Blocked-based sparse matrix-vector multiplication on distributed memory parallel computers

Joint Authors

Shahnaz, Rukhsana
Uthman, Anila

Source

The International Arab Journal of Information Technology

Issue

Vol. 8, Issue 2 (30 Apr. 2011), pp.130-136, 7 p.

Publisher

Zarqa University

Publication Date

2011-04-30

Country of Publication

Jordan

No. of Pages

7

Main Subjects

Information Technology and Computer Science

Topics

Abstract EN

The present paper discusses the implementations of sparse matrix-vector products, which are crucial for high performance solution of large-scale linear equations, on a PC-cluster.

Three storage formats for sparse matrices compressed row storage, block compressed row storage and sparse block compressed row storage are evaluated.

Although using BCRS format reduces the execution time but the improvement may be limited because of the extra work from filled-in zeros.

We show that the use of SBCRS not only improves the performance significantly but reduces matrix storage also.

American Psychological Association (APA)

Shahnaz, Rukhsana& Uthman, Anila. 2011. Blocked-based sparse matrix-vector multiplication on distributed memory parallel computers. The International Arab Journal of Information Technology،Vol. 8, no. 2, pp.130-136.
https://search.emarefa.net/detail/BIM-249328

Modern Language Association (MLA)

Shahnaz, Rukhsana& Uthman, Anila. Blocked-based sparse matrix-vector multiplication on distributed memory parallel computers. The International Arab Journal of Information Technology Vol. 8, no. 2 (Apr. 2011), pp.130-136.
https://search.emarefa.net/detail/BIM-249328

American Medical Association (AMA)

Shahnaz, Rukhsana& Uthman, Anila. Blocked-based sparse matrix-vector multiplication on distributed memory parallel computers. The International Arab Journal of Information Technology. 2011. Vol. 8, no. 2, pp.130-136.
https://search.emarefa.net/detail/BIM-249328

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 135

Record ID

BIM-249328