When reading
http://www.macs.hw.ac.uk/~dsg/gph/papers/html/Strategies/strategies.html
I got the impression, that when I want to compute in parallel I have to
suppress laziness at all costs, otherwise only a neglible portion of the
code is run in parallel. How can I parallelize the computation of two
lazily generated lists, where the list generation is expensive, but the
combination of the lists is cheap?
For example:
module Main where
expensiveList :: Int -> [Int]
expensiveList n =
map (\m -> sum [n..m]) [10000000..]
sequentialZip :: [Int]
sequentialZip =
zipWith (+)
(expensiveList 1)
(expensiveList 2)
main :: IO ()
main =
mapM_ print $ take 10 sequentialZip
It seems to me that this program must run almost twice as fast when using
two cores, because the expensive lists can be computed perfectly in
parallel. It requires however, that the zipWith can fetch data lazily
across threads. However applying a Parallel strategy to the expensive
list, will certainly try to evaluate it completely.
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