Parallel sparse multifrontal solver in a limited memory environment
Abstract
We consider the parallel solution of sparse linear systems of equations in a limited memory environment. A preliminary out-of core version of a sparse multifrontal code called MUMPS (MUltifrontal Massively Parallel Solver) has been developed as part of a collaboration between CERFACS, ENSEEIHT and INRIA (ENS-Lyon and Bordeaux).
We first briefly describe the current status of the out-of-core factorization phase. We then assume that the factors have been written on the hard disk during the factorization phase and we discuss the design of an efficient solution phase.Two different approaches are presented to read data from the disk, with a discussion on the advantages and the drawbacks of each one.
Our work differs and extends the work of Rothberg and Schreiber (1999) and of Rotkin and Toledo (2004) because firstly we consider a parallel out-of-core context, and secondly we also study the performance of the solve phase.
This is work on collaboration with E. Agullo, I.S Duff, A. Guermouche, J.-Y. L'Excellent, T. Slavova