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?
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. 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