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GrenchMark : A Framework for Analyzing, Testing, and Comparing Grids

GrenchMark : A Framework for Analyzing, Testing, and Comparing Grids. A. Iosup , D.H.J. Epema. PDS Group, ST/EWI, TU Delft. CCGrid 2006. Outline. Introduction and Motivation The GrenchMark Framework Past and Current Experience with GrenchMark A GrenchMark Success Story Future Work

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GrenchMark : A Framework for Analyzing, Testing, and Comparing Grids

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  1. GrenchMark: A Framework for Analyzing, Testing, and Comparing Grids A. Iosup, D.H.J. Epema PDS Group, ST/EWI, TU Delft CCGrid 2006

  2. Outline • Introduction and Motivation • The GrenchMark Framework • Past and Current Experience with GrenchMark • A GrenchMark Success Story • Future Work • Conclusions

  3. The Generic Problem of Analyzing, Testing, and Comparing Grids • Use cases for automatically analyzing, testing, and comparing Grids • Comparisons for system design and procurement • Functionality testing and system tuning • Performance testing/analysis of grid applications • … • For grids, this problem is hard! • Testing in real environments is difficult • Grids change rapidly • Validity of tests • …

  4. A Generic Solution to Analyzing, Testing, and Comparing Grids • “ Generate and run synthetic grid workloads, based on real and synthetic applications “ • Current alternatives (not covering all problems) • Benchmarking with real/synthetic applications (representative?) • User-defined test management (statistically sound?) • Advantages of using synthetic grid workloads • Statistically sound composition of benchmarks • Statistically sound test management • Generic: cover the use cases’ broad spectrum (to be shown)

  5. GrenchMark: a Framework for Analyzing, Testing, and Comparing grids • What’s in a name?grid benchmark→ working towards a generic tool for the whole community: help standardizing the testing procedures, but benchmarks are too early; we use synthetic grid workloads instead • What’s it about?A systematic approach to analyzing, testing, and comparing grid settings, based on synthetic workloads • A set of metrics for analyzing grid settings • A set of representative grid applications • Both real and synthetic • Easy-to-use tools to create synthetic grid workloads • Flexible, extensible framework

  6. GrenchMark: Iterative Research Roadmap

  7. GrenchMark: Iterative Research Roadmap Simple functional system A.Iosup, J.Maassen, R.V.van Nieuwpoort, D.H.J.Epema, Synthetic Grid Workloads with Ibis, KOALA, and GrenchMark, CoreGRID IW, Nov 2005.

  8. GrenchMark: Iterative Research Roadmap Open- GrenchMark CommunityEffort Complex extensible system This work

  9. GrenchMark Overview: Easy to Generate and Run Synthetic Workloads

  10. Workload structure User-defined and statistical models Dynamic jobs arrival Burstiness and self-similarity Feedback, background load Machine usage assumptions Users, VOs Metrics A(W) Run/Wait/Resp. Time Efficiency, MakeSpan Failure rate [!] (Grid) notions Co-allocation, interactive jobs, malleable, moldable, … Measurement methods Long workloads Saturated / non-saturated system Start-up, production, and cool-down scenarios Scaling workload to system Applications Synthetic Real Workload definition language Base language layer Extended language layer Other Can use thesame workload for both simulations and real environments … but More Complicated Than You Think

  11. GrenchMark Overview: Unitary and Composite Applications • Unitary applications • sequential,MPI, Java RMI, Ibis, … • Composite applications • Bag of tasks • Chain of jobs • Direct Acyclic Graph-based (Standard Task Graph Archive)

  12. GrenchMark Overview: Workload Description Files • Format: Number of jobs Co-allocation and number of components Language extensions Composition and application types Inter-arrival and start time Combining four workloads into one

  13. Using GrenchMark: Grid System Analysis • Performance testing: test the performance of an application (for sequential, MPI, Ibis applications) • Report runtimes, waiting times, grid middleware overhead • Automatic results analysis • What-if analysis: evaluate potential situations • System change • Grid inter-operability • Special situations: spikes in demand

  14. Using GrenchMark: Functionality Testing in Grid Environments • System functionality testing: show the ability of the system to run various types of applications • Report failure rates [ arguably, functionality in grids is even more important than performance !  10% job failure rate in a controlled system like the DAS ] • Periodic system testing: evaluate the current state of the grid • Replay workloads

  15. Using GrenchMark: Comparing Grid Settings • Single-site vs. co-allocated jobs: compare the success rate of single-site and co-allocated jobs, in a system without reservation capabilities • Single-site jobs 20% better vs. small co-allocated jobs (<32 CPUs), 30% better vs. large co-allocated jobs [setting and workload-dependent !] • Unitary vs. composite jobs: compare the success rate of unitary and composite jobs, with and without failure handling mechanisms • Both 100% with simple retry mechanism [setting and workload-dependent !]

  16. A GrenchMark Success Story:Releasing the Koala Grid Scheduler on the DAS • Koala [ http://www.st.ewi.tudelft.nl/koala/] • Grid Scheduler with co-allocation capabilities • DAS: The Dutch Grid, ~200 researchers • Initially • Koala, a tested (!) scheduler, pre-release version • Test specifics • 3 different job submission modules • Workloads with different jobs requirements, inter-arrival rates, co-allocated v. single site jobs… • Evaluate: job success rate, Koala overhead and bottlenecks • Results • 5,000+jobs successfully run (all workloads); functionality tests • 2 major bugs first day, 10+ bugs overall (all fixed) • KOALA is now officially released on the DAS(full credit to KOALA developers, 10x for testing with GrenchMark)

  17. GrenchMark’s Current Status: pre-”Open-GrenchMark” • Already done in Python[http://www.python.org] • Workload Generator • Generic Workload Submitter (Koala, Globus GRAM, option to extend for JSDL, Condor, PBS, LSF, SGE, …) • Applications • Unitary, 3 types: sequential, MPI, Ibis (Java) • +35 real and synthetic applications • Composite applications: DAG-based • Extending modeling capabilities A.Iosup, D.H.J.Epema (TU Delft), C. Franke, A. Papaspyrou, L. Schley, B. Song, R. Yahyapour (U Dortmund), On modeling synthetic workloads for Grid performance evaluation, 12th Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP), held in conjunction with SIGMETRICS 2006, Saint Malo, France, June 2006 (accepted).

  18. Towards Open-GrenchMark: Grid traces, Simulators, Benchmarks • Distributed testing • Integrate with DiPerF (C. Dumitrescu, I. Raicu, M. Ripeanu) • Grid traces analysis • Automatic tools for grid traces analysis • Use in conjunction with simulators • Ability to generate workloads which can be used in simulated environments (e.g., GangSim, GridSim, …) • Grid benchmarks • Analyze the requirements for domain-specific grid benchmarks A. Iosup, C. Dumitrescu, D.H.J. Epema (TU Delft), H. Li, L. Wolters (U Leiden), How are Real Grids Used? The Analysis of Four Grid Traces and Its Implications, (submitted).

  19. Conclusion • GrenchMarkgenerates diverse grid workloadseasy-to-use, flexible, portable, extensible, … • Experienceused GrenchMark to test KOALA’s functionality and performance. used GrenchMark to analyze, test, and compare grid settings. 15,000+ jobs generated and run … and counting. • (more) advertisementHave specific grid setting you would like to test? Test with GrenchMark!

  20. Thank you! Many thanks to Hashim Mohamed (Koala), Jason Maassen and Rob van Nieuwpoort (Ibis). Questions? Remarks? Observations? All welcome! GrenchMarkhttp://grenchmark.st.ewi.tudelft.nl/[10x Paulo]Alexandru IOSUP TU DelftA.Iosup@tudelft.nl http://www.pds.ewi.tudelft.nl/~iosup/index.html[google: “iosup”]

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