Loading [MathJax]/extensions/tex2jax.js

Perpret: A performance prediction tool for massively parallel systems

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autorschaft

  • Jürgen Brehm
  • Manish Madhukar
  • Evgenia Smirni
  • Larry Dowdy

Externe Organisationen

  • Vanderbilt University
Plum Print visual indicator of research metrics
  • Citations
    • Citation Indexes: 5
  • Captures
    • Readers: 1
see details

Details

OriginalspracheEnglisch
Titel des SammelwerksQuantitative Evaluation of Computing and Communication Systems
Untertitel8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems MMB 1995, Proceedings
Herausgeber/-innenHeinz Beilner, Falko Bause
Herausgeber (Verlag)Springer Verlag
Seiten284-298
Seitenumfang15
ISBN (Print)9783540603009
PublikationsstatusVeröffentlicht - 9 Juni 2005
Veranstaltung8th International Conference on Modelling Techniques and Tools for Computer performance Evaluation, Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems - Heidelberg, Deutschland
Dauer: 20 Sept. 199522 Sept. 1995

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band977
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Abstract

Today’s massively parallel machines are typically message passing systems consisting of hundreds or thousands of processors. Implementing parallel applications efficiently in this environment is a challenging task. The Performance Prediction Tool (PerPreT) presented in this paper is useful for system designers and application developers. The system designers can use the tool to examine the effects of changes of architectural parameters on parallel applications (e.g., reduction of setup time, increase of link bandwidth, faster execution units). Application developers are interested in a fast evaluation of different parallelization strategies of their codes. PerPreT uses a relatively simple analytical model to predict speedup, execution time, computation time, and communication time for a parametrized application. Especially for large numbers of processors, PerPreT s analytical model is preferable to traditional models (e.g., Markov based approaches such as queueing and Petri net models). The applications are modelled through parameterized formulae for communication and computation. The parameters used by PerPreT include the problem size and the number of processors used to execute the program. The target systems are described by architectural parameters (e.g., setup times for communication, link bandwidth, and sustained computing performance per node).

ASJC Scopus Sachgebiete

Zitieren

Perpret: A performance prediction tool for massively parallel systems. / Brehm, Jürgen; Madhukar, Manish; Smirni, Evgenia et al.
Quantitative Evaluation of Computing and Communication Systems : 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems MMB 1995, Proceedings. Hrsg. / Heinz Beilner; Falko Bause. Springer Verlag, 2005. S. 284-298 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 977).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Brehm, J, Madhukar, M, Smirni, E & Dowdy, L 2005, Perpret: A performance prediction tool for massively parallel systems. in H Beilner & F Bause (Hrsg.), Quantitative Evaluation of Computing and Communication Systems : 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems MMB 1995, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 977, Springer Verlag, S. 284-298, 8th International Conference on Modelling Techniques and Tools for Computer performance Evaluation, Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems, Heidelberg, Deutschland, 20 Sept. 1995. https://doi.org/10.1007/bfb0024322
Brehm, J., Madhukar, M., Smirni, E., & Dowdy, L. (2005). Perpret: A performance prediction tool for massively parallel systems. In H. Beilner, & F. Bause (Hrsg.), Quantitative Evaluation of Computing and Communication Systems : 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems MMB 1995, Proceedings (S. 284-298). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 977). Springer Verlag. https://doi.org/10.1007/bfb0024322
Brehm J, Madhukar M, Smirni E, Dowdy L. Perpret: A performance prediction tool for massively parallel systems. in Beilner H, Bause F, Hrsg., Quantitative Evaluation of Computing and Communication Systems : 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems MMB 1995, Proceedings. Springer Verlag. 2005. S. 284-298. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2005 Jan 1. doi: 10.1007/bfb0024322
Brehm, Jürgen ; Madhukar, Manish ; Smirni, Evgenia et al. / Perpret : A performance prediction tool for massively parallel systems. Quantitative Evaluation of Computing and Communication Systems : 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems MMB 1995, Proceedings. Hrsg. / Heinz Beilner ; Falko Bause. Springer Verlag, 2005. S. 284-298 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Download
@inproceedings{9ef90214c35c49b8adf6e3d56f9e9e97,
title = "Perpret: A performance prediction tool for massively parallel systems",
abstract = "Today{\textquoteright}s massively parallel machines are typically message passing systems consisting of hundreds or thousands of processors. Implementing parallel applications efficiently in this environment is a challenging task. The Performance Prediction Tool (PerPreT) presented in this paper is useful for system designers and application developers. The system designers can use the tool to examine the effects of changes of architectural parameters on parallel applications (e.g., reduction of setup time, increase of link bandwidth, faster execution units). Application developers are interested in a fast evaluation of different parallelization strategies of their codes. PerPreT uses a relatively simple analytical model to predict speedup, execution time, computation time, and communication time for a parametrized application. Especially for large numbers of processors, PerPreT s analytical model is preferable to traditional models (e.g., Markov based approaches such as queueing and Petri net models). The applications are modelled through parameterized formulae for communication and computation. The parameters used by PerPreT include the problem size and the number of processors used to execute the program. The target systems are described by architectural parameters (e.g., setup times for communication, link bandwidth, and sustained computing performance per node).",
keywords = "Performance evaluation, Performance prediction, Workload modeling",
author = "J{\"u}rgen Brehm and Manish Madhukar and Evgenia Smirni and Larry Dowdy",
year = "2005",
month = jun,
day = "9",
doi = "10.1007/bfb0024322",
language = "English",
isbn = "9783540603009",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "284--298",
editor = "Heinz Beilner and Falko Bause",
booktitle = "Quantitative Evaluation of Computing and Communication Systems",
address = "Germany",
note = "8th International Conference on Modelling Techniques and Tools for Computer performance Evaluation, Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems, MMB 1995 ; Conference date: 20-09-1995 Through 22-09-1995",

}

Download

TY - GEN

T1 - Perpret

T2 - 8th International Conference on Modelling Techniques and Tools for Computer performance Evaluation, Performance Tools 1995 and 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems

AU - Brehm, Jürgen

AU - Madhukar, Manish

AU - Smirni, Evgenia

AU - Dowdy, Larry

PY - 2005/6/9

Y1 - 2005/6/9

N2 - Today’s massively parallel machines are typically message passing systems consisting of hundreds or thousands of processors. Implementing parallel applications efficiently in this environment is a challenging task. The Performance Prediction Tool (PerPreT) presented in this paper is useful for system designers and application developers. The system designers can use the tool to examine the effects of changes of architectural parameters on parallel applications (e.g., reduction of setup time, increase of link bandwidth, faster execution units). Application developers are interested in a fast evaluation of different parallelization strategies of their codes. PerPreT uses a relatively simple analytical model to predict speedup, execution time, computation time, and communication time for a parametrized application. Especially for large numbers of processors, PerPreT s analytical model is preferable to traditional models (e.g., Markov based approaches such as queueing and Petri net models). The applications are modelled through parameterized formulae for communication and computation. The parameters used by PerPreT include the problem size and the number of processors used to execute the program. The target systems are described by architectural parameters (e.g., setup times for communication, link bandwidth, and sustained computing performance per node).

AB - Today’s massively parallel machines are typically message passing systems consisting of hundreds or thousands of processors. Implementing parallel applications efficiently in this environment is a challenging task. The Performance Prediction Tool (PerPreT) presented in this paper is useful for system designers and application developers. The system designers can use the tool to examine the effects of changes of architectural parameters on parallel applications (e.g., reduction of setup time, increase of link bandwidth, faster execution units). Application developers are interested in a fast evaluation of different parallelization strategies of their codes. PerPreT uses a relatively simple analytical model to predict speedup, execution time, computation time, and communication time for a parametrized application. Especially for large numbers of processors, PerPreT s analytical model is preferable to traditional models (e.g., Markov based approaches such as queueing and Petri net models). The applications are modelled through parameterized formulae for communication and computation. The parameters used by PerPreT include the problem size and the number of processors used to execute the program. The target systems are described by architectural parameters (e.g., setup times for communication, link bandwidth, and sustained computing performance per node).

KW - Performance evaluation

KW - Performance prediction

KW - Workload modeling

UR - http://www.scopus.com/inward/record.url?scp=84957024911&partnerID=8YFLogxK

U2 - 10.1007/bfb0024322

DO - 10.1007/bfb0024322

M3 - Conference contribution

AN - SCOPUS:84957024911

SN - 9783540603009

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 284

EP - 298

BT - Quantitative Evaluation of Computing and Communication Systems

A2 - Beilner, Heinz

A2 - Bause, Falko

PB - Springer Verlag

Y2 - 20 September 1995 through 22 September 1995

ER -