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-- $ runhaskell parallel.hs 2000
import System(getArgs)
import Numeric.LinearAlgebra
import Control.Parallel.Strategies
import System.Time
inParallel = parMap rwhnf id
-- rdeepseq (or older rnf) not needed in this case
-- matrix product decomposed into p parallel subtasks
parMul p x y = fromBlocks [ inParallel ( map (x <>) ys ) ]
where ys = splitColumns p y
-- x <||> y = fromColumns . inParallel . map (x <>) . toColumns $ y
main = do
n <- (read . head) `fmap` getArgs
let m = ident n :: Matrix Double
time $ print $ vectorMax $ takeDiag $ m <> m
-- time $ print $ vectorMax $ takeDiag $ m <||> m
time $ print $ vectorMax $ takeDiag $ parMul 2 m m
time $ print $ vectorMax $ takeDiag $ parMul 4 m m
time $ print $ vectorMax $ takeDiag $ parMul 8 m m
time act = do
t0 <- getClockTime
act
t1 <- getClockTime
print $ tdSec $ normalizeTimeDiff $ diffClockTimes t1 t0
splitColumns n m = splitColumns' (f n (cols m)) m
where
splitColumns' [] m = []
splitColumns' ((a,b):rest) m = subMatrix (0,a) (rows m, b-a+1) m : splitColumns' rest m
f :: Int -> Int -> [(Int,Int)]
f n c = zip ks (map pred $ tail ks)
where ks = map round $ toList $ linspace (fromIntegral n+1) (0,fromIntegral c)
splitRowsAt p m = (takeRows p m, dropRows p m)
splitColumnsAt p m = (takeColumns p m, dropColumns p m)
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