5 * This code is free software; you can redistribute it and/or modify it
6 * under the terms of the GNU General Public License version 2 only, as
7 * published by the Free Software Foundation.
8 *
9 * This code is distributed in the hope that it will be useful, but WITHOUT
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
12 * version 2 for more details (a copy is included in the LICENSE file that
13 * accompanied this code).
14 *
15 * You should have received a copy of the GNU General Public License version
16 * 2 along with this work; if not, write to the Free Software Foundation,
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18 *
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
20 * or visit www.oracle.com if you need additional information or have any
21 * questions.
22 *
23 */
24
25 #ifndef SHARE_VM_GC_IMPLEMENTATION_SHARED_GCUTIL_HPP
26 #define SHARE_VM_GC_IMPLEMENTATION_SHARED_GCUTIL_HPP
27
28 #include "memory/allocation.hpp"
29 #include "runtime/timer.hpp"
30 #include "utilities/debug.hpp"
31 #include "utilities/globalDefinitions.hpp"
32 #include "utilities/ostream.hpp"
33
34 // Catch-all file for utility classes
35
36 // A weighted average maintains a running, weighted average
37 // of some float value (templates would be handy here if we
38 // need different types).
39 //
40 // The average is adaptive in that we smooth it for the
41 // initial samples; we don't use the weight until we have
42 // enough samples for it to be meaningful.
43 //
44 // This serves as our best estimate of a future unknown.
45 //
46 class AdaptiveWeightedAverage : public CHeapObj<mtGC> {
199 double _sum_xy; // sum of all x * y.
200 double _intercept; // constant term
201 double _slope; // slope
202 // The weighted averages are not currently used but perhaps should
203 // be used to get decaying averages.
204 AdaptiveWeightedAverage _mean_x; // weighted mean of independent variable
205 AdaptiveWeightedAverage _mean_y; // weighted mean of dependent variable
206
207 public:
208 LinearLeastSquareFit(unsigned weight);
209 void update(double x, double y);
210 double y(double x);
211 double slope() { return _slope; }
212 // Methods to decide if a change in the dependent variable will
213 // achieve a desired goal. Note that these methods are not
214 // complementary and both are needed.
215 bool decrement_will_decrease();
216 bool increment_will_decrease();
217 };
218
219 #endif // SHARE_VM_GC_IMPLEMENTATION_SHARED_GCUTIL_HPP
|
5 * This code is free software; you can redistribute it and/or modify it
6 * under the terms of the GNU General Public License version 2 only, as
7 * published by the Free Software Foundation.
8 *
9 * This code is distributed in the hope that it will be useful, but WITHOUT
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
12 * version 2 for more details (a copy is included in the LICENSE file that
13 * accompanied this code).
14 *
15 * You should have received a copy of the GNU General Public License version
16 * 2 along with this work; if not, write to the Free Software Foundation,
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18 *
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
20 * or visit www.oracle.com if you need additional information or have any
21 * questions.
22 *
23 */
24
25 #ifndef SHARE_VM_GC_SHARED_GCUTIL_HPP
26 #define SHARE_VM_GC_SHARED_GCUTIL_HPP
27
28 #include "memory/allocation.hpp"
29 #include "runtime/timer.hpp"
30 #include "utilities/debug.hpp"
31 #include "utilities/globalDefinitions.hpp"
32 #include "utilities/ostream.hpp"
33
34 // Catch-all file for utility classes
35
36 // A weighted average maintains a running, weighted average
37 // of some float value (templates would be handy here if we
38 // need different types).
39 //
40 // The average is adaptive in that we smooth it for the
41 // initial samples; we don't use the weight until we have
42 // enough samples for it to be meaningful.
43 //
44 // This serves as our best estimate of a future unknown.
45 //
46 class AdaptiveWeightedAverage : public CHeapObj<mtGC> {
199 double _sum_xy; // sum of all x * y.
200 double _intercept; // constant term
201 double _slope; // slope
202 // The weighted averages are not currently used but perhaps should
203 // be used to get decaying averages.
204 AdaptiveWeightedAverage _mean_x; // weighted mean of independent variable
205 AdaptiveWeightedAverage _mean_y; // weighted mean of dependent variable
206
207 public:
208 LinearLeastSquareFit(unsigned weight);
209 void update(double x, double y);
210 double y(double x);
211 double slope() { return _slope; }
212 // Methods to decide if a change in the dependent variable will
213 // achieve a desired goal. Note that these methods are not
214 // complementary and both are needed.
215 bool decrement_will_decrease();
216 bool increment_will_decrease();
217 };
218
219 #endif // SHARE_VM_GC_SHARED_GCUTIL_HPP
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