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Performance prediction of parallel systems with scalable specifications—methodology and case study

Authors:

G. HaringAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 22, Issue 2-4

Pages 46 - 62

https://doi.org/10.1145/202100.202103

Published: 01 April 1995 Publication History

Abstract

This paper describes the general methodology of specifying parallel systems within the PAPS (Performance Analysis of Parallel Systems) toolset and presents a case study that shows the applicability and accuracy of the Petri net based performance prediction tools contained in the toolset. Parallel systems are specified in the PAPS toolset by separately defining the program workload, the hardware resources, and the mapping of the program to the hardware. The resource parameterization is described in detail for a multiprocessor computer with a store & forward communication network. The Gaussian elimination algorithm is taken as a workload example to demonstrate how regularly structured parallel algorithms are modelled with acyclic task graphs. Three different program specifications with various levels of model accuracy are developed and their parameterization is described. The predicted execution time is compared with the measured execution times of the real program on the parallel hardware. It is shown that the Petri net based performance prediction tools provide accurate performance predicitons.

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Cited By

Soucies NOuarti N(2014)Performance Prediction of Visual Algorithms on Different Hardware ArchitecturesProceedings of the 2014 International Symposium on Optomechatronic Technologies10.1109/ISOT.2014.16(28-32)Online publication date: 5-Nov-2014
https://dl.acm.org/doi/10.1109/ISOT.2014.16
Abawajy J(2005)Fault-tolerant dynamic job scheduling policyProceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing10.1007/11564621_19(165-173)Online publication date: 2-Oct-2005
https://dl.acm.org/doi/10.1007/11564621_19
Abawajy J(2004)Fault-tolerant scheduling policy for grid computing systems18th International Parallel and Distributed Processing Symposium, 2004. Proceedings.10.1109/IPDPS.2004.1303290(238-244)Online publication date: 2004
https://doi.org/10.1109/IPDPS.2004.1303290
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cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 22, Issue 2-4

April 1995

76 pages

ISSN:0163-5999

DOI:10.1145/202100

Editor:
Blaine D. Gaither
Hewlett-Packard, NSA, Fort Collins, CO

Issue’s Table of Contents

Copyright © 1995 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 1995

Published in SIGMETRICS Volume 22, Issue 2-4

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Cited By

Soucies NOuarti N(2014)Performance Prediction of Visual Algorithms on Different Hardware ArchitecturesProceedings of the 2014 International Symposium on Optomechatronic Technologies10.1109/ISOT.2014.16(28-32)Online publication date: 5-Nov-2014
https://dl.acm.org/doi/10.1109/ISOT.2014.16
Abawajy J(2005)Fault-tolerant dynamic job scheduling policyProceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing10.1007/11564621_19(165-173)Online publication date: 2-Oct-2005
https://dl.acm.org/doi/10.1007/11564621_19
Abawajy J(2004)Fault-tolerant scheduling policy for grid computing systems18th International Parallel and Distributed Processing Symposium, 2004. Proceedings.10.1109/IPDPS.2004.1303290(238-244)Online publication date: 2004
https://doi.org/10.1109/IPDPS.2004.1303290
Abawajy Dandamudi (2003)Parallel job scheduling on multicluster computing systemProceedings IEEE International Conference on Cluster Computing CLUSTR-0310.1109/CLUSTR.2003.1253294(11-18)Online publication date: 2003
https://doi.org/10.1109/CLUSTR.2003.1253294
Wu XWu X(1999)Parallel Performance PredictionPerformance Evaluation, Prediction and Visualization of Parallel Systems10.1007/978-1-4615-5147-8_5(163-191)Online publication date: 1999
https://doi.org/10.1007/978-1-4615-5147-8_5
Steed MClement M(1996)Performance Prediction of PVM ProgramsProceedings of the 10th International Parallel Processing Symposium10.5555/645606.661179(803-807)Online publication date: 15-Apr-1996
https://dl.acm.org/doi/10.5555/645606.661179
Clement MSteed MCrandall PClayton B(1996)Network performance modeling for PVM clustersProceedings of the 1996 ACM/IEEE conference on Supercomputing10.1145/369028.369040(6-es)Online publication date: 17-Nov-1996
https://dl.acm.org/doi/10.1145/369028.369040
Steed MClement M(1996)Performance prediction of PVM programsProceedings of International Conference on Parallel Processing10.1109/IPPS.1996.508151(803-807)Online publication date: 1996
https://doi.org/10.1109/IPPS.1996.508151

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