Hi Jakub and Julien,
Thank you so much for your replies. I've tried installing a new version
of MPI and this seems to have resolved my issue. I now get the correct
results independent of the shape of the process grid.
Thanks for the suggestions!
Jakub Kurzak wrote:
Let throw in my $0.02.
For the most part I agree with Julien.
It happened to me before that a vendor MPI implementation was buggy in
the shared memory part.
Definitely trying a different MPI is a good idea.
I saw the word "hyperthreading".
Perhaps you meant "hypertransport"?
I don't think hypertransport changes the memory consistency model, so
it should not be an issue.
I hope you're not using hyperthreading.
There is no performance gain to be expected from that for ScaLAPACK.
On Wed, Oct 7, 2009 at 10:47 AM, Julien Langou
<julien.langou@Domain.Removed <mailto:julien.langou@Domain.Removed>> wrote:
This is indeed baffling (as you put it). There is not much reason
for a ScaLAPACK code to perform correctly on a given machine and
to perform incorrectly on another one. Moreover if you managed to
get the incorrect installation to correctly work from time to
time. A suggestion is to try a different MPI ... I am not at all
convinced that this will change the problem but I have no other
On Tue, 6 Oct 2009, Jason Sadowski wrote:
I am currently using ScaLapack to perform research at the
University of Saskatchewan and have encountered some peculiar
problems. I am using the PDSYEVD routine to
perform the diagonalization of a matrix however occasionally I
get the wrong results. I believe the problem may be a memory
issue, but I am unable to determine what
is causing it. I am hoping somebody can give me an idea as to
where this problem may be occurring.
The matrix I am trying to diagonalize is 3200x3200 and I am
using a block size of 32x32. I've noticed that the
eigenvalues returned by PDSYEVD are different
depending on the particular shape of the process grid I
choose. Inside my program I have the lines which perform:
PRINT Matrix A
Diagonalize ( A, Z)
Where A is the input matrix, and Z is the matrix of
eigenvectors returned from PDSYEVD. I want to perform this
calculation using 4 processors, so I can choose
process grids of 1x4, 2x2, or 4x1. Here are the results of
performing such calculations:
1) Matrix A is independent of the grid shape. It is the same
in all cases.
2) Matrix Z is INCORRECT for grid shapes of 2x2 and 1x4.
3) Process grid 4x1 gives the CORRECT values for MatrixZ.
As I have mentioned before, I believe this may be some kind of
memory issue. The reason I think this is because I can
perform the previous calculations on a
different machine (called vortex) with no errors. Identical
code ran on Vortex gives correct values of MatrixZ for all
grid shapes. Only on this specific machine
(iglu) do the process grid problems arise. To my knowledge
the only difference between the machines is that Vortex is a
quad core machine with 8 GB of RAM, while
iglu is a dual core machine ( with hyperthreading enabled )
and 4 GB of RAM.
First I should ask are there any known issues with ScaLapack's
memory distribution scheme and hyperthreading technology? I
realize this email is quite lengthy, but I
am completely baffled as to why this problem is occurring.
Any ideas or comments as to where I should be looking would be
"He who never made a mistake never made a discovery" - Samuel
Scalapack mailing list
/"He who never made a mistake never made a discovery"/ - Samuel Smiles
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