On Sun, Apr 10, 2011 at 6:26 PM, Serguei Son wrote:

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.

Not sure if it is related, but this thread also documents issues folks had with replicateM and performance: http://www.haskell.org/pipermail/haskell-cafe/2011-March/090419.html Antoine

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?

_______________________________________________ Beginners mailing list Beginners@haskell.org http://www.haskell.org/mailman/listinfo/beginners