Table Of ContentPERFORMANCE ANALYSIS AND
GRID COMPUTING
PERFORMANCE
ANALYSIS AND
GRID COMPUTING
Selected Articles from the Workshop on
Performance Analysis and Distributed Computing
August 19-23, 2002, Dagstuhl, Germany
Edited by
Vladimir Getov
University of Westminster, UK
Michael Gerndt
Technical University Munich, Germany
Adolfy Hoisie
Los Alamos National Laboratory, USA
Allen Malony
University of Oregon-Eugene, USA
Barton Miller
University of Wisconsin-Madison, USA
SPRINGER SCIENCE+BUSINESS MEDIA, LLC
Library of Congress Cataloging-in-Publication Data
A CLP. Catalogue record for this book is available from the Library of Congress.
Performance Analysis and Grid Computing
Edited by Vladimir Getov, Michael Gerndt, Adolfy Hoisie, Allen Malony and
Barton Miller
ISBN 978-1-4613-5038-5 ISBN 978-1-4615-0361-3 (eBook)
DOI 10.1007/978-1-4615-0361-3
Copyright © 2004 by Springer Science+Business Media New York
Originally published by Kluwer Academic Publishers in 2004
Softcover reprint of the hardcover 1st edition 2004
All rights reserved. No part of this work may be reproduced, stored in a retrieval
system, or transmitted in any form or by any means, electronic, mechanical, photo
copying, microfilming, recording, or otherwise, without written permission from the
Publisher Springer Science+Business Media, LLC,
with the exception of any material supplied specifically for the
purpose of being entered and executed on a computer system, for exclusive use by the
purchaser of the work.
Printed on acid-free paper.
Contents
Preface vii
Contributing Authors xi
Part I Performance Modeling and Analysis
Different Approaches to Automatic Performance Analysis of Distributed
~~~ 3
Tomas Margalef, Josep Jorba. Oleg Morajko. Anna Morajko. Emilio Luque
Performance Modeling of Deterministic Transport Computations 21
Darren J. Kerbyson. Adolfy Hoisie, Shawn D. Pautz
Performance Optimization ofRK Methods Using Block-based Pipelining 41
Matthias Korch, Thomas Rauber, Gudula Runger
Performance Evaluation of Hybrid Parallel Programming Paradigms 57
Achal Prabhakar, Vladimir Getov
Performance Modelling for Task-Parallel Programs 77
Matthias Kuhnemann, Thomas Rauber, Gudula Runger
Collective Communication Patterns on the Quadrics Network 93
Salvador Coil. Jose Duato. Francisco J. Mora, Fabrizio Petrini. Adolfy Hoisie
Part II Performance Tools and Systems
The Design of a Performance Steering System for Component-based
Grid Applications 111
Ken Mayes, Graham D. Riley, Rupert W. Ford, Mikel Lujan. Len Freeman,
Cliff Addison
Advances in the TAU Performance System 129
Allen D. Malony. Sameer Shende, Robert Bell. Kai Li, Li Li. Nick Trebon
Uniform Resource Visualization: Software and Services 145
Kukjin Lee. Diane T. Rover
vi PERFORMANCE ANALYSIS AND GRID COMPUTING
A Performance Analysis Tool for Interactive Grid Applications 161
Marian Bubak. Wlodzimierz Funika. Roland Wismiiller
Dynamic Instrumentation for Java Using a Virtual JVM 175
Kwok Yeung. Paul H.J. Kelly. Sarah Bennett
Aksum: A Performance Analysis Tool for Parallel and Distributed
Applications 189
Thomas Fahringer, Clovis Seragiotto. Jr.
Part III Grid Performance and Applications
Commercial Applications of Grid Computing 211
Catherine Crawford. Daniel Dias. Arun Iyengar, Marcos Novaes. Li Zhang
Mesh Generation and Optimistic Computation on the Grid 231
Nikos Chrisochoides. Craig Lee. Bruce Lowekamp
Grid Performance and Resource Management using Mobile Agents 251
Beniamino Di Martino. Omer F. Rana
Monitoring of Interactive Grid Applications 265
Bartosz Balis. Marian Bubak. Wlodzimierz Funika. Tomasz Szepieniec.
Roland Wismiiller
The UNICORE Grid and Its Options for Performance Analysis 275
Sven Haubold. Hartmut Mix. Wolfgang E. Nagel. Mathilde Romberg
Index 289
Preface
Since the invention of the electronic computers, achieving higher perfor
mance of both systems and applications has always been a main concern and
motivation for the research community. Given the tremendous pace of evo
lution in information technologies, this field demands continuous efforts for
innovations in performance theory, methodologies, and tools. The joint devel
opment of both performance science and performance technology spans a rich
spectrum of related research areas, such as performance modeling, evaluation,
instrumentation, measurement, analysis, monitoring, interpretation, optimiza
tion, and prediction.
Past and current research in computer performance analaysis has focused
primarily on dedicated parallel machines. However, future applications in the
area of high-performance computing will not only use individual parallel sys
tems but a large set of networked resources. This scenario of computational
and data Grids is attracting a great deal of attention from both computer and
computational scientists. In addition to the inherent complexity of parallel ma
chines, the sharing and transparency of the available resources introduce new
challenges on performance analysis, techniques, and systems. In order to meet
those challenges, a multi-disciplinary approach to the multi-faceted problems
of performance is required. New degrees of freedom will come into play with a
direct impact on the performance of Grid computing, including wide-area net
work performance, quality-of-service (QoS), heterogeneity, and middleware
systems, to mention only a few.
Reflecting this new reality, the Dagstuhl Workshop on Performance Analysis
and Distributed Computing I , organized by members of the European Working
Group APART2, was designed to bring together researchers from both the high
performance computing and the distributed computing areas. Indeed, attendees
with expertise in a variety of topics in computer and computational sciences
arrived in Dagstuhl at the end of August 2002 to discuss the state-of-the-art and
I http://www.dagstuhl.del023411
2 http:www.fz-juelich.delapart
viii PERFORMANCE ANALYSIS AND GRID COMPUTING
the future of computer performance research as it applies to systems, applica
tions, and Grids. The topics covered by the workshop were grouped into five
areas:
1 Performance Modeling and Analysis. The contributions to this area ex
plored performance prediction and its application in different contexts,
emphasizing on distributes shared memory multiprocessors, large scale
systems, task parallel programs, and Grid computing.
2 Novel Architectures. This area covered quite diverse aspects, includ
ing mobile agents, cellular architectures in the context of future high
end computer systems such as IBM's Blue Gene project, and high
performance interconnects such as the Quadrics network.
3 Performance Tools and Systems. Two key issues were addressed in this
area, namely scalability of performance analysis tools, and tool automa
tion. Other presentations covered performance analysis for Java, perfor
mance visualization, and data management.
4 Grid Performance. The presentations in this area gave an overview of the
current approaches to performance monitoring and analysis in several
Grid-related European projects, such as CrossGrid, UNICORE, Data
Grid, and DAMIEN.
5 Grid Computing and Applications. The presentations concentrated on
programming aspects of Grid computing infrastructures and Grid appli
cations. In addition, performance aspects of Web and Grid services were
introduced and analyzed using application case studies.
The presentations during the seminar led to two major threads of evening
gatherings and discussions centered on Grid Computing and Future Architec
tures. The main open questions addressed in the Grid Computing discussion
were:
• Will QoS become a reality in the context of Grids? Most of the partic
ipants expressed the opinion that this will depend significantly on eco
nomic issues. If users pay for using the Grid services, performance
guarantees would be required.
• What are the new aspects of performance optimization in this area when
applied to computational Grids? In Grid environments, performance op
timization focuses mainly on efficient scheduling decisions in dynamic
and heterogeneous infrastructures, dynamic performance tuning, and per
formance steering.
PREFACE ix
• Does the analogy between the Grid computing and the electrical power
grid hold and, if yes, how different are they? Two main differences
were identified: first, users transfer information via the Grid which raises
major security problems, and second, the variety of Grid services and
resources is much richer, which makes performance steering, resource
management, and accounting very important topics for research and de
velopment.
• How will Grids be used? The majority of attendees favored the concept
of virtual organizations as the main usage of the Grid as opposed to the
metacomputing style of applications. The main programming paradigm
for Grid computing could follow a components-based approach.
In the area of future architectures, the discussions centered around funda
mental and practical topics likely to impact the development of next generation
systems, such as:
• How will the available chip space be used? Can scalar and vector pro
cessors be combined?
• What will be the impact of recent research on processor in memory
systems, multiprocessor, and multi-threading architectures on the future
high-end computers?
• When will Quantum Computing become a reality? The prevailing opin
ion seemed to be that the development of this technology might take
approximately another 50 years.
• What will be the role of reconfigurable architectures in the future dis
tributed and Grid computing systems?
The selected contributions which we are proud to preface here, are an en
capsulation of a scientifically rich event. The articles are organized in three
parts: Performance Modeling and Analysis, Performance Tools and Systems,
and Grid Performance and Applications.
To conclude, we would like to thank all the participants for their contribution
to making the workshop a resounding success; the staff of the International
Conference and Research Center for Computer Science at Schloss Dagstuhl
for their professional support in the organization; and, last but not least, all the
authors that contributed papers for publication in this volume.
Our thanks also go to the European Commission for sponsoring this vol
ume of selected articles from the workshop via the European Working Group
APART (Automatic Performance Analysis: Real Tools), project number IST-
2000-28077.
VLADIMIR GETOV, MICHAEL GERNDT, AoOLFY HOISIE, ALLEN MALONY, BARTON MILLER
Contributing Authors
ClifT Addison Computing Services Department, University of Liverpool, Liv
erpool L69 3BX, UK ([email protected])
Bartosz Balis Institute of Computer Science, AGH, al. Mickiewicza 30, 30-059
Krakow, Poland ([email protected])
Robert Bell Computer and Information Science Department, University of
Oregon, Eugene, OR 97403, USA ([email protected])
Sarah Bennett Department of Computing, Imperial College, 180 Queen's Gate,
London SW7 2BZ, UK ([email protected])
Marian Bubak Institute of Computer Science, AGH, at. Mickiewicza 30,
30-059 Krakow, Poland ([email protected])
Nikos Chrisochoides Department of Computer Science, College of William
and Mary, P.O. Box 8795, Williamsburg, VA 23187, USA ([email protected])
Salvador Coli Department of Electronic Engineering, Technical University of
Valencia, Camino de Vera, 46022 Valencia, Spain ([email protected])
Catherine Crawford IBM T. J. Watson Research Center, P.O. Box 704, York
town Heights, NY 10598, USA ([email protected])
Daniel Dias IBM T. 1. Watson Research Center, P.O. Box 704, Yorktown
Heights, NY 10598, USA ([email protected])
xii PERFORMANCE ANALYSIS AND GRID COMPUTING
Jose Duato Department of Electronic Engineering, Technical University of
Valencia, Camino de Vera, 46022 Valencia, Spain ([email protected])
Thomas Fahringer Institute for Software Science, University of Vienna,
Liechtenstein Str. 22, A-1090 Vienna, Austria ([email protected])
Rupert Ford Centre for Novel Computing, University of Manchester, Manch
ester M13 9PL, UK ([email protected])
Len Freeman Centre for Novel Computing, University of Manchester, Manch
ester M13 9PL, UK ([email protected])
Wlodzimierz Funika Institute of Computer Science, AGH, al. Mickiewicza
30,30-059 Krakow, Poland ([email protected])
Vladimir Getov School of Computer Science, University of Westminster, Wat
ford Rd, Harrow, London HAl 3TP, UK ([email protected])
Sven Haubold Center for High Performance Computing (ZHR), Technical
University of Dresden, 01062 Dresden, Germany ([email protected])
Adolfy Hoisie Performance and Architectures Laboratory, CCS-3, Los Alamos
National Laboratory, P.O. Box 1663, Los Alamos, NM 87545, USA
(hoisie@ lanl.gov)
Arun Iyengar IBM T. 1. Watson Research Center, P.O. Box 704, Yorktown
Heights, NY 10598, USA ([email protected])
Josep Jorba Computer Science Department, Universitat Autonoma de
Barcelona, 08193 Bellaterra, Spain ([email protected])
Paul H J Kelly Department of Computing, Imperial College, 180 Queen's Gate,
London SW7 2BZ, UK ([email protected])
Darren J. Kerbyson Performance and Architectures Laboratory, CCS-3, Los
Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545, USA
([email protected])
