Scalability analysis of parallel systems with multiple components of work

Authors:
E. Tambouris;P. Van Santen
Affiliations:
Archetypon S.A., Hellas and Department of Electronic and Computer Engineering, Brunel University, Uxbridge, Middlesex, UK;Department of Electronic and Computer Engineering, Brunel University, Uxbridge, Middlesex, UK
Venue:
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
Year:
2000

Citing 8
Cited 0

Introduction to parallel computing: design and analysis of algorithms

Introduction to parallel computing: design and analysis of algorithms
Analyzing scalability of parallel algorithms and architectures

Journal of Parallel and Distributed Computing - Special issue on scalability of parallel algorithms and architectures
Scaling Parallel Programs for Multiprocessors: Methodology and Examples

Computer
Scalability of Parallel Algorithm-Machine Combinations

IEEE Transactions on Parallel and Distributed Systems
Relationships Between Efficiency and Execution Time of Full Multigrid Methods on Parallel Computers

IEEE Transactions on Parallel and Distributed Systems
The Relation of Scalability and Execution Time

IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
A Methodology for Performance and Scalability Analysis

SOFSEM '95 Proceedings of the 22nd Seminar on Current Trends in Theory and Practice of Informatics
Analysis and design of scalable parallel algorithms for scientific computing

Analysis and design of scalable parallel algorithms for scientific computing

Quantified Score

Hi-index	0.03

Visualization

Abstract

In this paper, the generic fixed-value efficiency (fve) method is proposed to study the scalability of parallel algorithms with multiple components of work. The generic fve method is based on the isoefficiency method. Unlike isoefficiency however this method may be applied to parallel algorithm-machine combinations (parallel systems) where the relationship between the total work and its components is not predetermined by the decomposition method or any other factor. The objective of the method is to derive the relationships between the total work and its components in order for the efficiency of the parallel system to be preserved. The use of the method is demonstrated by analysing the impact of the sparsity of the input data on the scalability of a static state-estimator for power systems.