Present by Chen, Ting-WeiPresent by Chen, Ting-Wei

Adaptive Task Checkpointing Adaptive Task Checkpointing and Replication: Toward and Replication: Toward

Efficient Fault-Tolerant GridsEfficient Fault-Tolerant Grids

Maria Chtepen, Filip H.A. Claeys, Bart Dhoedt, MembMaria Chtepen, Filip H.A. Claeys, Bart Dhoedt, Member, IEEE, Filip De Turck, Member, IEEE, Piet Demeester, IEEE, Filip De Turck, Member, IEEE, Piet Demeester, Senior Member, IEEE, AND Peter A. Vanrolleghemer, Senior Member, IEEE, AND Peter A. Vanrolleghem

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Table of ContentTable of Content

• Introduction• Adaptive Checkpointing Heuristics• Replication-Based Heuristics• Conclusion and Future Work

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IntroductionIntroduction

• A novel fault-tolerant algorithm combine– Checkpointing– Replication

• Be evaluated– Newly developed grid simulation

environment Dynamic Scheduling in Distributed Environments (DSiDE)

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Introduction Introduction (cont.)(cont.)

• Simulation– Run employing workload– System parameters

• From several large-scale parallel production systems’ logs

– Using the discrete event grid simulator DSiDE

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Introduction Introduction (cont.)(cont.)

• Comparable throughput and fault tolerance– Static checkpointing with optimal

parameters– Replication with optimal parameters

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics

• The Checkpointing Model– Limites

• Runtime overhead (C)• Network latency (L)• Recovery delay (R)

– Concentrates on the reduction of the checkpointing runtime overhead

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Adaptive Checkpointing Adaptive Checkpointing HeuristicsHeuristics (cont.)(cont.)

– ProblemAssuming the execution time can be exactly determined in advance

– SimulationThe upper bounds of the algorithms performance, with respect to this parameter

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

• Last Failure Dependent Checkpointing (LastFailureCP)– Goal

• To reduce the overhead

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

• Mean Failure Dependent Checkpointing (MeanFailureCP)– Only considers checkpoint omissions– Modify the checkpointing interval based

on the runtime information• The remaining job execution time• The average failure interval of the resource

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

• DSiDE Simulation Environment– Goal

Validate– Architecture

• DExec• DGen

– Each DSiDE event has a time stamp• Provide a priori or at runtime

– Support several types of dynamic system modifications

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

• The DSiDE simulator architecture

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

– The resource performed useful computations

– Total grid availability

– DSiDE provides a set of events to specify network links and routes

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

• Simulation Result– To compare the performance

• Checkpointing heuristics• Realistic workload• System failure model

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

– Submit’s time• 80% (7 a.m. ~ 9 p.m.)• 20% (9 p.m. ~ 7 a.m.)

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

– Execution time• More than 80% of percent of all submitted

jobs have medium execution times• 1 hour to 6 hours

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

– I decreases and longer jobs can get processed

– Increase in job runtime is in effect– The results

• The results achieved with PeriodicCP are partially improved by LastFailureCP due to omission of redundant checkpoints

• The technique provides the best results for short checkpointing intervals

• The effectiveness of LastFailureCP strongly depends on failure periodically

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Adaptive Checkpointing Adaptive Checkpointing Heuristics Heuristics (cont.)(cont.)

• Failures occur quite periodically– Can easily be predicted by the algorithm– LastFailureCP will perform similar to PeriodicCP

• The fully dynamic scheme of MeanFailureCP proves to be the most effective

• Selective increase in checkpointing keeps the number of processed jobs and the average execution time of MeanFailureCP more or less constant

• PeriodicCP and LastFailureCP algorithms, the performance drops considerably

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Replication-based HeuristicsReplication-based Heuristics

• Load-Dependent Replication (LoadDependentRep)– Providing fault tolerance in distributed

environments through replication• Idle resources can be utilized to run job

copies without significantly delaying the execution of the original job

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)– The algorithm requires a number of par

ameters to be provided in advance• Minimum number of job copies (Repmin)• Maximum number of job copies (Repmax)• The CPU limit (CL)

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)

– The outcome of the comparison determines the choice for the next job to be scheduled

• CA >= CL (Less than Repmax)• 0 < CA < CL (Less than Repmin)• CA = 0 (Skip the current scheduling round)

– When one of the job duplicates finishes, other replicas are automatically canceled

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)

• Failure Detection and Load Dependent Replication (FailureDependentRep)– Increase the fault tolerance of the previousl

y discussed LoadDependentRep heuristic– Offer a higher level of fault tolerance comp

ared to solely replication-based strategies– Not ensure job execution

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)

• Adaptive Checkpoint and Replication-Based Fault Tolerance (CombinedFT)– Dynamically switches between both tech

niques based on runtime information on system load

• Checkpointing mode• Replication mode

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)– Checkpointing mode

• CPU availability is low (CA < CL)• Combined FT rolls back• The earlier distributed active job replicas (A

Rj) • Starts job checkpointing

– ARj > 0

– ARj = 0 & CA > 0– ARj = 0 & CA = 0 & ∃i: ARi > 1– ARj = 0 & CA = 0 & ¬∃i: ARi > 1

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)– Replication mode

• Either the system load decreases• Enough resources restore from failure (CA≧CL)• All jobs with less than Repmax replicas are c

onsidered for submission to the available resources

• Assign to the fastest resource connected to a grid site S with the maximum SpeedS

• The smallest number of identical replicas

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)

• Simulation Results– Approaches

• Unconditional RL(1)• Unconditional RL(2)• Unconditional RL(3)• LoadDependentRL(1, 3, 40)• FailureDependentRL(1, 3, 40)• MeanFailureCP• CombinedFT

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)

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Replication-based Heuristics Replication-based Heuristics (cont.)(cont.)

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Conclusion and Future Work Conclusion and Future Work

• Fault tolerance forms an important problem– Job checkpointing– Replication

• Evaluate in the DSiDE grid simulator• The runtime overhead characteristic to

periodic checkpointing can be reduced

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Conclusion and Future Work Conclusion and Future Work (cont.)(cont.)

• Advantage– When the distributed system properties

are not known in advance, both techniques can best be applied

• Future Work– Scheduling methods will be considered

Present by Chen, Ting-WeiPresent by Chen, Ting-Wei

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