jdk-24/hotspot/src/share/vm/gc/g1/g1Predictions.cpp
Thomas Schatzl b8367b252f 8137082: Factor out G1 prediction code from G1CollectorPolicy and clean up
Factor out G1 prediction code from G1CollectorPolicy into its own class, constify methods of G1CollectorPolicy and move more implementations to the cpp file.

Reviewed-by: jmasa, sangheki, ecaspole, kbarrett
2015-10-15 10:07:28 +02:00

99 lines
3.7 KiB
C++

/*
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* 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
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*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
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#include "precompiled.hpp"
#include "gc/g1/g1Predictions.hpp"
#ifndef PRODUCT
void G1Predictions::test() {
double const epsilon = 1e-6;
{
// Some basic formula tests with confidence = 0.0
G1Predictions predictor(0.0);
TruncatedSeq s;
double p0 = predictor.get_new_prediction(&s);
assert(p0 < epsilon, "Initial prediction of empty sequence must be 0.0 but is %f", p0);
s.add(5.0);
double p1 = predictor.get_new_prediction(&s);
assert(fabs(p1 - 5.0) < epsilon, "Prediction should be 5.0 but is %f", p1);
for (int i = 0; i < 40; i++) {
s.add(5.0);
}
double p2 = predictor.get_new_prediction(&s);
assert(fabs(p2 - 5.0) < epsilon, "Prediction should be 5.0 but is %f", p1);
}
{
// The following tests checks that the initial predictions are based on the
// average of the sequence and not on the stddev (which is 0).
G1Predictions predictor(0.5);
TruncatedSeq s;
s.add(1.0);
double p1 = predictor.get_new_prediction(&s);
assert(p1 > 1.0, "First prediction must be larger than average, but avg is %f and prediction %f", s.davg(), p1);
s.add(1.0);
double p2 = predictor.get_new_prediction(&s);
assert(p2 < p1, "First prediction must be larger than second, but they are %f %f", p1, p2);
s.add(1.0);
double p3 = predictor.get_new_prediction(&s);
assert(p3 < p2, "Second prediction must be larger than third, but they are %f %f", p2, p3);
s.add(1.0);
s.add(1.0); // Five elements are now in the sequence.
double p5 = predictor.get_new_prediction(&s);
assert(p5 < p3, "Fifth prediction must be smaller than third, but they are %f %f", p3, p5);
assert(fabs(p5 - 1.0) < epsilon, "Prediction must be 1.0+epsilon, but is %f", p5);
}
{
// The following tests checks that initially prediction based on the average is
// used, that gets overridden by the stddev prediction at the end.
G1Predictions predictor(0.5);
TruncatedSeq s;
s.add(0.5);
double p1 = predictor.get_new_prediction(&s);
assert(p1 > 0.5, "First prediction must be larger than average, but avg is %f and prediction %f", s.davg(), p1);
s.add(0.2);
double p2 = predictor.get_new_prediction(&s);
assert(p2 < p1, "First prediction must be larger than second, but they are %f %f", p1, p2);
s.add(0.5);
double p3 = predictor.get_new_prediction(&s);
assert(p3 < p2, "Second prediction must be larger than third, but they are %f %f", p2, p3);
s.add(0.2);
s.add(2.0);
double p5 = predictor.get_new_prediction(&s);
assert(p5 > p3, "Fifth prediction must be bigger than third, but they are %f %f", p3, p5);
}
}
void TestPredictions_test() {
G1Predictions::test();
}
#endif