我把Project Euler中的第12题作为一个编程练习,并比较了我在C、Python、Erlang和Haskell中的实现(当然不是最优的)。为了获得更高的执行时间,我搜索第一个因数超过1000的三角形数,而不是原始问题中所述的500。
结果如下:
C:
lorenzo@enzo:~/erlang$ gcc -lm -o euler12.bin euler12.c
lorenzo@enzo:~/erlang$ time ./euler12.bin
842161320
real 0m11.074s
user 0m11.070s
sys 0m0.000s
Python:
lorenzo@enzo:~/erlang$ time ./euler12.py
842161320
real 1m16.632s
user 1m16.370s
sys 0m0.250s
Python与PyPy:
lorenzo@enzo:~/Downloads/pypy-c-jit-43780-b590cf6de419-linux64/bin$ time ./pypy /home/lorenzo/erlang/euler12.py
842161320
real 0m13.082s
user 0m13.050s
sys 0m0.020s
Erlang:
lorenzo@enzo:~/erlang$ erlc euler12.erl
lorenzo@enzo:~/erlang$ time erl -s euler12 solve
Erlang R13B03 (erts-5.7.4) [source] [64-bit] [smp:4:4] [rq:4] [async-threads:0] [hipe] [kernel-poll:false]
Eshell V5.7.4 (abort with ^G)
1> 842161320
real 0m48.259s
user 0m48.070s
sys 0m0.020s
Haskell:
lorenzo@enzo:~/erlang$ ghc euler12.hs -o euler12.hsx
[1 of 1] Compiling Main ( euler12.hs, euler12.o )
Linking euler12.hsx ...
lorenzo@enzo:~/erlang$ time ./euler12.hsx
842161320
real 2m37.326s
user 2m37.240s
sys 0m0.080s
简介:
C: 100%
Python: 692% (PyPy占118%)
Erlang: 436%(135%归功于RichardC)
Haskell: 1421%
我认为C语言有一个很大的优势,因为它使用长来进行计算,而不是像其他三种那样使用任意长度的整数。它也不需要首先加载运行时(其他的呢?)
问题1:
Erlang, Python和Haskell是否会因为使用任意长度的整数而降低速度,或者只要值小于MAXINT就不会?
问题2:
哈斯克尔为什么这么慢?是否有一个编译器标志关闭刹车或它是我的实现?(后者是很有可能的,因为Haskell对我来说是一本有七个印章的书。)
问题3:
你能否给我一些提示,如何在不改变我确定因素的方式的情况下优化这些实现?以任何方式优化:更好、更快、更“原生”的语言。
编辑:
问题4:
我的函数实现是否允许LCO(最后调用优化,也就是尾递归消除),从而避免在调用堆栈中添加不必要的帧?
虽然我不得不承认我的Haskell和Erlang知识非常有限,但我确实试图用这四种语言实现尽可能相似的相同算法。
使用的源代码:
#include <stdio.h>
#include <math.h>
int factorCount (long n)
{
double square = sqrt (n);
int isquare = (int) square;
int count = isquare == square ? -1 : 0;
long candidate;
for (candidate = 1; candidate <= isquare; candidate ++)
if (0 == n % candidate) count += 2;
return count;
}
int main ()
{
long triangle = 1;
int index = 1;
while (factorCount (triangle) < 1001)
{
index ++;
triangle += index;
}
printf ("%ld\n", triangle);
}
#! /usr/bin/env python3.2
import math
def factorCount (n):
square = math.sqrt (n)
isquare = int (square)
count = -1 if isquare == square else 0
for candidate in range (1, isquare + 1):
if not n % candidate: count += 2
return count
triangle = 1
index = 1
while factorCount (triangle) < 1001:
index += 1
triangle += index
print (triangle)
-module (euler12).
-compile (export_all).
factorCount (Number) -> factorCount (Number, math:sqrt (Number), 1, 0).
factorCount (_, Sqrt, Candidate, Count) when Candidate > Sqrt -> Count;
factorCount (_, Sqrt, Candidate, Count) when Candidate == Sqrt -> Count + 1;
factorCount (Number, Sqrt, Candidate, Count) ->
case Number rem Candidate of
0 -> factorCount (Number, Sqrt, Candidate + 1, Count + 2);
_ -> factorCount (Number, Sqrt, Candidate + 1, Count)
end.
nextTriangle (Index, Triangle) ->
Count = factorCount (Triangle),
if
Count > 1000 -> Triangle;
true -> nextTriangle (Index + 1, Triangle + Index + 1)
end.
solve () ->
io:format ("~p~n", [nextTriangle (1, 1) ] ),
halt (0).
factorCount number = factorCount' number isquare 1 0 - (fromEnum $ square == fromIntegral isquare)
where square = sqrt $ fromIntegral number
isquare = floor square
factorCount' number sqrt candidate count
| fromIntegral candidate > sqrt = count
| number `mod` candidate == 0 = factorCount' number sqrt (candidate + 1) (count + 2)
| otherwise = factorCount' number sqrt (candidate + 1) count
nextTriangle index triangle
| factorCount triangle > 1000 = triangle
| otherwise = nextTriangle (index + 1) (triangle + index + 1)
main = print $ nextTriangle 1 1
只是为了好玩。下面是一个更“原生”的Haskell实现:
import Control.Applicative
import Control.Monad
import Data.Either
import Math.NumberTheory.Powers.Squares
isInt :: RealFrac c => c -> Bool
isInt = (==) <$> id <*> fromInteger . round
intSqrt :: (Integral a) => a -> Int
--intSqrt = fromIntegral . floor . sqrt . fromIntegral
intSqrt = fromIntegral . integerSquareRoot'
factorize :: Int -> [Int]
factorize 1 = []
factorize n = first : factorize (quot n first)
where first = (!! 0) $ [a | a <- [2..intSqrt n], rem n a == 0] ++ [n]
factorize2 :: Int -> [(Int,Int)]
factorize2 = foldl (\ls@((val,freq):xs) y -> if val == y then (val,freq+1):xs else (y,1):ls) [(0,0)] . factorize
numDivisors :: Int -> Int
numDivisors = foldl (\acc (_,y) -> acc * (y+1)) 1 <$> factorize2
nextTriangleNumber :: (Int,Int) -> (Int,Int)
nextTriangleNumber (n,acc) = (n+1,acc+n+1)
forward :: Int -> (Int, Int) -> Either (Int, Int) (Int, Int)
forward k val@(n,acc) = if numDivisors acc > k then Left val else Right (nextTriangleNumber val)
problem12 :: Int -> (Int, Int)
problem12 n = (!!0) . lefts . scanl (>>=) (forward n (1,1)) . repeat . forward $ n
main = do
let (n,val) = problem12 1000
print val
使用ghc -O3,它在我的机器上持续运行0.55-0.58秒(1.73GHz Core i7)。
C版本中一个更有效的factorCount函数:
int factorCount (int n)
{
int count = 1;
int candidate,tmpCount;
while (n % 2 == 0) {
count++;
n /= 2;
}
for (candidate = 3; candidate < n && candidate * candidate < n; candidate += 2)
if (n % candidate == 0) {
tmpCount = 1;
do {
tmpCount++;
n /= candidate;
} while (n % candidate == 0);
count*=tmpCount;
}
if (n > 1)
count *= 2;
return count;
}
在main中使用gcc -O3 -lm将long类型更改为int类型,该程序始终在0.31-0.35秒内运行。
如果您利用第n个三角形数= n*(n+1)/2,并且n和(n+1)具有完全不同的质因数分解,则可以使两者运行得更快,因此可以将每个一半的因数数相乘,以得到整体的因数数。以下几点:
int main ()
{
int triangle = 0,count1,count2 = 1;
do {
count1 = count2;
count2 = ++triangle % 2 == 0 ? factorCount(triangle+1) : factorCount((triangle+1)/2);
} while (count1*count2 < 1001);
printf ("%lld\n", ((long long)triangle)*(triangle+1)/2);
}
将c代码的运行时间减少到0.17-0.19秒,它可以处理更大的搜索——大于10000个因数在我的机器上大约需要43秒。我给感兴趣的读者留下了类似的haskell加速。
Erlang实现存在一些问题。作为下面的基准,我测量的未修改的Erlang程序的执行时间为47.6秒,而C代码的执行时间为12.7秒。
(编辑:在Erlang/OTP版本24,2021年,Erlang有一个自动JIT编译器,旧的+本机编译器选项不再支持或需要。我保留下面这段文字作为历史文件。关于export_all的注释对于jit生成良好代码的能力仍然是有效的。)
The first thing you should do if you want to run computationally intensive Erlang code is to use native code. Compiling with erlc +native euler12 got the time down to 41.3 seconds. This is however a much lower speedup (just 15%) than expected from native compilation on this kind of code, and the problem is your use of -compile(export_all). This is useful for experimentation, but the fact that all functions are potentially reachable from the outside causes the native compiler to be very conservative. (The normal BEAM emulator is not that much affected.) Replacing this declaration with -export([solve/0]). gives a much better speedup: 31.5 seconds (almost 35% from the baseline).
但是代码本身有一个问题:对于factorCount循环中的每一次迭代,都要执行以下测试:
factorCount (_, Sqrt, Candidate, Count) when Candidate == Sqrt -> Count + 1;
C代码不这样做。一般来说,在相同代码的不同实现之间进行公平的比较是很棘手的,特别是如果算法是数值的,因为您需要确保它们实际上在做相同的事情。在某个实现中由于某个类型转换而产生的轻微舍入错误可能会导致它比另一个实现进行更多的迭代,即使两者最终得到相同的结果。
为了消除这个可能的错误源(并在每次迭代中摆脱额外的测试),我重写了factorCount函数,如下所示,密切模仿C代码:
factorCount (N) ->
Sqrt = math:sqrt (N),
ISqrt = trunc(Sqrt),
if ISqrt == Sqrt -> factorCount (N, ISqrt, 1, -1);
true -> factorCount (N, ISqrt, 1, 0)
end.
factorCount (_N, ISqrt, Candidate, Count) when Candidate > ISqrt -> Count;
factorCount ( N, ISqrt, Candidate, Count) ->
case N rem Candidate of
0 -> factorCount (N, ISqrt, Candidate + 1, Count + 2);
_ -> factorCount (N, ISqrt, Candidate + 1, Count)
end.
这个重写,没有export_all和本机编译,给了我以下运行时:
$ erlc +native euler12.erl
$ time erl -noshell -s euler12 solve
842161320
real 0m19.468s
user 0m19.450s
sys 0m0.010s
这与C代码相比不算太糟:
$ time ./a.out
842161320
real 0m12.755s
user 0m12.730s
sys 0m0.020s
考虑到Erlang完全不适合编写数字代码,在这样的程序中只比C慢50%就已经很不错了。
最后,关于你的问题:
问题1:erlang、python和haskell是否会因为使用任意长度的整数而降低速度
只要值小于MAXINT,它们不就行了吗?
Yes, somewhat. In Erlang, there is no way of saying "use 32/64-bit arithmetic with wrap-around", so unless the compiler can prove some bounds on your integers (and it usually can't), it must check all computations to see if they can fit in a single tagged word or if it has to turn them into heap-allocated bignums. Even if no bignums are ever used in practice at runtime, these checks will have to be performed. On the other hand, that means you know that the algorithm will never fail because of an unexpected integer wraparound if you suddenly give it larger inputs than before.
问题4:我的函数实现是否允许LCO,从而避免在调用堆栈中添加不必要的帧?
是的,您的Erlang代码在最后调用优化方面是正确的。
只是为了好玩。下面是一个更“原生”的Haskell实现:
import Control.Applicative
import Control.Monad
import Data.Either
import Math.NumberTheory.Powers.Squares
isInt :: RealFrac c => c -> Bool
isInt = (==) <$> id <*> fromInteger . round
intSqrt :: (Integral a) => a -> Int
--intSqrt = fromIntegral . floor . sqrt . fromIntegral
intSqrt = fromIntegral . integerSquareRoot'
factorize :: Int -> [Int]
factorize 1 = []
factorize n = first : factorize (quot n first)
where first = (!! 0) $ [a | a <- [2..intSqrt n], rem n a == 0] ++ [n]
factorize2 :: Int -> [(Int,Int)]
factorize2 = foldl (\ls@((val,freq):xs) y -> if val == y then (val,freq+1):xs else (y,1):ls) [(0,0)] . factorize
numDivisors :: Int -> Int
numDivisors = foldl (\acc (_,y) -> acc * (y+1)) 1 <$> factorize2
nextTriangleNumber :: (Int,Int) -> (Int,Int)
nextTriangleNumber (n,acc) = (n+1,acc+n+1)
forward :: Int -> (Int, Int) -> Either (Int, Int) (Int, Int)
forward k val@(n,acc) = if numDivisors acc > k then Left val else Right (nextTriangleNumber val)
problem12 :: Int -> (Int, Int)
problem12 n = (!!0) . lefts . scanl (>>=) (forward n (1,1)) . repeat . forward $ n
main = do
let (n,val) = problem12 1000
print val
使用ghc -O3,它在我的机器上持续运行0.55-0.58秒(1.73GHz Core i7)。
C版本中一个更有效的factorCount函数:
int factorCount (int n)
{
int count = 1;
int candidate,tmpCount;
while (n % 2 == 0) {
count++;
n /= 2;
}
for (candidate = 3; candidate < n && candidate * candidate < n; candidate += 2)
if (n % candidate == 0) {
tmpCount = 1;
do {
tmpCount++;
n /= candidate;
} while (n % candidate == 0);
count*=tmpCount;
}
if (n > 1)
count *= 2;
return count;
}
在main中使用gcc -O3 -lm将long类型更改为int类型,该程序始终在0.31-0.35秒内运行。
如果您利用第n个三角形数= n*(n+1)/2,并且n和(n+1)具有完全不同的质因数分解,则可以使两者运行得更快,因此可以将每个一半的因数数相乘,以得到整体的因数数。以下几点:
int main ()
{
int triangle = 0,count1,count2 = 1;
do {
count1 = count2;
count2 = ++triangle % 2 == 0 ? factorCount(triangle+1) : factorCount((triangle+1)/2);
} while (count1*count2 < 1001);
printf ("%lld\n", ((long long)triangle)*(triangle+1)/2);
}
将c代码的运行时间减少到0.17-0.19秒,它可以处理更大的搜索——大于10000个因数在我的机器上大约需要43秒。我给感兴趣的读者留下了类似的haskell加速。