We consider the parallel solution of sparse linear systems 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 with members of INRIA project GRAAL. In this context, we 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 Rotkin and Toledo (2004) because firstly we consider a parallel out-ofcore context, and secondly we focus on the performance of the solve phase.