The Design and Implementation of the KOALA Co-allocating Grid Scheduler

Mohamed, Hashim; Epema, Dick

doi:10.1007/11508380_65

Cited by 32 publications

(27 citation statements)

References 9 publications

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“…As distinctive features, KOALA includes support for data and processor coallocation [25] and malleability management [12] for parallel applications.…”

Section: Architecturementioning

confidence: 99%

Scheduling Strategies for Cycle Scavenging in Multicluster Grid Systems

Sonmez

Grundeken

Mohamed

et al. 2009

2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid

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“…As distinctive features, KOALA includes support for data and processor coallocation [25] and malleability management [12] for parallel applications.…”

Section: Architecturementioning

confidence: 99%

Scheduling Strategies for Cycle Scavenging in Multicluster Grid Systems

Sonmez

Grundeken

Mohamed

et al. 2009

2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid

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“…[10]. Regarding similar tools to GRUBER for job steering and scheduling over a Grid, the most similar tools in intent, to the authors' knowledge, are the Pegasus framework [18] and KOALA Grid scheduler [19].…”

Section: Related Workmentioning

confidence: 99%

Usage SLA‐based scheduling in Grids

Dumitrescu

Raicu

Foster

2006

Concurrency and Computation

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SUMMARYManaging usage service level agreements (uSLAs) within environments that integrate participants and resources spanning multiple physical institutions is a challenging problem. Running workloads in such environments is often a similarly challenging problem owing to the scale of the environment, and to the resource partitioning based on various sharing strategies. Also, a resource may be taken down during a job execution, be improperly set up or fail job execution. Such elements have to be taken into account whenever targeting a Grid environment for problem solving. In this paper we explore uSLA-based scheduling on a real Grid, Grid3, by means of a specific workload (the BLAST workload) and a specific scheduling framework, GRUBER (an architecture and toolkit for resource uSLA specification and enforcement). The paper provides extensive experimental results and comparisons with other scheduling strategies. We also address, in great detail, the performance of different uSLA-based site selection strategies and the overall performance in scheduling workloads over Grid3 with workload sizes ranging from 10 to 10 000 jobs.

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“…KOALA [15] was developed by the PDS group in Delft [16] in the context of the Virtual Lab for e-Science (VLe [12]) project. Its main feature is the support for coallocation, i.e., simultaneous allocation of processors and memory on multiple Grid sites to a single application consisting of several work units.…”

Section: The Koala Co-allocation Schedulermentioning

confidence: 99%

“…We use the KOALA scheduler [15] for handling the simultaneous reservation (co-allocation) of the required resources based on the three-layer infrastructure proposed in [5]. Using the BWCF (Bandwidth-Aware Close-to-File) scheduling algorithm introduced in [5], a HOC-based application can be scheduled transparently to the user.…”

Section: Introductionmentioning

confidence: 99%