A scalable approach to MPI application performance analysis

Shirley Moore; Felix Wolf; Jack Dongarra; Sameer Shende; Allen Malony; Bernd Mohr

doi:10.1007/11557265_41

A scalable approach to MPI application performance analysis

Shirley Moore, Felix Wolf, Jack Dongarra, Sameer Shende, Allen Malony, Bernd Mohr

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

A scalable approach to performance analysis of MPI applications is presented that includes automated source code instrumentation, low overhead generation of profile and trace data, and database management of performance data. In addition, tools are described that analyze large-scale parallel profile and trace data. Analysis of trace data is done using an automated pattern-matching approach. Examples of using the tools on large-scale MPI applications are presented.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	309-316
Number of pages	8
DOIs	https://doi.org/10.1007/11557265_41
State	Published - 2005
Externally published	Yes
Event	12th European PVM/MPI Users' Group Meeting - Recent Advances in Parallel Virtual Machine and Message Passing Interface - Sorrento, Italy Duration: Sep 18 2005 → Sep 21 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3666 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th European PVM/MPI Users' Group Meeting - Recent Advances in Parallel Virtual Machine and Message Passing Interface
Country/Territory	Italy
City	Sorrento
Period	09/18/05 → 09/21/05

Access to Document

10.1007/11557265_41

Cite this

Moore, S., Wolf, F., Dongarra, J., Shende, S., Malony, A., & Mohr, B. (2005). A scalable approach to MPI application performance analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 309-316). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3666 LNCS). https://doi.org/10.1007/11557265_41

Moore, Shirley ; Wolf, Felix ; Dongarra, Jack et al. / A scalable approach to MPI application performance analysis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. pp. 309-316 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{178146f6ff36407aa2c268c145fe66f7,

title = "A scalable approach to MPI application performance analysis",

abstract = "A scalable approach to performance analysis of MPI applications is presented that includes automated source code instrumentation, low overhead generation of profile and trace data, and database management of performance data. In addition, tools are described that analyze large-scale parallel profile and trace data. Analysis of trace data is done using an automated pattern-matching approach. Examples of using the tools on large-scale MPI applications are presented.",

author = "Shirley Moore and Felix Wolf and Jack Dongarra and Sameer Shende and Allen Malony and Bernd Mohr",

year = "2005",

doi = "10.1007/11557265\_41",

language = "English",

isbn = "3540290095",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "309--316",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

note = "12th European PVM/MPI Users' Group Meeting - Recent Advances in Parallel Virtual Machine and Message Passing Interface ; Conference date: 18-09-2005 Through 21-09-2005",

}

Moore, S, Wolf, F, Dongarra, J, Shende, S, Malony, A & Mohr, B 2005, A scalable approach to MPI application performance analysis. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3666 LNCS, pp. 309-316, 12th European PVM/MPI Users' Group Meeting - Recent Advances in Parallel Virtual Machine and Message Passing Interface, Sorrento, Italy, 09/18/05. https://doi.org/10.1007/11557265_41

A scalable approach to MPI application performance analysis. / Moore, Shirley; Wolf, Felix; Dongarra, Jack et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. p. 309-316 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3666 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A scalable approach to MPI application performance analysis

AU - Moore, Shirley

AU - Wolf, Felix

AU - Dongarra, Jack

AU - Shende, Sameer

AU - Malony, Allen

AU - Mohr, Bernd

PY - 2005

Y1 - 2005

N2 - A scalable approach to performance analysis of MPI applications is presented that includes automated source code instrumentation, low overhead generation of profile and trace data, and database management of performance data. In addition, tools are described that analyze large-scale parallel profile and trace data. Analysis of trace data is done using an automated pattern-matching approach. Examples of using the tools on large-scale MPI applications are presented.

AB - A scalable approach to performance analysis of MPI applications is presented that includes automated source code instrumentation, low overhead generation of profile and trace data, and database management of performance data. In addition, tools are described that analyze large-scale parallel profile and trace data. Analysis of trace data is done using an automated pattern-matching approach. Examples of using the tools on large-scale MPI applications are presented.

UR - https://www.scopus.com/pages/publications/33646152753

U2 - 10.1007/11557265_41

DO - 10.1007/11557265_41

M3 - Conference contribution

AN - SCOPUS:33646152753

SN - 3540290095

SN - 9783540290094

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

SP - 309

EP - 316

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

T2 - 12th European PVM/MPI Users' Group Meeting - Recent Advances in Parallel Virtual Machine and Message Passing Interface

Y2 - 18 September 2005 through 21 September 2005

ER -

Moore S, Wolf F, Dongarra J, Shende S, Malony A, Mohr B. A scalable approach to MPI application performance analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. p. 309-316. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11557265_41

A scalable approach to MPI application performance analysis

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