PFEAST: A High Performance Sparse Eigenvalue Solver Using Distributed-Memory Linear Solvers
SessionNumerical Algorithms I
Session ChairHatem Ltaief
Event Type
Paper
Algorithms
Intermediate
Scientific Computing
TimeTuesday, November 15th1:30pm - 2pm
Location355-E
DescriptionThe FEAST algorithm and eigensolver for interior eigenvalue problems naturally possesses three distinct levels of parallelism. The solver is then suited to exploit modern computer architectures containing many interconnected processors. This paper highlights a recent development within the software package that allows the dominant computational task, solving a set of complex linear system, to be performed with a distributed-memory solver. The software, written with a reverse-communication-interface, can now be interfaced with any generic MPI linear-system solver using a customized data distribution for the eigenvector solutions. This work utilizes two common "black-box" distributed-memory linear-systems solvers (Cluster-MKL-Pardiso and MUMPS), as well as our own application-specific domain-decomposition MPI solver, for a collection of 3-dimensional finite-element systems. We discuss and analyze how parallel resources can be placed at all three levels simultaneously in order to achieve
good scalability and optimal use of the computing platform.
good scalability and optimal use of the computing platform.
