() {
iveresov@703:     _average = 0;
iveresov@703:     _sample_count = 0;
iveresov@703:     _last_sample = 0;
mikael@3763:     _is_old = false;
iveresov@703:   }
iveresov@703: 
ysr@1580:   // Useful for modifying static structures after startup.
ysr@1580:   void  modify(size_t avg, unsigned wt, bool force = false)  {
ysr@1580:     assert(force, "Are you sure you want to call this?");
ysr@1580:     _average = (float)avg;
ysr@1580:     _weight  = wt;
ysr@1580:   }
ysr@1580: 
duke@435:   // Accessors
duke@435:   float    average() const       { return _average;       }
duke@435:   unsigned weight()  const       { return _weight;        }
duke@435:   unsigned count()   const       { return _sample_count;  }
mikael@3763:   float    last_sample() const   { return _last_sample;   }
mikael@3763:   bool     is_old()  const       { return _is_old;        }
duke@435: 
duke@435:   // Update data with a new sample.
duke@435:   void sample(float new_sample);
duke@435: 
duke@435:   static inline float exp_avg(float avg, float sample,
duke@435:                                unsigned int weight) {
duke@435:     assert(0 <= weight && weight <= 100, "weight must be a percent");
duke@435:     return (100.0F - weight) * avg / 100.0F + weight * sample / 100.0F;
duke@435:   }
duke@435:   static inline size_t exp_avg(size_t avg, size_t sample,
duke@435:                                unsigned int weight) {
duke@435:     // Convert to float and back to avoid integer overflow.
duke@435:     return (size_t)exp_avg((float)avg, (float)sample, weight);
duke@435:   }
ysr@1580: 
ysr@1580:   // Printing
ysr@1580:   void print_on(outputStream* st) const;
ysr@1580:   void print() const;
duke@435: };
duke@435: 
duke@435: 
duke@435: // A weighted average that includes a deviation from the average,
duke@435: // some multiple of which is added to the average.
duke@435: //
duke@435: // This serves as our best estimate of an upper bound on a future
duke@435: // unknown.
duke@435: class AdaptivePaddedAverage : public AdaptiveWeightedAverage {
duke@435:  private:
duke@435:   float          _padded_avg;     // The last computed padded average
duke@435:   float          _deviation;      // Running deviation from the average
duke@435:   unsigned       _padding;        // A multiple which, added to the average,
duke@435:                                   // gives us an upper bound guess.
duke@435: 
duke@435:  protected:
duke@435:   void set_padded_average(float avg)  { _padded_avg = avg;  }
duke@435:   void set_deviation(float dev)       { _deviation  = dev;  }
duke@435: 
duke@435:  public:
duke@435:   AdaptivePaddedAverage() :
duke@435:     AdaptiveWeightedAverage(0),
duke@435:     _padded_avg(0.0), _deviation(0.0), _padding(0) {}
duke@435: 
duke@435:   AdaptivePaddedAverage(unsigned weight, unsigned padding) :
duke@435:     AdaptiveWeightedAverage(weight),
duke@435:     _padded_avg(0.0), _deviation(0.0), _padding(padding) {}
duke@435: 
duke@435:   // Placement support
coleenp@5614:   void* operator new(size_t ignored, void* p) throw() { return p; }
duke@435:   // Allocator
coleenp@5614:   void* operator new(size_t size) throw() { return CHeapObj<mtGC>::operator new(size); }
duke@435: 
duke@435:   // Accessor
duke@435:   float padded_average() const         { return _padded_avg; }
duke@435:   float deviation()      const         { return _deviation;  }
duke@435:   unsigned padding()     const         { return _padding;    }
duke@435: 
iveresov@703:   void clear() {
iveresov@703:     AdaptiveWeightedAverage::clear();
iveresov@703:     _padded_avg = 0;
iveresov@703:     _deviation = 0;
iveresov@703:   }
iveresov@703: 
duke@435:   // Override
duke@435:   void  sample(float new_sample);
ysr@1580: 
ysr@1580:   // Printing
ysr@1580:   void print_on(outputStream* st) const;
ysr@1580:   void print() const;
duke@435: };
duke@435: 
duke@435: // A weighted average that includes a deviation from the average,
duke@435: // some multiple of which is added to the average.
duke@435: //
duke@435: // This serves as our best estimate of an upper bound on a future
duke@435: // unknown.
duke@435: // A special sort of padded average:  it doesn't update deviations
duke@435: // if the sample is zero. The average is allowed to change. We're
duke@435: // preventing the zero samples from drastically changing our padded
duke@435: // average.
duke@435: class AdaptivePaddedNoZeroDevAverage : public AdaptivePaddedAverage {
duke@435: public:
duke@435:   AdaptivePaddedNoZeroDevAverage(unsigned weight, unsigned padding) :
duke@435:     AdaptivePaddedAverage(weight, padding)  {}
duke@435:   // Override
duke@435:   void  sample(float new_sample);
ysr@1580: 
ysr@1580:   // Printing
ysr@1580:   void print_on(outputStream* st) const;
ysr@1580:   void print() const;
duke@435: };
ysr@1580: 
duke@435: // Use a least squares fit to a set of data to generate a linear
duke@435: // equation.
duke@435: //              y = intercept + slope * x
duke@435: 
zgu@3900: class LinearLeastSquareFit : public CHeapObj<mtGC> {
duke@435:   double _sum_x;        // sum of all independent data points x
duke@435:   double _sum_x_squared; // sum of all independent data points x**2
duke@435:   double _sum_y;        // sum of all dependent data points y
duke@435:   double _sum_xy;       // sum of all x * y.
duke@435:   double _intercept;     // constant term
duke@435:   double _slope;        // slope
duke@435:   // The weighted averages are not currently used but perhaps should
duke@435:   // be used to get decaying averages.
duke@435:   AdaptiveWeightedAverage _mean_x; // weighted mean of independent variable
duke@435:   AdaptiveWeightedAverage _mean_y; // weighted mean of dependent variable
duke@435: 
duke@435:  public:
duke@435:   LinearLeastSquareFit(unsigned weight);
duke@435:   void update(double x, double y);
duke@435:   double y(double x);
duke@435:   double slope() { return _slope; }
duke@435:   // Methods to decide if a change in the dependent variable will
duke@435:   // achive a desired goal.  Note that these methods are not
duke@435:   // complementary and both are needed.
duke@435:   bool decrement_will_decrease();
duke@435:   bool increment_will_decrease();
duke@435: };
duke@435: 
duke@435: class GCPauseTimer : StackObj {
duke@435:   elapsedTimer* _timer;
duke@435:  public:
duke@435:   GCPauseTimer(elapsedTimer* timer) {
duke@435:     _timer = timer;
duke@435:     _timer->stop();
duke@435:   }
duke@435:   ~GCPauseTimer() {
duke@435:     _timer->start();
duke@435:   }
duke@435: };
stefank@2314: 
stefank@2314: #endif // SHARE_VM_GC_IMPLEMENTATION_SHARED_GCUTIL_HPP