elynx-tools-0.2.1: src/ELynx/Tools/Concurrent.hs
{-# LANGUAGE ScopedTypeVariables #-}
{- |
Module : ELynx.Tools.Concurrent
Description : Tools for concurrent random calculations
Copyright : (c) Dominik Schrempf 2020
License : GPL-3.0-or-later
Maintainer : dominik.schrempf@gmail.com
Stability : unstable
Portability : portable
Creation date: Tue May 7 10:33:24 2019.
-}
module ELynx.Tools.Concurrent
(
-- * MWC
splitGen
-- * Concurrent calculations
, parComp
, getChunks
)
where
import Control.Concurrent
import Control.Concurrent.Async
import Control.Monad
import Control.Monad.Primitive
import qualified Data.Vector as V
import Data.Word
import System.Random.MWC
-- | Split a generator.
splitGen :: PrimMonad m => Int -> Gen (PrimState m) -> m [Gen (PrimState m)]
splitGen n gen
| n <= 0 = return []
| otherwise = do
seeds :: [V.Vector Word32] <- replicateM n $ uniformVector gen 256
mapM initialize seeds
-- -- XXX: This just doesn't work... The only thing I found:
-- -- https://stackoverflow.com/a/16250010.
-- parComp :: (PrimMonad m, Monoid b) => Int -> (Int -> Gen (PrimState m) -> m b)
-- -> Gen (PrimState m) -> m b
-- parComp num fun gen = do
-- let ncap = ceiling (fromIntegral num / fromIntegral chunksize :: Double)
-- chunks = getChunks ncap num
-- gs <- splitGen ncap gen
-- mconcat <$> P.mapM (\(n', g') -> fun n' g') (zip chunks gs)
-- | Perform random calculation in parallel. Does only work with 'IO' and the moment.
parComp :: Int -> (Int -> GenIO -> IO b) -> GenIO -> IO [b]
parComp num fun gen = do
ncap <- getNumCapabilities
let chunks = getChunks ncap num
gs <- splitGen ncap gen
mapConcurrently (uncurry fun) (zip chunks gs)
-- | For a given number of capabilities and number of calculations, get chunk
-- sizes. The chunk sizes will be as evenly distributed as possible and sum up
-- to the number of calculations.
getChunks :: Int -> Int -> [Int]
getChunks c n = ns
where
n' = n `div` c
r = n `mod` c
ns = replicate r (n' + 1) ++ replicate (c - r) n'