{-# LANGUAGE MultiParamTypeClasses, FunctionalDependencies, CPP, FlexibleInstances, UndecidableInstances #-} -- UndecidableInstances {-| This module establishes a class hierarchy that captures the interfaces of @Par@ monads. There are two layers: simple futures ('ParFuture') and full @IVars@ ('ParIVar'). All @Par@ monads are expected to implement the former, some also implement the latter. For more documentation of the programming model, see * The "Control.Monad.Par" module in the @monad-par@ package. * The wiki\/tutorial () * The original paper () * Tutorial slides () * Other slides (, ) -} -- module Control.Monad.Par.Class ( -- * Futures ParFuture(..) -- * IVars , ParIVar(..) -- RRN: Not releasing this interface until there is a nice implementation of it: -- Channels (Streams) -- , ParChan(..) , NFData() -- This is reexported. ) where import Control.DeepSeq -------------------------------------------------------------------------------- -- | @ParFuture@ captures the class of Par monads which support -- futures. This level of functionality subsumes @par@/@pseq@ and is -- similar to the "Control.Parallel.Strategies.Eval" monad. -- -- A minimal implementation consists of `spawn_` and `get`. -- However, for monads that are also a member of `ParIVar` it is -- typical to simply define `spawn` in terms of `fork`, `new`, and `put`. class Monad m => ParFuture future m | m -> future where -- | Create a potentially-parallel computation, and return a /future/ -- (or /promise/) that can be used to query the result of the forked -- computataion. -- -- > spawn p = do -- > r <- new -- > fork (p >>= put r) -- > return r -- spawn :: NFData a => m a -> m (future a) -- | Like 'spawn', but the result is only head-strict, not fully-strict. spawn_ :: m a -> m (future a) -- | Wait for the result of a future, and then return it. get :: future a -> m a -- | Spawn a pure (rather than monadic) computation. Fully-strict. -- -- > spawnP = spawn . return spawnP :: NFData a => a -> m (future a) -- Default implementations: spawn p = spawn_ (do x <- p; deepseq x (return x)) spawnP a = spawn (return a) -------------------------------------------------------------------------------- -- | @ParIVar@ builds on futures by adding full /anyone-writes, anyone-reads/ IVars. -- These are more expressive but may not be supported by all distributed schedulers. -- -- A minimal implementation consists of `fork`, `put_`, and `new`. class ParFuture ivar m => ParIVar ivar m | m -> ivar where -- | Forks a computation to happen in parallel. The forked -- computation may exchange values with other computations using -- @IVar@s. fork :: m () -> m () -- | creates a new @IVar@ new :: m (ivar a) -- | put a value into a @IVar@. Multiple 'put's to the same @IVar@ -- are not allowed, and result in a runtime error. -- -- 'put' fully evaluates its argument, which therefore must be an -- instance of 'NFData'. The idea is that this forces the work to -- happen when we expect it, rather than being passed to the consumer -- of the @IVar@ and performed later, which often results in less -- parallelism than expected. -- -- Sometimes partial strictness is more appropriate: see 'put_'. -- put :: NFData a => ivar a -> a -> m () put v a = deepseq a (put_ v a) -- | like 'put', but only head-strict rather than fully-strict. put_ :: ivar a -> a -> m () -- Extra API routines that have default implementations: -- | creates a new @IVar@ that contains a value newFull :: NFData a => a -> m (ivar a) newFull a = deepseq a (newFull_ a) -- | creates a new @IVar@ that contains a value (head-strict only) newFull_ :: a -> m (ivar a) newFull_ a = do v <- new -- This is usually inefficient! put_ v a return v -------------------------------------------------------------------------------- -- class ParYieldable ?? -- TODO: I think we should add yield officially: -- Allows other parallel computations to progress. (should not be -- necessary in most cases). -- yield :: m () -------------------------------------------------------------------------------- -- | @ParChan@ provides communication via streams of values between -- computations in a Par monad. Channels in this case are split -- into separate send and receive ports. -- -- The critical thing to know about @Chan@s in @Par@ monads is that -- while the @recv@ method destructively advances the position of -- the consumer's \"cursor\" in the stream, this is only observable -- in the /local/ @Par@ thread. That is, at @fork@ points it is -- necessary to give the child computation a separate set of stream -- cursors so that it observes the same sequences as the parent. class Monad m => ParChan snd rcv m | m -> snd, m -> rcv where -- | Create a new communication channel, with separate send and receive ports. newChan :: m (snd a, rcv a) -- | Receive a message on a channel in a synchronous, blocking manner. recv :: rcv a -> m a -- | Send a message on a channel. This may or may not block. send :: snd a -> a -> m () ---------------------------------------------------------------------------------------------------- -- t1 :: P.Par Int -- If the ParIVar => ParFuture instance exists the following is sufficient: t1 :: (ParFuture v m) => m Int t1 = do x <- spawn (return 3) get x t2 :: (ParIVar v m) => m Int t2 = do x <- new put x "hi" return 3 -- TODO: SPECIALIZE generic routines for the default par monad (and possibly ParRNG)? -- SPECIALISE parMap :: (NFData b) => (a -> b) -> [a] -> Par [b] -- SPECIALISE parMapM :: (NFData b) => (a -> Par b) -> [a] -> Par [b]