我一直在学习更快速的指数算法(如k-ary、滑动门等),不知道哪些算法被用于CPU/编程语言中?(我不确定这是处理器还是编译器实现的)
只是出于好奇,哪个是最快的?
关于广度的编辑:我有意使问题比较宽泛,因为我知道有许多不同的技术可以做到这一点。选定答案就是我想要的。
我一直在学习更快速的指数算法(如k-ary、滑动门等),不知道哪些算法被用于CPU/编程语言中?(我不确定这是处理器还是编译器实现的)
只是出于好奇,哪个是最快的?
关于广度的编辑:我有意使问题比较宽泛,因为我知道有许多不同的技术可以做到这一点。选定答案就是我想要的。
exp()
、exp2()
、exp10()
和pow()
,以及单精度版本的expf()
、exp2f()
、exp10f()
和powf()
。math.h
或cmath
提供的指数函数。标准数学函数的实现细节,如exp()
,不同,但一个常见的方案遵循三个步骤:log(0.0)
,或特殊的浮点操作数,如NaN(非数字)。expf(float)
的C99代码,展示了一个具体示例的这些步骤。首先将参数a
分裂,使得exp(a)
= er * 2i,其中i
是整数,r
在[log(sqrt(0.5), log(sqrt(2.0)],即主逼近区间内。第二步,我们现在用多项式逼近er。这样的逼近可以根据各种设计标准进行设计,例如最小化绝对误差或相对误差。多项式可以以各种方式进行评估,包括Horner方案和Estrin方案。fmaf()
得到增强。a*b
在加法期间进行计算,并在最后应用单个舍入。在大多数现代硬件上,如GPU、IBM Power CPU、最新的x86处理器(例如Haswell)、最新的ARM处理器(作为可选扩展),这直接映射到硬件指令。在缺少这样的指令的平台上,fmaf()
将映射到相当慢的仿真代码,这种情况下,如果我们关心性能,就不想使用它。#include <math.h> /* import fmaf(), ldexpf(), INFINITY */
/* Like rintf(), but -0.0f -> +0.0f, and |a| must be < 2**22 */
float quick_and_dirty_rintf (float a)
{
const float cvt_magic = 0x1.800000p+23f;
return (a + cvt_magic) - cvt_magic;
}
/* Approximate exp(a) on the interval [log(sqrt(0.5)), log(sqrt(2.0))]. */
float expf_poly (float a)
{
float r;
r = 0x1.694000p-10f; // 1.37805939e-3
r = fmaf (r, a, 0x1.125edcp-07f); // 8.37312452e-3
r = fmaf (r, a, 0x1.555b5ap-05f); // 4.16695364e-2
r = fmaf (r, a, 0x1.555450p-03f); // 1.66664720e-1
r = fmaf (r, a, 0x1.fffff6p-02f); // 4.99999851e-1
r = fmaf (r, a, 0x1.000000p+00f); // 1.00000000e+0
r = fmaf (r, a, 0x1.000000p+00f); // 1.00000000e+0
return r;
}
/* Approximate exp2() on interval [-0.5,+0.5] */
float exp2f_poly (float a)
{
float r;
r = 0x1.418000p-13f; // 1.53303146e-4
r = fmaf (r, a, 0x1.5efa94p-10f); // 1.33887795e-3
r = fmaf (r, a, 0x1.3b2c6cp-07f); // 9.61833261e-3
r = fmaf (r, a, 0x1.c6af8ep-05f); // 5.55036329e-2
r = fmaf (r, a, 0x1.ebfbe0p-03f); // 2.40226507e-1
r = fmaf (r, a, 0x1.62e430p-01f); // 6.93147182e-1
r = fmaf (r, a, 0x1.000000p+00f); // 1.00000000e+0
return r;
}
/* Approximate exp10(a) on [log(sqrt(0.5))/log(10), log(sqrt(2.0))/log(10)] */
float exp10f_poly (float a)
{
float r;
r = 0x1.a56000p-3f; // 0.20574951
r = fmaf (r, a, 0x1.155aa8p-1f); // 0.54170728
r = fmaf (r, a, 0x1.2bda96p+0f); // 1.17130411
r = fmaf (r, a, 0x1.046facp+1f); // 2.03465796
r = fmaf (r, a, 0x1.53524ap+1f); // 2.65094876
r = fmaf (r, a, 0x1.26bb1cp+1f); // 2.30258512
r = fmaf (r, a, 0x1.000000p+0f); // 1.00000000
return r;
}
/* Compute exponential base e. Maximum ulp error = 0.86565 */
float my_expf (float a)
{
float t, r;
int i;
t = a * 0x1.715476p+0f; // 1/log(2); 1.442695
t = quick_and_dirty_rintf (t);
i = (int)t;
r = fmaf (t, -0x1.62e400p-01f, a); // log_2_hi; -6.93145752e-1
r = fmaf (t, -0x1.7f7d1cp-20f, r); // log_2_lo; -1.42860677e-6
t = expf_poly (r);
r = ldexpf (t, i);
if (a < -105.0f) r = 0.0f;
if (a > 105.0f) r = INFINITY; // +INF
return r;
}
/* Compute exponential base 2. Maximum ulp error = 0.86770 */
float my_exp2f (float a)
{
float t, r;
int i;
t = quick_and_dirty_rintf (a);
i = (int)t;
r = a - t;
t = exp2f_poly (r);
r = ldexpf (t, i);
if (a < -152.0f) r = 0.0f;
if (a > 152.0f) r = INFINITY; // +INF
return r;
}
/* Compute exponential base 10. Maximum ulp error = 0.95588 */
float my_exp10f (float a)
{
float r, t;
int i;
t = a * 0x1.a934f0p+1f; // log2(10); 3.321928
t = quick_and_dirty_rintf (t);
i = (int)t;
r = fmaf (t, -0x1.344140p-2f, a); // log10(2)_hi // -3.01030159e-1
r = fmaf (t, 0x1.5ec10cp-23f, r); // log10(2)_lo // 1.63332601e-7
t = exp10f_poly (r);
r = ldexpf (t, i);
if (a < -46.0f) r = 0.0f;
if (a > 46.0f) r = INFINITY; // +INF
return r;
}
#include <string.h>
#include <stdint.h>
uint32_t float_as_uint32 (float a)
{
uint32_t r;
memcpy (&r, &a, sizeof r);
return r;
}
float uint32_as_float (uint32_t a)
{
float r;
memcpy (&r, &a, sizeof r);
return r;
}
uint64_t double_as_uint64 (double a)
{
uint64_t r;
memcpy (&r, &a, sizeof r);
return r;
}
double floatUlpErr (float res, double ref)
{
uint64_t i, j, err, refi;
int expoRef;
/* ulp error cannot be computed if either operand is NaN, infinity, zero */
if (isnan (res) || isnan (ref) || isinf (res) || isinf (ref) ||
(res == 0.0f) || (ref == 0.0f)) {
return 0.0;
}
/* Convert the float result to an "extended float". This is like a float
with 56 instead of 24 effective mantissa bits.
*/
i = ((uint64_t)float_as_uint32(res)) << 32;
/* Convert the double reference to an "extended float". If the reference is
>= 2^129, we need to clamp to the maximum "extended float". If reference
is < 2^-126, we need to denormalize because of the float types's limited
exponent range.
*/
refi = double_as_uint64(ref);
expoRef = (int)(((refi >> 52) & 0x7ff) - 1023);
if (expoRef >= 129) {
j = 0x7fffffffffffffffULL;
} else if (expoRef < -126) {
j = ((refi << 11) | 0x8000000000000000ULL) >> 8;
j = j >> (-(expoRef + 126));
} else {
j = ((refi << 11) & 0x7fffffffffffffffULL) >> 8;
j = j | ((uint64_t)(expoRef + 127) << 55);
}
j = j | (refi & 0x8000000000000000ULL);
err = (i < j) ? (j - i) : (i - j);
return err / 4294967296.0;
}
#include <stdio.h>
#include <stdlib.h>
int main (void)
{
double ref, ulp, maxulp;
float arg, res, reff;
uint32_t argi, resi, refi, diff, sumdiff;
printf ("testing expf ...\n");
argi = 0;
sumdiff = 0;
maxulp = 0;
do {
arg = uint32_as_float (argi);
res = my_expf (arg);
ref = exp ((double)arg);
ulp = floatUlpErr (res, ref);
if (ulp > maxulp) maxulp = ulp;
reff = (float)ref;
refi = float_as_uint32 (reff);
resi = float_as_uint32 (res);
diff = (resi < refi) ? (refi - resi) : (resi - refi);
if (diff > 1) {
printf ("!! expf: arg=%08x res=%08x ref=%08x\n", argi, resi, refi);
return EXIT_FAILURE;
} else {
sumdiff += diff;
}
argi++;
} while (argi);
printf ("expf maxulp=%.5f sumdiff=%u\n", maxulp, sumdiff);
printf ("testing exp2f ...\n");
argi = 0;
maxulp = 0;
sumdiff = 0;
do {
arg = uint32_as_float (argi);
res = my_exp2f (arg);
ref = exp2 ((double)arg);
ulp = floatUlpErr (res, ref);
if (ulp > maxulp) maxulp = ulp;
reff = (float)ref;
refi = float_as_uint32 (reff);
resi = float_as_uint32 (res);
diff = (resi < refi) ? (refi - resi) : (resi - refi);
if (diff > 1) {
printf ("!! expf: arg=%08x res=%08x ref=%08x\n", argi, resi, refi);
return EXIT_FAILURE;
} else {
sumdiff += diff;
}
argi++;
} while (argi);
printf ("exp2f maxulp=%.5f sumdiff=%u\n", maxulp, sumdiff);
printf ("testing exp10f ...\n");
argi = 0;
maxulp = 0;
sumdiff = 0;
do {
arg = uint32_as_float (argi);
res = my_exp10f (arg);
ref = exp10 ((double)arg);
ulp = floatUlpErr (res, ref);
if (ulp > maxulp) maxulp = ulp;
reff = (float)ref;
refi = float_as_uint32 (reff);
resi = float_as_uint32 (res);
diff = (resi < refi) ? (refi - resi) : (resi - refi);
if (diff > 1) {
printf ("!! expf: arg=%08x res=%08x ref=%08x\n", argi, resi, refi);
return EXIT_FAILURE;
} else {
sumdiff += diff;
}
argi++;
} while (argi);
printf ("exp10f maxulp=%.5f sumdiff=%u\n", maxulp, sumdiff);
return EXIT_SUCCESS;
}
pow(double,double)
和pow(double,int)
经常是不同的代码路径,而exp(double)
则是另一个独立的函数。你对这些中哪一个感兴趣?pow(double,int)
通常采用基于指数位逐位扫描的平方乘法变体。x86处理器内部的旧x87 FPU具有F2XM1
指令,可用于实现exp()
和pow()
。现在基于x86的系统通常使用SSE指令,而x87 FPU主要用于遗留支持。如果需要,我可以展示expf(float)
的代码示例。 - njuffa