Revision as of 01:19, 8 September 2008
This benchmark measure how effectively you can schedule threads. A parallel version partitions the ring of threads over the cpus equally, and prevents redundant migrations.
1.1 Current entry
Compile flags: ghc -O2 -threaded A.hs --make Runtime flags: +RTS -N4 -qm -qw
-- The Great Computer Language Shootout -- http://shootout.alioth.debian.org/ -- Contributed by Jed Brown with improvements by Spencer Janssen and Don Stewart -- -- 503 threads are created with forkOnIO, with each thread -- creating one synchronised mutable variable (MVar) shared with the -- next thread in the ring. The last thread created returns an MVar to -- share with the first thread. Each thread reads from the MVar to its -- left, and writes to the MVar to its right. -- -- Each thread then waits on a token to be passed from its neighbour. -- Tokens are then passed around the threads via the MVar chain N times, -- and the thread id of the final thread to receive a token is printed. -- -- More information on Haskell concurrency and parallelism: -- http://www.haskell.org/ghc/dist/current/docs/users_guide/lang-parallel.html -- -- SMP parallelisation strategy is to partition the ring equally over each capability. -- import Control.Monad import Control.Concurrent import System.Environment import GHC.Conc ring = 503 new l i = do r <- newEmptyMVar forkOnIO n (thread i l r) return r where n | i < 125 = 0 | i < 250 = 1 | i < 375 = 2 | otherwise = 3 thread :: Int -> MVar Int -> MVar Int -> IO () thread i l r = go where go = do m <- takeMVar l when (m == 1) (print i) putMVar r $! m - 1 when (m > 0) go main = do a <- newMVar . read . head =<< getArgs z <- foldM new a [2..ring] thread 1 z a