Boost中还实现了某种类型的舍入:

#include <iostream>

#include <boost/numeric/conversion/converter.hpp>

template<typename T, typename S> T round2(const S& x) {
  typedef boost::numeric::conversion_traits<T, S> Traits;
  typedef boost::numeric::def_overflow_handler OverflowHandler;
  typedef boost::numeric::RoundEven<typename Traits::source_type> Rounder;
  typedef boost::numeric::converter<T, S, Traits, OverflowHandler, Rounder> Converter;
  return Converter::convert(x);
}

int main() {
  std::cout << round2<int, double>(0.1) << ' ' << round2<int, double>(-0.1) << ' ' << round2<int, double>(-0.9) << std::endl;
}

注意，这仅在执行到整数的转换时有效。

正如在评论和其他回答中指出的那样，ISO c++标准库直到ISO c++ 11才添加round()，当时该函数是通过引用ISO C99标准数学库而引入的。

For positive operands in [½, ub] round(x) == floor (x + 0.5), where ub is 223 for float when mapped to IEEE-754 (2008) binary32, and 252 for double when it is mapped to IEEE-754 (2008) binary64. The numbers 23 and 52 correspond to the number of stored mantissa bits in these two floating-point formats. For positive operands in [+0, ½) round(x) == 0, and for positive operands in (ub, +∞] round(x) == x. As the function is symmetric about the x-axis, negative arguments x can be handled according to round(-x) == -round(x).

这导致了下面的压缩代码。它在各种平台上编译成合理数量的机器指令。我观察到gpu上最紧凑的代码，其中my_roundf()需要大约12条指令。根据处理器架构和工具链的不同，这种基于浮点的方法可能比在不同答案中引用的newlib基于整数的实现更快或更慢。

我使用Intel编译器版本13对my_roundf()与newlib roundf()实现进行了详尽的测试，同时使用/fp:strict和/fp:fast。我还检查了newlib版本是否与Intel编译器mathimf库中的roundf()匹配。对于双精度round()不可能进行详尽的测试，但是代码在结构上与单精度实现相同。

#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <string.h>
#include <math.h>

float my_roundf (float x)
{
    const float half = 0.5f;
    const float one = 2 * half;
    const float lbound = half;
    const float ubound = 1L << 23;
    float a, f, r, s, t;
    s = (x < 0) ? (-one) : one;
    a = x * s;
    t = (a < lbound) ? x : s;
    f = (a < lbound) ? 0 : floorf (a + half);
    r = (a > ubound) ? x : (t * f);
    return r;
}

double my_round (double x)
{
    const double half = 0.5;
    const double one = 2 * half;
    const double lbound = half;
    const double ubound = 1ULL << 52;
    double a, f, r, s, t;
    s = (x < 0) ? (-one) : one;
    a = x * s;
    t = (a < lbound) ? x : s;
    f = (a < lbound) ? 0 : floor (a + half);
    r = (a > ubound) ? x : (t * f);
    return r;
}

uint32_t float_as_uint (float a)
{
    uint32_t r;
    memcpy (&r, &a, sizeof(r));
    return r;
}

float uint_as_float (uint32_t a)
{
    float r;
    memcpy (&r, &a, sizeof(r));
    return r;
}

float newlib_roundf (float x)
{
    uint32_t w;
    int exponent_less_127;

    w = float_as_uint(x);
    /* Extract exponent field. */
    exponent_less_127 = (int)((w & 0x7f800000) >> 23) - 127;
    if (exponent_less_127 < 23) {
        if (exponent_less_127 < 0) {
            /* Extract sign bit. */
            w &= 0x80000000;
            if (exponent_less_127 == -1) {
                /* Result is +1.0 or -1.0. */
                w |= ((uint32_t)127 << 23);
            }
        } else {
            uint32_t exponent_mask = 0x007fffff >> exponent_less_127;
            if ((w & exponent_mask) == 0) {
                /* x has an integral value. */
                return x;
            }
            w += 0x00400000 >> exponent_less_127;
            w &= ~exponent_mask;
        }
    } else {
        if (exponent_less_127 == 128) {
            /* x is NaN or infinite so raise FE_INVALID by adding */
            return x + x;
        } else {
            return x;
        }
    }
    x = uint_as_float (w);
    return x;
}

int main (void)
{
    uint32_t argi, resi, refi;
    float arg, res, ref;

    argi = 0;
    do {
        arg = uint_as_float (argi);
        ref = newlib_roundf (arg);
        res = my_roundf (arg);
        resi = float_as_uint (res);
        refi = float_as_uint (ref);
        if (resi != refi) { // check for identical bit pattern
            printf ("!!!! arg=%08x  res=%08x  ref=%08x\n", argi, resi, refi);
            return EXIT_FAILURE;
        }
        argi++;
    } while (argi);
    return EXIT_SUCCESS;
}

你可以四舍五入到n位精度:

double round( double x )
{
const double sd = 1000; //for accuracy to 3 decimal places
return int(x*sd + (x<0? -0.5 : 0.5))/sd;
}

它在cmath中从c++ 11开始提供(根据http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2012/n3337.pdf)

#include <cmath>
#include <iostream>

int main(int argc, char** argv) {
  std::cout << "round(0.5):\t" << round(0.5) << std::endl;
  std::cout << "round(-0.5):\t" << round(-0.5) << std::endl;
  std::cout << "round(1.4):\t" << round(1.4) << std::endl;
  std::cout << "round(-1.4):\t" << round(-1.4) << std::endl;
  std::cout << "round(1.6):\t" << round(1.6) << std::endl;
  std::cout << "round(-1.6):\t" << round(-1.6) << std::endl;
  return 0;
}

输出:

round(0.5):  1
round(-0.5): -1
round(1.4):  1
round(-1.4): -1
round(1.6):  2
round(-1.6): -2

不需要实现任何东西，所以我不确定为什么这么多答案涉及定义、函数或方法。

C99中

我们有下面的and和header <tgmath.h>用于类型泛型宏。

#include <math.h>
double round (double x);
float roundf (float x);
long double roundl (long double x);

如果您不能编译它，那么您可能遗漏了数学库。类似的命令适用于我拥有的每个C编译器(几个)。

gcc -lm -std=c99 ...

c++ 11

我们在#include <cmath>中有以下和其他依赖于IEEE双精度浮点数的重载。

#include <math.h>
double round (double x);
float round (float x);
long double round (long double x);
double round (T x);

在std名称空间中也有等价物。

如果不能编译，则可能使用C编译而不是c++。下面的基本命令对于g++ 6.3.1、x86_64-w64-mingw32-g++ 6.3.0、clang-x86_64++ 3.8.0和Visual c++ 2015 Community既不会产生错误也不会产生警告。

g++ -std=c++11 -Wall

有序数除法

当除两个序数时，其中T是短的，int，长，或另一个序数，舍入表达式是这样的。

T roundedQuotient = (2 * integerNumerator + 1)
    / (2 * integerDenominator);

精度

毫无疑问，浮点运算中会出现奇怪的错误，但这只是在数字出现时才会出现，与四舍五入无关。

来源不仅仅是IEEE浮点数表示的尾数中的有效数字的数量，它与我们作为人类的十进制思维有关。

10是5和2的乘积，5和2是相对质数。因此，IEEE浮点标准不可能完美地表示为所有二进制数字表示的十进制数。

这不是舍入算法的问题。在选择类型和设计计算、数据输入和数字显示时，应该考虑到数学现实。如果应用程序显示的数字显示了这些十进制-二进制转换问题，那么该应用程序在视觉上表达了数字现实中不存在的、应该更改的准确性。

现在，使用包含C99/ c++ 11数学库的c++ 11编译器应该不是问题。但接下来的问题是:选择哪个舍入函数?

C99/ c++ 11 round()通常不是你想要的舍入函数。它使用了一种时髦的舍入模式，在一半的情况下(+-xxx.5000)舍入0作为抢七。如果你确实特别想要这种舍入模式，或者你的目标是一个round()比rint()更快的c++实现，那么就使用它(或者用这个问题的其他答案之一来模仿它的行为，从表面上看，仔细地复制特定的舍入行为)。

round()的舍入不同于IEEE754默认的舍入到最接近的模式，以偶数作为抢七。最接近偶数避免了数字平均大小的统计偏差，但确实偏向偶数。

有两个数学库舍入函数使用当前默认的舍入模式:std::nearbyint()和std::rint()，它们都是在C99/ c++ 11中添加的，所以它们在std::round()存在的任何时候都可用。唯一的区别是nearbyint从不引发FE_INEXACT。

出于性能考虑，更倾向于rint(): gcc和clang都更容易内联它，但gcc从不内联nearbyint()(即使使用- fast-math)

gcc/clang用于x86-64和AArch64

我把一些测试函数放在Matt Godbolt的编译器资源管理器上，在那里你可以看到source + asm输出(用于多个编译器)。有关阅读编译器输出的更多信息，请参阅此问答和Matt的CppCon2017演讲:“我的编译器最近为我做了什么?”打开编译器的盖子”，

In FP code, it's usually a big win to inline small functions. Especially on non-Windows, where the standard calling convention has no call-preserved registers, so the compiler can't keep any FP values in XMM registers across a call. So even if you don't really know asm, you can still easily see whether it's just a tail-call to the library function or whether it inlined to one or two math instructions. Anything that inlines to one or two instructions is better than a function call (for this particular task on x86 or ARM).

在x86上，任何内联到SSE4.1 roundsd的东西都可以使用SSE4.1 roundpd(或AVX vroundpd)自动向量化。(FP->整数转换也可用打包SIMD形式，除了FP->64位整数，它需要AVX512。)

std::nearbyint(): x86 clang: inlines to a single insn with -msse4.1. x86 gcc: inlines to a single insn only with -msse4.1 -ffast-math, and only on gcc 5.4 and earlier. Later gcc never inlines it (maybe they didn't realize that one of the immediate bits can suppress the inexact exception? That's what clang uses, but older gcc uses the same immediate as for rint when it does inline it) AArch64 gcc6.3: inlines to a single insn by default. std::rint: x86 clang: inlines to a single insn with -msse4.1 x86 gcc7: inlines to a single insn with -msse4.1. (Without SSE4.1, inlines to several instructions) x86 gcc6.x and earlier: inlines to a single insn with -ffast-math -msse4.1. AArch64 gcc: inlines to a single insn by default std::round: x86 clang: doesn't inline x86 gcc: inlines to multiple instructions with -ffast-math -msse4.1, requiring two vector constants. AArch64 gcc: inlines to a single instruction (HW support for this rounding mode as well as IEEE default and most others.) std::floor / std::ceil / std::trunc x86 clang: inlines to a single insn with -msse4.1 x86 gcc7.x: inlines to a single insn with -msse4.1 x86 gcc6.x and earlier: inlines to a single insn with -ffast-math -msse4.1 AArch64 gcc: inlines by default to a single instruction

舍入到int / long / long:

你有两个选择:使用lrint(像rint一样，但返回long，或llrint返回long long)，或使用FP->FP四舍五入函数，然后以正常的方式(带截断)转换为整数类型。有些编译器的一种优化方式比另一种更好。

long l = lrint(x);

int  i = (int)rint(x);

注意int i = lrint(x)首先转换float或double -> long，然后将整型截断为int。对于超出范围的整数，这是有区别的:在c++中未定义行为，但在x86 FP -> int指令中定义良好(编译器将发出除非它在编译时看到UB，同时进行常量传播，那么它被允许使代码在执行时中断)。

On x86, an FP->integer conversion that overflows the integer produces INT_MIN or LLONG_MIN (a bit-pattern of 0x8000000 or the 64-bit equivalent, with just the sign-bit set). Intel calls this the "integer indefinite" value. (See the cvttsd2si manual entry, the SSE2 instruction that converts (with truncation) scalar double to signed integer. It's available with 32-bit or 64-bit integer destination (in 64-bit mode only). There's also a cvtsd2si (convert with current rounding mode), which is what we'd like the compiler to emit, but unfortunately gcc and clang won't do that without -ffast-math.

还要注意，从unsigned int / long到/从unsigned int / long的FP在x86上效率较低(没有AVX512)。在64位机器上转换为32位无符号是非常便宜的;只需转换为64位符号并截断即可。但除此之外，它明显变慢了。

x86 clang with/without -ffast-math -msse4.1: (int/long)rint inlines to roundsd / cvttsd2si. (missed optimization to cvtsd2si). lrint doesn't inline at all. x86 gcc6.x and earlier without -ffast-math: neither way inlines x86 gcc7 without -ffast-math: (int/long)rint rounds and converts separately (with 2 total instructions of SSE4.1 is enabled, otherwise with a bunch of code inlined for rint without roundsd). lrint doesn't inline. x86 gcc with -ffast-math: all ways inline to cvtsd2si (optimal), no need for SSE4.1. AArch64 gcc6.3 without -ffast-math: (int/long)rint inlines to 2 instructions. lrint doesn't inline AArch64 gcc6.3 with -ffast-math: (int/long)rint compiles to a call to lrint. lrint doesn't inline. This may be a missed optimization unless the two instructions we get without -ffast-math are very slow.