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PSBLAS: a library for parallel linear algebra computation on sparse matrices

Editor: Ronald F. Boisvert Authors:

Salvatore Filippone,

Michele ColajanniAuthors Info & Claims

ACM Transactions on Mathematical Software (TOMS), Volume 26, Issue 4

Pages 527 - 550

https://doi.org/10.1145/365723.365732

Published: 01 December 2000 Publication History

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Abstract

Many computationally intensive problems in engineering and science give rise to the solution of large, sparse, linear systems of equations. Fast and efficient methods for their soltion are very important because these systems usually occur in the innermost loop of the computational scheme. Parallelization is often necessary to achieve an acceptable level of performance. This paper presents the design, implementation, and interface of a library of Basic Linear Algebra Subroutines for sparse matrices (PSBLAS) which is specifically tailored to distributed-memory computers. PSBLAS enables easy, efficient, and portable implementations of parallel iterative solvers for linear systems. The interface keeps in view a Single Program Multiple Data programming model on distributed-memory machines. However, the architecture of the library does not exclude an implementation in different paradigms, such as those based on the shared-memory model.

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PSBLAS: a library for parallel linear algebra computation on sparse matrices

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Reviews

Reviewer: Maurice W. Benson

A Fortran 77 Parallel Sparse Basic Linear Algebra Subroutine (PSBLAS) library for sparse matrix operations on distributed-memory computers is presented along with a Fortran 90 object oriented user interface to this library. The focus is on operations that support iterative methods for the solution of large sparse linear systems such as those arising from the numerical solution of partial differential equations with an emphasis on preconditioned methods where the preconditioner has at most the same communication needs as matrix vector multiplication. Each processor works with a set of rows from the full system and serial sparse Basic Linear Algebra Subroutines (BLAS) are used by the processors for their serial computations. A substantial part of the development involves a clear summary of communications, data structures, PSBLAS operations and the object oriented interface to these operations. The advantages of the object oriented approach are stressed and well illustrated with a couple of examples. Efficiency is illustrated through a set of experimental results and a summary of related software is included. This work should be of interest to researchers working with parallel iterative methods as well as software developers needing parallel sparse matrix operations for an application.

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Published In

cover image ACM Transactions on Mathematical Software

ACM Transactions on Mathematical Software Volume 26, Issue 4

Dec. 2000

155 pages

ISSN:0098-3500

EISSN:1557-7295

DOI:10.1145/365723

Editor:
Ronald F. Boisvert
National Institute of Standards, Gaithersburg, MD

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2000

Published in TOMS Volume 26, Issue 4

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https://doi.org/10.5194/gmd-16-2795-2023
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Abstract

References

Cited By

Index Terms

Recommendations

Extending PSBLAS to build parallel schwarz preconditioners

A MATLAB-Based Code Generator for Parallel Sparse Matrix Computations Utilizing PSBLAS

On the development of PSBLAS-based parallel two-level Schwarz preconditioners

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