Abstract de la publi numéro 2364
This paper provides a comprehensive study and comparison of two
state-of-the-art direct solvers for
large sparse sets of linear equations on large-scale distributed-memory
computers. One is a multifrontal solver called MUMPS, the other is a
supernodal solver called SUPERLU.
We describe the main algorithmic features of the two solvers and compare
their performance characteristics with respect to uniprocessor speed,
interprocessor communication, and memory requirements.
For both solvers, preorderings for numerical stability
and sparsity play an important role in achieving high
We analyse the results with various ordering algorithms.
Our performance analysis is based on data obtained from runs on a 512-processor
Cray T3E using a set of matrices from real applications.
We also use regular 3D grid problems to study the scalability
of the two solvers.