The problem isn't the list or the library library. It is the use of
the function sum, which is lazy and when you try to sum a very large
list, it makes a thunk for every single element in the list before
finally evaluating them all backwards to get the sum.
main = do
let n = 40000000
let lst = map sin [1..n]
print $ sum' lst
where
sum' = foldl1' (+)
This is linear, repeatable and quite a bit faster.
On Sun, Apr 10, 2011 at 7:26 PM, Serguei Son
I call GSL's gsl_ran_ugaussian function in the following way (using bindings-gsl):
module Main where
import Bindings.Gsl.RandomNumberGeneration import Bindings.Gsl.RandomNumberDistributions import Foreign import Control.Monad import Data.List
main = do let n = 100000 p <- peek p'gsl_rng_mt19937 rng <- c'gsl_rng_alloc p lst <- replicateM n $ c'gsl_rng_uniform rng print $ sum lst
As I increase n from 10^4 to 10^5 to 10^6 execution time grows superlinearly.
To forestall the answer that the reason is the overhead of List, this code scales approximately linearly:
module Main where
import Foreign import Control.Monad import Data.List
main = do let n = 100000 let lst = map sin [1..n] print $ sum lst
Another interesting observation: when I wrap the sin function of math.h with signature CDouble -> IO CDouble calling it repeatedly scales superlinearly, whereas when I wrap it as a pure function calling it repeatedly scales linearly.
What is the reason for this performance and how can I make the first code scale linearly in execution time?
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