On Tuesday, September 07, 2010 09:18:51 pm Christoph Pospiech wrote:
> Hi,
>
> I was trying to do the equivalent of an MPI_Gather using code like this.
>
> finish for ( pt(i) in v_dst ) {
> v_loc(i).copyFrom(0,v_dst(pt),0,vsize);
>
> where
> static type Array1D = Array[Double]{rank==1};
>
> global val v_dst: DistArray[Array1D]{rank==1};
> global val v_loc: Array[Array1D]{rank==1};
>
> - the region for all objects of type Array1D is [0..vsize-1],
> - the region for v_loc and v_dst is [0..number_of_places-1],
> - the distribution for v_dst maps exactly one point to each place.
>
> The above code runs fine on one place. But on two places, it throws a
> x10.lang.BadPlaceException: point (1) not defined at (Place 0).
> pt(1) lives on place 1 by definition, so the exception is thrown correctly.
> Means - the above code snippet is wrong. I tried about half a dozen
> variants of the above, but no avail.
>
> How to do it right ?
Thinking it over, I am even more interested in the equivalent of an MPI_Reduce
along the lines above. I could think of the following four strategies.
1. Gathering all data to an Array v_loc as described above, then (vector-) add
the array elements of v_loc to get a single value of type Array1D.
2. Call Array1D.reduce(). The complicated part is the definition of an
appropriate reduction function Array1D.+ (Array1D, Array1D) => Array1D.
3. Change the data type of v_dst to DistArray[Double] with region [0..vsize-1,
0..number_of_places-1]. Then try to use the ordinary reduce() after
restricting the region to [x..x, 0..number_of_places-1], for each 0 <= x <
vsize. This means that you have to execute vsize many reductions.
4. @Native call of MPI_reduce(). Apart from being unclear how to do this, it
is not very X10-like.
Anyone any suggestions on which of these is the most promising ?
--
Mit freundlichen Grüßen / Kind regards
Dr. Christoph Pospiech
High Performance & Parallel Computing
Phone: +49-351 86269826
Mobile: +49-171-765 5871
E-Mail: christoph.pospi...@de.ibm.com
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