Haskell 平行哈斯克尔。限制生产者的税率
在Haskell的并行和并发编程中,Simon Marlow根据以下数据以及一些生产者和消费者提供了一个:Haskell 平行哈斯克尔。限制生产者的税率,haskell,parallel-processing,monads,Haskell,Parallel Processing,Monads,在Haskell的并行和并发编程中,Simon Marlow根据以下数据以及一些生产者和消费者提供了一个: data IList a = Nil | Cons a (IVar (IList a)) type Stream a = IVar (IList a) streamFromList :: NFData a => [a] -> Par (Stream a) streamFromList xs = do var <- new fork $
data IList a
= Nil
| Cons a (IVar (IList a))
type Stream a = IVar (IList a)
streamFromList :: NFData a => [a] -> Par (Stream a)
streamFromList xs = do
var <- new
fork $ loop xs var
return var
where
loop [] var = put var Nil
loop (x:xs) var = do
tail <- new
put var (Cons x tail)
loop xs tail
然而,他并没有完成这种方法:
我将把这个想法的其余部分作为练习留给你自己去尝试。查看是否可以修改streamFromList
、streamFold
和streamMap
以合并Fork
构造函数。区块大小和分叉距离应该是生产者的参数(streamFromList
和streamMap
)
同样的问题,但没有人回答
那么如何限制生产者的比率呢?重要的部分在于
循环功能:
loop [] var = put var Nil
loop (x:xs) var = do
tail <- new
put var (Cons x tail)
loop xs tail
在每次迭代中,分叉距离都会减小。当叉距离为零时,我们需要做什么?我们提供了一个Fork op t
,其中op
继续生成列表:
loop 0 c (x:xs) var = do
tail <- new
let op = loop c xs tail
put var (Fork op (Cons x tail))
现在,为了使用它,我们需要更改streamFold
中的大小写
:
streamFold :: (a -> b -> a) -> a -> Stream b -> Par a
streamFold fn acc instrm = acc `seq` do
ilst <- get instrm
case ilst of
Cons h t -> streamFold fn (fn acc h) t
Fork p (Cons h t) -> -- see below
_ -> return acc
streamMap
类似。只有在这种情况下,才能在循环中再次使用其他参数,如streamFromList
我认为以下是一个有效的实现
{-# LANGUAGE BangPatterns #-}
import Control.Monad.Par (IVar, Par, fork, get, new, put, put_, runPar)
import Control.DeepSeq (NFData, rnf)
data IList a
= Nil
| Cons a (IVar (IList a))
| Fork (Par ()) (IVar (IList a))
instance NFData a => NFData (IList a) where
rnf Nil = ()
rnf (Cons a b) = rnf a `seq` rnf b
rnf (Fork a b) = rnf (runPar a) `seq` rnf b
type Stream a = IVar (IList a)
main :: IO ()
main = print $ sum (pipeline [1 .. 10000])
pipeline :: [Int] -> [Int]
pipeline list = runPar $ do
strm <- streamFromList list 100 200
xs <- streamFold (\x y -> (y : x)) [] strm
return (reverse xs)
streamFromList :: NFData a => [a] -> Int -> Int -> Par (Stream a)
streamFromList xs k n = do
var <- new
fork $ loop xs var k
return var
where
loop [] var _ = put var Nil
loop xs var 0 = do
var' <- new
put_ var (Fork (loop xs var' n) var')
loop (x:xs) var i = do
tail <- new
put var (Cons x tail)
loop xs tail (i - 1)
streamFold :: (a -> b -> a) -> a -> Stream b -> Par a
streamFold fn !acc strm = do
ilst <- get strm
case ilst of
Nil -> return acc
Cons h t -> streamFold fn (fn acc h) t
Fork p s -> fork p >> streamFold fn acc s
{-#语言模式}
进口控制,MaNAD.PAR(IVAR,PAR,FACK,GET,NEW,PUT,PUTIG,RUNPAR)
导入控制.DeepSeq(NFData,rnf)
数据列表a
=零
|Cons a(IVar(ILST a))
|Fork(Par())(IVar(IList a))
实例NFData=>NFData(IList a),其中
rnf Nil=()
rnf(Cons a b)=rnf a`seq`rnf b
rnf(Fork a b)=rnf(runPar a)`seq`rnf b
类型流a=IVar(IList a)
main::IO()
main=打印$sum(管道[1..10000])
管道::[Int]->[Int]
管道列表=runPar$do
STRM[A] -INT> INT> PAR(流A)
streamFromList xs k n=do
Value:ValueNoDATA实例定义为<代码> For < /代码>构造函数是:<代码> RNF(OrthyA)= RNF A < /C> >即忽略<代码> PAR(<)/Cord>字段> @ USE5402:<代码> NealPar A= PAR{RunCONT::(A->Trror)> Trace} /Cult>,因此操作是一个简单的函数。因此,受函数的NFData实例(NFData(a->b)
)的启发,我将使用rnf(Fork op a)=seq op$rnf a
let op=loop c xs tail
streamFromList :: NFData a => Int -> Int -> [a] -> Par (Stream a)
streamFromList f c xs = do
var <- new
fork $ loop f c xs var
return var
streamFold :: (a -> b -> a) -> a -> Stream b -> Par a
streamFold fn acc instrm = acc `seq` do
ilst <- get instrm
case ilst of
Cons h t -> streamFold fn (fn acc h) t
Fork p (Cons h t) -> -- see below
_ -> return acc
Fork p (Cons h t) -> fork p >> streamFold fn (fn acc h) t
{-# LANGUAGE BangPatterns #-}
import Control.Monad.Par (IVar, Par, fork, get, new, put, put_, runPar)
import Control.DeepSeq (NFData, rnf)
data IList a
= Nil
| Cons a (IVar (IList a))
| Fork (Par ()) (IVar (IList a))
instance NFData a => NFData (IList a) where
rnf Nil = ()
rnf (Cons a b) = rnf a `seq` rnf b
rnf (Fork a b) = rnf (runPar a) `seq` rnf b
type Stream a = IVar (IList a)
main :: IO ()
main = print $ sum (pipeline [1 .. 10000])
pipeline :: [Int] -> [Int]
pipeline list = runPar $ do
strm <- streamFromList list 100 200
xs <- streamFold (\x y -> (y : x)) [] strm
return (reverse xs)
streamFromList :: NFData a => [a] -> Int -> Int -> Par (Stream a)
streamFromList xs k n = do
var <- new
fork $ loop xs var k
return var
where
loop [] var _ = put var Nil
loop xs var 0 = do
var' <- new
put_ var (Fork (loop xs var' n) var')
loop (x:xs) var i = do
tail <- new
put var (Cons x tail)
loop xs tail (i - 1)
streamFold :: (a -> b -> a) -> a -> Stream b -> Par a
streamFold fn !acc strm = do
ilst <- get strm
case ilst of
Nil -> return acc
Cons h t -> streamFold fn (fn acc h) t
Fork p s -> fork p >> streamFold fn acc s