Abstract de la publi numéro 4568
We consider the direct solution of general sparse linear systems based on a multifrontal method. The approach combines partial static scheduling of the task dependency graph during the symbolic
distributed dynamic scheduling during the numerical factorization
to balance the work among the
processes of a distributed memory computer.
We show that to address clusters of SMP
(Symmetric Multi-Processor) architectures, and more
generally non-uniform memory access multiprocessors, our algorithms
for both the static and the dynamic scheduling
need to be revisited to take account of the non-uniform cost of communication.
The performance analysis on an IBM SP3 with 16 processors per SMP node and up to 128 processors shows that we can significantly reduce both the
amount of inter-node communication and the solution time.