streamly-0.3.0: benchmark/Linear.hs
-- |
-- Module : Main
-- Copyright : (c) 2018 Harendra Kumar
--
-- License : BSD3
-- Maintainer : harendra.kumar@gmail.com
import Control.DeepSeq (NFData)
-- import Data.Functor.Identity (Identity, runIdentity)
import System.Random (randomRIO)
import qualified LinearOps as Ops
import Streamly
import Gauge
-- We need a monadic bind here to make sure that the function f does not get
-- completely optimized out by the compiler in some cases.
benchIO :: (IsStream t, NFData b) => String -> (t IO Int -> IO b) -> Benchmark
benchIO name f = bench name $ nfIO $ randomRIO (1,1000) >>= f . Ops.source
benchSrcIO
:: (t IO Int -> SerialT IO Int)
-> String
-> (Int -> t IO Int)
-> Benchmark
benchSrcIO t name f
= bench name $ nfIO $ randomRIO (1,1000) >>= Ops.toNull t . f
{-
_benchId :: NFData b => String -> (Ops.Stream m Int -> Identity b) -> Benchmark
_benchId name f = bench name $ nf (runIdentity . f) (Ops.source 10)
-}
main :: IO ()
main = do
defaultMain
[ bgroup "serially"
[ bgroup "generation"
[ benchSrcIO serially "unfoldr" $ Ops.sourceUnfoldr
, benchSrcIO serially "unfoldrM" Ops.sourceUnfoldrM
, benchSrcIO serially "fromFoldable" Ops.sourceFromFoldable
, benchSrcIO serially "fromFoldableM" Ops.sourceFromFoldableM
, benchSrcIO serially "foldMapWith" Ops.sourceFoldMapWith
, benchSrcIO serially "foldMapWithM" Ops.sourceFoldMapWithM
]
, bgroup "elimination"
[ benchIO "toList" Ops.toList
, benchIO "fold" Ops.foldl
, benchIO "last" Ops.last
]
, bgroup "transformation"
[ benchIO "scan" Ops.scan
, benchIO "map" Ops.map
, benchIO "mapM" (Ops.mapM serially)
, benchIO "concat" Ops.concat
]
, bgroup "filtering"
[ benchIO "filter-even" Ops.filterEven
, benchIO "filter-all-out" Ops.filterAllOut
, benchIO "filter-all-in" Ops.filterAllIn
, benchIO "take-all" Ops.takeAll
, benchIO "takeWhile-true" Ops.takeWhileTrue
, benchIO "drop-all" Ops.dropAll
, benchIO "dropWhile-true" Ops.dropWhileTrue
]
, benchIO "zip" $ Ops.zip
, bgroup "compose"
[ benchIO "mapM" Ops.composeMapM
, benchIO "map-with-all-in-filter" Ops.composeMapAllInFilter
, benchIO "all-in-filters" Ops.composeAllInFilters
, benchIO "all-out-filters" Ops.composeAllOutFilters
]
-- Scaling with same operation in sequence
, bgroup "compose-scaling"
[ benchIO "1" $ Ops.composeScaling 1
, benchIO "2" $ Ops.composeScaling 2
, benchIO "3" $ Ops.composeScaling 3
, benchIO "4" $ Ops.composeScaling 4
]
]
, bgroup "asyncly"
[ -- benchIO "unfoldr" $ Ops.toNull asyncly
-- , benchSrcIO asyncly "fromFoldable" Ops.sourceFromFoldable
benchSrcIO asyncly "unfoldrM" Ops.sourceUnfoldrM
, benchSrcIO asyncly "fromFoldableM" Ops.sourceFromFoldableM
, benchSrcIO asyncly "foldMapWith" Ops.sourceFoldMapWith
, benchSrcIO asyncly "foldMapWithM" Ops.sourceFoldMapWithM
, benchIO "mapM" $ Ops.mapM asyncly
]
, bgroup "wAsyncly"
[ -- benchIO "unfoldr" $ Ops.toNull wAsyncly
-- , benchSrcIO wAsyncly "fromFoldable" Ops.sourceFromFoldable
benchSrcIO wAsyncly "unfoldrM" Ops.sourceUnfoldrM
, benchSrcIO wAsyncly "fromFoldableM" Ops.sourceFromFoldableM
, benchSrcIO wAsyncly "foldMapWith" Ops.sourceFoldMapWith
, benchSrcIO wAsyncly "foldMapWithM" Ops.sourceFoldMapWithM
, benchIO "mapM" $ Ops.mapM wAsyncly
]
-- unfoldr and fromFoldable are always serial and thereofore the same for
-- all stream types.
, bgroup "aheadly"
[ -- benchIO "unfoldr" $ Ops.toNull aheadly
-- , benchSrcIO aheadly "fromFoldable" Ops.sourceFromFoldable
benchSrcIO aheadly "unfoldrM" Ops.sourceUnfoldrM
, benchSrcIO aheadly "fromFoldableM" Ops.sourceFromFoldableM
, benchSrcIO aheadly "foldMapWith" Ops.sourceFoldMapWith
, benchSrcIO aheadly "foldMapWithM" Ops.sourceFoldMapWithM
, benchIO "mapM" $ Ops.mapM aheadly
]
-- XXX need to use smaller streams to finish in reasonable time
, bgroup "parallely"
[ --benchIO "unfoldr" $ Ops.toNull parallely
--, benchSrcIO parallely "fromFoldable" Ops.sourceFromFoldable
benchSrcIO parallely "unfoldrM" Ops.sourceUnfoldrM
, benchSrcIO parallely "fromFoldableM" Ops.sourceFromFoldableM
, benchSrcIO parallely "foldMapWith" Ops.sourceFoldMapWith
, benchSrcIO parallely "foldMapWithM" Ops.sourceFoldMapWithM
, benchIO "mapM" $ Ops.mapM parallely
-- Zip has only one parallel flavor
, benchIO "zip" $ Ops.zipAsync
]
]