High performance parametric modeling with Nimrod/G: killer application for the global grid?

By David Abramson, Jonathan Giddy, Lew Kotler. Proceedings, International Parallel and Distributed Processing Symposium (IPDPS), 2000

584 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/3b5507aa37e80742f604bbf50d9b12bd471dff52

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Citations in the corpus

A Computational Economy for Grid Computing and its Implementation in the Nimrod-G Resource Brok (2001, background): “They enable the coordinated use of geographically distributed resources, often owned by autonomous organizations, for creating virtual enterprises for solving large-scale problems in science, engineering, and commerce [1][7].”
A taxonomy of Data Grids for distributed data sharing, management, and processing (2005, background): “Such applications arise in parameter studies [Abramson et al. 2000] wherein a set of tasks is created by running the same program on different inputs.”
The AppLeS Parameter Sweep Template: User-Level Middleware for the Grid (2000, methodology): “However, we expect that the APST client in its current form can serve as a building block for more sophisticated user interfaces (e.g. within a PSE such as SCIRun [35] or Nimrod [16], or from a Web/CGI interface).”
Analyzing Market-Based Resource Allocation Strategies for the Computational Grid (2001, background): “While a great dealof researchconcerningthe softwaremechanismsthat will be necessaryto bring Computational Grids to fruition is underway [3, 16, 20, 8, 4, 24, 21, 1, 34], little work hasfocusedon the resourcecontrol policies that are likely to succeed.”
A Taxonomy of Workflow Management Systems for Grid Computing (2005, methodology): “ovides a simple XML-based workflow language for users to define their tasks and dependencies. The workflow description language of Gridbus is aimed towards enabling the expression of parameterization [8] and users’ QoS requirement. The workflow engine of Gridbus provides a hierarchical scheduling ar”
Pegasus, a workflow management system for science automation (2015, methodology): “The Nimrod toolkit [89, 90] is a specialized parametric modeling system that provides a declarative parametric modeling language to express parametric experiments, and automates the formulation, execution, monitoring, and verification of the results from multiple individual experiments using many-ta”
Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid (2000, background): “The architecture of Nimrod/G is shown in Figure 1 and its key components are: • Client or User Station • Parametric Engine • Scheduler • Dispatcher • Job-Wrapper The interaction between the above components and grid resources is shown in Figure 2.”
GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing (2002, background): “The user essentially interacts with a resource broker that hides the complexities of grid computing [7][8].”
A taxonomy and survey of grid resource management systems for distributed computing (2002, methodology): “A high throughput Grid increases the completion rate of a stream of jobs and are well suited for ‘parameter sweep’ type applications such as Monte Carlo simulations [10,11].”
Grids and Grid technologies for wide‐area distributed computing (2002, methodology): “Grid resources can be used to solve grand challenge problems in areas such as biophysics, chemistry, biology, scientific instrumentation [27], drug design [11,47], tomography [48], highenergy physics [49], data mining, financial analysis, nuclear simulations, material science, chemical engineering, ”
Economic-based Distributed Resource Management and Scheduling for Grid Computing (2002, background): “, ionization chamber calibration [19], drug design [108], operations research, electronic CAD, and ecological modeling), where large processing problems can easily be divided into sub-problems and solved independently, are taking great advantage of Grid computing.”
Economic models for resource management and scheduling in Grid computing (2002, methodology): “Computational Grids and Peer-to-Peer (P2P) computing systems are emerging as a new paradigm for solving large-scale problems in science, engineering, and commerce [1][5].”
Adaptive Computing on the Grid Using AppLeS (2003, methodology): “APST is related to other Grid projects such as ILAB [50], Nimrod/G [51], and Condor [57], which also provide mechanisms for running PSAs and, more generally, to projects in industry [63], [64], [65] that aim at deploying a large number of jobs on widely distributed resources.”
A case for economy grid architecture for service oriented grid computing (2001, methodology): “In our previous experiments (performed on GUSTO test bed in 1999 [1]), the resource prices were hardwired into a file owned by the user.”
The Grid Economy (2005, background): “A plan file modeling this application as a parameter sweep application using the Nimrod-G parameter specification language is shown in Fig.”