以下哪一种技术是整数除2的最佳选择,为什么?

技巧1:

x = x >> 1;

技巧2:

x = x / 2;

这里x是整数。


当前回答

只是加了一个注释

在一些基于vm的语言中,x *= 0.5通常会更快——尤其是actionscript,因为变量不需要被检查是否除以0。

其他回答

X/Y是正确的…和" >> "移位运算符..如果我们想要二除一个整数,我们可以使用(/)被除数运算符。移位运算符用于移位位。

x = x / 2; x / = 2;我们可以这样用…

查看编译器的输出来帮助您做出决定。我在x86-64上使用 gcc (gcc) 4.2.1 20070719 [FreeBSD]

也可以在godbolt上看到编译器的在线输出。

What you see is the compiler does use a sarl (arithmetic right-shift) instruction in both cases, so it does recognize the similarity between the two expressions. If you use the divide, the compiler also needs to adjust for negative numbers. To do that it shifts the sign bit down to the lowest order bit, and adds that to the result. This fixes the off-by-one issue when shifting negative numbers, compared to what a divide would do. Since the divide case does 2 shifts, while the explicit shift case only does one, we can now explain some of the performance differences measured by other answers here.

C代码与汇编输出:

对于除法,你的输入是

int div2signed(int a) {
  return a / 2;
}

这个编译成

    movl    %edi, %eax
    shrl    $31, %eax            # (unsigned)x >> 31
    addl    %edi, %eax           # tmp = x + (x<0)
    sarl    %eax                 # (x + 0 or 1) >> 1  arithmetic right shift
    ret

shift也是一样

int shr2signed(int a) {
  return a >> 1;
}

输出:

    sarl    %edi
    movl    %edi, %eax
    ret

其他isa即使不能做得更好,也能同样有效地做到这一点。例如GCC For AArch64使用:

        add     w0, w0, w0, lsr 31      // x += (unsigned)x>>31
        asr     w0, w0, 1               // x >>= 1
        ret

我同意其他答案,你应该支持x / 2,因为它的意图更清楚,编译器应该为你优化它。

然而,选择x / 2而不是x >> 1的另一个原因是,如果x是一个有符号int并且是负的,那么>>的行为是依赖于实现的。

ISO C99标准第6.5.7节第5项:

E1 >> E2的结果是E1位右移E2位位置。如果E1 无符号类型,或者E1有符号类型且值为非负值, 结果值为E1 /商的积分部分 2 e2。如果E1具有符号类型和负值,则结果值为 是由实现定义的。

x / 2更清晰,x >> 1快不了多少(根据一个微基准测试,对于Java JVM快30%左右)。正如其他人所注意到的,对于负数,舍入略有不同,所以当您想处理负数时必须考虑这一点。一些编译器可能会自动将x / 2转换为x >> 1,如果他们知道这个数字不可能是负数(即使我无法验证这一点)。

即使x / 2可能不使用(慢)除法CPU指令,因为一些捷径是可能的,但它仍然比x >> 1慢。

(This is a C / C++ question, other programming languages have more operators. For Java there is also the unsigned right shift, x >>> 1, which is again different. It allows to correctly calculate the mean (average) value of two values, so that (a + b) >>> 1 will return the mean value even for very large values of a and b. This is required for example for binary search if the array indices can get very large. There was a bug in many versions of binary search, because they used (a + b) / 2 to calculate the average. This doesn't work correctly. The correct solution is to use (a + b) >>> 1 instead.)

在性能方面。CPU的移位运算比除法运算快得多。 所以除以2或乘以2等都可以从移位运算中获益。

至于外观和感觉。作为工程师,我们什么时候变得如此依赖化妆品,连漂亮的女士都不用!:)