Accession Number:

ADA625864

Title:

Parallel Sparse Linear System and Eigenvalue Problem Solvers: From Multicore to Petascale Computing

Descriptive Note:

Final rept. 15 Sep 2011-14 Sep 2014

Corporate Author:

PURDUE UNIV LAFAYETTE IN

Personal Author(s):

Report Date:

2015-06-01

Pagination or Media Count:

15.0

Abstract:

Sparse matrix computations arise in numerous computational science and engineering computations as well as in network analysis and databased simulations. On parallel computing platforms, however, sparse matrix computations represent a major impediment to realizing high performance. Our project aims at designing and implementing solvers for i large sparse linear systems, and ii large sparse symmetric eigenvalue problems that achieve high performance on a single multicore node and clusters of many multicore nodes. Further, we demonstrate both the superior robustness and parallel scalability of our solvers compared to other publicly available parallel solvers for these two fundamental problems.

Subject Categories:

  • Computer Programming and Software
  • Computer Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE