Ah okay. Thanks for the timings. Have you monitored the CPU usage when you using umfpack? On my machine, it's definitely not running on a single process, so I wouldn't consider it a sequential solver.
On 15 May 2012 09:54, Thomas Witkowski <thomas.witkowski at tu-dresden.de> wrote: > Am 15.05.2012 09:36, schrieb Dave May: > >> I have seem similar behaviour comparing umfpack and superlu_dist, >> however the difference wasn't enormous, possibly umfpack was a factor >> of 1.2-1.4 times faster on 1 - 4 cores. >> What sort of time differences are you observing? Can you post the >> numbers somewhere? > > I attached my data to this mail. For the largest matrix, umfpack failed > after allocating 4 GB of memory. I have not tried to figure out what's the > problem there. As you can see, for these matrices the distributed solvers > are slower by a factor of 2 or 3 compared to umfpack. For all solvers, I > have used the standard parameters, so I have not played around with the > permutation strategies and such things. This may be also the reason why > superlu is much slower than superlu_dist with just one core as it makes use > of different col and row permutation strategies. > >> However, umpack will not work on a distributed memory machine. >> My personal preference is to use superlu_dist in parallel. In my >> experience using it as a coarse grid solver for multigrid, I find it >> much more reliable than mumps. However, when mumps works, its is >> typically slightly faster than superlu_dist. Again, not by a large >> amount - never more than a factor of 2 faster. > > In my codes I also make use of the distributed direct solvers for the coarse > grid problems. I just wanted to make some tests how far away these solvers > are from the sequential counterparts. > > Thomas > >> >> The failure rate using mumps is definitely higher (in my experience) >> when running on large numbers of cores compared to superlu_dist. I've >> never got to the bottom as to why it fails. >> >> Cheers, >> ? Dave >> >> >> On 15 May 2012 09:25, Thomas Witkowski<thomas.witkowski at tu-dresden.de> >> ?wrote: >>> >>> I made some comparisons of using umfpack, superlu, superlu_dist and mumps >>> to >>> solve systems with sparse matrices arising from finite element method. >>> The >>> size of the matrices range from around 50000 to more than 3 million >>> unknowns. I used 1, 2, 4, 8 and 16 nodes to make the benchmark. Now, I >>> wonder that in all cases the sequential umfpack was the fastest one. So >>> even >>> with 16 cores, superlu_dist and mumps are slower. Can anybody of you >>> confirm >>> this observation? Are there any other parallel direct solvers around >>> which >>> are more efficient? >>> >>> Thomas > >
