Modelling the Behaviour of an Adaptive Scheduling Controller

Barone, Giovanni; Boccia, Vania; Bottalico, D.; Carracciuolo, Luisa; Doria, A.; Laccetti, Giuliano

doi:10.1109/cisis.2012.26

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…The Adaptive Scheduling Controller (ASC) proposes a control system that uses an adaptive approach in job scheduling policy, which aims to allow a “balanced, effective, and efficient use of the computational resources.” ASC is built on top of existent batch‐queuing system such as OGE and PBS and defines a heuristic approach to find the most suitable probability distribution function to model the time jobs spend in the queue before execution. The heuristic is based on the job duration and degree of parallelism.…”

Section: Related Workmentioning

confidence: 99%

On the use of HCM to develop a resource allocation algorithm for heterogeneous clusters

Soares

Santos

Lobosco

2018

Concurrency and Computation

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Summary This work presents a resource allocation algorithm that considers the characteristics of regular applications to choose the subset of processors, accelerators, and networks that minimize their parallel execution time in a small heterogeneous cluster environment. The resource allocation algorithm uses Heterogeneous Cluster Model (HCM) to estimate the execution time of the parallel applications. The experimental results have shown that, for applications with distinct behaviors, the resource allocation algorithm has successfully chosen the set of resources that minimizes their execution time.

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Section: Related Workmentioning

confidence: 99%

On the use of HCM to develop a resource allocation algorithm for heterogeneous clusters

Soares

Santos

Lobosco

2018

Concurrency and Computation

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“…In this scenario, where on the same resources run both the traditional jobs and some parallel applications, HPC communities are usually penalized by general-purpose scheduler configurations. For this reason, system administrators experimented a combination of some mechanisms provided by the Local Resources Manager/Scheduling System with the aims to gain a balanced, efficient and effective use of the computing resources by heterogeneous communities without neglecting the users satisfaction [14].…”

Section: B Scheduling Policies For Hpc Systems In a Distributed Envimentioning

confidence: 99%

The HPC Testbed of the Italian Grid Infrastructure

Alfieri

Arezzini

Barone

et al. 2013

2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing

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Even though the Italian Grid Infrastructure (IGI) is a general purpose distributed platform, in the past it has been used mainly for serial computations. Parallel applications have been typically executed on supercomputer facilities or, in case of "not high-end" HPC applications, on local commodity parallel clusters. Nowadays, with the availability of multiple cores processors, Grid computing is becoming very attractive also for parallel applications but some problems exist in supporting of HPC applications on Grid environment. Here we describe the work made to set up a HPC testbed for "not high-end" HPC applications, based on IGI Grid technologies, to find solutions to those problems. Participating sites have been selected among the ones running HPC clusters in Grid environment. Each of them contributed with their specific HPC experience and their available resources to the present test, which encompasses an unprecedented large set of applications from different disciplines in the fields of astronomy, astrophysics, chemistry, climatology, material science and oceanography. In addition to computing resources sharing, the main contribution of each participant was the identification of the real requirements of his application also related to the current middleware limitations and then the realization of a test platform enhanced with additional HPC solutions and configurations developed in a tight collaboration between HPC administrators, users and IGI managers. The main work was on computational resources selection, data management and the definition, the deployment and the documentation of the software execution environment. The outcoming results of the testbed represent the basis of the HPC support in the IGI production infrastructure.

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One Size Does Not Fit All: Clustering Supercomputer Failures Using a Multiple Time Window Approach

Martino

2013

Lecture Notes in Computer Science

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Modelling the Behaviour of an Adaptive Scheduling Controller

Cited by 5 publications

References 11 publications

On the use of HCM to develop a resource allocation algorithm for heterogeneous clusters

On the use of HCM to develop a resource allocation algorithm for heterogeneous clusters

The HPC Testbed of the Italian Grid Infrastructure

One Size Does Not Fit All: Clustering Supercomputer Failures Using a Multiple Time Window Approach

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