Shi, There is never a better test problem then your actual problem. Send the results from running on 1, 4, and 8 processes with the options -log_summary -ksp_view (use the optimized version of PETSc (running config/configure.py --with-debugging=0))
Barry On Fri, 9 Feb 2007, Shi Jin wrote: > Hi there, > > I am tuning our 3D FEM CFD code written with PETSc. > The code doesn't scale very well. For example, with 8 > processes on a linux cluster, the speedup we achieve > with a fairly large problem size(million of elements) > is only 3 to 4 using the Congugate gradient solver. We > can achieve a speed up of a 6.5 using a GMRes solver > but the wall clock time of a GMRes is longer than a CG > solver which indicates that CG is the faster solver > and it scales not as good as GMRes. Is this generally > true? > > I then went to the examples and find a 2D example of > KSPSolve (ex2.c). I let the code ran with a 1000x1000 > mesh and get a linear scaling of the CG solver and a > super linear scaling of the GMRes. These are both much > better than our code. However, I think the 2D nature > of the sample problem might help the scaling of the > code. So I would like to try some 3D example using the > KSPSolve. Unfortunately, I couldn't find such an > example either in the src/ksp/ksp/examples/tutorials > directory or by google search. There are a couple of > 3D examples in the src/ksp/ksp/examples/tutorials but > they are about the SNES not KSPSolve. If anyone can > provide me with such an example, I would really > appreciate it. > Thanks a lot. > > Shi > > > > ____________________________________________________________________________________ > Finding fabulous fares is fun. > Let Yahoo! FareChase search your favorite travel sites to find flight and > hotel bargains. > http://farechase.yahoo.com/promo-generic-14795097 > >
