omi*_*iel 14 java arrays microbenchmark jmh
我正在玩JMH(http://openjdk.java.net/projects/code-tools/jmh/),我偶然发现了一个奇怪的结果.
我正在对数组的浅层副本进行基准测试,我可以观察到预期的结果(循环遍历数组是一个坏主意#clone(),System#arraycopy()并且在Arrays#copyOf()性能方面没有显着差异).
除了System#arraycopy()是一个季度的慢时,数组的长度是硬编码的......等等,什么？这怎么会慢？
有没有人知道可能是什么原因？
结果(吞吐量):
# JMH 1.11 (released 17 days ago)
# VM version: JDK 1.8.0_05, VM 25.5-b02
# VM invoker: /Library/Java/JavaVirtualMachines/jdk1.8.0_05.jdk/Contents/Home/jre/bin/java
# VM options: -Dfile.encoding=UTF-8 -Duser.country=FR -Duser.language=fr -Duser.variant
# Warmup: 20 iterations, 1 s each
# Measurement: 20 iterations, 1 s each
# Timeout: 10 min per iteration
# Threads: 1 thread, will synchronize iterations
# Benchmark mode: Throughput, ops/time
Benchmark Mode Cnt Score Error Units
ArrayCopyBenchmark.ArraysCopyOf thrpt 20 67100500,319 ± 455252,537 ops/s
ArrayCopyBenchmark.ArraysCopyOf_Class thrpt 20 65246374,290 ± 976481,330 ops/s
ArrayCopyBenchmark.ArraysCopyOf_Class_ConstantSize thrpt 20 65068143,162 ± 1597390,531 ops/s
ArrayCopyBenchmark.ArraysCopyOf_ConstantSize thrpt 20 64463603,462 ± 953946,811 ops/s
ArrayCopyBenchmark.Clone thrpt 20 64837239,393 ± 834353,404 ops/s
ArrayCopyBenchmark.Loop thrpt 20 21070422,097 ± 112595,764 ops/s
ArrayCopyBenchmark.Loop_ConstantSize thrpt 20 24458867,274 ± 181486,291 ops/s
ArrayCopyBenchmark.SystemArrayCopy thrpt 20 66688368,490 ± 582416,954 ops/s
ArrayCopyBenchmark.SystemArrayCopy_ConstantSize thrpt 20 48992312,357 ± 298807,039 ops/s
而基准类:
import java.util.Arrays;
import java.util.concurrent.TimeUnit;
import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.BenchmarkMode;
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;
@State(Scope.Benchmark)
@BenchmarkMode(Mode.Throughput)
@OutputTimeUnit(TimeUnit.SECONDS)
public class ArrayCopyBenchmark {
private static final int LENGTH = 32;
private Object[] array;
@Setup
public void before() {
array = new Object[LENGTH];
for (int i = 0; i < LENGTH; i++) {
array[i] = new Object();
}
}
@Benchmark
public Object[] Clone() {
Object[] src = this.array;
return src.clone();
}
@Benchmark
public Object[] ArraysCopyOf() {
Object[] src = this.array;
return Arrays.copyOf(src, src.length);
}
@Benchmark
public Object[] ArraysCopyOf_ConstantSize() {
Object[] src = this.array;
return Arrays.copyOf(src, LENGTH);
}
@Benchmark
public Object[] ArraysCopyOf_Class() {
Object[] src = this.array;
return Arrays.copyOf(src, src.length, Object[].class);
}
@Benchmark
public Object[] ArraysCopyOf_Class_ConstantSize() {
Object[] src = this.array;
return Arrays.copyOf(src, LENGTH, Object[].class);
}
@Benchmark
public Object[] SystemArrayCopy() {
Object[] src = this.array;
int length = src.length;
Object[] array = new Object[length];
System.arraycopy(src, 0, array, 0, length);
return array;
}
@Benchmark
public Object[] SystemArrayCopy_ConstantSize() {
Object[] src = this.array;
Object[] array = new Object[LENGTH];
System.arraycopy(src, 0, array, 0, LENGTH);
return array;
}
@Benchmark
public Object[] Loop() {
Object[] src = this.array;
int length = src.length;
Object[] array = new Object[length];
for (int i = 0; i < length; i++) {
array[i] = src[i];
}
return array;
}
@Benchmark
public Object[] Loop_ConstantSize() {
Object[] src = this.array;
Object[] array = new Object[LENGTH];
for (int i = 0; i < LENGTH; i++) {
array[i] = src[i];
}
return array;
}
}
Ale*_*lev 10
像往常一样,通过研究生成的代码可以快速回答这些问题.JMH为您提供-prof perfasmLinux和-prof xperfasmWindows.如果你在JDK 8u40上运行基准测试,那么你会看到(注意我曾经-bm avgt -tu ns让得分更容易理解):
Benchmark Mode Cnt Score Error Units
ACB.SystemArrayCopy avgt 25 13.294 ± 0.052 ns/op
ACB.SystemArrayCopy_ConstantSize avgt 25 16.413 ± 0.080 ns/op
为什么这些基准测试表现不同？让我们先-prof perfnorm解剖(我放弃了无关紧要的行):
Benchmark Mode Cnt Score Error Units
ACB.SAC avgt 25 13.466 ± 0.070 ns/op
ACB.SAC:·CPI avgt 5 0.602 ± 0.025 #/op
ACB.SAC:·L1-dcache-load-misses avgt 5 2.346 ± 0.239 #/op
ACB.SAC:·L1-dcache-loads avgt 5 24.756 ± 1.438 #/op
ACB.SAC:·L1-dcache-store-misses avgt 5 2.404 ± 0.129 #/op
ACB.SAC:·L1-dcache-stores avgt 5 14.929 ± 0.230 #/op
ACB.SAC:·LLC-loads avgt 5 2.151 ± 0.217 #/op
ACB.SAC:·branches avgt 5 17.795 ± 1.003 #/op
ACB.SAC:·cycles avgt 5 56.677 ± 3.187 #/op
ACB.SAC:·instructions avgt 5 94.145 ± 6.442 #/op
ACB.SAC_ConstantSize avgt 25 16.447 ± 0.084 ns/op
ACB.SAC_ConstantSize:·CPI avgt 5 0.637 ± 0.016 #/op
ACB.SAC_ConstantSize:·L1-dcache-load-misses avgt 5 2.357 ± 0.206 #/op
ACB.SAC_ConstantSize:·L1-dcache-loads avgt 5 25.611 ± 1.482 #/op
ACB.SAC_ConstantSize:·L1-dcache-store-misses avgt 5 2.368 ± 0.123 #/op
ACB.SAC_ConstantSize:·L1-dcache-stores avgt 5 25.593 ± 1.610 #/op
ACB.SAC_ConstantSize:·LLC-loads avgt 5 1.050 ± 0.038 #/op
ACB.SAC_ConstantSize:·branches avgt 5 17.853 ± 0.697 #/op
ACB.SAC_ConstantSize:·cycles avgt 5 66.680 ± 2.049 #/op
ACB.SAC_ConstantSize:·instructions avgt 5 104.759 ± 4.831 #/op
因此,ConstantSize不知何故更多的L1-dcache存储,但少一个LLC负载.嗯,这就是我们正在寻找的,在不变的情况下更多的商店.-prof perfasm方便地突出显示装配中的热部件:
default:
4.32% 6.36% 0x00007f7714bda2dc: movq $0x1,(%rax) ; alloc
0.09% 0.04% 0x00007f7714bda2e3: prefetchnta 0x100(%r9)
2.95% 1.48% 0x00007f7714bda2eb: movl $0xf80022a9,0x8(%rax)
0.38% 0.18% 0x00007f7714bda2f2: mov %r11d,0xc(%rax)
1.56% 3.02% 0x00007f7714bda2f6: prefetchnta 0x140(%r9)
4.73% 2.71% 0x00007f7714bda2fe: prefetchnta 0x180(%r9)
ConstantSize:
0.58% 1.22% 0x00007facf921132b: movq $0x1,(%r14) ; alloc
0.84% 0.72% 0x00007facf9211332: prefetchnta 0xc0(%r10)
0.11% 0.13% 0x00007facf921133a: movl $0xf80022a9,0x8(%r14)
0.21% 0.68% 0x00007facf9211342: prefetchnta 0x100(%r10)
0.50% 0.87% 0x00007facf921134a: movl $0x20,0xc(%r14)
0.53% 0.82% 0x00007facf9211352: mov $0x10,%ecx
0.04% 0.14% 0x00007facf9211357: xor %rax,%rax
0.34% 0.76% 0x00007facf921135a: shl $0x3,%rcx
0.50% 1.17% 0x00007facf921135e: rex.W rep stos %al,%es:(%rdi) ; zeroing
29.49% 52.09% 0x00007facf9211361: prefetchnta 0x140(%r10)
1.03% 0.53% 0x00007facf9211369: prefetchnta 0x180(%r10)
所以有麻烦的rex.W rep stos %al,%es:(%rdi)消耗很长时间.这会将新分配的数组归零.在ConstantSize测试中,JVM无法关联您覆盖整个目标数组,因此在深入实际数组副本之前必须将其预先归零.
如果您查看JDK 9b82上生成的代码(最新版本),那么您将看到它将非零复制中的两种模式折叠起来,如您所见-prof perfasm,并且还可以通过以下方式确认-prof perfnorm:
Benchmark Mode Cnt Score Error Units
ACB.SAC avgt 50 14.156 ± 0.492 ns/op
ACB.SAC:·CPI avgt 5 0.612 ± 0.144 #/op
ACB.SAC:·L1-dcache-load-misses avgt 5 2.363 ± 0.341 #/op
ACB.SAC:·L1-dcache-loads avgt 5 28.350 ± 2.181 #/op
ACB.SAC:·L1-dcache-store-misses avgt 5 2.287 ± 0.607 #/op
ACB.SAC:·L1-dcache-stores avgt 5 16.922 ± 3.402 #/op
ACB.SAC:·branches avgt 5 21.242 ± 5.914 #/op
ACB.SAC:·cycles avgt 5 67.168 ± 20.950 #/op
ACB.SAC:·instructions avgt 5 109.931 ± 35.905 #/op
ACB.SAC_ConstantSize avgt 50 13.763 ± 0.067 ns/op
ACB.SAC_ConstantSize:·CPI avgt 5 0.625 ± 0.024 #/op
ACB.SAC_ConstantSize:·L1-dcache-load-misses avgt 5 2.376 ± 0.214 #/op
ACB.SAC_ConstantSize:·L1-dcache-loads avgt 5 28.285 ± 2.127 #/op
ACB.SAC_ConstantSize:·L1-dcache-store-misses avgt 5 2.335 ± 0.223 #/op
ACB.SAC_ConstantSize:·L1-dcache-stores avgt 5 16.926 ± 1.467 #/op
ACB.SAC_ConstantSize:·branches avgt 5 19.469 ± 0.869 #/op
ACB.SAC_ConstantSize:·cycles avgt 5 62.395 ± 3.898 #/op
ACB.SAC_ConstantSize:·instructions avgt 5 99.891 ± 5.435 #/op
当然,所有这些用于阵列复制的纳米标记都容易受到矢量化复制存根中奇怪的对齐引起的性能差异的影响,但这是另一个(恐怖)故事,我没有勇气说出来.