[Haskell-cafe] Using DPH

[Wilfried Kirschenmann]

> Repa and DPH are different projects. The compilation mechanism and approach to parallelism is quite different between them. You only need -fvectorise to turn on the vectoriser for DPH code. You don't need (or want) -fvectorise for Repa programs. DPH is also still at the "research prototype" stage, and not yet at a point where you'd try to use it for anything real.
>
OK.


> With your example code, you also need to use R.force at appropriate points, and add matches against @(Array _ [Region RangeAll (GenManifest _)]). The reasons for both of these are explained in [1]. Hopefully the second will be fixed by a subsequent GHC release. You must also add {-# INLINE fun #-} pragmas to polymorphic functions or you will pay the price of dictionary passing for the type class overloading.
>
> This runs but doesn't scale with an increasing number of threads. I haven't looked at why. If all the work is in R.sum then that might be the problem -- I haven't put much time into optimising reductions, just maps and filters.
>
surprisingly, when removing the R.force from the code you attached,
performances are better (speed-up=2). I suppose but I am not sure that
this allow for loop fusions beetween the R.map ant the R.sum.

I use ghc 7.0.3, Repa 2.0.0.3 and LLVM 2.9.

By the end, the performances with this new version (0.48s) is 15x
better than my original version (6.9s)
However, the equivalent sequential C code is still 15x better (0.034s).

This may indeed be explained by the fact that all computations are
performed inside the R.sum.
Carrefully tuned, this function shouldn't scale well (x3 on a dual
processor, each with 4 core)  since the performances are limited by
the memory bandwidth. However, this implementation doesn't scale at
all.
Whthout R.force, parallel performances are exactly the same as
sequential performances. With R.force, using the 8 core achieves a 1.1
speed-up.

Thank you for your help.