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new 65ebfaa Delete benchmark file that used the previous API.
65ebfaa is described below
commit 65ebfaa427f8f8d6b99c5f3acde482757763cb23
Author: Gilles Sadowski <gillese...@gmail.com>
AuthorDate: Tue Jun 15 01:17:02 2021 +0200
Delete benchmark file that used the previous API.
---
.../examples/jmh/core/NormsPerformance.java | 198 ---------------------
1 file changed, 198 deletions(-)
diff --git
a/commons-numbers-examples/examples-jmh/src/main/java/org/apache/commons/numbers/examples/jmh/core/NormsPerformance.java
b/commons-numbers-examples/examples-jmh/src/main/java/org/apache/commons/numbers/examples/jmh/core/NormsPerformance.java
deleted file mode 100644
index d600c43..0000000
---
a/commons-numbers-examples/examples-jmh/src/main/java/org/apache/commons/numbers/examples/jmh/core/NormsPerformance.java
+++ /dev/null
@@ -1,198 +0,0 @@
-/*
- * 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.numbers.examples.jmh.core;
-
-import java.util.concurrent.TimeUnit;
-import java.util.function.ToDoubleFunction;
-
-import org.apache.commons.numbers.core.Norms;
-import org.apache.commons.rng.UniformRandomProvider;
-import org.apache.commons.rng.simple.RandomSource;
-import org.openjdk.jmh.annotations.Benchmark;
-import org.openjdk.jmh.annotations.BenchmarkMode;
-import org.openjdk.jmh.annotations.Fork;
-import org.openjdk.jmh.annotations.Measurement;
-import org.openjdk.jmh.annotations.Mode;
-import org.openjdk.jmh.annotations.OutputTimeUnit;
-import org.openjdk.jmh.annotations.Param;
-import org.openjdk.jmh.annotations.Scope;
-import org.openjdk.jmh.annotations.Setup;
-import org.openjdk.jmh.annotations.State;
-import org.openjdk.jmh.annotations.Warmup;
-import org.openjdk.jmh.infra.Blackhole;
-
-/**
- * Execute benchmarks for the methods in the {@link Norms} class.
- */
-@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", "-Xms512M", "-Xmx512M"})
-public class NormsPerformance {
-
- /** Class providing input vectors for benchmarks.
- */
- @State(Scope.Benchmark)
- public static class VectorArrayInput {
-
- /** Number of vector samples. */
- @Param("100000")
- private int samples;
-
- /** Minimum possible double exponent. */
- @Param("-550")
- private int minExp;
-
- /** Maximum possible double exponent. */
- @Param("+550")
- private int maxExp;
-
- /** Range of exponents within a single vector. */
- @Param("26")
- private int vectorExpRange;
-
- /** Array of input vectors. */
- private double[][] vectors;
-
- /** Get the input vectors.
- * @return input vectors
- */
- public double[][] getVectors() {
- return vectors;
- }
-
- /** Create the input vectors for the instance.
- */
- @Setup
- public void createVectors() {
- final UniformRandomProvider rng =
RandomSource.create(RandomSource.XO_RO_SHI_RO_1024_PP);
-
- vectors = new double[samples][];
- for (int i = 0; i < vectors.length; ++i) {
- // pick a general range for the vector element exponents and
then
- // create values within that range
- final int vMidExp = rng.nextInt(maxExp - minExp + 1) + minExp;
- final int vExpRadius = vectorExpRange / 2;
- final int vMinExp = vMidExp - vExpRadius;
- final int vMaxExp = vMidExp + vExpRadius;
-
- vectors[i] = DoubleUtils.randomArray(getLength(), vMinExp,
vMaxExp, rng);
- }
- }
-
- /** Get the length of the input vectors.
- * @return input vector length
- */
- protected int getLength() {
- return 3;
- }
- }
-
- /** Class providing 2D input vectors for benchmarks.
- */
- @State(Scope.Benchmark)
- public static class VectorArrayInput2D extends VectorArrayInput {
-
- /** {@inheritDoc} */
- @Override
- protected int getLength() {
- return 2;
- }
- }
-
- /** Evaluate a norm computation method with the given input.
- * @param fn function to evaluate
- * @param input computation input
- * @param bh blackhole
- */
- private static void eval(final ToDoubleFunction<double[]> fn, final
VectorArrayInput input,
- final Blackhole bh) {
- final double[][] vectors = input.getVectors();
- for (int i = 0; i < vectors.length; ++i) {
- bh.consume(fn.applyAsDouble(vectors[i]));
- }
- }
-
- /** Compute the Euclidean norm directly with no checks for overflow or
underflow.
- * @param v input vector
- * @return Euclidean norm
- */
- private static double directEuclideanNorm(final double[] v) {
- double n = 0;
- for (int i = 0; i < v.length; i++) {
- n += v[i] * v[i];
- }
- return Math.sqrt(n);
- }
-
- /** Compute a baseline performance metric with a method that does nothing.
- * @param input benchmark input
- * @param bh blackhole
- */
- @Benchmark
- public void baseline(final VectorArrayInput input, final Blackhole bh) {
- eval(v -> 0d, input, bh);
- }
-
- /** Compute a baseline performance metric using direct computation of the
- * Euclidean norm.
- * @param input benchmark input
- * @param bh blackhole
- */
- @Benchmark
- public void directEuclideanArray(final VectorArrayInput input, final
Blackhole bh) {
- eval(NormsPerformance::directEuclideanNorm, input, bh);
- }
-
- /** Compute a baseline performance metric using {@link Math#hypot(double,
double)}.
- * @param input benchmark input
- * @param bh blackhole
- */
- @Benchmark
- public void hypot(final VectorArrayInput2D input, final Blackhole bh) {
- eval(v -> Math.hypot(v[0], v[1]), input, bh);
- }
-
- /** Compute the performance of the {@link Norms#euclidean(double, double)}
method.
- * @param input benchmark input
- * @param bh blackhole
- */
- @Benchmark
- public void euclidean2d(final VectorArrayInput2D input, final Blackhole
bh) {
- eval(v -> Norms.euclidean(v[0], v[1]), input, bh);
- }
-
- /** Compute the performance of the {@link Norms#euclidean(double, double,
double)} method.
- * @param input benchmark input
- * @param bh blackhole
- */
- @Benchmark
- public void euclidean3d(final VectorArrayInput input, final Blackhole bh) {
- eval(v -> Norms.euclidean(v[0], v[1], v[2]), input, bh);
- }
-
- /** Compute the performance of the {@link Norms#euclidean(double[])}
method.
- * @param input benchmark input
- * @param bh blackhole
- */
- @Benchmark
- public void euclideanArray(final VectorArrayInput input, final Blackhole
bh) {
- eval(Norms::euclidean, input, bh);
- }
-}
