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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.rng.examples.jmh.sampling.distribution;
import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.BenchmarkMode;
import org.openjdk.jmh.annotations.Mode;
import org.openjdk.jmh.annotations.Warmup;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.State;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.Scope;
import org.openjdk.jmh.annotations.OutputTimeUnit;
import java.util.concurrent.TimeUnit;
import java.util.Random;
/**
* Benchmark for {@link Random#nextGaussian()} in order to compare
* the speed of generation of normally-distributed random numbers.
*/
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.NANOSECONDS)
@Warmup(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@State(Scope.Benchmark)
@Fork(value = 1, jvmArgs = {"-server", "-Xms128M", "-Xmx128M"})
public class NextGaussianPerformance {
/** JDK's generator. */
private final Random random = new Random();
/**
* The value.
*
* <p>This must NOT be final!</p>
*/
private double value;
/**
* Baseline for the JMH timing overhead for production of an {@code double} value.
*
* @return the {@code double} value
*/
@Benchmark
public double baseline() {
return value;
}
/**
* Run JDK random gaussian sampler.
*
* @return the double
*/
@Benchmark
public double runJDKRandomGaussianSampler() {
return random.nextGaussian();
}
}