[Trilinos-Users] ML/AztecOO scalability

[Eric Marttila]

Dear all,

I've used ML and AztecOO for solving linear systems on a single processor.  
Now I'm looking at running on multiple processors.  As a first step I compiled 
and ran the ML/AztecOO example (solving Laplace equation) from:

http://code.google.com/p/trilinos/wiki/MLAztecOO

I used a problem size of 8 million and ran with 1, 2, 3, and 4 processors.  
The solution times for each case are listed below:

np=1               Solution time: 38.168500 (sec.)
np=2               Solution time: 26.174297 (sec.)
np=3               Solution time: 21.492841 (sec.)
np=4               Solution time: 21.108066 (sec.)

Can anyone comment on whether or not these timing results are reasonable?  I 
was expecting that I would see close to linear speedup, but with this case I 
see a speedup of only 1.8 with 4 processors, and based on the trend there 
would be little or no additional speedup with more processors.  I tested with 
smaller problem sizes and saw the same results.

I'm using Trilinos 10.8.5, configured as release, with MPI enabled.  I'm using 
mpich2 and the tests were run on a quad-core (Intel i7) with 8 Gb of memory. 
(OS is 64bit linux fedora 14)

I would appreciate any comments and/or suggestions of what I could do to 
improve the scalability.

Thank you.
--Eric

-- 
Eric A. Marttila
ThermoAnalytics, Inc.
23440 Airpark Blvd.
Calumet, MI 49913

email: Eric.Marttila at ThermoAnalytics.com
phone: 810-636-2443
fax:   906-482-9755
web: http://www.thermoanalytics.com