Combining Measurement and Stochastic Modelling to Enhance Scheduling Decisions for a Parallel Mean Value Analysis Algorithm

Yaikhom, Gagarine; Cole, Murray; Gilmore, Stephen

doi:10.1007/11758525_123

Cited by 12 publications

(6 citation statements)

References 15 publications

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“…Recent work on adaptive systems [15,16] has reinforced the importance of platform adaptation for optimisation of parallel codes in heterogeneous distributed systems. While implementation of parallel pipelines can be found in several established skeletal libraries [17,18], adaptive skeletal constructs have recently started to use resource-aware mechanisms based on process algebra [19] and statistical methodologies [20], paving the way to the development of a comprehensive library of self-adaptive algorithmic skeletons for non-dedicated heterogeneous systems.…”

Section: Related Workmentioning

confidence: 99%

Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

González–Vélez

Cole

2006

Parallel and Distributed Processing and Applications

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This work describes an adaptive parallel pipeline skeleton which maps pipeline stages to the best processors available in the system and clears dynamically emerging performance bottlenecks at run-time by re-mapping affected stages to other processors. It is implemented in C and MPI and evaluated on a non-dedicated heterogeneous Linux cluster. We report upon the skeleton's ability to respond to an artificially generated variation in the background load across the cluster.

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Section: Related Workmentioning

confidence: 99%

Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

González–Vélez

Cole

2006

Parallel and Distributed Processing and Applications

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“…The saving in time is considerable empirically though it is harder to quantify because of the iterative nature of the approximate algorithms. Parallel MVA algorithms have been proposed in [8,24].…”

Section: Handing Multiple Classes Of Usersmentioning

confidence: 99%

Translating Service Level Objectives to lower level policies for multi-tier services

Chen

Iyer

et al. 2008

Cluster Comput

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Service providers and their customers agree on certain quality of service guarantees through Service Level Agreements (SLA). An SLA contains one or more Service Level Objectives (SLO)s that describe the agreed-upon quality requirements at the service level. Translating these SLOs into lower-level policies that can then be used for design and monitoring purposes is a difficult problem. Usually domain experts are involved in this translation that often necessitates application of domain knowledge to this problem. In this article, we propose an approach that combines performance modeling with regression analysis to solve this problem. We demonstrate that our approach is practical and that it can be applied to different n-tier services. Our experiments show that for a typical 3-tier e-commerce application in a virtualized environment, the SLA can be met while improving CPU utilization by up to 3 times.

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“…eSkel has employed reactive process algebra methods to predict the performance and incorporate the reactive scheduling into a pipeline skeleton [43].…”

Section: Applesmentioning

confidence: 99%

Adaptive structured parallelism for distributed heterogeneous architectures: a methodological approach with pipelines and farms

González–Vélez

Cole

2010

Concurrency and Computation

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SUMMARYAlgorithmic skeletons abstract commonly used patterns of parallel computation, communication, and interaction. Based on the algorithmic skeleton concept, structured parallelism provides a high-level parallel programming technique that allows the conceptual description of parallel programs while fostering platform independence and algorithm abstraction. This work presents a methodology to improve skeletal parallel programming in heterogeneous distributed systems by introducing adaptivity through resource awareness. As we hypothesise that a skeletal program should be able to adapt to the dynamic resource conditions over time using its structural forecasting information, we have developed adaptive structured parallelism (ASPARA). ASPARA is a generic methodology to incorporate structural information at compilation into a parallel program, which will help it to adapt at execution. ASPARA comprises four phases: programming, compilation, calibration, and execution. We illustrate the feasibility of this approach and its associated performance improvements using independent case studies based on two algorithmic skeletons-the task farm and the pipeline-evaluated in a non-dedicated heterogeneous multi-cluster system.

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Combining Measurement and Stochastic Modelling to Enhance Scheduling Decisions for a Parallel Mean Value Analysis Algorithm

Abstract: Abstract. In this paper we apply the high-level modelling language PEPA to the performance analysis of a parallel program with a pipeline skeleton which computes the Mean Value Analysis (MVA) algorithm for queueing networks.

Cited by 12 publications

References 15 publications

Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

Translating Service Level Objectives to lower level policies for multi-tier services

Adaptive structured parallelism for distributed heterogeneous architectures: a methodological approach with pipelines and farms

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