
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?