Re: [Haskell-cafe] SMP parallelism increasing GC time dramatically

7 Oct 2011


      I am guessing that it is slowdown caused by GC needing to co-ordinate with
blocked threads.  That requires lots of re-scheduling to happen in the
kernel.
This is a hard problem I think, but also increasingly important as
virtualization becomes more important and the number of schedulable cores
unknown.

Alexander

On 7 October 2011 12:31, Oliver Batchelor  wrote:
...
I'm not sure if this is at all related, but if I run a small Repa program
with more threads than I have cores/CPUs then it gets drastically slower, I
have a dual core laptop - and -N2 makes my small program take approximately
0.6 of the time. Increasing to -N4 and we're running about 2x the time, -N8
and it's taking 20x or more. I guess this is probably more down to the
design of Repa rather than GHC itself?
Oliver
On Sat, Oct 8, 2011 at 1:21 AM, Tom Thorne wrote:
...
I have made a dummy program that seems to exhibit the same GC
slowdown behavior, minus the segmentation faults. Compiling with -threaded
and running with -N12 I get very bad performance (3x slower than -N1),
running with -N12 -qg it runs approximately 3 times faster than -N1. I don't
know if I should submit this as a bug or not? I'd certainly like to know why
this is happening!
import Numeric.LinearAlgebra
import Numeric.GSL.Special.Gamma
import Control.Parallel.Strategies
import Control.Monad
import Data.IORef
import Data.Random
import Data.Random.Source.PureMT
import Debug.Trace
--
subsets s n = (subsets_stream s) !! n
subsets_stream [] = [[]] : repeat []
subsets_stream (x:xs) =
 let r = subsets_stream xs
    s = map (map (x:)) r
 in [[]] : zipWith (++) s (tail r)
testfun :: Matrix Double -> Int -> [Int] -> Double
testfun x k cs = lngamma (det (c+u))
 where
(m,c) = meanCov xx
 m' = fromRows [m]
u = (trans m') <> m'
 xx = fromColumns ( [(toColumns x)!!i] ++ [(toColumns x)!!j] ++
[(toColumns x)!!k] )
 i = cs !! 0
j = cs !! 1
test :: Matrix Double -> Int -> Double
test x i = sum p
where
 p = parMap (rdeepseq) (testfun x (i+1)) (subsets [0..i] 2)
ranMatrix :: Int -> RVar (Matrix Double)
ranMatrix n = do
xs <- mapM (\_ -> mapM (\_ -> uniform 0 1.0) [1..n]) [1..n]
 return (fromLists xs)
loop :: Int -> Double -> Int -> RVar Double
loop n s i = traceShow i $ do
x <- ranMatrix n
 let r = sum $ parMap (rdeepseq) (test x) [2..(n-2)]
return (r+s)
main = do
let n = 100
 let iter = 5
rng <- newPureMT
 rngr <- newIORef rng
p <- runRVar (foldM (loop n) 0.0 [1..iter]) rngr
 print p
I have also found that the segmentation faults in my code disappear if I
switch from Control.Parallel to Control.Monad.Par, which is quite strange. I
get slightly better performance with Control.Parallel when it completes
without a seg. fault, and the frequency with which it does so seems to
depend on the number of sparks that are being created.
On Thu, Oct 6, 2011 at 1:56 PM, Tom Thorne wrote:
...
I'm trying to narrow it down so that I can submit a meaningful bug
report, and it seems to be something to do with switching off parallel GC
using -qg, whilst also passing -Nx.
Are there any known issues with this that people are aware of? At the
moment I am using the latest haskell platform release on arch.
I'd like to give 7.2 a try in case that fixes it, but I'm using rather a
lot of libraries (hmatrix, fclabels, random fu) and I don't know how to
install them for multiple ghc versions
On Wed, Oct 5, 2011 at 10:43 PM, Johan Tibell wrote:
...
On Wed, Oct 5, 2011 at 2:37 PM, Tom Thorne wrote:
...
The only problem is that now I am getting random occasional
segmentation faults that I was not been getting before, and once got a
message saying:
Main: schedule: re-entered unsafely
Perhaps a 'foreign import unsafe' should be 'safe'?
I think this may be something to do with creating a lot of sparks
though, since this occurs whether I have the parallel GC on or not.
Unless you (or some library you're using) is doing what the error
message says then you should file a GHC bug here:
http://hackage.haskell.org/trac/ghc/
-- Johan
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Re: [Haskell-cafe] SMP parallelism increasing GC time dramatically

Alexander Kjeldaas