Towards a Cloud Based Decision Support System for Solar Map Generation

Boulmier, Anthony; White, J.K.; Abdennadher, Nabil

doi:10.1109/cloudcom.2016.0047

Cited by 9 publications

(5 citation statements)

References 8 publications

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“…For example, AWF [15] and FAC [14] were used to balance a load of a heat conduction application on an unstructured grid [20]. Nonadaptive and adaptive DLS techniques such as self-scheduling 1 (SS) [11], GSS [13], FAC [14], AWF [15], and its variants, were used over the years to enhance applications, such as simulations of wave packet dynamics, automatic quadrature routines [16], N-Body simulations [21], solar map generation [22], an image denoising model, the simulation of a vector functional coefficient autoregressive (VFCAR) model for multivariate nonlinear time series [23], and a parallel spin-image algorithm from computer vision (PSIA) [24].…”

Section: Introductionmentioning

confidence: 99%

An approach for realistically simulating the performance of scientific applications on high performance computing systems

Mohammed

Eleliemy

Ciorba

et al. 2020

Future Generation Computer Systems

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Section: Introductionmentioning

confidence: 99%

An approach for realistically simulating the performance of scientific applications on high performance computing systems

Mohammed

Eleliemy

Ciorba

et al. 2020

Future Generation Computer Systems

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“…For example at the process-level, SS, FAC, AWF, and AF were used in heat diffusion application on an unstructured grid [20]. Also, FSC, WF, and AF were used to balance the load of the shadow process in decision support systems for solar energy potential [21]. DLS techniques have also been used to balance the load of automatic quadrature routines [18], N-Body simulations [22], and parallel spin image algorithm (PSIA) [23].…”

Section: Introductionmentioning

confidence: 99%

rDLB: A Novel Approach for Robust Dynamic Load Balancing of Scientific Applications with Parallel Independent Tasks

M¹,

Cavelan²,

Ciorba³

2019

Preprint

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Scientific applications often contain large and computationallyintensive parallel loops. Dynamic loop self-scheduling (DLS) is used to achieve a balanced load execution of such applications on high performance computing (HPC) systems. Large HPC systems are vulnerable to processors or node failures and perturbations in the availability of resources. Most self-scheduling approaches do not consider fault-tolerant scheduling or depended on failure or perturbation detection and react by rescheduling failed tasks. In this work, a robust dynamic load balancing (rDLB ) approach is proposed for the robust self-scheduling of independent tasks. The proposed approach is proactive and does not depend on failure or perturbation detection. The theoretical analysis of the proposed approach shows that it is linearly scalable and its cost decrease quadratically by increasing the system size. rDLB is integrated into an MPI DLS library to evaluate its performance experimentally with two computationally-intensive scientific applications. Results show that rDLB enables the tolerance of up to (P −1) processor failures, where P is the number of processors executing an application. In the presence of perturbations, rDLB boosted the robustness of DLS techniques up to 30 times and decreased application execution time up to 7 times compared to their counterparts without rDLB .

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“…memory and computing power) and the complete integration with web-based GIS portals when required [12].…”

Section: Decision Support System Design and Developmentmentioning

confidence: 99%

“…Also, for the utility companies, there are proposals of DSS for the planning and expansion of the distribution system network based on geographic information system (GIS) [7,8], for power grid operation and planning considering meteorological conditions [9], for analyzing disturbances of electrical power distribution transformers to diagnosing failures [10], and for assisting utilities to comply with the limits of sulfur dioxide (SO 2 ) emissions [11]. Additionally, some DSSs have been proposed for the producers and consumers, including support for the calculation of the solar energy potential of surfaces in urban landscapes [12], for managing energy-efficient buildings [13], and also for assisting consumers to participate in demand response programs [14]. There are still proposals of DSS for assisting regulators in deciding about the installation of DG facilities [15] and about the deregulation of the electricity market [1].…”

Section: Introductionmentioning

confidence: 99%

A Decision Support System for Planning and Operation of Maintenance and Customer Services in Electric Power Distribution Systems

Barriquello¹,

Garcia²,

MagdielSchmitz³

et al. 2017

System Reliability

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This chapter aims to present the design and development of a decision support system (DSS) for the analysis, simulation, planning, and operation of maintenance and customer services in electric power distribution system (EPDS). The main objective of the DSS is to improve the decision-making processes through visualization tools and simulation of real cases in the EPDS, in order to allow better planning in the short, medium, and long term.Therefore, the DSS helps managers and decision-makers to reduce maintenance and operational costs, to improve system reliability, and to analyze new scenarios and conditions for system expansion planning. First, we introduce the key challenges faced by the decisionmakers in the planning and operation of maintenance and customer services in EPDS. Next, we discuss the benefits and the requirements for the DSS design and development, including use cases modeling and the software architecture. Afterwards, we present the capabilities of the DSS and discuss important decisions made during the implementation phases. We conclude the chapter with a discussion about the obtained results, pointing out the possible enhancements of the DSS, future extensions, and new use cases that may be addressed.

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Towards a Cloud Based Decision Support System for Solar Map Generation

Cited by 9 publications

References 8 publications

An approach for realistically simulating the performance of scientific applications on high performance computing systems

An approach for realistically simulating the performance of scientific applications on high performance computing systems

rDLB: A Novel Approach for Robust Dynamic Load Balancing of Scientific Applications with Parallel Independent Tasks

A Decision Support System for Planning and Operation of Maintenance and Customer Services in Electric Power Distribution Systems

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