On Friday 27 June 2008, Anatoly Yakovenko wrote:
$ cat htestdot.hs {-# OPTIONS_GHC -O2 -fexcess-precision -funbox-strict-fields -fglasgow-exts -fbang-patterns -lcblas#-} module Main where
import Data.Vector.Dense.IO import Control.Monad
main = do let size = 10 let times = 10*1000*1000 v1::IOVector Int Double <- newListVector size $ replicate size 0.1 v2::IOVector Int Double <- newListVector size $ replicate size 0.1 sum <- foldM (\ ii zz -> do rv <- v1 `getDot` v2 return $ zz + rv ) 0.0 [0..times] print $ sum
Hackage is down for the time being, so I can't install blas and look at the core for your program. However, there are still some reasons why this code would be slow. For instance, a brief experiment seems to indicate that foldM is not a good consumer in the foldr/build sense, so no deforestation occurs. Your program is iterating over a 10-million element lazy list. That's going to add overhead. I wrote a simple test program which just adds 0.1 in each iteration: ---- snip ---- {-# LANGUAGE BangPatterns #-} module Main (main) where import Control.Monad main = do let times = 10*1000*1000 sum <- foldM (\_ zz -> return $ zz + 0.1) 0.0 [0..times] -- sum <- foo 0 times 0.0 print $ sum foo :: Int -> Int -> Double -> IO Double foo k m !zz | k <= m = foo (k+1) m (zz + 0.1) | otherwise = return zz ---- snip ---- With foldM, it takes 2.5 seconds on my machine. If you comment that line, and use foo instead, it takes around .1 seconds. So that's a factor of what, 250? That loop allows for a lot more unboxing, which allows much better code to be generated. When Hackage comes back online, I'll take a look at your code, and see if I can make it run faster, but you might want to try it yourself in the time being. Strictifying the addition of the accumulator is probably a good idea, for instance. Cheers, -- Dan