Task Scheduling in an Asynchronous Distributed Memory Multifrontal Solver

摘要

This document describes the improvements to the task scheduling for MUMPS, an asynchronous distributed memory direct solver for sparse linear systems. In the new approach, it determines, during the analysis of the matrix, candidate processes for the tasks that will be dynamically scheduled during the subsequent factorization. This approach significantly improves the scalability of the solver in terms of execution time and storage.