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GameOfLifeBenchmark.java
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GameOfLifeBenchmark.java
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/*
* JVM Performance Benchmarks
*
* Copyright (C) 2019 - 2024 Ionut Balosin
*
* 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 com.ionutbalosin.jvm.performance.benchmarks.miscellaneous.gameoflife;
import com.ionutbalosin.jvm.performance.benchmarks.miscellaneous.gameoflife.functional.FunctionalGameOfLife;
import com.ionutbalosin.jvm.performance.benchmarks.miscellaneous.gameoflife.iterative.IterativeGameOfLife;
import java.util.Random;
import java.util.concurrent.TimeUnit;
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.Scope;
import org.openjdk.jmh.annotations.Setup;
import org.openjdk.jmh.annotations.State;
import org.openjdk.jmh.annotations.Warmup;
/*
* Conway's Game of Life, often referred to simply as the Game of Life, is a cellular automaton devised by mathematician John Conway in 1970.
* It is a mathematical "zero-player" game, meaning that its evolution is determined by its initial state, with no further input required.
*
* The Game of Life is played on a 2D grid of cells, where each cell can be in one of two states: alive or dead (0 or 1).
* The game progresses through generations, with the state of each cell in a generation being determined by the state of its neighboring cells
* in the previous generation according to a set of rules. These rules are based on the concept of birth, death, and survival:
* - Birth: A dead cell with exactly three live neighbors becomes a live.
* - Death: A live cell with fewer than two live neighbors (underpopulation) or more than three live neighbors (overpopulation) becomes a dead cell.
* - Survival: A live cell with two or three live neighbors remains alive.
*
* Despite its simple rules, the Game of Life can produce complex and intricate patterns, including gliders (moving structures),
* oscillators (repeating patterns), and even structures that can act as logic gates and memory cells.
*
* The benchmark involves several alternative strategies:
* - Game of Life with Functional Programming
* - Game of Life with Imperative Style
*/
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.MILLISECONDS)
@Warmup(iterations = 5, time = 10, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 5, time = 10, timeUnit = TimeUnit.SECONDS)
@Fork(value = 5)
@State(Scope.Benchmark)
public class GameOfLifeBenchmark {
// $ java -jar */*/benchmarks.jar ".*GameOfLifeBenchmark.*"
private final int ROWS = 24;
private final int COLS = 24;
private final int GENERATIONS = 2048;
private final Random random = new Random(16384);
private byte[][] grid;
@Setup()
public void setup() {
grid = new byte[ROWS][COLS];
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
grid[i][j] = (byte) (random.nextBoolean() == true ? 1 : 0);
}
}
// make sure the results are equivalent before any further benchmarking
sanityCheck(
FunctionalGameOfLife.evolve(grid, GENERATIONS),
IterativeGameOfLife.evolve(grid, GENERATIONS));
}
@Benchmark
public byte[][] functional() {
return FunctionalGameOfLife.evolve(grid, GENERATIONS);
}
@Benchmark
public byte[][] iterative() {
return IterativeGameOfLife.evolve(grid, GENERATIONS);
}
private void sanityCheck(byte[][] grid1, byte[][] grid2) {
if (grid1.length != ROWS
|| grid2.length != ROWS
|| grid1[0].length != COLS
|| grid2[0].length != COLS) {
throw new AssertionError("Invalid array dimensions for population grids.");
}
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
if (grid1[i][j] != grid2[i][j]) {
throw new AssertionError("Generated populations contain different values.");
}
}
}
}
}