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package org.openjdk.jmh.samples;
import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.infra.Blackhole;
import org.openjdk.jmh.runner.Runner;
import org.openjdk.jmh.runner.RunnerException;
import org.openjdk.jmh.runner.options.Options;
import org.openjdk.jmh.runner.options.OptionsBuilder;
import java.util.Random;
import java.util.concurrent.TimeUnit;
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.NANOSECONDS)
@Warmup(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Fork(5)
@State(Scope.Benchmark)
public class JMHSample_37_CacheAccess {
/*
* This sample serves as a warning against subtle differences in cache access patterns.
*
* Many performance differences may be explained by the way tests are accessing memory.
* In the example below, we walk the matrix either row-first, or col-first:
*/
private final static int COUNT = 4096;
private final static int MATRIX_SIZE = COUNT * COUNT;
private int[][] matrix;
@Setup
public void setup() {
matrix = new int[COUNT][COUNT];
Random random = new Random(1234);
for (int i = 0; i < COUNT; i++) {
for (int j = 0; j < COUNT; j++) {
matrix[i][j] = random.nextInt();
}
}
}
@Benchmark
@OperationsPerInvocation(MATRIX_SIZE)
public void colFirst(Blackhole bh) {
for (int c = 0; c < COUNT; c++) {
for (int r = 0; r < COUNT; r++) {
bh.consume(matrix[r][c]);
}
}
}
@Benchmark
@OperationsPerInvocation(MATRIX_SIZE)
public void rowFirst(Blackhole bh) {
for (int r = 0; r < COUNT; r++) {
for (int c = 0; c < COUNT; c++) {
bh.consume(matrix[r][c]);
}
}
}
/*
Notably, colFirst accesses are much slower, and that's not a surprise: Java's multidimensional
arrays are actually rigged, being one-dimensional arrays of one-dimensional arrays. Therefore,
pulling n-th element from each of the inner array induces more cache misses, when matrix is large.
-prof perfnorm conveniently highlights that, with >2 cache misses per one benchmark op:
Benchmark Mode Cnt Score Error Units
JMHSample_37_MatrixCopy.colFirst avgt 25 5.306 ± 0.020 ns/op
JMHSample_37_MatrixCopy.colFirst:·CPI avgt 5 0.621 ± 0.011 #/op
JMHSample_37_MatrixCopy.colFirst:·L1-dcache-load-misses avgt 5 2.177 ± 0.044 #/op <-- OOPS
JMHSample_37_MatrixCopy.colFirst:·L1-dcache-loads avgt 5 14.804 ± 0.261 #/op
JMHSample_37_MatrixCopy.colFirst:·LLC-loads avgt 5 2.165 ± 0.091 #/op
JMHSample_37_MatrixCopy.colFirst:·cycles avgt 5 22.272 ± 0.372 #/op
JMHSample_37_MatrixCopy.colFirst:·instructions avgt 5 35.888 ± 1.215 #/op
JMHSample_37_MatrixCopy.rowFirst avgt 25 2.662 ± 0.003 ns/op
JMHSample_37_MatrixCopy.rowFirst:·CPI avgt 5 0.312 ± 0.003 #/op
JMHSample_37_MatrixCopy.rowFirst:·L1-dcache-load-misses avgt 5 0.066 ± 0.001 #/op
JMHSample_37_MatrixCopy.rowFirst:·L1-dcache-loads avgt 5 14.570 ± 0.400 #/op
JMHSample_37_MatrixCopy.rowFirst:·LLC-loads avgt 5 0.002 ± 0.001 #/op
JMHSample_37_MatrixCopy.rowFirst:·cycles avgt 5 11.046 ± 0.343 #/op
JMHSample_37_MatrixCopy.rowFirst:·instructions avgt 5 35.416 ± 1.248 #/op
So, when comparing two different benchmarks, you have to follow up if the difference is caused
by the memory locality issues.
*/
/*
* ============================== HOW TO RUN THIS TEST: ====================================
*
* You can run this test:
*
* a) Via the command line:
* $ mvn clean install
* $ java -jar target/benchmarks.jar JMHSample_37
*
* b) Via the Java API:
* (see the JMH homepage for possible caveats when running from IDE:
* http://openjdk.java.net/projects/code-tools/jmh/)
*/
public static void main(String[] args) throws RunnerException {
Options opt = new OptionsBuilder()
.include(".*" + JMHSample_37_CacheAccess.class.getSimpleName() + ".*")
.build();
new Runner(opt).run();
}
}
