我在弄清楚如何减少运行在模拟中的内存使用和 GC 时间时遇到了一些麻烦State
单子。目前我必须运行编译后的代码+RTS -K100M
为了避免堆栈空间溢出,GC 统计数据非常可怕(见下文)。
以下是相关代码片段。完整的工作 (GHC 7.4.1) 代码可以在以下位置找到http://hpaste.org/68527 http://hpaste.org/68527.
-- 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,配置文件似乎暗示System.Random
功能,除了(,)
,是记忆的罪魁祸首。我无法直接包含图像,但您可以在此处查看堆配置文件:https://i.stack.imgur.com/ZMNDA.png https://i.stack.imgur.com/ZMNDA.png.
我不知道如何进一步减少这些东西的存在。随机变量是在外部生成的State
monad(以避免在每次迭代时分割生成器),我相信唯一的实例(,)
inside simKernel
当从惰性列表中取出一对时出现(pairStream
)包含在模拟配置中。
包括GC在内的统计数据如下:
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,我必须增加最大堆栈大小才能运行模拟。我知道某个地方一定有一个大重击……但我不知道在哪里?
在这样的问题中,如何改进堆/栈分配和 GC?我如何识别 thunk 可能在哪里堆积?是使用State
monad 这里被误导了吗?
--
UPDATE:
编译时我忽略了查看探查器的输出-fprof-auto
。这是该输出的头部:
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
我不确定如何准确解释这一点,但是随机双打的惰性流,randomList
,让我皱眉。我不知道如何改进。