Performance evalRandIO的怪异表演

我在evalRandIO上遇到了一些奇怪的性能问题。以下是违规代码：

import Control.Monad.Random

inf :: (RandomGen g, Random a) => Rand g [a]
inf = sequence $ repeat $ getRandom

many :: (RandomGen g, Random a) => Int -> Rand g [a]
many n = sequence $ replicate n $ getRandom

main = do
  m <- evalRandIO $ many 1000000 :: IO [Bool]
  i <- evalRandIO $ inf :: IO [Bool]
  putStrLn $ show $ take 5 m 
  putStrLn $ show $ take 5 i

---

无法在MacOS X 10.6.4上复制：

botanix:~ stolz$ ghci rand.hs 
GHCi, version 6.12.3: http://www.haskell.org/ghc/  :? for help
Loading package ghc-prim ... linking ... done.
Loading package integer-gmp ... linking ... done.
Loading package base ... linking ... done.
Loading package ffi-1.0 ... linking ... done.
[1 of 1] Compiling Main             ( rand.hs, interpreted )
Ok, modules loaded: Main.
*Main> main
Loading package old-locale-1.0.0.2 ... linking ... done.
Loading package time-1.1.4 ... linking ... done.
Loading package random-1.0.0.2 ... linking ... done.
Loading package transformers-0.2.2.0 ... linking ... done.
Loading package mtl-2.0.1.0 ... linking ... done.
Loading package MonadRandom-0.1.6 ... linking ... done.
[True,False,False,True,True]
[False,True,False,True,False]

更新：D'oh，编译时行为不同，所以我吃我的话：

botanix:~ stolz$ ./a.out 
[False,True,True,False,True]
Stack space overflow: current size 8388608 bytes.

---

答案比看起来要简单。当你写作时：

 m <- evalRandIO $ many 1000000 :: IO [Bool]

---

m我已经在ghci和ghc版本6.12.3中试用过了。我使用的是OSX10.6.Hm，这里是10.6.4。图书馆的版本如何？您可以发布ghci运行的完整输出吗？我得到的结果与nitromaster101、GHC 7.0.2、Linux相同。@Tener：结果是“什么都没发生，我按了Ctrl-C”，还是堆栈溢出？堆栈溢出。我认为“什么都没发生”是不对的，程序实际上是在计算种子值。好的，你中断了运行。只是为了好玩，你能让它运行直到它自己退出吗（如果它真的退出的话）？程序在毫无限制地消耗内存。是的，我在想这是否和中的问题一样。但这不能解释堆栈溢出。当然，重复重新播种应该使用恒定的堆栈空间。我想知道是否有泄漏的地方，但我不能使剖析足够详细。
botanix:~ stolz$ ./a.out 
[False,True,True,False,True]
Stack space overflow: current size 8388608 bytes.

 m <- evalRandIO $ many 1000000 :: IO [Bool]

import Control.Monad.Random

inf :: (RandomGen g, Random a) => Rand g [a]
inf = sequence $ repeat $ getRandom

many :: (RandomGen g, Random a) => Int -> Rand g [a]
many n = sequence $ replicate n $ getRandom

main = do
  newGen' <- newStdGen
  m <- evalRandIO $ many 1000000 :: IO [Bool]
  setStdGen newGen'
  i <- evalRandIO $ inf :: IO [Bool]
  putStrLn $ show $ take 5 m 
  putStrLn $ show $ take 5 i