Hi again.
This is the system information:
- Ubuntu 12.04 32-bit
- Intel® Core™2 Duo CPU T5270 @ 1.40GHz × 2
- 2.9 GiB RAM
GHC version:
- GHC 7.4.1
DPH libraries:
- dph-base-0.6.1.1
- (dph-lifted-base-0.6.1.1)
- (dph-lifted-vseg-0.6.1.2)
- (dph-prim-interface-0.6.1.1)
- (dph-prim-par-0.6.1.1)
- (dph-prim-seq-0.6.1.1)
Compilation flags:
I'm using two combinations of flags, taken from different sources. In both
cases results are identical:
- From https://github.com/ghc/packages-dph: -rtsopts -threaded -fllvm
-optlo-O3 -Odph -fcpr-off -fno-liberate-case -package dph-lifted-vseg
- From dph-examples: -rtsopts -threaded -fllvm -Odph -package
dph-lifted-vseg -fcpr-off -fno-liberate-case -fsimpl-tick-factor=1000
Execution flags:
+RTS -N
Tests:
Computing the product of two 400*400 matrices takes 6.037993 seconds.
Computing the product of two 600*600 matrices yields "out of memory
(requested 1728053248 bytes)".
DPH code:
-
{-# NOINLINE matMult_wrapper #-}
matMult_wrapper :: Matrix_wrapper -> Matrix_wrapper -> Matrix_wrapper
matMult_wrapper mA mB = toPArrayP (mapP toPArrayP (matMult
(fromNestedPArrayP mA) (fromNestedPArrayP mB)))
matMult :: Matrix -> Matrix -> Matrix
matMult mA mB = mapP (\row -> mapP (\col -> dotp row col) mB) mA
-- I removed the call to transposeP, so It's no longer an actual matrix
product
dotp :: MVector -> MVector -> MMultType
dotp row col = D.sumP (zipWithP (D.*) row col)
-
I'm attaching the files with the full example code
If there is any other information needed, please let me know
Any help is very appreciated
On Tue, Jul 10, 2012 at 9:51 AM, Mauro Blanco wrote:
> Thanks for both answers
>
> I have used repa with the newer interface for the same example, but I
> wanted to have another example using DPH. I know repa is more suited for
> regular representations, but I wanted to express the same program in DPH
> where I don´t have to worry of nested parallel computation.
>
> The transposeP did not seem to be the problem as only
> executing transposeP on "big" matrices generated no memory issues. But,
> something like this (on square matrices) still have memory problems:
> matMult :: Matrix -> Matrix -> Matrix
> matMult mA mB = mapP (\row -> mapP (\col -> dotp row col) *mB*) mA
>
> dotp :: MVector -> MVector -> MMultType
> dotp row col = D.sumP (zipWithP (D.*) row col)
>
> Later today (or tomorrow) I will post exact OS, GHC and libraries version
> as the command line options and execution information on the simplified
> example.
>
> Thanks again
>
>
> On Tue, Jul 10, 2012 at 8:43 AM, Manuel M T Chakravarty <
> c...@cse.unsw.edu.au> wrote:
>
>> Firstly, especially when you are talking about performance, please
>> provided detailed information on (a) the versions of the compiler and
>> libraries that you used and (b) of the command line options that you used
>> for compilation.
>>
>> Secondly, your function 'transposeP' doesn't make for a good nested
>> data-parallel program. I haven't looked at the generated code, but I
>> wouldn't be surprised if it doesn't optimise very well.
>>
>> The core benefit of nested data parallelism is that the sub-arrays in a
>> nested array of arrays can be of varying size leading to irregular
>> parallelism. However, that flexibility comes at a price, namely that it is
>> a fairly inefficient representation for *rectangular arrays*, such as
>> regular two-dimensional matrices (as in your example). It shouldn't be
>> quite as inefficient as what you report, but it will never be competitive
>> with a dedicated regular representation.
>>
>> Hence, for code, such as yours, we recommend to use our Repa library:
>> http://hackage.haskell.org/package/repa
>>
>> It generates very fast code for regular array problems, see also
>> http://www.cse.unsw.edu.au/~chak/papers/LCKP12.html
>>
>> Manuel
>>
>>
>> mblanco :
>>
>> Hi, I'm trying to implement a matrix product example using DPH. This is
>> the code:
>> --**--**
>> --**-
>> type MMultType = Double
>> type Matrix = [:[:MMultType:]:]
>> type MVector = [:MMultType:]
>> type Matrix_wrapper = PArray (PArray MMultType)
>>
>> {-# NOINLINE matMult_wrapper #-}
>> matMult_wrapper :: Matrix_wrapper -> Matrix_wrapper -> Matrix_wrapper
>> matMult_wrapper mA mB = toPArrayP (mapP toPArrayP (matMult
>&g
