Yeah, the Repa fold and sum functions just use the equivalent Data.Vector
ones. They're not parallelised and I haven't looked at the generated code.
I'll add a ticket to the trac to fix these, but won't have time to work on it
myself in the near future.
Ok.
Thank you for your help.
I
Hi,
In order to do a performance comparison beetween different approaches for
our application, I make different implementation of a simple example
(computing the norm of a vector expression.
I rely on Repa to do this.
However, when I tried to build the parallel version (-threaded -fvectorise
On 12/04/2011, at 7:32 PM, Wilfried Kirschenmann wrote:
Hi,
In order to do a performance comparison beetween different approaches for our
application, I make different implementation of a simple example (computing
the norm of a vector expression.
I rely on Repa to do this.
However,
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
On 12/04/2011, at 11:50 PM, Wilfried Kirschenmann wrote:
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
