Iterative solution of large, sparse linear systems on a static data flow architecture: Performance studies

Author

Reed, Daniel A. ; Patrick, Merrell L.

Author_Institution

Dept. of Comput. Sci., Illinois Univ., Urbana, IL, USA

Issue

10

fYear

1985

Firstpage

874

Lastpage

880

Abstract

The applicability of static data flow architectures to the iterative solution of sparse linear systems of equations is investigated. An analytic performance model of a static data flow computation is developed. This model includes both spatial parallelism, concurrent execution in multiple PEs, and pipelining, the streaming of data from array memories through the PEs. The performance model is used to analyze a row-partitioned iterative algorithms for solving sparse linear systems of algebraic equations. On the basis of this analysis, design parameters for the static data flow architecture as a function of matrix sparsity and dimension are proposed.

Keywords

computer architecture; iterative methods; parallel processing; algebraic equations; analytic performance model; array memories; concurrent execution; data streaming; design parameters; iterative solution; matrix sparsity; performance studies; pipelining; sparse linear systems; spatial parallelism; static data flow architecture; Arrays; Computational modeling; Convergence; Flow graphs; Sparse matrices; Vectors; Algorithm analysis; data flow; parallel algorithms; performance models; sparse linear systems;

fLanguage

English

Journal_Title

Computers, IEEE Transactions on

Publisher

ieee

ISSN

0018-9340

Type

jour

DOI

10.1109/TC.1985.6312190

Filename

6312190