Fatal编程技术网
  • performance/
  • Performance 从ghci和shell运行的编译加速代码的性能差异

Performance 从ghci和shell运行的编译加速代码的性能差异

performance haskell

Performance 从ghci和shell运行的编译加速代码的性能差异,performance,haskell,profiling,ghci,accelerate-haskell,Performance,Haskell,Profiling,Ghci,Accelerate Haskell,问题 您好，我正在使用accelerate库创建一个应用程序，允许用户以交互方式调用处理图像的函数，这就是我基于ghc api并使用ghc api扩展ghci的原因 问题在于，当从shell运行编译后的可执行文件时，计算在100ms（略小于80）的时间内完成，而在ghci中运行相同的编译代码则需要100ms（平均略大于140）才能完成 $ ghc -O2 Main.hs -o main -threaded [1 of 1] Compiling Main ( Main.hs

问题

您好，我正在使用accelerate库创建一个应用程序，允许用户以交互方式调用处理图像的函数，这就是我基于ghc api并使用ghc api扩展ghci的原因

问题在于，当从shell运行编译后的可执行文件时，计算在100ms（略小于80）的时间内完成，而在ghci中运行相同的编译代码则需要100ms（平均略大于140）才能完成

$ ghc -O2 Main.hs -o main -threaded
[1 of 1] Compiling Main             ( Main.hs, Main.o )
Linking main ...
$ ./main
Array (Z) [1000001.0]
0.092906s
资源

$ ghc -O2 Main.hs -c -dynamic
$ ghci Main
ghci> main
Array (Z) [1000001.0]
0.258224s
示例代码+执行日志：

说明

$ ghc -O2 -dynamic -c -threaded Main.hs && ghci 
GHCi, version 7.8.3: http://www.haskell.org/ghc/  :? for help
…
Loading package ghc-prim ... linking ... done.
Loading package integer-gmp ... linking ... done.
Loading package base ... linking ... done.
Ok, modules loaded: Main.
Prelude Main> Loading package transformers-0.3.0.0 ... linking ... done.
…
Loading package array-0.5.0.0 ... linking ... done.
(...)
Loading package accelerate-cuda-0.15.0.0 ... linking ... done.
>>>>> run
>>>>> runAsyncIn.execute
>>>>>  runAsyncIn.seq ctx
<<<<<  runAsyncIn.seq ctx: 4.1609e-2 CPU  0.041493s TOTAL
>>>>>  runAsyncIn.seq a
<<<<<  runAsyncIn.seq a: 1.0e-6 CPU  0.000001s TOTAL
>>>>>  runAsyncIn.seq acc
>>>>>   convertAccWith True
<<<<<   convertAccWith: 0.0 CPU  0.000017s TOTAL
<<<<<  runAsyncIn.seq acc: 2.68e-4 CPU  0.000219s TOTAL
>>>>>  evalCUDA
>>>>>   push
<<<<<   push: 0.0 CPU  0.000002s TOTAL
>>>>>   evalStateT
>>>>>    runAsyncIn.compileAcc
>>>>>     compileOpenAcc
>>>>>      compileOpenAcc.traveuseAcc.Alet
>>>>>      compileOpenAcc.traveuseAcc.Use
>>>>>       compileOpenAcc.traveuseAcc.use3
>>>>>       compileOpenAcc.traveuseAcc.use1
<<<<<       compileOpenAcc.traveuseAcc.use1: 0.0 CPU  0.000001s TOTAL
>>>>>       compileOpenAcc.traveuseAcc.use2
>>>>>        compileOpenAcc.traveuseAcc.seq arr
<<<<<        compileOpenAcc.traveuseAcc.seq arr: 0.105716 CPU  0.105501s TOTAL
>>>>>        useArrayAsync
<<<<<        useArrayAsync: 1.234e-3 CPU  0.001505s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use2: 0.108012 CPU  0.108015s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use3: 0.108539 CPU  0.108663s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Use: 0.109375 CPU  0.109005s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Fold1
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Fold1: 2.059e-3 CPU  0.002384s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Alet: 0.111434 CPU  0.112034s TOTAL
<<<<<     compileOpenAcc: 0.11197 CPU  0.112615s TOTAL
<<<<<    runAsyncIn.compileAcc: 0.11197 CPU  0.112833s TOTAL
>>>>>    runAsyncIn.dumpStats
<<<<<    runAsyncIn.dumpStats: 2.0e-6 CPU  0.000001s TOTAL
>>>>>    runAsyncIn.executeAcc
>>>>>     executeAcc
<<<<<     executeAcc: 8.96e-4 CPU  0.00049s TOTAL
<<<<<    runAsyncIn.executeAcc: 9.36e-4 CPU  0.0007s TOTAL
>>>>>    runAsyncIn.collect
<<<<<    runAsyncIn.collect: 0.0 CPU  0.000027s TOTAL
<<<<<   evalStateT: 0.114156 CPU  0.115327s TOTAL
>>>>>   pop
<<<<<   pop: 0.0 CPU  0.000002s TOTAL
>>>>>   performGC
<<<<<   performGC: 5.7246e-2 CPU  0.057814s TOTAL
<<<<<  evalCUDA: 0.17295 CPU  0.173943s TOTAL
<<<<< runAsyncIn.execute: 0.215475 CPU  0.216563s TOTAL
<<<<< run: 0.215523 CPU  0.216771s TOTAL
Array (Z) [1000001.0]
0.217148s
Prelude Main> Leaving GHCi.

$ ghc -O2 -threaded Main.hs && ./Main
[1 of 1] Compiling Main             ( Main.hs, Main.o )
Linking Main ...
>>>>> run
>>>>> runAsyncIn.execute
>>>>>  runAsyncIn.seq ctx
<<<<<  runAsyncIn.seq ctx: 4.0639e-2 CPU  0.041498s TOTAL
>>>>>  runAsyncIn.seq a
<<<<<  runAsyncIn.seq a: 1.0e-6 CPU  0.000001s TOTAL
>>>>>  runAsyncIn.seq acc
>>>>>   convertAccWith True
<<<<<   convertAccWith: 1.2e-5 CPU  0.000005s TOTAL
<<<<<  runAsyncIn.seq acc: 1.15e-4 CPU  0.000061s TOTAL
>>>>>  evalCUDA
>>>>>   push
<<<<<   push: 2.0e-6 CPU  0.000002s TOTAL
>>>>>   evalStateT
>>>>>    runAsyncIn.compileAcc
>>>>>     compileOpenAcc
>>>>>      compileOpenAcc.traveuseAcc.Alet
>>>>>      compileOpenAcc.traveuseAcc.Use
>>>>>       compileOpenAcc.traveuseAcc.use3
>>>>>       compileOpenAcc.traveuseAcc.use1
<<<<<       compileOpenAcc.traveuseAcc.use1: 0.0 CPU  0.000001s TOTAL
>>>>>       compileOpenAcc.traveuseAcc.use2
>>>>>        compileOpenAcc.traveuseAcc.seq arr
<<<<<        compileOpenAcc.traveuseAcc.seq arr: 3.6651e-2 CPU  0.03712s TOTAL
>>>>>        useArrayAsync
<<<<<        useArrayAsync: 1.427e-3 CPU  0.001427s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use2: 3.8776e-2 CPU  0.039152s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use3: 3.8794e-2 CPU  0.039207s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Use: 3.8808e-2 CPU  0.03923s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Fold1
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 2.0e-6 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 2.0e-6 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Fold1: 1.342e-3 CPU  0.001284s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Alet: 4.0197e-2 CPU  0.040578s TOTAL
<<<<<     compileOpenAcc: 4.0248e-2 CPU  0.040895s TOTAL
<<<<<    runAsyncIn.compileAcc: 4.0834e-2 CPU  0.04103s TOTAL
>>>>>    runAsyncIn.dumpStats
<<<<<    runAsyncIn.dumpStats: 0.0 CPU  0s TOTAL
>>>>>    runAsyncIn.executeAcc
>>>>>     executeAcc
<<<<<     executeAcc: 2.87e-4 CPU  0.000403s TOTAL
<<<<<    runAsyncIn.executeAcc: 2.87e-4 CPU  0.000488s TOTAL
>>>>>    runAsyncIn.collect
<<<<<    runAsyncIn.collect: 9.2e-5 CPU  0.000049s TOTAL
<<<<<   evalStateT: 4.1213e-2 CPU  0.041739s TOTAL
>>>>>   pop
<<<<<   pop: 0.0 CPU  0.000002s TOTAL
>>>>>   performGC
<<<<<   performGC: 9.41e-4 CPU  0.000861s TOTAL
<<<<<  evalCUDA: 4.3308e-2 CPU  0.042893s TOTAL
<<<<< runAsyncIn.execute: 8.5154e-2 CPU  0.084815s TOTAL
<<<<< run: 8.5372e-2 CPU  0.085035s TOTAL
Array (Z) [1000001.0]
0.085169s
首先：测试是在编译CUDA内核之后运行的（编译本身增加了2秒，但事实并非如此）

从shell运行编译后的可执行文件时，计算在10毫秒内完成。（
shell第一次运行
和
第二次shell运行
传递了不同的参数，以确保数据没有缓存到任何地方）

当试图从ghci运行相同的代码并处理输入数据时，计算需要超过100毫秒。我知道解释代码比编译代码慢，但我在ghci会话中加载相同的编译代码，并调用相同的顶级绑定（
packedFunction
）。我已经显式地键入它以确保它是专门化的（与使用专门化的pragma的结果相同）

但是，如果我在ghci中运行
main
函数（即使在连续调用之间使用
：set args
更改输入数据），计算所需时间也不到10毫秒

使用
ghc-o Main.hs-O2-dynamic-threaded编译
Main.hs

我想知道开销是从哪里来的。有人对为什么会发生这种情况有什么建议吗



示例的简化版本由以下人员发布：

但当我预编译它并在解释器中运行时，需要0,25秒


$ ghc -O2 Main.hs -c -dynamic
$ ghci Main
ghci> main
Array (Z) [1000001.0]
0.258224s



我调查了
accelerate
和
accelerate cuda
，并在ghci下和编译优化版本中放置了一些调试代码来测量时间

结果如下，您可以看到堆栈跟踪和执行时间

ghci运行


$ ghc -O2 -dynamic -c -threaded Main.hs && ghci 
GHCi, version 7.8.3: http://www.haskell.org/ghc/  :? for help
…
Loading package ghc-prim ... linking ... done.
Loading package integer-gmp ... linking ... done.
Loading package base ... linking ... done.
Ok, modules loaded: Main.
Prelude Main> Loading package transformers-0.3.0.0 ... linking ... done.
…
Loading package array-0.5.0.0 ... linking ... done.
(...)
Loading package accelerate-cuda-0.15.0.0 ... linking ... done.
>>>>> run
>>>>> runAsyncIn.execute
>>>>>  runAsyncIn.seq ctx
<<<<<  runAsyncIn.seq ctx: 4.1609e-2 CPU  0.041493s TOTAL
>>>>>  runAsyncIn.seq a
<<<<<  runAsyncIn.seq a: 1.0e-6 CPU  0.000001s TOTAL
>>>>>  runAsyncIn.seq acc
>>>>>   convertAccWith True
<<<<<   convertAccWith: 0.0 CPU  0.000017s TOTAL
<<<<<  runAsyncIn.seq acc: 2.68e-4 CPU  0.000219s TOTAL
>>>>>  evalCUDA
>>>>>   push
<<<<<   push: 0.0 CPU  0.000002s TOTAL
>>>>>   evalStateT
>>>>>    runAsyncIn.compileAcc
>>>>>     compileOpenAcc
>>>>>      compileOpenAcc.traveuseAcc.Alet
>>>>>      compileOpenAcc.traveuseAcc.Use
>>>>>       compileOpenAcc.traveuseAcc.use3
>>>>>       compileOpenAcc.traveuseAcc.use1
<<<<<       compileOpenAcc.traveuseAcc.use1: 0.0 CPU  0.000001s TOTAL
>>>>>       compileOpenAcc.traveuseAcc.use2
>>>>>        compileOpenAcc.traveuseAcc.seq arr
<<<<<        compileOpenAcc.traveuseAcc.seq arr: 0.105716 CPU  0.105501s TOTAL
>>>>>        useArrayAsync
<<<<<        useArrayAsync: 1.234e-3 CPU  0.001505s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use2: 0.108012 CPU  0.108015s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use3: 0.108539 CPU  0.108663s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Use: 0.109375 CPU  0.109005s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Fold1
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Fold1: 2.059e-3 CPU  0.002384s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Alet: 0.111434 CPU  0.112034s TOTAL
<<<<<     compileOpenAcc: 0.11197 CPU  0.112615s TOTAL
<<<<<    runAsyncIn.compileAcc: 0.11197 CPU  0.112833s TOTAL
>>>>>    runAsyncIn.dumpStats
<<<<<    runAsyncIn.dumpStats: 2.0e-6 CPU  0.000001s TOTAL
>>>>>    runAsyncIn.executeAcc
>>>>>     executeAcc
<<<<<     executeAcc: 8.96e-4 CPU  0.00049s TOTAL
<<<<<    runAsyncIn.executeAcc: 9.36e-4 CPU  0.0007s TOTAL
>>>>>    runAsyncIn.collect
<<<<<    runAsyncIn.collect: 0.0 CPU  0.000027s TOTAL
<<<<<   evalStateT: 0.114156 CPU  0.115327s TOTAL
>>>>>   pop
<<<<<   pop: 0.0 CPU  0.000002s TOTAL
>>>>>   performGC
<<<<<   performGC: 5.7246e-2 CPU  0.057814s TOTAL
<<<<<  evalCUDA: 0.17295 CPU  0.173943s TOTAL
<<<<< runAsyncIn.execute: 0.215475 CPU  0.216563s TOTAL
<<<<< run: 0.215523 CPU  0.216771s TOTAL
Array (Z) [1000001.0]
0.217148s
Prelude Main> Leaving GHCi.



$ ghc -O2 -threaded Main.hs && ./Main
[1 of 1] Compiling Main             ( Main.hs, Main.o )
Linking Main ...
>>>>> run
>>>>> runAsyncIn.execute
>>>>>  runAsyncIn.seq ctx
<<<<<  runAsyncIn.seq ctx: 4.0639e-2 CPU  0.041498s TOTAL
>>>>>  runAsyncIn.seq a
<<<<<  runAsyncIn.seq a: 1.0e-6 CPU  0.000001s TOTAL
>>>>>  runAsyncIn.seq acc
>>>>>   convertAccWith True
<<<<<   convertAccWith: 1.2e-5 CPU  0.000005s TOTAL
<<<<<  runAsyncIn.seq acc: 1.15e-4 CPU  0.000061s TOTAL
>>>>>  evalCUDA
>>>>>   push
<<<<<   push: 2.0e-6 CPU  0.000002s TOTAL
>>>>>   evalStateT
>>>>>    runAsyncIn.compileAcc
>>>>>     compileOpenAcc
>>>>>      compileOpenAcc.traveuseAcc.Alet
>>>>>      compileOpenAcc.traveuseAcc.Use
>>>>>       compileOpenAcc.traveuseAcc.use3
>>>>>       compileOpenAcc.traveuseAcc.use1
<<<<<       compileOpenAcc.traveuseAcc.use1: 0.0 CPU  0.000001s TOTAL
>>>>>       compileOpenAcc.traveuseAcc.use2
>>>>>        compileOpenAcc.traveuseAcc.seq arr
<<<<<        compileOpenAcc.traveuseAcc.seq arr: 3.6651e-2 CPU  0.03712s TOTAL
>>>>>        useArrayAsync
<<<<<        useArrayAsync: 1.427e-3 CPU  0.001427s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use2: 3.8776e-2 CPU  0.039152s TOTAL
<<<<<       compileOpenAcc.traveuseAcc.use3: 3.8794e-2 CPU  0.039207s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Use: 3.8808e-2 CPU  0.03923s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Fold1
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 2.0e-6 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 2.0e-6 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
>>>>>      compileOpenAcc.traveuseAcc.Avar
<<<<<      compileOpenAcc.traveuseAcc.Avar: 0.0 CPU  0.000001s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Fold1: 1.342e-3 CPU  0.001284s TOTAL
<<<<<      compileOpenAcc.traveuseAcc.Alet: 4.0197e-2 CPU  0.040578s TOTAL
<<<<<     compileOpenAcc: 4.0248e-2 CPU  0.040895s TOTAL
<<<<<    runAsyncIn.compileAcc: 4.0834e-2 CPU  0.04103s TOTAL
>>>>>    runAsyncIn.dumpStats
<<<<<    runAsyncIn.dumpStats: 0.0 CPU  0s TOTAL
>>>>>    runAsyncIn.executeAcc
>>>>>     executeAcc
<<<<<     executeAcc: 2.87e-4 CPU  0.000403s TOTAL
<<<<<    runAsyncIn.executeAcc: 2.87e-4 CPU  0.000488s TOTAL
>>>>>    runAsyncIn.collect
<<<<<    runAsyncIn.collect: 9.2e-5 CPU  0.000049s TOTAL
<<<<<   evalStateT: 4.1213e-2 CPU  0.041739s TOTAL
>>>>>   pop
<<<<<   pop: 0.0 CPU  0.000002s TOTAL
>>>>>   performGC
<<<<<   performGC: 9.41e-4 CPU  0.000861s TOTAL
<<<<<  evalCUDA: 4.3308e-2 CPU  0.042893s TOTAL
<<<<< runAsyncIn.execute: 8.5154e-2 CPU  0.084815s TOTAL
<<<<< run: 8.5372e-2 CPU  0.085035s TOTAL
Array (Z) [1000001.0]
0.085169s


结果：


    

  • 评估向量在ghci下取0.121653s，在ghci下取0.035162s
编译版本
    • 

  • 在ghci和
0.00031s在编译版本中
    • 



这可能是另一个问题，但可能有人知道：我们可以调整垃圾收集器，使其在ghci下工作得更快吗？
您可以打开分析并获取报告吗？您的意思是：？我会尽快尝试。我已经在
Data.Array.Accelerate.CUDA.run
中注入了一些时间度量代码，我注意到当
accreate
库加载到ghci时，
run
的执行速度比在可执行文件中使用时慢3倍。我尝试添加以下pragas，但没有效果<代码>{-#专用运行：：Acc（数组DIM2双精度）->（数组DIM2双精度）{-}{-#专用运行：：Acc（数组DIM2浮点）->（数组DIM2浮点）#-}
。我们能否以某种方式优化ghci的这个运行函数？我已经更新了要点–添加了评测报告（main.prof）@ChristianConkle，我在这里尝试了您的测试，并将此重写规则注入加速cuda库-结果：
isoptimized=True
，但代码仍然很慢。