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Dagstuhl Seminar Proceedings, Volume 5501

Part of: Series: Dagstuhl Seminar Proceedings (DagSemProc)

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published at: 2006-03-22
Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik

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Document

DOI: 10.4230/DagSemProc.05501.1

05501 Abstracts Collection – Automatic Performance Analysis

Authors: Hans Michael Gerndt, Allen Malony, Barton P. Miller, and Wolfgang Nagel

Abstract

From 12.12.05 to 16.12.05, the Dagstuhl Seminar 05501 ``Automatic Performance Analysis'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

Cite as

Hans Michael Gerndt, Allen Malony, Barton P. Miller, and Wolfgang Nagel. 05501 Abstracts Collection – Automatic Performance Analysis. In Automatic Performance Analysis. Dagstuhl Seminar Proceedings, Volume 5501, pp. 1-13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{gerndt_et_al:DagSemProc.05501.1,
  author =	{Gerndt, Hans Michael and Malony, Allen and Miller, Barton P. and Nagel, Wolfgang},
  title =	{{05501 Abstracts Collection – Automatic Performance Analysis}},
  booktitle =	{Automatic Performance Analysis},
  pages =	{1--13},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5501},
  editor =	{Hans Michael Gerndt and Allen Malony and Barton P. Miller and Wolfgang Nagel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05501.1},
  URN =		{urn:nbn:de:0030-drops-5085},
  doi =		{10.4230/DagSemProc.05501.1},
  annote =	{Keywords: Parallel computing, performance analysis, programming environments}
}

Document

DOI: 10.4230/DagSemProc.05501.2

05501 Summary – Automatic Performance Analysis

Authors: Hans Michael Gerndt, Allen Malony, Barton P. Miller, and Wolfgang Nagel

Abstract

The Workshop on Automatic Performance Analysis (WAPA 2005, Dagstuhl Seminar 05501), held December 13-16, 2005, brought together performance researchers, developers, and practitioners with the goal of better understanding the methods, techniques, and tools that are needed for the automation of performance analysis for high performance computing.

Cite as

Hans Michael Gerndt, Allen Malony, Barton P. Miller, and Wolfgang Nagel. 05501 Summary – Automatic Performance Analysis. In Automatic Performance Analysis. Dagstuhl Seminar Proceedings, Volume 5501, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{gerndt_et_al:DagSemProc.05501.2,
  author =	{Gerndt, Hans Michael and Malony, Allen and Miller, Barton P. and Nagel, Wolfgang},
  title =	{{05501 Summary – Automatic Performance Analysis}},
  booktitle =	{Automatic Performance Analysis},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5501},
  editor =	{Hans Michael Gerndt and Allen Malony and Barton P. Miller and Wolfgang Nagel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05501.2},
  URN =		{urn:nbn:de:0030-drops-5069},
  doi =		{10.4230/DagSemProc.05501.2},
  annote =	{Keywords: Automatic Performance Analysis, Parallel Computers, Performance Tuning}
}

Document

DOI: 10.4230/DagSemProc.05501.3

Development and Tuning Framework of Master/Worker Applications

Authors: Paola Caymes-Scutari, Anna Morajko, Eduardo César, Genaro Costa, José G. Mesa, Tomàs Margalef, Joan Sorribes, and Emilio Luque

Abstract

Parallel/distributed programming is a complex task that requires a high degree of expertise to fulfill the expectations of high performance computation. The Master/Worker paradigm is one of the most commonly used because it is easy to understand and there is a wide range of applications that match this paradigm. However, there are certain features, such as data distribution and the number of workers that must be tuned properly to obtain adequate performance. In most cases such features cannot be tuned statically since they depend on the particular conditions of each execution. In this paper, we show a dynamic tuning environment that is based on a theoretical model of Master/Worker behavior and allows for the adaptation of such applications to the dynamic conditions of execution. The environment includes a pattern based application development framework that allows the user to concentrate on the design phase and makes it easier to overcome performance bottlenecks.

Cite as

Paola Caymes-Scutari, Anna Morajko, Eduardo César, Genaro Costa, José G. Mesa, Tomàs Margalef, Joan Sorribes, and Emilio Luque. Development and Tuning Framework of Master/Worker Applications. In Automatic Performance Analysis. Dagstuhl Seminar Proceedings, Volume 5501, pp. 1-6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{caymesscutari_et_al:DagSemProc.05501.3,
  author =	{Caymes-Scutari, Paola and Morajko, Anna and C\'{e}sar, Eduardo and Costa, Genaro and Mesa, Jos\'{e} G. and Margalef, Tom\`{a}s and Sorribes, Joan and Luque, Emilio},
  title =	{{Development and Tuning Framework of Master/Worker Applications}},
  booktitle =	{Automatic Performance Analysis},
  pages =	{1--6},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5501},
  editor =	{Hans Michael Gerndt and Allen Malony and Barton P. Miller and Wolfgang Nagel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05501.3},
  URN =		{urn:nbn:de:0030-drops-5057},
  doi =		{10.4230/DagSemProc.05501.3},
  annote =	{Keywords: Dynamic tuning, performance analysis, performance model}
}

Document

DOI: 10.4230/DagSemProc.05501.4

Holistic Hardware Counter Performance Analysis of Parallel Programs

Authors: Brian J. N. Wylie, Bernd Mohr, and Felix Wolf

Abstract

The KOJAK toolkit has been augmented with refined hardware performance counter support, including more convenient measurement specification, additional metric derivations and hierarchical structuring, and an extended algebra for integrating multiple experiments. Comprehensive automated analysis of a hybrid OpenMP/MPI parallel program, the ASC Purple sPPM benchmark, is demonstrated with performance experiments on equisized POWER4-II-based IBM Regatta p690+ cluster, Opteron-based Cray XD1 cluster and UltraSPARC-IV-based Sun Fire E25000 systems. Automatically assessed communication and synchronisation performance properties, combined with a rich set of measured and derived counter metrics, provide a holistic analysis context and facilitate multi-platform comparison.

Cite as

Brian J. N. Wylie, Bernd Mohr, and Felix Wolf. Holistic Hardware Counter Performance Analysis of Parallel Programs. In Automatic Performance Analysis. Dagstuhl Seminar Proceedings, Volume 5501, pp. 1-30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{wylie_et_al:DagSemProc.05501.4,
  author =	{Wylie, Brian J. N. and Mohr, Bernd and Wolf, Felix},
  title =	{{Holistic Hardware Counter Performance Analysis of Parallel Programs}},
  booktitle =	{Automatic Performance Analysis},
  pages =	{1--30},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5501},
  editor =	{Hans Michael Gerndt and Allen Malony and Barton P. Miller and Wolfgang Nagel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05501.4},
  URN =		{urn:nbn:de:0030-drops-5071},
  doi =		{10.4230/DagSemProc.05501.4},
  annote =	{Keywords: Parallel program execution tracing, hardware performance counters, automated structured analysis, performance comparison}
}

Document

DOI: 10.4230/DagSemProc.05501.5

Remote Performance Monitor (RPM)

Authors: Chandra Krintz and Selim Gurun

Abstract

Mobile, resource-constrained, battery-powered devices have emerged as key access points to the world's digital infrastructure. To enable our understanding of the performance of these devices, we must be able to efficiently collect accurate profile data from these devices after they are deployed in the field. Moreover, understanding the full-system power and energy behavior of these systems for real programs is vital if users are to accurately characterize, model, and develop effective techniques for extending battery life. Unfortunately, extant approaches to measuring and characterizing power and energy consumption focus on high-end processors, do not consider the complete device, employ inaccurate (program-only) simulation, rely on inaccurate, course-grained battery level data from the device, or employ expensive power measurement tools that are difficult to share across research groups and students. To address these issues, we developed remote performance monitor (RPM). The first component of RPM is an efficient technique for collecting accurate sample-based program profiles. The key to the efficacy of this technique is that we identify when to sample using the repeating patterns in program execution, phases. To enable fine-grained, full-system characterization of embedded computers, we couple and unify phase-aware profiling, hardware performance monitoring, and power and energy measurement within RPM. RPM consists of a tightly coupled set of components which (1) control lab equipment for power measurements and analysis, (2) configure target system characteristics at run-time (such as CPU and memory bus speed), (3) collect target system data using on-board hardware performance monitors (HPMs) and (4) provide a remote access interface. Users of RPM can submit and configure experiments that execute programs on the RPM target device (currently a Stargate sensor platform that is very similar to an HP iPAQ) to collect very accurate power, energy, and CPU performance data with high resolution.

Cite as

Chandra Krintz and Selim Gurun. Remote Performance Monitor (RPM). In Automatic Performance Analysis. Dagstuhl Seminar Proceedings, Volume 5501, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{krintz_et_al:DagSemProc.05501.5,
  author =	{Krintz, Chandra and Gurun, Selim},
  title =	{{Remote Performance Monitor (RPM)}},
  booktitle =	{Automatic Performance Analysis},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5501},
  editor =	{Hans Michael Gerndt and Allen Malony and Barton P. Miller and Wolfgang Nagel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05501.5},
  URN =		{urn:nbn:de:0030-drops-5046},
  doi =		{10.4230/DagSemProc.05501.5},
  annote =	{Keywords: Profiling, hardware performance monitors, sampling, phase behavior, power, energy}
}

Filters

Authors
C
Caymes-Scutari, Paola
César, Eduardo
Costa, Genaro
G
Gerndt, Hans Michael
Gurun, Selim
K
Krintz, Chandra
L
Luque, Emilio
M
Malony, Allen
Margalef, Tomàs
Mesa, José G.
Miller, Barton P.
Mohr, Bernd
Morajko, Anna
N
Nagel, Wolfgang
S
Sorribes, Joan
W
Wolf, Felix
Wylie, Brian J. N.

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