On Wed, Mar 25, 2020 at 12:18 PM Mark Adams <mfad...@lbl.gov> wrote: > Also, a better test is see where streams pretty much saturates, then run > that many processors per node and do the same test by increasing the nodes. > This will tell you how well your network communication is doing. > > But this result has a lot of stuff in "network communication" that can be > further evaluated. The worst thing about this, I would think, is that the > partitioning is blind to the memory hierarchy of inter and intra node > communication. >
Hierarchical partitioning was designed for this purpose. https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/MatOrderings/MATPARTITIONINGHIERARCH.html#MATPARTITIONINGHIERARCH Fande, > The next thing to do is run with an initial grid that puts one cell per > node and the do uniform refinement, until you have one cell per process > (eg, one refinement step using 8 processes per node), partition to get one > cell per process, then do uniform refinement to get a reasonable sized > local problem. Alas, this is not easy to do, but it is doable. > > On Wed, Mar 25, 2020 at 2:04 PM Mark Adams <mfad...@lbl.gov> wrote: > >> I would guess that you are saturating the memory bandwidth. After >> you make PETSc (make all) it will suggest that you test it (make test) and >> suggest that you run streams (make streams). >> >> I see Matt answered but let me add that when you make streams you will >> seed the memory rate for 1,2,3, ... NP processes. If your machine is decent >> you should see very good speed up at the beginning and then it will start >> to saturate. You are seeing about 50% of perfect speedup at 16 process. I >> would expect that you will see something similar with streams. Without >> knowing your machine, your results look typical. >> >> On Wed, Mar 25, 2020 at 1:05 PM Amin Sadeghi <aminthefr...@gmail.com> >> wrote: >> >>> Hi, >>> >>> I ran KSP example 45 on a single node with 32 cores and 125GB memory >>> using 1, 16 and 32 MPI processes. Here's a comparison of the time spent >>> during KSP.solve: >>> >>> - 1 MPI process: ~98 sec, speedup: 1X >>> - 16 MPI processes: ~12 sec, speedup: ~8X >>> - 32 MPI processes: ~11 sec, speedup: ~9X >>> >>> Since the problem size is large enough (8M unknowns), I expected a >>> speedup much closer to 32X, rather than 9X. Is this expected? If yes, how >>> can it be improved? >>> >>> I've attached three log files for more details. >>> >>> Sincerely, >>> Amin >>> >>
