Scheduling strategies for master-slave tasking on heterogeneous processor platforms

Banino, Cyril; Beaumont, Olivier; Carter, L.; Ferrante, Jeanne; Legrand, Arnaud; Robert, Yves

doi:10.1109/tpds.2004.1271181

Cited by 145 publications

(94 citation statements)

References 10 publications

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“…Banino et al (2004) have developed a polynomial solution for the steady-state case, where all processing capabilities, applications requirements, and communication links are known in advance. The Uniform MultiRound algorithm assumes that every node receives decreasing, fixed task sizes in every round and provides an approximation to the optimal number of rounds by minimising the application makespan in a simulated environment ).…”

Section: Related Workmentioning

confidence: 99%

Adaptive statistical scheduling of divisible workloads in heterogeneous systems

González–Vélez

Cole

2009

J Sched

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This article presents a statistical approach to the scheduling of divisible workloads. Structured as a task farm with different scheduling modes including adaptive single and multi-round scheduling, this novel divisible load theory approach comprises two phases, calibration and execution, which dynamically adapt the installment size and number. It introduces the concept of a generic installment factor based on the statistical dispersion of the calibration times of the participating nodes, which allows automatic determination of the number and size of the workload installments. Initially, the calibration ranks processors according to their fitness and determines an installment factor based on how different their execution times are. Subsequently, the execution iteratively distributes the workload according to the processor fitness, which is continuously re-assessed throughout the program execution. Programmed as an adaptive algorithmic skeleton, our task farm has been successfully evaluated for single-round scheduling and generic multi-round scheduling using a computational biology parameter-sweep in a nondedicated multi-cluster system.

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Section: Related Workmentioning

confidence: 99%

Adaptive statistical scheduling of divisible workloads in heterogeneous systems

González–Vélez

Cole

2009

J Sched

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“…Previous work [3,14] illustrates the benefits of using integer programming techniques to solve scheduling problems. However, our model tries to fit computation and communication parallel job requirements to resource capacity, and considers the sharing of the resources between parallel and local applications.…”

Section: Introductionmentioning

confidence: 99%

Resource Matching in Non-dedicated Multicluster Environments

Lérida

Solsona

Giné

et al. 2008

High Performance Computing for Computational Science - VECPAR 2008

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Abstract. We are interested in making use of Multiclusters to execute parallel applications. The present work is developed within the M-CISNE project. M-CISNE is a non-dedicated and heterogeneous Multicluster environment which includes MetaLoRaS, a two-level MetaScheduler that manages the appropriate job allocation to available resources. In this paper, we present a new resource-matching model for MetaLoRaS, which is aimed at mitigating the degraded turnaround time of co-allocated jobs, caused by the contention on shared inter-cluster links. The model is linear programming based and considers the availability of computational resources and the contention of shared inter and intra-cluster links. Its goal is to minimize the average turnaround time of the parallel applications without disturbing the local applications excessively and maximize the prediction accuracy. We also present a parallel job model that takes both computation and communication characterizations into account. By doing this, greater accuracy is obtained than in other models only focused on one of these characteristics. Our preliminary performance results indicate that the linear programming model for on-line resource matching is efficient in speed and accuracy and can be successfully applied to co-allocate jobs across different clusters.

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“…Neste trabalho, em particular, estamos analisando e comparando variações do modelo mestre-escravo (BANINO et al, 2004;LEGRAND;ROBERT, 2003) em relaçãoà divisão e distribuição das cargas computacionais. Normalmente, a distribuição do trabalho entre os escravosé feita de maneira estática, como no caso da estratégia VRP (Seção 4.10.2).…”

Section: Modelos Para Aplicações Paralelasunclassified

Uma metodologia para desenvolvimento de programas paralelos eficientes em ambientes homogêneos e heterogêneos.

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Scheduling strategies for master-slave tasking on heterogeneous processor platforms

Cited by 145 publications

References 10 publications

Adaptive statistical scheduling of divisible workloads in heterogeneous systems

Adaptive statistical scheduling of divisible workloads in heterogeneous systems

Resource Matching in Non-dedicated Multicluster Environments

Uma metodologia para desenvolvimento de programas paralelos eficientes em ambientes homogêneos e heterogêneos.

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