research-article

Performance analysis of idle programs

Authors:

Matthew Arnold,

Nick MitchellAuthors Info & Claims

OOPSLA '10: Proceedings of the ACM international conference on Object oriented programming systems languages and applications

Pages 739 - 753

https://doi.org/10.1145/1869459.1869519

Published: 17 October 2010 Publication History

Abstract

This paper presents an approach for performance analysis of modern enterprise-class server applications. In our experience, performance bottlenecks in these applications differ qualitatively from bottlenecks in smaller, stand-alone systems. Small applications and benchmarks often suffer from CPU-intensive hot spots. In contrast, enterprise-class multi-tier applications often suffer from problems that manifest not as hot spots, but as idle time, indicating a lack of forward motion. Many factors can contribute to undesirable idle time, including locking problems, excessive system-level activities like garbage collection, various resource constraints, and problems driving load.

We present the design and methodology for WAIT, a tool to diagnosis the root cause of idle time in server applications. Given lightweight samples of Java activity on a single tier, the tool can often pinpoint the primary bottleneck on a multi-tier system. The methodology centers on an informative abstraction of the states of idleness observed in a running program. This abstraction allows the tool to distinguish, for example, between hold-ups on a database machine, insufficient load, lock contention in application code, and a conventional bottleneck due to a hot method. To compute the abstraction, we present a simple expert system based on an extensible set of declarative rules.

WAIT can be deployed on the fly, without modifying or even restarting the application. Many groups in IBM have applied the tool to diagnosis performance problems in commercial systems, and we present a number of examples as case studies.

References

[1]

}}M. K. Aguilera, J. C. Mogul, J. L. Wiener, P. Reynolds, and A. Muthitacharoen. Performance debugging for distributed systems of black boxes. In Symposium on Operating System Principles. ACM, 2003.

Digital Library

[2]

}}W. P. Alexander, R. F. Berry, F. E. Levine, and R. J. Urquhart. A unifying approach to performance analysis in the java environment. IBM Systems Journal, 39(1), 2000.

Digital Library

[3]

}}G. Ammons, J.-D. Choi, M. Gupta, and N. Swamy. Finding and removing performance bottlenecks in large systems. In The European Conference on Object-Oriented Programming. Springer, 2004.

[4]

}}B. Darmawan, R. Gummadavelli, S. Kuppusamy, C. Tan, D. Rintoul, H. Anglin, H. Chuan, A. Subhedar, A. Firtiyan, P. Nambiar, P. Lall, R. Dhall, and R. Pires. IBM Tivoli Composite Application Manager Family: Installation, Configuration, and Basic Usage. http://www.redbooks.ibm.com/abstracts/sg247151.html?Open.

[5]

}}W. De Pauw, E. Jensen, N. Mitchell, G. Sevitsky, J. Vlissides, and J. Yang. Visualizing the execution of Java programs. In Software Visualization, State-of-the-art Survey, volume 2269 of Lecture Notes in Computer Science. Springer-Verlag, 2002.

Digital Library

[6]

}}R. J. Hall. Cpprofj: Aspect-capable call path profiling of multi-threaded java applications. In Automated Software Engineering, pages 107--116. IEEE Computer Society Press, 2002.

Digital Library

[7]

}}J. K. Hollingsworth. Finding Bottlenecks in Large-scale Parallel Programs. PhD thesis, University of Wisconsin, Aug. 1994.

Digital Library

[8]

}}E. W. Host and B. M. Ostvold. Debugging method names. In The European Conference on Object-Oriented Programming. Springer, 2009.

Digital Library

[9]

}}N. Mitchell, G. Sevitsky, and H. Srinivasan. Modeling runtime behavior in framework-based applications. The European Conference on Object-Oriented Programming, 2006.

Digital Library

[10]

}}K. Srinivas and H. Srinivasan. Summarizing application performance from a components perspective. Foundations of Software Engineering, 30(5):136--145, 2005.

Digital Library

[11]

}}Borland Software Corporation. OptimizeItTM Enterprise Suite. http://www.borland.com/us/products/optimizeit, 2005.

[12]

}}Compuware. Compuware Vantage Analyzer. http://www.compuware.com/solutions/e2e brochures factsheets.asp.

[13]

}}Eclipse. Eclipse Test & Performance Tools Platform Project. http://www.eclipse.org/tptp.

[14]

}}HP. HP Diagnostics for J2EE.

[15]

}}IBM. Compuware Vantage Analyzer. http://alphaworks.ibm.com/tech/dcva4j/download.

[16]

}}IBM. IBM OMEGAMON XE for WebSphere. http://www-01.ibm.com/software/tivoli/products/omegamon-xe-was.

[17]

}}IBM. Thread and Monitor Dump Analyzer for Java. http://www.alphaworks.ibm.com/tech/jca.

[18]

}}IBM. Tivoli Monitoring for Transaction Performance. http://www-01.ibm.com/software/tivoli/products/monitor-transaction.

[19]

}}Sun Microsystems. HPROF JVM profiler. http://java.sun.com/developer/technicalArticles/Programming/HPROF.html, 2005.

[20]

}}Yourkit LLC. Yourkit profiler. http://www.yourkit.com.

[21]

}}G. Xu, M. Arnold, N. Mitchell, A. Rountev, and G. Sevitsky. Go with the flow: profiling copies to find runtime bloat. In PLDI '09: Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation, pages 419--430, New York, NY, USA, 2009. ACM.

Digital Library

[22]

}}W. Xu, L. Huang, A. Fox, D. Patterson, and M. I. Jordan. Detecting large-scale system problems by mining console logs. In Symposium on Operating System Principles. ACM, 2009.

Digital Library

[23]

}}D. Yuan, H. Mai, W. Xiong, L. Tan, Y. Zhou, and S. Pasupathy. Sherlog: Error diagnosis by connecting clues from run-time logs. In Architectural Support for Programming Languages and Operating Systems, Mar. 2010.

Digital Library

[24]

}}Y. Zhao, J. Shi, K. Zheng, H. Wang, H. Lin, and L. Shao. Allocation wall: a limiting factor of java applications on emerging multi-core platforms. In OOPSLA '09: Proceeding of the 24th ACM SIGPLAN conference on Object oriented programming systems languages and applications, pages 361--376, New York, NY, USA, 2009. ACM.

Digital Library

Cited By

Liao LLi HShang WSporea CToma ASajedi SChandra SBlincoe KTonella P(2023)Adapting Performance Analytic Techniques in a Real-World Database-Centric System: An Industrial Experience ReportProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3613893(1855-1866)Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1145/3611643.3613893
Li JZhang YLu SGunawi HGu XHuang FLi D(2023)Performance Bug Analysis and Detection for Distributed Storage and Computing SystemsACM Transactions on Storage10.1145/358028119:3(1-33)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3580281
Rezazadeh MEzzati-Jivan NAzhari SDagenais M(2022)Performance evaluation of complex multi-thread applications through execution path analysisPerformance Evaluation10.1016/j.peva.2022.102289155-156(102289)Online publication date: Jun-2022
https://doi.org/10.1016/j.peva.2022.102289
Show More Cited By

Index Terms

Performance analysis of idle programs

Recommendations

Performance analysis of idle programs
OOPSLA '10

This paper presents an approach for performance analysis of modern enterprise-class server applications. In our experience, performance bottlenecks in these applications differ qualitatively from bottlenecks in smaller, stand-alone systems. Small ...
Diagnosing performance overheads in the xen virtual machine environment
VEE '05: Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments

Virtual Machine (VM) environments (e.g., VMware and Xen) are experiencing a resurgence of interest for diverse uses including server consolidation and shared hosting. An application's performance in a virtual machine environment can differ markedly from ...
Fine-grained Nested Virtual Machine Performance Analysis Through First Level Hypervisor Tracing
CCGrid '17: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

Nowadays, nested VMs are often being used to address compatibility issues, security concerns, software scaling and continuous integration scenarios. With the increased adoption of nested VMs, there is a need for newer techniques to troubleshoot any ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

OOPSLA '10: Proceedings of the ACM international conference on Object oriented programming systems languages and applications

October 2010

984 pages

ISBN:9781450302036

DOI:10.1145/1869459

General Chairs:
William R. Cook
University of Texas at Austin
,
Siobhán Clarke
Trinity College Dublin
,
Program Chairs:
Martin Rinard
MIT
,
Kevin J. Sullivan
University of Virginia
,
Daniel H. Steinberg
Dim Sum Thinking Inc.

ACM SIGPLAN Notices Volume 45, Issue 10
OOPSLA '10
October 2010
957 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/1932682
Issue’s Table of Contents

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGPLAN: ACM Special Interest Group on Programming Languages

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SPLASH '10

Sponsor:

SIGPLAN

SPLASH '10: Systems Programming Languages and Applications: Software for Humanity

October 17 - 21, 2010

Nevada, Reno/Tahoe, USA

Acceptance Rates

Overall Acceptance Rate 268 of 1,244 submissions, 22%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

104
Total Citations
View Citations
562
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)8

Reflects downloads up to 16 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Liao LLi HShang WSporea CToma ASajedi SChandra SBlincoe KTonella P(2023)Adapting Performance Analytic Techniques in a Real-World Database-Centric System: An Industrial Experience ReportProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3613893(1855-1866)Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1145/3611643.3613893
Li JZhang YLu SGunawi HGu XHuang FLi D(2023)Performance Bug Analysis and Detection for Distributed Storage and Computing SystemsACM Transactions on Storage10.1145/358028119:3(1-33)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3580281
Rezazadeh MEzzati-Jivan NAzhari SDagenais M(2022)Performance evaluation of complex multi-thread applications through execution path analysisPerformance Evaluation10.1016/j.peva.2022.102289155-156(102289)Online publication date: Jun-2022
https://doi.org/10.1016/j.peva.2022.102289
Liao LChen JLi HZeng YShang WSporea CToma ASajedi S(2021)Locating Performance Regression Root Causes in the Field Operations of Web-based Systems: An Experience ReportIEEE Transactions on Software Engineering10.1109/TSE.2021.3131529(1-1)Online publication date: 2021
https://doi.org/10.1109/TSE.2021.3131529
Nair RField TAmaral JKoziolek ATrubiani CIosup A(2020)GAPP: A Fast Profiler for Detecting Serialization Bottlenecks in Parallel Linux ApplicationsProceedings of the ACM/SPEC International Conference on Performance Engineering10.1145/3358960.3379136(257-264)Online publication date: 20-Apr-2020
https://dl.acm.org/doi/10.1145/3358960.3379136
Zhao YXiao LWang XChen ZChen BLiu Y(2020)Butterfly Space: An Architectural Approach for Investigating Performance Issues2020 IEEE International Conference on Software Architecture (ICSA)10.1109/ICSA47634.2020.00027(202-213)Online publication date: Mar-2020
https://doi.org/10.1109/ICSA47634.2020.00027
Ocariza FZhao B(2020)Localizing software performance regressions in web applications by comparing execution timelinesSoftware Testing, Verification and Reliability10.1002/stvr.175031:5Online publication date: 11-Aug-2020
https://doi.org/10.1002/stvr.1750
Carver DGouicem RLozi JSopena JLepers BZwaenepoel WPalix NLawall JMuller G(2019)Fork/Wait and Multicore Frequency ScalingProceedings of the 10th Workshop on Programming Languages and Operating Systems10.1145/3365137.3365400(53-59)Online publication date: 27-Oct-2019
https://dl.acm.org/doi/10.1145/3365137.3365400
Inagaki TUeda YNakaike TOhara MApte VDi Marco ALitoiu MMerseguer J(2019)Profile-based Detection of Layered BottlenecksProceedings of the 2019 ACM/SPEC International Conference on Performance Engineering10.1145/3297663.3310296(197-208)Online publication date: 4-Apr-2019
https://dl.acm.org/doi/10.1145/3297663.3310296
Bouksiaa MTrahay FLescouet AVoron GDulong RGuermouche ABrunet EThomas G(2019)Using Differential Execution Analysis to Identify Thread InterferenceIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2019.292748130:12(2866-2878)Online publication date: 1-Dec-2019
https://doi.org/10.1109/TPDS.2019.2927481
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents