GANESH: Grid Application Management and Enhanced Scheduling

Bhatt, Haresh S.; Patel, Rashmit; Kotecha, H.J.; Patel, Vishvas; Dasgupta, Anshuman

doi:10.1177/1094342007083777

Cited by 3 publications

(1 citation statement)

References 11 publications

(15 reference statements)

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“…Based on security, authentication, monitoring and discovery and data transfer (GridFTP) of Globus Toolkit 2.4.3 and SAC developed scheduler GANESH [53], a prototype satellite based grid was established. It was desired to submit compute intensive jobs from this grid to GARUDA's unprecedented resource.…”

Section: Satgrid-garuda Interfacementioning

confidence: 99%

GARUDA: Pan-Indian distributed e-infrastructure for compute-data intensive collaborative science

Mangala

Rao

Chattopadhyay

et al. 2013

CSIT

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GARUDA is a nation-wide grid of computational nodes, mass storage and scientific instruments with an aim to provide technological advancements required to enable compute-data intensive, collaborative applications for the twenty-first century. From a Proof-of-Concept, the GARUDA has evolved to an operational grid, aggregating nearly 70TF-15TB compute-storage power, via high-speed National Knowledge Network and hosts a stack of middleware and tools to enable hundreds of users from diverse communities like life science, earth science, computer aided engineering, material science, etc. Evolution and confluence of research and technologies has led to the maturity of GARUDA grid: there have been addition of several hundred CPUs, large data stores, standardization of grid middleware, research on interoperability between grids and participation from varied application communities that have made significant impact to GARUDA. The GARUDA partner institutes are using this e-infrastructure to grid enable applications of societal and national importance. The authors in this paper present the manner of building a nation-wide operational grid and its evolution, its deliverables, architecture and applications.

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Section: Satgrid-garuda Interfacementioning

confidence: 99%

GARUDA: Pan-Indian distributed e-infrastructure for compute-data intensive collaborative science

Mangala

Rao

Chattopadhyay

et al. 2013

CSIT

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End-To-End Cache System for Grid Computing: Design and Efficiency Analysis of a High-Throughput Bioinformatic Docking Application

Garzón

Huedo

Montero

et al. 2009

The International Journal of High Performance Computing Applica

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Cache techniques are an efficient tool to reduce latency times in transfer operations through Grid systems. Although different approximations to introduce cache facilities into Grid computing have already been studied, they require intrusive modifications of Grid software and hardware. Here, we propose an end-to-end cache system that is implemented over scheduling services. This cache system requires neither changes in the Grid software nor introduction of new software in the Grid resources. Parallel Grid adaptation of many high-throughput computing applications that use the same data intensively could enjoy great benefits from our cache system. The maintenance of cacheable data in the resources of already-executed tasks allows faster executions of future tasks assigned to the same resources. To analyze the performance of our end-to-end cache system, we tested it with a new protein—protein docking application. The obtained results confirm our cache system’s robustness and efficiency gain for this kind of high-throughput application.

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A Study on the Priority Processing of Data Using the SLA on the Network of GARA(Globus Architecture for Reservation and Allocation)

Kim²

2014

Journal of Digital Contents Society

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As a way to overcome the problems that when you transmit data to and receive data from End Device to participate in the GRID network, QoS has not been, GARA supports the Diffserv system basically. However, the problem when it is assumed settings related to the Diffserv between the ISP and the ISP is wrong with each other, that it is not possible to receive a complete QoS services began to appear. In this paper, we tried to overcome these drawbacks, in networks based GARA the (Globus Architecture for Reservation and Allocation), using the SLA (Service Level Agrement) server, was treated in the highest priority to the data, the ISP there is provided a method for setting the Diffserv the ISP is even wrong and, using the TOS of the IP header, to solve this, it is described about the direction of future research.

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GANESH: Grid Application Management and Enhanced Scheduling

Cited by 3 publications

References 11 publications

GARUDA: Pan-Indian distributed e-infrastructure for compute-data intensive collaborative science

GARUDA: Pan-Indian distributed e-infrastructure for compute-data intensive collaborative science

End-To-End Cache System for Grid Computing: Design and Efficiency Analysis of a High-Throughput Bioinformatic Docking Application

A Study on the Priority Processing of Data Using the SLA on the Network of GARA(Globus Architecture for Reservation and Allocation)

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