TeraGrid: A Foundation for US Cyberinfrastructure

Catlett, Charles E.

doi:10.1007/11577188_1

Cited by 27 publications

(20 citation statements)

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“…In general most of the solutions are Globus-based (however there are also other middleware stacks like UNICORE [7]). In the US the major Grid initiatives are OSG [8] and TeraGrid [9] (now XSEDE). Open Science Grid (OSG), facilitates distributed computing for scientific research.…”

Section: Description Of the Context A Grid Middlewarementioning

confidence: 99%

Workflows orchestration in distributed computing infrastructures

Płóciennik

Żok

Gómez-Iglesias

et al. 2012

2012 International Conference on High Performance Computing &Amp; Simulation (HPCS)

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This paper presents an overview of the new developments carried out to offer a reliable and efficient support for different computing infrastructures in the Kepler workflow orchestration system. The aim of the work is to help scientists to transparently use these infrastructures regardless of the underlying middleware. We introduce new complex workflow scenarios developed in the context of the EU EGI Inspire project and their exploitation by two nuclear fusion applications. The presented use cases represent typical scenarios which are common also in other fields and could be easily reused for other applications.

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Section: Description Of the Context A Grid Middlewarementioning

confidence: 99%

Workflows orchestration in distributed computing infrastructures

Płóciennik

Żok

Gómez-Iglesias

et al. 2012

2012 International Conference on High Performance Computing &Amp; Simulation (HPCS)

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“…It was created simultaneously with the Department of Computer Science and Engineering of the Universidad Nacional del Sur in 1994. The main general objectives of LISiDi are: (1) identify application areas for the grid computing paradigm, (2) develop applications according to the areas identified in the previous item, (3) generate projects (possibly in conjunction with other groups) with research content in various of these application areas (4) train new researchers in this field 3 .…”

Section: The Lisidi Perspectivementioning

confidence: 99%

“…The first class consists of general purpose grids that provide computing and data resources to a broad class of application communities: EGEE [12], TeraGrid [3], Open Science Grid [25] and Naregi [13]. The second category of grids are those devoted to a specific scientific or technical application field, such as geosciences, chemical informatics, earthquake science, astronomy and atmospheric science.…”

Section: Introductionmentioning

confidence: 99%

Latin American Perspectives on Grid Computing, from Bahia Blanca, Argentina

Echaiz

Ardenghi

2007

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)

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A computational grid is a distributed infrastructure that appears to the end user as one large computing resource across organization boundaries. Grid technologies enable large-scale sharing of resources within formal or informal consortia of individuals and/or institutions, usually called virtual organizations. In these settings, the discovery, characterization, and monitoring of resources, services, and computations can be challenging due to the considerable diversity, large numbers, dynamic behavior, and geographical distribution of the entities in which a user might be interested. This work explores the grid computing current state and perspectives in Latin America. In particular, we describe potential grid application areas and the experiences of our group in this promising field of research. Also, considering that grid trends are showing the importance of grid services we also identify some limitations and future research directions on this domain.

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“…Today these infrastructures are based on large-scale distributed systems such as TeraGRID [1] used by 4000 users around 200 universities, and Open Science Grid [2] hosting up to 25000 machines used for research work in molecular bioscience, mathematics, neuroscience, physics etc. Implementing new paradigms such as Cloud computing on large IT infrastructures obviously requires analysis of the current state and of the benefits that a new approach would bring.…”

Section: Introductionmentioning

confidence: 99%

TimeCap: Methodology for Comparing IT Infrastructures Based on Time and Capacity Metrics

Mastelić

Brandić

2013

2013 IEEE Sixth International Conference on Cloud Computing

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Abstract-Scientific community is one of the major driving forces for developing and utilizing IT technologies such as Supercomputers and Grid. Although, the main race has always been for bigger and faster infrastructures, an easier access to such infrastructures in recent years created a demand for more customizable and scalable environments. However, introducing new technologies and paradigms such as Cloud computing requires a comprehensive analysis of its benefits before the actual implementation.In this paper we introduce the TimeCap, a methodology for comparing IT infrastructures based on time requirements and resource capacity wastage. We go beyond comparing just the execution time by introducing the Time Complexity as part of TimeCap, a methodology used for comparing arbitrary time related tasks required for completing a procedure, i.e., obtaining the scientific results. Moreover, a resource capacity wastage is compared using the Discrete Capacity, a second methodology as part of TimeCap used for analyzing resource assignment and utilization. We evaluate our methodology by comparing a traditional physical infrastructure and a Cloud infrastructure using our local IT resources. We use a real world scientific application for calculating plasma instabilities for analyzing time and capacity required for computation.

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TeraGrid: A Foundation for US Cyberinfrastructure

Cited by 27 publications

References 0 publications

Workflows orchestration in distributed computing infrastructures

Workflows orchestration in distributed computing infrastructures

Latin American Perspectives on Grid Computing, from Bahia Blanca, Argentina

TimeCap: Methodology for Comparing IT Infrastructures Based on Time and Capacity Metrics

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