Analytical Estimation of the Scalability of Iterative Numerical Algorithms on Distributed Memory Multiprocessors

This article presents a new high-level parallel computational model named BSF "— Bulk Synchronous Farm. The BSF model extends the BSP model to deal with the computeintensive iterative numericalmethods executed on distributed-memory multiprocessor systems. The BSF model is based on the master-wo...

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Veröffentlicht in:Lobachevskii journal of mathematics Jg. 39; H. 4; S. 571 - 575
1. Verfasser: Sokolinsky, L. B.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Moscow Pleiades Publishing 01.05.2018
Springer Nature B.V
Schlagworte:
Algebra
Analysis
Computer memory
Distributed memory
Geometry
Iterative methods
Mathematical Logic and Foundations
Mathematical models
Mathematics
Mathematics and Statistics
Model accuracy
Multiprocessing
Probability Theory and Stochastic Processes
distributed memory
Parallel computation model
bulk synchronous farm
scalability bound
BSF model
iterative algorithms
ISSN:1995-0802, 1818-9962
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:This article presents a new high-level parallel computational model named BSF "— Bulk Synchronous Farm. The BSF model extends the BSP model to deal with the computeintensive iterative numericalmethods executed on distributed-memory multiprocessor systems. The BSF model is based on the master-worker paradigm and the SPMD programming model. The BSF model makes it possible to predict the upper scalability bound of a BSF-program with great accuracy. The BSF model also provides equations for estimating the speedup and parallel efficiency of a BSF-program.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1995-0802
1818-9962
DOI:10.1134/S1995080218040121