Coscheduling based on runtime identification of activity working sets

Feitelson, Dror G.; Rudolph, Larry

doi:10.1007/bf02577787

Cited by 36 publications

(24 citation statements)

References 23 publications

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“…Also, the lack o f m ultiprogramming can hurt when a process performs a lot of I O. The second approach i s a h ybrid scheme, called exact coscheduling or gang scheduling 12,5,4,6 , that combines time sharing with space sharing. The processes of a job are scheduled on their respective nodes at the same time for a given time quantum, the expiration of which results in a synchronization between the nodes using logical or physical clocks to decide on the next job to run.…”

Section: Introductionmentioning

confidence: 99%

A simulation-based study of scheduling mechanisms for a dynamic cluster environment

Zhang

Sivasubramaniam

Moreira

et al. 2000

Proceedings of the 14th International Conference on Supercomputing

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Scheduling of processes onto processors of a parallel machine has always been an important and challenging area of research. The issue becomes even more crucial and di cult as we gradually progress to the use of o -the-shelf workstations, operating systems, and high bandwidth networks to build cost-e ective clusters for demanding applications. Clusters are gaining acceptance not just in scienti c applications that need supercomputing power, but also in domains such as databases, web service and multimedia, which place diverse Quality-of-Service QoS demands on the underlying system. Further, these applications have diverse characteristics in terms of their computation, communication and I O requirements, making conventional parallel scheduling solutions, such as space sharing or coscheduling, an unattractive option. At the same time, leaving it to the native operating system of each node to make decisions independently can lead to ine ective use of system resources whenever there is communication. Instead, an emerging class of dynamic coscheduling mechanisms, that attempt to take remedial actions to guide the system towards coscheduled execution without requiring explicit synchronization, o er a lot of promise for cluster scheduling. Using a detailed simulator, this paper evaluates the pros and cons of di erent dynamic coscheduling alternatives, while comparing their advantages over traditional coscheduling and not performing any coordinated scheduling at all. The impact of dynamic job arrivals, job characteristics and di erent system parameters on these alternatives are evaluated in terms of several performance criteria.

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Section: Introductionmentioning

confidence: 99%

A simulation-based study of scheduling mechanisms for a dynamic cluster environment

Zhang

Sivasubramaniam

Moreira

et al. 2000

Proceedings of the 14th International Conference on Supercomputing

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“…For clarity, the examples will use short sequences T and small values of m. It should be clear, however, that the concepts presented (1), (2), (3), (4), (5), (6), (7), (8) [1], [2], [3], [4], [5], [6], [7], [8] 0.35 [3,4], [5,6], [7,8] 0.25 Arbitrary (1), (2,3,4), (5), (6), (7,8) [1], [2,3,4], [5], [6], [7,8] (2), (3), (2), (3), (1), (4) [1], [3], [2], [3], [2], [3], [1], [4] apply as well to arbitrarily large sequences and values of m. Table 1 shows the locality of simple path sequences with different partitionings.…”

Section: The Locality Measurementioning

confidence: 99%

Modeling Communication Locality in Multiprocessors

Salisbury¹,

Chen²,

Melhem³

1999

Journal of Parallel and Distributed Computing

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“…• Exact Co-Scheduling Schemes In order to address the inefficiencies of space sharing, exact co-scheduling, or gang scheduling [17,7,6,22,8], allows time-sharing on each node. It manages the scheduling via a two-dimensional scheduling matrix (called the Ousterhout matrix), with columns denoting number of nodes in the system, and rows denoting the time slices.…”

Section: Summary Of Cluster Scheduling Strategiesmentioning

confidence: 99%

ClusterSchedSim: A Unifying Simulation Framework for Cluster Scheduling Strategies

Zhang

Sivasubramaniam

2004

SIMULATION

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As clusters are being deployed to support a wide range of parallel workloads, scheduling becomes a challenging research issue because these workloads exhibit diverse characteristics and impose varying quality-of-service requirements. Many scheduling strategies are thus proposed, each intended for a different application/system setting. Due to the lack of a uniform simulation platform, a significant amount of research effort is spent in building a unique simulator for each algorithm, which may lead to false conclusions. This article presents ClusterSchedSim, which is a unifying simulation frame-work of cluster scheduling strategies. The core of ClusterSchedSim includes the node model and an interconnect model. ClusterSchedSim has implemented variations of popular cluster scheduling schemes, and it is flexible enough to add on new schemes. Using ClusterSchedSim, one can conveniently compare different scheduling schemes, profile their executions, and understand the impact of different application and system configuration parameters.

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Coscheduling based on runtime identification of activity working sets

Cited by 36 publications

References 23 publications

A simulation-based study of scheduling mechanisms for a dynamic cluster environment

A simulation-based study of scheduling mechanisms for a dynamic cluster environment

Modeling Communication Locality in Multiprocessors

ClusterSchedSim: A Unifying Simulation Framework for Cluster Scheduling Strategies

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