| ... | ... | @@ -341,3 +341,77 @@ Some concerns: |
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- what names should the new primops have? I planned to use names with a dot preceeding the operator for `Int#` and `Double#` comparisons (e.g. `./=#`, `.>##`) and names with "St" suffix for `Word#` and `Float#`, e.g. `gtWordSt#`, `gtFloatSt#` (`St` stands for 'strict' because the result can be used with the strict bitwise logical operators).
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- how to remove the old `Compare` primops (ones of type `T -> T -> Bool`)?
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- once we have the new primops do we really care about the unboxed `Bool#`?
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### Benchmarks for the proposed patch
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Below is a benchmark for the proof-of-concept filter function that demonstrates performance gains possible with the new primops:
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```wiki
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{-# LANGUAGE BangPatterns, MagicHash #-}
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module Main (
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main
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) where
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import Control.Monad.ST (runST)
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import Criterion.Config (Config, cfgPerformGC,
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defaultConfig, ljust)
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import Criterion.Main
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import Data.Vector.Unboxed.Mutable (unsafeNew, unsafeSlice, unsafeWrite)
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import Data.Vector.Unboxed as U (Vector, filter, foldM',
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fromList, length, unsafeFreeze)
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import GHC.Exts (Int (I#), (.>=#))
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import System.Random (RandomGen, mkStdGen, randoms)
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import Prelude hiding (filter, length)
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filterN :: U.Vector Int -> U.Vector Int
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filterN vec = runST $ do
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let !size = length vec
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fVec <- unsafeNew size
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let put i x = do
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let !(I# v) = x
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inc = I# (v .>=# 0#)
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unsafeWrite fVec i x
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return $ i + inc
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fSize <- foldM' put 0 vec
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unsafeFreeze $ unsafeSlice 0 fSize fVec
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main :: IO ()
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main = return (mkStdGen 1232134332) >>=
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defaultMainWith benchConfig (return ()) . benchmarks
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benchmarks :: RandomGen g => g -> [Benchmark]
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benchmarks gen =
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let dataSize = 10 ^ (7 :: Int)
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inputList = take dataSize . randoms $ gen :: [Int]
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inputVec = fromList inputList
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isPositive = (> 0)
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in [
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bgroup "Filter"
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[
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bench "New" $ whnf (filterN) inputVec
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, bench "Vector" $ whnf (filter isPositive) inputVec
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]
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]
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benchConfig :: Config
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benchConfig = defaultConfig {
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cfgPerformGC = ljust True
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}
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```
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Compile and run with:
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```wiki
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ghc -O2 -fllvm -optlo-O3 Main.hs
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./Main -o report.html
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```
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Benchmarking shows that `filterN` function is 60% faster than the `filter` function based on stream fusion (tested for unboxed vectors containing 10 thousand and 10 million elements). |
