On Sun, Apr 10, 2011 at 6:26 PM, Serguei Son <serguei....@gmail.com> 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 > beginn...@haskell.org > http://www.haskell.org/mailman/listinfo/beginners > _______________________________________________ Haskell-Cafe mailing list Haskell-Cafe@haskell.org http://www.haskell.org/mailman/listinfo/haskell-cafe
