{-# LANGUAGE ScopedTypeVariables #-} -- | Parallelism combinators with explicit thread-pool creation and -- passing. -- -- The most basic example of usage is: -- -- > main = withPool 2 $ \pool -> parallel_ pool [putStrLn "Echo", putStrLn " in parallel"] -- -- Make sure that you compile with @-threaded@ and supply @+RTS -N2 -RTS@ -- to the generated Haskell executable, or you won't get any parallelism. -- -- The "Control.Concurrent.ParallelIO.Global" module is implemented -- on top of this one by maintaining a shared global thread pool -- with one thread per capability. module Control.Concurrent.ParallelIO.Local ( WorkItem, WorkQueue, Pool, withPool, startPool, stopPool, enqueueOnPool, extraWorkerWhileBlocked, spawnPoolWorkerFor, killPoolWorkerFor, parallel_, parallel, parallelInterleaved ) where import qualified Control.Concurrent.ParallelIO.ConcurrentSet as CS import Control.Concurrent import Control.Exception.Extensible as E import Control.Monad import System.IO -- | Type of work items you can put onto the queue. The 'Bool' -- returned from the 'IO' action specifies whether the invoking -- thread should terminate itself immediately. type WorkItem = IO Bool -- | A 'WorkQueue' is used to communicate 'WorkItem's to the workers. type WorkQueue = CS.ConcurrentSet WorkItem -- | The type of thread pools used by 'ParallelIO'. -- The best way to construct one of these is using 'withPool'. data Pool = Pool { pool_threadcount :: Int, pool_spawnedby :: ThreadId, pool_queue :: WorkQueue } -- | A slightly unsafe way to construct a pool. Make a pool from the maximum -- number of threads you wish it to execute (including the main thread -- in the count). -- -- If you use this variant then ensure that you insert a call to 'stopPool' -- somewhere in your program after all users of that pool have finished. -- -- A better alternative is to see if you can use the 'withPool' variant. startPool :: Int -> IO Pool startPool threadcount = do threadId <- myThreadId queue <- CS.new let pool = Pool { pool_threadcount = threadcount, pool_spawnedby = threadId, pool_queue = queue } replicateM_ (threadcount - 1) (spawnPoolWorkerFor pool) return pool -- | Clean up a thread pool. If you don't call this then no one holds the queue, -- the queue gets GC'd, the threads find themselves blocked indefinitely, and you get -- exceptions. -- -- This cleanly shuts down the threads so the queue isn't important and you don't get -- exceptions. -- -- Only call this /after/ all users of the pool have completed, or your program may -- block indefinitely. stopPool :: Pool -> IO () stopPool pool = replicateM_ (pool_threadcount pool - 1) $ killPoolWorkerFor pool -- | A safe wrapper around 'startPool' and 'stopPool'. Executes an 'IO' action using a newly-created -- pool with the specified number of threads and cleans it up at the end. withPool :: Int -> (Pool -> IO a) -> IO a withPool threadcount = E.bracket (startPool threadcount) stopPool -- | Internal method for scheduling work on a pool. enqueueOnPool :: Pool -> WorkItem -> IO () enqueueOnPool pool = CS.insert (pool_queue pool) -- | Wrap any IO action used from your worker threads that may block with this method: -- it temporarily spawns another worker thread to make up for the loss of the old blocked -- worker. -- -- This is particularly important if the unblocking is dependent on worker threads actually doing -- work. If you have this situation, and you don't use this method to wrap blocking actions, then -- you may get a deadlock if all your worker threads get blocked on work that they assume will be -- done by other worker threads. extraWorkerWhileBlocked :: Pool -> IO () -> IO () extraWorkerWhileBlocked pool wait = E.bracket (spawnPoolWorkerFor pool) (\() -> killPoolWorkerFor pool) (\() -> wait) -- | Internal method for adding extra unblocked threads to a pool if one is going to be -- temporarily blocked. spawnPoolWorkerFor :: Pool -> IO () spawnPoolWorkerFor pool = do _ <- forkIO $ workerLoop `E.catch` \(e :: E.SomeException) -> do hPutStrLn stderr $ "Exception on thread: " ++ show e throwTo (pool_spawnedby pool) $ ErrorCall $ "Control.Concurrent.ParallelIO: parallel thread died.\n" ++ show e return () where workerLoop :: IO () workerLoop = do kill <- join $ CS.delete (pool_queue pool) unless kill workerLoop -- | Internal method for removing threads from a pool after we become unblocked. killPoolWorkerFor :: Pool -> IO () killPoolWorkerFor pool = enqueueOnPool pool $ return True -- | Run the list of computations in parallel. -- -- Has the following properties: -- -- 1. Never creates more or less unblocked threads than are specified to -- live in the pool. NB: this count includes the thread executing 'parallel_'. -- This should minimize contention and hence pre-emption, while also preventing -- starvation. -- -- 2. On return all actions have been performed. -- -- 3. The function returns in a timely manner as soon as all actions have -- been performed. -- -- 4. The above properties are true even if 'parallel_' is used by an -- action which is itself being executed by 'parallel_'. parallel_ :: Pool -> [IO a] -> IO () parallel_ _ [] = return () parallel_ pool xs | pool_threadcount pool <= 1 = sequence_ xs parallel_ _ [x] = x >> return () parallel_ pool (x1:xs) = do count <- newMVar $ length xs pause <- newEmptyMVar forM_ xs $ \x -> enqueueOnPool pool $ do _ <- x modifyMVar count $ \i -> do let i' = i - 1 kill = i' == 0 when kill $ putMVar pause () return (i', kill) _ <- x1 -- NB: it is safe to spawn a worker because at least one will die - the -- length of xs must be strictly greater than 0. spawnPoolWorkerFor pool takeMVar pause -- | Run the list of computations in parallel, returning the results in the -- same order as the corresponding actions. -- -- Has the following properties: -- -- 1. Never creates more or less unblocked threads than are specified to -- live in the pool. NB: this count includes the thread executing 'parallel_'. -- This should minimize contention and hence pre-emption, while also preventing -- starvation. -- -- 2. On return all actions have been performed. -- -- 3. The function returns in a timely manner as soon as all actions have -- been performed. -- -- 4. The above properties are true even if 'parallel' is used by an -- action which is itself being executed by 'parallel'. parallel :: Pool -> [IO a] -> IO [a] parallel _ [] = return [] parallel pool xs | pool_threadcount pool <= 1 = sequence xs parallel _ [x] = fmap return x parallel pool (x1:xs) = do count <- newMVar $ length xs resultvars <- forM xs $ \x -> do resultvar <- newEmptyMVar enqueueOnPool pool $ do x >>= putMVar resultvar modifyMVar count $ \i -> let i' = i - 1 in return (i', i' == 0) return resultvar result1 <- x1 -- NB: it is safe to spawn a worker because at least one will die - the -- length of xs must be strictly greater than 0. spawnPoolWorkerFor pool fmap (result1:) $ mapM takeMVar resultvars -- | Run the list of computations in parallel, returning the results in the -- approximate order of completion. -- -- Has the following properties: -- -- 1. Never creates more or less unblocked threads than are specified to -- live in the pool. NB: this count includes the thread executing 'parallel_'. -- This should minimize contention and hence pre-emption, while also preventing -- starvation. -- -- 2. On return all actions have been performed. -- -- 3. The result of running actions appear in the list in undefined order, but which -- is likely to be very similar to the order of completion. -- -- 3. The above properties are true even if 'parallelInterleaved' is used by an -- action which is itself being executed by 'parallelInterleaved'. parallelInterleaved :: Pool -> [IO a] -> IO [a] parallelInterleaved _ [] = return [] parallelInterleaved pool xs | pool_threadcount pool <= 1 = sequence xs parallelInterleaved _ [x] = fmap return x parallelInterleaved pool (x1:xs) = do let thecount = length xs count <- newMVar $ thecount resultschan <- newChan forM_ xs $ \x -> do enqueueOnPool pool $ do x >>= writeChan resultschan modifyMVar count $ \i -> let i' = i - 1 in return (i', i' == 0) result1 <- x1 -- NB: it is safe to spawn a worker because at least one will die - the -- length of xs must be strictly greater than 0. spawnPoolWorkerFor pool results <- fmap ((result1:) . take thecount) $ getChanContents resultschan return $ seqList results seqList :: [a] -> [a] seqList [] = [] seqList (x:xs) = x `seq` xs' `seq` (x:xs') where xs' = seqList xs -- An alternative implementation of parallel_ might: -- -- 1. Avoid spawning an additional thread -- -- 2. Remove the need for the pause mvar -- -- By having the thread invoking parallel_ also pull stuff from the -- work pool, and poll the count variable after every item to see -- if everything has been processed (which would cause it to stop -- processing work pool items). However: -- -- 1. This is less timely, because the main thread might get stuck -- processing a big work item not related to the current parallel_ -- invocation, and wouldn't poll (and return) until that was done. -- -- 2. It actually performs a bit less well too - or at least it did on -- my benchmark with lots of cheap actions, where polling would -- be relatively frequent. Went from 8.8s to 9.1s. -- -- For posterity, the implementation was: -- -- @ -- parallel_ :: [IO a] -> IO () -- parallel_ xs | numCapabilities <= 1 = sequence_ xs -- parallel_ [] = return () -- parallel_ [x] = x >> return () -- parallel_ (x1:xs) = do -- count <- newMVar $ length xs -- forM_ xs $ \x -> -- enqueueOnPool globalPool $ do -- x -- modifyMVar_ count $ \i -> return (i - 1) -- return False -- x1 -- done <- fmap (== 0) $ readMVar count -- unless done $ myWorkerLoop globalPool count -- -- myWorkerLoop :: Pool -> MVar Int -> IO () -- myWorkerLoop pool count = do -- kill <- join $ readChan (pool_queue pool) -- done <- fmap (== 0) $ readMVar count -- unless (kill || done) (myWorkerLoop pool count) -- @ -- -- NB: in this scheme, kill is only True when the program is exiting.