Dynamic Grid Scheduling Using Job Runtime Requirements and Variable Resource Availability

Verboven, Sam; Hellinckx, Peter; Broeckhove, J.; Arickx, F.

doi:10.1007/978-3-540-85451-7_25

Cited by 5 publications

(8 citation statements)

References 8 publications

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“…To determine the impact of these changes the tests conducted in [10] are repeated. Figure 4 shows that using the improved PGS a speedup of up to 13.74% can be achieved when compared to the previous version.…”

Section: B Testing and Resultsmentioning

confidence: 99%

“…For the purpose of this implementation we will narrow the field of BoT applications down to parameter sweeps. The techniques used in PGS and the implementation details can be found in [10]. The most recent version of the PGS scheduler includes some small changes, intended to enhance performance, that can be viewed separate from the changes made to accommodate the prediction errors introduced by using the GIPSy framework.…”

Section: Pgs Improvementsmentioning

confidence: 99%

“…After introducing GIPSy we will combine it with an improved version of PGS [10], a scheduling technique and implementation based on two constraints: the availability of job runtime estimates and resource availability estimates. Using these constraints the technique pro-actively prevents failures from occurring by distributing jobs only to resources available for the full execution time of the job.…”

Section: Introductionmentioning

confidence: 99%

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Runtime Prediction Based Grid Scheduling of Parameter Sweep Jobs

Verboven

Hellinckx

Arickx

et al. 2008

2008 IEEE Asia-Pacific Services Computing Conference

Self Cite

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This paper examines the problem of predicting job runtimes by exploiting the properties of parameter sweeps. A new parameter sweep prediction framework GIPSy (Grid Information Prediction System) is introduced. Predictions are made based on prior runtime information and the parameters used to configure each job. The main objective is providing a tool combining development, simulation and application of prediction models within one framework. The different kinds of available sample selectors and models are discussed in detail. Results are presented for a quantum physics problem. A previously introduced scheduling technique and the implementation called PGS (Prediction based Grid Scheduling) is improved and presented in combination with GIPSy to obtain a real-world grid implementation that optimizes the distribution of parameter sweeps.

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Section: B Testing and Resultsmentioning

confidence: 99%

Section: Pgs Improvementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Runtime Prediction Based Grid Scheduling of Parameter Sweep Jobs

Verboven

Hellinckx

Arickx

et al. 2008

2008 IEEE Asia-Pacific Services Computing Conference

Self Cite

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“…These characteristics were explained in Section II to have significant impacts on scheduling performance. In our model, we particularly emphasised the behaviour of BoTs since they have recently received much attention of scheduling researchers [1], [3], [6], [27]. We analysed properties of BoTs in Section IV and showed that up to 70% jobs of parallel systems are submitted as part of BoTs.…”

Section: Discussionmentioning

confidence: 99%

“…They have been recognized as a very important characteristic, and several scheduling algorithms have been designed for BoT applications [3], [6], [27]. However, these studies only use randomly generated or unrealistic workloads in their experiments.…”

Section: Bags-of-tasksmentioning

confidence: 99%

A Realistic Integrated Model of Parallel System Workloads

Minh

Wolters

Epema

2010

2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing

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Abstract-Performance evaluation is a significant step in the study of scheduling algorithms in large-scale parallel systems ranging from supercomputers to clusters and grids. One of the key factors that have a strong effect on the evaluation results is the workloads (or traces) used in experiments. In practice, several researchers use unrealistic synthetic workloads in their scheduling evaluations because they lack models that can help generate realistic synthetic workloads. In this paper we propose a full model to capture the following characteristics of real parallel system workloads: 1) long range dependence in the job arrival process, 2) temporal and spatial burstiness, 3) bag-oftasks behaviour, and 4) correlation between the runtime and the number of processors. Validation of our model with real traces shows that our model not only captures the above characteristics but also fits the marginal distributions well. In addition, we also present an approach to quantify burstiness in a job arrival process (temporal) as well as burstiness in the load of a trace (spatial).

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