一些运行/ JIT的故障后Java循环变慢了?

时间:2014-07-22 08:55:20

标签: java performance benchmarking jit

所以我想对一些基本的java功能进行基准测试,以便为这个问题添加一些信息:What is the gain from declaring a method as static

我知道写作基准有时并不容易,但这里发生的事情我无法解释。

请注意,我并没有考虑如何解决这个问题,而是为什么会发生这种情况*

测试类:

public class TestPerformanceOfStaticVsDynamicCalls {

    private static final long RUNS = 1_000_000_000L;

    public static void main( String [] args ){

        new TestPerformanceOfStaticVsDynamicCalls().run();
    }

    private void run(){

        long r=0;
        long start, end;

        for( int loop = 0; loop<10; loop++ ){

            // Benchmark

            start = System.currentTimeMillis();
            for( long i = 0; i < RUNS; i++ ) {
                r += addStatic( 1, i );
            }
            end = System.currentTimeMillis();
            System.out.println( "Static: " + ( end - start ) + " ms" );

            start = System.currentTimeMillis();
            for( long i = 0; i < RUNS; i++ ) {
                r += addDynamic( 1, i );
            }
            end = System.currentTimeMillis();
            System.out.println( "Dynamic: " + ( end - start ) + " ms" );

            // Do something with r to keep compiler happy
            System.out.println( r );

        }

    }


    private long addDynamic( long a, long b ){

        return a+b;
    }

    private static long addStatic( long a, long b ){

        return a+b;
    }

}

我期待第一个循环是热身,以下循环更快。

在Eclipse中运行它会产生奇怪的结果:

Static: 621 ms
Dynamic: 631 ms
1000000001000000000
Static: 2257 ms
Dynamic: 2501 ms
2000000002000000000
Static: 2258 ms
Dynamic: 2469 ms
3000000003000000000
Static: 2231 ms
Dynamic: 2464 ms
4000000004000000000

那么wtf?它变慢了。要进行交叉检查,我使用java / c 7运行相同的代码:

Static: 620 ms
Dynamic: 627 ms
1000000001000000000
Static: 897 ms
Dynamic: 617 ms
2000000002000000000
Static: 901 ms
Dynamic: 615 ms
3000000003000000000
Static: 888 ms
Dynamic: 616 ms
4000000004000000000

所以这里只有静态调用对于以下循环变慢了。更奇怪的是,如果我重新排列代码只在最终循环后打印r我在Eclipse中得到它:

Static: 620 ms
Dynamic: 635 ms
Static: 2285 ms
Dynamic: 893 ms
Static: 2258 ms
Dynamic: 900 ms
Static: 2280 ms
Dynamic: 905 ms
4000000004000000000

这与java / c 7:

Static: 620 ms
Dynamic: 623 ms
Static: 890 ms
Dynamic: 614 ms
Static: 890 ms
Dynamic: 616 ms
Static: 886 ms
Dynamic: 614 ms
4000000004000000000

在改变eclipse中动态/静态基准测试的顺序时:

Dynamic: 618 ms
Static: 626 ms
1000000001000000000
Dynamic: 632 ms
Static: 2524 ms
2000000002000000000
Dynamic: 617 ms
Static: 2528 ms
3000000003000000000
Dynamic: 622 ms
Static: 2506 ms
4000000004000000000

和java / c 7:

Dynamic: 625 ms
Static: 646 ms
1000000001000000000
Dynamic: 2470 ms
Static: 633 ms
2000000002000000000
Dynamic: 2459 ms
Static: 635 ms
3000000003000000000
Dynamic: 2464 ms
Static: 645 ms
4000000004000000000

那么这里发生了什么?

编辑:一些系统信息:

Java version "1.7.0_55"
OpenJDK Runtime Environment (IcedTea 2.4.7) (7u55-2.4.7-1ubuntu1)
OpenJDK 64-Bit Server VM (build 24.51-b03, mixed mode)

Intel(R) Core(TM) i7-2720QM CPU @ 2.20GHz

EDIT2:

使用Java8:

Static: 620 ms
Dynamic: 624 ms
1000000001000000000
Static: 890 ms
Dynamic: 618 ms
2000000002000000000
Static: 891 ms
Dynamic: 616 ms
3000000003000000000
Static: 892 ms
Dynamic: 617 ms
4000000004000000000

其他代码排序在这里产生类似的奇怪(但是更好)的结果。

3 个答案:

答案 0 :(得分:10)

序言:手动编写微基准测试几乎总是注定要失败 有frameworks已经解决了常见的基准测试问题。

  1. JIT编译单元是一种方法。将几个基准合并到一个方法中会导致不可预测的结果。

  2. JIT严重依赖于执行配置文件,即运行时统计信息。如果方法长时间运行第一个场景,JIT将优化生成的代码。当该方法突然切换到另一种情况时,不要指望它以相同的速度运行。

  3. JIT可能会跳过优化未执行的代码。它将为此代码留下一个不常见的陷阱。如果陷阱被击中,JVM将取消优化编译的方法,切换到解释器,然后用新知识重新编译代码。例如。当你的方法run第一次在第一个热循环中编译时,JIT还不知道System.out.println。一旦执行到达println,早期编译的代码很可能会被去优化。

  4. 方法越大 - 为JIT编译器优化它就越困难。例如。可能看起来没有足够的备用寄存器来保存所有局部变量。那就是你的情况。

  5. 总而言之,您的基准测试似乎通过以下方案:

    1. 第一个热循环(addStatic)触发run方法的编译。除addStatic方法外,执行配置文件不知道任何内容。
    2. System.out.println触发去优化,之后第二个热循环(addDynamic)导致重新编译run方法。
    3. 现在执行配置文件仅包含有关addDynamic的信息,因此JIT优化了第二个循环,第一个循环似乎有额外的寄存器溢出:
    4. 优化循环:

      0x0000000002d01054: add    %rbx,%r14
      0x0000000002d01057: add    $0x1,%rbx          ;*ladd
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::addDynamic@2
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@105
      
      0x0000000002d0105b: add    $0x1,%r14          ; OopMap{rbp=Oop off=127}
                                                    ;*goto
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@116
      
      0x0000000002d0105f: test   %eax,-0x1c91065(%rip)        # 0x0000000001070000
                                                    ;*lload
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@92
                                                    ;   {poll}
      0x0000000002d01065: cmp    $0x3b9aca00,%rbx
      0x0000000002d0106c: jl     0x0000000002d01054
      

      使用额外的寄存器溢出循环:

      0x0000000002d011d0: mov    0x28(%rsp),%r11  <---- the problem is here
      0x0000000002d011d5: add    %r10,%r11
      0x0000000002d011d8: add    $0x1,%r10
      0x0000000002d011dc: add    $0x1,%r11
      0x0000000002d011e0: mov    %r11,0x28(%rsp)    ;*ladd
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::addStatic@2
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@33
      
      0x0000000002d011e5: mov    0x28(%rsp),%r11  <---- the problem is here
      0x0000000002d011ea: add    $0x1,%r11          ; OopMap{[32]=Oop off=526}
                                                    ;*goto
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@44
      
      0x0000000002d011ee: test   %eax,-0x1c911f4(%rip)        # 0x0000000001070000
                                                    ;*goto
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@44
                                                    ;   {poll}
      0x0000000002d011f4: cmp    $0x3b9aca00,%r10
      0x0000000002d011fb: jl     0x0000000002d011d0  ;*ifge
                                                    ; - TestPerformanceOfStaticVsDynamicCalls::run@25
      

      P.S。以下JVM选项对于分析JIT编译非常有用:

      -XX:+PrintCompilation -XX:+UnlockDiagnosticVMOptions -XX:+PrintInlining -XX:+PrintAssembly -XX:CompileOnly=TestPerformanceOfStaticVsDynamicCalls
      

答案 1 :(得分:1)

看起来Java正在向变量r添加值。 我做了一些更改,添加了方法run2()

public class TestPerformanceOfStaticVsDynamicCalls {
    private static final long RUNS = 1_000_000_000L;
    public static void main(String[] args) {
        System.out.println("Test run 1 =================================");
        new TestPerformanceOfStaticVsDynamicCalls().run();
        System.out.println("Test run 2 =================================");
        new TestPerformanceOfStaticVsDynamicCalls().run2();
    }
    private void run2() {
        long r = 0;
        long start, end;
        for (int loop = 0; loop < 10; loop++) {
            // Benchmark
            long stat = 0;
            start = System.currentTimeMillis();
            for (long i = 0; i < RUNS; i++) {
                stat += addStatic(1, i);
            }
            end = System.currentTimeMillis();
            System.out.println("Static: " + (end - start) + " ms");
            long dyna = 0;
            start = System.currentTimeMillis();
            for (long i = 0; i < RUNS; i++) {
                dyna += addDynamic(1, i);
            }
            end = System.currentTimeMillis();
            System.out.println("Dynamic: " + (end - start) + " ms");
            // If you really want to have values in "r" then...
            r += stat + dyna;
            // Do something with r to keep compiler happy
            System.out.println(r);
        }
    }
    private void run() {
        long r = 0;
        long start, end;
        for (int loop = 0; loop < 10; loop++) {
            // Benchmark
            start = System.currentTimeMillis();
            for (long i = 0; i < RUNS; i++) {
                r += addStatic(1, i);
            }
            end = System.currentTimeMillis();
            System.out.println("Static: " + (end - start) + " ms");
            start = System.currentTimeMillis();
            for (long i = 0; i < RUNS; i++) {
                r += addDynamic(1, i);
            }
            end = System.currentTimeMillis();
            System.out.println("Dynamic: " + (end - start) + " ms");
            // If you really want to have values in "r" then...
            // Do something with r to keep compiler happy
            System.out.println(r);
        }
    }
    private long addDynamic(long a, long b) {
        return a + b;
    }
    private static long addStatic(long a, long b) {
        return a + b;
    }
}

结果是:

Test run 1 =================================
Static: 582 ms
Dynamic: 579 ms
1000000001000000000
Static: 2065 ms
Dynamic: 2352 ms
2000000002000000000
Static: 2084 ms
Dynamic: 2345 ms
3000000003000000000
Static: 2095 ms
Dynamic: 2347 ms
4000000004000000000
Static: 2102 ms
Dynamic: 2338 ms
5000000005000000000
Static: 2073 ms
Dynamic: 2345 ms
6000000006000000000
Static: 2074 ms
Dynamic: 2341 ms
7000000007000000000
Static: 2102 ms
Dynamic: 2355 ms
8000000008000000000
Static: 2062 ms
Dynamic: 2354 ms
9000000009000000000
Static: 2057 ms
Dynamic: 2350 ms
-8446744063709551616
Test run 2 =================================
Static: 584 ms
Dynamic: 582 ms
1000000001000000000
Static: 587 ms
Dynamic: 577 ms
2000000002000000000
Static: 577 ms
Dynamic: 579 ms
3000000003000000000
Static: 577 ms
Dynamic: 577 ms
4000000004000000000
Static: 578 ms
Dynamic: 579 ms
5000000005000000000
Static: 578 ms
Dynamic: 580 ms
6000000006000000000
Static: 577 ms
Dynamic: 579 ms
7000000007000000000
Static: 578 ms
Dynamic: 577 ms
8000000008000000000
Static: 580 ms
Dynamic: 578 ms
9000000009000000000
Static: 576 ms
Dynamic: 579 ms
-8446744063709551616

至于为什么直接添加到r,我没有任何线索。也许有人可以提供更多见解,了解为什么在r内访问loop block会让事情变得更慢。

答案 2 :(得分:0)

只需一个注释。如果我对longr使用i,我只能观察到这种奇怪的行为。如果我将它们转换为int,那么我会得到这些时间:

Static: 352 ms
Dynamic: 353 ms
Static: 348 ms
Dynamic: 349 ms
Static: 349 ms
Dynamic: 348 ms
Static: 349 ms
Dynamic: 344 ms

所以一个可能的结论是在这些情况下避免long。至少在Linux / Amd64 Java7中,性能很重要。