在State monad中运行的模拟中，如何减少内存使用量和GC时间，我遇到了一些麻烦。目前我必须使用+RTS -K100M运行已编译的代码以避免堆栈空间溢出，并且GC统计数据非常可怕（见下文）。
以下是代码的相关摘要。完整的，有效的（GHC 7.4.1）代码可以在http://hpaste.org/68527找到。
-- Lone algebraic data type holding the simulation configuration.
data SimConfig = SimConfig {
numDimensions :: !Int -- strict
, numWalkers :: !Int -- strict
, simArray :: IntMap [Double] -- strict spine
, logP :: Seq Double -- strict spine
, logL :: Seq Double -- strict spine
, pairStream :: [(Int, Int)] -- lazy (infinite) list of random vals
, doubleStream :: [Double] -- lazy (infinite) list of random vals
} deriving Show
-- The transition kernel for the simulation.
simKernel :: State SimConfig ()
simKernel = do
config <- get
let arr = simArray config
let n = numWalkers config
let d = numDimensions config
let rstm0 = pairStream config
let rstm1 = doubleStream config
let lp = logP config
let ll = logL config
let (a, b) = head rstm0 -- uses random stream
let z0 = head . map affineTransform $ take 1 rstm1 -- uses random stream
where affineTransform a = 0.5 * (a + 1) ^ 2
let proposal = zipWith (+) r1 r2
where r1 = map (*z0) $ fromJust (IntMap.lookup a arr)
r2 = map (*(1-z0)) $ fromJust (IntMap.lookup b arr)
let logA = if val > 0 then 0 else val
where val = logP_proposal + logL_proposal - (lp `index` (a - 1)) - (ll `index` (a - 1)) + ((fromIntegral n - 1) * log z0)
logP_proposal = logPrior proposal
logL_proposal = logLikelihood proposal
let cVal = (rstm1 !! 1) <= exp logA -- uses random stream
let newConfig = SimConfig { simArray = if cVal
then IntMap.update (\_ -> Just proposal) a arr
else arr
, numWalkers = n
, numDimensions = d
, pairStream = drop 1 rstm0
, doubleStream = drop 2 rstm1
, logP = if cVal
then Seq.update (a - 1) (logPrior proposal) lp
else lp
, logL = if cVal
then Seq.update (a - 1) (logLikelihood proposal) ll
else ll
}
put newConfig
main = do
-- (some stuff omitted)
let sim = logL $ (`execState` initConfig) . replicateM 100000 $ simKernel
print sim
就堆而言，配置文件似乎提示除了System.Random之外，(,)函数是内存的罪魁祸首。我无法直接包含图像，但您可以在此处查看堆配置文件：http://i.imgur.com/5LKxX.png。
我不知道如何进一步减少这些东西的存在。随机变量是在State monad之外生成的（以避免在每次迭代时拆分生成器），并且我相信(,)中simKernel的唯一实例是从lazy中取出一对时出现的列表（pairStream）包含在模拟配置中。
统计数据，包括GC，如下：
1,220,911,360 bytes allocated in the heap
787,192,920 bytes copied during GC
186,821,752 bytes maximum residency (10 sample(s))
1,030,400 bytes maximum slop
449 MB total memory in use (0 MB lost due to fragmentation)
Tot time (elapsed) Avg pause Max pause
Gen 0 2159 colls, 0 par 0.80s 0.81s 0.0004s 0.0283s
Gen 1 10 colls, 0 par 0.96s 1.09s 0.1094s 0.4354s
INIT time 0.00s ( 0.00s elapsed)
MUT time 0.95s ( 0.97s elapsed)
GC time 1.76s ( 1.91s elapsed)
EXIT time 0.00s ( 0.00s elapsed)
Total time 2.72s ( 2.88s elapsed)
%GC time 64.9% (66.2% elapsed)
Alloc rate 1,278,074,521 bytes per MUT second
Productivity 35.1% of total user, 33.1% of total elapsed
同样，我必须提高最大堆栈大小才能运行模拟。我知道在某个地方肯定会有一个大笨蛋......但我无法弄清楚在哪里？
如何在这样的问题中改进堆/堆栈分配和GC？我怎样才能确定thunk可能在哪里积聚？这里State monad的使用是否被误导了？
-
更新：
在使用-fprof-auto进行编译时，我忽略了查看探查器的输出。以下是该输出的主管：
COST CENTRE MODULE no. entries %time %alloc %time %alloc
MAIN MAIN 58 0 0.0 0.0 100.0 100.0
main Main 117 0 0.0 0.0 100.0 100.0
main.randomList Main 147 1 62.0 55.5 62.0 55.5
main.arr Main 142 1 0.0 0.0 0.0 0.0
streamToAssocList Main 143 1 0.0 0.0 0.0 0.0
streamToAssocList.go Main 146 5 0.0 0.0 0.0 0.0
main.pairList Main 137 1 0.0 0.0 9.5 16.5
consPairStream Main 138 1 0.7 0.9 9.5 16.5
consPairStream.ys Main 140 1 4.3 7.8 4.3 7.8
consPairStream.xs Main 139 1 4.5 7.8 4.5 7.8
main.initConfig Main 122 1 0.0 0.0 0.0 0.0
logLikelihood Main 163 0 0.0 0.0 0.0 0.0
logPrior Main 161 5 0.0 0.0 0.0 0.0
main.sim Main 118 1 1.0 2.2 28.6 28.1
simKernel Main 120 0 4.8 5.1 27.6 25.8
我不确定如何准确地解释这一点，但随机双打的懒惰流randomList让我畏缩。我不知道如何改进。
答案 0 :(得分：3)
我用一个工作示例更新了hpaste。看起来匪徒是：
SimConfig字段中的严格注释：simArray，logP和logL data SimConfig = SimConfig {
numDimensions :: !Int -- strict
, numWalkers :: !Int -- strict
, simArray :: !(IntMap [Double]) -- strict spine
, logP :: !(Seq Double) -- strict spine
, logL :: !(Seq Double) -- strict spine
, pairStream :: [(Int, Int)] -- lazy
, doubleStream :: [Double] -- lazy
} deriving Show
newConfig从未在simKernel循环中评估，因为State是懒惰的。另一种选择是使用严格的State monad。
put $! newConfig
execState ... replicateM也构建了thunk。我最初将其替换为foldl'并将execState移到了折叠中，但我认为在replicateM_中交换相同且更易于阅读：
let sim = logL $ execState (replicateM_ epochs simKernel) initConfig
-- sim = logL $ foldl' (const . execState simKernel) initConfig [1..epochs]
mapM .. replicate的一些来电已被replicateM取代。特别值得注意的是consPairList，它可以减少内存使用量。仍然有改进的余地，但最低的悬挂水果涉及不安全的互联网......所以我停了下来。
我不知道输出结果是否符合您的要求：
fromList [-4.287033457733427,-1.8000404912760795,-5.581988678626085,-0.9362372340483293,-5.267791907985331]
但这是统计数据：
268,004,448 bytes allocated in the heap
70,753,952 bytes copied during GC
16,014,224 bytes maximum residency (7 sample(s))
1,372,456 bytes maximum slop
40 MB total memory in use (0 MB lost due to fragmentation)
Tot time (elapsed) Avg pause Max pause
Gen 0 490 colls, 0 par 0.05s 0.05s 0.0001s 0.0012s
Gen 1 7 colls, 0 par 0.04s 0.05s 0.0076s 0.0209s
INIT time 0.00s ( 0.00s elapsed)
MUT time 0.12s ( 0.12s elapsed)
GC time 0.09s ( 0.10s elapsed)
EXIT time 0.00s ( 0.00s elapsed)
Total time 0.21s ( 0.22s elapsed)
%GC time 42.2% (45.1% elapsed)
Alloc rate 2,241,514,569 bytes per MUT second
Productivity 57.8% of total user, 53.7% of total elapsed