source code
-- The Computer Language Benchmarks Game
-- https://salsa.debian.org/benchmarksgame-team/benchmarksgame/
--
-- Contributed by Jaro Reinders
module Main where
import Data.Word
import qualified Data.Vector.Unboxed.Mutable as M
import qualified Data.Vector.Unboxed as V
import qualified Data.Vector.Storable.Mutable as S
import qualified Data.ByteString as B
import qualified Data.ByteString.Lazy.Char8 as BL
import Control.Concurrent
import Control.Monad
import System.IO
import System.IO.Unsafe (unsafePerformIO)
import Data.Char
import Data.Maybe
import Data.IORef
import System.Environment
import Data.Int
import Data.List
-- First some constants
lineLength :: Int
lineLength = 60
workers :: Int
workers = 4
ia, ic, im :: Word32
ia = 3877
ic = 29573
im = 139968
alu :: B.ByteString
alu =
"GGCCGGGCGCGGTGGCTCACGCCTGTAATCCCAGCACTTTGGGAGGCCGAGGCGGGCGGATCACCTGAGGTCAGG\
\AGTTCGAGACCAGCCTGGCCAACATGGTGAAACCCCGTCTCTACTAAAAATACAAAAATTAGCCGGGCGTGGTGG\
\CGCGCGCCTGTAATCCCAGCTACTCGGGAGGCTGAGGCAGGAGAATCGCTTGAACCCGGGAGGCGGAGGTTGCAG\
\TGAGCCGAGATCGCGCCACTGCACTCCAGCCTGGGCGACAGAGCGAGACTCCGTCTCAAAAA"
-- An mvar that is used to ensure that no two threads will print to stdout at
-- the same time.
output :: MVar ()
output = unsafePerformIO (newMVar ())
-- Make sure that the program does not exit before all child processes are
-- done.
children :: MVar [MVar ()]
children = unsafePerformIO (newMVar [])
waitForChildren :: IO ()
waitForChildren = do
cs <- takeMVar children
case cs of
[] -> putMVar children []
m:ms -> do
putMVar children ms
takeMVar m
waitForChildren
forkChild :: IO () -> IO ThreadId
forkChild io = do
mvar <- newEmptyMVar
childs <- takeMVar children
putMVar children (mvar:childs)
forkFinally io (\_ -> putMVar mvar ())
-- Firstly the repeated fasta
-- Helper function that cuts a lazy bytestring into a list of equal size
-- chunks.
toChunksOf :: Int64 -> BL.ByteString -> [BL.ByteString]
toChunksOf !n = unfoldr (Just . BL.splitAt n)
-- Find the smallest multiple of the alu that aligns with the line length.
-- Then print that repeatedly. Finally, print the remainder.
printRepeatedFasta :: Int -> Int -> B.ByteString -> IO ()
printRepeatedFasta !n !l !s = do
replicateM_ q (B.putStr buffer)
B.putStr $ B.take (r + r `quot` lineLength) buffer
B.putStr "\n"
where
m = l * gcd l lineLength
(q,r) = n `quotRem` (lineLength * m)
buffer = BL.toStrict
$ BL.unlines
$ take m
$ toChunksOf (fromIntegral lineLength)
$ BL.cycle
$ BL.fromStrict s
-- Secondly the random fasta
-- fill a vector with pseudorandom values from the LCG.
genSeeds :: Word32 -> M.IOVector Word32 -> Word32 -> IO Word32
genSeeds !bufferSize !v !s = go 0 s where
go :: Word32 -> Word32 -> IO Word32
go !n !s
| n < bufferSize = do
M.unsafeWrite v (fromIntegral n) s'
go (n + 1) s'
| otherwise = return s
where
-- This is the LCG formula
!s' = (ia * s + ic) `rem` im
-- The worker is designed to run in a separate thread. It first generates a
-- block of random values, then it consumes that block. This is done repeatedly
-- until no more characters need to be generated.
worker
:: Int
-> V.Vector Word32
-> V.Vector Word8
-> MVar (Word32, MVar ())
-> IORef Int
-> IO ()
worker !bufferSize !p0 !p1 !mvar !ref = do
m <- M.new bufferSize
-- We freeze it unsafely here, but we expect it to be changed in the loop.
v <- V.unsafeFreeze m
s <- S.new (bufferSize + bufferSize `quot` lineLength)
let
loop = do
-- Find out how many characters still need to be done.
n <- atomicModifyIORef' ref $ \x ->
if x > 0
then (max 0 (x - bufferSize), min x bufferSize)
else (0, 0)
when (n > 0) $ do
next <- newEmptyMVar
(rnd, prev) <- takeMVar mvar
rnd' <- genSeeds (fromIntegral n) m rnd
putMVar mvar (rnd', next)
consume n p0 p1 s v prev next
loop
loop
-- Do the cumulative probability sampling and print the resulting string.
-- It turns out that using two separate vectors for the lookup table is faster.
consume
:: Int
-> V.Vector Word32
-> V.Vector Word8
-> S.IOVector Word8
-> V.Vector Word32
-> MVar ()
-> MVar ()
-> IO ()
consume !bufferSize !p0 !p1 !s !v !prev !next = do
loop lineLength 0 0
takeMVar prev
S.unsafeWith s $ \ptr ->
hPutBuf stdout ptr (bufferSize + bufferSize `quot` lineLength)
putMVar next ()
where
loop :: Int -> Int -> Int -> IO ()
loop 0 !si !vi = S.unsafeWrite s si 10 *> loop lineLength (si + 1) vi
loop !l !si !vi
| vi < bufferSize = do
S.unsafeWrite s si (lookupCumul (V.unsafeIndex v (fromIntegral vi)))
loop (l - 1) (si + 1) (vi + 1)
| otherwise = return ()
lookupCumul !c = V.unsafeIndex p1 (fromJust (V.findIndex (c <=) p0))
-- Convert a list of characters with probabilities to a cumulative lookup
-- table.
cumulativeProbabilities :: [(Char, Float)] -> V.Vector (Word32, Word8)
cumulativeProbabilities = V.unfoldr uncons . (0,) where
uncons (_ , []) = Nothing
uncons (prev, ((c,p):xs)) = let p' = p + prev in Just
((floor (fromIntegral im * p'), fromIntegral (ord c)), (p', xs))
printRandomFasta
:: V.Vector Word32
-> V.Vector Word8
-> Int
-> Word32
-> IO Word32
printRandomFasta !p0 !p1 !n !s = do
ref <- newIORef n
prev <- newMVar ()
var <- newMVar (s, prev)
replicateM_ workers (forkChild (worker bufferSize p0 p1 var ref))
waitForChildren
when (n `rem` lineLength /= 0) (putStrLn "")
fst <$> takeMVar var
where
bufferSize = (max (n `quot` (100 * lineLength)) 100) * lineLength
main :: IO ()
main = do
n <- readIO . head =<< getArgs
let
p0 = cumulativeProbabilities
[('a', 0.27), ('c', 0.12), ('g', 0.12), ('t', 0.27), ('B', 0.02),
('D', 0.02), ('H', 0.02), ('K', 0.02), ('M', 0.02), ('N', 0.02),
('R', 0.02), ('S', 0.02), ('V', 0.02), ('W', 0.02), ('Y', 0.02)]
p00 = V.map fst p0
p01 = V.map snd p0
let
p1 = cumulativeProbabilities
[('a', 0.3029549426680), ('c', 0.1979883004921),
('g', 0.1975473066391), ('t', 0.3015094502008)]
p10 = V.map fst p1
p11 = V.map snd p1
putStrLn ">ONE Homo sapiens alu"
printRepeatedFasta (2 * n) (B.length alu) alu
putStrLn ">TWO IUB ambiguity codes"
s' <- printRandomFasta p00 p01 (3 * n) 42
putStrLn ">THREE Homo sapiens frequency"
printRandomFasta p10 p11 (5 * n) s'
return ()