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{-# LANGUAGE BangPatterns #-}
-- $ ghc --make -O2 benchmarks.hs
import Numeric.LinearAlgebra
import System.Time
import System.CPUTime
import Text.Printf
import Data.List(foldl1')
time act = do
t0 <- getCPUTime
act
t1 <- getCPUTime
printf "%.3f s CPU\n" $ (fromIntegral (t1 - t0) / (10^12 :: Double)) :: IO ()
--------------------------------------------------------------------------------
main = sequence_ [bench1,bench2,bench3,bench4,bench5 1000000 3]
w :: Vector Double
w = constant 1 5000000
w2 = 1 * w
bench1 = do
putStrLn "Sum of a vector with 5M doubles:"
print$ vectorMax (w+w2) -- evaluate it
time $ printf " BLAS: %.2f: " $ sumVB w
time $ printf " Haskell: %.2f: " $ sumVH w
time $ printf " BLAS: %.2f: " $ sumVB w
time $ printf " Haskell: %.2f: " $ sumVH w
time $ printf " innerH: %.2f: " $ innerH w w2
sumVB v = constant 1 (dim v) <.> v
sumVH v = go (d - 1) 0
where
d = dim v
go :: Int -> Double -> Double
go 0 s = s + (v @> 0)
go !j !s = go (j - 1) (s + (v @> j))
innerH u v = go (d - 1) 0
where
d = dim u
go :: Int -> Double -> Double
go 0 s = s + (u @> 0) * (v @> 0)
go !j !s = go (j - 1) (s + (u @> j) * (v @> j))
-- These functions are much faster if the library
-- is configured with -funsafe
--------------------------------------------------------------------------------
bench2 = do
putStrLn "-------------------------------------------------------"
putStrLn "Multiplication of 1M different 3x3 matrices:"
-- putStrLn "from [[]]"
-- time $ print $ manymult (10^6) rot'
-- putStrLn "from (3><3) []"
time $ print $ manymult (10^6) rot
print $ cos (10^6/2)
rot' :: Double -> Matrix Double
rot' a = matrix [[ c,0,s],
[ 0,1,0],
[-s,0,c]]
where c = cos a
s = sin a
matrix = fromLists
rot :: Double -> Matrix Double
rot a = (3><3) [ c,0,s
, 0,1,0
,-s,0,c ]
where c = cos a
s = sin a
manymult n r = foldl1' (<>) (map r angles)
where angles = toList $ linspace n (0,1)
-- angles = map (k*) [0..n']
-- n' = fromIntegral n - 1
-- k = recip n'
--------------------------------------------------------------------------------
bench3 = do
putStrLn "-------------------------------------------------------"
putStrLn "foldVector"
let v = flatten $ ident 500 :: Vector Double
print $ vectorMax v -- evaluate it
putStrLn "sum, dim=5M:"
-- time $ print $ foldLoop (\k s -> w@>k + s) 0.0 (dim w)
time $ print $ sumVector w
putStrLn "sum, dim=0.25M:"
--time $ print $ foldLoop (\k s -> v@>k + s) 0.0 (dim v)
time $ print $ sumVector v
let getPos k s = if k `mod` 500 < 200 && v@>k > 0 then k:s else s
putStrLn "foldLoop for element selection, dim=0.25M:"
time $ print $ (`divMod` 500) $ maximum $ foldLoop getPos [] (dim v)
foldLoop f s d = go (d - 1) s
where
go 0 s = f (0::Int) s
go !j !s = go (j - 1) (f j s)
foldVector f s v = foldLoop g s (dim v)
where g !k !s = f k (v@>) s
{-# INLINE g #-} -- Thanks Ryan Ingram (http://permalink.gmane.org/gmane.comp.lang.haskell.cafe/46479)
sumVector = foldVector (\k v s -> v k + s) 0.0
-- foldVector is slower if used in two places unless we use the above INLINE
-- this does not happen with foldLoop
--------------------------------------------------------------------------------
bench4 = do
putStrLn "-------------------------------------------------------"
putStrLn "1000x1000 inverse"
let a = ident 1000 :: Matrix Double
let b = 2*a
print $ vectorMax $ flatten (a+b) -- evaluate it
time $ print $ vectorMax $ flatten $ linearSolve a b
--------------------------------------------------------------------------------
op1 a b = a <> trans b
op2 a b = a + trans b
timep = time . print . vectorMax . flatten
bench5 n d = do
putStrLn "-------------------------------------------------------"
putStrLn "transpose in multiply"
let ms = replicate n ((ident d :: Matrix Double))
let mz = replicate n (diag (constant (0::Double) d))
timep $ foldl1' (<>) ms
timep $ foldl1' op1 ms
putStrLn "-------------------------------------------------------"
putStrLn "transpose in add"
timep $ foldl1' (+) ms
timep $ foldl1' op2 ms
|
