Generic and fault-tolerant bag-of-tasks framework based on JavaSpace technology

Mocanu, Eleonora Maria; Galtier, Virginie; Țăpuș, Nicolae

doi:10.1109/syscon.2012.6189511

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…One way to implement an MTC application is through the JavaSpaces task-based parallelism technology [59]. A JavaSpaces program can support the master-worker architecture wherein a master program runs on one compute node having a unique Internet Protocol (IP) address along with n W workers who run on other, internet-accessible compute nodes and busy themselves by executing tasks that have been posted by the master on a JavaSpace bulletin board.…”

Section: Methodsmentioning

confidence: 99%

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Developing political-ecological theory: The need for Many-Task Computing

Haas

2019

Preprint

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8Models of political-ecological systems can inform policies for managing ecosystems that 9 contain endangered species. One way to increase the credibility of these models is to 10 subject them to a rigorous suite of data-based statistical assessments. Doing so involves 11 statistically estimating the model's parameters, computing confidence intervals for these 12 parameters, determining the model's prediction error rate, and assessing its sensitivity to 13 parameter misspecification. 14 Here, these statistical algorithms along with a method for constructing politically fea-15 sible policies from a statistically fitted model, are coded as JavaSpaces TM programs that 16 run as compute jobs on either supercomputers or a collection of in-house workstations. 17 Several new algorithms for implementing such jobs in distributed computing environments 18 are described. 19 This downloadable code is used to compute each job's output for the management 20 challenge of conserving the East African cheetah (Acinonyx jubatus). This case study shows 21 that the proposed suite of statistical tools can be run on a supercomputer to establish the 22 credibility of a managerially-relevant model of a political-ecological system that contains 23 one or more endangered species. This demonstration means that the new standard of 24 credibility that any political-ecological model needs to meet before being used to inform 25 ecosystem management decisions, is the one given herein. 26 1 27 Keywords: social-ecological systems; ecosystem policymaking; agent-based modeling; 28 high performance computing; sensitivity analysis; statistical estimation of large models 29 1 Introduction 30There is a need to acknowledge the complexity of political-ecological systems and the signif-31 icant challenges to building theories of them [1]. Such systems lie at the interface between 32 social/political science and ecology. The complexity of each of these fields coupled with an 33 additional layer of complexity introduced by the interactions between sociological/political 34 systems and natural systems can result in highly complex system dynamics, i.e., ones that 35 are stiff, nonlinear, and possess feedback loops. For example, Schoon and Van der Leeuw [2] 36 note that systems composed of interacting sociological and ecological subsystems are quick 37 to change and rarely stay in equilibrium for long. Further, many state variables are needed 38 to describe both the decision making processes of the relevant social groups, and the func-39 tioning of the involved ecosystem. A political-ecological system is also referred to as a 40 socio-ecological system or social-ecological system (e.g., see [3]). The former term is em-41 phasized herein because those political actions and processes that drive social movements 42 are often initiated by groups seeking to gain increased political power [4]. Building such 43 models is more than an academic exercise. Indeed, the alarming decline in the planet's 44 biodiversity [5], creates a crucial need for credible politi...

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Section: Methodsmentioning

confidence: 99%

“…Fault-tolerant: Dursi [56] shows that processor failure is almost certain during a job that employs thousands of processors. The authors of [63] and [59] both argue that this feature makes JavaSpaces a very attractive tool for HPC applications.…”

Section: Methodsmentioning

confidence: 99%

Developing political-ecological theory: The need for Many-Task Computing

Haas

2019

Preprint

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“…An approach similar to the one presented in this paper, although with a few significant di↵erences, as discussed in the introduction, is presented in [1], which shows the implementation of a framework for exploiting the bag-of-tasks pattern in the Azure cloud platform. A Java framework for the development of faulttolerant applications is proposed in [20].…”

Section: Related Workmentioning

confidence: 99%

A framework for cloud-aware development of bag-of-tasks scientific applications

Benedictis

Rak

Turtur

et al. 2016

IJGUC

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The potential of cloud computing is still underutilized in the scientific computing field. Even if clouds probably are not fit for high-end HPC applications, they could be profitably used to bring the power of low-cost and scalable parallel computing to the masses. But this requires simple and friendly development environments, able to exploit cloud scalability and to provide fault tolerance. This paper presents a framework built on the top of a cloud-aware platform (mOSAIC) for the development of bag-of-tasks scientific applications.

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“…An implementation of BOT similar to the one presented in this paper, although with a few significant differences, is presented in [4]. A Java framework for the development of fault-tolerant applications is proposed in [38].…”

Section: Related Workmentioning

confidence: 99%

Early Prediction of the Cost of Cloud Usage for HPC Applications

Rak¹,

Turtur²,

Villano³

2015

SCPE

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After a decade of diffusion, cloud computing has received wide acceptance, but it is not yet attractive for the HPC community. Clouds could be a cost-effective alternative to clusters and supercomputers, providing economy of scale, elasticity, flexibility, and easy customization. Unfortunately, most clouds are optimized for running business applications, not for HPC. However, they can be profitably used to run small-scale parallelism codes. This paper presents a framework built on the top of a cloud-aware programming platform (mOSAIC) for the development of bag-of-tasks scientific applications. The framework integrates a cloud-based simulation environment able to predict the behavior of the developed applications. Simulations enable the developer to predict at an early development stage performance and cloud resource usage, and so the infrastructure lease cost on a public cloud. The paper sketches the framework organization and presents the approach followed for the performance simulation of applications, focusing on a software development methodology that hinges on early performance prediction. After showing the results of some validation tests of simulation accuracy, an example of early performance prediction is presented.

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Generic and fault-tolerant bag-of-tasks framework based on JavaSpace technology

Cited by 5 publications

References 7 publications

Developing political-ecological theory: The need for Many-Task Computing

Developing political-ecological theory: The need for Many-Task Computing

A framework for cloud-aware development of bag-of-tasks scientific applications

Early Prediction of the Cost of Cloud Usage for HPC Applications

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